Abstract
Background Since the onset, prevalence, and course of specific psychopathological features rarely have been analyzed simultaneously from the start of dissimilar psychotic illnesses, we compared symptom-clusters in first-episode DSM-IV affective and non-affective psychotic disorders. Methods Subjects ( N = 377) from the McLean–Harvard First Episode Project hospitalized for first-lifetime primary psychotic illnesses were followed prospectively for 2 years to verify stable DSM-IV diagnoses. We ascertained initial symptoms from baseline SCID and clinical assessments, applying AMDP and Bonn psychopathology schemes systematically to describe a broad range of features. Final consensus diagnoses were based on intake and follow-up SCID assessments, family interviews, and medical records. Factor-analytic methods defined first-episode symptom-clusters (Factors), and multiple-regression modeling related identified factors to initial DSM-IV diagnoses and to later categories ( affective, non-affective, or schizoaffective disorders). Results Psychopathological features were accommodated by four factors: I represented mania with psychosis; II a mixed depressive-agitated state; III an excited-hallucinatory-delusional state; IV a disorganized-catatonic-autistic state. Each factor was associated with characteristic prodromal symptoms. Factors I and III associated with DSM-IV mania, II with major depression or bipolar mixed-state, III negatively with delusional disorder, IV with major depression and negatively with mania. Factors I and II predicted later affective diagnoses; absence of Factor I features predicted non-affective diagnoses, and no Factor predicted later schizoaffective diagnoses. Conclusion The findings contribute to descriptive categorizations of psychopathology from onset of dissimilar psychotic illnesses. This approach was effective in identifying and subtyping affective psychotic disorders early in their clinical evolution, but non-affective and schizoaffective conditions appear to be more complex and unstable.
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