Affiliation:
1. Mental Health Team, Department of Public Health and Welfare Finnish Institute for Health and Welfare Helsinki Finland
2. Department of Psychiatry University of Helsinki and Helsinki University Hospital Helsinki Finland
3. Department of Psychiatry University of Turku and Turku University Hospital Turku Finland
4. Department of Psychiatry University of Cambridge Cambridge UK
5. Cambridgeshire and Peterborough NHS Foundation Trust Fulbourn UK
6. The Finnish Medical Society Duodecim Helsinki Finland
Abstract
AbstractIntroductionAccurate detection of cardiometabolic risk in early psychosis is crucial to reducing somatic morbidity and mortality in people with psychotic disorders. We conducted an external validation of the psychosis metabolic risk calculator (PsyMetRiC), a cardiometabolic risk prediction tool developed in the UK and tailored for young people with psychosis. We compared the predictive accuracy and clinical usefulness of PsyMetRiC and a general population‐based risk prediction tool for type 2 diabetes, the Finnish Diabetes Risk Score (FINDRISC).MethodsWe included first‐episode psychosis and ultra‐high‐risk for psychosis patients without metabolic syndrome aged 18–35 years from the Helsinki Early Psychosis and Turku Early Psychosis Study cohorts. We tested two versions of PsyMetRiC: the full model including age, sex, ethnicity, body‐mass index, smoking status, prescription of metabolically‐active antipsychotic medication, high‐density lipoprotein, and triglyceride concentrations, and the partial‐model excluding biochemical predictors, and the simplified FINDRISC including BMI, sex, systolic blood pressure, and fasting glucose. Discrimination, calibration, and decision curve analyses were used to assess the predictive performance and clinical usefulness of both PsyMetRiC and FINDRISC. We performed a site‐specific re‐calibration of PsyMetRiC (PsyMetRiC‐Fi).ResultsThe study sample consisted of 278 individuals (all White European ethnicity, 58.6% male, mean age 24.8 years, 37.8% smoking, mean BMI 23.5). Discrimination was marginally better in the PsyMetRiC full model (C = 0.72, 95% CI, 0.59–0.82) compared with partial model (C = 0.70, 95% CI 0.59–0.80) or FINDRISC (C = 0.63, 95% CI 0.54–0.71). Calibration plots displayed evidence of minor miscalibration for PsyMetRiC, which corrected following recalibration. Miscalibration was more pronounced for FINDRISC. Decision curve analysis showed that PsyMetRiC offers likely clinical usefulness in improving cardiometabolic risk management in early psychosis compared with giving everyone or no one an intervention.ConclusionPsyMetRiC has utility in predicting cardiometabolic risk in Finnish patients with early psychosis. It has better discriminatory accuracy and offers more accurate risk prediction compared to other available strategies.
Funder
Helsingin ja Uudenmaan Sairaanhoitopiiri
Turun Yliopistollinen Keskussairaala
Research Council of Finland
Sigrid Juséliuksen Säätiö
Suomen Kulttuurirahasto
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