Evaluation of Factors Related to Survival Time in HIV-Infected Persons in Mashhad, Iran, Between 1994 - 2014: A Bayesian Joint Model

Shabani, Niloofar; Esmaily, Habibollah; Alimi, Rasul; Roknabadi, Abdolhamid Rezaei

doi:10.5812/iji.91712

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…CD4 cells are a major target for HIV patients, the virus binds to the surface of CD4 cells, enters them, and either replicates immediately, killing the cells in the process, or remains in a resting state, replicating later [ 13 ]. For healthy adult peoples CD4 cell count in the normal range between 500 and 1500 cells/mm 3 .Otherwise, an indication of immunological failure of patients whose CD4 cell count less than 500 cells/mm 3 and HIV strongly affects the immune system below 100 cells/mm 3 [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Predictors for CD4 cell count and hemoglobin level with survival time to default for HIV positive adults under ART treatment at University of Gondar Comprehensive and Specialized Hospital, Ethiopia

Muhie,

Tegegne

2023

BMC Res Notes

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Background HIV/AIDS is the most known powerful risk factor for morbidity and mortality in the world. The greatest biological markers in HIV patients are CD4 cell count and hemoglobin level, as they are independent predictors of survival of HIV patients. The objective of this study was to investigate the common socio-demographic, clinical, and behavioral Predictor’s affecting the CD4 cell count, and hemoglobin level with survival time to default from ART treatment among HIV positive adults under ART treatment at university of Gondar comprehensive and specialized hospital, North-west Ethiopia. Method This study was conducted at University of Gondar comprehensive specialized hospital by using a retrospective cohort follow up study design. The source of data in this study was secondary data obtained from patients chart. Bayesian joint models were employed to get wide-ranging information about HIV/AIDS progression. Result From a total of 403 HIV positive adults, about 44.2% were defaulted from therapy and the rest were actively followed ART treatment. The estimate of the association parameter for the current true value of CD4 cell count ($${\alpha }_{1}$$ α 1 ), and hemoglobin level ($${\alpha }_{2}$$ α 2 ), trend of CD4 cell count ($${\alpha }_{2}$$ α 2 ) and hemoglobin level ($${b}_{2}$$ b 2 ) is positive. Positive values indicating that the higher CD4 cell count and hemoglobin level is related with the higher time of defaulting from ART. Predictor’s hematocrit, weight, platelet cell count, lymphocyte count, sex, adherence, and WHO clinical stage were joint determinate risk factors affecting CD4 cell count, hemoglobin level and time to default at 5% level of significance. Conclusion Current study results revealed that hematocrit, weight, BMI, platelet cell count, lymphocyte count, sex (female), and good treatment adherence were significantly associated with higher CD4 cell count, hemoglobin level and time to default while having advanced WHO clinical stage-IV had significantly decreased CD4 cell, hemoglobin level, and time to default from treatment. Patients with HIV should be given special attention based on these important factors to improve their health and prolong their lives.

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Section: Introductionmentioning

confidence: 99%

Predictors for CD4 cell count and hemoglobin level with survival time to default for HIV positive adults under ART treatment at University of Gondar Comprehensive and Specialized Hospital, Ethiopia

Muhie,

Tegegne

2023

BMC Res Notes

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Evaluation of factors related to longitudinal CD4 count and the risk of death among HIV-infected patients using Bayesian joint models

Pilangorgi,

khodakarim,

Nejat

2024

Preprint

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Background In many epidemiological HIV studies, patients are frequently monitored over time to predict their survival by examining their CD4 levels repeatedly. This study aims to evaluate factors related to longitudinal CD4 count and the risk of death among HIV-infected patients using Bayesian joint models. Methods The information of patients who were infected with HIV in Fars Province, from 2011–2016 and followed up until 2022 was used in this study. A joint model of count longitudinal outcome and time to death is used to model information of HIV patients. Results The majority of patients were male (64.8%) with a median age of 35 years. During the follow-up, 123 patients (19%) died. The age-standardized mortality and incidence rates from 2011 to 2016 were 0.496 and 2.49 per 100000 person-years respectively. The 1-year and 5-year survival rates are 98% (95%CI: 97%, 99%) and 88% (95%CI: 85%, 91%) respectively. There is a significant association in this model between the CD4 cell count and the risk of death. Age, addiction, and unemployment were all significantly linked to a lower CD4 cell count. Age was positively correlated with the risk of death. Men, unemployed individuals, and those with hepatitis B had a higher risk of death. Conclusion In this study, we used the Bayesian joint model to investigate the association between the risk of death and the change in CD4 biomarkers that is repeatedly measured over time to determine the factors associated with the survival of HIV-infected persons. The joint model finds a strong association between the CD4 cell count and the risk of death. The joint model allows for a more comprehensive understanding of the factors influencing the CD4 cell count and survival time, compared to using separate models.

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Evaluation of Factors Related to Survival Time in HIV-Infected Persons in Mashhad, Iran, Between 1994 - 2014: A Bayesian Joint Model

Cited by 2 publications

References 16 publications

Predictors for CD4 cell count and hemoglobin level with survival time to default for HIV positive adults under ART treatment at University of Gondar Comprehensive and Specialized Hospital, Ethiopia

Predictors for CD4 cell count and hemoglobin level with survival time to default for HIV positive adults under ART treatment at University of Gondar Comprehensive and Specialized Hospital, Ethiopia

Evaluation of factors related to longitudinal CD4 count and the risk of death among HIV-infected patients using Bayesian joint models

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