Abstract

Persistent somatic symptoms (PSS) are a diagnostic core criterion of the somatic symptom disorder. This longitudinal study aims to determine the frequency of PSS in patients with cardiac disease, identify potential predictive factors, and investigate its impact on healthcare utilization. Somatic symptoms were assessed with the Somatic Symptom Scale-8 four times over the course of three months in consecutively approached cardiac outpatients. Patients were grouped having PSS vs. not having PSS following a psychometric-driven approach based on the SSS-8 cut-off score and a data-driven approach applying cluster analysis. T-tests were performed to compare the characteristics between patients having vs. not having PSS. To identify predictors of group affiliation, we conducted multivariable logistic regressions. Additionally, analyses of covariance were used to further examine associations between healthcare utilization and group affiliation. The study included 95 patients (30.5% female) with a mean age of 60.5 years (SD = 8.7). All patients had at least one of the following cardiac diseases recorded in their medical history: coronary heart disease (n = 51), myocardial infarction (n = 21), valve disease (n = 22), cardiomyopathy (n = 15), cardiac dysrhythmia (n = 43), and heart failure (n = 12). 30 (32%) were grouped having PSS according to the psychometric-driven approach and 27 (28%) according to the data-driven approach. For both approaches, patients with PSS were more likely to be female, unemployed, reporting angina pectoris, having higher depression, and higher anxiety severity (for all: p ≤ 0.05). Predictors of PSS group affiliation were female gender, higher age, depression severity, and angina pectoris (for all: p ≤ 0.015). Patients with PSS more frequently visited general practitioners and cardiologists compared to patients without PSS (p ≤ 0.013). Enhancing our knowledge of PSS in patients with cardiac disease could help to improve identification of patients’ specific needs and the factors to consider in diagnosis and individualized treatment.

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