Psychometric analysis of the heart failure somatic perception scale as a measure of patient symptom perception

Background: Symptoms are known to predict survival among patients with heart failure ( HF ), but discrepancies exist between patients’ and health providers’ perceptions of HF symptom burden. Objective: The purpose of this study is to quantify the internal consistency, validity, and prognostic value of patient perception of a broad range of HF symptoms using an HF-specific physical symptom measure, the 18-item HF Somatic Perception Scale v. 3. Methods: Factor analysis of the HF Somatic Perception Scale was conducted in a convenience sample of 378 patients with chronic HF. Convergent validity was examined using the Physical Limitation subscale of the Kansas City Cardiomyopathy Questionnaire. Divergent validity was examined using the Self-care of HF Index self-care management score. One-year survival based on HF Somatic Perception Scale scores was quantified using Cox regression controlling for Seattle HF Model scores to account for clinical status, therapeutics, and lab values. Results: The sample was 63% male, 85% white, 67% functionally compromised ( New York Heart Association class III–IV ) with a mean ( SD ) age of 63 ( 12.8 ) years. Internal consistency of the HF Somatic Perception Scale was [alpha] = .90. Convergent ( r = -0.54, P < .0001 ) and divergent ( r = 0.18, P > .05 ) validities were supported. Controlling for Seattle HF scores, HF Somatic Perception Scale was a significant predictor of 1-year survival, with those most symptomatic having worse survival ( hazard ratio, 1.012; 95% confidence interval, 1.001–1.024; P = .038 ). Conclusions: Perception of HF symptom burden as measured by the HF Somatic Perception Scale is a significant predictor of survival, contributing additional prognostic value over and above objective Seattle HF Risk Model scores. This analysis suggests that assessment of a broad range of HF symptoms, or those related to dyspnea or early and subtle symptoms, may be useful in evaluating therapeutic outcomes and predicting event-free survival.