Abstract\sBackground— A higher BMI (weight/height2) puts people's lives in danger, even if they don't have a history of heart disease. Low BMI has been linked to an increased risk of death in people with certain chronic conditions, such as heart failure.

 

In the Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity (CHARM) study, we looked at the impact of BMI on prognosis using Cox proportional hazards models in 7599 patients (mean age, 65 years; 35% women) with symptoms of heart failure (New York Heart Association class II to IV) and a wide range of left ventricular ejection fractions (mean, 39%). One thousand eight hundred thirty-one individuals died over a median follow-up of 37.7 months. Compared to individuals with a BMI between 30 and 34.9, those with a lower BMI had a slightly elevated risk of mortality after adjusting for relevant confounders. According to the 95 percent confidence intervals, the hazard ratios for individuals with BMIs of 25 to 29.9, 22.5 to 24.9, and 22.5 were 1.22 (1.06 to 1.41), 1.46 (1.24) to 1.71, and 1.69 (1.43 to 2.01). There was no statistically significant increase in mortality risk among individuals with a BMI of 35. (hazard ratio, 1.17; 95 percent confidence interval, 0.95 to 1.43). Age, smoking status, or left ventricular ejection fraction did not affect the link between BMI and death (P for interaction >0.20). All-cause mortality risk was higher in individuals with no edema but not in those with edema. (P for interaction = 0.0001) The risk of cardiovascular and noncardiovascular mortality was higher in people with a lower BMI. At baseline, BMI did not affect the likelihood of being admitted to the hospital owing to worsening heart failure or other reasons.

Heart failure is more likely to develop in those with a high BMI (body mass index) (HF).

1–4 A curvilinear relationship between BMI and overall mortality has been shown in healthy adults, with death rates increasing at the lowest and highest BMI levels and decreasing in the middle. 5,6 The risk of death appears to be nonsignificant15 in patients with established HF who have an elevated BMI in the opposite direction of the normal range (7–13 no,14). In most of these studies, HF patients with all ejection fractions and those with a wide range of ejection fractions were not included in the research. BMI's predictive importance for all-cause death, cause-specific death, and morbid outcomes in individuals with chronic HF remain unclear.

 

588 of the editorial

 

Pp. 636-637 in Clinical Perspective

 

The Candesartan in Heart Failure: Assessment Of Reduction In Mortality and Morbidity (CHARM) study included patients with HF symptoms and either diminished or maintained left ventricular systolic function. We looked at the effect of BMI on prognosis in these patients. Low BMI (and raised BMI) were related to an increased risk of mortality and adverse cardiovascular outcomes in individuals with chronic HF.

 

Methods

 

The CHARM program's concept and outcomes have been previously reported.

 

16,17 Throughout the CHARM clinical trials, which ran from March 1999 to March 2003, 7599 men and women ages 18 and older with symptomatic chronic HF (NYHA class II to IV, regardless of left ventricular ejection fraction) were randomly assigned to receive candesartan or a placebo.As we can see at bodyvisualizer.net candesartan's efficacy was evaluated in both groups. All patients who have a serum creatinine level of 265 mmol/L; serum potassium level of 5.5 mmol/L; known bilateral renal arterial obstruction; symptomatic hypotension; critical aortic or mitral stenosis; recent myocardial infarction; stroke; or open-heart surgery; use of an angiotensin-receptor blocker in the previous two weeks; any noncardiac disease judged to limit 2-year survival; and those unwilling to provide consent, as well as women of childbearing potential who are not using adequacy. Treatment and follow-up were expected to last anywhere from 24 to 48 months.

 

Covariates and Results

 

Each participant's demographics, height and weight, history of cardiovascular disease (CVD), and the presence of any known symptoms or indicators of congestive heart failure (HF) were collected at the time of recruitment. In addition, foot, ankle, leg, and sacral pitting edema were evaluated for the presence or absence of a complication. To get at a person's BMI, we divided their weight in kilograms by height in meters squared. All-cause mortality (the major endpoint of the CHARM overall program), cardiovascular death, noncardiovascular death, hospitalization for worsening HF, and hospitalization for reasons were included in this analysis. All-cause death or hospitalization for worsening HF, all-cause death or hospitalization for all causes, and cardiovascular death or hospitalization for worsening HF were analyzed as composite outcomes. One and two-year follow-up periods were used to measure days spent out of the hospital as an endpoint. Using predetermined definitions and blinded to the baseline BMI status, an impartial adjudicatory body determined all outcomes, then published them. In the absence of evidence to the contrary, a death was automatically attributed to causes other than cardiovascular disease. It was characterized as an unplanned admission to the hospital for treatment of HF or when the patient's hospitalization included an increased focus on HF. To be hospitalized, a patient's HF symptoms and signs had to be deteriorating, necessitating IV diuretic therapy. At least one of the following items had to be present:

  • Increasing dyspnea on exertion.
  • Orthopnea.
  • Nocturnal dyspnea.
  • Pulmonary edema.
  • Increasing peripheral edema.
  • Increasing fatigue or decreasing exercise tolerance.
  • Renal hypoperfusion (i.e., worsening renal function).
  • Raised jugular venous pressure.
  • Radiological signs of HF.

 

Analyses based on Data

 

Continuous (every 1-kg/m2 drop) and categorical (between 22.5 to 24.9 and 30.0 to 34.9 kg/m2 [referent]) BMI was measured. The World Health Organization18 and the National Institutes of Health suggested cut points for the BMI categories. 19

 

We derived the mean and standard deviation for continuous variables and the proportions for categorical variables as a starting point for each BMI category. We used linear or logistic regression models to examine the connection between baseline factors and BMI as a continuous variable (per 1-kg/m2 change). Our study used Cox proportional hazards regression models to calculate hazard ratios (HRs), 95% confidence intervals (CIs), and 2-sided probability values to examine the relationship between BMI and the risk of various outcomes, defined as the time from the onset of the first occurrence of the event.

 

At 1 and 2 years of follow-up, we used linear regression to determine if BMI was associated with a longer time spent alive outside the hospital. As part of the CHARM initiative, we used multivariable models that accounted for all of the major variables of mortality and morbidity. 20 Age (per 10 years over 60 years), left ventricular ejection fraction (per 5% decrease below 45%), diabetes mellitus (none [referent], insulin-treated, and oral therapy or diet only), male sex, New York Heart Association class (II [referent], III, and IV), current smoking, bundle-branch block, cardiomegaly, and previous hospitalization for HF (none) were listed in order of strength of association with all-cause death. Age ( (candesartan versus placebo). These terms included linear, quadratic, linear plus quadratic, logarithmic, squared root, exponential and categorical (groups as defined above) transformations of BMI in multivariable models to examine BMI's connection with all-cause mortality.