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Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study.

ABSTRACT: Patients with schizophrenia (SCZ) represent a vulnerable population who have been understudied in COVID-19 research. We aimed to establish whether health outcomes and care differed between patients with SCZ and patients without a diagnosis of severe mental illness. We conducted a population-based cohort study of all patients with identified COVID-19 and respiratory symptoms who were hospitalized in France between February and June 2020. Cases were patients who had a diagnosis of SCZ. Controls were patients who did not have a diagnosis of severe mental illness. The outcomes were in-hospital mortality and intensive care unit (ICU) admission. A total of 50 750 patients were included, of whom 823 were SCZ patients (1.6%). The SCZ patients had an increased in-hospital mortality (25.6% vs 21.7%; adjusted OR 1.30 [95% CI, 1.08-1.56], P = .0093) and a decreased ICU admission rate (23.7% vs 28.4%; adjusted OR, 0.75 [95% CI, 0.62-0.91], P = .0062) compared with controls. Significant interactions between SCZ and age for mortality and ICU admission were observed (P = .0006 and P < .0001). SCZ patients between 65 and 80 years had a significantly higher risk of death than controls of the same age (+7.89%). SCZ patients younger than 55 years had more ICU admissions (+13.93%) and SCZ patients between 65 and 80 years and older than 80 years had less ICU admissions than controls of the same age (-15.44% and -5.93%, respectively). Our findings report the existence of disparities in health and health care between SCZ patients and patients without a diagnosis of severe mental illness. These disparities differed according to the age and clinical profile of SCZ patients, suggesting the importance of personalized COVID-19 clinical management and health care strategies before, during, and after hospitalization for reducing health disparities in this vulnerable population.

SUBMITTER: Fond G

PROVIDER: S-EPMC7665717 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMultiple factors contribute to mortality after ICU, but it is unclear how the predictive value of these factors changes during ICU admission. We aimed to compare the changing performance over time of the acute illness component, antecedent patient characteristics, and ICU length of stay (LOS) in predicting 1-year mortality.MethodsIn this retrospective observational cohort study, the discriminative value of four generalized mixed-effects models was compared for 1-year and hospital mortality. Among patients with increasing ICU LOS, the models included (a) acute illness factors and antecedent patient characteristics combined, (b) acute component only, (c) antecedent patient characteristics only, and (d) ICU LOS. For each analysis, discrimination was measured by area under the receiver operating characteristics curve (AUC), calculated using the bootstrap method. Statistical significance between the models was assessed using the DeLong method (p value <?0.05).ResultsIn 400,248 ICU patients observed, hospital mortality was 11.8% and 1-year mortality 21.8%. At ICU admission, the combined model predicted 1-year mortality with an AUC of 0.84 (95% CI 0.84-0.84). When analyzed separately, the acute component progressively lost predictive power. From an ICU admission of at least 3 days, antecedent characteristics significantly exceeded the predictive value of the acute component for 1-year mortality, AUC 0.68 (95% CI 0.68-0.69) versus 0.67 (95% CI 0.67-0.68) (p value <?0.001). For hospital mortality, antecedent characteristics outperformed the acute component from a LOS of at least 7 days, comprising 7.8% of patients and accounting for 52.4% of all bed days. ICU LOS predicted 1-year mortality with an AUC of 0.52 (95% CI 0.51-0.53) and hospital mortality with an AUC of 0.54 (95% CI 0.53-0.55) for patients with a LOS of at least 7 days.ConclusionsComparing the predictive value of factors influencing 1-year mortality for patients with increasing ICU LOS, antecedent patient characteristics are more predictive than the acute component for patients with an ICU LOS of at least 3 days. For hospital mortality, antecedent patient characteristics outperform the acute component for patients with an ICU LOS of at least 7 days. After the first week of ICU admission, LOS itself is not predictive of hospital nor 1-year mortality.

Project description:BACKGROUND:Admission to the intensive care unit (ICU) outside daytime hours has been shown to be variably associated with increased morbidity and mortality. We aimed to describe the characteristics and outcomes of patients admitted to the ICU afterhours (22:00-06:59 h) in a large Canadian health region. We further hypothesized that the association between afterhours admission and mortality would be modified by indicators of strained ICU capacity. METHODS:This is a population-based cohort study of 12,265 adults admitted to nine ICUs in Alberta from June 2012 to December 2014. We used a path-analysis modeling strategy and mixed-effects multivariate regression analysis to evaluate direct and integrated associations (mediated through Acute Physiology and Chronic Health Evaluation (APACHE) II score) between afterhours admission (22:00-06:59 h) and ICU mortality. Further analysis examined the effects of strained ICU capacity and varied definitions of afterhours and weekend admissions. ICU occupancy ? 90% or clustering of admissions (??0.15, defined as number of admissions 2 h before or after the index admission, divided by the number of ICU beds) were used as indicators of strained capacity. RESULTS:Of 12,265 admissions, 34.7% (n?=?4251) occurred afterhours. The proportion of afterhours admissions varied amongst ICUs (range 26.7-37.8%). Patients admitted afterhours were younger (median (IQR) 58 (44-70) vs 60 (47-70) years, p?<?0.0001), more likely to have a medical diagnosis (75.9% vs 72.1%, p?<?0.0001), and had higher APACHE II scores (20.9 (8.6) vs 19.9 (8.3), p?<?0.0001). Crude ICU mortality was greater for those admitted afterhours (15.9% vs 14.1%, p?=?0.007), but following multivariate adjustment there was no direct or integrated effect on ICU mortality (odds ratio (OR) 1.024; 95% confidence interval (CI) 0.923-1.135, p?=?0.658). Furthermore, direct and integrated analysis showed no association of afterhours admission and hospital mortality (p?=?0.90) or hospital length of stay (LOS) (p?=?0.27), although ICU LOS was shorter (p?=?0.049). Early-morning admission (00:00-06:59 h) with ICU occupancy ? 90% was associated with short-term (??7 days) and all-cause ICU mortality. CONCLUSIONS:One-third of critically ill patients are admitted to the ICU afterhours. Afterhours ICU admission was not associated with greater mortality risk in most circumstances but was sensitive to strained ICU capacity.

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Disparities in Intensive Care Unit Admission and Mortality Among Patients With Schizophrenia and COVID-19: A National Cohort Study.

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