Diabetes and idiopathic cardiomyopathy: a nationwide case-control study

Diabetes Care. 2003 Oct;26(10):2791-5. doi: 10.2337/diacare.26.10.2791.

Abstract

Objective: Controversy exists regarding the relation between diabetes and nonischemic idiopathic cardiomyopathy (ICM), and only limited data on the incidence of ICM in adults with diabetes are available. Therefore, we used the 1995 Nationwide Inpatient Sample (NIS) to determine discharge rates and test the hypothesis that diabetes is independently associated with ICM.

Research design and methods: The 1995 NIS includes demographic and diagnostic data on all discharges from >900 representative hospitals in 19 states. ICD-9 codes were used to identify ICM, defined as discharges with a diagnosis of primary cardiomyopathy but without established risk factors for cardiomyopathy. Control subjects were selected by stratified random sampling by age to yield 10 per ICM case. The analyzed covariates included age, race, median income, diabetes, and hypertension. Multivariate logistic regression was used to conduct case-control analyses.

Results: Using sampling weights, we estimated that in 1995, the rate of hospital discharge for ICM among individuals diagnosed with diabetes was 7.6 per 1000. The prevalence of diabetes was substantially higher in the 44837 ICM vs. 450254 control subjects (26.6 vs. 17.2%), corresponding to a relative odds (RO) of 1.75 (95% CI 1.71-1.79). After adjusting for age, sex, race, hypertension, and median income using multiple logistic regression, diabetes remained significantly associated with ICM (RO 1.58, 95% CI 1.55-1.62).

Conclusions: We concluded that diabetes is independently associated with ICM in the general U.S. population.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cardiomyopathies / epidemiology*
  • Case-Control Studies
  • Diabetes Mellitus / epidemiology*
  • Female
  • Hospitalization
  • Humans
  • Incidence
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Prevalence
  • Risk Factors
  • United States / epidemiology