Increasing transfers-out from an antiretroviral treatment service in South Africa: patient characteristics and rates of virological non-suppression

Transfers between health facilities of people living with diabetes attending primary health care services in the Western Cape Province of South Africa: A retrospective cohort study

OBJECTIVES

Transfers between health facilities of people living with HIV attending primary health care (PHC) including hospital to PHC facility, PHC facility to hospital and PHC facility to PHC facility transfers occur frequently, affect health service planning, and are associated with disengagement from care and viraemia. Data on transfers among people living with diabetes attending PHC, particularly transfers between PHC facilities, are few. We assessed the transfer incidence rate of people living with diabetes attending PHC, and the association between transfers between PHC facilities and subsequent HbA1c values.

METHODS

We analysed data on HbA1c tests at public sector facilities in the Western Cape Province (2016-March 2020). Individuals with an HbA1c in 2016-2017 were followed-up for 27 months and included in the analysis if ≥18 years at first included HbA1c, ≥2 HbA1cs during follow-up and ≥1 HbA1c at a PHC facility. A visit interval was the duration between two consecutive HbA1cs. Successive HbA1cs at different facilities of any type indicated any transfer, and HbA1cs at different PHC facilities indicated a transfer between PHC facilities. Mixed effects logistic regression adjusted for sex, age, rural/urban facility attended at the start of the visit interval, disengagement (visit interval >14 months) and a hospital visit during follow-up assessed the association between transfers between PHC facilities and HbA1c >8%.

RESULTS

Among 102,813 participants, 22.6% had ≥1 transfer of any type. Including repeat transfers, there were 29,994 transfers (14.4 transfers per 100 person-years, 95% confidence interval [CI] 14.3-14.6). A total of 6996 (30.1%) of those who transferred had a transfer between PHC facilities. Visit intervals with a transfer between PHC facilities were longer (349 days, interquartile range [IQR] 211-503) than those without any transfer (330 days, IQR 182-422). The adjusted relative odds of an HbA1c ≥8% after a transfer between PHC facilities versus no transfer were 1.20 (95% CI 1.05-1.37).

CONCLUSION

The volume of transfers involving PHC facilities requires consideration when planning services. Individuals who transfer between PHC facilities require additional monitoring and support.

Mortality Among HIV-Infected Adults on Antiretroviral Therapy in Southern Uganda

BACKGROUND

Monitoring and evaluation of clinical programs requires assessing patient outcomes. Numerous challenges complicate these efforts, the most insidious of which is loss to follow-up (LTFU). LTFU is a composite outcome, including individuals out of care, undocumented transfers, and unreported deaths. Incorporation of vital status information from routine patient outreach may improve the mortality estimates for those LTFU.

SETTINGS

We analyzed routinely collected clinical and patient tracing data for individuals (15 years or older) initiating antiretroviral treatment between January 2014 and December 2018 at 2 public HIV care clinics in greater Rakai, Uganda.

METHODS

We derived unadjusted mortality estimates using Kaplan-Meier methods. Estimates, adjusted for unreported deaths, applied weighting through the Frangakis and Rubin method to represent outcomes among LTFU patients who were successfully traced and for whom vital status was ascertained. Confidence intervals were determined through bootstrap methods.

RESULTS

Of 1969 patients with median age at antiretroviral treatment initiation of 31 years (interquartile range: 25-38), 1126 (57.2%) were female patients and 808 (41%) were lost. Of the lost patients, 640 patient files (79.2%) were found and reviewed, of which 204 (31.8%) had a tracing attempt. Within the electronic health records of the program, 28 deaths were identified with an estimated unadjusted mortality 1 year after antiretroviral treatment initiation of 2.5% (95% CI: 1.8% to 3.3%). Using chart review and patient tracing data, an additional 24 deaths (total 52) were discovered with an adjusted 1-year mortality of 3.8% (95% CI: 2.6% to 5.0%).

CONCLUSIONS

Data from routine outreach efforts by HIV care and treatment programs can be used to support plausible adjustments to estimates of client mortality. Mortality estimates without active ascertainment of vital status of LTFU patients may significantly underestimate program mortality.

Reaching Viral Suppression Among People With HIV With Suspected Treatment Failure who Received Enhanced Adherence Counseling in Southern Nigeria: A Retrospective Analysis

Background

This study assessed viral load (VL) testing and viral suppression following enhanced adherence counseling (EAC) among people with HIV (PWH) with suspected treatment failure and identified factors associated with persistent viremia.

Methods

We conducted a retrospective review of electronic medical records of PWH aged 15 years or older who had received antiretroviral therapy (ART) for at least 6 months as of December 2020 and had a high viral load (HVL; ≥1000 copies/mL) across 22 comprehensive HIV treatment facilities in Akwa Ibom State, Nigeria. Patients with HVL were expected to receive 3 EAC sessions delivered in person or virtually and repeat VL testing upon completion of EAC and after documented good adherence. At 6 months post-EAC enrollment, we reviewed the data to determine client uptake of 1 or more EAC sessions, completion of 3 EAC sessions, a repeat viral load (VL) test conducted post-EAC, and persistent viremia with a VL of ≥1000 copies/mL. Selected sociodemographic and clinical variables were analyzed to identify factors associated with persistent viremia using SPSS, version 26.

Results

Of the 3257 unsuppressed PWH, EAC uptake was 94.8% (n = 3088), EAC completion was 81.5% (2517/3088), post-EAC VL testing uptake was 75.9% (2344/3088), and viral resuppression was 73.8% (2280/3088). In multivariable analysis, those on ART for <12 months (P ≤ .001) and those who completed EAC within 3 months (P = .045) were less likely to have persistent viremia.

Conclusions

An HVL resuppression rate of 74% was achieved, but EAC completion was low. Identification of the challenges faced by PWH with a higher risk of persistent viremia is recommended to optimize the potential benefit of EAC.

Self-transfers and factors associated with successful tracing among persons lost to follow-up from HIV care, Sheema District, Southwestern Uganda: retrospective medical records review, 2017-2021

BACKGROUND

Due to improved coverage and scale-up of antiretroviral therapy (ART), patients are increasingly transferring between ART-providing sites. Self-transfers may constitute a high proportion of patients considered lost to follow-up (LTFU), and if overlooked when reporting patients who have dropped out of HIV care, may result in an incorrect estimation of retention. We determined the prevalence of self-transfers, and successful tracing, and identified associated factors among people living with HIV (PLHIV) LTFU from care at public health facilities in Sheema District, Southwestern Uganda.

METHODS

We conducted a cross-sectional retrospective medical records review during February and March 2022. We included records of all PLHIV who were LTFU from 2017 to 2021, and who were registered at government-owned ART clinics in Sheema District. LTFU was considered for those who were not taking ART refills for a period of ≥ 3 months. We abstracted demographic and clinical data from medical records at the selected clinics. Participants were traced via phone calls or in-person to ascertain the outcomes of LTFU. We performed multivariate modified Poisson regression to identify factors associated with self-transfer, and successful tracing.

RESULTS

Overall, 740 patients were identified as LTFU from three ART-providing clinics; of these, 560 (76%) were self-transfers. The mean age was 30 (SD ± 10) years, and most (69%, n = 514) were female; the majority (87%, 641/740) were successfully traced. Age (adjusted prevalence ratio [aPR] = 1.13, 95% CI 1.01-1.25, P = 0.026 for those aged 18-30 years compared to > 30 years), female sex (aPR = 1.18, 95% CI 1.11-1.25, P < 0.001), and having WHO clinical stage 1-2 (aPR = 2.34, 95% CI 1.89-3.91, P < 0.001) were significantly associated with self-transfer. Presence of a phone contact in the patient's file (aPR = 1.10, 95% CI 1.01-1.90, P = 0.026) was associated with successful tracing of the patients considered LTFU.

CONCLUSION

Self-transfers accounted for the majority of patients recorded as LTFU, highlighting the need to account for self-transfers among patients considered LTFU, to accurately estimate retention in care. ART-providing facilities should regularly update contact information for PLHIV to enable successful tracing, in the event that the patients are LTFU. This calls for a health-tracking system that easily identifies self-transfers across ART-providing clinics using unique patient identifiers.

Transfer of Patients on Antiretroviral Therapy Attending Primary Health Care Services in South Africa

BACKGROUND

Patients stable on antiretroviral therapy (ART) may require transfer between health care facilities to maintain continuous care, yet data on the frequency, predictors, and virologic outcomes of transfers are limited.

METHODS

Data for all viral load (VL) testing at public sector health facilities in the Western Cape Province (2011-2018) were obtained. Participant inclusion criteria were a first VL between 2011 and 2013, age >15 years at ART initiation, and >1 VL within 5 years of ART initiation, of which ≥1 was at a primary health care facility. Two successive VLs taken at different facilities indicated a transfer. We assessed predictors of transfer using generalized estimating equations with Poisson regression and the association between transfer and subsequent VL> 1000 copies/mL using generalized mixed effects.

RESULTS

Overall 84,814 participants (median age at ART initiation 34 years and 68% female) were followed up for up to 4.5 years after their first VL: 34% (n = 29,056) transferred at least once, and among these, 26% transferred twice and 11% transferred thrice or more. Female sex, age <30 years, and first VL > 1000 copies/mL were independently associated with an increased rate of transfer [adjusted rate ratio 1.24, 95% confidence interval (CI): 1.21 to 1.26; 1.34, 95% CI: 1.31 to 1.36; and 1.42, 95% CI: 1.38 to 1.45, respectively]. Adjusting for age, sex, and disengagement, transfer was associated with an increased relative odds of VL > 1000 copies/mL (odds ratio 1.35, 95% CI: 1.29 to 1.42).

CONCLUSIONS

Approximately one-third of participants transferred and virologic outcomes were poor post-transfer. Stable patients who transfer may require additional support to maintain adherence.

Investigating clinic transfers among HIV patients considered lost to follow-up to improve understanding of the HIV care cascade: Findings from a cohort study in rural north-eastern South Africa

Investigating clinical transfers of HIV patients is important for accurate estimates of retention and informing interventions to support patients. We investigate transfers for adults reported as lost to follow-up (LTFU) from eight HIV care facilities in the Agincourt health and demographic surveillance system (HDSS), South Africa. Using linked clinic and HDSS records, outcomes of adults more than 90 days late for their last scheduled clinic visit were determined through clinic and routine tracing record reviews, HDSS data, and supplementary tracing. Factors associated with transferring to another clinic were determined through Cox regression models. Transfers were graphically and geospatially visualised. Transfers were more common for women, patients living further from the clinic, and patients with higher baseline CD4 cell counts. Transfers to clinics within the HDSS were more likely to be undocumented and were significantly more likely for women pregnant at ART initiation. Transfers outside the HDSS clustered around economic hubs. Patients transferring to health facilities within the HDSS may be shopping for better care, whereas those who transfer out of the HDSS may be migrating for work. Treatment programmes should facilitate transfer processes for patients, ensure continuity of care among those migrating, and improve tracking of undocumented transfers.

Patient Transfers and Their Impact on Gaps in Clinical Care: Differences by Gender in a Large Cohort of Adults Living with HIV on Antiretroviral Therapy in South Africa

For people living with HIV (PLWH), patient transfers may affect engagement in care. We followed a cohort of PLWH in Cape Town, South Africa who tested positive for HIV in 2012-2013 from ART initiation in 2012-2016 through December 2016. Patient transfers were defined as moving from one healthcare facility to another on a different day, considering all healthcare visits and recorded HIV-visits only. We estimated incidence rates (IR) for transfers by time since ART initiation, overall and by gender, and associations between transfers and gaps of > 180 days in clinical care. Overall, 4,176 PLWH were followed for a median of 32 months, and 8% (HIV visits)-17% (all healthcare visits) of visits were patient transfers. Including all healthcare visits, transfers were highest through 3 months on ART (IR 20.2 transfers per 100 visits, 95% CI 19.2-21.2), but increased through 36 months on ART when only HIV visits were included (IR 9.7, 95% CI 8.8-10.8). Overall, women were more likely to transfer than men, and transfers were associated with gaps in care (IR ratio [IRR] 3.06 95% CI 2.83-3.32; HIV visits only). In this cohort, patient transfers were frequent, more common among women, and associated with gaps in care.

Factors Associated with Loss to Follow-Up Among Patients Receiving HIV Treatment in Nairobi, Kenya

We investigated factors associated with loss to follow-up (LTFU) in 24 urban health facilities in Nairobi, Kenya. We conducted a retrospective analysis of routinely collected data to assess factors associated with LTFU in the period October 1, 2016, to June 30, 2017. LTFU was defined as no antiretroviral therapy (ART) refill for ≥90 days and no documentation of transfer, death, or treatment cessation in the patient chart, and if no lapse of ≥90 days between ART refills, patients were considered retained in care. Multivariable logistic regression modeling was used to compute odds ratios and 95% confidence interval (CI) for LTFU. Our analysis included 633 individuals who were LTFU and 13,098 individuals retained in care. Most participants (69.6%) were women, and median age was 33.0 years (interquartile range, 27.2-38.3 years). Median ART duration was shorter among those LTFU (0.4 years) than retained patients (2.5 years, p < .0001). Being male [adjusted odds ratio (aOR) 1.30; 95% CI: 1.04-1.63, p = .02], transferring into facilities while already receiving ART (aOR 11.58; 95% CI: 8.23-16.29, p < .0001), and having a shorter ART duration (<6 months) were associated with increased odds of LTFU. Patients who transferred into a facility while already receiving ART had the highest adjusted odds of being LTFU compared with those retained in care. In this urban and highly mobile population, transferring into facilities while already receiving ART was strongly associated with LTFU. Focusing programming efforts on patients transferring between urban clinics to identify reasons for transfer and potential barriers to treatment adherence could help improve patient outcomes. Supplementary case management and support may be needed to promote a seamless transition and ensure uninterrupted engagement in HIV care and treatment.

Outcomes After Being Lost to Follow-up Differ for Pregnant and Postpartum Women When Compared With the General HIV Treatment Population in Rural South Africa

Supplemental Digital Content is Available in the Text.

Undetermined attrition prohibits full understanding of the coverage and effectiveness of HIV programs. Outcomes following loss to follow-up (LTFU) among antiretroviral therapy (ART) patients may differ according to their reasons for ART initiation.

'They are inconveniencing us' - exploring how gaps in patient education and patient centred approaches interfere with TB treatment adherence: perspectives from patients and clinicians in the Free State Province, South Africa

BACKGROUND

Tuberculosis (TB) treatment loss to follow up (LTFU) plays an important contributory role to the staggering TB epidemic in South Africa. Reasons for treatment interruption are poorly understood. Treatment interruption appears to be the culmination of poor health literacy of patients and inadequate health education provided by clinicians. We explored clinician and patient perspectives of the gaps in TB messaging that influence TB treatment LTFU.

METHODS

We conducted semi-structured in-depth interviews between January and May 2018 with a sample of 15 clinicians managing TB and 7 patients identified as LTFU in public clinics in the Free State Province, South Africa. Thematic analysis using a mixed deductive/inductive thematic approach was used.

RESULTS

Limited occupational opportunities, fear of disclosure and stigmatization all contributed to treatment LTFU. Patients felt that the TB messaging received was inadequate. Many of the clinicians interviewed felt that improving patient's TB knowledge would reinforce adherence to treatment and thus focused on sharing information on treatment completion, side effects and infection control. However, the inability of clinicians to establish rapport with patients or to identify social support challenged TB treatment adherence by patients. Clinicians perceived this as patients not following their instructions despite what they considered lengthy TB education. Having said this, clinicians concurred that their medical management of TB lacked the psycho-social dimension to treat a social disease of this magnitude.

CONCLUSIONS

Limited occupational opportunities, fear of disclosure and stigmatization all contributed to treatment LTFU. Clinicians concurred that poor patient understanding of TB and that biomedical management lacking a psycho-social dimension further exacerbated the poor treatment outcome. TB remains a social disease, the successful management of which hinges on patient-centred care.

Transfer of primary care patients receiving chronic care: the next step in the continuum of care

The burden of chronic conditions is increasing rapidly in low- and middle-income countries. Chronic conditions require long-term and continuous care, including for patients transferring between facilities. Patient transfer is particularly important in the context of health service decentralization, which has led to increasing numbers of primary care facilities at which patients can access care, and high levels of migration, which suggest that patients might require care at multiple facilities. This article provides a critical review of existing evidence regarding transfer of stable patients receiving primary care for chronic conditions. Patient transfer has received limited consideration in people living with HIV, with growing concern that patients who transfer are at risk of poor outcomes; this appears similar for people with TB, although studies are few. There are minimal data on transfer of patients with non-communicable diseases, including diabetes. Patient transfer for chronic conditions has thus received surprisingly little attention from researchers; considering the potential risks, more research is urgently required regarding reasons for and outcomes of transfers, transfer processes and interventions to optimize transfers, for different chronic conditions. Ultimately, it is the responsibility of health systems to facilitate successful transfers, and this issue requires increased attention from researchers and policy-makers.

Loss to follow-up from antiretroviral therapy clinics: A systematic review and meta-analysis of published studies in South Africa from 2011 to 2015

Background

South Africa has the largest antiretroviral therapy (ART) programme in the world. To optimise programme outcomes, it is critical that patients are retained in care and that retention is accurately measured.

Objectives

To identify all studies published in South Africa from 2011 to 2015 that used loss to follow-up (LTFU) as an indicator or outcome to describe the variation in definitions and to estimate the proportion of patients lost to care across studies.

Method

All studies published between 01 January 2011 and October 2015 that included loss to follow-up or default from ART care in a South African cohort were included by use of a broad search strategy across multiple databases. To be included, the cohort had to include any patient ART data, including follow-up time, from 01 January 2010. Two authors, working independently, extracted data and assessed risk of bias from all manuscripts. Meta-analysis was performed for studies stratified by the same loss to follow-up definition.

Results

Forty-eight adult, 15 paediatric and 4 pregnant cohorts were included. Median cohort size was 3737; follow-up time ranged from 9 weeks to 5 years. Meta-analysis did not reveal an important difference in LTFU estimates in adult cohorts at 1 year between loss to follow-up defined as 3 months (11.0%, n = 4; 95% CI 10.7% – 11.2%) compared with 6 months (12.0%, n = 4; 95% CI 11.8% – 12.2%). Only two cohorts reported reliable LTFU estimates at 5 years: this was 25.1% (95% CI 24.8% – 25.4%).

Conclusion

South Africa should standardise a LTFU definition. This would aid in monitoring and evaluation of ART programmes, with the broader goal of improving patient outcomes.

Outcomes of Patients Lost to Follow-up in African Antiretroviral Therapy Programs: Individual Patient Data Meta-analysis

Background

Low retention on combination antiretroviral therapy (cART) has emerged as a threat to the Joint United Nations Programme on human immunodeficiency virus (HIV)/AIDS (UNAIDS) 90-90-90 targets. We examined outcomes of patients who started cART but were subsequently lost to follow-up (LTFU) in African treatment programs.

Methods

This was a systematic review and individual patient data meta-analysis of studies that traced patients who were LTFU. Outcomes were analyzed using cumulative incidence functions and proportional hazards models for the competing risks of (i) death, (ii) alive but stopped cART, (iii) silent transfer to other clinics, and (iv) retention on cART.

Results

Nine studies contributed data on 7377 patients who started cART and were subsequently LTFU in sub-Saharan Africa. The median CD4 count at the start of cART was 129 cells/μL. At 4 years after the last clinic visit, 21.8% (95% confidence interval [CI], 20.8%-22.7%) were known to have died, 22.6% (95% CI, 21.6%-23.6%) were alive but had stopped cART, 14.8% (95% CI, 14.0%-15.6%) had transferred to another clinic, 9.2% (95% CI, 8.5%-9.8%) were retained on cART, and 31.6% (95% CI, 30.6%-32.7%) could not been found. Mortality was associated with male sex, more advanced disease, and shorter cART duration; stopping cART with less advanced disease andlonger cART duration; and silent transfer with female sex and less advanced disease.

Conclusions

Mortality in patients LTFU must be considered for unbiased assessments of program outcomes and UNAIDS targets in sub-Saharan Africa. Immediate start of cART and early tracing of patients LTFU should be priorities.

Predictors of loss to follow-up among children on long-term antiretroviral therapy in Zambia (2003-2015)

Background

Retention in care is critical for children living with HIV taking antiretroviral therapy (ART). Loss to follow-up (LTFU) is high in HIV treatment programs in resource limited settings. We estimated the cumulative incidence of LTFU and identified associated risk factors among children on ART at Livingstone Central Hospital (LCH), Zambia.

Methods

Using a retrospective cohort study design, we abstracted data from medical records of children who received ART between 2003 and 2015. Loss to follow-up was defined as no clinical and pharmacy contact for at least 90 days after the child missed their last scheduled clinical visit. Non-parametric competing risks models were used to estimate the cumulative incidence of death, LTFU and transfer. Cause-specific Cox regression was used to estimate the hazard ratios of the risk factors of LTFU.

Results

A total of 1039 children aged 0–15 years commenced ART at LCH between 2003 and 2015. Median duration of follow-up was 3.8 years (95% CI: 1.2–6.5), median age at ART initiation was 3.6 years (IQR: 1.3–8.6), 179 (17%) started treatment during their first year of life. At least 167 (16%) were LTFU and we traced 151 (90%). Of those we traced, 39 (26%) had died, 71 (47%) defaulted, 20 (13%) continued ART at other clinics and 21 (14%) continued treatment with gaps. The cumulative incidence of LTFU for the entire cohort was 2.7% (95% CI: 1.9–3.9) at 3 months, 4.1% (95% CI: 2.9–5.4) at 6 months and 14.1% (95% CI: 12.4–16.9) after 5 years on ART. Associated risk factors were: 1) non-disclosure of HIV status at baseline, aHR = 1.9 (1.2–2.9), 2) No phone ownership, aHR = 2.1 (1.6–2.9), 3) starting treatment between 2013 to 2015, aHR = 5.6 (2.2–14.1).

Conclusion

Among the children LTFU mortality and default were substantially high. Children who started treatment in recent years (2013–2015) had the highest hazard of LTFU. Lack of access to a phone and non-disclosure of HIV-status to the index child was associated with higher hazards of LTFU. We recommend re-enforcement of client counselling and focused follow-up strategies using modern technology such as mobile phones as adjunct to current approaches.

Improving management of tuberculosis in people living with HIV in South Africa through integration of HIV and tuberculosis services: a proof of concept study

BACKGROUND

South Africa's tuberculosis burden is the third highest globally and is closely associated with the country's devastating HIV epidemic. The separation of HIV and TB services in primary healthcare services in South Africa hampers TB case finding in patients who are co-infected with HIV and TB. This operational proof of concept study assessed an approach to improving tuberculosis detection and treatment by integrating tuberculosis management into HIV care.

METHODS

The intervention involved workforce re-engineering accompanied by changes to the physical environment in three primary healthcare facilities in Gert Sibande district, Mpumalanga Province, that allowed HIV providers to test their HIV patients for TB and initiate and monitor TB treatment when indicated. To assess the proof of concept we compared the management of TB patients by HIV and TB providers, by reviewing the records of all facility patients who tested positive for tuberculosis between July 2015 and February 2016. We also considered the perceptions of healthcare providers and facility managers about the intervention through structured interviews.

RESULTS

Approximately 30% of the 1855 patients with presumed TB in the three clinics had been identified by HIV providers. The percentage of patients consecutively tested for TB was 81.0% and 85.0% (p = 0.0551) for HIV and TB providers, respectively. Of the patients identified with TB by HIV and TB providers, 75.4% and 79.2% (p = 0.2876), respectively, were initiated on treatment. The defaulter rate was higher among HIV, compared to TB, providers (12.8% versus 4.2%). Overall, healthcare providers and facility managers had positive views of the intervention but raised concerns regarding potential increase in workload and administrative issues, as well as infection control.

CONCLUSIONS

The results of this proof-of-concept study indicate that the full spectrum of TB services can be easily and effectively integrated into existing HIV care programs. However, a possible shift in the service providers' workload, including administrative tasks, must be tackled and effective infection control must be ensured. Further research is needed to assess the impact of TB service integration into the scope of HIV care (or other chronic care programs) on patient outcomes, including analysis of routine data.

Comparison of six methods to estimate adherence in an ART-naïve cohort in a resource-poor setting: which best predicts virological and resistance outcomes?

Background

Incomplete adherence to antiretroviral therapy (ART) results in virologic failure and resistance. It remains unclear which adherence measure best predicts these outcomes. We compared six patient-reported and objective adherence measures in one ART-naïve cohort in South Africa.

Methods

We recruited 230 participants from a community ART clinic and prospectively collected demographic data, CD4 count and HIV-RNA at weeks 0, 16 and 48. We quantified adherence using 3-day self-report (SR), clinic-based pill count (CPC), average adherence by pharmacy refill (PR-average), calculation of medication-free days (PR-gaps), efavirenz therapeutic drug monitoring (TDM) and an electronic adherence monitoring device (EAMD). Associations between adherence measures and virologic and genotypic outcomes were modelled using logistic regression, with the area under the curve (AUC) from the receiver operator characteristic (ROC) analyses derived to assess performance of adherence measures in predicting outcomes.

Results

At week 48 median (IQR) adherence was: SR 100% (100–100), CPC 100% (95–107), PR-average 103% (95–105), PR-gaps 100% (95–100) and EAMD 86% (59–94), and efavirenz concentrations were therapeutic (>1 mg/L) in 92%. EAMD, PR-average, PR-gaps and CPC best predicted virological outcome at week 48 with AUC ROC of 0.73 (95% CI 0.61–0.83), 0.73 (95% CI 0.61–0.85), 0.72 (95% CI 0.59–0.84) and 0.64 (95% CI 0.52–0.76) respectively. EAMD, PR-gaps and PR-average were highly predictive of detection of resistance mutations at week 48, with AUC ROC of 0.92 (95% CI 0.87–0.97), 0.86 (0.67–1.0) and 0.83 (95% CI 0.65–1.0) respectively. SR and TDM were poorly predictive of outcomes at week 48.

Conclusion

EAMD and both PR measures predicted resistance and virological failure similarly. Pharmacy refill data is a pragmatic adherence measure in resource-limited settings where electronic monitoring is unavailable.

Trial registration The trial was retrospectively registered in the Pan African Clinical Trials Registry, number PACTR201311000641402, on the 13 Sep 2013 (www.pactr.org). The first participant was enrolled on the 12th July 2012. The last patient last visit (week 48) was 15 April 2014

Electronic supplementary material

The online version of this article (doi:10.1186/s12981-017-0138-y) contains supplementary material, which is available to authorized users.

Movement between facilities for HIV care among a mobile population in Kenya: transfer, loss to follow-up, and reengagement

HIV treatment is life-long, yet many patients travel or migrate for their livelihoods, risking treatment interruption. We examine timely reengagement in care among patients who transferred-out or were lost-to-follow-up (LTFU) from a rural HIV facility. We conducted a cohort study among 369 adult patients on antiretroviral therapy between November 2011 and November 2013 on Mfangano Island, Kenya. Patients who transferred or were LTFU (i.e., missed a scheduled appointment by ≥90 days) were traced to determine if they reengaged or accessed care at another clinic. We report cumulative incidence and time to reengagement using Cox proportional hazards models adjusted for patient demographic and clinical characteristics. Among 369 patients at the clinic, 23(6%) requested an official transfer and 78(21%) were LTFU. Among official transfers, cumulative incidence of linkage to their destination facility was 91% at three months (95%CI (confidence intervals) 69-98%). Among LTFU, cumulative incidence of reengagement in care at the original or a new clinic was 14% at three months (95%CI 7-23%) and 60% at six months (95%CI 48-69%). In the adjusted Cox model, patients who left with an official transfer reengaged in care six times faster than those who did not (adjusted hazard ratio 6.2, 95%CI 3.4-11.0). Patients who left an island-based HIV clinic in Kenya with an official transfer letter reengaged in care faster than those who were LTFU, although many in both groups had treatment gaps long enough to risk viral rebound. Better coordination of transfers between clinics, such as assisting patients with navigating the process or improving inter-clinic communication surrounding transfers, may reduce delays in treatment during transfer and improve overall clinical outcomes.

The Challenge of and Opportunities for Transitioning and Maintaining a Continuum of Care Among Adolescents and Young Adults Living with HIV in Resource Limited Settings

An unprecedented number of youth living with HIV (YLHIV) are aging into adolescence and young adulthood, increasing concerns about the possibility of these youth being lost in the transition from supported care (sometimes in pediatric settings) to more independent healthcare settings and perhaps furthering the emerging disparities in outcomes (e.g., higher nonadherence to treatment, increased morbidity and mortality). In resource-rich settings where there is likely greater recognition of adolescent cognitive and developmental challenges, transitioning YLHIV to adult healthcare has emerged as a major challenge. In resource limited settings (RLS), where the burden of HIV is significant and healthcare resources often stretched, the challenge to move toward healthcare independence and maintain a fluid continuum of care for YLHIV may be the greatest. We review key issues in transitioning YLHIV in RLS, highlighting steps in the transition process, examining evidence where available, and discussing challenges and opportunities to understanding and optimizing outcomes.

Different modalities of entry in a large urban clinic in Uganda and impact on outcomes of patients assessing HIV care and treatment

In resource-limited settings, a number of patients do not receive continuous HIV care. In this analysis, we compared outcomes in patients who entered care by different modality of entry. This was a retrospective analysis of all patients started on antiretroviral treatment (ART) at a large urban center in Uganda from 2005 to 2012. Patients were categorized into three groups (1) Front door: started on ART without interruption during follow-up; (2) drop-out side door: restarted on ART after having an interruption >6 months and (3) transfer-in side door: transferred-in after being started on ART somewhere else. We compared characteristics at enrollment in the three groups and investigated the following outcomes: (1) retention in care (2) switch to second line. In the study period 11,528 (87.2%) were enrolled through the front door, 1159 (8.7%) resumed ART after dropping out, while 527 (4%) patients were transferred in on ART. The three groups were generally comparable, although patients transferred in were sicker. A larger proportion of patients entered through the drop-out side door died or was lost to follow-up (37.3%), as compared to patients in the front door group (24.9%) and transferred-in side door group (17.7%). More patients in the front door group (32.1%) were transferred out during the follow-up. The highest probability of switching to second line was found in the transferred-in group. Patients who re-enter our program after dropping out are at higher risk of dropping out of care and often need to be switched to second-line ART. The high demand for second-line therapy among patients in transfer-in side door reflects failure in management of complicated patients who are usually require "up-transfer" to better treatment centers. In future understanding, the different modes of entry into HIV care will be key in reshaping the general cascade of HIV care.

A Randomized Controlled Trial of Real-Time Electronic Adherence Monitoring With Text Message Dosing Reminders in People Starting First-Line Antiretroviral Therapy

BACKGROUND

There are conflicting findings about whether mobile phone text message reminders impact on antiretroviral adherence. We hypothesized that text reminders sent when dosing was late would improve adherence and HIV viral suppression.

METHODS

Antiretroviral therapy (ART)-naive participants, from a South African outpatient ART clinic, were randomized to standard of care (SoC, 3 pretreatment education sessions), or intervention (SoC and automated text reminders if dosing >30 minutes late). Dosing time was recorded by real-time electronic adherence monitoring devices, given to participants at ART start. CD4 cell count and HIV RNA were determined at baseline, 16 and 48 weeks. Primary outcome was cumulative adherence execution by electronic adherence monitoring device. HIV-1 viral suppression (<40 copies/mL) at week 48 and count of treatment interruptions (TIs) >72 hours were secondary outcomes. Analysis was by intention to treat (missing = failure). Registration was with the Pan-African Clinical Trials Registry: PACTR201311000641402.

RESULTS

A total of 230 participants were randomly assigned to control (n = 115) or intervention (n = 115) arms. Median adherence was 82.1% (interquartile range, 56.6%-94.6%) in the intervention arm, compared with 80.4% (interquartile range, 52.8%-93.8%) for SoC [adjusted odds ratio for adherence 1.08; 95% confidence interval (CI): 0.77 to 1.52]. Suppressed HIV RNA (<40 copies/mL) occurred in 80 (69.6%) of control and 75 (65.2%) of intervention (adjusted odds ratio for virological failure in intervention arm 0.77; 95% CI: 0.42 to 1.40). In the intervention arm, the count of TIs of >72 hours was reduced (adjusted incident rate ratio, 0.84; 95% CI: 0.75 to 0.94).

CONCLUSIONS

Text message reminders linked to late doses detected by real-time adherence monitoring reduced the number of prolonged TIs, but did not significantly improve adherence or viral suppression.

Self-transfer and mortality amongst adults lost to follow-up in ART programmes in low- and middle-income countries: systematic review and meta-analysis

OBJECTIVE

To ascertain estimates of adult patients, recorded as lost to follow-up (LTFU) within antiretroviral treatment (ART) programmes, who have self-transferred care, died or truly stopped ART in low- and middle-income countries.

METHODS

PubMed, EMBASE, Web of Science, Science Direct, LILACS, IndMed and AIM databases (2003-2013) and IAS/AIDS conference abstracts (2011-2013) were searched for tracing studies reporting the proportion of traced patients found to have self-transferred, died or stopped ART. These estimates were then combined using random-effects meta-analysis. Risk of bias was assessed through subgroup and sensitivity analyses.

RESULTS

Twenty eight studies were eligible for inclusion, reporting true outcomes for 10,806 traced patients attending approximately 258 ART facilities. None were from outside sub-Saharan Africa. Twenty three studies reported 4.5-54.4% traced LTFU patients self-transferring care, providing a pooled estimate of 18.6% (95% CI 15.8-22.0%). A significant positive association was found between rates of self-transfer and LTFU in the ART cohort. The pooled estimates for unreported deaths were 38.8% (95% CI 30.8-46.8%; 27 studies) and 28.6% (95% CI 21.9-36.0%; 20 studies) for patients stopping ART. A significant decrease in unreported deaths from 50.0% (95% CI 41.5-58.4%) to 30.0% (95% CI 21.1-38.9%) was found comparing study periods before and after 31 December 2007.

CONCLUSIONS

Substantial unaccounted for transfers and deaths amongst patients LTFU confirms that retention and mortality is underestimated where the true outcomes of LTFU patients are not ascertained.

Mortality among adults transferred and lost to follow-up from antiretroviral therapy programmes in South Africa: a multicenter cohort study

BACKGROUND AND OBJECTIVES

Little is known about outcomes after transfer out (TFO) and loss to follow-up (LTF) and how differential outcomes might bias mortality estimates, as analyses generally censor or exclude TFOs/LTF. Using data linked to the National Population Register, we explored mortality among TFO and LTF patients compared with patients who were retained and investigated how linkage impacted on mortality estimates.

METHODS

A cohort analysis of routine data on adults with civil identification numbers starting antiretroviral therapy (ART) 2004-2009 in 4 large South African ART cohorts. The number, proportion, timing, and mortality of TFOs and LTF were reported. Mortality was compared using Kaplan-Meier curves, Cox's proportional hazards, and competing risks regression.

RESULTS

Before linkage, 1207 patients (6%) had died, 2624 (13%) were LTF, 1067 (5%) were TFO and 14,583 (75%) were retained. Compared with retained, mortality risk was 3 times higher among TFO patients [adjusted hazard ratio (aHR), 3.11; 95% confidence interval (CI): 2.42 to 3.99] and 20 times higher among LTF patients (aHR, 22.03; 95% CI: 20.05 to 24.21). Excluding early deaths after TFO or LTF, the risk was comparable among TFOs and retained (aHR, 0.75; 95% CI: 0.54 to 1.03) and higher among LTF (aHR, 2.85; 95% CI: 2.43 to 3.33). After linkage, corrected mortality was higher than site-reported mortality. Censoring did not, however, lead to substantial underestimation of mortality among TFOs.

CONCLUSIONS

Although TFO and LTF predicted mortality, the lower incidence of TFO and subsequent death compared with LTF meant that censoring TFOs did not bias mortality estimates. Future cohort analyses should explicitly consider proportions of TFO/LTF and mortality event rates.