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Predictors of 10-year outcome of first-episode psychosis

  • C. White (a1), J. Stirling (a2), R. Hopkins (a1), J. Morris (a1), L. Montague (a1), D. Tantam (a3) and S. Lewis (a1)
  • DOI: http://dx.doi.org/10.1017/S003329170800514X
  • Published online: 01 February 2009
Abstract
Background

Predictors of outcome for psychosis are poorly understood. Duration of untreated psychosis (DUP) appears to predict short-term outcome although its medium- to long-term role remains unclear. Neurodevelopmental indices such as pre-morbid function and/or neurological soft signs may predict longer-term outcome. We aimed to assess the impact of a range of clinical and demographic variables on long-term outcome of a geographically defined, epidemiological first-episode psychosis cohort.

Method

A 10-year follow-up was undertaken of a consecutively presenting sample of 109 cases of first-episode psychosis aged 16–50 years. Baseline assessments included positive, negative and depression symptoms, DUP, neurological soft signs and pre-morbid functioning. Multi-dimensional outcomes were assessed blind to baseline data.

Results

All participants were traced at a mean of 10.5 years post-index admission: 11 had died, 10 from non-natural causes. Of the surviving cases, 70% were comprehensively re-assessed by interview. Summary data on the remainder were collected from their family practitioner and chart review. Poor 10-year outcomes were predicted independently by poor pre-morbid functioning, baseline negative symptoms and longer DUP. The same measures, plus neurological soft signs, appeared to predict outcomes in a DSM-IV schizophrenia/schizo-affective subgroup.

Conclusions

Poor pre-morbid functioning, baseline symptoms, DUP and neurological soft signs at onset independently predict poor long-term outcome in first-episode psychosis.

Copyright
Corresponding author
*Address for correspondence: J. Stirling, D.Phil., Department of Psychology and Speech Pathology, Manchester Metropolitan University, Hathersage Road, Manchester M13 0JA, UK. (Email: j.stirling@mmu.ac.uk)
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