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Barthel’s Index: a better predictor for COVID-19 mortality than comorbidities

Tuberc Respir Dis (Seoul). 2022 Jun 23. doi: 10.4046/trd.2022.0006. Online ahead of print.


BACKGROUND: The most consistent identified mortality determinants for the new coronavirus 2019 infection (COVID-19) are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous condition. The main goal of our study was to test if activities of daily living (ADL) dependence measured by Barthel’s index could be a predictor for COVID-19 mortality.

METHODS: Prospective cohort study with a consecutive sample of 340 COVID-19 patients representing patients from all over the Northern region of Portugal from 10/2020 to 03/2021. Mortality risk factors were determined controlling for demographics, activities of daily living (ADL) dependence, admission time, comorbidities, clinical manifestations, and delay-time for diagnosis. Central tendency measures were used to analyze continuous variables and absolute numbers (proportions) for categorical variables. For univariable analysis we used T-Test/Chi-Square/Fisher Exact Test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. Statistical software: IBM®SPSS®27.

RESULTS: The cohort included 340 patients (55.3% females, mean age 80.6±11.0) with a mortality rate of 19.7%. Aging, ADL dependence, pneumonia and dementia were associated with mortality and dyslipidemia and obesity with survival in univariate analysis. In multivariable analysis dyslipidemia (OR=0.35, 95%CI:0.17-0.71) was independently associated with survival. Age ≥ 86-year-old (pooled OR 2.239, 95% CI: 1.100-4.559), pneumonia (pooled OR 3.00, 95% CI: 1.362-6.606), and ADL dependence (pooled OR 6.296, 95% CI: 1.795-22.088) were significantly related to mortality (ROC AUC=82.1% (p<0.0001)).

CONCLUSION: ADL dependence, aging and pneumonia are the 3 main COVID-19 mortality predictors among an elderly population.

PMID:35734879 | DOI:10.4046/trd.2022.0006

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