Despite of the heightened risks and burdens of physical comorbidities across the entire schizophrenia spectrum disorders (SSD), relatively little is known about physical multimorbidity (CPM) in this population. The study’s main objective was to explore the differences in the CPM prevalence between SSD patients and the general population (GEP).

The primary outcome was to explore the difference in CPM prevalence in the younger SSD and GEP groups (<35 years).The secondary outcome was the number of psychiatric readmissions.

This nested cross-sectional study enrolled 343 SSD patients and 620 GEP participants.

Younger SSD patients had more than three-fold higher odds for CPM than GEP. We also demonstrated an association between the presence of CPM and the number of psychiatric admissions in the SSD population independently of possible confounders. We did not observe significant interaction of CPM and age in the prediction of clozapine use. Younger women with SSD had statistically significant, almost four-fold higher odds of CPM than women from GEP.

This study suggests that women with SSD are at increased physical comorbidity risk compared to men, particularly early in the course of psychiatric illness. Our results highlight the importance of addressing physical health from the first contact with a mental health service to preserve general health, and provide the best possible treatment outcome. Treatment of SSD must be customized to meet the needs of patients with different physical multimorbidity patterns.

No significant relationships.

Unplanned readmissions rates are an important indicator of the quality of care provided in a psychiatric unit. However, there is no validated risk model to predict this outcome in patients with psychotic spectrum disorders.

This paper aims to establish a clinical risk prediction model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders.

Adult patients with psychotic spectrum disorders discharged within a 5-year period from all psychiatric units in Hong Kong were included in this study. Information on the socioeconomic background, past medical and psychiatric history, current discharge episode and Health of the Nation Outcome Scales (HoNOS) scores were used in a logistic regression to derive the risk model and the predictive variables. The sample was randomly split into two to derive (n = 10 219) and validate (n = 10 643) the model.

The rate of unplanned readmission was 7.09%. The risk factors for unplanned readmission include higher number of previous admissions, comorbid substance misuse, history of violence and a score of one or more in the discharge HoNOS overactivity or aggression item. Protective factors include older age, prescribing clozapine, living with family and relatives after discharge and imposition of conditional discharge. The model had moderate discriminative power with a c-statistic of 0.705 and 0.684 on the derivation and validation data-set.

The risk of readmission for each patient can be identified and adjustments in the treatment for those with a high risk may be implemented to prevent this undesirable outcome.