Does specific psychopathology predict development of psychosis in ultra high-risk (UHR) patients?. (April 2013) - Thompson, Andrew; Nelson, Barnaby; Bruxner, Annie; O'Connor, Karen; Mossaheb, Nilufar; Simmons, Magenta B; Yung, Alison
Objectives: Studies have attempted to identify additional risk factors within the group identified as 'ultra high risk' (UHR) for developing psychotic disorders in order to characterise those at highest risk. However, these studies have often neglected clinical symptom types as additional risk factors. We aimed to investigate the relationship between baseline clinical psychotic or psychotic-like symptoms and the subsequent transition to a psychotic disorder in a UHR sample. Method: A retrospective 'case–control' methodology was used. We identified all individuals from a UHR clinic who had subsequently developed a psychotic disorder (cases) and compared these to a random sample of individuals from the clinic who did not become psychotic within the sampling time frame (controls). The sample consisted of 120 patients (60 cases, 60 controls). An audit tool was used to identify clinical symptoms reported at entry to the clinic (baseline) using the clinical file. Diagnosis at transition was assessed using the Operational Criteria for Psychotic Illness (OPCRIT) computer program. The relationship between transition to a psychotic disorder and baseline symptoms was explored using survival analysis. Results: Presence of thought disorder, any delusions and elevated mood significantly predicted transition to a psychotic disorder. When other symptoms were adjusted for, only the presence of elevated mood significantly predicted subsequent transition (hazard ratio 2.69, p = 0.002). Thought disorder was a predictor of transition to a schizophrenia-like psychotic disorder (hazard ratio 3.69, p = 0.008). Conclusions: Few individual clinical symptoms appear to be predictive of transition to a psychotic disorder in the UHR group. Clinicians should be cautious about the use of clinical profile alone in such individuals when determining who is at highest risk.