학술논문
Incidence and severity prediction score of COVID-19 in people living with HIV (SCOVHIV): experience from the first and second waves of the pandemic in Indonesia.
Document Type
Article
Author
Source
Subject
*HIV-positive persons
*DISEASE progression
*EXPERIMENTAL design
*HOSPITALS
*OPPORTUNISTIC infections
*COVID-19
*CONFIDENCE intervals
*RESEARCH methodology
*MULTIPLE regression analysis
*MORTALITY
*RETROSPECTIVE studies
*DISEASE incidence
*ANTIRETROVIRAL agents
*SEVERITY of illness index
*RISK assessment
*CD4 lymphocyte count
*DESCRIPTIVE statistics
*SENSITIVITY & specificity (Statistics)
*COVID-19 pandemic
*LONGITUDINAL method
*COMORBIDITY
*PROBABILITY theory
*EVALUATION
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Language
ISSN
1742-6405
Abstract
Background: People living with HIV (PLHIV) have higher risk of COVID-19 infection and mortality due to COVID-19. Health professionals should be able to assess PLHIV who are more likely to develop severe COVID-19 and provide appropriate medical treatment. This study aimed to assess clinical factors associated with COVID-19 severity and developed a scoring system to predict severe COVID-19 infection among PLHIV. Methods: This retrospective cohort study evaluated PLHIV at four hospitals diagnosed with COVID-19 during the first and second wave COVID-19 pandemic in Indonesia. The independent risk factors related to the severity of COVID-19 were identified with multivariate logistic regression. Results: 342 PLHIV were diagnosed with COVID-19, including 23 with severe-critical diseases. The cumulative incidence up to December 2021 was 0.083 (95% CI 0.074–0.092). Twenty-three patients developed severe-critical COVID-19, and the mortality rate was 3.2% (95% CI 1.61%–5.76%). Having any comorbidity, CD4 count of < 200 cells/mm3, not being on ART, and active opportunistic infection were independent risk factors for developing severe COVID-19. SCOVHIV score was formulated to predict severity, with 1 point for each item. A minimum score of 3 indicated a 58.4% probability of progressing to severe COVID-19. This scoring system had a good discrimination ability with the area under the curve (AUC) of 0.856 (95% CI 0.775–0.936). Conclusion: SCOVHIV score, a four-point scoring system, had good accuracy in predicting COVID-19 severity in PLHIV. [ABSTRACT FROM AUTHOR]