Cluster Analysis – ABC CARDIOL

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Original Article

Influence of Arm Fat on the Indirect Measurement of Blood Pressure: A Statistical and Machine Learning Approach

Paôla de Oliveira Souza et al. José Maria Parente de Oliveira Letícia Helena Januário

Abstract

Background

The indirect measurement of blood pressure (BP) is known to be influenced by many factors such as the technique, observer, and equipment; however, the influence of arm composition has not been investigated yet.

Objective

To identify the influence of arm fat on the indirect measurement of blood pressure using statistical inference and machine learning models.

Methods

Cross-sectional study, with 489 healthy young adults aged from 18 to 29 years old. Measurements of arm length (AL), arm circumference (AC) and arm fat index (AFI) were taken. BP was measured in both arms simultaneously. Data were processed using Python 3.0 and its specific packages for descriptive analysis, regression and cluster analysis. Significance levels: 5% for all calculations.

Results

BP and anthropometric measurements were different between the hemi-bodies. In the right arm, systolic blood pressure (SBP), AL and AFI were higher, while AC was similar compared with the left arm. AL and AC showed positive correlation with SBP. According to the regression model, for a fixed value of AC and AL, SBP readings could be reduced by a mean of 1.80 mmHg in the right arm, and 1.62 mmHg in the left arm for every 10% increase in AFI. Clustering analysis corroborated the regression results.

Conclusion

There was a significant influence of AFI on BP readings. SBP had a positive correlation with AL and AC, and a negative correlation with AFI, suggesting the need for further investigations on the relationship between BP and percentages of arm muscle and fat.

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Editorial

Co-occurrence of Cardiometabolic Disease Risk Factors: Unhealthy Eating, Tobacco, Alcohol, Sedentary Lifestyle and Socioeconomic Aspects

Maury-Sintjago Eduard et al. Parra-Flores Julio Rodríguez-Fernández Alejandra

Cardiometabolic disease (CMD) is the principal cause of morbi-mortality worldwide. The risk factors in the development of CMD are diverse; understanding them significantly contributes to the design of clinical and/or community strategies for their prevention and/or treatment. An unhealthy diet, cigarette smoking, sedentary lifestyle, and higher alcohol consumption significantly increase the risk of CMD, cancer, loss of healthy life years, and premature mortality.

In a systematic review by Meader et al., 37 studies were proposed in order to evaluate risk behaviors such as smoking, physical inactivity, and unhealthy diet by a meta-analysis. A greater association was found when groups of risk factors co-existed (≥ 4) compared with individual risk factors. Alcohol abuse and smoking were the most commonly identified risk factors. They also reported that the socioeconomic level is a predictor of multiple risks. On the other hand, in a cohort study of more than 20 years, mortality associated with 1, 2, 3, or 4 risk factors was 1.85 (C I 95%, 1.28-2.68), 2.23 (CI 95%, 1.55-3.20), 2.76 (CI 95%, 1.91-3.99), and 3.49 (CI 95%, 2.31-5.26), respectively. The risk of mortality by CMD was higher than for other causes of death such as cancer.

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Artigo Original

Echocardiographic criteria for the definition of ventricular dysfunction severity in aortic banded rats

Vanessa Oliveira Moreira et al. Ana Valéria Barros de Castro Marcelle Yumi Yaegaschi Antonio Carlos Cicogna … Marina Politi Okoshi Camila Alves Pereira Flávio Ferrari Aragon Mário Batista Bruno Carlos Roberto Padovani Katashi Okoshi

OBJECTIVE: The purpose of this study was to identify echocar-diographic parameters that allow distinguishing different levels of cardiac dysfunction in aortic banded rats. METHODS: Wistar male rats (90-100 g) were subjected to aortic banding (n=23) or a sham operation (n=12). The following echocardiographic parameters were evaluated and used to group rats into groups with similar characteristics using cluster analysis: absolute values and after normalization to body weight of left ventricular end-diastolic diameter (LVDD) and left atrial systolic diameter; left ventricular end-systolic diameter (LVSD); LV weight to body weight ratio (LVW/BW); three indexes of left ventricular shortening (endocardial fractional shortening, EFS; midwall FS, MFS; and posterior wall shortening velocity, (PWSV). RESULTS: The cluster analysis could group aortic banded rats into two groups: mild (n=13) and severe (n=9) stage of heart failure. There was no overlapping among the values of the 95% confidence interval of the following parameters between the two groups: LVDD, LVSD, EFS, MFS, LVW/BW, and PWSV. CONCLUSION: It is feasible to distinguish two groups of aortic banded rats according to the level of cardiac dysfunction using those echocardiographic parameters. This allows to perform longitudinal studies in homogeneous groups of rats with aortic banding and cardiac dysfunction.

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Influence of Arm Fat on the Indirect Measurement of Blood Pressure: A Statistical and Machine Learning Approach

Abstract

Background

Objective

Methods

Results

Conclusion

Co-occurrence of Cardiometabolic Disease Risk Factors: Unhealthy Eating, Tobacco, Alcohol, Sedentary Lifestyle and Socioeconomic Aspects

Echocardiographic criteria for the definition of ventricular dysfunction severity in aortic banded rats

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Electronic Document Format (Vancouver)

Electronic Document Format (ABNT)

Electronic Document Format (APA)

Electronic Document Format (ISO)

Electronic Document Format (Vancouver)

Electronic Document Format (ABNT)

Electronic Document Format (APA)

Electronic Document Format (ISO)