Predicting COVID-19 outcomes in patients at advanced stages of HIV infection: a model-based approach

Author:

Tsygankova Anna E.ORCID,Chulanov Vladimir P.ORCID,Gerasimov Andrey N.ORCID,Volchkova Elena V.ORCID,Privalenko Anton A.ORCID,Bakhtina Viktoriya A.ORCID,Khabudaev Vladimir A.,Baimukhambetova Dina V.ORCID

Abstract

BACKGROUND: Today, clinicians and their decisions extensively rely on specific treatment algorithms. These algorithms include prognostic models to identify high risk patients requiring hospital admission and clinical monitoring. This study suggests a prognostic model for forecasting COVID-19 outcomes in patients with advanced HIV infection, considering the high risk of unfavorable outcomes and the need for a specialized approach. AIM: To develop a prognostic model that combines predictors of unfavorable COVID-19 outcomes in patients with advanced HIV infection. MATERIALS AND METHODS: The study was based on 500 medical records of patients with advanced HIV infection admitted for confirmed COVID-19 between March 1, 2020, and December 31, 2022, and inpatient treatment at the Infectious Diseases Hospital in Moscow. RESULTS: All 500 patients were evaluated for 167 predictive markers for unfavorable COVID-19 outcomes, outlining 50 indicators that significantly varied across the subgroups of patients with both advanced HIV infection and COVID-19 depending on the presence of favorable or poor outcomes. Oxygen therapy was the most significant factor showing a strong correlation with poor outcomes in patients with advanced HIV infection and COVID-19. Subsequently, predictors were selected stepwise to enhance the predictive accuracy of the resulting model by adding more factors. The resulting model included seven factors: oxygen therapy requirements, CD4+ count under 50 cells/μL; manifested CMV infection with lung damage; elevated levels of lactate dehydrogenase, urea, and fibrinogen; and the presence of unspecified encephalitis. Using the available data in the calculations, a prognostic scenario and a receiver operating characteristic (ROC) curve were created to assess the practical significance of the proposed prognostic model. The area under the ROC curve was 90.9%, confirming the prediction accuracy and overall practical significance of the model. CONCLUSIONS: The proposed prognostic model enables the assessment of potential outcomes and planning of adequate therapies in patients with HIV and COVID-19 co-infection admitted to hospitals at advanced stages of the disease.

Publisher

ECO-Vector LLC

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