Abstract
The objective of this study is to describe the 2-year real-world clinical outcomes after transition to psychosis in patients at clinical high-risk. The study used the clinical electronic health record cohort study including all patients receiving a first index primary diagnosis of nonorganic International Classification of Diseases (ICD)-10 psychotic disorder within the early psychosis pathway in the South London and Maudsley (SLaM) National Health Service (NHS) Trust from 2001 to 2017. Outcomes encompassed: cumulative probability (at 3, 6, 12, and 24 months) of receiving a first (1) treatment with antipsychotic, (2) informal admission, (3) compulsory admission, and (4) treatment with clozapine and (5) numbers of days spent in hospital (at 12 and 24 months) in patients transitioning to psychosis from clinical high-risk services (Outreach and Support in south London; OASIS) compared to other first-episode groups. Analyses included logistic and 0-inflated negative binomial regressions. In the study, 1561 patients were included; those who had initially been managed by OASIS and had subsequently transitioned to a first episode of psychosis (n = 130) were more likely to receive antipsychotic medication (at 3, 6, and 24 months; all P < .023), to be admitted informally (at all timepoints, all P < .004) and on a compulsory basis (at all timepoints, all P < .013), and to have spent more time in hospital (all timepoints, all P < .007) than first-episode patients who were already psychotic when seen by the OASIS service (n = 310), or presented to early intervention services (n = 1121). The likelihood of receiving clozapine was similar across all groups (at 12/24 months, all P < .101). Transition to psychosis from a clinical high-risk state is associated with severe real-world clinical outcomes. Prevention of transition to psychosis should remain a core target of future research. The study protocol was registered on www.researchregistry.com; researchregistry5039).
Racial and ethnic disparity in clinical outcomes among patients with confirmed COVID-19 infection in a large US electronic health record database
