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Fig. 1 | Annals of General Psychiatry

Fig. 1

From: Cardiometabolic comorbidities, readmission, and costs in schizophrenia and bipolar disorder: a real-world analysis

Fig. 1

Length of stay, 30-day all-cause readmission, and hospital mortality by number of cardiometabolic comorbidities. a The mean length of stay was 8.5 days for overall patients with schizophrenia and 5.2 days for patients with bipolar disorder. Negative binomial regressions showed a negative association between cardiometabolic comorbidity burden with length of stay for schizophrenia (−.015; 95% CI −.024, −.007, p < .001), but a positive association for bipolar disorder (.029; 95% CI .024, .034, p < .001). b Overall, 11.8% of the patients with schizophrenia and 9.3% of the patients with bipolar disorder were readmitted for any reason within 30 days of discharge from the index hospitalization. For each additional cardiometabolic comorbidity, logistic regressions showed the odds of readmission increased by 3.1% (OR 1.031; 95% CI 1.001, 1.061, p = .042) for schizophrenia and by 6.4% (OR 1.064; 95% CI 1.041, 1.087, p < .001) for bipolar disorder. c The index hospitalization mortality rate was 1.2% for overall patients with schizophrenia and .7% for patients with bipolar disorder. In schizophrenia, cardiometabolic comorbidity was not significantly associated with mortality (OR 1.014; 95% CI .937, 1.098, p = .727). A Chi square test showed that patients with schizophrenia who had one or more cardiometabolic comorbidities had a higher risk of mortality compared to those with no comorbidities (1.7 vs. .3%, p < .001). In bipolar disorder, each additional cardiometabolic comorbidity was associated with a 21.8% increase in mortality during the index hospitalization (OR 1.218; 95% CI 1.129, 1.314, p < .001). A Chi square test showed that patients with bipolar disorder who had one or more cardiometabolic comorbidities had a higher risk of mortality compared to those with no comorbidities (1.45 vs. .10%, p < .001). * The following covariates were included in all regression analyses: age, gender, race, payer, CCI, hospital region, hospital location (urban/rural), hospital type (teaching/non-teaching), and hospital bed count

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