Tuberc Respir Dis > Epub ahead of print
DOI:    [Epub ahead of print]
Published online June 23, 2022.
Barthel’s Index: A Better Predictor for COVID-19 Mortality Than Comorbidities
João Cordeiro da Costa, M.D., M.Sc.1,2  , Maria Conceição Manso, Ph.D.3, Susana Gregório, M.Sc.1,4, Márcia Leite, M.D.1, João Moreira Pinto, M.D., Ph.D.1,5
1Hospital-Escola da Universidade Fernando Pessoa, Gondomar, Portugal
2Center for Innovative Care and Health Technology (ciTechCare), Polytechnic Institute of Leiria, Leiria, Portugal
3FP-I3ID (FP-ENAS), Faculdade de Ciências da Saúde, Universidade Fernando Pessoa, Gondomar, Portugal
4Escola Superior de Saúde/Faculdade de Ciências da Saúde, Universidade Fernando Pessoa, Gondomar, Portugal
5Instituto de Saúde Pública da Universidade do Porto (ISPUP), Porto, Portugal
Correspondence:  João Cordeiro da Costa, Tel: 351-222455455, Fax: 351-222455499, 
Received: 21 January 2022   • Revised: 13 May 2022   • Accepted: 13 June 2022
The most consistently identified mortality determinants for the new coronavirus 2019 (COVID-19) infection are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous conditions. The main goal of this study was to determine if activities of daily living (ADL) dependence measured by Barthel’s index could be a predictor for COVID-19 mortality.
A prospective cohort study was performed with a consecutive sample of 340 COVID-19 patients representing patients from all over the northern region of Portugal from October 2020 to March 2021. Mortality risk factors were determined after controlling for demographics, 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 test, or Fisher exact test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. IBM SPSS version 27 statistical software was used for data analysis.
The cohort included 340 patients (55.3% females) with a mean age of 80.6±11.0 years. The mortality rate was 19.7%. Univariate analysis revealed that aging, ADL dependence, pneumonia, and dementia were associated with mortality and that dyslipidemia and obesity were associated with survival. In multivariable analysis, dyslipidemia (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.17–0.71) was independently associated with survival. Age ≥86 years (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 (receiver operating characteristic area under the curve, 82.1%; p<0.001).
ADL dependence, aging, and pneumonia are three main predictors for COVID-19 mortality in an elderly population.
Key Words: COVID-19, Infections, Mortality, Elderly, Frailty
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