Dataset Information

Clozapine treatment and risk of severe COVID-19 infection.

ABSTRACT:

Objective

To investigate whether patients with clozapine treatment are at an increased risk of a more severe COVID-19 infection as compared with patients on other antipsychotic drugs.

Methods

In this register-based cohort study, all residents (age 18 or older) in the Stockholm Region with a psychotic disorder diagnosis and antipsychotic treatment were included (N = 8 233) and followed from 1 March 2020 to 14 January 2021. The exposure was defined as clozapine treatment and the outcome measures (indicating a more severe COVID-19 infection) were: inpatient care, care within intensive care unit or death due to COVID-19 infection. Differences in outcome rates between exposed (n = 966) and unexposed (other antipsychotics; n = 7 267) were examined using Cox proportional hazards models and expressed as hazard ratios (HR) with 95% confidence intervals (CI).

Results

No statistically significant differences in outcome rates were found between the two groups of patients after adjusting for age, sex and residence in retirement homes. The adjusted HR for the exposed compared to the unexposed was 0.96 (95% CI: 0.54, 1.70) for inpatient care; 1.69 (0.48, 5.93) for care in intensive care unit (ICU); and 0.86 (0.26, 2.80) for death. Regarding inpatient care, additional adjusting for country of birth, living in socioeconomically vulnerable areas, number of care visits during the previous year, and comorbid medical illnesses did not alter the results.

Conclusions

Our results may add support to the present guidelines, recommending sustained clozapine treatment during the current COVID-19 pandemic with careful monitoring and readiness to alter drug doses as needed.

SUBMITTER: Ohlis A

PROVIDER: S-EPMC8653206 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAbout 10-20% of patients with Coronavirus disease 2019 (COVID-19) infection progressed to severe illness within a week or so after initially diagnosed as mild infection. Identification of this subgroup of patients was crucial for early aggressive intervention to improve survival. The purpose of this study was to evaluate whether computer tomography (CT) - derived measurements of body composition such as myosteatosis indicating fat deposition inside the muscles could be used to predict the risk of transition to severe illness in patients with initial diagnosis of mild COVID-19 infection.MethodsPatients with laboratory-confirmed COVID-19 infection presenting initially as having the mild common-subtype illness were retrospectively recruited between January 21, 2020 and February 19, 2020. CT-derived body composition measurements were obtained from the initial chest CT images at the level of the twelfth thoracic vertebra (T12) and were used to build models to predict the risk of transition. A myosteatosis nomogram was constructed using multivariate logistic regression incorporating both clinical variables and myosteatosis measurements. The performance of the prediction models was assessed by receiver operating characteristic (ROC) curve including the area under the curve (AUC). The performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve.ResultsA total of 234 patients were included in this study. Thirty-one of the enrolled patients transitioned to severe illness. Myosteatosis measurements including SM-RA (skeletal muscle radiation attenuation) and SMFI (skeletal muscle fat index) score fitted with SMFI, age and gender, were significantly associated with risk of transition for both the training and validation cohorts (P < 0.01). The nomogram combining the SM-RA, SMFI score and clinical model improved prediction for the transition risk with an AUC of 0.85 [95% CI, 0.75 to 0.95] for the training cohort and 0.84 [95% CI, 0.71 to 0.97] for the validation cohort, as compared to the nomogram of the clinical model with AUC of 0.75 and 0.74 for the training and validation cohorts respectively. Favorable clinical utility was observed using decision curve analysis.ConclusionWe found CT-derived measurements of thoracic myosteatosis to be associated with higher risk of transition to severe illness in patients affected by COVID-19 who presented initially as having the mild common-subtype infection. Our study showed the relevance of skeletal muscle examination in the overall assessment of disease progression and prognosis of patients with COVID-19 infection.