Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis.

OBJECTIVE: Cardiometabolic risk prediction algorithms are common in clinical practice. Young people with psychosis are at high risk for developing cardiometabolic disorders. We aimed to examine whether existing cardiometabolic risk prediction algorithms are suitable for young people with psychosis. METHODS: We conducted a systematic review and narrative synthesis of studies reporting the development and validation of cardiometabolic risk prediction algorithms for general or psychiatric populations. Furthermore, we used data from 505 participants with or at risk of psychosis at age 18 years in the ALSPAC birth cohort, to explore the performance of three algorithms (QDiabetes, QRISK3 and PRIMROSE) highlighted as potentially suitable. We repeated analyses after artificially increasing participant age to the mean age of the original algorithm studies to examine the impact of age on predictive performance. RESULTS: We screened 7820 results, including 110 studies. All algorithms were developed in relatively older participants, and most were at high risk of bias. Three studies (QDiabetes, QRISK3 and PRIMROSE) featured psychiatric predictors. Age was more strongly weighted than other risk factors in each algorithm. In our exploratory analysis, calibration plots for all three algorithms implied a consistent systematic underprediction of cardiometabolic risk in the younger sample. After increasing participant age, calibration plots were markedly improved. CONCLUSION: Existing cardiometabolic risk prediction algorithms cannot be recommended for young people with or at risk of psychosis. Existing algorithms may underpredict risk in young people, even in the face of other high-risk features. Recalibration of existing algorithms or a new tailored algorithm for the population is required.

Disease Risk Analysis and Post-Release Health Surveillance for a Reintroduction Programme: the Pool Frog Pelophylax lessonae.

There are risks from disease in undertaking wild animal reintroduction programmes. Methods of disease risk analysis have been advocated to assess and mitigate these risks, and post-release health and disease surveillance can be used to assess the effectiveness of the disease risk analysis, but results for a reintroduction programme have not to date been recorded. We carried out a disease risk analysis for the reintroduction of pool frogs (Pelophylax lessonae) to England, using information gained from the literature and from diagnostic testing of Swedish pool frogs and native amphibians. Ranavirus and Batrachochytrium dendrobatidis were considered high-risk disease threats for pool frogs at the destination site. Quarantine was used to manage risks from disease due to these two agents at the reintroduction site: the quarantine barrier surrounded the reintroduced pool frogs. Post-release health surveillance was carried out through regular health examinations of amphibians in the field at the reintroduction site and collection and examination of dead amphibians. No significant health or disease problems were detected, but the detection rate of dead amphibians was very low. Methods to detect a higher proportion of dead reintroduced animals and closely related species are required to better assess the effects of reintroduction on health and disease.