Mortality and associated factors in Cuban HIV-infected patients
DOI:
https://doi.org/10.51481/amc.v64i4.1207Keywords:
HIV, AIDS, mortality, factors associated with mortality, binary logistic regressionAbstract
Aim: To determine the main causes of death and associated factors in HIV-infected patients admitted to the Tropical Medicine Institute ""Pedro Kourí"" hospital during the years 2017-2018.
Methods: A retrospective case-control study was carried out to determine the causes of death and some factors associated with it, in the Tropical Medicine Institute ""Pedro Kourí"" hospital, in the period 2017-2018. To determine these factors, a multivariate analysis based on a binary logistic regression model was used.
Results: The most frequent causes of death were those associated with AIDS, mainly opportunistic infections of the respiratory system (41.4%), followed by neoplasms not associated with AIDS (25.1%). The factors that had the greatest influence on mortality were the presence of opportunistic disease (OR 14.07 p <0.001) and neoplasms not associated with AIDS (OR 6.76 p = 0.005), alteration of renal functions (3, 54 p = 0.019) and liver (OR 2.90 p = 0.054) and have a higher viral load (OR 1.50 p = 0.001) and less time to diagnosis at admission (OR 0.793 p <0.001). The mathematical model resulting from the analysis made it possible to identify the main factors associated with mortality and explain their relationship with it.
Conclusions: AIDS-associated diseases, mainly opportunistic infections of the respiratory system, followed by non-AIDS-associated neoplasms were the predominant causes of death in HIV-infected patients who died in the Tropical Medicine Institute ""Pedro Kourí"" during the study period. The presence of neoplasms not associated with AIDS, opportunistic diseases, alterations in kidney and liver functions, increased viral load and having fewer years of diagnosis at the time of admission, were the factors that most contributed to mortality in patients admitted and infected with HIV. The resulting mathematical model fitted the data well and consistently explained the factors associated with mortality.
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