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<article article-type="research-article" dtd-version="1.1" specific-use="sps-1.9" xml:lang="en" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
	<front>
		<journal-meta>
			<journal-id journal-id-type="nlm-ta">abchf</journal-id>
			<journal-id journal-id-type="publisher-id">abchf</journal-id>
			<journal-title-group>
				<journal-title>ABC Heart Fail Cardiomyop</journal-title>
				<abbrev-journal-title abbrev-type="publisher">ABC Heart Fail Cardiomyop</abbrev-journal-title>
			</journal-title-group>
			<issn pub-type="ppub">2764-3107</issn>
			<publisher>
				<publisher-name>Sociedade Brasileira de Cardiologia - SBC</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="doi">10.36660/abchf.20250018i</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Original Article</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Prevalence and Clinical Determinants of Optimized Pharmacological Therapy in Heart Failure with Reduced Ejection Fraction</article-title>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<name>
						<surname>Estevan</surname>
						<given-names>Anderson Oliveira</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>Acquisition of data</role>
					<role>Analysis and interpretation of the data</role>
					<role>Writing of the manuscript</role>
					<role>Statistical analysis</role>
					<role>Critical revision of the manuscript for intellectual content</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<name>
						<surname>Silva</surname>
						<given-names>Ana Luísa Guedes de Franca e</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>Acquisition of data</role>
					<role>Analysis and interpretation of the data</role>
					<role>Writing of the manuscript</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0009-0001-2444-754X</contrib-id>
					<name>
						<surname>Rassi</surname>
						<given-names>Salvador</given-names>
						<suffix>Filho</suffix>
					</name>
					<role>Conception and design of the research</role>
					<role>Acquisition of data</role>
					<role>Analysis and interpretation of the data</role>
					<role>Writing of the manuscript</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0003-3778-7153</contrib-id>
					<name>
						<surname>Freitas</surname>
						<given-names>Aguinaldo Figueiredo de</given-names>
						<suffix>Júnior</suffix>
					</name>
					<role>Conception and design of the research</role>
					<role>Acquisition of data</role>
					<role>Analysis and interpretation of the data</role>
					<role>Writing of the manuscript</role>
					<role>Statistical analysis</role>
					<role>Critical revision of the manuscript for intellectual content</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-7210-6486</contrib-id>
					<name>
						<surname>Rassi</surname>
						<given-names>Salvador</given-names>
					</name>
					<role>Conception and design of the research</role>
					<role>Acquisition of data</role>
					<role>Analysis and interpretation of the data</role>
					<role>Writing of the manuscript</role>
					<role>Statistical analysis</role>
					<role>Critical revision of the manuscript for intellectual content</role>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
			</contrib-group>
			<aff id="aff1">
				<label>1</label>
				<institution content-type="orgname">Universidade Federal de Goiás</institution>
				<addr-line>
					<named-content content-type="city">Goiania</named-content>
					<named-content content-type="state">GO</named-content>
				</addr-line>
				<country country="BR">Brazil</country>
				<institution content-type="original">Universidade Federal de Goiás, Goiania, GO – Brazil</institution>
			</aff>
			<author-notes>
				<corresp id="c01">
					<label>Mailing Address:</label>Anderson Oliveira Estevan Universidade Federal de Goiás – Cardiologia - R. 235, s/n. Postal Code 74605-220, Setor Leste, Universitário Goiânia, GO - Brazil E-mail: <email>estevan.anderson@hotmail.com</email>
				</corresp>
				<fn fn-type="coi-statement">
					<label>Potential Conflict of Interest:</label>
					<p> No potential conflict of interest relevant to this article was reported.</p>
				</fn>
				<fn fn-type="edited-by">
					<label>Editor responsible for the review:</label>
					<p>Germano Souza</p>
				</fn>
			</author-notes>
			<pub-date date-type="pub" publication-format="electronic">
				<day>31</day>
				<month>12</month>
				<year>2025</year>
			</pub-date>
			<pub-date date-type="collection" publication-format="electronic">
				<year>2025</year>
			</pub-date>
			<volume>5</volume>
			<issue>4</issue>
			<elocation-id>e20250018</elocation-id>
			<history>
				<date date-type="received">
					<day>25</day>
					<month>04</month>
					<year>2025</year>
				</date>
				<date date-type="rev-recd">
					<day>23</day>
					<month>12</month>
					<year>2025</year>
				</date>
				<date date-type="accepted">
					<day>26</day>
					<month>02</month>
					<year>2026</year>
				</date>
			</history>
			<permissions>
				<license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xml:lang="en">
					<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License</license-p>
				</license>
			</permissions>
			<abstract>
				<title>Abstract</title>
				<sec>
					<title>Background</title>
					<p> In heart failure with reduced ejection fraction (HFrEF), optimized medical therapy (OMT) with beta-blockers, angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs) (or sacubitril/valsartan), spironolactone, and sodium-glucose cotransporter-2 inhibitors (SGLT2i), at target or maximally tolerated doses, reduces morbidity and mortality. However, real-world data show its underuse.</p>
				</sec>
				<sec>
					<title>Objective</title>
					<p> To estimate the prevalence and clinical associations that influence the use of OMT in clinical practice.</p>
				</sec>
				<sec>
					<title>Methods</title>
					<p> Cross-sectional observational study including outpatients with HFrEF treated at a tertiary hospital. Clinical factors associated with therapy were assessed using binary logistic regression (95% confidence interval).</p>
				</sec>
				<sec>
					<title>Results</title>
					<p> A total of 266 patients were analyzed (mean age 61 years; 62.4% male), 113 (42.5%) with Chagas disease etiology. Mean ejection fraction was 34.2%. Vasodilators, beta-blockers, spironolactone, and SGLT2i were prescribed in 88%, 95.9%, 85.3%, and 27.4% of patients, respectively. The prevalence of OMT was 7.9% (21 patients). Diabetes was associated with a higher likelihood of OMT use (p = 0.034). Chagas disease was associated with lower probability of receiving vasodilators (p = 0.015) and greater use of furosemide, amiodarone, and digoxin (p &lt; 0.005). Chronic kidney disease (CKD), age &gt; 60 years, systolic blood pressure &lt; 100 mmHg, and use of furosemide were associated with lower use of vasodilators (p = 0.003; 0.025; 0.010; and 0.046). CKD was associated with lower use of spironolactone (p = 0.002). Diabetes (p = 0.002) and use of furosemide (p = 0.005) were associated with SGLT2i use.</p>
				</sec>
				<sec>
					<title>Conclusion</title>
					<p> Despite the high prevalence of prescription of disease-modifying drugs, the use of OMT was significantly lower than expected. CKD, advanced age, arterial hypotension, and concomitant use of furosemide were associated with a reduced likelihood of receiving these agents, whereas diabetes was associated with a higher probability of OMT use.</p>
				</sec>
			</abstract>
			<kwd-group xml:lang="en">
				<title>Keywords:</title>
				<kwd>Heart Failure</kwd>
				<kwd>Systolic Heart Failure</kwd>
				<kwd>Drug Therapy</kwd>
			</kwd-group>
			<funding-group>
				<funding-statement><bold>Sources of Funding:</bold> There were no external funding sources for this study.</funding-statement>
			</funding-group>
			<counts>
				<fig-count count="4"/>
				<table-count count="6"/>
				<equation-count count="0"/>
				<ref-count count="37"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<p>
					<fig id="f01">
						<label>Central Illustration:</label>
						<caption>
							<title>Prevalence and Clinical Determinants of Optimized Pharmacological Therapy in Heart Failure with Reduced Ejection Fraction</title>
						</caption>
						<graphic xlink:href="2764-3107-abchf-5-4-e20250018-gf01.tif"/>
						<attrib>ACEI: angiotensin-converting enzyme inhibitors; ARBs: angiotensin II receptor blockers; MRA: mineralocorticoid receptor antagonists; ARNIs: angiotensin receptor-neprilysin inhibitors; SGLT2i: sodium-glucose cotransporter-2 inhibitors; CKD: chronic kidney disease. Source: the authors.</attrib>
					</fig>
				</p>
		<sec sec-type="intro">
			<title>Introduction</title>
			<p>Heart failure (HF) represents a significant challenge for global public health, demanding effective therapeutic approaches to improve patients’ quality of life and survival.<sup><xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B2">2</xref></sup> In recent decades, there has been substantial progress in understanding the pathophysiology of HF with reduced ejection fraction (HFrEF), which has led to the development of pharmacological treatments capable of modifying the prognosis of the disease.<sup><xref ref-type="bibr" rid="B3">3</xref>-<xref ref-type="bibr" rid="B5">5</xref></sup></p>
			<p>Initially, the management of HFrEF was guided by hemodynamic strategies focused on symptom relief, with the use of diuretics, digitalis, and vasodilators. However, this approach proved insufficient to alter disease progression. With a better understanding of HF pathophysiology, modulation of the neurohormonal system became the focus of treatment.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B5">5</xref></sup> Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin ii receptor blockers (ARBs) represented a milestone in the treatment of HFrEF, with reductions in morbidity and mortality.<sup><xref ref-type="bibr" rid="B6">6</xref></sup> Subsequently, mineralocorticoid receptor antagonists (MRAs) and beta-blockers (BBs) were incorporated into therapy, consolidating the “triple therapy” as the cornerstone of HFrEF management.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> More recently, Angiotensin Receptor–Neprilysin Inhibitors (ARNIs) as well as Sodium–Glucose Cotransporter-2 Inhibitors (SGLT2i) have demonstrated efficacy in clinical trials and have been incorporated into the therapeutic arsenal for HFrEF.<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref></sup></p>
			<p>The use of these drugs has transformed the treatment of HFrEF, providing significant improvements in quality of life and survival. The use of quadruple therapy, at the recommended target doses or at the maximum dose tolerated by the patient, has become conventionally defined as Optimized Medical Therapy (OMT) for HFrEF.<sup><xref ref-type="bibr" rid="B10">10</xref>-<xref ref-type="bibr" rid="B12">12</xref></sup> Despite the clinical evidence and established guidelines, a significant gap persists between literature recommendations and the implementation of OMT in clinical practice, reflecting multifactorial challenges.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
			<p>The aim of this study was to estimate the prevalence of OMT prescription in a population of patients with HFrEF, according to current guidelines, as well as to identify possible clinical factors that may interfere with the use of the recommended pharmacological classes and their respective doses. Understanding the application of OMT in real-world patients contributes to identifying barriers and promoting strategies to improve treatment and, consequently, the prognosis of HFrEF.</p>
		</sec>
		<sec sec-type="methods">
			<title>Methods</title>
			<sec>
				<title>Data collection</title>
				<p>Data were collected over a 12-month period. The study was approved by the institutional Research Ethics Committee (REC) on 03/28/2022, under protocol number 5,315,449. The REC granted a waiver of the informed consent form, as provided by Resolution No. 466/2012. Information was collected through a structured questionnaire, based on the records of routine consultations of patients treated at the HF outpatient clinic of a tertiary university hospital.</p>
				<p>The study included adults of both sexes aged 18 years or older with a diagnosis of HF with reduced left ventricular ejection fraction (LVEF ≤ 40%). Patients with at least two visits to the cardiology outpatient clinic were included. Exclusion criteria were palliative care (end-stage HF), hemodialysis, heart transplantation, and hospitalization within the three months prior to the consultation, since such conditions could alter the prescription of HF pharmacological therapy.</p>
			</sec>
			<sec>
				<title>Variables and definitions</title>
				<p>The data assessment questionnaire included demographic variables (sex, age, and race), HF history (etiology and ejection fraction), clinical variables (functional class, blood pressure, and heart rate), laboratory variables (glomerular filtration rate, blood glucose, and electrolytes), and comorbidities. LVEF was measured using Simpson’s method, based on the most recent echocardiogram.</p>
				<p>Quadruple therapy was defined as the concomitant use of ACEI/ARB/ARNI combined with a beta-blocker, mineralocorticoid receptor antagonist, and SGLT2 inhibitor. OMT was defined as the concomitant use of quadruple therapy at target dose or at the maximum tolerated dose, according to the latest Update on Emerging Topics of the Brazilian Heart Failure Guideline – 2021.<sup><xref ref-type="bibr" rid="B15">15</xref></sup> The maximum tolerated dose was defined by the presence of a previous unsuccessful attempt at dose escalation and by the presence of hypotension (blood pressure &lt; 100 mmHg) and/or heart rate (HR) below 60 bpm. Dose titration was evaluated by comparing prescriptions over the last 12 months in a longitudinal manner.</p>
			</sec>
			<sec>
				<title>Statistical analysis</title>
				<p>The database was tabulated in EPIDATA® version 3.0, with double data entry and subsequent verification to minimize typing errors. Analyses were conducted using IBM SPSS (Statistical Package for Social Science) version 26.0 (IBM Corp., Armonk, NY, USA), considering a significance level of 5% (p &lt; 0.05). For comparison of categorical variables between groups, Pearson’s chi-square test was used, while continuous variables were analyzed using Student’s t-test for independent samples. Results were expressed as mean and standard deviation for continuous variables and as absolute and relative frequencies for categorical variables.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
				<p>The sociodemographic profile, etiologies, clinical and medication profiles were tested in five distinct models (use of OMT, vasodilators, beta-blockers, mineralocorticoid antagonists, and SGLT2 inhibitors). Each model consisted of two stages. First, a univariate logistic regression was performed to assess the association between each potential predictor variable and the response variable of each model. Variables with p &lt; 0.20 in the first stage were included in the multivariate logistic regression analysis (second stage). Results were presented in terms of Wald statistics, pseudo-R<sup>2</sup> determination coefficient, odds ratio (OR) with 95% CI, and p-values.</p>
			</sec>
		</sec>
		<sec sec-type="results">
			<title>Results</title>
			<p>Data from 524 patients treated during the study period were evaluated. After applying inclusion and exclusion criteria, the final sample consisted of 266 patients with HFrEF.</p>
			<sec>
				<title>Sample characteristics</title>
				<p>The characterization of the total sample and according to OMT is presented in <xref ref-type="table" rid="t1">Table 1</xref>. The mean age of patients was 61.33 ± 13.24 years, with no significant difference between groups (p = 0.583). Most participants were male (62.4%), with no differences between groups with and without OMT (p = 0.174). LVEF was significantly lower in patients who received OMT (29.57 ± 8.94%) compared to those who did not receive this approach (34.64 ± 10.68%; p = 0.049). HR was also significantly lower in the OMT group (62.05 ± 8.15 bpm vs. 68.26 ± 12.41 bpm; p = 0.045).</p>
				<p>
					<table-wrap id="t1">
						<label>Table 1</label>
						<caption>
							<title>– Characterization of the epidemiological profile and comorbidities in the total sample and according to optimized medical therapy (n = 266)</title>
						</caption>
						<table frame="hsides" rules="groups">
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left" style="font-weight:normal"> </th>
									<th colspan="4">TMO</th>
								</tr>
								<tr>
									<th align="left" style="font-weight:normal"> </th>
									<th>Total</th>
									<th>No</th>
									<th>Yes</th>
									<th>p</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td><bold>Age – year (Mean ± SD)</bold></td>
									<td align="center">61.33 ± 13.24</td>
									<td align="center">61.20 ± 13.45</td>
									<td align="center">62.86 ± 10.77</td>
									<td align="center">0.583</td>
								</tr>
								<tr>
									<td><bold>Sex n (%)</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>Female</td>
									<td align="center">100 (37.6)</td>
									<td align="center">95 (38.8)</td>
									<td align="center">5 (23.8)</td>
									<td align="center">0.174</td>
								</tr>
								<tr>
									<td>Male</td>
									<td align="center">166 (62.4)</td>
									<td align="center">150 (61.2)</td>
									<td align="center">16 (76.2)</td>
									<td> </td>
								</tr>
								<tr>
									<td><bold>Race n (%)</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>Yellow</td>
									<td align="center">3 (1.1)</td>
									<td align="center">3 (1.2)</td>
									<td align="center">0 (0.0)</td>
									<td> </td>
								</tr>
								<tr>
									<td>White</td>
									<td align="center">78 (29.3)</td>
									<td align="center">73 (29.8)</td>
									<td align="center">5 (23.8)</td>
									<td align="center">0.334</td>
								</tr>
								<tr>
									<td>Brown</td>
									<td align="center">162 (60.9)</td>
									<td align="center">150 (61.2)</td>
									<td align="center">12 (57.1)</td>
									<td> </td>
								</tr>
								<tr>
									<td>Black</td>
									<td align="center">23 (8.6)</td>
									<td align="center">19 (7.8)</td>
									<td align="center">4 (19.0)</td>
									<td> </td>
								</tr>
								<tr>
									<td><bold>Etiology of HF n (%)</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>Chagas</td>
									<td align="center">113 (42.5)</td>
									<td align="center">104 (42.4)</td>
									<td align="center">9 (42.9)</td>
									<td> </td>
								</tr>
								<tr>
									<td>Idiopathic</td>
									<td align="center">56 (21.1)</td>
									<td align="center">52 (21.2)</td>
									<td align="center">4 (19.0)</td>
									<td align="center">0.962</td>
								</tr>
								<tr>
									<td>Ischemic</td>
									<td align="center">44 (16.5)</td>
									<td align="center">41 (16.7)</td>
									<td align="center">3 (14.3)</td>
									<td> </td>
								</tr>
								<tr>
									<td>Others</td>
									<td align="center">53 (19.9)</td>
									<td align="center">48 (19.6)</td>
									<td align="center">5 (23.8)</td>
									<td> </td>
								</tr>
								<tr>
									<td>SBP (mmHg) mean ± DP</td>
									<td align="center">111.91 ± 19.53</td>
									<td align="center">112.43 ± 19.33</td>
									<td align="center">105.81 ± 21.25</td>
									<td align="center">0.136</td>
								</tr>
								<tr>
									<td>Ejection fraction (%)</td>
									<td align="center">34.54 ± 10.63</td>
									<td align="center">34.64 ± 10.68</td>
									<td align="center">29.57 ± 8.94</td>
									<td align="center">0.049</td>
								</tr>
								<tr>
									<td>Heart rate (bpm)</td>
									<td align="center">67.77 ± 12.23</td>
									<td align="center">68.26 ± 12.41</td>
									<td align="center">62.05 ± 8.15</td>
									<td align="center">0.045</td>
								</tr>
								<tr>
									<td><bold>NYHA</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>I</td>
									<td align="center">111 (41.7)</td>
									<td align="center">105 (42.9)</td>
									<td align="center">6 (28.6)</td>
									<td> </td>
								</tr>
								<tr>
									<td>II</td>
									<td align="center">108 (40.6)</td>
									<td align="center">95 (38.8)</td>
									<td align="center">13 (61.9)</td>
									<td> </td>
								</tr>
								<tr>
									<td>III</td>
									<td align="center">40 (15.0)</td>
									<td align="center">38 (15.5)</td>
									<td align="center">2 (9.5)</td>
									<td> </td>
								</tr>
								<tr>
									<td>IV</td>
									<td align="center">7 (2.6)</td>
									<td align="center">7 (2.9)</td>
									<td align="center">0 (0.0)</td>
									<td> </td>
								</tr>
								<tr>
									<td><bold>Use of devices n (%)</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>No</td>
									<td align="center">189 (71.1)</td>
									<td align="center">175 (71.4)</td>
									<td align="center">14 (66.7)</td>
									<td align="center">0.644</td>
								</tr>
								<tr>
									<td>Yes</td>
									<td align="center">77 (28.9)</td>
									<td align="center">70 (28.6)</td>
									<td align="center">7 (33.3)</td>
									<td> </td>
								</tr>
								<tr>
									<td><bold>Comorbidities n (%)</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td>HAS</td>
									<td align="center">135 (50.8)</td>
									<td align="center">128 (52.2)</td>
									<td align="center">7 (33.3)</td>
									<td align="center">0.096</td>
								</tr>
								<tr>
									<td>DLP</td>
									<td align="center">76 (28.6)</td>
									<td align="center">69 (28.2)</td>
									<td align="center">7 (33.3)</td>
									<td align="center">0.612</td>
								</tr>
								<tr>
									<td>Atrial fibrillation</td>
									<td align="center">54 (20.3)</td>
									<td align="center">48 (19.6)</td>
									<td align="center">6 (28.6)</td>
									<td align="center">0.326</td>
								</tr>
								<tr>
									<td>VT/VF</td>
									<td align="center">35 (13.2)</td>
									<td align="center">33 (13.5)</td>
									<td align="center">2 (9.5)</td>
									<td align="center">0.605</td>
								</tr>
								<tr>
									<td>PAD</td>
									<td align="center">9 (3.4)</td>
									<td align="center">8 (3.3)</td>
									<td align="center">1 (4.8)</td>
									<td align="center">0.716</td>
								</tr>
								<tr>
									<td>Depression</td>
									<td align="center">6 (2.3)</td>
									<td align="center">6 (2.4)</td>
									<td align="center">0 (0.0)</td>
									<td align="center">0.468</td>
								</tr>
								<tr>
									<td>hypothyroidism</td>
									<td align="center">61 (22.9)</td>
									<td align="center">55 (22.4)</td>
									<td align="center">6 (28.6)</td>
									<td align="center">0.522</td>
								</tr>
								<tr>
									<td>DM</td>
									<td align="center">58 (21.8)</td>
									<td align="center">50 (20.4)</td>
									<td align="center">8 (38.1)</td>
									<td align="center">0.064</td>
								</tr>
								<tr>
									<td>AMI</td>
									<td align="center">32 (12.0)</td>
									<td align="center">29 (11.8)</td>
									<td align="center">3 (14.3)</td>
									<td align="center">0.741</td>
								</tr>
								<tr>
									<td>CKD</td>
									<td align="center">45 (16.9)</td>
									<td align="center">39 (15.9)</td>
									<td align="center">6 (28.6)</td>
									<td align="center">0.138</td>
								</tr>
								<tr>
									<td>Stroke</td>
									<td align="center">20 (7.5)</td>
									<td align="center">19 (7.8)</td>
									<td align="center">1 (4.8)</td>
									<td align="center">0.618</td>
								</tr>
								<tr>
									<td>Anemia</td>
									<td align="center">37 (13.9)</td>
									<td align="center">34 (13.9)</td>
									<td align="center">3 (14.3)</td>
									<td align="center">0.959</td>
								</tr>
								<tr>
									<td>COPD</td>
									<td align="center">26 (9.8)</td>
									<td align="center">25 (10.2)</td>
									<td align="center">1 (4.8)</td>
									<td align="center">0.420</td>
								</tr>
								<tr>
									<td>Current smoker</td>
									<td align="center">17 (6.4)</td>
									<td align="center">17 (6.9)</td>
									<td align="center">0 (0.0)</td>
									<td align="center">0.212</td>
								</tr>
								<tr>
									<td>Former smoker</td>
									<td align="center">72 (27.1)</td>
									<td align="center">66 (26.9)</td>
									<td align="center">6 (28.6)</td>
									<td align="center">0.876</td>
								</tr>
							</tbody>
						</table>
						<table-wrap-foot>
							<fn id="TFN1">
								<p>*Pearson’s chi-square; Student’s t-test; n: absolute frequency; %: relative frequency; AMI: acute myocardial infarction; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease; DLP: dyslipidemia; DM: diabetes mellitus; HR: heart rate; M: mean; NYHA: New Yor Heart Association; OMT: optimized medical therapy; PAD: peripheral arterial disease; SAH: systemic arterial hypertension; SBP: systolic blood pressure; SD: standard deviation; VT/VF: ventricular tachycardia / ventricular fibrillation.</p>
							</fn>
						</table-wrap-foot>
					</table-wrap>
				</p>
				<p>Other variables, including hypertension, diabetes mellitus, Chronic Kdney Disease (CKD), and other comorbidities, did not show statistically significant differences between groups (<xref ref-type="table" rid="t1">Table 1</xref>). The most prevalent etiology of HF in this population was Chagas disease, representing 42.5% (113) of the sample, followed by idiopathic dilated cardiomyopathy (21%) and ischemic etiology (16.5%).</p>
			</sec>
			<sec>
				<title>Prevalence of OMT and medication classes</title>
				<p>The prevalence of concomitant use of ACEI/ARB/ARNI, beta-blockers, MRAs, and SGLT2 inhibitors (quadruple therapy) was 20.3% (54 patients). The prevalence of OMT, defined as the use of quadruple therapy at target dose or maximum tolerated dose (as shown in the <xref ref-type="fig" rid="f01">Central Figure</xref>), was 7.9% (21 patients). Vasodilators, beta-blockers, spironolactone, and gliflozins were prescribed in 88%, 95.9%, 85.3%, and 27.4% of patients, respectively.</p>
				<p>Among the 116 patients using ACEIs, 96.5% (112) received enalapril, followed by 2.6% (3) captopril and 0.9% (1) ramipril. Among ARB users, 97.0% (64) were on losartan and 3.0% (2) on valsartan. A total of 12.0% (32) had a recorded contraindication to some vasodilator (renal dysfunction or hypotension). Regarding beta-blockers, carvedilol, metoprolol, and bisoprolol were used by 52.6% (134), 18.4% (47), and 29% (74) of patients, respectively. Contraindication to beta-blocker use was recorded in 2.3% (6), mainly due to severe asthma or bradycardia.</p>
				<p>Spironolactone was the MRA used, and dapagliflozin was the SGLT2 inhibitor prescribed. MRA use was contraindicated in 5.3% (14), with renal dysfunction and hyperkalemia as the main causes. For SGLT2 inhibitors, 0.4% (1) had a reported contraindication described as “intolerance.”</p>
			</sec>
			<sec>
				<title>Dose evaluation</title>
				<p>
					<xref ref-type="fig" rid="f02">Figure 1</xref> shows the distribution for each drug class according to the percentile of the target dose. It was observed that the BB class had the lowest proportion of patients receiving doses above 50% of the target dose, as shown in item C of <xref ref-type="fig" rid="f02">Figure 1</xref>.</p>
				<p>
					<fig id="f02">
						<label>Figure 1</label>
						<caption>
							<title>– Percentile of target dose in the pharmacological treatment of patients with heart failure with reduced ejection fraction (HFrEF); ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blocker; ARNI: angiotensin receptor–neprilysin inhibitor.</title>
						</caption>
						<graphic xlink:href="2764-3107-abchf-5-4-e20250018-gf02.tif"/>
					</fig>
				</p>
			</sec>
			<sec>
				<title>Etiology and pharmacological treatment</title>
				<p>The logistic regression analysis between HF etiologies and pharmacological treatment revealed that patients with Chagas disease were 61% less likely to receive vasodilators (OR = 0.39; 95% CI = 0.18–0.85; p = 0.015). Conversely, these patients were more likely to be prescribed furosemide (OR = 2.40; 95% CI = 1.39–4.11; p = 0.001), amiodarone (OR = 4.98; 95% CI = 2.89–8.59; p &lt; 0.001), and digoxin (OR = 3.75; 95% CI = 1.40–9.98; p = 0.005). <xref ref-type="table" rid="t2">Table 2</xref> shows the associations found. No significant differences were observed in the use of HF medications across the other etiologies analyzed.</p>
				<p>
					<table-wrap id="t2">
						<label>Table 2</label>
						<caption>
							<title>– Result of the association between Chagas disease and pharmacological treatment of heart failure with reduced ejection fraction (n = 266)</title>
						</caption>
						<table frame="hsides" rules="groups">
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left" style="font-weight:normal"> </th>
									<th colspan="2">Chagas n (%)</th>
									<th rowspan="2">OR (95%CI)</th>
									<th rowspan="2">p</th>
								</tr>
								<tr>
									<th align="left">Treatment</th>
									<th>No</th>
									<th>Yes</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td>Quadruple therapy</td>
									<td align="center">33 (21.6)</td>
									<td align="center">21 (18.6)</td>
									<td align="center">0.83 (0.45–1.52)</td>
									<td align="center">0.550</td>
								</tr>
								<tr>
									<td>OPT</td>
									<td align="center">12 (7.8)</td>
									<td align="center">9 (8.0)</td>
									<td align="center">1.01 (0.41–2.50)</td>
									<td align="center">0.971</td>
								</tr>
								<tr>
									<td>Betablockers</td>
									<td align="center">149 (97.4)</td>
									<td align="center">106 (93.8)</td>
									<td align="center">0.40 (0.11–1.42)</td>
									<td align="center">0.147</td>
								</tr>
								<tr>
									<td>Vasodilators</td>
									<td align="center">141 (92.2)</td>
									<td align="center">93 (82.3)</td>
									<td align="center">0.39 (0.18–0.85)</td>
									<td align="center">0.015</td>
								</tr>
								<tr>
									<td>Spironolactone</td>
									<td align="center">129 (84.3)</td>
									<td align="center">98 (86.7)</td>
									<td align="center">1.21 (0.60–2.63)</td>
									<td align="center">0.581</td>
								</tr>
								<tr>
									<td>SGLT2i</td>
									<td align="center">40 (26.1)</td>
									<td align="center">33 (29.2)</td>
									<td align="center">1.65 (0.68–2.00)</td>
									<td align="center">0.580</td>
								</tr>
								<tr>
									<td>ACEI</td>
									<td align="center">73 (47.7)</td>
									<td align="center">43 (38.1)</td>
									<td align="center">0.67 (0.41–1.14)</td>
									<td align="center">0.116</td>
								</tr>
								<tr>
									<td>ARB</td>
									<td align="center">43 (28.1)</td>
									<td align="center">23 (20.4)</td>
									<td align="center">0.65 (0.36–1.16)</td>
									<td align="center">0.148</td>
								</tr>
								<tr>
									<td>ARNIs</td>
									<td align="center">25 (16.3)</td>
									<td align="center">27 (23.9)</td>
									<td align="center">1.60 (0.87–2.96)</td>
									<td align="center">0.125</td>
								</tr>
								<tr>
									<td>Ivabradine</td>
									<td align="center">13 (8.5)</td>
									<td align="center">4 (3.5)</td>
									<td align="center">0.39 (0.12–1.24)</td>
									<td align="center">0.102</td>
								</tr>
								<tr>
									<td>Furosemide</td>
									<td align="center">89 (58.2)</td>
									<td align="center">87 (77.0)</td>
									<td align="center">2.40 (1.39–4.11)</td>
									<td align="center">0.001</td>
								</tr>
								<tr>
									<td>Amiodarone</td>
									<td align="center">30 (19.6)</td>
									<td align="center">62 (54.9)</td>
									<td align="center">4.98 (2.89–8.59)</td>
									<td align="center">&lt;0.001</td>
								</tr>
								<tr>
									<td>Digoxin</td>
									<td align="center">6 (3.9)</td>
									<td align="center">15 (13.3)</td>
									<td align="center">3.75 (1.40–9.98)</td>
									<td align="center">0.005</td>
								</tr>
							</tbody>
						</table>
						<table-wrap-foot>
							<fn id="TFN2">
								<p>*Logistic regression; n: absolute frequency; %: relative frequence; ACEI: angiotensin-converting enzyme inhibitors; ARBs: angiotensin II receptor blockers; ARNIs: angiotensin receptor–neprilysin inhibitors; OTM: optimized pharmacological therapy; SGLT2i: sodium-glucose cotransporter-2 inhibitors.</p>
							</fn>
						</table-wrap-foot>
					</table-wrap>
				</p>
			</sec>
			<sec>
				<title>Predictors of OMT use and medication classes</title>
				<p>
					<xref ref-type="table" rid="t3">Table 3</xref> shows the results of the multivariate logistic regression analyses regarding the use of OMT and medication classes. In the multivariate analysis for OMT use, diabetes mellitus emerged as a significant predictor, increasing the likelihood of OMT use by 2.82 times (OR = 2.82; 95% CI = 1.07–7.24; p = 0.036). In addition, patients on OMT were more likely to present SBP &lt; 100 mmHg (OR = 2.80; 95% CI = 1.03–7.02; p = 0.043).</p>
				<p>
					<table-wrap id="t3">
						<label>Table 3</label>
						<caption>
							<title>– Multivariate logistic regression analyses for the use of optimized pharmacological therapy (OPT) and the drug classes employed in heart failure with reduced ejection fraction</title>
						</caption>
						<table frame="hsides" rules="groups">
							<colgroup>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
								<col/>
							</colgroup>
							<thead>
								<tr>
									<th align="left" style="font-weight:normal"> </th>
									<th align="left" style="font-weight:normal"> </th>
									<th>No</th>
									<th>Yes</th>
									<th>Wald</th>
									<th style="font-weight:normal">r<sup><bold>2</bold></sup></th>
									<th>OR (95%CI)</th>
									<th>p</th>
								</tr>
							</thead>
							<tbody>
								<tr>
									<td><bold>OPT</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Male sex</td>
									<td align="center">150 (61.2)</td>
									<td align="center">16 (76.2)</td>
									<td align="center">1.42</td>
									<td align="center" rowspan="4">0.08</td>
									<td align="center">1.91 (0.66–5.54)</td>
									<td align="center">0.231</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">CKD</td>
									<td align="center">39 (15.9)</td>
									<td align="center">6 (28.6)</td>
									<td align="center">1.02</td>
									<td align="center">1.71 (0.60–4.86)</td>
									<td align="center">0.312</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">DM</td>
									<td align="center">50 (20.4)</td>
									<td align="center">8 (38.1)</td>
									<td align="center">4.42</td>
									<td align="center">2.82 (1.07–7.24)</td>
									<td align="center">0.036</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">SBP &lt;100</td>
									<td align="center">43 (17.6)</td>
									<td align="center">7 (33.3)</td>
									<td align="center">4.08</td>
									<td align="center">2.80 (1.03–7.02)</td>
									<td align="center">0.043</td>
								</tr>
								<tr>
									<td><bold>Betablockers</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Stroke</td>
									<td align="center">2 (18.2)</td>
									<td align="center">18 (7.1)</td>
									<td align="center">0.91</td>
									<td align="center" rowspan="4">0.06</td>
									<td align="center">0.44 (0.08–2.37)</td>
									<td align="center">0.341</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Atrial fibrillation</td>
									<td align="center">4 (36.4)</td>
									<td align="center">50 (19.6)</td>
									<td align="center">0.48</td>
									<td align="center">0.63 (0.17–2.34)</td>
									<td align="center">0.490</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Chagas</td>
									<td align="center">7 (63.6)</td>
									<td align="center">106 (41.6)</td>
									<td align="center">0.25</td>
									<td align="center">0.71 (0.18–2.79)</td>
									<td align="center">0.618</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Amiodarone</td>
									<td align="center">7 (63.6)</td>
									<td align="center">85 (33.3)</td>
									<td align="center">2.17</td>
									<td align="center">0.36 (0.09–1.40)</td>
									<td align="center">0.140</td>
								</tr>
								<tr>
									<td><bold>Vasodilators</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Age &gt;60 years</td>
									<td align="center">26 (81.3)</td>
									<td align="center">129 (55.1)</td>
									<td align="center">5.05</td>
									<td align="center" rowspan="9">0.20</td>
									<td align="center">0.32 (0.12–0.87)</td>
									<td align="center">0.025</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">CKD</td>
									<td align="center">14 (43.8)</td>
									<td align="center">31 (13.2)</td>
									<td align="center">8.75</td>
									<td align="center">0.28 (0.12–0.65)</td>
									<td align="center">0.003</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Stroke</td>
									<td align="center">7 (21.9)</td>
									<td align="center">13 (5.6)</td>
									<td align="center">2.57</td>
									<td align="center">0.39 (0.13–1.23)</td>
									<td align="center">0.109</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">VT/VF</td>
									<td align="center">10 (31.3)</td>
									<td align="center">25 (10.7)</td>
									<td align="center">1.10</td>
									<td align="center">0.56 (0.19–1.65)</td>
									<td align="center">0.294</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Chagas</td>
									<td align="center">20 (62.5)</td>
									<td align="center">93 (39.7)</td>
									<td align="center">0.87</td>
									<td align="center">1.61 (0.59–4.35)</td>
									<td align="center">0.352</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Idiopathic</td>
									<td align="center">2 (6.3)</td>
									<td align="center">54 (23.1)</td>
									<td align="center">1.89</td>
									<td align="center">3.10 (0.62–15.60)</td>
									<td align="center">0.169</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">SBP &lt;100</td>
									<td align="center">12 (37.5)</td>
									<td align="center">38 (16.2)</td>
									<td align="center">6.61</td>
									<td align="center">0.32 (0.14–0.76)</td>
									<td align="center">0.010</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Furosemide</td>
									<td align="center">27 (84.4)</td>
									<td align="center">149 (63.7)</td>
									<td align="center">3.97</td>
									<td align="center">0.35 (0.12–0.98)</td>
									<td align="center">0.046</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Amiodarone</td>
									<td align="center">19 (59.4)</td>
									<td align="center">73 (31.2)</td>
									<td align="center">1.26</td>
									<td align="center">0.58 (0.22–1.51)</td>
									<td align="center">0.262</td>
								</tr>
								<tr>
									<td><bold>Spironolactone</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td align="center" rowspan="7">0.15</td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Age &gt; 60 years</td>
									<td align="center">27 (69.2)</td>
									<td align="center">128 (56.4)</td>
									<td align="center">0.24</td>
									<td align="center">0.82 (0.37–1.82)</td>
									<td align="center">0.621</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">CKD</td>
									<td align="center">12 (30.8)</td>
									<td align="center">33 (14.5)</td>
									<td align="center">9.34</td>
									<td align="center">0.26 (0.11–0.62)</td>
									<td align="center">0.002</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">PAD</td>
									<td align="center">3 (7.7)</td>
									<td align="center">6 (2.6)</td>
									<td align="center">1.89</td>
									<td align="center">0.34 (0.07–1.58)</td>
									<td align="center">0.169</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">SBP &lt;100</td>
									<td align="center">2 (5.1)</td>
									<td align="center">48 (21.1)</td>
									<td align="center">4.74</td>
									<td align="center">5.27 (1.18–23.53)</td>
									<td align="center">0.029</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">HR</td>
									<td align="center">13 (33.3)</td>
									<td align="center">38 (16.7)</td>
									<td align="center">3.89</td>
									<td align="center">0.43 (0.19–1.00)</td>
									<td align="center">0.049</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Furosemide</td>
									<td align="center">16 (41.0)</td>
									<td align="center">160 (70.5)</td>
									<td align="center">12.87</td>
									<td align="center">3.90 (1.85–8.20)</td>
									<td align="center">&lt;0.001</td>
								</tr>
								<tr>
									<td><bold>SGLT2i</bold></td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
									<td> </td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Age &gt; 60 yeas</td>
									<td align="center">107 (55.4)</td>
									<td align="center">48 (65.8)</td>
									<td align="center">0.33</td>
									<td align="center" rowspan="8">0.09</td>
									<td align="center">1.20 (0.65–2.22)</td>
									<td align="center">0.567</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">DM</td>
									<td align="center">32 (16.6)</td>
									<td align="center">26 (35.6)</td>
									<td align="center">9.30</td>
									<td align="center">2.63 (1.41–4.91)</td>
									<td align="center">0.002</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">AMI</td>
									<td align="center">20 (10.4)</td>
									<td align="center">12 (16.4)</td>
									<td align="center">0.03</td>
									<td align="center">0.91 (0.28–2.90)</td>
									<td align="center">0.868</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">CKD</td>
									<td align="center">26 (13.5)</td>
									<td align="center">19 (26.0)</td>
									<td align="center">1.57</td>
									<td align="center">1.60 (0.77–3.35)</td>
									<td align="center">0.210</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Stroke</td>
									<td align="center">10 (5.2)</td>
									<td align="center">10 (13.7)</td>
									<td align="center">1.91</td>
									<td align="center">2.07 (0.74–5.80)</td>
									<td align="center">0.167</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Ischemic</td>
									<td align="center">27 (14.0)</td>
									<td align="center">17 (23.3)</td>
									<td align="center">1.27</td>
									<td align="center">1.82 (0.64–5.14)</td>
									<td align="center">0.260</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Idiopathic</td>
									<td align="center">45 (23.3)</td>
									<td align="center">11 (15.1)</td>
									<td align="center">0.38</td>
									<td align="center">0.78 (0.36–1.72)</td>
									<td align="center">0.540</td>
								</tr>
								<tr>
									<td> </td>
									<td align="center">Furosemide</td>
									<td align="center">117 (60.6)</td>
									<td align="center">59 (80.8)</td>
									<td align="center">8.05</td>
									<td align="center">2.60 (1.34–5.03)</td>
									<td align="center">0.005</td>
								</tr>
							</tbody>
						</table>
						<table-wrap-foot>
							<fn id="TFN3">
								<p>*Logistic regression; n: absolute frequency; %: relative frequence; AMI: acute myocardial infarction; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease; DM: diabetes mellitus; HR: heart rate; OTM: optimized pharmacological therapy; PAD: peripheral arterial disease; SBP: systolic blood pressure; SGLT2i: sodium-glucose cotransporter-2 inhibitors; VT/VF: ventricular tachycardia / ventricular fibrillation.</p>
							</fn>
						</table-wrap-foot>
					</table-wrap>
				</p>
				<p>In the final model for vasodilator use, the presence of CKD reduced the probability of using this drug class by 72% (OR = 0.28; 95% CI = 0.12–0.65; p = 0.003). Furthermore, SBP &lt; 100 mmHg reduced the likelihood of vasodilator use by 68% (OR = 0.32; 95% CI = 0.14–0.76; p = 0.010). Age over 60 years (OR = 0.32; 95% CI = 0.12–0.87; p = 0.025) and furosemide use (OR = 0.35; 95% CI = 0.12–0.98; p = 0.046) were also associated with a lower probability of vasodilator use.</p>
				<p>No variable showed statistical significance in the multivariate model regarding beta-blocker use.</p>
				<p>Regarding the use of spironolactone, the multivariate analysis showed that patients with CKD were 74% less likely to receive spironolactone (OR = 0.26; 95% CI = 0.11–0.62; p = 0.002). On the other hand, furosemide use was strongly associated with spironolactone use, tripling the likelihood of prescribing this medication (OR = 3.90; 95% CI = 1.85–8.20; p &lt; 0.001). The variable “furosemide use” presented the highest Wald statistic (Wald = 12.87), indicating a strong association between these two drug classes.</p>
				<p>For SGLT2 inhibitors, the final multivariate model indicated that the presence of diabetes mellitus increased the likelihood of use of this class by 2.63 times (OR = 2.63; 95% CI = 1.41–4.91; p = 0.002). Furosemide use was also a significant factor, with a 2.60-fold increase in the probability of SGLT2 inhibitor prescription (OR = 2.60; 95% CI = 1.34–5.03; p = 0.005).</p>
			</sec>
		</sec>
		<sec sec-type="discussion">
			<title>Discussion</title>
			<p>In the current scenario of high morbidity and mortality rates among patients with HF, it is crucial to improve pharmacological treatment to ensure a more favorable prognosis for these patients. A better understanding, with real-world data, of the determinants of non-adoption of evidence-based pharmacological therapy has a major impact on improving care for HF patients.<sup><xref ref-type="bibr" rid="B17">17</xref></sup></p>
			<p>The present study found a prevalence of 7.9% for the use of OMT. Real-world patients, with multiple comorbidities and particularities, may represent a challenge in initiating and titrating medications compared to clinical trials. Several factors may contribute to the underuse of evidence-based therapy in patients with HFrEF: factors related to the physician, the patient, and the healthcare system. Therapeutic inertia – defined as the tendency to maintain the current dose in clinically stable patients with low functional class – is also a limiting factor in achieving OMT. Lack of access to medical care (due to shortage of healthcare professionals or geographic limitations) may also hinder medication titration. In addition, drug costs may represent another barrier.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
			<p>In this study, it was observed that 21.6% of patients were on quadruple therapy, while the prevalence of OMT (target dose or maximum tolerated dose of quadruple therapy) was 7.9%. In the CHAMP-HF registry, a U.S. observational study with 3,518 outpatients with HFrEF, only 1.1% were simultaneously on target doses of triple therapy (according to the guidelines available at the time of the study).<sup><xref ref-type="bibr" rid="B18">18</xref></sup> The cited registry included non-specialized cardiology centers, which may explain the lower OMT rate observed compared to that found in the present study.</p>
			<p>The IMPROVE-HF study demonstrated an increase in the prevalence of OMT from 14.1% to 22.8% in patients with HFrEF following the implementation of educational measures on HF treatment and management.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> Academic centers may achieve high rates of OMT utilization, and continuous medical education and training are fundamentally important as the basis for maintaining high-quality care for HF patients.</p>
			<p>A Brazilian observational study reported a prevalence of OMT (33.1%) in patients with HFrEF. However, this prevalence referred to the use of triple therapy,<sup><xref ref-type="bibr" rid="B20">20</xref></sup> differing from the present study, which included the use of SGLT2 inhibitors. Other studies have estimated the prevalence of concomitant use of HF drug classes,<sup><xref ref-type="bibr" rid="B2">2</xref>
				<xref ref-type="bibr" rid="B1">1</xref></sup> but analyzed only triple therapy and did not assess use at target or maximum tolerated doses.</p>
			<p>The prevalence of vasodilator use (ACEI or ARB or ARNI) in the studied sample was 88%, with 49.5% (116), 28.2% (66), and 22.2% (52) using ACEIs, ARBs, and ARNIs, respectively. The prevalence of vasodilator use in this study is higher than those reported in international registries, which range from 73.4% to 85.8%.<sup><xref ref-type="bibr" rid="B15">15</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref></sup> In the present study, ARNI use was 19.5% (52). This rate is higher than that observed in the U.S. population (13.0%) and in Middle Eastern registries (3.6%). The higher ARNI use is possibly associated with the recent availability (since 2021) of the drug in public high-cost medication distribution services in the studied region.<sup><xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B21">21</xref></sup></p>
			<p>The prevalence of beta-blocker use was 95.9% (255). This high utilization rate of this drug class has also been reported in other Brazilian studies (ranging from 80% to 100%, depending on the region of the country).<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B10">10</xref>,<xref ref-type="bibr" rid="B11">11</xref></sup> The prevalence of beta-blocker use in international registries varies from 67% to 86.2% in U.S. data, while in European studies it ranges from 52% to 84%.<sup><xref ref-type="bibr" rid="B15">15</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B22">22</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup></p>
			<p>The utilization rate of spironolactone was 85.3% (227). In international registries, lower frequencies of MRA use are observed, ranging from 32.0% to approximately 56.0%.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> Brazilian data show prescription rates for this drug class ranging from 64% to 93%.<sup><xref ref-type="bibr" rid="B20">20</xref>,<xref ref-type="bibr" rid="B22">22</xref></sup></p>
			<p>The prevalence of SGLT2 inhibitor use was 27.4% (73). According to the literature, treatment rates with this class range from 12% to 20.1% in observational studies, which mostly included diabetic patients (11.9%) and few patients with HF (7.6%).<sup><xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B26">26</xref></sup> Compared with the literature, we observed a higher prevalence of SGLT2 inhibitor prescription. This is possibly due to the high prevalence of diabetes in the studied population (21.8%), for whom this medication is more readily available in the public healthcare system.</p>
			<sec>
				<title>Factors associated with the use of drug classes</title>
				<p>Regarding vasodilator use, it was observed that the presence of CKD, advanced age, hypotension, and furosemide use were associated with a lower likelihood of prescribing this drug class. CKD is widely described in the literature as a limiting factor for the use of these medications.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup> Similarly, advanced age is associated with non-use of ACEI/ARB, possibly reflecting a tendency toward under-medication in elderly patients, whether due to intolerance or therapeutic inertia.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> Arterial hypotension may be a marker of more advanced disease and intolerance to this drug class.</p>
				<p>Furosemide is not reported as a classic limiting factor for vasodilator use, but its negative association is possibly due to its hypotensive effect, which ultimately restricts the initiation or titration of vasodilators.<sup><xref ref-type="bibr" rid="B28">28</xref>,<xref ref-type="bibr" rid="B29">29</xref></sup> This finding highlights the need for caution with other prescribed medications and their potential interactions in the pharmacological treatment of HFrEF.</p>
				<p>The presence of CKD was an independent predictor of non-use of spironolactone. CKD is classically reported as a limiting factor for the use of this medication, with worsening renal function and hyperkalemia being the most frequent complications.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup> In this study, no association was found between hyperkalemia and lower likelihood of MRA use. The positive association between spironolactone use and the presence of hypotension suggests that HF patients treated with this drug class tend to have lower blood pressure levels due to the hypotensive effect of MRAs.<sup><xref ref-type="bibr" rid="B15">15</xref></sup></p>
				<p>Furosemide use was positively associated with spironolactone use, which may reflect the commonly observed association in clinical practice, where more congested patients require concomitant use of both drugs. In a Swedish registry with more than 11,000 patients, it was observed that patients using other diuretics were more likely to use MRAs,<sup><xref ref-type="bibr" rid="B24">24</xref></sup> corroborating the findings of the present study.</p>
				<p>Regarding the use of SGLT2 inhibitors, a positive association was observed between this drug class and the presence of diabetes mellitus (DM) as well as furosemide use. The association with DM may be explained by an indication bias, since patients with DM often receive SGLT2 inhibitors for glycemic control regardless of the HF indication, which increases OMT rates among diabetic patients. Although evidence shows a reduction in HF mortality regardless of the presence of DM,<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup> registries report higher prescription rates of SGLT2 inhibitors for patients with DM than for those with HF.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> The association between SGLT2 inhibitors and furosemide suggests that more congested and symptomatic patients may be more likely to receive concomitant loop diuretics and SGLT2 inhibitors. SGLT2 inhibitors tend to be more frequently prescribed in congested patients.<sup><xref ref-type="bibr" rid="B28">28</xref></sup></p>
				<p>Chagas disease presents inherent autonomic dysfunction as well as progressive damage to the heart’s electrical conduction system.<sup><xref ref-type="bibr" rid="B30">30</xref>-<xref ref-type="bibr" rid="B32">32</xref></sup> The use of amiodarone is frequent in this population due to the presence of severe arrhythmias, which justifies the observed association whereby Chagas etiology increases the likelihood of amiodarone use.<sup><xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B34">34</xref></sup> Furthermore, the presence of Chagas disease was associated with a lower likelihood of vasodilator use, which may be explained by the borderline blood pressure commonly observed in this group,<sup><xref ref-type="bibr" rid="B35">35</xref></sup> preventing prescription of this drug class due to patient intolerance.</p>
				<p>The STRONG-HF study investigated the impact of quadruple therapy in patients with HF. The results demonstrated that early intensification of treatment, combined with close follow-up, significantly reduced the rate of hospitalization for HF and all-cause mortality at 180 days compared with usual care.<sup><xref ref-type="bibr" rid="B36">36</xref></sup> In addition, improvements were observed in symptoms, quality of life, and biomarkers such as NT-proBNP. There was no significant increase in serious or fatal adverse events. These findings suggest that the implementation of an aggressive strategy for titration of quadruple therapy can substantially improve the prognosis of patients with HF, highlighting the importance of intensive and personalized management of these patients.</p>
				<p>An observational study analyzed the impact of comorbidities on the prescription of pharmacological therapy in patients with HFrEF. Hypertension, DM, CKD, atrial fibrillation, and chronic obstructive pulmonary disease were the most prevalent comorbidities. The presence of multiple comorbidities negatively influenced the prescription of triple therapy, especially vasodilators and MRAs. However, the implementation of quadruple therapy, which included the addition of SGLT2 inhibitors, did not differ significantly between groups with different comorbidity burdens.<sup><xref ref-type="bibr" rid="B37">37</xref></sup> These findings suggest that although multimorbidity may hinder the prescription of triple therapy, the addition of SGLT2 inhibitors may be feasible regardless of the number of comorbidities. In the present study, no comorbidity was negatively associated with the use of SGLT2 inhibitors.</p>
				<p>This study has limitations arising from its cross-sectional design, which restricts the assessment of adherence or therapeutic changes over time. Its single-center nature also limits the generalizability of the findings to other populations. Furthermore, the possibility of under-reporting contraindications in medical records may have influenced the classification of the therapies evaluated. These factors should be considered when interpreting the results.</p>
				<p>The barriers to OMT use observed in the present study highlight the need for systematic strategies to overcome therapeutic inertia and ensure appropriate treatment in HFrEF. The implementation of outpatient dose-titration protocols, continuous medical education, and periodic systematic review of drug classes and doses are measures that should be adopted by specialized services. The findings point to the need for a proactive and structured model of care focused on therapeutic progression in HF patients.</p>
			</sec>
		</sec>
		<sec sec-type="conclusions">
			<title>Conclusions</title>
			<p>The present study found a high prevalence of the use of prognostic-modifying drugs in HFrEF; however, the use of target or maximum tolerated doses fell short of guideline recommendations. Chagas etiology, CKD, advanced age, arterial hypotension, and concomitant use of furosemide were associated with a reduced likelihood of receiving prognostic-modifying drugs in HFrEF, whereas the presence of diabetes was associated with a greater chance of OMT use.</p>
		</sec>
	</body>
	<back>
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		<fn-group>
			<fn fn-type="other">
				<label>Study Association:</label>
				<p> This article is part of the thesis of master submitted by Anderson Oliveira Estevan, from Universidade Federal de Goiás (UFG).</p>
			</fn>
			<fn fn-type="other">
				<label>Ethics Approval and Consent to Participate:</label>
				<p> This article does not contain any studies with human participants or animals performed by any of the authors.</p>
			</fn>
			<fn fn-type="financial-disclosure">
				<label>Sources of Funding:</label>
				<p> There were no external funding sources for this study.</p>
			</fn>
		</fn-group>
	</back>
	<sub-article article-type="translation" id="TRpt" xml:lang="pt">
		<front-stub>
			<article-id pub-id-type="doi">10.36660/abchf.20250018</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Artigo Original</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Prevalência e Determinantes Clínicos da Terapia Farmacológica Otimizada na Insuficiência Cardíaca com Fração de Ejeção Reduzida</article-title>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<name>
						<surname>Estevan</surname>
						<given-names>Anderson Oliveira</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>Obtenção de dados</role>
					<role>Análise e interpretação dos dados</role>
					<role>Redação do manuscrito</role>
					<role>Análise estatística</role>
					<role>Revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<xref ref-type="aff" rid="aff1002"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<name>
						<surname>Silva</surname>
						<given-names>Ana Luísa Guedes de Franca e</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>Obtenção de dados</role>
					<role>Análise e interpretação dos dados</role>
					<role>Redação do manuscrito</role>
					<xref ref-type="aff" rid="aff1002"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0009-0001-2444-754X</contrib-id>
					<name>
						<surname>Rassi</surname>
						<given-names>Salvador</given-names>
						<suffix>Filho</suffix>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>Obtenção de dados</role>
					<role>Análise e interpretação dos dados</role>
					<role>Redação do manuscrito</role>
					<xref ref-type="aff" rid="aff1002"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0003-3778-7153</contrib-id>
					<name>
						<surname>Freitas</surname>
						<given-names>Aguinaldo Figueiredo de</given-names>
						<suffix>Júnior</suffix>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>Obtenção de dados</role>
					<role>Análise e interpretação dos dados</role>
					<role>Redação do manuscrito</role>
					<role>Análise estatística</role>
					<role>Revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<xref ref-type="aff" rid="aff1002"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<contrib-id contrib-id-type="orcid">0000-0001-7210-6486</contrib-id>
					<name>
						<surname>Rassi</surname>
						<given-names>Salvador</given-names>
					</name>
					<role>Concepção e desenho da pesquisa</role>
					<role>Obtenção de dados</role>
					<role>Análise e interpretação dos dados</role>
					<role>Redação do manuscrito</role>
					<role>Análise estatística</role>
					<role>Revisão crítica do manuscrito quanto ao conteúdo intelectual importante</role>
					<xref ref-type="aff" rid="aff1002"><sup>1</sup></xref>
				</contrib>
			</contrib-group>
			<aff id="aff1002">
				<label>1</label>
				<country country="BR">Brasil</country>
				<institution content-type="original">Universidade Federal de Goiás, Goiania, GO – Brasil</institution>
			</aff>
			<author-notes>
				<corresp id="c01002">
					<label>Correspondência:</label> Anderson Oliveira Estevan Universidade Federal de Goiás – Cardiologia - R. 235, s/n. CEP 74605-220, Setor Leste, Universitário Goiânia, GO - Brasil E-mail: estevan.anderson@hotmail.com </corresp>
				<fn fn-type="edited-by">
					<label>Editor responsável pela revisão:</label>
					<p>Germano Souza</p>
				</fn>
				<fn fn-type="coi-statement">
					<label>Potencial Conflito de Interesse:</label>
					<p> Declaro não haver conflito de interesses pertinentes.</p>
				</fn>
			</author-notes>
			<abstract>
				<title>Resumo</title>
				<sec>
					<title>Fundamento</title>
					<p> Na insuficiência cardíaca com fração de ejeção reduzida (ICFEr), o tratamento medicamentoso otimizado (TMO) com betabloqueador, inibidores da enzima conversora de angiotensina (IECA), bloqueadores dos receptores de angiotensina II (BRA) (ou sacubitril/valsartana), espironolactona e inibidores do co-transportador de sódio-glicose 2 (iSGLT2) em dose-alvo ou máxima tolerada reduz morbimortalidade. Contudo, dados reais mostram sua subutilização.</p>
				</sec>
				<sec>
					<title>Objetivo</title>
					<p> Estimar a prevalência e associações clínicas que interfiram na utilização do TMO na prática clínica.</p>
				</sec>
				<sec>
					<title>Método</title>
					<p> Estudo observacional de corte transversal com pacientes ambulatoriais com ICFEr atendidos em hospital terciário. Fatores clínicos associados ao tratamento foram avaliados por regressão logística binária (intervalo de confiança de 95%).</p>
				</sec>
				<sec>
					<title>Resultados</title>
					<p> Foram analisados 266 pacientes (idade média de 61 anos; 62,4% do sexo masculino), 113 (42,5%) com etiologia chagásica. Fração de ejeção média foi 34,2%. Vasodilatadores, betabloqueadores, espironolactona e gliflozinas foram prescritos em 88%, 95,9%, 85,3% e 27,4%, respectivamente. A prevalência de TMO foi de 7,9% (21 pacientes). Diabetes foi associado à maior probabilidade de uso da TMO (p=0,034). Doença de Chagas foi associada a menor probabilidade de receber vasodilatadores (p=0,015) e maior uso de furosemida, amiodarona e digoxina (p&lt;0,005). Doença renal crônica (DRC), idade maior que 60 anos, pressão arterial menor que 100mmHg e uso de furosemida foram associados a menor uso de vasodilatadores (p=0,003; 0,025, 0,010 e 0,046). DRC foi associada a menor uso de espironolactona (p=0,002). Diabetes (p=0,002) e uso de furosemida (0,005) foram associadas ao uso de iSGLT2.</p>
				</sec>
				<sec>
					<title>Conclusão</title>
					<p> Apesar da prevalência elevada da prescrição de drogas modificadoras de doença, o uso do TMO foi significativamente menor que o esperado. DRC, idade avançada, hipotensão arterial e uso concomitante de furosemida foram associados à redução da probabilidade de receber esses fármacos, enquanto diabetes foi associado com maior chance de uso do TMO.</p>
				</sec>
			</abstract>
			<kwd-group xml:lang="pt">
				<title>Palavras-chave:</title>
				<kwd>Insuficiência Cardíaca</kwd>
				<kwd>Insuficiência Cardíaca Sistólica</kwd>
				<kwd>Tratamento Farmacológico</kwd>
			</kwd-group>
		</front-stub>
		<body>
			<p>
					<fig id="f01002">
						<label>Figura Central:</label>
						<caption>
							<title>Prevalência e Determinantes Clínicos da Terapia Farmacológica Otimizada na Insuficiência Cardíaca com Fração de Ejeção Reduzida</title>
						</caption>
						<graphic xlink:href="2764-3107-abchf-5-4-e20250018-gf01-pt.tif"/>
						<attrib>IECA: inibidores da enzima conversora de angiotensina; BRA: bloqueadores dos receptores de angiotensina II; ARM: antagonistas dos receptores mineralocorticoides; INRA: inibidores do receptor de angiotensina–neprilisina; iSGLT2: inibidores do cotransportador sódio–glicose tipo 2; DRC: doença renal crônica. Fonte: os autores.</attrib>
					</fig>
				</p>
			<sec sec-type="intro">
				<title>Introdução</title>
				<p>A insuficiência cardíaca (IC) representa um desafio significativo para a saúde pública global, demandando abordagens terapêuticas eficazes para melhorar a qualidade de vida e a sobrevida dos pacientes.<sup><xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B2">2</xref></sup> Nas últimas décadas, houve um avanço substancial na compreensão da fisiopatologia da IC com fração de ejeção reduzida (ICFEr), o que levou ao desenvolvimento de tratamentos farmacológicos capazes de modificar o prognóstico da doença.<sup><xref ref-type="bibr" rid="B3">3</xref>-<xref ref-type="bibr" rid="B5">5</xref></sup></p>
				<p>Inicialmente, o manejo da ICFEr foi guiado por estratégias hemodinâmicas focadas em sintomas, com uso de diuréticos, digitálicos e vasodilatadores. No entanto, essa abordagem mostrou-se insuficiente para alterar a progressão da doença. Com melhor entendimento da fisiopatologia da IC, a modulação do sistema neuro-hormonal passou a ser o foco do tratamento.<sup><xref ref-type="bibr" rid="B4">4</xref>,<xref ref-type="bibr" rid="B5">5</xref></sup> Inibidores da enzima conversora de angiotensina (IECA) e bloqueadores dos receptores de angiotensina II (BRA) representaram um marco no tratamento da ICFEr, com redução na morbimortalidade da doença.<sup><xref ref-type="bibr" rid="B6">6</xref></sup> Posteriormente, antagonistas dos receptores mineralocorticoides (ARM) e betabloqueadores (BB) foram incorporados ao tratamento, consolidando a “terapia tripla” como a base do tratamento para ICFEr.<sup><xref ref-type="bibr" rid="B7">7</xref></sup> Recentemente, os inibidores da neprilisina e dos receptores de angiotensina (INRA), bem como os Inibidores do co-Transportador de Sódio-Glicose 2 (iSGLT2), tiveram sua eficácia demonstrada em ensaios clínicos, sendo incorporados ao arsenal terapêutico na ICFEr.<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B9">9</xref></sup></p>
				<p>O uso dessas drogas modificou o tratamento da ICFEr, proporcionando melhorias significativas na qualidade de vida e sobrevida. O uso da terapia quádrupla, nas doses-alvo recomendadas ou na dose máxima tolerada pelo paciente, convencionou-se como tratamento medicamentoso otimizado (TMO) para ICFEr.<sup><xref ref-type="bibr" rid="B10">10</xref>-<xref ref-type="bibr" rid="B12">12</xref></sup> Apesar das evidências clínicas e das diretrizes estabelecidas, persiste uma lacuna significativa entre as recomendações da literatura e a implementação do TMO na prática clínica, refletindo desafios multifatoriais.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
				<p>O objetivo deste estudo foi estimar a prevalência de prescrição do TMO em uma população de pacientes com ICFEr, de acordo com as diretrizes atuais, bem como identificar possíveis fatores clínicos que possam interferir no uso das classes farmacológicas recomendadas e de suas respectivas doses. Compreender a aplicação da TMO em pacientes de mundo real contribui para identificar barreiras e promover estratégias para melhorar o tratamento e consequentemente o prognóstico da ICFEr.</p>
			</sec>
			<sec sec-type="methods">
				<title>Métodos</title>
				<sec>
					<title>Coleta de dados</title>
					<p>Os dados foram coletados em um período de 12 meses. O estudo foi aprovado pelo Comitê de Ética em Pesquisa institucional (CEP) em 28/03/2022, sob o número 5.315.449. O CEP concedeu dispensa do Termo de consentimento livre e esclarecido, conforme previsto pela Resolução n° 466/2012. As informações foram coletadas, por meio de questionário estruturado, a partir do registro da consulta de rotina dos pacientes atendidos no ambulatório de IC de um hospital universitário terciário.</p>
					<p>O estudo incluiu adultos de ambos os sexos com idade igual ou superior a 18 anos com diagnóstico de IC com fração de ejeção do ventrículo esquerdo (FEVE) reduzida (≤ 40%). Foram incluídos pacientes com pelo menos duas visitas ao ambulatório de cardiologia. Os critérios de exclusão foram: cuidados paliativos (IC terminal), hemodiálise, transplante cardíaco e internação nos três meses anteriores à consulta, uma vez que tais condições poderiam alterar a prescrição da terapia farmacológica da IC.</p>
				</sec>
				<sec>
					<title>Variáveis e definições</title>
					<p>O questionário de avaliação de dados incluiu variáveis demográficas (sexo, idade e raça), história da IC (etiologia e fração de ejeção), variáveis clínicas (classe funcional, pressão arterial e frequência cardíaca), variáveis laboratoriais (taxa de filtração glomerular, glicemia e eletrólitos) e comorbidades. A FEVE foi aferida pelo método de Simpson, com base no último ecocardiograma.</p>
					<p>A terapia quádrupla foi definida como uso concomitante de IECA/BRA/INRA associado a betabloqueador, antagonista de receptor mineralocorticoide e iSGLT2. O TMO foi definido como uso concomitante da terapia quádrupla em dose-alvo ou na máxima dose tolerada, de acordo com a última Atualização de Tópicos Emergentes da Diretriz Brasileira de Insuficiência Cardíaca – 2021.<sup><xref ref-type="bibr" rid="B15">15</xref></sup>A dose máxima tolerada foi definida pela presença de tentativa anterior de progressão de dose sem sucesso e pela presença de hipotensão (menos de 100 mmHg) e/ou frequência cardíaca (FC) menor que 60 bpm. A titulação da dose foi avaliada comparando-se de forma evolutiva as prescrições dos últimos 12 meses.</p>
				</sec>
				<sec>
					<title>Análise estatística</title>
					<p>O banco de dados foi tabulado no EPIDATA® versão 3.0, com dupla digitação e posterior checagem para minimizar erros de digitação. As análises foram conduzidas utilizando o software IBM SPSS (<italic>Statistical Package for Social Science</italic>) versão 26.0 (IBM Corp., Armonk, NY, EUA), considerando um nível de significância de 5% (p &lt; 0,05). Para a comparação das variáveis categóricas entre os grupos, utilizou-se o teste do qui-quadrado de Pearson, enquanto as variáveis contínuas foram analisadas pelo teste t de Student para amostras independentes. Os resultados foram expressos em média e desvio-padrão para variáveis contínuas e em frequência absoluta e relativa para variáveis categóricas.<sup><xref ref-type="bibr" rid="B16">16</xref></sup></p>
					<p>O perfil sociodemográfico, as etiologias, o perfil clínico e de medicamentos foram testados em cinco modelos distintos (uso do TMO, vasodilatadores, betabloqueadores, antagonista mineralocorticoides e iSGLT2). Cada modelo foi composto de duas etapas. Primeiramente, foi realizada uma regressão logística univariada para avaliar a associação entre cada possível variável preditora e a variável resposta de cada modelo. As variáveis que apresentaram valor de p &lt; 0,20 na primeira etapa foram incluídas na análise de regressão logística multivariada (segunda etapa). Os resultados foram apresentados em termos de estatística de Wald, coeficiente de determinação pseudo-R<sup>2</sup>, odds ratio (OR) com IC 95% e valores de p.</p>
				</sec>
			</sec>
			<sec sec-type="results">
				<title>Resultados</title>
				<p>Foram avaliados dados de 524 pacientes atendidos no período do estudo. Após aplicação dos critérios de inclusão e exclusão, a amostra final foi de 266 pacientes com ICFEr.</p>
				<sec>
					<title>Características da amostra</title>
					<p>A caracterização da amostra total e conforme o TMO é apresentada na <xref ref-type="table" rid="t1002">Tabela 1</xref>. A idade média dos pacientes foi de 61,33 ± 13,24 anos, sem diferença significativa entre os grupos (p = 0,583). A maioria dos participantes era do sexo masculino (62,4%), sem diferenças entre os grupos com e sem TMO (p = 0,174). A FEVE foi significativamente menor nos pacientes que receberam TMO (29,57 ± 8,94%) em comparação aos que não receberam essa abordagem (34,64 ± 10,68%; p = 0,049). A FC, similarmente, foi significativamente menor no grupo com TMO (62,05 ± 8,15 bpm vs. 68,26 ± 12,41 bpm; p = 0,045).</p>
					<p>
						<table-wrap id="t1002">
							<label>Tabela 1</label>
							<caption>
								<title>– Caracterização do perfil epidemiológico e comorbidades na amostra total e de acordo com o tratamento médico otimizado (n = 266)</title>
							</caption>
							<table frame="hsides" rules="groups">
								<colgroup>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
								</colgroup>
								<thead>
									<tr>
										<th align="left" style="font-weight:normal"> </th>
										<th colspan="4">TMO</th>
									</tr>
									<tr>
										<th align="left" style="font-weight:normal"> </th>
										<th>Total</th>
										<th>Não</th>
										<th>Sim</th>
										<th>p</th>
									</tr>
								</thead>
								<tbody>
									<tr>
										<td><bold>Idade – anos (M ± DP)</bold></td>
										<td align="center">61,33 ± 13,24</td>
										<td align="center">61,20 ± 13,45</td>
										<td align="center">62,86 ± 10,77</td>
										<td align="center">0,583</td>
									</tr>
									<tr>
										<td><bold>Sexo n (%)</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>Feminino</td>
										<td align="center">100 (37,6)</td>
										<td align="center">95 (38,8)</td>
										<td align="center">5 (23,8)</td>
										<td align="center">0,174</td>
									</tr>
									<tr>
										<td>Masculino</td>
										<td align="center">166 (62,4)</td>
										<td align="center">150 (61,2)</td>
										<td align="center">16 (76,2)</td>
										<td> </td>
									</tr>
									<tr>
										<td><bold>Raça n (%)</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>Amarela</td>
										<td align="center">3 (1,1)</td>
										<td align="center">3 (1,2)</td>
										<td align="center">0 (0,0)</td>
										<td> </td>
									</tr>
									<tr>
										<td>Branca</td>
										<td align="center">78 (29,3)</td>
										<td align="center">73 (29,8)</td>
										<td align="center">5 (23,8)</td>
										<td align="center">0,334</td>
									</tr>
									<tr>
										<td>Parda</td>
										<td align="center">162 (60,9)</td>
										<td align="center">150 (61,2)</td>
										<td align="center">12 (57,1)</td>
										<td> </td>
									</tr>
									<tr>
										<td>Preta</td>
										<td align="center">23 (8,6)</td>
										<td align="center">19 (7,8)</td>
										<td align="center">4 (19,0)</td>
										<td> </td>
									</tr>
									<tr>
										<td><bold>Etiologia da IC n (%)</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>Chagas</td>
										<td align="center">113 (42,5)</td>
										<td align="center">104 (42,4)</td>
										<td align="center">9 (42,9)</td>
										<td> </td>
									</tr>
									<tr>
										<td>Idiopática</td>
										<td align="center">56 (21,1)</td>
										<td align="center">52 (21,2)</td>
										<td align="center">4 (19,0)</td>
										<td align="center">0,962</td>
									</tr>
									<tr>
										<td>Isquêmica</td>
										<td align="center">44 (16,5)</td>
										<td align="center">41 (16,7)</td>
										<td align="center">3 (14,3)</td>
										<td> </td>
									</tr>
									<tr>
										<td>Outras</td>
										<td align="center">53 (19,9)</td>
										<td align="center">48 (19,6)</td>
										<td align="center">5 (23,8)</td>
										<td> </td>
									</tr>
									<tr>
										<td>PAS (mmHg) média ± DP</td>
										<td align="center">111,91 ± 19,53</td>
										<td align="center">112,43 ± 19,33</td>
										<td align="center">105,81 ± 21,25</td>
										<td align="center">0,136</td>
									</tr>
									<tr>
										<td>Fração de ejeção (%)</td>
										<td align="center">34,54 ± 10,63</td>
										<td align="center">34,64 ± 10,68</td>
										<td align="center">29,57 ± 8,94</td>
										<td align="center">0,049</td>
									</tr>
									<tr>
										<td>Frequência cardíaca (bpm)</td>
										<td align="center">67,77 ± 12,23</td>
										<td align="center">68,26 ± 12,41</td>
										<td align="center">62,05 ± 8,15</td>
										<td align="center">0,045</td>
									</tr>
									<tr>
										<td><bold>NYHA</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>I</td>
										<td align="center">111 (41,7)</td>
										<td align="center">105 (42,9)</td>
										<td align="center">6 (28,6)</td>
										<td> </td>
									</tr>
									<tr>
										<td>II</td>
										<td align="center">108 (40,6)</td>
										<td align="center">95 (38,8)</td>
										<td align="center">13 (61,9)</td>
										<td> </td>
									</tr>
									<tr>
										<td>III</td>
										<td align="center">40 (15,0)</td>
										<td align="center">38 (15,5)</td>
										<td align="center">2 (9,5)</td>
										<td> </td>
									</tr>
									<tr>
										<td>IV</td>
										<td align="center">7 (2,6)</td>
										<td align="center">7 (2,9)</td>
										<td align="center">0 (0,0)</td>
										<td> </td>
									</tr>
									<tr>
										<td><bold>Uso de dispositivos n (%)</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>Não</td>
										<td align="center">189 (71,1)</td>
										<td align="center">175 (71,4)</td>
										<td align="center">14 (66,7)</td>
										<td align="center">0,644</td>
									</tr>
									<tr>
										<td>Sim</td>
										<td align="center">77 (28,9)</td>
										<td align="center">70 (28,6)</td>
										<td align="center">7 (33,3)</td>
										<td> </td>
									</tr>
									<tr>
										<td><bold>Comorbidades n (%)</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td>HAS</td>
										<td align="center">135 (50,8)</td>
										<td align="center">128 (52,2)</td>
										<td align="center">7 (33,3)</td>
										<td align="center">0,096</td>
									</tr>
									<tr>
										<td>DLP</td>
										<td align="center">76 (28,6)</td>
										<td align="center">69 (28,2)</td>
										<td align="center">7 (33,3)</td>
										<td align="center">0,612</td>
									</tr>
									<tr>
										<td>Fibrilação atrial</td>
										<td align="center">54 (20,3)</td>
										<td align="center">48 (19,6)</td>
										<td align="center">6 (28,6)</td>
										<td align="center">0,326</td>
									</tr>
									<tr>
										<td>TV/FV</td>
										<td align="center">35 (13,2)</td>
										<td align="center">33 (13,5)</td>
										<td align="center">2 (9,5)</td>
										<td align="center">0,605</td>
									</tr>
									<tr>
										<td>DAOP</td>
										<td align="center">9 (3,4)</td>
										<td align="center">8 (3,3)</td>
										<td align="center">1 (4,8)</td>
										<td align="center">0,716</td>
									</tr>
									<tr>
										<td>Depressão</td>
										<td align="center">6 (2,3)</td>
										<td align="center">6 (2,4)</td>
										<td align="center">0 (0,0)</td>
										<td align="center">0,468</td>
									</tr>
									<tr>
										<td>Hipotireoidismo</td>
										<td align="center">61 (22,9)</td>
										<td align="center">55 (22,4)</td>
										<td align="center">6 (28,6)</td>
										<td align="center">0,522</td>
									</tr>
									<tr>
										<td>DM</td>
										<td align="center">58 (21,8)</td>
										<td align="center">50 (20,4)</td>
										<td align="center">8 (38,1)</td>
										<td align="center">0,064</td>
									</tr>
									<tr>
										<td>IAM</td>
										<td align="center">32 (12,0)</td>
										<td align="center">29 (11,8)</td>
										<td align="center">3 (14,3)</td>
										<td align="center">0,741</td>
									</tr>
									<tr>
										<td>DRC</td>
										<td align="center">45 (16,9)</td>
										<td align="center">39 (15,9)</td>
										<td align="center">6 (28,6)</td>
										<td align="center">0,138</td>
									</tr>
									<tr>
										<td>AVC</td>
										<td align="center">20 (7,5)</td>
										<td align="center">19 (7,8)</td>
										<td align="center">1 (4,8)</td>
										<td align="center">0,618</td>
									</tr>
									<tr>
										<td>Anemia</td>
										<td align="center">37 (13,9)</td>
										<td align="center">34 (13,9)</td>
										<td align="center">3 (14,3)</td>
										<td align="center">0,959</td>
									</tr>
									<tr>
										<td>DPOC</td>
										<td align="center">26 (9,8)</td>
										<td align="center">25 (10,2)</td>
										<td align="center">1 (4,8)</td>
										<td align="center">0,420</td>
									</tr>
									<tr>
										<td>Tabagismo</td>
										<td align="center">17 (6,4)</td>
										<td align="center">17 (6,9)</td>
										<td align="center">0 (0,0)</td>
										<td align="center">0,212</td>
									</tr>
									<tr>
										<td>Ex-tabagista</td>
										<td align="center">72 (27,1)</td>
										<td align="center">66 (26,9)</td>
										<td align="center">6 (28,6)</td>
										<td align="center">0,876</td>
									</tr>
								</tbody>
							</table>
							<table-wrap-foot>
								<fn id="TFN1002">
									<p>*Qui-quadrado de Pearson; **Teste t de Student; n: frequência absoluta; %: frequência relativa; AVC: acidente vascular cerebral; DAOP: doença arterial obstrutiva periférica; DLP: dislipidemia; DM: diabetes mellitus; DPOC: doença pulmonar obstrutiva crônica; DRC: doença renal crônica; FC: frequência cardíaca; HAS: hipertensão arterial sistêmica; IAM: infarto agudo do miocárdio; M: média; NYHA: New York Heart Association; PAS: pressão arterial sistólica; DP: desvio padrão; TMO: tratamento medicamentoso otimizado; TV/FV: taquicardia ventricular / fibrilação ventricular.</p>
								</fn>
							</table-wrap-foot>
						</table-wrap>
					</p>
					<p>As demais variáveis, incluindo hipertensão arterial, diabetes mellitus, Doença Renal Crônica (DRC), e outras comorbidades, não apresentaram diferenças estatisticamente significativas entre os grupos (<xref ref-type="table" rid="t1002">Tabela 1</xref>). A etiologia da IC mais prevalente nesta população foi a doença de Chagas, representando 42,5% (113) da amostra, seguida pela cardiomiopatia dilatada idiopática (21%) e pela etiologia isquêmica (16,5%).</p>
				</sec>
				<sec>
					<title>Prevalência do TMO e das classes de medicamentos</title>
					<p>A prevalência do uso concomitante de IECA/BRA/INRA, betabloqueadores, ARM e iSGLT2 (terapia quádrupla) foi de 20,3% (54 pacientes). A prevalência do TMO, definida como a utilização de terapia quádrupla em dose-alvo ou máxima tolerada (conforme <xref ref-type="fig" rid="f01002">Figura central</xref>), foi de 7,9% (21 pacientes). Vasodilatadores, betabloqueadores, espironolactona e gliflozinas foram prescritos em 88%, 95,9%, 85,3% e 27,4%, respectivamente.</p>
					<p>Dos 116 pacientes em uso de IECA, 96,5% (112) receberam enalapril, seguido de 2,6% (3) de captopril e 0,9% (1) de ramipril. Entre os usuários de BRA, 97,0% (64) estavam em uso de losartana e 3,0% (2) em uso de valsartana. 12,0% (32) apresentavam registro de contraindicação a algum vasodilatador (disfunção renal seguida ou hipotensão). Em relação aos betabloqueadores, carvedilol, metoprolol e bisoprolol foram utilizados por 52,6% (134), 18,4% (47) e 29% (74) dos pacientes, respectivamente. 2,3% (6) possuíam registro de contraindicação ao uso dos betabloqueadores (asma grave ou bradicardia).</p>
					<p>A espironolactona foi o ARM utilizado e a dapagliflozina, o iSGLT2. O uso de ARM foi contraindicado em 5,3% (14), sendo as principais causas disfunção renal e hipercalemia. Quanto ao iSGLT2, 0,4% (1) possuía relato de contraindicação ao uso de iSGLT2 descrito como “intolerância”.</p>
				</sec>
				<sec>
					<title>Avaliação das doses</title>
					<p>A <xref ref-type="fig" rid="f02002">Figura 1</xref> mostra a distribuição para cada classe de medicamentos de acordo com o percentil da dose-alvo. Observou-se que a classe dos betabloqueadores apresentou a menor proporção de pacientes com doses acima de 50% da dose-alvo, conforme visto no item C da <xref ref-type="fig" rid="f02002">Figura 1</xref>.</p>
					<p>
						<fig id="f02002">
							<label>Figura 1</label>
							<caption>
								<title>– Percentil da dose-alvo no tratamento farmacológico de pacientes com insuficiência cardíaca com fração de ejeção reduzida (ICFEr); IECA: inibidor da enzima conversora de angiotensina; BRA: bloqueador do receptor de angiotensina II; INRA: inibidor da neprilisina e do receptor da angiotensina.</title>
							</caption>
							<graphic xlink:href="2764-3107-abchf-5-4-e20250018-gf02-pt.tif"/>
						</fig>
					</p>
				</sec>
				<sec>
					<title>Etiologia e tratamento farmacológico</title>
					<p>A análise de regressão logística entre as etiologias da IC e o tratamento medicamentoso revelou que pacientes com doença de Chagas tiveram 61% menos chances de receber vasodilatadores (OR = 0,39; IC 95% = 0,18 - 0,85; p = 0,015). Em contrapartida, esses pacientes tiveram maior probabilidade de prescrição de furosemida (OR = 2,40; IC 95% = 1,39 - 4,11; p = 0,001), amiodarona (OR = 4,98; IC 95% = 2,89 - 8,59; p &lt; 0,001) e digoxina (OR = 3,75; IC 95% = 1,40 - 9,98; p = 0,005). A <xref ref-type="table" rid="t2002">Tabela 2</xref> mostra as associações encontradas. Não houve diferença significativa entre o uso dos medicamentos para IC e as demais etiologias analisadas.</p>
					<p>
						<table-wrap id="t2002">
							<label>Tabela 2</label>
							<caption>
								<title>– Resultado da associação entre doença de Chagas e tratamento farmacológico da insuficiência cardíaca com fração de ejeção reduzida (n = 266)</title>
							</caption>
							<table frame="hsides" rules="groups">
								<colgroup>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
								</colgroup>
								<thead>
									<tr>
										<th align="left" style="font-weight:normal"> </th>
										<th colspan="2">Chagas n (%)</th>
										<th rowspan="2">OR (IC 95%)</th>
										<th rowspan="2">p</th>
									</tr>
									<tr>
										<th align="left">Tratamento</th>
										<th>Não</th>
										<th>Sim</th>
									</tr>
								</thead>
								<tbody>
									<tr>
										<td>Terapia quádrupla</td>
										<td align="center">33 (21,6)</td>
										<td align="center">21 (18,6)</td>
										<td align="center">0,83 (0,45–1,52)</td>
										<td align="center">0,550</td>
									</tr>
									<tr>
										<td>TMO</td>
										<td align="center">12 (7,8)</td>
										<td align="center">9 (8,0)</td>
										<td align="center">1,01 (0,41–2,50)</td>
										<td align="center">0,971</td>
									</tr>
									<tr>
										<td>Betabloqueadores</td>
										<td align="center">149 (97,4)</td>
										<td align="center">106 (93,8)</td>
										<td align="center">0,40 (0,11–1,42)</td>
										<td align="center">0,147</td>
									</tr>
									<tr>
										<td>Vasodilatadores</td>
										<td align="center">141 (92,2)</td>
										<td align="center">93 (82,3)</td>
										<td align="center">0,39 (0,18–0,85)</td>
										<td align="center">0,015</td>
									</tr>
									<tr>
										<td>Espironolactona</td>
										<td align="center">129 (84,3)</td>
										<td align="center">98 (86,7)</td>
										<td align="center">1,21 (0,60–2,63)</td>
										<td align="center">0,581</td>
									</tr>
									<tr>
										<td>ISGLT2</td>
										<td align="center">40 (26,1)</td>
										<td align="center">33 (29,2)</td>
										<td align="center">1,65 (0,68–2,00)</td>
										<td align="center">0,580</td>
									</tr>
									<tr>
										<td>IECA</td>
										<td align="center">73 (47,7)</td>
										<td align="center">43 (38,1)</td>
										<td align="center">0,67 (0,41–1,14)</td>
										<td align="center">0,116</td>
									</tr>
									<tr>
										<td>BRA</td>
										<td align="center">43 (28,1)</td>
										<td align="center">23 (20,4)</td>
										<td align="center">0,65 (0,36–1,16)</td>
										<td align="center">0,148</td>
									</tr>
									<tr>
										<td>INRA</td>
										<td align="center">25 (16,3)</td>
										<td align="center">27 (23,9)</td>
										<td align="center">1,60 (0,87–2,96)</td>
										<td align="center">0,125</td>
									</tr>
									<tr>
										<td>Ivabradina</td>
										<td align="center">13 (8,5)</td>
										<td align="center">4 (3,5)</td>
										<td align="center">0,39 (0,12–1,24)</td>
										<td align="center">0,102</td>
									</tr>
									<tr>
										<td>Furosemida</td>
										<td align="center">89 (58,2)</td>
										<td align="center">87 (77,0)</td>
										<td align="center">2,40 (1,39–4,11)</td>
										<td align="center">0,001</td>
									</tr>
									<tr>
										<td>Amiodarona</td>
										<td align="center">30 (19,6)</td>
										<td align="center">62 (54,9)</td>
										<td align="center">4,98 (2,89–8,59)</td>
										<td align="center">&lt;0,001</td>
									</tr>
									<tr>
										<td>Digoxina</td>
										<td align="center">6 (3,9)</td>
										<td align="center">15 (13,3)</td>
										<td align="center">3,75 (1,40–9,98)</td>
										<td align="center">0,005</td>
									</tr>
								</tbody>
							</table>
							<table-wrap-foot>
								<fn id="TFN2002">
									<p>*Regressão logística; n: frequência absoluta; %: frequência relativa; BRA: bloqueadores dos receptores de angiotensina II; IECA: inibidores da enzima conversora de angiotensina; INRA: inibidores do receptor de angiotensina–neprilisina; iSGLT2: inibidores do cotransportador sódio–glicose tipo 2; TMO: tratamento medicamentoso otimizado.</p>
								</fn>
							</table-wrap-foot>
						</table-wrap>
					</p>
				</sec>
				<sec>
					<title>Preditores de uso do TMO e das classes medicamentosas</title>
					<p>A <xref ref-type="table" rid="t3002">Tabela 3</xref> mostra o resultado das análises de regressão logística multivariada em relação ao uso de TMO e das classes medicamentosas. Na análise multivariada para o uso do TMO, diabetes mellitus mostrou-se um preditor significativo, aumentando em 2,82 vezes a chance de uso do TMO (OR = 2,82; IC 95% = 1,07 - 7,24; p = 0,036). Além disso, os pacientes em uso do TMO apresentaram maior probabilidade de apresentar PAS &lt;100mmHg (OR = 2,80; IC 95% = 1,03 - 7,02; p = 0,043).</p>
					<p>
						<table-wrap id="t3002">
							<label>Tabela 3</label>
							<caption>
								<title>– Análises de regressão logística multivariada para o uso do tratamento medicamentoso otimizado e das classes medicamentosas utilizadas na insuficiência cardíaca com fração de ejeção reduzida</title>
							</caption>
							<table frame="hsides" rules="groups">
								<colgroup>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
									<col/>
								</colgroup>
								<thead>
									<tr>
										<th align="left" style="font-weight:normal"> </th>
										<th align="left" style="font-weight:normal"> </th>
										<th>Não</th>
										<th>Sim</th>
										<th>Wald</th>
										<th style="font-weight:normal">r<sup><bold>2</bold></sup></th>
										<th>OR (IC 95%)</th>
										<th>p</th>
									</tr>
								</thead>
								<tbody>
									<tr>
										<td><bold>TMO</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Sexo masculino</td>
										<td align="center">150 (61,2)</td>
										<td align="center">16 (76,2)</td>
										<td align="center">1,42</td>
										<td align="center" rowspan="4">0,08</td>
										<td align="center">1,91 (0,66–5,54)</td>
										<td align="center">0,231</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DRC</td>
										<td align="center">39 (15,9)</td>
										<td align="center">6 (28,6)</td>
										<td align="center">1,02</td>
										<td align="center">1,71 (0,60–4,86)</td>
										<td align="center">0,312</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DM</td>
										<td align="center">50 (20,4)</td>
										<td align="center">8 (38,1)</td>
										<td align="center">4,42</td>
										<td align="center">2,82 (1,07–7,24)</td>
										<td align="center">0,036</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">PAS &lt;100</td>
										<td align="center">43 (17,6)</td>
										<td align="center">7 (33,3)</td>
										<td align="center">4,08</td>
										<td align="center">2,80 (1,03–7,02)</td>
										<td align="center">0,043</td>
									</tr>
									<tr>
										<td><bold>Betabloqueadores</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">AVC</td>
										<td align="center">2 (18,2)</td>
										<td align="center">18 (7,1)</td>
										<td align="center">0,91</td>
										<td align="center" rowspan="4">0,06</td>
										<td align="center">0,44 (0,08–2,37)</td>
										<td align="center">0,341</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Fibrilação atrial</td>
										<td align="center">4 (36,4)</td>
										<td align="center">50 (19,6)</td>
										<td align="center">0,48</td>
										<td align="center">0,63 (0,17–2,34)</td>
										<td align="center">0,490</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Chagas</td>
										<td align="center">7 (63,6)</td>
										<td align="center">106 (41,6)</td>
										<td align="center">0,25</td>
										<td align="center">0,71 (0,18–2,79)</td>
										<td align="center">0,618</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Amiodarona</td>
										<td align="center">7 (63,6)</td>
										<td align="center">85 (33,3)</td>
										<td align="center">2,17</td>
										<td align="center">0,36 (0,09–1,40)</td>
										<td align="center">0,140</td>
									</tr>
									<tr>
										<td><bold>Vasodilatadores</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Faixa etária &gt;60</td>
										<td align="center">26 (81,3)</td>
										<td align="center">129 (55,1)</td>
										<td align="center">5,05</td>
										<td align="center" rowspan="9">0,20</td>
										<td align="center">0,32 (0,12–0,87)</td>
										<td align="center">0,025</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DRC</td>
										<td align="center">14 (43,8)</td>
										<td align="center">31 (13,2)</td>
										<td align="center">8,75</td>
										<td align="center">0,28 (0,12–0,65)</td>
										<td align="center">0,003</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">AVC</td>
										<td align="center">7 (21,9)</td>
										<td align="center">13 (5,6)</td>
										<td align="center">2,57</td>
										<td align="center">0,39 (0,13–1,23)</td>
										<td align="center">0,109</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">TV/FV</td>
										<td align="center">10 (31,3)</td>
										<td align="center">25 (10,7)</td>
										<td align="center">1,10</td>
										<td align="center">0,56 (0,19–1,65)</td>
										<td align="center">0,294</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Chagas</td>
										<td align="center">20 (62,5)</td>
										<td align="center">93 (39,7)</td>
										<td align="center">0,87</td>
										<td align="center">1,61 (0,59–4,35)</td>
										<td align="center">0,352</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Idiopática</td>
										<td align="center">2 (6,3)</td>
										<td align="center">54 (23,1)</td>
										<td align="center">1,89</td>
										<td align="center">3,10 (0,62–15,60)</td>
										<td align="center">0,169</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">PAS &lt;100</td>
										<td align="center">12 (37,5)</td>
										<td align="center">38 (16,2)</td>
										<td align="center">6,61</td>
										<td align="center">0,32 (0,14–0,76)</td>
										<td align="center">0,010</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Furosemida</td>
										<td align="center">27 (84,4)</td>
										<td align="center">149 (63,7)</td>
										<td align="center">3,97</td>
										<td align="center">0,35 (0,12–0,98)</td>
										<td align="center">0,046</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Amiodarona</td>
										<td align="center">19 (59,4)</td>
										<td align="center">73 (31,2)</td>
										<td align="center">1,26</td>
										<td align="center">0,58 (0,22–1,51)</td>
										<td align="center">0,262</td>
									</tr>
									<tr>
										<td><bold>Espironolactona</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td align="center" rowspan="7">0,15</td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Faixa etária &gt;60</td>
										<td align="center">27 (69,2)</td>
										<td align="center">128 (56,4)</td>
										<td align="center">0,24</td>
										<td align="center">0,82 (0,37–1,82)</td>
										<td align="center">0,621</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DRC</td>
										<td align="center">12 (30,8)</td>
										<td align="center">33 (14,5)</td>
										<td align="center">9,34</td>
										<td align="center">0,26 (0,11–0,62)</td>
										<td align="center">0,002</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DAOP</td>
										<td align="center">3 (7,7)</td>
										<td align="center">6 (2,6)</td>
										<td align="center">1,89</td>
										<td align="center">0,34 (0,07–1,58)</td>
										<td align="center">0,169</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">PAS &lt;100</td>
										<td align="center">2 (5,1)</td>
										<td align="center">48 (21,1)</td>
										<td align="center">4,74</td>
										<td align="center">5,27 (1,18–23,53)</td>
										<td align="center">0,029</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">FC</td>
										<td align="center">13 (33,3)</td>
										<td align="center">38 (16,7)</td>
										<td align="center">3,89</td>
										<td align="center">0,43 (0,19–1,00)</td>
										<td align="center">0,049</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Furosemida</td>
										<td align="center">16 (41,0)</td>
										<td align="center">160 (70,5)</td>
										<td align="center">12,87</td>
										<td align="center">3,90 (1,85–8,20)</td>
										<td align="center">&lt;0,001</td>
									</tr>
									<tr>
										<td><bold>ISGLT2</bold></td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
										<td> </td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Faixa etária &gt;60</td>
										<td align="center">107 (55,4)</td>
										<td align="center">48 (65,8)</td>
										<td align="center">0,33</td>
										<td align="center" rowspan="8">0,09</td>
										<td align="center">1,20 (0,65–2,22)</td>
										<td align="center">0,567</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DM</td>
										<td align="center">32 (16,6)</td>
										<td align="center">26 (35,6)</td>
										<td align="center">9,30</td>
										<td align="center">2,63 (1,41–4,91)</td>
										<td align="center">0,002</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">IAM</td>
										<td align="center">20 (10,4)</td>
										<td align="center">12 (16,4)</td>
										<td align="center">0,03</td>
										<td align="center">0,91 (0,28–2,90)</td>
										<td align="center">0,868</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">DRC</td>
										<td align="center">26 (13,5)</td>
										<td align="center">19 (26,0)</td>
										<td align="center">1,57</td>
										<td align="center">1,60 (0,77–3,35)</td>
										<td align="center">0,210</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">AVC</td>
										<td align="center">10 (5,2)</td>
										<td align="center">10 (13,7)</td>
										<td align="center">1,91</td>
										<td align="center">2,07 (0,74–5,80)</td>
										<td align="center">0,167</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Isquêmica</td>
										<td align="center">27 (14,0)</td>
										<td align="center">17 (23,3)</td>
										<td align="center">1,27</td>
										<td align="center">1,82 (0,64–5,14)</td>
										<td align="center">0,260</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Idiopática</td>
										<td align="center">45 (23,3)</td>
										<td align="center">11 (15,1)</td>
										<td align="center">0,38</td>
										<td align="center">0,78 (0,36–1,72)</td>
										<td align="center">0,540</td>
									</tr>
									<tr>
										<td> </td>
										<td align="center">Furosemida</td>
										<td align="center">117 (60,6)</td>
										<td align="center">59 (80,8)</td>
										<td align="center">8,05</td>
										<td align="center">2,60 (1,34–5,03)</td>
										<td align="center">0,005</td>
									</tr>
								</tbody>
							</table>
							<table-wrap-foot>
								<fn id="TFN3002">
									<p>*Regressão logística; n: frequência absoluta; %: frequência relativa; ARM/TMO: tratamento medicamentoso otimizado; AVC: acidente vascular cerebral; DAOP: doença arterial obstrutiva periférica; DM: diabetes mellitus; DPOC: doença pulmonar obstrutiva crônica; DRC: doença renal crônica; FC: frequência cardíaca; IAM: infarto agudo do miocárdio; iSGLT2: inibidores do cotransportador sódio–glicose tipo 2; PAS: pressão arterial sistólica; TV/FV: taquicardia ventricular / fibrilação ventricular.</p>
								</fn>
							</table-wrap-foot>
						</table-wrap>
					</p>
					<p>No modelo final para uso dos vasodilatadores, a presença de DRC reduziu em 72% a probabilidade de uso desta classe (OR = 0,28; IC 95% = 0,12 - 0,65; p = 0,003). Além disso, PAS &lt; 100 mmHg reduziu em 68% a chance de uso dessa classe medicamentosa (OR = 0,32; IC 95% = 0,14 - 0,76; p = 0,010). Além disso, idade acima de 60 anos (OR = 0.32; IC 0.12 - 0.87; p = 0,025) e uso de furosemida (OR = 0.35; IC 0.12 - 0.98; p = 0,046) foram associados com menor probabilidade de uso dessa classe.</p>
					<p>Nenhuma variável apresentou significância estatística no modelo multivariado em relação ao uso de betabloqueadores.</p>
					<p>Em relação ao uso de espironolactona, a análise multivariada mostrou que pacientes com DRC apresentaram 74% menos chances de receber espironolactona (OR = 0,26; IC 95% = 0,11 - 0,62; p = 0,002). Por outro lado, o uso de furosemida foi fortemente associado ao uso de espironolactona, triplicando a probabilidade de uso dessa medicação (OR = 3,90; IC 95% = 1,85 - 8,20; p &lt; 0,001). A variável uso de furosemida apresentou a maior estatística de Wald (Wald = 12,87), indicando forte associação entre essas duas classes de medicamentos.</p>
					<p>Para os iSGLT2, o modelo final multivariado indicou que a presença de diabetes mellitus aumentou em 2,63 vezes a chance de uso dessa classe (OR = 2,63; IC 95% = 1,41 - 4,91; p = 0,002). O uso de furosemida também foi um fator significativo, com um aumento de 2,60 vezes na probabilidade de prescrição de iSGLT2 (OR = 2,60; IC 95% = 1,34 - 5,03; p = 0,005).</p>
				</sec>
			</sec>
			<sec sec-type="discussion">
				<title>Discussão</title>
				<p>No cenário atual de elevadas taxas de morbidade e mortalidade em pacientes com IC, é crucial aprimorar o tratamento farmacológico para assegurar um prognóstico mais favorável a esses pacientes. Uma melhor compreensão com dados do mundo real dos determinantes da não adoção da terapia farmacológica baseada em evidências tem grande impacto na melhoria do cuidado aos pacientes com IC.<sup><xref ref-type="bibr" rid="B17">17</xref></sup></p>
				<p>O presente estudo encontrou prevalência de 7,9% do uso de TMO. Pacientes do mundo real, com múltiplas comorbidades e peculiaridades, podem representar um desafio no início e na titulação de medicamentos em relação aos ensaios clínicos. Vários fatores podem contribuir para que os pacientes com ICFEr sejam submedicados: fatores relacionados ao profissional, ao paciente e ao sistema de saúde. A inércia terapêutica, ou seja, a tendência de manter a dose atual em pacientes clinicamente estáveis e com classe funcional baixa, também é um fator limitante para alcançar a TMO. A falta de acesso a cuidados médicos (devido à falta de profissionais de saúde ou limitações geográficas) também pode dificultar a titulação dos medicamentos. Além disso, o custo dos mesmos também pode ser um obstáculo.<sup><xref ref-type="bibr" rid="B13">13</xref>,<xref ref-type="bibr" rid="B14">14</xref></sup></p>
				<p>Neste estudo, observou-se que 21,6% dos pacientes estavam em uso de terapia quádrupla, enquanto a prevalência de TMO (dose-alvo ou máxima tolerada da terapia quádrupla) foi de 7,9%. No registro CHAMP-HF, estudo observacional norte-americano com 3.518 pacientes ambulatoriais com ICFEr, apenas 1,1% estavam em uso da dose-alvo da terapia tripla simultaneamente (seguindo as diretrizes daquele momento do estudo).<sup><xref ref-type="bibr" rid="B18">18</xref></sup> Este registro citado incluiu centros de cardiologia não especializados, o que pode justificar a menor taxa de TMO observada em comparação à observada no presente estudo.</p>
				<p>O estudo IMPROVE-HF mostrou um aumento na prevalência de TMO de 14,1% para 22,8% em pacientes com ICFEr após aplicação de medidas educativas sobre o tratamento e manejo da IC.<sup><xref ref-type="bibr" rid="B19">19</xref></sup> Os centros acadêmicos podem atingir altas taxas de utilização da TMO e é de fundamental importância a educação e o treinamento médico contínuo como base para a manutenção de uma assistência de boa qualidade aos pacientes com IC.</p>
				<p>Um estudo observacional brasileiro mostrou prevalência de TMO (33,1%) em pacientes com ICFEr. Entretanto, essa prevalência foi observada em uso da terapia tripla,<sup><xref ref-type="bibr" rid="B20">20</xref></sup> diferente do presente estudo que incluiu uso do iSGLT2. Outros estudos têm estimado a prevalência de uso concomitante das classes medicamentosas para IC,<sup><xref ref-type="bibr" rid="B21">21</xref></sup> porém analisando apenas terapia tripla e sem observar o uso em dose-alvo ou máxima tolerada.</p>
				<p>A prevalência do uso de vasodilatadores (IECA ou BRA ou INRA) na amostra estudada foi de 88%, sendo 49,5% (116), 28,2% (66) e 22,2% (52) utilizando IECA, BRA e INRA, respectivamente. A prevalência do uso de vasodilatadores neste trabalho é superior às relatadas em registros internacionais, que variam de 73,4% a 85,8%.<sup><xref ref-type="bibr" rid="B15">15</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref></sup> No presente estudo, a utilização da classe INRA foi de 19,5% (52). Esta taxa está acima da observada na população americana (13,0%) e em registos do Oriente Médio (3,6%). Essa maior taxa de uso de INRA possivelmente está associada à recente disponibilidade (a partir de 2021) do medicamento em serviços públicos de distribuição de medicamentos de alto custo na região estudada.<sup><xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B21">21</xref></sup></p>
				<p>A prevalência de uso de betabloqueador foi de 95,9% (255). Essa alta taxa de utilização dessa classe também foi relatada em outros estudos brasileiros (80 a 100% conforme região do país).<sup><xref ref-type="bibr" rid="B8">8</xref>,<xref ref-type="bibr" rid="B10">10</xref>,<xref ref-type="bibr" rid="B11">11</xref></sup> A prevalência do uso desta classe em registros internacionais varia de 67% a 86,2% em dados americanos, enquanto em estudos europeus varia de 52% a 84%.<sup><xref ref-type="bibr" rid="B15">15</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref>,<xref ref-type="bibr" rid="B22">22</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup></p>
				<p>A taxa de utilização de espironolactona foi de 85,3% (227). Nos registros internacionais, observa-se menor frequência de uso de ARM, variando de 32,0% a cerca de 56,0%.<sup><xref ref-type="bibr" rid="B24">24</xref></sup> Dados brasileiros mostram que a taxa de prescrição dessa classe varia de 64% a 93%.<sup><xref ref-type="bibr" rid="B20">20</xref>,<xref ref-type="bibr" rid="B22">22</xref></sup></p>
				<p>A prevalência do uso de iSGLT2 foi de 27,4% (73). Segundo a literatura, as taxas de tratamento com esta classe variam de 12% a 20,1% em estudos observacionais, que incluíram em sua maioria pacientes diabéticos (11,9%) e poucos pacientes com IC (7,6%).<sup><xref ref-type="bibr" rid="B25">25</xref>,<xref ref-type="bibr" rid="B26">26</xref></sup> Em comparação com a literatura, observamos prevalência elevada de prescrição de iSGLT2. Possivelmente, isso se deve à alta prevalência de diabéticos na população estudada (21.8%), para os quais esta medicação possui maior disponibilidade no sistema público.</p>
				<sec>
					<title>Fatores associados ao uso das classes medicamentosas</title>
					<p>Quanto ao uso de vasodilatadores, observou-se que a presença de DRC, idade avançada, hipotensão e o uso de furosemida estiveram associados à menor chance de uso dessa classe. A DRC é amplamente descrita na literatura como fator limitante para o uso dessas medicações.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup> Similarmente, a idade avançada associa-se ao não uso de IECA/BRA, possivelmente refletindo uma tendência de submedicação em pacientes idosos, seja por intolerância ou inércia terapêutica.<sup><xref ref-type="bibr" rid="B27">27</xref></sup> A hipotensão arterial pode ser um marcador de doença mais avançada e de intolerância a esta classe.</p>
					<p>A furosemida não é relatada como fator clássico limitante do uso dos vasodilatadores, mas sua associação negativa se deve possivelmente a seu efeito hipotensor que acaba limitando a introdução ou progressão dos vasodilatadores.<sup><xref ref-type="bibr" rid="B28">28</xref>,<xref ref-type="bibr" rid="B29">29</xref></sup> Esse achado levanta a necessidade de cautela com outros medicamentos prescritos e sua potencial interação no tratamento farmacológico da ICFEr.</p>
					<p>A presença de DRC foi preditor independente de não uso de espironolactona. A DRC é classicamente relatada como fator limitante para o uso dessa medicação, sendo a piora da função renal e a hipercalemia as complicações mais frequentes.<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B23">23</xref></sup> Neste estudo, não houve associação entre hipercalemia e menor chance de uso de ARM. A associação positiva entre o uso de espironolactona e a presença de hipotensão sugere que pacientes com IC tratados com essa classe tendem a ter níveis menores de pressão arterial devido ao efeito hipotensivo dos ARM.<sup><xref ref-type="bibr" rid="B15">15</xref></sup></p>
					<p>O uso de furosemida foi associado positivamente com uso da espironolactona, o que pode representar a associação comumente observada na prática clínica, em que pacientes mais congestos requerem o uso concomitante das duas drogas. Em um registro sueco com mais de 11.000 pacientes, observou-se que pacientes em uso de outros diuréticos tinham maior chance de usar ARM,<sup><xref ref-type="bibr" rid="B24">24</xref></sup> corroborando os achados do presente estudo.</p>
					<p>Em relação ao uso de iSGLT2, observou-se associação positiva entre uso desta classe com a presença de DM e com uso de furosemida. A associação com DM pode ser explicada por um viés de indicação, pois pacientes com DM frequentemente recebem iSGLT2 para controle glicêmico independentemente da indicação para IC, o que aumenta a taxa de TMO no grupo dos diabéticos. Apesar das evidências mostrarem uma redução na mortalidade por IC independentemente da presença de DM,<sup><xref ref-type="bibr" rid="B12">12</xref>,<xref ref-type="bibr" rid="B15">15</xref></sup> registros mostram maior taxa de prescrição de iSGLT2 para pacientes com DM do que para pacientes com IC.<sup><xref ref-type="bibr" rid="B26">26</xref></sup> A associação dos iSGLT2 com furosemida sugere que pacientes mais congestos e sintomáticos podem ter maior propensão a receber concomitantemente diuréticos de alça e inibidores de SGLT2. Os iSGLT2 tendem a ser mais prescritos em pacientes congestos.<sup><xref ref-type="bibr" rid="B28">28</xref></sup></p>
					<p>A doença de Chagas apresenta disfunção autonômica inerente à doença além de lesão progressiva no sistema de condução elétrica do coração.<sup><xref ref-type="bibr" rid="B30">30</xref>-<xref ref-type="bibr" rid="B32">32</xref></sup> O uso de amiodarona é frequente nessa população devido à presença de arritmias graves, o que justifica a associação observada em que etiologia chagásica aumenta a probabilidade de uso dessa medicação.<sup><xref ref-type="bibr" rid="B33">33</xref>,<xref ref-type="bibr" rid="B34">34</xref></sup> Além disso a presença de doença de Chagas esteve associada a menor chance de uso de vasodilatadores, o que pode ser explicado pela pressão arterial limítrofe comumente observada nesse grupo,<sup><xref ref-type="bibr" rid="B35">35</xref></sup> o que impede a prescrição dessa classe por intolerância do paciente.</p>
					<p>O estudo STRONG-HF investigou o impacto da terapia quádrupla em pacientes com IC. Os resultados demonstraram que a intensificação precoce do tratamento, aliada a um acompanhamento rigoroso, reduziu significativamente a taxa de internação hospitalar por IC e mortalidade por todas as causas em 180 dias, em comparação ao cuidado usual.<sup><xref ref-type="bibr" rid="B36">36</xref></sup> Além disso, observou-se uma melhora nos sintomas, qualidade de vida e biomarcadores como o NT-proBNP. Não houve aumento significativo de eventos adversos graves ou fatais. Esses achados sugerem que a implementação de uma estratégia agressiva de titulação da terapia quádrupla pode melhorar substancialmente o prognóstico de pacientes com IC, destacando a importância de um manejo intensivo e personalizado destes pacientes.</p>
					<p>Um estudo observacional analisou o impacto da presença de comorbidades sobre a prescrição da terapia farmacológica em pacientes com ICFEr. Hipertensão arterial, DM, DRC, Fibrilação atrial e doença pulmonar obstrutiva crônica foram as comorbidades mais prevalentes. A presença de múltiplas comorbidades influenciou negativamente a prescrição da terapia tripla, especialmente os vasodilatadores e ARM. Contudo, a implementação da terapia quádrupla, que incluiu a adição de iSGLT2, não diferiu significativamente entre os grupos com diferentes cargas de comorbidades.<sup><xref ref-type="bibr" rid="B37">37</xref></sup> Esses achados sugerem que, embora a multimorbidade possa dificultar a prescrição da terapia tripla, a adição de iSGLT2 pode ser viável independentemente do número de comorbidades. No presente estudo, nenhuma comorbidade foi associada negativamente com o uso de iSGLT2.</p>
					<p>Este estudo apresenta limitações decorrentes de seu desenho transversal, o que limita a avaliação de adesão ou mudanças terapêuticas ao longo do tempo. Seu caráter unicêntrico também limita a extrapolação dos achados para outras populações. Além disso, a possibilidade de sub-registro de contraindicações nos prontuários pode ter influenciado a classificação das terapias avaliadas. Esses fatores devem ser considerados na interpretação dos resultados.</p>
					<p>As barreiras para uso do TMO observadas no presente estudo evidenciam a necessidade de estratégias sistematizadas para superar a inércia terapêutica e garantir tratamento adequado na ICFEr. A implementação de protocolos ambulatoriais de titulação de dose, educação médica continuada e revisão periódica e sistemática das classes e doses utilizadas são medidas que devem ser adotadas pelos serviços especializados. Os dados encontrados apontam a necessidade de um modelo de cuidado proativo e estruturado com foco na progressão terapêutica dos pacientes com IC.</p>
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			<sec sec-type="conclusions">
				<title>Conclusões</title>
				<p>O presente estudo encontrou prevalência elevada do uso das drogas modificadoras de prognóstico na ICFEr, porém o uso de doses-alvo ou máximas toleradas ficou aquém do preconizado. Etiologia chagásica, DRC, idade avançada, hipotensão arterial e uso concomitante de furosemida foram associados à redução da probabilidade de receber drogas modificadoras do prognóstico na ICFEr, enquanto a presença de diabetes foi associada a uma maior chance de uso do TMO.</p>
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					<label>Vinculação Acadêmica:</label>
					<p> Este artigo é parte de dissertação de Mestrado de Anderson Oliveira Estevan pela Universidade Federal de Goiás (UFG).</p>
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					<label>Aprovação Ética e Consentimento Informado:</label>
					<p> Este artigo não contém estudos com humanos ou animais realizados por nenhum dos autores.</p>
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				<fn fn-type="financial-disclosure">
					<label>Fontes de Financiamento:</label>
					<p> O presente estudo não teve fontes de financiamento externas.</p>
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