Determinants of hospital length of stay for schizophrenia: retrospective negative binomial analysis in a university hospital

影响精神分裂症患者住院时间的因素:大学医院回顾性负二项式分析

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Abstract

BACKGROUND: Limited data exist on factors influencing the length of hospital stay (HLoS) in patients with schizophrenia. AIMS: This study aimed to identify and quantify patient characteristics associated with HLoS. METHOD: A retrospective study was conducted on patients diagnosed with schizophrenia (F20, ICD-10) admitted to the County Emergency Hospital of Cluj-Napoca, Romania, from 2018 to 2022. Demographics, comorbidities, symptom severity (Positive and Negative Syndrome Scale/Brief Psychiatric Rating Scale), antipsychotic treatment and adverse effects data were collected from medical charts. Predictors of HLoS for patients with one hospitalisation were assessed using negative binomial regression. RESULTS: The sample comprised 288 patients aged 18-65 years, with 75% over 30 years and a balanced gender distribution. Most patients had no comorbidities (64.24%) whereas 49.46% reported addictions. Men had higher rates of tobacco use (62.00 v. 53.49%) and self-reported use of substances/drugs (15.49 v. 3.91%). Independent predictors of HLoS (P < 0.05) in the multivariable model included gender, being retired, experiencing fear or violence in the context of psychotic decompensation, percentage score reduction in symptom severity score, first-generation antipsychotics treatment and the presence of reasons for late discharge. Men had an expected HLoS 39% longer than women. Experiencing fear (adjusted incidence rate ratio (aIRR) 1.13, 95% CI [1.01; 1.27]) and violence in the context of psychotic decompensation (aIRR 1.19, 95% CI [1.06; 1.34]), and first-generation antipsychotics treatment (aIRR 1.17, 95% CI [1.02; 1.35]) were associated with longer stay, whereas being retired predicted shorter HLoS (aIRR 0.83, 95% CI [0.70; 0.98]). CONCLUSIONS: The length of hospital stay in patients with schizophrenia is influenced by demographic, clinical and treatment factors. Targeted interventions addressing these predictors may optimise the duration of hospitalisation.

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