Predicting Mortality Risks Using Body Mass Index and Weight Loss at Admission in Patients with Heart Failure

Abstract

Background: The association of the combination of body mass index (BMI) and weight change at admission with prognoses in patients with heart failure (HF) is unclear. Therefore, we investigated whether BMI and weight changes at admission affect mortality in patients with HF.

Methods: This retrospective cohort study lasted 99 months, starting in April 2014, and included 4,862 patients with HF from a Japanese real-world database. Cubic and thin-plate smoothing spline analyses were performed to investigate the association of BMI and weight changes with mortality. The percentage weight change was calculated every 6 months. The study outcome was the presence or absence of death.

Results: The patients' mean age was 81.5±9.6 years, and 1,239 (25.5%) patients died. Cubic spline analysis revealed a negative correlation of BMI with mortality hazard ratio (HR) (BMI of 18.5 kg/m2 and 25 kg/m2; HR=1.3 [1.2-1.4] and 0.8 [0.7-0.9], respectively). Cubic spline analysis of weight change showed that weight loss tended to increase the mortality HR (each 6% decrease in weight change rate was associated with a 1.1 times higher mortality risk (95% CI [1.0-1.2]) Thin-plate smoothing spline analysis showed that the odds ratio (OR) negatively correlated with BMI (1-year mortality: BMI of 18.5 kg/m2, 22 kg/m2, and 25 kg/m2; OR at 0% weight change=1.5, 1.0, and 0.7, respectively; 2-year mortality: BMI=18.5 kg/m2, 22 kg/m2, and 25 kg/m2; OR at 0% weight change=1.4, 0.9, and 0.7, respectively).

Conclusion: A low BMI in patients with HF was associated with a higher risk of mortality. Weight loss in patients, regardless of BMI, was associated with a higher OR for mortality.

Keywords: Asian; Cachexia; Heart failure; Obesity paradox; Prognosis.

Fig. 1.

Restricted cubic splines for mortality. (A, B) The association between BMI/weight change and mortality hazard ratios allowed for nonlinear effects with 95% CIs. The model fitted with four knots restricted the cubic spline to BMI/weight change. The bar graph shows the histogram. BMI, body mass index; CI, confidence interval.

Fig. 2.

Body mass index (BMI) and weight change in mortality odds ratio (OR) using a contour map (unadjusted model): (A) 1-year mortality and (B) 2-year mortality. The solid black line indicates an OR of 1.0. The dashed-and-dotted, dashed, and dotted lines indicate ORs of 0.8, 1.2, and 1.4, respectively. There is a higher OR for mortality with a lower BMI and weight gain/loss.

Fig. 3.

Body mass index and weight change in mortality odds ratio (OR) using a contour map (adjusted model): (A) 1-year mortality and (B) 2-year mortality. The model was adjusted for age, sex, Charlson Comorbidity Index, Barthel Index, and New York Heart Association classification.

Fig. 4.

Restricted cubic spline analysis of patients repeatedly hospitalized for heart failure. The association between weight change and mortality hazard ratios allowed for nonlinear effects with 95% CIs: (a) restricted cubic splines for (A) mortality and (b) in-hospital mortality. CI, confidence interval.