A Predictive Scoring Model for Perioperative Psychiatric Symptom Exacerbation in Schizophrenia Spectrum Disorders:...

Area of Science:

• Psychiatry
• Surgical Care
• Medical Informatics

Background:

• Patients with schizophrenia spectrum disorders (SSD) face significant risks of psychiatric deterioration during the perioperative period.
• Existing research has studied delirium and non-delirious psychiatric worsening separately, lacking an integrated prediction tool for SSD patients.
• Perioperative psychiatric complications can complicate medical and surgical care in general hospitals.

Purpose of the Study:

• To develop and internally validate a predictive scoring tool for perioperative psychiatric symptom exacerbation in patients with SSD.
• To identify key predictors of psychiatric deterioration in this vulnerable patient population undergoing surgery.

Main Methods:

• A retrospective multicenter registry study involving 200 patients with SSD undergoing surgery at three Japanese general acute care hospitals.
• Perioperative psychiatric symptom exacerbation was defined by specific criteria including medication changes, restraints, or transfer to a psychiatric ward.
• Multivariable logistic regression identified predictors, and a simplified scoring system was developed and validated using bootstrap resampling.

Main Results:

• Perioperative psychiatric symptom exacerbation occurred in 12.5% of patients.
• Key predictors identified were emergency surgery, operative time ≥180 minutes, and admission from another facility.
• The simplified score (0-3) demonstrated acceptable discrimination (AUC 0.741) with high sensitivity (88.0%) and negative predictive value (95.5%) at a cut-off score of ≥1.

Conclusions:

• A preliminary scoring model shows promise as a perioperative triage-support tool for patients with SSD.
• The model's high sensitivity and negative predictive value suggest utility in ruling out high-risk patients.
• Further external validation is necessary before widespread clinical implementation.