Impact of social determinants on antiretroviral therapy access and outcomes entering the era of universal treatment for people living with HIV in Italy

Saracino, Annalisa; Zaccarelli, Mauro; Lorenzini, Patrizia; Bandera, Alessandra; Marchetti, Giulia; Castelli, Francesco; Gori, Andrea; Girardi, Enrico; Mussini, Cristina; Bonfanti, Paolo; Ammassari, Adriana; Monforte, Antonella d’Arminio

doi:10.1186/s12889-018-5804-z

Cited by 21 publications

(20 citation statements)

References 24 publications

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“…This might be due to literate patients having work capacity, financial resources, and access to quality health care. Patients in the middle-aged group were significantly decelerating time to immunological deterioration compared with those older patients, a finding that is in accordance with the literature [40,41], which noted that middle-aged adults experienced higher rates of CD4 recovery than the elderly. Furthermore, patients with many sex partners were significantly decelerating the recovery from severe to advanced stages compared with those with no sexual partner.…”

Section: Discussionsupporting

confidence: 90%

Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model

Dessie

Zewotir

Mwambi

et al. 2020

Theor Biol Med Model

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Background: HIV infected patients may experience many intermediate events including between-event transition throughout their follow up. Through modelling these transitions, we can gain a deeper understanding of HIV disease process and progression and of factors that influence the disease process and progression pathway. In this work, we present transition-specific parametric multi-state models to describe HIV disease process and progression. Methods: The data is from an ongoing prospective cohort study conducted amongst adult women who were HIVinfected in KwaZulu-Natal, South Africa. Participants were enrolled during the acute HIV infection phase and then followed up during chronic infection, up to ART initiation. Results: Transition specific distributions for multi-state models, including a variety of accelerated failure time (AFT) models and proportional hazards (PH) models, were presented and compared in this study. The analysis revealed that women enrolling with a CD4 count less than 350 cells/mm 3 (severe and advanced disease stages) had a far lower chance of immune recovery, and a considerably higher chance of immune deterioration, compared to women enrolling with a CD4 count of 350 cells/mm 3 or more (normal and mild disease stages). Our analyses also showed that older age, higher educational levels, higher scores for red blood cell counts, higher mononuclear scores, higher granulocytes scores, and higher physical health scores, all had a significant effect on a shortened time to immunological recovery, while women with many sex partners, higher viral load and larger family size had a significant effect on accelerating time to immune deterioration. Conclusion: Multi-state modelling of transition-specific distributions offers a flexible tool for the study of demographic and clinical characteristics' effects on the entire disease progression pathway. It is hoped that the article will help applied researchers to familiarize themselves with the models, including interpretation of results.

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Section: Discussionsupporting

confidence: 90%

Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model

Dessie

Zewotir

Mwambi

et al. 2020

Theor Biol Med Model

View full text Add to dashboard Cite

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“…Factors such as psychiatric disorders, cognitive impairment, social stigma, substance abuse, and volatile housing can prevent optimal adherence [ 19 , 20 ]. Burch et al [ 21 ] found clear associations between markers of the social determinants of health and HIV outcomes.…”

Section: Introductionmentioning

confidence: 99%

mHealth Interventions to Promote Anti-Retroviral Adherence in HIV: Narrative Review

Lee¹,

Valerius²

2020

JMIR Mhealth Uhealth

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Background Antiretrovirals (ARVs) are key in the management of HIV. Although no cure exists, ARVs help patients live healthy lives and prevent transmission to others. Adherence to complex regimens is paramount to outcomes and in avoiding the emergence of drug-resistant viruses. The goal of therapy is to reach an undetectable viral load. However, adherence is a common problem, stemming from issues such as mental health, chaotic home situations, and busy work schedules. Mobile health (mHealth) represents a new approach in improving medication adherence, and multiple studies have been performed in this area. Objective This study aims to review the current implementation of mHealth in the management of HIV among different groups of patients. Methods We used PubMed, Academic Search Elite, and 1 journal database with various search terms to review the current implementation of mHealth in HIV care. Results Titles and abstracts were screened, and 61 papers were identified and fully reviewed. The literature was divided into lower- and higher-income nations, as defined by the United Nations. A total of 20 studies with quantitative results were identified, with 10 being text- and SMS-based interventions (the majority of these being in lower-income countries) and 8 being smartphone-based apps (primarily in higher-income countries). The majority of these studies determined whether there was an effect on adherence or biochemical parameters (viral load and CD4 count). Various qualitative studies have also been conducted, and many have focused on determining the specific design of interventions that were successful (frequency of messaging, types of messages, etc) as well as priorities for patients with regard to mHealth interventions. Conclusions There seems to be a role of mHealth in the management of HIV in lower-income nations; however, the optimal design of an intervention needs to be delineated. In higher-income countries, where the 2 significant risk factors were injection drugs and men who have sex with men, the benefit was less clear, and more research is needed.

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“…In particular, the effects of age are larger for a patient being in the "normal and mild" immunological stage than that of a patient being in the "normal" immunological stage. Previous studies [43,44] also reported that middle-aged adults experienced higher rates of CD4 recovery. Contrary to our findings, an inverse relationship between the age of the patient and CD4 count recovery has been reported in previous studies [45][46][47].…”

Section: Discussionmentioning

confidence: 71%

Multilevel ordinal model for CD4 count trends in seroconversion among South Africa women

et al. 2020

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Background: Ordinal health longitudinal response variables have distributions that make them unsuitable for many popular statistical models that assume normality. We present a multilevel growth model that may be more suitable for medical ordinal longitudinal outcomes than are statistical models that assume normality and continuous measurements. Methods: The data is from an ongoing prospective cohort study conducted amongst adult women who are HIVinfected patients in Kwazulu-Natal, South Africa. Participants were enrolled into the acute infection, then into early infection subsequently into established infection and afterward on cART. Generalized linear multilevel models were applied. Results: Multilevel ordinal non-proportional and proportional-odds growth models were presented and compared. We observed that the effects of covariates can't be assumed identical across the three cumulative logits. Our analyses also revealed that the rate of change of immune recovery of patients increased as the follow-up time increases. Patients with stable sexual partners, middle-aged, cART initiation, and higher educational levels were more likely to have better immunological stages with time. Similarly, patients having high electrolytes component scores, higher red blood cell indices scores, higher physical health scores, higher psychological well-being scores, a higher level of independence scores, and lower viral load more likely to have better immunological stages through the follow-up time. Conclusion: It can be concluded that the multilevel non-proportional-odds method provides a flexible modeling alternative when the proportional-odds assumption of equal effects of the predictor variables at every stage of the response variable is violated. Having higher clinical parameter scores, higher QoL scores, higher educational levels, and stable sexual partners were found to be the significant factors for trends of CD4 count recovery.

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Impact of social determinants on antiretroviral therapy access and outcomes entering the era of universal treatment for people living with HIV in Italy

Cited by 21 publications

References 24 publications

Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model

Modelling HIV disease process and progression in seroconversion among South Africa women: using transition-specific parametric multi-state model

mHealth Interventions to Promote Anti-Retroviral Adherence in HIV: Narrative Review

Multilevel ordinal model for CD4 count trends in seroconversion among South Africa women

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