Gender disparity in a large nonreferral-based cohort of hypertrophic cardiomyopathy patients

J Womens Health (Larchmt). 2008 Dec;17(10):1629-34. doi: 10.1089/jwh.2007.0734.

Abstract

Background: Hypertrophic cardiomyopathy (HCM) is a genetic disease of the heart muscle that affects 1 in 500 people. HCM is highly heterogeneous in its clinical presentation and severity. HCM research has typically been carried out using hospital-based and referral populations. The Hypertrophic Cardiomyopathy Association (HCMA) is a patient support group founded in 1996. The HCMA membership and related database represent a large, heterogeneous, and diverse nonhospital and nonreferral-based HCM patient population.

Methods: To examine gender disparities in self-reported symptom and medication patterns among HCM patients participating in the HCMA database, HCMA patient information was entered into an Access database. Patients were added to the HCMA database when they joined or requested information from the HCMA. Consenting patients were interviewed by phone or mailed an intake survey.

Results: Information was available for 1228 HCM patients from 49 states and 32 countries (549 females, 679 males). Females were significantly more likely to report a family history of HCM to experience chest pain, fatigue, lightheadedness, and palpitations and to be taking non-HCM-related medications. In terms of symptom clustering, 44.9% of females had four or five symptoms vs. 31.4% of the males.

Conclusions: The HCMA patient database represents a nonhospital-based patient cohort useful in scientific investigations of HCM. Observed gender-related disparities in HCM symptom profiles are significant but are subject to the design and self-report-based limitations of the HCM database.

MeSH terms

  • Adult
  • Aged
  • Cardiomyopathy, Hypertrophic / diagnosis
  • Cardiomyopathy, Hypertrophic / epidemiology*
  • Cohort Studies
  • Female
  • Global Health
  • Humans
  • Male
  • Medical Records / statistics & numerical data*
  • Middle Aged
  • Patients / statistics & numerical data
  • Population Groups / statistics & numerical data*
  • Sex Distribution
  • Sex Factors
  • United States / epidemiology
  • Women's Health*