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. 2021 Dec 31;9(4):e138.
doi: 10.15190/d.2021.17. eCollection 2021 Oct-Dec.

Reversal of hypertensive heart disease: a multiple linear regression model

Affiliations

Reversal of hypertensive heart disease: a multiple linear regression model

Shah Newaz Ahmed et al. Discoveries (Craiova). .

Abstract

The development of left ventricular hypertrophy in primary hypertension increases cardiovascular mortality and morbidity. Reversal of left ventricular hypertrophy through therapeutic control of blood pressure reduces the risk of adverse cardiovascular incidents. Objective: In our study, we explored for the determinants of left ventricular hypertrophy regression. Methods: A cohort (n=217) of patients with hypertensive left ventricular hypertrophy was identified by screening consecutive patients in medical outpatient unit. The primary inclusion criteria were (i) Blood pressure more than140/90 mm of Hg (ii) Left Ventricular Mass Index more than 115 and 95 gm/m2 for males and females respectively. Left Ventricular Mass Index was determined by echocardiography at the time of recruitment and after 24 weeks of standard pharmacotherapy. The change in Left Ventricular Mass Index was modelled using multiple linear regression with both categorical and continuous explanatory variables. The effect of drug therapy on change in Left Ventricular Mass Index was tested in the model with dummy coded variables for the treatment categories. Results: In simple linear regression, the variables significantly correlating with change in Left Ventricular Mass Index were baseline Left Ventricular Mass Index (r=0.62, p<0.001), change in systolic blood pressure (r=0.22, p=0.001), change in mean blood pressure (r=0.16, p=0.02), baseline systolic blood pressure (r=0.15, p=0.02), age (r=0.12, p=0.09) and diabetes (r=0.12, p=0.09). The best fit model (r2=0.408) retained baseline Left Ventricular Mass Index (β=0.59, p<0.001), change in systolic blood pressure (β=0.14, p=0.01) and diabetes (β=-0.104, p=0.05) as the significant predictors. Introduction of treatment effect into the model non-significantly increased the fit of the model (r2=0.414, p=0.27-0.98). Conclusions: Pre-treatment Left Ventricular Mass Index and reduction in systolic blood pressure were the major determinants of left ventricular hypertrophy regression. We also observed that there is lesser left ventricular hypertrophy regression in diabetic patients, warranting future research to explore glycaemic control as a modifiable factor in left ventricular hypertrophy reversal.

Keywords: Hypertension; left ventricular hypertrophy; left ventricular mass.; linear regression; renin angiotensin system.

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Conflict of interest statement

Conflict of interests: The authors declare no competing interests.

Figures

Figure 1
Figure 1. Diagram showing relationship of change in LVMI with the baseline LVMI (A.) and change in SBP (B.).
LVMI - left ventricular mass index; SBP - systolic blood pressure
Figure 2
Figure 2. Box and Whisker plot representing mean change in LVMI with 95% confidence interval in the four treatment groups
LVMI- Left ventricular mass indexLVMI - left ventricular mass index; SBP - systolic blood pressure.
Figure 3
Figure 3. Plot of bivariate correlation between the actual and the modelled values of change in LVMI in the hold-out validation method (A.; R=0.59) and the leave-one-out validation method (B.; R=0.64) respectively.
The negative values of the variables are not shown in graph.

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