Little is known about the clinical presentation and outcomes amongst older HIV infected populations accessing ART in sub-Saharan Africa. We compared mortality amongst HIV infected patients accessing ART that were <  50 years to those ≥50 years in Kwa-Zulu Natal, South Africa.N = 4003). HIV infected patients, 14 years or older were enrolled. All-cause mortality and treatment response to ART in those < 50 years to those ≥50 years were compared. A Kaplan-Meier curve and log-rank test were used to compare the cumulative probability of death between the two age groups with the primary endpoint being mortality. Statistical analysis was done using SAS .We undertook a retrospective review of medical records of patients that accessed HIV services at the CAPRISA AIDS Treatment program (CAT) between June 2004 to December 2012 (p = 0.137). In the multivariable model older patients had a significantly higher risk of death compared to younger patients. (hazard ratio (HR) 1.60, 95% CI: 1.08–2.39, p = 0.019).The rate of CD4+ cell count increase was higher in those < 50 years  with no difference in viral suppression. The older group showed significantly higher prevalence of diabetes (6.3%) and hypertension (21.5%), p < 0.001.Of 4003 individuals, 262 (6.5%) were ≥ 50 years (older group). The median age in those ≥50 years and <  50 year was 54.5 and 32.0 years, respectively. The younger group was mainly female (64.7%). There was no difference in mortality rate, between the older (6.9/100 person-years (py), 95% confidence interval (CI): 4.7–9.6) and younger group  at 60 months  contains supplementary material, which is available to authorized users. In 2015, there were approximately 36.7 million people living with human immunodeficiency virus (HIV) . The ATHSouth Africa had approximately 6.4 million HIV infected people in 2012 accounting for 17% of the global burden of HIV infection  and ≥ 50 years [older]. Demographic and clinical variables were summarized using median with interquartile range (IQR), mean with standard deviation and percentages. All statistical tests were two sided. Fisher’s exact test was used for the analysis of categorical data. The t-test for independent samples or Wilcoxon two-sample test was used for the analysis of continuous data.Linear mixed model was used to determine the difference in rate of increase in CD4+ cell count between the two age groups. Square root transformation was used to achieve CD4+ cell count normality.A Kaplan-Meier curve and log-rank test were used to compare the cumulative probability of death between the two age groups with the primary endpoint being mortality. Censorship was at the earliest recorded date of death, date of loss to follow-up or date of transfer out of the cohort. Poisson approximations were used to calculate confidence intervals (CIs) for mortality rates. Univariate and multivariate proportional hazards regression models were used to assess predictors of mortality. Multivariable models were adjusted for the following baseline covariates: gender, clinic site, CD4+ cell count, body mass index (BMI), World Health Organisation (WHO) stage, diabetes status, hypertension status, past history of tuberculosis (TB) and current tuberculosis disease. Proportionality was assessed by fitting time dependent covariates in a model created by interacting baseline variables with survival time. All-cause mortality was assessed. Statistical analysis was done using SAS .A total of 4003 individuals initiated antiretroviral treatment (ART) between June 2004 and December 2012; 6.5% were 50 years and older (older group). The baseline demographic characteristics of the two groups are illustrated in Table p = 0.003.There were 28 pregnant women in this cohort. More older individuals (62.2%) was found in the rural site compared to 54.8%, in the urban site, (p = 0.021). Most patients in both groups presented with WHO clinical stage 3 or 4 disease prior to initiating ART. A significantly higher prevalence of diabetes (6.3%) and hypertension (21.5%) was observed in the older group (p < 0.001), Table There was no significant difference between the groups overall in terms of body mass index, baseline viral load, WHO clinical stage or current or past history of TB. Gender distribution between the groups varied, with the younger group comprising 64.7% female compared to 55.3% in the older group,  p = 0.02. Most pa3, with older patients demonstrating a significantly higher median baseline CD4+ cell count compared to younger patients,142 vs.124 cells/mm3, p = 0.001  compared to those > 50 years, Fig. p < 0 .001). The proportion of individuals that achieved virologic suppression during follow-up did not differ between the groups,   : 4.6–9.4) in the older group and 5.1 per 100 person-years (95% CI: 4.6–5.7) (p = 0.019). An increase in CD4+ cell count and body mass index was associated with a decline in the risk of mortality.Age group was not associated with mortality in the univariate model. In the multivariable model older patients had a significantly higher risk of death compared to younger patients. (hazard ratio (HR) 1.60, 95% CI: 1.08–2.39, Other variables associated with a higher risk of mortality included low BMI, and WHO stage 3 and 4 disease, a diagnosis of prevalent diabetes and the absence of prevalent TB at ART initiation. WHO clinical stage 4 was associated with a fourfold risk of mortality. These factors together with male gender and hypertension were significant in the sensitivity analysis Table .Table 2PIn this prospective, observational cohort comparing outcomes of HIV infected individuals among patients 50 years and older to those younger than 50 years, we observed a higher mortality in the older compared to those younger than 50 years following 60 months of treatment. Unsurprisingly, most deaths occurred in the first 24 months post ART initiation. The mortality in the first 12 months did not differ significantly in both groups and is in keeping with other reports from sub Saharan Africa where high mortality is reported following initial initiation of ART .Cause of death, where established was found to be not related to HIV or TB in the vast majority of patients older than 50 years of age in our study. Conversely, almost two-thirds of all deaths were found to be associated to either TB and/or HIV among patients that were less than 50 years old. These findings illustrate the benefit of ART in protecting against AIDS related morbidity and mortality over time. Furthermore, older patients had an overall higher prevalence of co-morbidity such as hypertension and diabetes at ART initiation .We found that irrespective of age, men were more likely to die within the ART programme compared to women. This however may, in part, be reflecting the epidemiology of HIV in Sub-Saharan Africa. Here women acquire HIV at a younger age and enroll in ART programs earlier in the course of their disease through enhanced contact with health care services that traditionally offer an entry point into the HIV care continuum such as sexual reproductive health services, antenatal and perinatal services . This di+ cell count. Without CD4+ cell count in the model the difference in risk of death between the older and younger group was insignificant and hence CD4 + cell count at ART initiation is an important predictor of mortality in those ≥50 years.Our study also demonstrated that patients ≥50 years demonstrated poorer immununologic recovery on ART, as shown by poorer CD4+ cell count recovery, compared to younger patients. The slow CD4+ cell count recovery in our older cohort is consistent with other studies which indicate that older individuals have a lower rate of increase in CD4+ cell counts following ART exposure compared to younger individuals . This abTraditional age related co-morbidities appear to occur earlier in older HIV infected patients compared to HIV uninfected counterparts of the same age . We saw At baseline we noted a nine fold increase in prevalent diabetes in older patients in comparison to the younger cohort and a similar trend in hypertension prevalence.Table . A recenWhilst the prevalence of hypertension and diabetes appear to be lower than the general population, this cohort illustrates the opportunity that HIV treatment provides for comprehensive multi-morbidity care in Sub Saharan Africa.A similar prevalence was found in a Malawi cohort . PresentThe strategies of anti-retroviral therapy (SMART) and evaluation of subcutaneous Proleukein ® in randomized International trial (ESPIRIT) trials demonstrated that the frequency of Non-AIDS events was approximately 50% higher than AIDS events and the mortality of non AIDS events were double that of AIDS events . In thisThis study has the advantage of a large sample size; however, survival bias may have resulted in patients with a better prognosis entering the cohort especially in the older group. Furthermore, the proportion of those older than 50 years was smaller than those in the younger group. This disproportion may have further contributed to bias. Furthermore, the change in ART eligibility guidelines and CD4+ cell counts  treatment program (CAT) with HIV infection on antiretroviral treatment (ART) from June 2004 to December 2012. Figure S2. CD4+ count at ART initiation at different years of enrolment reflecting time dependent bias of increasing CD4+ count thresholds at ART initiation. Figure S3. Kaplan-Meier estimates of cumulative probability of death during the first 6 months for patients exposed to ART according to age groups (log rank p = 0.90). (DOCX 236 kb)Additional file 2:Table S1. Causes of death in both groups. Table S2. Mortality rate over time by age. Table S3. Mean CD4+ count over time and mean increase in relation ART initiation measurements. (DOCX 27 kb)


Introduction: A proof-of-concept study was designed to evaluate the antiviral efficacy, safety and tolerability of a two-drug regimen with dolutegravir 50 mg once daily (QD) plus lamivudine 300 mg once daily as initial highly active antiretroviral therapy (HAART) among antiretroviral (ARV)-naive patients.Methods: PADDLE is a pilot study including 20 treatment-naive adults. To be selected, participants had no IAS-USA-defined resistance, HIV-1 RNA ≤100,000 copies/mL at screening and negative HBsAg. Plasma viral load (pVL) was measured at baseline; days 2, 4, 7, 10, 14, 21 and 28; weeks 6, 8 and 12; and thereafter every 12 weeks up to 96 weeks. Primary endpoint was the proportion of patients with HIV-1 RNA <50 copies/mL in an intention to treat (ITT)-exposed analysis at 48 weeks .Results: Median HIV-1 RNA at entry was 24,128 copies/mL (interquartile range (IQR): 11,686–36,794). Albeit as per protocol, all patients had pVL ≤100,000 copies/mL at screening as required by inclusion criteria, four patients had ≥100,000 copies/mL at baseline. Median baseline CD4+ T-cell count was 507 per cubic millimetre (IQR: 296–517). A rapid decline in pVL was observed (median VL decay from baseline to week 12 was 2.74 logs). All patients were suppressed at week 8 onwards up to week 24. At week 48, 90% (18/20) reached the primary endpoint of a pVL <50 copies/mL. Median change in CD4 cell count between baseline and week 48 was 267 cells/mm3 (IQR: 180–462). No major tolerability/toxicity issues were observed. Nineteen patients completed 48 weeks of the study, and one patient (with undetectable VL at last visit) committed suicide. One patient presented a low-level protocol-defined confirmed virological failure at week 36, being the only observed failure. This patient had pVL <50 copies/mL at the end-of-study visit without having changed the two-drug regimen. Observed failure rate was 5%. This is the first report of integrase strand transfer inhibitor/lamivudine dual regimen in ARV-naive patients.Conclusions: This novel dual regimen of dolutegravir and lamivudine warrants further clinical research and consideration as a potential therapeutic option for ARV-therapy-naive patients.ClinicalTrials.gov Identifier: NCT02211482. Zidovudine (ZDV) monotherapy was the first attempt to control HIV replication. Soon after, two-drug combination became the preferred strategy, as ZDV effects lasted only for the short term, due to selection of resistance mutations. Unfortunately, the dual strategy also failed in achieving long-lasting virologic control. Combination antiretroviral therapy (ART) containing three active drugs from at least two different classes has been the standard of care for HIV treatment all over the world since 1996, based on the findings of two seminal studies .Expansion of access to antiretroviral (ARV) therapy has been the main driver of a striking 38% decline in HIV incidence and a 35% reduction in AIDS-associated mortality since 2000 .To reduce toxicity, complexity, and costs, strategies that decrease the number of active drugs have been evaluated, both as initial therapy and as maintenance therapy for patients who achieved virologic suppression. Most efforts have yielded unacceptable high rates of treatment failure . A two-dDolutegravir (DTG) is a potent INSTI, exhibiting rapid reduction in VL and a high barrier to resistance. DTG is a QD drug, well tolerated, that can be taken with or without food , with a Lamivudine (3TC) is a potent cytidine nucleoside analogue without major side effects, and it has a well-proven safety profile. In monotherapy, it has shown VL reduction up to 1.19 log . It has The purpose of this pilot study was to assess the antiviral efficacy, safety and tolerability of a two-drug regimen with DTG 50 mg QD plus 3TC 300 mg QD as initial HAART among ARV-naive patients.PADDLE is an ongoing pilot study involving HIV-1-infected patients naive to ARV treatment. Participants were enrolled in Argentina between 24 September 2014 and 28 February 2015. The last participant completed 48 weeks of treatment on 24 February 2016.This study was conducted in accordance with good clinical practice procedures, all applicable regulatory requirements and the guiding principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board . All patients provided written informed consent before entering the study.Eligible participants were 18 years of age or older, had HIV-1 infection, were naive to ARV treatment (never exposed to ARV drugs), had a plasma HIV-1 RNA level at screening visit >5000 copies and ≤100,000 copies per millilitre and a CD4+ T-cell count >200 per cubic millimetre with no evidence of genotypic of viral resistance to lamivudine as per IAS-USA 2013 resistance panel .Main exclusion criteria were previous exposure to ARVs, VL >100,000 copies/mL, CD4 count below 200 cells/mL at screening, pregnancy or breastfeeding, severe hepatic impairment, grade 4 laboratory abnormalities or alanine aminotransferase (ALT) >5 times the upper limit of normal (ULN) or ALT ≥3 times the ULN and bilirubin ≥1.5 times the ULN (with >35% direct bilirubin) or creatinine clearance of <50 mL/min via Cockroft–Gault method.All participants were assigned to receive DTG 50 mg once daily plus 3TC 300 mg once daily.In order to ensure patient’s safety, a phase 2 implementation protocol was designed: In phase 1, 10 patients were included. If, at week 8, at least 8 out of 10 patients showed a VL decrease >1 log, the study would continue to phase 2 in which another 10 patients would be enrolled. If more than two patients showed a VL decrease <1 log, the study would be discontinued. In addition, all patients would have an intensive follow-up. Patients would continue on study unless any of the following stopping rules were met: Patients with VL ≥1000 copies/mL at week 12, patients with VL ≥400 copies/mL at week 24 or 36 or patients with a confirmed viral rebound (>200 c/mL) after VL <50 c/mL.Study visits were scheduled at baseline; days 2, 4, 7 and 10; and weeks 2, 3, 4, 6, 8, 12, 24, 36 and 48. On completion of the week 48 visits, all the participants were offered the opportunity to continue in a study extension until week 96. The Abbott Real-Time HIV-1 assay was used to detect the HIV-1 RNA plasma level . Adverse events (AEs), serious adverse events (SAEs) and laboratory measurements  were assessed intermittently throughout the study, and their severity graded according to the criteria of the Division of AIDS (DAIDS) at the National Institute of Allergy and Infectious Diseases of the National Institutes of Health. Specifically, safety evaluations were completed as follows: AEs and concomitant medications on all visits and laboratory parameters and vital signs on screening, baseline and weeks 2, 4, 8, 12, 24, 36 and 48. Viral genotype was analysed (TRUGENE HIV-1 Genotyping Kit) at the screening visit and had to be obtained at time of protocol-defined virologic failure (PDVF) defined as VL ≥1000 copies/mL at week 12, VL ≥400 copies/mL at week 24 or 36 or a confirmed viral rebound (>200 c/mL) after VL <50 c/mL.Participants were required to withdraw from the study if PDVF was confirmed. Baseline was assessed with the AIDS Clinical Trials Group (ACTG) Adherence/Baseline questionnaire at baseline visit and with ACTG/Follow-up Questionnaire at visits: 4, 8, 12, 24, 36 and 48.The primary efficacy endpoint was the proportion of subjects with plasma HIV-1 RNA below 50 copies per millilitre at week 48 using the FDA snapshot algorithm  for the intention-to-treat exposed population . Secondary safety and efficacy endpoints included the frequency, type and severity of AEs and laboratory abnormalities, the proportion of patients with HIV-1 RNA <1000 copies/mL at week 12, the proportion of patients with HIV-RNA <400 at week 24, the incidence of genotypic and phenotypic resistance in case of virologic failure, the change from baseline in the CD4+-cell count, the lipid profile changes between baseline and week 48 and the viral decay rate.Virological efficacy is shown as intention-to-treat (exposed) and as per protocol. Final analysis includes 48-week results for the 20 patients. Descriptive statistics were used to evaluate the primary and secondary outcomes. The results are given as median and interquartile ranges (IQRs) or frequencies (%) as appropriate. Changes in CD4 were analysed similarly. All AEs were evaluated, summarized and described as the proportion of patients presenting events and the total number of events. In all samples with plasma HIV-RNA below limit of detection, absence of signal was tested.The study was sponsored by Fundación Huésped. Trial funding was provided by ViiV Healthcare. ViiV Healthcare contributed towards scientific review of the study design and this report. All operational aspects of the study, including study design, monitoring, data collection, data analysis and writing of the report, were managed by Fundación Huésped. All the authors had full access to all the data in the study and are responsible for the veracity and completeness of the data reported. The corresponding author has final responsibility for the decision to submit for publication.A total of 35 patients were screened, and 20 patients were included and treated .Figure Demographic and baseline disease characteristics are referred to in 3 (IQR: 180–462).All but one patient, who committed suicide, completed 48 weeks in the study and were evaluated for the primary endpoint. At week 48, 18 out of 20 subjects : 77–100), reached plasma HIV-1 RNA level of less than 50 copies per millilitre in ITT-exposed analyses .Figure In the per-protocol analyses, 18 out of 19 subjects were responders . All subjects, including the four subjects that entered the study with baseline pVL above 100,000 copies/mL, achieved VL below 400 copies at week 3 and HIV-1 RNA level of <50 copies per millilitre at 8 weeks.A rapid antiviral response was observed (median VL decay from baseline to week 12 was 2.74 logs).Through week 48, only one patient met the criteria for protocol-defined virologic failure. This patient entered the study with a pVL of 106,320 copies, achieved pVL below 400 copies/mL at day 10 and pVL below 50 copies/mL at week 4 and remained so until week 24. On the week 36 visit, his pVL was 99 copies/mL. After reviewing patient’s compliance with the protocol, and ruling out potential intercurrent infections or vaccinations, a retest was performed three weeks later, showing a pVL of 246 copies/mL. The patient was discontinued from the study, as mandated by the protocol, but was followed off-study until week 48. The latest pVL obtained at that time was below 50 copies/mL, without any change on his ARV regimen .Figure in vitro protein adjusted IC90 of viral suppression (0.064 µg/mL) [Albeit initially the subject denied any sex behaviour that might have put him at risk for reinfection, later on he disclosed that he had unprotected sexual intercourse with another male partner, who is HIV positive and on treatment, but still with detectable pVL. A virus pattern comparison between baseline and rebound could not be performed. Genotypic testing was performed at confirmed virological failure, but only the transcriptase region could be successfully amplified due to the low viremia. No mutations were found. Phenotypic resistance testing was not performed. The baseline genotypic test for integrase region did not reveal any mutation. A DTG plasma concentration was also obtained at failure. The DTG concentration in a sample collected 12 h after drug intake was 2.70 µg/mL, which was consistent with the pharmacokinetics and half-life reported in SPRING-1  and far 4 µg/mL) , providiThe study drugs were well tolerated. Eight drug-related AEs were reported in six patients: headache (3), somnolence (1), epigastric pain (1), diarrhoea (1) and nausea (2) (grade 1 to 2), with no AEs leading to discontinuation of the study drug. The most frequent drug-related AE was headache in three patients. Grade 2 to 3 laboratory abnormalities (three events in three patients) were proteinuria , creatinine phosphokinase  and haematuria . One patient reported grade 2 insomnia at entry, without changes during the study and was deemed as not related to the study drugs.One patient died during the study. He committed suicide, in the context of severe stress and emotional trauma. A relative disclosed that he had previous psychiatric disturbances, including a failed suicide attempt, which was not disclosed by the patient during his clinical visits. His death was noticed when he failed to show up at the week 36 visit. He achieved pVL below 50 copies/mL since week 2 and remained so until his last visit on week 24. No other SAEs were reported.This pilot study was designed to test the concept that a two-drug regimen based on an INSTI and lamivudine could be considered as an option for treatment-naive, HIV-infected patients. Successful dual therapy may reduce toxicity, treatment cost and the amount of drug required to be co-formulated in single tablet treatment regimens.Dual-therapy strategies have been studied with heterogeneous results that were summarized in two recent systematic reviews ,22.One of the first studies using an NRTI-sparing dual therapy was the ACTG 5142 study that compared three arms as initial ART: EFV + 2 NRTIs, ritonavir-boosted LPV/r + 2 NRTIs or EFV + LPV/r. As the dual therapy showed lower efficacy and higher risk of emergency or resistance than the others, EFV + 2 NRTIs arm became the standard of care until recent years . The GARThe patient that presented the only SAE (suicide) achieved pVL below 50 copies/mL at week 2 and remained so until his last visit on week 24. HIV and/or HAART have been previously related to suicidality. A nationwide Swiss study showed that in 2008, suicide rates in HIV-infected individuals were more than three times higher than the rates of the general population . In a voEFV relationship with suicidality has been studied with divergent conclusions, ranging from a twofold increased hazard of suicidality compared with a regimen without EFV to no increased risk at all –32. WithPDVF . Therefore, the primary analysis shows 90% of the patients with pVL <50 copies in the ITT-exposed, FDA snapshot analysis. Observed failure, as the patient who committed suicide had undetectable pVL at last visit, was 5%.Through week 48, one patient met the criteria for The clinical implications of low-level viremia are controversial. Department of Human Health Services (DHHS) ARV guidelines define virologic failure as the inability to achieve or maintain suppression of viral replication to an HIV-RNA level <200 copies/mL and state that viremia “blips” are not usually associated with subsequent virologic failure .Our study has some limitations. As a pilot proof-of-concept trial, it has a small sample size. Given that this dual regimen has been never tested before, we preferred a cautious design, treating first a cohort of 10 patients, and recruiting the second cohort when initial success was achieved, as pre-defined in the study protocol. Other limitations include being an open-label study, with a single arm and a low median VL at entry, albeit four of the volunteers had baseline pVL above 100,000 copies/mL.A limitation for using this dual regimen is that patients with active hepatitis B infection (HBV) would not be eligible, as HBV would be exposed to 3TC monotherapy, which is no longer the standard-of-care for that infection. Universal HBV vaccination is encouraged as a public health intervention, regardless of the ARV strategy selected. Special populations like pregnant women and patients with active tuberculosis were excluded, hence this strategy cannot be considered for those populations until specific studies are completed. Nevertheless, the PADDLE study strategy might potentially address several unmet needs. First, toxicities associated with NRTIs other than 3TC may compromise lifelong exposures to those compounds. Tenofovir disoproxil fumarate (TDF) lowers bone density more than other NRTIs and can be nephrotoxic ,36. AbacThe results of this small, proof-of-concept, pilot study encourage further exploration of this strategy. Our results suggest that the combination of DTG and 3TC could be considered as an alternative option in first line, sparing exposure to other nucleosides and preserving other treatment options downstream, if needed. The low rate of side effects reported in the study is attributable to the avoidance of the second NRTI. Dual therapy with DTG + 3TC could be a highly effective, simple and, in some settings, cost-effective first-line option for HIV patients. If our findings are confirmed in the ongoing randomized trials GEMINI 1 (NCT02831673) and GEMINI 2 (NCT02831764), this strategy may challenge the value of adding a third nucleosid(t)ide to the outcomes of HAART. Until then, the decision of using this dual regimen outside clinical trials should be carefully considered.


Tenofovir disoproxil fumarate (TDF)–associated renal dysfunction may abate when TDF is replaced with abacavir (ABC). The extent to which the third drug atazanavir contributes to renal dysfunction is unclear.A retrospective analysis was conducted on adults who had plasma viral load (pVL)<200 copies/mL for≥six months while receiving TDF/lamivudine (3TC) – or TDF/emtricitabine (FTC)–based antiretroviral therapy (ART), then switched to ABC/3TC while retaining the third drug in the ART regimen. CD4, pVL, creatinine, estimated glomerular filtration rate (eGFR), serum phosphorus, urine albumin to creatinine ratio and serum lipids were compared between pre-switch baseline and 3, 6 and 12 months after the switch to ABC.A total of 286 patients switched from TDF to ABC between 2004 and 2014: 232 (81%) male, median age 48 years (interquartile range (IQR) 42, 56). The third drug was atazanavir (± ritonavir) in 141 (49%) cases. The pVL was<50 copies/mL in 93 to 96% at all time points. Median serum creatinine was 93 µmol/L (IQR 80–111) at baseline and decreased to 88 µmol/L (IQR 78–98) at 12 months after the switch to ABC. Median eGFR increased from 74 (IQR 60–88) mL/min at baseline to 80 mL/min (IQR 69–89) at 12 months. Results were not significantly different between patients on atazanavir versus those on another third drug.Viral suppression was maintained among patients who switched from TDF/3TC or TDF/FTC to ABC/3TC. Serum creatinine and eGFR improved up to 12 months after switching to ABC/3TC, irrespective of whether or not patients were also receiving atazanavir±ritonavir. The appropriate use of active antiretroviral therapy (ART) among HIV-1-infected individuals leads to the suppression of viral replication, sustained undetectable plasma viral load (pVL) and CD4 recovery. ART thus halts disease progression to AIDS and premature death and increases life expectancy to near normal levels . RecommeABC is generally safe and well-tolerated, especially since the implementation of HLA-B*5701 allele screening used to predict increased risk for ABC hypersensitivity . TDF useCo-administration of PIs with TDF may be an additional risk factor for renal dysfunction ,7,10,11.TDF has an effect with a possible rebound effect after its discontinuation . In the We conducted a retrospective study to evaluate changes in serum creatinine, estimated glomerular filtration rate (eGFR) and lipid parameters among HIV-positive adults who switched ART regimens from TDF+3TC or FTC to ABC+3TC, while the remainder of the regimen continued unchanged. We also assessed whether the presence of atazanavir in the regimen affected the aforementioned parameters after the switch.www.cfenet.ubc.ca/drug-treatment-program). The DTP has received ethical approval from the University of British Columbia ethics review committee at its St. Paul's Hospital site. The program also conforms to the province's Freedom of Information and Protection of Privacy Act.We analyzed population-based data from the Drug Treatment Program (DTP) at the British Columbia Centre for Excellence in HIV/AIDS (BC-CfE) from 2004 until 2015. The DTP is a province-wide health care program, which provides free HIV medication to all medically eligible HIV-positive individuals in BC. The BC-CfE collects and de-identifies patient information and uses it for public health monitoring, drug safety, health research and other health system purposes . Starting 1 February 2008, this assay was replaced by the new COBAS Ampliprep Taqman HIV-1 assay (Roche Diagnostic Systems). In view of the documented increased frequency of detectable HIV RNA levels near the lower limit of the Taqman assay (50 copies/mL), for theRenal parameters were assessed within 12 months prior to switching and 3, 6 and 12 months (if available) after switching: serum creatinine, eGFR  , serum pMcNemar's test was used on categorical variables and Wilcoxon signed-rank test was used to compare laboratory values before and after the switch. Chi-squared test was used on categorical variables and Wilcoxon rank-sum test was used on continuous variables when comparing atazanavir and non-atazanavir groups. All analyses were performed using SAS software version 9.2  with significance level set at 0.05.n=15), Black 2.8% (n=8), First Nations 11.5% (n=33), Hispanic 2.5% (n=7), unknown 35.0% (n=100) and Caucasian 43.0% (n=123). Nearly one-third  were treatment naïve prior to initiating TDF-containing ART. The TDF-based regimen was started between 2002 and 2014 and switched to an ABC-based regimen between 2004 and 2014. Most patients (95.8%) had pVL<50 copies/mL at their most recent test prior to switching to ABC and this remained the case at 3, 6 and 12 months after the switch (93.2%–94.4%)  and increased after the switch to 550 cells/mm3 at 6 and 12 months later  were male, median age was 48 years (interquartile range (IQR): 42, 56), 15% had a prior AIDS-defining illness and the median duration of HIV infection was seven years . The eth%–94.4%) . Median hs later .Overall, renal parameters improved at each time point after switching from TDF to ABC . Serum cFasting lipid parameters showed small changes after switching from TDF to ABC, as expected . Small in=141) were taking atazanavir as the third agent in their ART regimen: 132 ritonavir-boosted (46.1%) and 9 unboosted (3.1%). Of the other 145 patients, 90 (62%) were taking non-nucleoside-based regimens (efavirenz (n=43), etravirine (n=1), rilpivirine (n=2), nevirapine (n=44)); 38 (26%) were taking a ritonavir-boosted PI other than atazanavir (amprenavir (n=1), darunavir (n=4), lopinavir (n=31), saquinavir (n=2)) and 16 (6%) were taking an integrase inhibitor . There were no significant differences between the atazanavir and the non-atazanavir groups with regard to CD4 cell counts, pVL or renal parameters at either baseline or any time point thereafter, with the exception of serum phosphorus, which was lower  in the non-atazanavir group than in the atazanavir group at 12 months . Otherwise, there was no significant difference in lipid parameters between the non- atazanavir and atazanavir groups at any time point (With regard to lipid changes, triglycerides were higher in the atazanavir group than in the non-atazanavir group at month 12 only (2.21 vs. 1.70 mmol/L, respectively, me point .We conducted a retrospective analysis of 286 HIV-infected patients who were switched from a TDF- to an ABC-based ART, while continuing the rest of antiretroviral drugs in the regimen. Our results show a modest, but significant, improvement in serum creatinine, eGFR and UACR results up to 12 months after the switch, without significant changes in the proportion of patients with undetectable plasma HIV RNA after the switch to ABC.The median baseline eGFR in the study group was 74 mL/min, indicating some degree of kidney impairment according to standard definitions . WhetherIt has been reported that HIV-positive patients exposed to TDF-based regimens have a higher incidence of chronic renal dysfunction that in many cases is reversible once TDF is discontinued , but notet al. [Other antiretrovirals, particularly the PIs indinavir and atazanavir, have also been associated with renal function abnormalities . In a stet al.  patientset al. . It is iIn this retrospective analysis, patients receiving atazanavir had no statistically different changes in their serum creatinine and eGFR after the discontinuation of TDF as compared to those not receiving atazanavir. In a retrospective analysis of 230 patients, half of which received TDF and the other half ABC-based therapy, a significant renal impairment in the patients receiving TDF was observed, but there was no correlation to PI use . FurtherWith respect to the lipid parameters, our results confirm the earlier findings of an increase in lipids after TDF discontinuation , althougWe recognize this study has several limitations. Firstly, this is not a randomized controlled trial and given its retrospective nature does not allow for comparison with a control group and may be affected by selection bias. Next, we could only assume the reason why the patients were switched from TDF to ABC based on the standard of care in our clinic. Because of the retrospective nature of this analysis, we were unable to examine novel indicators of proximal renal cell dysfunction, like urinary excretion of phosphate, glucose, uric acid or the fractional excretion of phosphate . FinallyIn conclusion, a significant improvement of the serum creatinine, eGFR and UACR was observed in 286 HIV-positive patients who were switched to ABC after receiving a TDF-based ART regimen for at least six months. Of note, after the switch, the plasma HIV RNA remained suppressed and the CD4 cell count increased in the majority of patients. Similar trends were observed regardless of whether or not the third drug in the regimen was atazanavir. These findings highlight that it is safe and effective to switch from TDF to ABC if there are concerns regarding serum creatinine and eGFR, as long as the HLA-B*5701 test is negative and the patient's HIV RNA viral load is suppressed. Finally, the continued use of atazanavir did not appear to have a significant effect on the recovery of the renal function parameters.


We investigated whether patients receiving selected antiretroviral combinations had a higher risk of chronic kidney disease (CKD) using traditional regression modeling and a causal approach in a large prospective cohort.st January 2004, (ii) had at least one serum creatinine measurement within 6 months before ART initiation (study entry), and (iii) had at least two measurements after study entry. Baseline eGFR was defined from the last serum creatinine measurement before study entry. All eGFR values were calculated using the Modification of Diet and Renal Disease (MDRD) equation. Both traditional Cox proportional hazards model and Cox marginal structural models were applied. Distinct coding for antiretroviral therapy exposure were investigated as well as double robust estimators.For the purpose of this study, we selected 6301 patients who (i) started their first antiretroviral regimen after 1Overall we showed that patients receiving tenofovir (TDF) with a ritonavir boosted protease inhibitor (rbPI) exhibited a higher risk of CKD compared with patients who received TDF with a non-nucleosidic reverse transcriptase inhibitor (NNRTI). Such an increased risk was observed considering both initial and current regimens. Our analysis revealed a clinician-driven switch away from TDF among persons experiencing a decline in renal function while receiving this drug.Our results show that combination of TDF and boosted protease inhibitor is associated with a higher CKD risk than TDF and a NNRTI. Patients living with HIV have an increased risk of chronic kidney disease (CKD) by comparison with the general age-matched population, for various reasons including the use of some antiretroviral agents (ARVs) , 2. ARVs2 or >90 ml/min/1.73m2 [2), CKD stage 3b (<45 ml/min/1.73m2), CKD stage 4 (<30 ml/min/1.73m2), or a change in the eGFR slope (pre-ART versus on ART) [Many studies aimed to investigate CKD risk factors, including both traditional renal risk factors and ARVs. Summarizing the information is complex due to the various studied populations, endpoints, statistical methods and variables coding. The studied population may concern all HIV-infected individuals with at least two estimated glomerular filtration rates (eGFR) measurements or be restricted to individuals with baseline eGFR>60 ml/min/1.73mn/1.73m2 –9. Outco on ART) . Differe on ART) , whether on ART) . Analyse on ART) , 12.Some studies have shown that regimens including tenofovir (TDF) in association with a ritonavir boosted protease inhibitor (rbPI) were related with greater eGFR decline by comparison with regimens based on TDF and a non-nucleosidic reverse transcriptase inhibitor (NNRTI). Unfortunately, those studies involved relatively small numbers of patients and did not investigate the occurrence of CKD –15. A re2) using different statistical considerations applied to a large prospective cohort of patients living with HIV. We investigated the risk of CKD in patients receiving a combination with or without TDF in association either with a rbPI or a NNRTI. CKD risk was investigated in relation with the initial regimen for all events occurring during the follow-up or only for those occurring during the initial regimen.Our aim was to evaluate ARV exposure as a risk factor for CKD  equation. Other baseline values were defined at or before ART initiation.Information was collected from 12 centers in France participating in the Dat’AIDS cohort  after approval by French National Committee on Informatics and Human Rights (CNIL n°1357652) . The aut2. Time to event was the time between ART initiation and the first eGFR below 60 ml/min/1.73m2. Antiretroviral regimens were categorized into five mutually exclusive combinations: TDF combined with a rbPI (TDF+/rbPI); TDF combined with a NNRTI (TDF+/NNRTI); a rbPI without TDF (TDF-/rbPI); a NNRTI without TDF (TDF-/NNRTI); and any other combination with or without TDF (Other ART). The “other” regimen was only used to adjust for other types of regimens and no hazard ratios are provided. Initial, current or past regimens were classified according to these categories. Past regimens included only the regimens immediately prescribed before the current regimen.CKD event was defined by a confirmed (3 months apart) eGFR below 60 ml/min/1.73mOur main objective was to determine whether patients receiving a regimen of TDF+/rbPI had a greater risk of developing CKD by comparison with patients receiving other regimens, in particular those receiving TDF+/NNRTI. We also compared results obtained using different statistical methods corresponding to different analyses and objectives. We conducted two analyses as to examine the effect of ART exposure on the risk of CKD. The first analysis was based on a series of standard proportional hazard models involving all CKD events occurring during the follow-up. Different ways of exploring the association between regimen-types and CKD were investigated. All those models were adjusted for baseline and time-varying variables introduced in the next section. The second analysis examined only the association between the initial regimen type and CKD occurring while patients received this first regimen, censoring patients upon any change in ART. This latter analysis involved both standard Cox regression models and marginal structural proportional hazards model based on a causal approach. Double robust estimators were also provided to prevent potential model misspecification –19.Potential baseline confounding factors were age, CD4 cell count nadir, CD4 cell count, viral load (HIV-1 RNA), eGFR, year of ART initiation, gender, HIV exposure , HCV or HBV co-infections, prior diabetes, hypertension and cardiovascular disease (CVD). Prior diabetes, hypertension and CVD were considered present if notified in the patient’s medical history or if the patient’s prescriptions contained any drugs in relation with these diseases.Standard proportional hazards models were adjusted for baseline confounders and also for time-varying CD4 cell count and viral load using the last value-carried-forward method. In the causal approach, eGFR measured at different visits was also used as time-varying confounders of the relationship between ART exposure and both censoring and switch from the initial regimen.A first series of standard proportional hazards models was fitted to the dataset. These models were used to examine the relationship between regimen-type exposure with CKD adjusted for baseline and time-varying variables. In this first series the number of events is the total number of CKD occurring during follow-up. A first model investigated the association between occurrence of CKD with initial regimen-type, a second model considered the regimen-type as a time-varying covariate (current regimen-type), and a third model used both current and past regimen-types. All patients were included in these analyses whether or not they remained on their initial ART regimen.Propensity scores and Marginal Structural Models (MSM) have been introduced to overcome the lack of randomization in observational studies , 20, 21.Doubly robust estimation combines outcome regression with weighting by the propensity score such that the effect estimator is robust to misspecification of one of these two models , 19, 22.Negative binomial models were used to investigate ART regimen-type discontinuation rates in relationship to the current eGFR level . No adjuA.Baseline and time-varying continuous variables were explored in different ways including linear terms, categories, cubic and quadratic spline with four knots. In particular, we followed the recommendations and guidelines of Cole and Hernan for constructing IPTW . IPTW weth, 50th and 90th percentiles) for the month since study entry were used for a time-dependent intercept [3), viral load  and eGFR  were included as step function (categories) in pooled logistic models. The mean of the final stabilized weights SW(t) were 0.998  with a range of 0.33 to 3.73. These weights are shown over follow-up in Each person’s follow-up was divided into a series of consecutive 1-month periods and each person’s covariate data  was also updated at the start of each month . Pooled ntercept . ContinuBaseline characteristics of the 6 301 included patients are described in Overall, 2 963 (47%) patients remained on their initial regimen throughout the follow-up, including 48 and 66% of the patients who received initially TDF+/rbPI or TDF+/NNRTI, respectively, and 37% and 34% of the patients who received initially a TDF-/rbPI or TDF-/NNRTI regimen respectively. The median number of regimens received was 2 (IQR: 1–2) and only 610 (10%) patients received 3 or more regimens in addition to the initial regimen. From 2004 to 2013, the relative proportion of person-years receiving a regimen without TDF decreased from 65 to 23%. In contrast, the relative proportion receiving a TDF-containing regimen increased from 9 to 58%, especially with a NNRTI, from 3 to 29% .Incidence rate ratio, adjusted for baseline covariates, of switching away from current regimen-types during follow-up significantly increased as eGFR declined for the TDF+/rbPI regimen . Conside2, respectively.Occurrence of CKD was observed in 211 (3.4%) patients, corresponding to an incidence of 9.6 , 8.3–10.9) cases per 1000 person-years. Among those, 87 (41%) patients developed CKD while on their initial ART regimen, incidence of 6.9  cases per 1 000 person-years. Of note, only 31 (0.5%) and 9 (0.1%) patients developed CKD stage 3b defined with a confirmed eGFR below 45 and 30 ml/min/1.73mAll comparisons in both Tables Results of analyses of the risk of CKD occurring while patients were still receiving their initial regimen are summarized in Adjusting models with baseline and time-varying confounders show similar HR estimates although not statistically significant for patients receiving TDF-/rbPI. Weighted and double robust models, based on our causal approach, show that patients who received TDF+/rbPI had still a higher risk of CKD than those treated with TDF+/NNRTI . Patients who received TDF-/rbPI have also a higher risk of CKD though marginally significant.We showed that patients receiving tenofovir in association with a ritonavir boosted protease inhibitor exhibited a higher risk of CKD by comparison with patients receiving tenofovir in association with a non-nucleosidic reverse transcriptase inhibitor. This result was found in all our analyses, whatever the statistical methods, both for the CKD events occurring while patients received their initial regimen and for the CKD events observed during the follow-up. Rates of discontinuation in patients receiving a TDF-containing regimen increased as current eGFR decreased, indicating clearly that eGFR is a time-varying confounder in the relationship between CKD and ART exposure.Several studies suggested a higher risk of CKD in patients receiving TDF in combination with a rbPI by comparison with patients receiving TDF with a NNRTI , 13, 14.Our study has some limits. We used MDRD estimations of GFR because our available data did not allow the use of Cockroft-Gault formula nor Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation, which is currently recommended by the latest guidelines of the Infectious Diseases Society of America . Not allThe first series of analyses based on standard proportional hazard models provided different results according to how ART exposure was coded in models, corresponding to different objectives. Approximately 60% of CKD occurred after patients moved from their initial regimen. Thus, considering only the initial regiment-type captures only a part of the relationship between ART exposure and risk of CKD. This has been done in the study published by Kalayjian and colleagues . It shouThe use of current ART exposure as a time-varying variable in standard proportional hazard models indicated that all regimen-types are associated with an increased CKD risk compared with TDF+/NNRTI. Omission of variables summarizing the history of ART exposure in that model likely explained such results. Some CKD events occurred after many years of ARV exposure. This can be explained by the long-term effect of ARV on CKD risk . AdditioAnalyses based on our causal approach, though limited to a relatively small number (87) of CKD events, show an association between an initial regimen based on TDF+/rbPI and an increased risk, by comparison with initial regimens based on TDF+/NNRTI. Considering only CKD events occurring while patients were still receiving their initial regimen, all models provide similar findings.In conclusion, we observed a higher risk of CKD in patients receiving TDF+rbPI, compared with patients receiving TDF+NNRTI. Incidence rates of CKD found in our work are in agreement with those found in other studies. Current eGFR is clearly shown as a prognostic factor of switching away from a TDF-containing regimen. Consequently, e-GFR should be then taking into account in estimated stabilized weights for marginal structural models and double robust estimators.This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.S1 File(DOCX)Click here for additional data file.S1 Fig(DOCX)Click here for additional data file.


Systematic reviews have described high rates of attrition in patients with HIV receiving antiretroviral therapy (ART). However, migration and clinical transfer may lead to an overestimation of attrition (death and loss to follow-up). Using a newly linked national laboratory database in South Africa, we assessed national retention in South Africa’s national HIV program.3 (IQR: 81–230), and 66.7% were female. Six-year initiating clinic retention was 29.1% (95% CI: 28.7%–29.5%). After allowing for transfers, national 6-year retention was 63.3% (95% CI: 62.9%–63.7%). Results differed little when tightening or relaxing matching procedures. We found strong differences in retention by province, ranging from 74.2% (95% CI: 73.2%–75.2%) in Western Cape to 52.2% (95% CI: 50.6%–53.7%) in Mpumalanga at 6 years. National attrition was higher among patients initiating at lower CD4 counts and higher viral loads, and among patients initiating ART at larger facilities. The study’s main limitation is lack of perfect cohort matching, which may lead to over- or underestimation of retention. We also did not have data from KwaZulu-Natal province prior to 2010.Patients receiving care in South Africa’s national HIV program are monitored through regular CD4 count and viral load testing. South Africa’s National Health Laboratory Service has maintained a database of all public-sector CD4 count and viral load results since 2004. We linked individual laboratory results to patients using probabilistic matching techniques, creating a national HIV cohort. Validation of our approach in comparison to a manually matched dataset showed 9.0% undermatching and 9.5% overmatching. We analyzed data on patients initiating ART in the public sector from April 1, 2004, to December 31, 2006, when ART initiation could be determined based on first viral load among those whose treatment followed guidelines. Attrition occurred on the date of a patient’s last observed laboratory measure, allowing patients to exit and reenter care prior to that date. All patients had 6 potential years of follow-up, with an additional 2 years to have a final laboratory measurement to be retained at 6 years. Data were censored at December 31, 2012. We assessed (a) national retention including all laboratory tests regardless of testing facility and (b) initiating facility retention, where laboratory tests at other facilities were ignored. We followed 55,836 patients initiating ART between 2004 and 2006. At ART initiation, median age was 36 years (IQR: 30–43), median CD4 count was 150 cells/mmIn this study, HIV care retention was substantially higher when viewed from a national perspective than from a facility perspective. Our results suggest that traditional clinical cohorts underestimate retention. In a large observational study, Matthew Fox and colleagues investigate retention in HIV care in South Africa allowing for patient transfers between clinics. Since the large-scale rollout of HIV treatment in resource-limited settings, evidence suggests that retention in HIV treatment programs  has been suboptimal.However, to date, most analyses have been from the perspective of individual cohorts where researchers do not have the ability to trace patients who move from one HIV treatment site to another, something we suspect is common.Failure to account for patient movement between clinics (sometimes referred to as “silent transfer”) can make estimates of retention in care seem worse than they really are, and this has implications for planning and where to target interventions to reduce losses from HIV programs.We took advantage of the fact that South Africa has a national provider of laboratory investigations, the National Health Laboratory Service (NHLS), that has maintained results on most patients in South Africa since the beginning of the treatment program in 2004 .We used probabilistic matching techniques to turn these data into a longitudinal cohort that could be used to determine when patients were lost to follow-up and when they moved between clinics.This allowed us to compare retention in care from the perspective of the clinic (the perspective most often reported) and from the national perspective, which accounts for movement between sites.We found that from the clinic perspective, among patients who started HIV treatment according to national guidelines between 2004 and 2006, 29.1% were still in care 6 years later.However, when looking from a national perspective, which accounted for movement between clinics, retention was estimated to be 63.3% at 6 years.Our findings suggest that there is substantial movement between HIV clinics in South Africa, and that ignoring these movements has the potential to strongly underestimate retention in HIV care.Future efforts to see if these trends continue in later cohorts will be important to developing effective interventions aimed at reducing loss from HIV care. In 2015, the World Health Organization (WHO) recommended removing CD4 count thresholds for HIV treatment eligibility  and reduTo date, estimates of retention worldwide in HIV treatment programs have varied widely. In a 2015 review, we found that global retention was 74% at 24 months and 60% at 60 months . ResultsIn contrast, the numbers estimated to be on ART in cross-sectional analyses suggest that a higher proportion of patients who have started ART are still in care . It is uThe impact of patient movement may potentially be a large source of bias in retention estimates in countries like South Africa where in-country migration is common . AdditioUntil now, lack of a national, integrated clinical ART database in South Africa has made it difficult to determine if retention outcomes observed in research cohorts are nationally representative, and we have not been able to correct for silent transfers . We used probabilistic matching to link individual laboratory results to transform South Africa’s national laboratory database into a national longitudinal HIV cohort ,30. The The National Health Laboratory Service (NHLS) provides nearly all diagnostic pathology services for South Africa’s public-sector health system, including all CD4 count and viral load tests conducted in public-sector facilities since ART rollout in 2004 . All laboratory test results are stored at the NHLS Corporate Data Warehouse. Patients do not pay for treatment or for testing to be done.NHLS data include patient name, birth date, sex, facility, test dates, and results. Because the database has no unique patient identifier, we created a probabilistic record-linkage algorithm, using a modified version of the Fellegi–Sunter method ,33, in wWe validated our approach against a manually matched quasi-gold standard developed by manually coding a random sample of >59,000 potential matches. All of these potential matches were validated by having a team of research assistants adjudicate if the match was indeed a true match. Our algorithm performed well in terms of avoiding overmatching  and undermatching . We found a sensitivity of 91.0%  and positive predictive value of 90.5% . We additionally used our algorithm to identify the subset of 55,836 patients who were linked with high confidence, i.e., those who neither lost nor gained records as the threshold to define a match was varied. Because overmatching could lead to falsely identifying transfers across facilities, we restricted the study sample to these high-quality matches  for our primary analysis. In robustness checks, we included all 72,256 patients and completed other sensitivity analyses using less restrictive criteria (described below) that included up to 118,720 patients.n = 19,415). We defined ART initiation to have occurred at the date of the first viral load.We included patients initiating ART during the period April 1, 2004–December 31, 2006, when viral load testing was recommended at ART staging . While aAttrition (defined as 1 minus the proportion of patients who were retained) included death and loss to follow-up as we cannot distinguish between the 2 events with our data. As clinic visit dates are not available, we defined retention based on laboratory monitoring. During the study period, there were some changes in monitoring protocols; however, the longest a patient should have gone without monitoring is 1 year.We defined attrition retrospectively, with attrition occurring on the patient’s last observed laboratory date, allowing patients to exit and reenter care prior to that date. Patients contributed person-time from ART initiation  until the earlier of attrition or December 31, 2012. All patients had 6 potential follow-up years plus an additional 2 years  to have a laboratory measurement to determine retention at end of follow-up . Patients with a lab test in those additional 2 years were considered retained at 6 years; otherwise, they were considered lost and censored at their last lab date. Two years was used to allow patients a grace period of 1 year after the maximum period a patient should have had between viral loads, which was 1 year. We censored follow-up at the end of 2012 as some facility identifiers in the NHLS dataset changed in 2015, making it difficult to identify retention at the same clinic. For this analysis, patients contributed person-time up to the time of their last viral load even if they missed viral load tests in between.Numerous definitions of retention have been proposed –41. We dWe defined transfer between clinics as a patient having a laboratory test at a clinic other than their initial clinic. We defined the transfer date as the last date the patient was at their initiating clinic. We cannot distinguish between formal transfer (where a patient notifies the clinic) and silent transfer (where the patient switches clinics without informing the initiating clinic). For the analysis of transfers, we considered only the first movement between clinics and did not consider further movements to a third clinic or back to the initiating clinic. Patients who made multiple moves were still considered retained in the retention analysis as long as they continued to meet the retention definition. CD4 count at ART initiation was defined as the value closest to initiation that was between 12 months prior to and 3 months after a patient’s date of first viral load.We did not do any sample size calculations but included all patients in the national cohort who met the inclusion criteria. We described retention using Kaplan–Meier curves of time since ART initiation from both the clinic and the national perspective. We stratified analyses by sex, age, CD4 count and viral load at ART initiation, clinic size , and province. We assessed predictors of retention using Cox proportional hazards regression. Finally, we looked at movement between provinces by classifying patients by whether they moved to facilities outside their initiating province and, if not, by any movement between facilities within their initiating province. We did not impute missing data but do report the numbers missing from analyses. We did not have a pre-established analysis plan or published protocol.The study was approved by the Human Research Ethics Committee of the University of the Witwatersrand and the Boston University Institutional Review Board for use of de-identified data with a waiver of consent.3 (IQR: 81–230).The NHLS cohort contained 55,836 people who initiated ART in South Africa between 2004 and 2006 . The popSix-year retention for the national cohort is shown in 3  and saw little change in the results  and those with a CD4 count of <50 cells/mm3  over the 6 years. We found similar associations with viral load at ART initiation . Further, we found a small but consistent dose–response increase in attrition associated with quintile of clinic size. Those in clinics in the highest quintile  were 25%  more likely to experience attrition as those in the smallest clinics (1–43 patients). We also observed an association between male sex  and increased attrition. With respect to age, the relationship was not linear, with the oldest and youngest groups having the highest rates of attrition.The previous analyses are not adjusted for other covariates. Adjusted hazard ratios (HRs) of national attrition are shown in In this national assessment of retention in South Africa’s HIV program, we found that among patients starting ART in 2004–2006, national retention was 63.3% (95% CI: 62.9%–63.7%) at 6 years, more than twice the proportion retained at the initiating clinic . This 34.2 percentage point difference suggests that considering retention only from the perspective of the initiating clinic, the approach most commonly used to estimate retention in clinical cohort studies, strongly overstates attrition.We note that our estimates—which are based on laboratory monitoring data—may understate retention if there are gaps in clinical adherence to national monitoring protocols. Nevertheless, the relative difference in retention observed when moving from a facility to a national perspective suggests that existing facility-based estimates of patient retention may be too low. Further, even in our sensitivity analysis in which we used a prospective attrition definition (first time to attrition), the differences were still meaningful, with patients more than twice as likely to be retained within the health system as at the initiating clinic at 6 years. The lower estimate of national retention obtained using a prospective definition most likely reflects the fact that gaps in care are common, though this is also likely influenced by imperfections in linking laboratory results.While there are no systematic reviews with sufficient follow-up to compare our findings to, we can compare them to our 2015 retention review through 5 years , but onlAs our results reflect retention for all patients, even those who transferred clinics, we were also able to assess retention from the clinic perspective (which often would not have been informed about transfers). Our 6-year retention results accounting for patient movement differ dramatically from our results assuming that a patient who left a clinic was lost, with about a 30 percentage point difference between them. We note that this analysis does not account for known formal transfers, which clinics typically would not count as attrition but we did. Still, we found that movement between clinics was common. This is important for reporting on overall retention as well as numbers initiating ART, as silent transfers are often treated by clinics as new patients, biasing retention estimates .It is not clear at this point whether our results generalize to other countries, and there is reason to believe they may not tell us what is occurring outside South Africa. South Africa’s national program includes some very large clinics in urban areas, which may drive the results to a certain extent, and clinic practices in South Africa likely differ from those in other countries. In addition, we do not yet know if these findings represent what is occurring in South Africa’s ART program currently, as scale-up of treatment may mean that transfers are more common now (as patients have more options) but may also mean less attrition from a national perspective as care may be more convenient to patients. In addition, shifts to decentralizing HIV care and moving care out of stand-alone clinics and into primary care may also impact generalizability. As we refine our methodology to allow us to identify ART initiation after viral load testing at ART initiation was discontinued, we will be able to assess changes in retention over time.3 had the highest attrition while those in each of the CD4 categories ≥100 cells/mm3 had roughly similar attrition to each other. The impact of mortality may be muted by the impact of higher loss to follow-up among those who are younger. We also found a relationship between clinic size and attrition, with higher attrition seen at larger clinics. We do not know for sure the reason for this, but we do suspect that this represents a combination of factors including a rural–urban divide, with larger clinics in urban areas, while also representing the impact of clinic crowding and the fact that large clinics likely see complicated cases that are at higher risk of attrition and early mortality. We also found some differences by age, with highest attrition among the oldest and youngest patients. This likely reflects mortality among the oldest patients and loss to follow-up among the younger patients, but without specific mortality data we cannot say for sure. Differences were small by sex, with somewhat higher attrition among men, but to the extent that they reflect real patterns, they probably reflect differences in care seeking behaviors between men and women.Our findings that CD4 count and viral load at entry into care are predictive of attrition are not surprising. Many prior cohorts have found similar patterns ,44, and Our results highlight the impact of silent transfers on retention estimates. One approach proposed for dealing with silent transfers is tracing methods that use samples of patients lost and that apply the resulting proportion of patients in care at a new clinic from the sample to the full cohort ,26,45. AAnother key finding in our study is that movement between clinics over time was quite common in this population. We found that nearly half of all patients enrolled in the early years of the program had at least 1 transfer. Most of those transfers were within the same province. This high rate of transfers makes sense for several reasons. First, as the national HIV care and treatment program developed, more clinics opened, particularly in urban areas, giving patients more choices for where to seek care. Patients might move to a different clinic farther from their community to allow some level of anonymity, or to a clinic closer for more convenience. Second, migration is common in South Africa for work-related reasons, particularly among men, and it is common among women at the time of pregnancy, when women may return to a family home either during or after giving birth in order to receive support for caring for the child. In terms of movement between provinces, much of this movement reflects movement to areas with higher population density and opportunities for work, especially Gauteng province, where Johannesburg and Pretoria reside. It will be important for future research to attempt to determine the reason for this movement to ensure a high rate of linkage to care as movement occurs.We note that our results only apply to patients who received viral load testing at baseline as recommended by treatment guidelines at the time. Other patients who initiated ART but did not have a viral load test would not be observed. During the time, government data suggest that 239,000 patients were receiving ART in early 2006  compared3 (the eligibility cutoff at the time) at the time of ART initiation. Some of these patients may have had a first viral load observed in the database when they were already on ART, either because no baseline viral load was taken at initiation or because of possible undermatching in the probabilistic linkage, in spite of high matching sensitivity. Because our analysis was approved only on de-identified data, we could not validate first viral load as a proxy for ART initiation. Taken together, however, these limitations suggest that our analyses did not start at ART initiation for all patients, but it is unclear what direction this would bias results. We also note that our definitions of cycling in and out of care and transfer between sites are limited in that we cannot observe clinic visits and as such we can only observe large gaps in care. This analysis is also limited by the fact that we cannot distinguish between movement between sites and patients who seek care at more than 1 site . Finally, our primary analysis includes patients with 2 viral loads to ensure initiation, but this could overstate retention, excluding in particular those patients who were lost to follow-up shortly after initiating therapy. Our sensitivity analyses show that although the overall levels of retention are sensitive to the inclusion/exclusion of patients with just 1 viral load, the substantive conclusions are largely the same.Our data have some important limitations. First, our probabilistic matching to create our cohort was subject to both over- and undermatching, which may lead to over- or underestimation of retention. However, our primary results excluded patients linked to laboratory results with low confidence, and our results were robust to the inclusion of these patients. Second, we used information on clinic to determine the match probability, meaning that, all things being equal, laboratory tests from the same facility were more likely to be linked to each other, which biases estimates of movement between clinics downward. Third, we focused only on the 2004–2006 cohort in order to describe retention since ART initiation. Trends may change with later cohorts as more clinics were in place, stigma was reduced, and treatment initiation protocols were different. It is also not clear that such patterns will continue to hold as the program matured and CD4 count thresholds increased and, more recently, were removed. Healthier patients enrolling into programs and initiating ART may have different retention patterns than those initiating with very low CD4 counts. In addition, it is not clear that the mobility patterns we observed will have continued as the program and the countrywide migration patterns changed. Future analyses could shed light on this if a validated approach can be identified to allow identification of ART initiation in this laboratory cohort after viral load testing at staging was no longer recommended in South Africa. Fourth, because we defined retention based on laboratory values and not visits, it is possible patients could have been in care but not receiving laboratory monitoring. These patients would be considered lost when they should be considered retained in care. This likely accounts for differences between our cohort and other cohorts and TIER.net. Fifth, we were not able to include data from KwaZulu-Natal, a province with large numbers of patients on treatment. Because HIV prevalence is so high in this province, our numbers are lower than would be expected in a national analysis. In addition, because migration is common in this province, our estimate of movement between clinics may be underestimated. Sixth, we cannot distinguish between loss to follow-up and death. Seventh, we cannot guarantee that all clinics in South Africa were using viral load testing at ART staging as guidelines stipulated. If some clinics were ignoring the viral load at staging, we might be identifying the first viral load on treatment rather than the date of ART initiation; if so, we might be missing some attrition that occurred between ART initiation and first viral load on therapy. Further, if a patient was particularly ill, it is possible that a clinician may have initiated the patient onto treatment without taking the ART initiation viral load. Our results also featured a higher than expected number of patients with CD4 counts at or above 200 cells/mmThe world over, retention in HIV care is suboptimal, but few analyses have shown this on a national scale. Our results show that, compared to clinic-only perspectives, national retention is likely substantially higher. This is because patients exiting care from the initiating clinic may reenter care elsewhere  and appear as lost to follow-up when they are still in care. These results are encouraging as they suggest patients who left care after starting treatment early in the epidemic often returned to care at later points in time. Further research will be needed to understand the care trajectories and long-run health outcomes of patients who cycle into and out of care at multiple facilities.S1 STROBE Checklist(DOC)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.S4 Appendix(DOCX)Click here for additional data file.S5 Appendix(DOCX)Click here for additional data file.


Deep venous thrombosis (DVT) and its major complication pulmonary embolism (PE) are collectively known as venous thromboembolism. In Uganda, the prevalence of DVT among HIV patients has not been previously published. The aim of the study was to determine the prevalence and sonographic features of lower limb deep venous thrombosis among HIV positive patients on anti-retroviral treatment (ART).This was a cross sectional study in which HIV positive patients on ART were recruited from an out-patient HIV clinic at Mulago National Referral Hospital. Patients were randomly selected and enrolled until a sample size of 384 was reached. Study participants underwent compression and Doppler ultrasound studies of both lower limb deep veins using Medison Sonoacer7 ultrasound machine.We found a prevalence of DVT of 9.1% (35 of 384 participants) among HIV patients on ART. The prevalence of latent (asymptomatic) DVT was 2.3%. Among 35 patients with DVT, 42.8% had chronic DVT; 31.1% had acute DVT and the rest had latent DVT. Among the risk factors, the odds of occurrence of DVT among patients with prolonged immobility were 4.81 times as high as in those with no prolonged immobility . Treatment with second line anti-retroviral therapy (ART) including protease inhibitors (PIs) was associated with higher odds of DVT occurrence compared with first line ART . The odds of DVT occurrence in patients with a lower CD4 count (< 200 cells/µl) were 5.36 times as high as in patients with CD4 counts above 500 cells/µl (p = 0.008). About 48.6% patients with DVT had a low risk according to Well’s score.DVT was shown in nearly 10% of HIV patients attending an out-patient clinic in an urban setting in Uganda. Risk factors included protease inhibitors in their ART regimen, prolonged immobility, and low CD4 count (< 200 cells/µl). Clinicians should have a low threshold for performing lower limb Doppler ultrasound scan examination on infected HIV patients on ART who are symptomatic for DVT. Therefore, clinicians should consider anti-coagulant prophylaxis and lower deep venous ultrasound screening of patients who are on second line ART regimen with low CD4 cell counts and/or with prolonged immobility or hormonal contraception. Deep venous thrombosis is one of the most prevalent medical conditions . The risThis study was conducted from May 2014 to January 2015. This was a cross sectional study in which adult HIV positive outpatients on ART were recruited from the Infectious Diseases Institute and HIV clinic at Mulago Hospital. Participants were attending for routine follow-up of their HIV. Participants unable to understand the procedure and unable to consent for ultrasound scan examination were excluded. Using systematic sampling , patientThe patients were categorized depending on the ultrasound findings: latent DVT when there was lack of venous compressibility or reduction of blood flow on ultrasound; acute DVT was diagnosed in the presence of hypoechoic thrombus with limited venous compressibility; chronic DVT when there was hyper echoic or heterogeneous thrombus and limitation of venous compressibility. Proximal DVT was diagnosed in the presence of a thrombus in common femoral vein up to popliteal vein whereas distal DVT was seen below the popliteal fossa. A Wells score was calculated for each patient based on the presence of clinical symptoms. At the time of the study, WHO and Ugandan guidelines recommended first line ART to be backbone of nucleoside reverse transcriptase inhibitors (lamivudine/zidovudine or lamivudine/tenofovir) with either nevirapine or efavirenz non-nucleoside reverse transcriptase inhibitors. Second line regimens for those who had failed first line was either of these backbones with a protease inhibitor; either ritonavir boosted lopinavir or ritonavir boosted atazanavir. A structured non-disguised questionnaire was used and acquired data were entered using EPI—DATA 3.02 and exported to be analysed using a statistical software program STATA 13.The study was approved by the IDI Scientific Review Committee (SRC) and the School of Medicine Research and Ethics Committee (SOMREC).Three hundred eighty-four patients were enrolled. 286 participants were aged between 18 and 50 years (74.5%) and the remainder were above 50 years (25.5%). The most common occupation in 38.5% of participants was business  were on first line ART regimen and 155 (40.4%) participants were on second line.The prevalence of lower limb DVT was 9.1% (35/384) Table . Among 3Among participants who had DVT, 4 (11.4%) reported the use of hormonal contraception. Patients with hormonal contraception use had a high probability of DVT (p = 0.024).On the Wells scoring out of 35 patients with DVT, 17 (48.6%) patients had a low probability of DVT, 8 (22.9%) patients had moderate probability of DVT and 10 patients had high probability of DVT. Study findings showed that among 35 patients with DVT, 23 (65.7%) patients had leg swelling (p < 0.0001).In the bivariate analysis, study findings showed that prolonged immobility, platelets count, latest CD4 count, and ART line regimen had an association with deep venous thrombosis . The other sonographic characteristic of DVT noted in this study were the same characteristics reported in other studies , 14.Majority of participants found with DVT had clinical symptoms of this pathology Table  and onlyThere was a significant association between PIs containing second line ART and deep venous thrombosis in patients (p = 0.02) which is in keeping with several other studies. HIV-infected patients on second line ART regimen (PIs) have higher risk for blood clot formation than those on first line treatment , 15, 16.This study shows significant association between hormonal contraception use and DVT (p = 0.024) as per well known evidence for increased risk of VTE associated with combined hormonal contraceptive use generally .Eleven (2.9%) of 384 participants had history of immobility in the last 3 months. Among 35 participants with DVT, 4 (11.4%) had history of immobility (p = 0.005). This is also in line with other studies suggesting that chronic immobility (> 30 days) is a high risk for deep venous thrombosis –19. Thes3), 5 participants (14.3%) had DVT. Therefore, correlation between low CD4 and DVT was significant even after correcting for immobility which may be associated with higher rates of opportunistic infections in people with low CD4 counts. Several studies reported the same findings [Our study showed that among 23 participants (6%) with low CD4 cell counts  and analysis of other coagulation biomarkers should also be considered in relation to blood clot formation in this population with hypercoagulable state.The prevalence of DVT among ambulatory HIV positive patients on ART is 9.1%. Majority of participants with DVT were symptomatic. Prolonged immobility, low CD4 count (< 200 cells/µl) and ART second line (PIs) were associated with risk of DVT. It is advisable to perform lower limb Doppler ultrasound scan examination on infected HIV patients on ART who are symptomatic for DVT. However, half of patients with a DVT had a low Wells score suggesting that they did not have typical clinical features of DVT. Therefore, clinicians should consider prophylactic anti-coagulation or routine Doppler ultrasound scan monitoring in HIV patients with low CD4 counts and PIs who are immobile knowing that they may develop an asymptomatic DVT. Patients using oral contraception on PIs and with low CD4 count should be counselled on signs and symptoms of DVT that they should report to their doctor and should be monitored closely for DVT.


Although the use of highly active antiretroviral therapy in HIV positive individuals has proved to be effective in suppressing the virus to below detection limits of commonly used assays, virological failure associated with drug resistance is still a major challenge in some settings. The prevalence and effect of pre-treatment resistance associated variants on virological outcomes may also be underestimated because of reliance on conventional population sequencing data which excludes minority species. We investigated long term virological outcomes and the prevalence and pattern of pre-treatment minority drug resistance mutations in individuals initiating HAART at a local HIV clinic.Patient’s records of viral load results and CD4 cell counts from routine treatment monitoring were used and additional pre-treatment blood samples for Sanger sequencing were obtained. A selection of pre-treatment samples from individuals who experienced virological failure were evaluated for minority resistance associated mutations to 1 % prevalence and compared to individuals who achieved viral suppression.At least one viral load result after 6 months or more of treatment was available for 65 out of 78 individuals followed for up to 33 months. Twenty (30.8 %) of the 65 individuals had detectable viremia and eight (12.3 %) of them had virological failure  after at least 6 months of HAART. Viral suppression, achieved by month 8 to month 13, was followed by low level viremia in 10.8 % of patients and virological failure in one patient after month 20. There was potentially reduced activity to Emtricitabine or Tenofovir in three out of the eight cases in which minority drug resistance associated variants were investigated but detectable viremia occurred in one of these cases while the activity of Efavirenz was generally reduced in all the eight cases.Early viral suppression was followed by low level viremia for some patients which may be an indication of failure to sustain viral suppression over time. The low level viremia may also be representing early stages of resistance development. The mutation patterns detected in the minority variants showed potential reduced drug sensitivity which highlights their potential to dominate after treatment initiation.Not applicable.The online version of this article (doi:10.1186/s12985-016-0628-x) contains supplementary material, which is available to authorized users. Highly active antiretroviral therapy (HAART) has resulted in improved quality of life among people infected with human immunodeficiency virus (HIV) including reduced mortality and morbidity rates. However, virological failure caused by emergence of drug resistant variants still occurs in some individuals on HAART . Some inThe effect of pre-treatment resistance associated minority variants on treatment outcomes is a subject of many studies –14. WhilViral load (VL) testing in individuals on HAART is the method used to detect HIV replication and virological failure. The measure of a successful HAART program would be a sustained viral suppression over time in individuals on the program. The South Africa HIV management guidelines recommend VL testing 6 months after HAART initiation followed by VL testing at 12 months and every 12 months thereafter . BaselinParticipants were recruited from Tshwane District Hospital HIV clinic in Pretoria central, South Africa between July 2013 and May 2014 after written informed consent and followed up for at least 12 months and up to 33 months. Eligible participants were HIV infected treatment naïve adults with CD4 cell counts < 350 cells/μl and/or World Health Organization (WHO) clinical stage 3 or stage 4. Participants were initiated on a NNRTI based regimen consisting of Efavirenz (EFV), Emtricitabine (FTC) and Tenofovir (TDF).Samples were obtained before treatment initiation. Plasma was isolated from 10 to 15 ml of whole blood collected in EDTA tubes by centrifugation at 1600 g for 10 min and stored at −70 °C until required for RNA extraction. RNA was extracted from 210 μl of plasma using the QIAamp Viral RNA Mini kits (Qiagen) and eluted with 60 μl elution buffer.Follow up HIV-1 VLs for treatment monitoring were done after at least 6 months of treatment using Abbott Real Time HIV-1 test  with a detection limit of 40 RNA copies/ml. Suppression was defined as a VL < 50 RNA copies/ml. Virological failure was defined as a VL ≥ 1000 RNA copies/ml after at least 6 months of HAART.PR) gene and the first 300 codons of the reverse transcriptase (RT) gene (HXB2 nucleotide 2166–3440). BigDye Terminator V3.1 Cycle Sequencing Ready Reaction Kit  was used for sequencing reactions with two forward and two reverse primers and sequencing was done on the 3100 Automatic capillary sequencer . Sequences were edited and assembled on Sequencher V 4.5 . The Stanford HIVdb algorithm Version 7.0. (http://hivdb.stanford.edu/) was used for subtyping, resistance mutations interpretation and quality assessment.A previously described method and primers was used for nucleic acid amplification and sequencing . SuperscFor ultra-deep sequencing (UDS) amplicons obtained from pre-treatment samples from four individuals who experienced virological failure were sent to Inqaba Biotechnical industries in Pretoria South Africa for sequencing up to 1 % prevalence. Additional samples from three individuals who virally suppressed and one sample from an individual who experienced low level viremia were also deep sequenced to provide comparison.Briefly, cDNA samples were fragmented using an ultrasonication approach and the resulting fragments were purified and size selected, end repaired and an illumina specific adapter sequence ligated. Following quantification, the samples were individually indexed and a second size selection step was performed using AMPure XP Beads. Libraries were quality controlled on a DNA chip  and then sequenced on illumina’s MiSeq platform, using a MiSeq v3 kit according to the manufacturer’s protocol. Fifty (50) Mb of data (2 × 300bp long paired end reads) were produced for each sample. This was followed by HIV sequence analysis and quality check, genotyping and drug resistance interpretations using Deepchek 1.4 HIV analysis software. A minimum of 461 sequences was required for 99 % confidence at 1 % threshold and a Q30 score measure was applied for basecalling.Pre-treatment drug resistance was defined as identification of a mutation that is known to cause a reduced susceptibility to at least one prescribed drug.Adherence was monitored using a combination of measures including checking for missed clinic visits, participant interviews and investigating reasons for which participants had been sent for counselling sessions.t-test Two sample assuming equal variances.Differences between mean CD4 cell counts were calculated in excel using the A total of 78 participants were recruited into the study. At least one follow up viral load result was available for 65 participants. Follow up viral loads were not available for 13 participants (16.6 %) due to loss to follow up. Participant characteristics are shown in Table After treatment initiation, participants came for the first viral load monitoring at different time points Fig. .Fig. 1TiThere were 20 participants (30.8 %) with detectable viremia at some point after at least 6 months of HAART , L022, L038, L039, L049, L058, L061, L063 and L067, who had initially suppressed the virus to below detection limits by month 8 to month 13 followed by detectable viremia at month 20 or after in all cases. The detected VLs after initial suppression were < 1 000 RNA copies/ml except for L039 with a VL of 21 646 RNA copies/ml. Subsequent viral load results after the initial rebound were available for two of these individuals, L038 and L039, and were done 10 and 3 months later respectively. The detectable viremia was shown to persist in both cases.There were no differences in mean baseline CD4 cell counts between the group that managed to achieve viral suppression and the groups with detectable viremia Table . The samDetection of baseline minority resistance associated mutations using ultra deep sequencing to 1 % threshold was done for eight participants. The coverage and basis for excluding some mutations from analysis is shown in Fig. NRTI drugs TDF or FTC had potentially reduced activity in three out of the eight cases in which minority drug resistance associated variants were detected but detectable viremia occurred in one of these cases. The activity of EFV was reduced in all the eight cases ranging from low level resistance (two cases) to high level resistance (1 case). Taken together, the pattern of minority variants detected showed potentially reduced EFV treatment efficacy and were generally susceptible to the NRTI drugs TDF and FTC at 1 % prevalence.The goal of HIV antiretroviral therapy is to achieve sustained viral suppression in individuals on treatment. Virological failure due to development of drug resistance is still a challenge for many HIV treatment programmes in developing countries due to lack of resources for effective treatment monitoring and treatment optimization among other challenges. Furthermore, the effect of pre-treatment resistance associated minority variants on virological outcomes is still not well understood and largely underestimated because of reliance on conventional population sequencing data which do not include minority species. In this long term follow up study, baseline samples showed a high prevalence of pre-treatment resistance associated minority variants although their clinical relevance requires further study. There was high prevalence (30.8 %) of detectable viremia of any kind after at least 6 months of HAART and in 40 % of these cases detectable viremia occurred after previous viral suppression to below detection limits.Virological failure occurred in 12.3 % of the participants compared to an overall 15 % virological failure rate (range 0–43 %) calculated from 19 studies done in sub-Saharan Africa countries . HoweverWe noted that viral suppression had been achieved by month 8 to month 13 and viral rebound occurred after month 20 in a subset of individuals indicating failure to sustain viral suppression over time. Although the rebound resulted in low level viremia ranging from 83 RNA copies/ml to 579 RNA copies/ml in seven of the cases, detection of low level viremia after previous viral suppression should be monitored as these detections may be early stages of resistance development.The association of pre-treatment minority drug resistance associated HIV variants of < 1 % frequency or greater with increased risk of virological failure for individuals on NNRTI based regimens has been highlighted . The mutPre-treatment HIV drug resistance has been shown to increase regimen switches in developing countries  which reWe noted that 43 % of individuals who experienced low level viral rebound after initially suppressing the virus generally had poor immunological outcomes with a CD4 cell count < 350 cells/μl after more than 6 months of HAART. The same poor immunological outcome pattern was observed in individuals who experienced virological failure where 75 % of them had a CD4 cell count < 350 cells/μl. However CD4 cell count monitoring in isolation has been shown to be a poor marker for treatment failure , 26 and The study has a number of limitations in particular the absence of resistance data at the time of virological failure. Additional samples taken at the time of routine viral load testing were not always available since the researchers were not part of the routine patient care personnel at the clinic where participants accessed care. The small number of samples that were deep sequenced also limited the information and conclusions that could be derived from this data. The data obtained however provide a basis for further investigation using larger sample sizes and comparison of baseline minority mutations with sequences dominating at time of failure. We also relied on self-reported information on treatment adherence to monitor participant’s treatment adherence levels. Poor adherence to treatment may have been the cause of virological failure in some individuals given that there was a high loss to follow up of 20 % in our cohort. Many studies have shown that poor treatment adherence is associated with virological failure in resource limited settings –30 and tWhile the development of low level viremia or virological failure after previously suppressing the virus that we noticed in a subgroup of our participants could be due to viral persistence emanating from established viral reservoirs, there is need to establish if such occurrences might be due to resistant minority variants beginning to take over and dominate following suppression of the treatment sensitive population. These data therefore highlight the need for a better understanding of the role played by pre-treatment HIV drug resistance associated minority variants under various clinical settings.