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- Title
Misclassification of hypertrophic cardiomyopathy: validation of diagnostic codes.
- Authors
Magnusson, Peter; Palm, Andreas; Branden, Eva; Mörner, Stellan
- Abstract
Purpose: To validate diagnostic codes for hypertrophic cardiomyopathy (HCM), analyze misclassfications, and estimate the prevalence of HCM in an unselected Swedish regional cohort. Patients and methods: Using the hospitals' electronic medical records (used for the Swedish National Patient Register), we identified 136 patients from 2006 to 2016 with the HCM-related codes 142.1 and 142.2 (International Classification of Diseases). Results: Of a total of 129 residents in the catchment area, 88 patients were correctly classified as HCM (positive predictive value 68.2%) and 41 patients (31.8%) were misclassified as HCM. Among the 88 HCM patients (52.2% males), 74 were alive and 14 were dead (15.9%). This yields an HCM prevalence of 74/183,337, that is, 4.0 diagnosed cases per 10,000 in the adult population aged ≥18 years. The underlying diagnoses of misclassified cases were mainly hypertension (31.7%) and aortic stenosis (22.0%). Other types of cardiomyopathies accounted for several cases of misclassification: dilated (nonischemic or ischemic), left ventricular noncompaction, and Takotsubo. Miscellaneous diagnoses were amyloidosis, pulmonary stenosis combined with ventricular septal defect, aortic insufficiency, athelete's heart, and atrioventricular conduction abnormality. The mean age was not significantly different between HCM and misclassified patients (65.8±15.8 vs 70.1±13.4 years; P=0.177). There were 47.8% females among HCM and 60.8% females among misclassified (P=0.118). Conclusion: One-third of patients diagnosed as HCM are misclassified, so registry data should be interpreted with caution. A correct diagnosis is important for decision-making and implementation of optimal HCM care; efforts should be made to increase awareness of HCM and diagnostic competence throughout the health care system.
- Subjects
HYPERTROPHIC cardiomyopathy; DIAGNOSTIC errors; EPIDEMIOLOGY; ELECTRONIC health records; COHORT analysis; DIAGNOSIS
- Publication
Clinical Epidemiology, 2017, Vol 9, p403
- ISSN
1179-1349
- Publication type
Article
- DOI
10.2147/CLEP.S139300