Prediction of symptom remission in schizophrenia during inpatient treatment

Abstract

Objective: Standardized consensus criteria for remission in schizophrenia were recently proposed. The present study applied the symptom-severity component of these criteria to a sample of inpatients in order to determine the rates of remission during inpatient treatment and to explore predictors of remission. Method: A total of 288 inpatients from a multi-centre follow-up programme who fulfilled ICD-10 criteria for schizophrenia were included in the present analyses. PANSS ratings at admission and at discharge from hospitalization were used to examine remission status. Clinical and sociodemographic variables at admission were tested for their ability to predict remission at discharge. Results: In total, 55% of the sample achieved symptom remission during inpatient treatment; 84% percent showed remission with respect to ‘reality distortion’, 85% with respect to ‘disorganization’ and only 65% with respect to ‘negative symptoms’. Logistic regression analysis revealed that the global functioning (GAF) in the year before admission, the total score of the Strauss–Carpenter Prognostic Scale and the PANSS negative subscore at admission were predictive for symptom remission. The regression model showed a predictive value of about 70% and explained 36% of the observed variance. Conclusion: The results highlight the impact of negative symptoms for the course and treatment response of schizophrenic illness.