Abstract
PURPOSE: Acute and transient psychotic disorder (ATPD), a psychosis frequently diagnosed, can potentially evolve into chronic conditions like schizophrenia (SCZ) and other mental disorders. This study aimed to develop a predictive model based on clinical data to forecast the transition from ATPD to SCZ and to identify the predictive factors. METHODS: According to the diagnostic criteria issued by the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10), 396 inpatients diagnosed with ATPD were collected in this study. The Cox proportional-hazards regression model was performed using demographic data, clinical characteristics, and inflammatory markers to identify independent predictors for subsequent diagnostic transition (SDT) to SCZ. RESULTS: During the follow-up period, 43.69% (n = 173) of ATPD patients had their diagnoses revised to SCZ. The multivariate Cox regression analysis identified post-treatment monocyte count, post-treatment monocyte/lymphocyte ratio (MLR), and the presence of schizophreniform symptoms as significant predictors for the diagnostic revision. Time-dependent receiver operating characteristic (TimeROC) analyses were developed. The AUC value at the 5-year follow-up was 0.728 for combined predictors, 0.702 for post-treatment monocyte count, 0.764 for post-treatment MLR, and 0.535 for the presence of schizophreniform symptoms. CONCLUSION: The combined predictors had good predictive ability for the diagnostic transition from acute and transient psychotic disorder to schizophrenia.