Little is known regarding HIV disease outcomes among individuals who become infected with HIV while receiving antiretroviral medications for prevention. We compared HIV disease parameters among women who seroconverted while receiving tenofovir-containing oral or vaginal pre-exposure prophylaxis (PrEP) to placebo.Participants with HIV seroconversion in a randomized placebo-controlled trial of oral tenofovir, oral tenofovir/emtricitabine, and vaginal tenofovir gel (MTN-003) were followed in a longitudinal cohort study (MTN-015). The effect of oral and vaginal tenofovir-containing PrEP on HIV disease progression was compared to placebo using linear mixed effects and Cox proportional hazard models, as appropriate. Additional analyses were performed to compare the outcomes among participants with detectable tenofovir or emtricitabine in plasma at the first quarterly visit in MTN-003.+ T cell counts  at 90 days after estimated HIV seroconversion and higher average rates of change over 12 months compared to placebo . With a median follow-up of 31 months, no significant differences were observed for time to CD4+ T cell count ≤350 cells/mm3, or the composite endpoint of CD4+ T cells ≤350 cells/mm3, initiation of antiretroviral therapy or death for each active arm compared to placebo. Additionally, there were no significant differences in the HIV RNA or CD4+ T cell counts at baseline, the change to month 12, or any disease progression outcomes among participants with oral drug detected and no oral drug detected compared to placebo.A total of 224 participants were included in the analysis; 93% from South Africa and 94% clade C virus. No differences in HIV RNA at steady state or the trajectory over 12 months were observed for each active arm compared to placebo; tenofovir gel recipients had higher CD4No clinically significant differences in HIV seroconversion outcomes were observed among women randomized to tenofovir-containing oral or vaginal PrEP regimens, however low overall adherence limits the generalizability of these findings. Oral pre-exposure prophylaxis (PrEP) with tenofovir-emtricitabine for prevention of HIV has been recommended for high-risk individuals based on results of randomized, placebo-controlled, efficacy trials conducted among several populations.–8 Oral tDespite the overall success of oral tenofovir-containing PrEP, breakthrough infection with HIV occurs among PrEP users, especially with sub-optimal adherence. Additionally sporadic cases of infection despite high adherence have been recently reported in clinical practice. The inciThe MTN-003 trial assessed the safety and effectiveness of daily oral tenofovir disoproxil fumarate (TDF), oral TDF/emtricitabine (TDF/FTC) and 1% tenofovir (TFV) vaginal gel for HIV prevention among HIV uninfected heterosexual women in Sub-Saharan Africa. All partThe study population for this analysis consisted of women who acquired HIV infection during participation in the MTN-003 (VOICE) trial and who enrolled into MTN-015. MTN-003 was conducted from September 2009 through August 2012 at 15 sites in South Africa, Uganda and Zimbabwe . were generated to assess time from the estimated HIV seroconversion to the following outcomes (at any point during follow-up): first CD4+ T cell count ≤ 200 cells/mm3, first CD4+ T cell count ≤ 350 cells/mm3, first AIDS-defining illness and initiation of ART. The same methods were used to assess a composite HIV disease progression endpoint, defined as the time to the first occurrence of CD4+ T cell count ≤ 350 cells/mm3, initiation of ART, or non-traumatic death. Participant follow-up was censored at the time of initiation of ART or PMTCT for all analyses, excluding those where ART initiation was the outcome. Because of low adherence to study product in MTN-003, we planned a priori to perform sensitivity analyses categorizing participants by whether or not study drug was detected in plasma at their first quarterly follow-up visit in MTN-003. Analyses were repeated comparing participants who had study drug detected compared to those who did not have study drug detected. In addition, as part of an exploratory analysis to better describe HIV disease progression by clade, we repeated the above analyses restricting the analysis population to those with clade C virus.The primary objective of MTN-015 was to assess HIV disease progression 12 months post-seroconversion among participants who received an active product compared to placebo participants in the parent MTN study. MTN-003 included both an oral tablet placebo arm and a vaginal gel placebo arm; the placebo arms were combined into one comparison group for this analysis. The estimated seroconversion date was defined as the midpoint between the last negative and first positive HIV rapid test in MTN-003. Change in CD4A total of 334 women were identified to have HIV seroconversion during participation in MTN-003 , includi+ T cell count were collected as part of the confirmation of seroconversion visit in MTN-003; therefore the first available results may be collected prior to enrollment in MTN-015. The median time from the first positive antibody test to the first HIV RNA was 30 days and for CD4 T-cell count was 30 days. The median initial CD4 T-cell count was 562 cells/mm3 and HIV RNA was 4.4 log10 copies/mL. The median follow-up time from estimated seroconversion date for the study participants was 31 months with a total of 548 person-years of observation. One death was reported during follow-up in a participant from the tenofovir gel arm. The cause of death was not identified but no AIDS-defining conditions were reported.The baseline characteristics of evaluable participants at enrollment into MTN-015 by MTN-003 study arm are displayed in Twenty-one (9%) of the 224 participants reported an AIDS-defining event during follow-up. The most frequently reported event (14 participants) was unexplained severe weight loss (>10% of body weight). Seventy-four (33%) participants reported a total of 86 HIV-related events during follow-up. Unexplained moderate weight loss of <10% of body weight  was the most frequently reported HIV-related event.+ T cell treatment guidelines for ART initiation. In addition, 56 (25%) initiated ART after enrollment into MTN-015 and 13 (6%) received antiretroviral medications for PMTCT, including 3 who subsequently initiated combination ART. All initial ART regimens contained non-nucleoside reverse transcriptase inhibitor (NNRTI), and the most frequently reported initial ART combination was efavirenz, tenofovir and either lamivudine or emtricitabine (46/59 [78%]).Three (1%) participants initiated ART before enrollment into MTN-015 and were included in disease progression analyses based on follow-up time from their estimated seroconversion dates. All three participants met local CD4+ T cell count result. The overall mean change from baseline to month 12 for HIV RNA was -0.2 log10 (N = 160) and for CD4+ T cell count was -80 cells/mm3 (N = 161).A total of 160 (71%) of participants were included in the month 12 HIV viral load analysis and 161 were included for CD4+ T cell count. Of the 64 participants excluded from this analysis, 17 (27%) had received antiretroviral mediations (ART or PMTCT) before the 12-month visit, 32 (50%) did not return for a visit within the 12-month visit window although they completed a later visit, 11 (17%) were lost-to-follow-up, and 4 (6%) participants had missing values for HIV RNA, one of whom had a CD4+ T cell count are also provided in + T cell at 90 days after the estimated HIV seroconversion date was not significantly different among participants assigned to the oral TDF arm compared to placebo. However, CD4+ T cell counts were higher for the TFV gel arm  and there was a trend toward a higher CD4+ T cell count in the TDF/FTC arm  at 90 days after the estimated HIV seroconversion date. CD4+ T cell counts decreased from baseline to month 12 for participants in all four groups and did not differ significantly among participants assigned to the oral TDF and TDF/FTC arms compared to placebo. However, the TFV gel arm trended toward a higher average rate of change over 12 months compared to placebo .The results of the model comparing the first HIV RNA result (intercept) and HIV RNA trajectories (slope) to the 12-month visit are shown in + T cell count ≤350 cells/mm3 are shown in + T cell count ≤350 cells/mm3 during follow-up. No statistically significant differences were observed for the time to first CD4+ T cell count ≤ 350 cells/mm3 among participants randomized to any active agent in MTN-003 compared to placebo. The time to initiation of ART, first AIDS-defining condition, and CD4+ T cell count ≤200 cells/mm3 also did not differ across the treatment arms (data not shown). For the composite HIV disease progression endpoint , there were 92 events observed with no significant differences among participants randomized to an active agent in MTN-003 compared to placebo  for TDF, 13/38 (33%) for TDF/FTC, and 4/40 (10%) for TFV gel . The TFV gel group was excluded from further analysis as the number of participants with detectable TFV was low, and the TDF and TDF/FTC groups were combined. Thus the analysis population included 172 participants: 23 with drug detected and 52 with no drug detected from the combined oral arms, and 97 placebo.+ T cell results. In the linear mixed effects models, there were no significant differences in the HIV RNA or CD4+ T cell counts at baseline or the change to month 12 among participants with oral drug detected and no oral drug detected compared to placebo. There were no statistically significant differences among participants with and without oral drug detected compared to the placebo group for any of the disease progression outcomes. Results were similar after stratifying by country (data not shown).A total of 119 (69%) of the 172 eligible participants had a viral load result available at the 12-month visit and prior to PMTCT or initiation of ART including 17/23 (74%) with drug detected, 34/52 (65%) with no drug detected, and 68/97 (70%) from the placebo arms; and 120/172 had CD4+ T cell count in the first year of infection. Post-estimated seroconversion CD4+ T cell counts for the tenofovir gel arm were higher relative to the placebo group, but similar mean CD4+ T cell counts were noted at 12 months. No differences were observed between MTN-003 study arms for HIV disease outcomes as measured by time to CD4 ≤ 350 cells/mm3, ART initiation, or death. This study comprises the largest cohort of seroconverters from a PrEP trial and includes participants who received oral and topical tenofovir-containing PrEP.In this analysis of a large cohort of women who acquired HIV infection while receiving oral or vaginal tenofovir-based PrEP, we observed no clinically significant impact of study treatment on subsequent HIV disease parameters, including viral set point and change in HIV RNA or CD4+ T cell count and HIV RNA until completion of the trial.[+ T cell count or HIV RNA at the time of seroconversion or subsequently for up to 60 weeks following seroconversion. However, the number of seroconverters who were followed and median duration of follow-up was not reported. Similarly, in the Bangkok Tenofovir Study that enrolled Thai men and women who inject drugs, HIV seroconverters were seen every four months.[Several randomized clinical trials have demonstrated clear efficacy for the use of tenofovir for PrEP in men who have sex with men (MSM), heterosexual men and women, and intravenous drug users.–5 In thehe trial. No differ months. In the B+ T cell counts were observed between the TDF/FTC and placebo recipients over a period of 120 weeks from seroconversion. Garrett, et al. reported the findings from extensive follow-up of 83 tenofovir gel and placebo participants who seroconverted while participating in the CAPRISA 004 trial.[+ T cell counts at quarterly intervals up to 24 months, there was a higher median HIV RNA among the tenofovir gel recipients (N = 32) compared to placebo. This difference was statistically significant only at the month 12 visit  but the interpretation is complicated by an unusually high proportion of participants with viral load below the limit of detection in the placebo arm. There was no difference in time to CD4+ T cell count <350 cells/mm3 between the tenofovir gel arm and placebo.Three studies have reported more detailed outcomes of seroconverters in separate reports., 22, 23 Finally, Grant et al. have reported follow up data on seroconverters from the FemPrEP trial of daily TDF/FTC comparing 33 seroconverters in the active arm to 35 who received placebo. TenofoviThere are several potential reasons why we and others have observed little impact of tenofovir-containing PrEP on HIV disease progression. The most compelling reason is that in efficacy studies to date, only a minority of participants with seroconversion had detectable tenofovir at the time of seroconversion, and in many cases, adherence to the study product among those who seroconverted was poor throughout the trial period. Thus theThe findings of our study were limited by the low overall study product adherence in MTN-003. When ourIn summary, we observed similar HIV disease outcomes in women who were receiving tenofovir-based oral or vaginal pre-exposure prophylaxis compared to placebo in the MTN-003 trial–similar to other studies these data are limited by the overall low adherence to the study products. Although reassuring, longitudinal follow-up of seroconverters from ongoing and future trials of antiretroviral drugs used for prevention are necessary to inform policy and best practices for PrEP.S1 Table(DOCX)Click here for additional data file.


CD4 cell count in HIV‐1 seroconverters initiating combination antiretroviral therapy (cART), and to quantify the influence of very early treatment initiation. We make use of all pre‐treatment CD4 counts, because analyses using only a single observation at initiation may be subject to biases.To investigate factors that predict speed of recovery and long‐term CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) multinational cohort collaboration of HIV‐1 seroconverters. We analysed pre‐ and post‐treatment data of patients with seroconversion dates estimated January 2003–March 2014  using a statistical model in which the characteristics of recovery in CD4 counts are determined by multiple predictive factors. Secondary analyses were performed incorporating uncertainty in the exact timing of seroconversion to allow more precise estimation of the benefit of very early treatment initiation.We used data from the CD4 count at cART initiation was the strongest predictor of CD4 count beyond 3 years on cART. Allowing for lack of complete certainty in the date of seroconversion, CD4 recovery was more rapid for patients in whom treatment was initiated within 4 months. For a given CD4 count, higher viral load (VL) at initiation was strongly associated with higher post‐treatment CD4 recovery. For other patient and drug characteristics, associations with recovery were statistically significant but small in magnitude.‘True’ CD4 count at cART initiation is the most important factor in predicting post‐treatment recovery, but VL provides substantial additional information. If cART is initiated in the first 4 months following seroconversion, recovery of CD4 counts appears to be more rapid. Observational studies have consistently found that, for HIV‐1 positive patients initiating combination antiretroviral therapy (cART), higher CD4 cell counts at baseline are associated with higher CD4 count levels after several years of treatment et al. μL, those who initiated cART within 4 months of their estimated date of infection experienced substantially higher CD4 cell levels over the first 4 years on treatment. Ding et al. There is some evidence that initiation of cART close to the date of HIV‐1 infection is associated with a higher level of CD4 recovery than that expected by the baseline CD4 cell count alone. Le Higher viral load (VL) prior to treatment also has been found to be associated with better recovery in CD4 counts from baseline In this study we present results from a novel analysis of the pre‐ and post‐treatment CD4 data of a large dataset of HIV‐1 seroconverters, with the aim of assessing the associations with CD4 response of all available relevant patient and drug regimen characteristics within a single statistical model. We also present an analysis in which uncertainty in the exact date of seroconversion for each patient is taken into account, with the aim of evaluating the potential additional benefit conveyed by very early treatment initiation and the timescale within which this can be obtained. Our modelling approach makes use of all pre‐treatment CD4 count data, accounts for measurement error in these observations, and does not rely on the stratification of continuous predictors of post‐treatment recovery (i.e. grouping into arbitrary subsets). This, in combination with the use of a large dataset of patients with well estimated date of seroconversion, has enabled a more comprehensive analysis of post‐treatment recovery in CD4 counts than has been reported previously in the literature.www.EuroCoord.net) cohort collaboration dataset We fitted combined models We restricted our analysis to patients with an estimated date of HIV‐1 seroconversion during or after 2003, with this cut‐off chosen to balance the needs for an adequate number of patients and length of follow‐up with the aim for the analysis to reflect relatively modern treatment regimes. Patients who started a regimen of antiretroviral drugs that did not correspond to the definition of cART given below were excluded, as were patients without post‐treatment CD4 count measurements. Those patients without pre‐treatment CD4 counts were not excluded, because the ‘true’ baseline value can still be modelled without this information. cART is defined as a regimen of at least three drugs, with at least two different drug classes ), and regimens meeting this general definition were further subdivided for analysis. The nonnucleoside reverse transcriptase inhibitor (NNRTI) regimen included regimens with at least one NNRTI and at least two NRTI. The ritonavir‐boosted protease inhibitor (r/PI) regimen included at least one r/PI with at least two NRTI. The integrase strand transfer inhibitor (INSTI) regimen included at least one INSTI with any combination of NRTI, NNRTI and PI. Drug regimens that met the general definition for cART, but not those for the specific NNRTI, r/PI or INSTI regimens, were grouped into an ‘other’ category.n = 910) and those for whom the mode of infection was unknown (n = 366). The resulting cohort for analysis included a total of 7600 patients, with 39 225 pre‐treatment and 61 487 post‐treatment CD4 counts.These criteria resulted in a total of 8838 patients from 22 contributing cohorts. We were interested in evaluating the associations between response to cART and multiple patient characteristics and so we also initially excluded patients for whom no VL measurement was recorded within 6 months before the start of cART (n = 410) or negative (n = 5881) HCV test . Other patient characteristics included in the analysis were sex, age at treatment initiation and diagnosis of an AIDS‐defining condition prior to treatment.There was no hepatitis C virus (HCV) test recorded prior to cART in a substantial proportion of patients in the analysis cohort (1309 of 7600) and, as such, we included these patients as a separate grouping in the analysis along with those with a positive  as follows: 0 ≤ ttrt ≤ 0.5, 0.5 < ttrt ≤ 1.0 or 1.0 < ttrt.For the initial analysis, we treated the estimated date of seroconversion as fixed, taking the recorded date of seroconversion illness or laboratory evidence of seroconversion , if observed, or the mid‐point between last negative and first positive HIV‐1 tests if not. For these analyses, we stratified modelling of response to treatment according to estimated timing of treatment initiation from seroconversion . The shape of the fitted curve indicated that, on average, there is a rapid improvement in CD4 count in the 2–3 months following cART initiation with a subsequent gradual increase that continues in most cases for more than 5 years , adjusted for CD4 count at treatment initiation, but similar levels beyond around 5 years on cART were predicted by the model  = 5.7 vs. 620 cells/μL for log10(VL) = 4.7); this provides evidence that, for a given baseline CD4 level, baseline VL is positively linked to CD4 recovery following cART initiation independent of the time since infection. Once the baseline CD4 and VL at treatment initiation and the time from seroconversion to treatment had been included in the model, estimated effect sizes for additional patient and drug characteristics were small. However, all were statistically significant, with P < 0.005, a consequence of the large sample size, and so we present results that relate to the full model containing all factors. CD4 recovery is predicted to be slightly worse for male patients infected through sex between men and women , and recovery is predicted to be better on average in younger patients . An AIDS diagnosis prior to treatment initiation was associated with slightly better recovery  and a positive HCV test prior to treatment initiation was associated with slightly worse recovery . Of the cART regimens at treatment initiation, patients initiating cART with an INSTI showed improved CD4 recovery .Conditional on baseline CD4 level and the time elapsed from seroconversion to treatment, higher VL at treatment initiation was associated with substantially better post‐treatment recovery in CD4 counts , but with minimal changes in the parameter estimates associated with other variables.The residual unexplained variation between patients in their post‐treatment recovery in CD4 counts was substantial Fig. . None ofr^ = −0.28) and slope (r^ = −0.50) of pre‐treatment CD4 counts (i.e. higher pre‐treatment VL was associated with lower CD4 count at seroconversion and with a steeper decline), which is important given that the positive association with CD4 recovery is conditional on the baseline CD4 count at treatment initiation.When uncertainty in precise date of seroconversion was taken into account, we found that there was a more rapid CD4 recovery when treatment was initiated within 4 months of seroconversion . It would have been interesting to have also tested for an independent effect of rate of pre‐treatment CD4 decline in the present analysis, but this was not attempted following the failure to fit such models in our pilot investigation A previous study by Mussini The other patient and drug regimen characteristics that were included in our analysis only showed small to moderate associations with post‐treatment recovery in CD4 counts. Because this is an analysis of an observational dataset, observed differences that are small in magnitude need to be interpreted with caution. Increasing patient age at date of treatment initiation was found to be associated with a moderate reduction in CD4 recovery conditional on the baseline value, which is consistent with previous research The finding that a pre‐treatment AIDS diagnosis was associated with an improvement in the post‐treatment recovery could be considered surprising, but it should be noted that the effect size was small, that this is conditional on baseline CD4 count and that we did not distinguish between the severity of the various conditions included. It is possible that the difference observed could be explained by greater sequestration of CD4 cells in the lymphoid tissue in such cases, leading to a greater increase on initiation of cART, as has been suggested for cases with higher pre‐treatment VL Comparison of recovery by sex and infection group in the present analysis is hampered by the fact that the sample size for some subgroups is small. Recovery was observed to be slightly worse on average amongst heterosexual men, which has not been reported previously. However, it is possible that this difference could be due to correlated factors such as ethnicity and associated differences in socioeconomic circumstances, for which data were only available in a minority of patients in this cohort. Some previous studies have observed better post‐treatment CD4 recovery in women μL) at 48 weeks after initiation of ART regimens containing an INSTI Of the classifications of drug regimens included in the analysis, use of an INSTI regimen at treatment initiation was found to be associated with a moderate improvement in post‐treatment recovery in CD4 relative to the NNRTI regimen. These findings warrant further investigation, but are not conclusive on their own given the potential for residual confounding and the moderate effect sizes found. There is evidence that the use of INSTI regimens is associated with more rapid viral suppression, but the evidence regarding potential differences in CD4 recovery is less clear No substantial differences were observed when the analysis was repeated for a processed dataset with censoring of post‐treatment CD4 counts following the observation of a detectable VL beyond 6 months from initiation of cART. This is surprising given that the observation of a detectable VL on cART could be taken to indicate poor adherence. The fact that no difference was observed when censoring was applied could be explained by sufficiently high levels of drug adherence within the studied cohort or by effective recording of treatment interruptions. The level of unexplained residual variation in CD4 recovery on cART remained high in these analyses, indicating that the clinical factors included in our models do not allow accurate prediction of those patients who will go on to show suboptimal CD4 recovery on treatment despite successful viral suppression.In this study we provide a comprehensive analysis of factors that predict recovery in CD4 cell counts following initiation of cART in HIV‐1 patients. Our findings are largely consistent with those reported previously in the literature, but we provide further information regarding the timescale for the potential additional benefit conveyed by early treatment initiation, after adjusting for baseline CD4 count, and also demonstrate the relative importance of different factors. The findings also provide further supporting evidence for the initiation of cART soon after HIV diagnosis, as now recommended in World Health Organization guidelines Appendix S1 Document including in‐depth description of the statistical methodology, further details of the fitted models and some further discussion of the results.Click here for additional data file.


Cross-resistance after first-line antiretroviral therapy (ART) failure is expected to impair activity of nucleoside reverse-transcriptase inhibitors (NRTIs) in second-line therapy for patients with HIV, but evidence for the effect of cross-resistance on virological outcomes is limited. We aimed to assess the association between the activity, predicted by resistance testing, of the NRTIs used in second-line therapy and treatment outcomes for patients infected with HIV.Controlled-Trials.com (number ISRCTN 37737787) and ClinicalTrials.gov (number NCT00988039).We did an observational analysis of additional data from a published open-label, randomised trial of second-line ART (EARNEST) in sub-Saharan Africa. 1277 adults or adolescents infected with HIV in whom first-line ART had failed  were randomly assigned to a boosted protease inhibitor (standardised to ritonavir-boosted lopinavir) with two to three NRTIs ; or with raltegravir; or alone as protease inhibitor monotherapy (discontinued after week 96). We tested genotypic resistance on stored baseline samples in patients in the protease inhibitor and NRTI group and calculated the predicted activity of prescribed second-line NRTIs. We measured viral load in stored samples for all patients obtained every 12–16 weeks. This trial is registered with Baseline genotypes were available in 391 (92%) of 426 patients in the protease inhibitor and NRTI group. 176 (89%) of 198 patients prescribed a protease inhibitor with no predicted-active NRTIs had viral suppression  at week 144, compared with 312 (81%) of 383 patients in the protease inhibitor and raltegravir group at week 144 (p=0·02) and 233 (61%) of 280 patients in the protease inhibitor monotherapy group at week 96 (p<0·0001). Compared with results with no active NRTIs, 95 (85%) of 112 patients with one predicted-active NRTI had viral suppression (p=0·3) and 20 (77%) of 26 patients with two or three active NRTIs had viral suppression (p=0·08). Over all follow-up, greater predicted NRTI activity was associated with worse viral load suppression .Genotypic resistance testing might not accurately predict NRTI activity in protease inhibitor-based second-line ART. Our results do not support the introduction of routine resistance testing in ART programmes in low-income settings for the purpose of selecting second-line NRTIs.European and Developing Countries Clinical Trials Partnership, UK Medical Research Council, Institito de Salud Carlos III, Irish Aid, Swedish International Development Cooperation Agency, Instituto Superiore di Sanita, WHO, Merck. More than 17 million people receive antiretroviral therapy (ART) for HIV infection, mainly delivered with the WHO-recommended public health approach, characterised by use of standardised sequential regimens.Evidence before this studyWe searched PubMed with no start date or language restrictions for articles published until Aug 1, 2016, with the terms “second-line therapy”, “protease inhibitors”, “resistance testing”, and the individual drug names, and we also reviewed relevant HIV conference abstracts. This search identified studies that examined the association between nucleoside reverse-transcriptase inhibitor (NRTI) resistance and virological outcomes for NRTI plus protease inhibitor second-line therapy after failure on a first-line non-NRTI (NNRTI)-containing regimen. We found two cohort studies done in sub-Saharan Africa  and one in Asia  and analyses of the NRTI plus protease inhibitor arm in two randomised controlled trials . These studies either reported no association or an inverse association between predicted activity of prescribed NRTIs and viral load suppression.Added value of this studyIn the EARNEST trial, we prospectively followed up a large group of HIV-infected patients taking a protease inhibitor and NRTI second-line regimen and collected adherence data and relevant outcome data, including viral load, with greater frequency and with lower incidence of loss-to-follow-up than in preceding cohort studies. This trial was also larger (426 patients on protease inhibitor and NRTI) than the other two randomised controlled trials of second-line therapy and had longer follow-up (144 weeks). Our analysis shows that a regimen containing NRTIs with no or limited predicted activity achieved viral load suppression in a high proportion of patients, which was sustained throughout longer-term follow-up. The size and duration of our study also allows for a more robust model for analysing predictors of outcome than previous studies: we found a paradoxical inverse association between extent of baseline resistance and viral suppression  but were also able to show more clearly that this inverse association persisted after adjustment for other relevant factors including baseline viral load and CD4 cell count and adherence during follow-up . The main added value of this analysis is the availability of two comparison groups within the same trial, allowing us to show the contribution of the NRTIs to regimen activity. In the group with no predicted active NRTIs in the prescribed regimen, viral load suppression was at least as good as that of a regimen containing a predicted fully active drug from a new drug class  and clearly superior to that obtained with the protease inhibitor used alone. Thus the good outcomes obtained with a protease inhibitor and NRTI second-line regimen in programme settings are not solely attributable to the high potency of protease inhibitors (proposed as the explanation in some earlier studies) but also reflect a substantial additional contribution from NRTIs predicted to have limited or no activity as a result of cross-resistance.Implications of all the available evidenceDespite extensive cross-resistance, NRTIs make a major contribution to viral load suppression in second-line therapy when combined with a protease inhibitor. Predictions based on genotypic resistance testing appear to overestimate the detrimental effect of resistance mutations on the activity of NRTIs and should be re-examined for use in the context of second-line switch to a protease inhibitor-based regimen and possibly for other specific regimen changes. Taken together, the data support WHO treatment guidelines that do not recommend resistance testing at switch to second-line therapy. Adherence seems to be an important determinant of outcomes in second-line therapy and NRTI selection might best be based on minimising toxicity and maximising tolerability, in view of the effect that these might have on adherence.We did an observational analysis within an open-label, randomised trial of second-line ART (EARNEST) in sub-Saharan Africa. The EARNEST trial,Eligible patients were randomly assigned using computer-generated randomisation list with variable block size to receive a protease inhibitor (standardised to ritonavir-boosted lopinavir) together with two or three NRTIs (protease inhibitor and NRTI group), or with raltegravir , or alone as monotherapy . In the protease inhibitor and NRTI group, NRTIs were selected by clinicians (without resistance testing) on the basis of NRTIs used first-line, side-effects, local standard-of-care, drug availability, and WHO guidelines .Patients were followed for 144 weeks with clinic visits every 1–2 months. Adherence was assessed by structured questions and intensive adherence counselling was given when lapses were identified. Treatment was monitored clinically and with CD4 cell counts every 12–16 weeks.We measured viral load on stored samples in a central laboratory  with the Abbott RealTime HIV-1 assay  at weeks 4, 12, 24, 36, 48, 60, 80, 96, 110, 126 and 144. In the protease inhibitor monotherapy group, viral load was tested at all timepoints to week 48, and at week 96, after which the group was discontinued. Viral load results were reviewed by a data monitoring committee, but not returned to managing physicians.Stanford algorithm (version 7) to predict drug susceptibility.We genotyped reverse transcriptase on all available baseline samples in the protease inhibitor and NRTI group using a WHO-accredited in-house assayWe calculated the number of predicted-active NRTIs in the prescribed second-line regimen by counting the NRTI drugs initially prescribed that had no more than low-level resistance  predicted from baseline genotyping. We also calculated the genotypic susceptibility scoreAnalyses were by intention-to-treat  and based on observed viral loads . We used generalised estimating equations  to test differences between treatment groups in the proportion of patients with virological suppression across the whole follow-up period. Risk differences were used to compare groups at the latest timepoint in the study . We used logistic multivariable regression with fractional polynomials and backwards elimination  to identify independent predictors of a viral load of less than 400 copies per mL at week 144 in complete cases in the protease inhibitor and NRTI group. Variables included in the analysis were age (continuous), sex, viral subtype, proportion of visits missed or when non-adherence was self-reported (continuous), years on first-line ART (continuous), history of ever smoking, ever drinking alcohol, years of education, job status , hours worked if employed (continuous), household income , availability of food for regular meals, clinical history , and, at switch to second-line, viral load, CD4 cell count, haemoglobin, blood glucose, and estimated glomerular filtration rate . We tested the additional effect of individual mutations, pairs of mutations with more than 10% prevalence, and the presence of mutations in the well recognised thymidine analogue mutations type 1  and type 2  pathways one at a time in the selected model. We also did two sensitivity analyses, first without backwards elimination including all factors with p<0·2 on univariable analysis , and secThe funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.Between April 12, 2010, and April 29, 2011, 1277 patients were randomly assigned . Baseline characteristics were similar between the groups .Baseline genotypes were available for 391 (92%) of 426 participants in the protease inhibitor and NRTI group. 95% had at least one NRTI mutation . 230 patAt week 144, 176 (89%) of 198 prescribed a second-line protease inhibitor and NRTI regimen containing no predicted-active NRTIs had viral suppression  compared with 312 (81%) of 383 in the protease inhibitor and raltegravir group . At week 96, 181 (88%) of 205 prescribed a regimen with no predicted-active NRTIs had viral suppression compared with 233 (61%) of 380 in the protease inhibitor monotherapy group . This suggests that in the context of a switch from a first-line NNRTI-based to a second-line protease-inhibitor-based regimen, predictions based on genotypic resistance testing might overestimate the detrimental effect of cross-resistance on the activity of NRTIs. Prediction of clinical outcomes from genotypic resistance tests is challenging,In addition to our finding of substantial efficacy of NRTIs that had limited or no predicted activity, the paradoxical association we found between greater predicted NRTI activity and worse viral load suppression also contrasts with standard assumptions underlying resistance. Our findings are consistent with other second-line studies that have also found an absent or paradoxical association between NRTI resistance and outcomes,The observed NRTI effect might, in part, arise from resistance mutations such as Met184Val and Lys65Arg affecting viral replicative capacity, with effects increasing with more mutations.The strengths of our study include large numbers of patients, long follow-up, high retention, regular viral load testing at predetermined timepoints, centralised viral load and resistance testing, and the availability of two relevant treatment comparison groups  that enable the contribution of NRTIs to the regimen to be delineated. Although patients were participating in a clinical trial, the trial eligibility criteria were kept broad and we followed the widely used approach of clinical and CD4 cell count monitoring . The results are therefore probably generalisable to patients failing first-line therapy in programmes that follow the public health approach to ART delivery.The main limitation of our study is that most patients were taking zidovudine-based first-line regimens; whereas, contemporary WHO guidelines recommend tenofovir-based first-line ART. The similar results seen in the analysis of the subgroup failing on first-line tenofovir, however, support the generalisability of our findings. The protease inhibitor was standardised in this trial to ritonavir-boosted lopinavir, which is recommended as a preferred protease inhibitor in WHO guidelinesOur findings are relevant to discussions about the merit of introducing routine resistance testing into the public health approach to ART for patients switching to the standard protease inhibitor-based second-line regimen. Although genotypic resistance testing is recommended in treatment guidelines for individualised therapy and widely used by clinicians in high-income countries for ART drug selection at treatment failure,


The respiratory syncytial virus (RSV) is recognized as an important cause of respiratory tract infections. Immunocompromised patients, healthcare workers (HCWs) and children contacts are at increased risk of acquiring the infection. However, the impact of asymptomatic infection in transmission has not been well studied. Objectives: this study evaluated the frequency and viral load (VL) of RSV in nasal swab samples of individuals with different risk factors for acquiring infection in a university hospital in Sao Paulo, Brazil.We included 196 symptomatic children and their 192 asymptomatic caregivers, 70 symptomatic and 95 asymptomatic HCWs, 43 samples from symptomatic HIV‐positive outpatients, and 100 samples of asymptomatic HIV patients in the period of 2009‐2013.P < .0001). The VL of symptomatic patients (4.7 log copies/mL) was significantly higher compared to asymptomatic patients (2.3 log copies/mL). RSV detection among asymptomatic caregivers  was significantly higher compared to other asymptomatic adults, HIV and HCWs . A close contact with an infected child at home was an important risk to RSV acquisition [OR 22.6 (95% CI 4.8‐106.7)]. Children who possibly transmitted the virus to their asymptomatic contacts had significantly higher viral load than children who probably did not transmit (P < .0001).RSV infection was detected in 10.1% (70/696) of samples, 4.4% (17/387) of asymptomatic patients, and 17.1% (53/309) from symptomatic patients. (According to our results, it is important to know if people circulating inside the hospital have close contact with acute respiratory infected children. The frequency of RSV detection in individuals with different risk factors for acquiring infection is described. Comparisons of viral load were also performed. The individuals included in this study were HCWs, HIV‐infected patients, children, and caregivers of children with respiratory symptoms.22.1This was a cross‐sectional study in which patients were enrolled through active recruitment. A total sample size of 696 nasal swab samples was established considering the 6 groups studied: symptomatic and asymptomatic healthcare workers; symptomatic and asymptomatic HIV‐positive individuals; symptomatic children; asymptomatic caregivers of symptomatic children.The sample size was calculated to be sufficient to determine a prevalence of RSV at least up to 10%, with 90% confidence interval and a relative precision of 0.25 of the a priori estimated proportion. The goal of sampling was that we could determine the prevalence of RSV in 4 different groups.These samples were collected in the period of 2009‐2013, in different care units of a university hospital complex in Sao Paulo, Brazil, during all over the year, including RSV season and off‐season months. The university hospital has 700 beds and is a referral hospital with both basic services and specific care from patients attended at primary care health service in ambulatory or specific units.2.2The inclusion criteria for asymptomatic adults was the absence of any respiratory symptoms during the 15 days before sample collection; for symptomatic adults and children (up to 12 years of age), the criteria was the diagnosis of acute respiratory infection (ARI) within a week before sample collection. Acute respiratory infections were defined as fever or feverish and cough or sore throat. For the analysis among symptomatic children and their asymptomatic caregivers, the child was considered as “possibly transmitting” if had a positive sample and their related caregiver also had a positive sample.2.3All the volunteers were invited to participate and, after appropriate clarifications, signed a free informed consent. The study was approved by the UNIFESP Research Ethics Committee (Process number 369.760). The volunteers or their companion filled a questionnaire about the clinical signs, and the collected samples were immediately processed and stored. The healthcare workers (physicians and nurses who had direct contact with patients) were actively recruited in different hospital wards/clinics  of the university hospital twice a week. The HIV‐positive patients were enrolled during the schedule routine visits once a week in the outpatient clinic of the Infectious Diseases Department. The symptomatic children and caregivers were enrolled, twice a week, in the pediatrics sector of the Employee Health Care Center (NASF) during medical care. One researcher interviewed a pair of asymptomatic caregivers and a symptomatic child, referred by a pediatrician, and samples were collected only from children which the asymptomatic caregiver agreed to participate.2.4Nasopharyngeal swabs were collected, immediately transported to the virology laboratory, and aliquots were frozen at −80°C for further analysis by PCR. Nucleic acid was extracted from 140 μL using the ”QIAmp Viral RNA Extraction Kit”  according to the manufacturer's instructions.2.5For the detection of RSV, we selected the protocol described by Homaira et al, 2012.2.6t test for independent samples, and ANOVA. The programs used were OpenEpi version 2.3.1 and GraphPad. A P value of <.05 was considered statistically significant.The analysis of RSV occurrence for the different studied populations and among symptomatics and asymptomatics was made using chi‐squared, odds ratio, Fisher's exact test, Student's 3We analyzed 387 samples from non‐hospitalized asymptomatic adults: 100 samples from HIV positive; 95 HCWs; 192 caregivers  of 196 symptomatic outpatient children. The symptomatic outpatients’ adults included were 43 HIV patients and 70 HCWs.Of the 696 samples analyzed, 85.4% (594/696) were collected from March to September, corresponding to the period of greatest circulation of RSV in Sao Paulo city.The characteristics of asymptomatic and symptomatic subjects are described in the Table P < .0001). Someone infected with RSV has 4.5 greater odds of presenting symptoms [OR 4.5 (95% CI 2.5‐7.9)], than being asymptomatic. The exclusion of children patients from this analysis showed a positive rate of 5.3% (6/113) for the symptomatic and 4.4% (17/387) for the asymptomatic subjects (P = .62). Nonetheless, RSV positivity of asymptomatic caregivers  obtained a significant difference compared to other asymptomatic adults subjects individuals, HIV, and HCWs . The RSV detection rate was 4.4% (17/387) for asymptomatic individuals and 17.1% (53/309) for symptomatic individuals. . Two RSV cases reported previous contact with a symptomatic person. We quantified RSV viral load for 2 samples and obtained 1.4 and 5.3 log copies/mL.In the group of symptomatic HIV individuals, the positivity of RSV was 7% (3/43) and the average age of these positive patients was 46 years. The mean CD4 of patients with positive samples was 442.6 cells/mm3. There was no statistically significant difference between the CD4 T‐cell count of RSV‐positive and the RSV‐negative ones. (P = .72). The average time from onset of symptoms until the date of sample collection was 11 days for patients with positive samples.In the group of asymptomatic patients, RSV was detected in 3% (3/100) of the samples. The average age of these patients was 33.7 years and the mean CD4 T‐cell count was 499 cells/mmOnly 1 of the individuals reported close contact with symptomatic children at home.The viral load found for each positive sample of symptomatic patients was 5.3, 6.5, and 3.2 log copies/mL, with an average value of 4.8 log copies/mL.3.2P = .31).The RSV‐positive rate for asymptomatic HCWs was 1% (1/95) and 4.3% (3/70) for the symptomatic subjects.  had their samples collected in 5.3 days (mean) and 2 of them reported a previous contact with symptomatic children at home. Viral loads obtained for 2 of these 3 samples were 8.4 and 1.1 log copies/mL.There was no statistically significant difference for the positivity rates among symptomatic and asymptomatic groups comparing the populations of HCWs and HIV patients.3.3P = .17). The average time from onset of symptoms until the date of sample collection was 3.4 days (range 1‐7 days).The average viral load for the samples was 4.6‐log copies/mL, ranging from 1.2 to 8.4‐log copies/mL. We found significantly higher viral load for children younger than 2 years of age compared with children older than 2 years of age (P = .0077). The average values for viral load found in the different age groups of children are listed in Table An RSV rate of 24% (47/196) was obtained for children included in the study. The mean age of children who had positive samples was 2.9 years (0.25‐12 years). The mean age of children with positive samples was not statistically different from the mean age of 3.8 years among children with RSV‐negative samples  of the samples among the group of asymptomatic caregivers. Mean age of RSV‐positive cases was 34.3 years (20‐64 years); 11  of them living at home with symptomatic children tested positive for RSV in this study. In this case, living with an RSV‐infected child at home was 22 times more likely to be infected with RSV [OR 22.6 (95% CI 4.8‐106.7)]. RSV viral load of the 13 samples varied from 0.1 to 5.4‐log copies/mL (mean 2.1 log copies/mL).3.5P < .0001). This difference between groups remained statistically higher even after excluding the children from the analysis of values obtained for symptomatic adults (4.9 log copies/mL and a median of 5.4 log copies/mL) and those asymptomatic (P = .0159).The average viral load of samples from the symptomatic group and the asymptomatic group was 4.7 log/mL (median of 4.9 log/mL) and 2.3 log/mL (median of 1.9 log/mL), respectively. The symptomatic individuals showed higher RSV viral load than asymptomatic individuals (P = .82).It was not found statistically significant difference between the symptomatic adult group and the symptomatic children group in the analysis of viral load values (P < .0001).The average RSV viral load for the 11 samples from asymptomatic caregivers infected was 2.5‐log copies/mL and for the 11 children was 6.4‐log copies/mL. The symptomatic children have higher viral load than their asymptomatic contacts (P < .0001).The RSV viral load among children with an asymptomatic contact infected with RSV obtained an average of 6.4 log copies/mL . Among children without an asymptomatic contact infected with RSV, the quantification was 4.1‐log copies/mL . These children possibly transmitting the virus to their asymptomatic contacts had significantly higher viral load than children who probably not transmit , and additional studies related to RSV infection among these patients would understand the dynamic of this type of viral infection.New drugs have been studied in challenge trials and therapeutically reduced both viral load and clinical manifestations of RSV infections.In the analysis of the viral load in asymptomatic caregivers’ contacts of symptomatic children, the viral load in children's samples was significantly higher than the viral load in their contacts and significantly higher than the viral load of children without an infected caregiver. This may indicate a need for high viral load values to occur the transmission.Although considering the limitations of our cross‐sectional study, mainly the absence of following the patients and the non‐differentiation of species A and B, it was demonstrated that the close contact with infected children is an important risk factor for acquiring RSV infection. This risk could be extended to healthcare workers, HIV‐positive patients, and visitors of hospitalized patients who have contact with children at home mainly during RSV seasons.Additional studies should be conducted for a better understanding of the clinical significance of asymptomatic RSV infection carriers on nosocomial transmissions during RSV seasons.According to our results, it is important to know if people circulating inside the hospital have close contact with acute respiratory infected children. Indeed, the need to maintain the team of professionals and the public informed about the infection prevention and control measures against the acquisition of infection by respiratory syncytial virus is critical.


Malawi’s national antiretroviral therapy program provides atazanavir/ritonavir–based second line regimens which cause concentration-dependent rise in indirect bilirubin. We sought to determine if elevated bilirubin, as a surrogate of atazanavir/ritonavir adherence, can aid in the evaluation of second line virological failure in Malawi.We conducted a cross-sectional study of HIV-infected patients ≥15 years who were on boosted protease inhibitor-based second line antiretroviral therapy for at least 6 months in two urban HIV clinics in Lilongwe, Malawi. Antiretroviral therapy history and adherence data were extracted from the electronic medical records and blood was drawn for viral load, complete blood count, total bilirubin, and CD4 cell count at a clinic visit. Factors associated with virological failure were assessed using multivariate logistic regression model.p < 0.001), although adherence by pill count was similar . The odds of virological failure were higher for adults aged 25–40 years (adjusted odds ratio (aOR) 2.5, p = 0.048), those with CD4 cell count <100 , and those with normal bilirubin levels ; but were lower for the overweight/obese patients . Poor pill count adherence  and male gender  were not associated with second line virological failure.Out of 376 patients on second line antiretroviral therapy evaluated, 372 (98.9%) were on atazanavir/ritonavir-based therapy and 142 (37.8%) were male. Mean age was 40.9 years (SD ± 10.1), mean duration on second line antiretroviral therapy was 41.9 months (SD ± 27.6) and 256 patients (68.1%) had elevated bilirubin >1.3 mg/dL. Overall, 35 (9.3%) patients had viral load >1000 copies/ml . Among the virologically failing vs. non-failing patients, bilirubin was elevated in 34.3% vs. 72.0% respectively (Among patients receiving atazanavir/ritonavir-based second line antiretroviral therapy, bilirubin levels better predicted virological failure than pill count adherence. Therefore, strategic use of bilirubin and viral load testing to target adherence counseling and support may be cost-effective in monitoring second line antiretroviral therapy adherence and virological failure. Drug resistance testing targeted for patients with virological failure despite elevated bilirubin levels would facilitate timely switch to third line antiretroviral regimens whenever available. Despite these improved outcomes in many patients on ART, some eventually fail first line and second line treatment resulting in increased morbidity and mortality for people living with HIV (PLHIV) [http://www.who.int/hiv/pub/arv/adult2010/en/; http://www.who.int/hiv/topics/treatment/First_Line_ART_failure_RLS_metanalysis.pdf [Antiretroviral therapy (ART) scale-up in developing countries reversed upward trends in HIV-associated mortality, morbidity, and disease transmission (ysis.pdf ), particysis.pdf , 5. Poorysis.pdf , 7. Whilysis.pdf , poor adysis.pdf –13. Therysis.pdf , 15.http://www.unaids.org/sites/default/files/country/documents/MWI_narrative_report_2015.pdf). Malawi adopted atazanavir/ritonavir (ATV/r) as the boosted protease inhibitor (PI/r) of choice in 2013; this being a switch from lopinavir/ritonavir (LPV/r) used earlier in its second line ART regimens [Approximately 1% of patients in Malawi’s national ART program were on second line regimens with the majority (91%) assessed as adherent based on indirect medication adherence measurements such as pill count and self-reported missed doses . Second line ART is AZT/3TC or TDF/3TC plus ATV/r. Lopinavir/ritonavir (LPV/r) is available as a substitute for ATV/r’s toxicity or when TB treatment is required ([http://www.who.int/hiv/pub/guidelines/arv2013/download/en/).This study was conducted at Lighthouse (LH) and Martin Preuss Centre (MPC) outpatient HIV clinics in Lilongwe, Malawi. The Lighthouse Trust, operating both LH clinic and MPC, is the largest provider of adult HIV care for PLHIV in Malawi. The integrated Tuberculosis(TB)/HIV care program and Option B+ program for HIV positive pregnant and breastfeeding women and their families is based at MPC, while all other services are provided at both sites. Viral load (VL) monitoring is done according to Malawi’s national ART guidelines at 6 months following initiation of a new ART regimen and at 2 years and every 2 years thereafter . First lequired  systems. They included HIV-infected patients aged ≥15 years attending the MPC and LH outpatient HIV clinics who were receiving PI/r-based second line ART for at least 6 months and with HIV-1 RNA (VL) results. At their regularly scheduled outpatient visits between December 2013 and May 2014, blood was collected for VL, complete blood count (CBC), CD4 cell count, renal function tests and liver panel. We then conducted a cross-sectional study of these participants to assess the factors associated with second line VF within these two facilities. At the time of evaluation, it was estimated that approximately 400 individuals had been initiated on second line therapy in Lighthouse clinics (approximately 2% of the Lighthouse ART population). This proportion is slightly higher than the national average  because Lighthouse, as a center of excellence, serves as a referral centre as well as one of the first and largest providers of ART services in the country.All HIV-infected individuals receiving care at LH and MPC were registered in the EMR systems, as described previously . CD4 cell counts were determined by flow cytometry using the Becton Dickinson FACSCount system . Complete blood count (CBC) was analyzed in the Beckman Coulter AcT 5diff Cap Pierce hematology analyzer , while liver and renal function tests were analyzed in the Roche Cobas C 311 chemistry analyzer. Laboratory results were graded according to the National Institute of Health Division of AIDS (DAIDS) Tables for grading the severity of adult and pediatric adverse events: Version 2.0 - November 2014 (http://rsc.tech-res.com/Document/safetyandpharmacovigilance/DAIDS_AE_GRADING_TABLE_v2_NOV2014.pdf).All the blood samples were processed at the University of North Carolina Research Project Laboratory in Lilongwe. VL was measured using the Abbott Real Ti. The primary predictor variable was the cumulative PI/r pill count adherence, whenever possible, which is the average PI/r pill count adherence for at least 6 months prior to the VL sample collection date. This is calculated as:The primary outcome was the proportion of patients on second line PI/r-based ART with virological failure (VF) defined as VL >1000 copies/ml per Malawi’s guidelines  based on➢Pill sum difference = (previous pill sum) – (current pill count)➢Previous pill sum = (pill count prior to supply visit) + (pills dispensed at supply visit)➢Pill use interval = (no. of days used pills since last supply) X (number of PI/r pills taken per day)(pill adherence) = (pill sum difference) / , where;We defined good adherence for desirable virological outcome (VL ≤ 1000 copies/ml) in this study as average pill count adherence of ≥95% and ≤105% . The oth2 test for categorical variables and the Student’s t-test for continuous variables. We used univariate logistic regression analysis to identify factors associated with VF, in addition to the known determinants of VF [Descriptive statistics were used to summarize the study population characteristics and the overall prevalence of second line VF. Continuous variables were summarized using mean and standard deviation (SD); categorical variables were summarized using frequency and percent (%). The distribution of viral load measurement in our study sample was non-normal due to the high proportion of individuals that were successfully suppressed. Other variables were normally distributed. Associations between socio-demographic or HIV-related variables and VF were assessed using the χts of VF , 26. SenOut of 376 HIV-infected patients on second line ART evaluated, 372 (98.9%) were on ATV/r-based therapy at the time of study and 142 (37.8%) were male (Table p = 0.0025), had lower CD4 cell count , and had significantly lower bilirubin levels . Bilirubin was elevated in 34.3% vs. 72.0% respectively (p < 0.001), although adherence by pill count were similar . The distributions of other population characteristics were similar among the virologically failing vs. non-failing patients. We observed medium correlation between VF and World Health Organization (WHO) defined immunological failure (CD4 cell count <100 cells/mm3) .Overall, out of 35 (9.3%) patients who had Malawi-defined VF (VL > 1000 copies/ml) while on second line ART Table , the majThe sensitivity and specificity of using bilirubin testing at the 1.3 mg/dL level to screen for VF was 65.7% and 72% respectively with a false negative rate of 34.3% and false positive rate of 28%. Bilirubin testing had a negative predictive value (NPV) of 95.3% and a positive predictive value (PPV) of 19.5%. The positive likelihood ratio (PLR) was 2.3 while the negative likelihood ratio (NLR) was 0.5. Using higher bilirubin cutpoints increased sensitivity but reduced specificity (Table p = 0.048), those with CD4 cell count <100 cells/mm3 , and those with normal bilirubin levels ; but were lower for the overweight/obese patients . Poor adherence by pill count  and male gender  were not associated with increased risk of VF. Similarly, time on second line ART  and time on ATV/r  were not associated with increased risk of VF and did not demonstrate collinearity. Additionally, using bilirubin as a continuous variable, the odds of VF were 0.31 less for every unit rise in total bilirubin .Univariate and multivariate logistic regressions identified factors associated with VF Table . The oddWe found a surprisingly low prevalence rate of VF (9.3%) among patients retained on second line ART at these two urban outpatient HIV clinics in Lilongwe, Malawi. Importantly, we identified several easily measureable factors predicting VF including bilirubin levels, CD4 cell count, BMI and age. Bilirubin testing, as a biologic marker for adherence to ATV/r-based therapy, may be an effective tool in evaluating patients for ART adherence and VF prior to the more expensive and less available genotype resistance testing and third line therapy.http://www.who.int/hiv/pub/guidelines/arv2013/download/en/) also may potentially explain the improved virological outcomes evidenced in this study.The prevalence rate of second line VF was lower in this study than reported elsewhere , althougObjective biologic measures of ART adherence are more reliable in predicting poor adherence and VF than pill count or patient’s self-report, which often over-estimate adherence levels , 31–35. Lower CD4 cell count was significantly associated with VF in this study. A previous study conducted within Malawi’s national ART program had indicated an association of lower CD4 cell count (<100cells/ml) with high levels of first line ART resistance, possibly contributing to second line ART failure . HoweverThe findings of this study should be considered in light of their strengths and limitations. Firstly, there is the likelihood of selection bias. Only participants receiving second line ART and who presented to the clinic during the period of the study were included for analysis. Those missing visits, and hence at higher risk for VF due to poor adherence to clinic appointments and missed doses, were not included for the analysis. Therefore, our results represent VF rates among persons on second line ART retained in care and may underestimate the true rate of treatment failure. Secondly, this analysis was based on cross-sectional observational data thereby limiting our ability to determine a causal relationship between laboratory parameters used to monitor second-line ART adherence and VF. Similarly, baseline values which would have improved our understanding of the factors associated with VF by looking at the temporal associations of clinical and laboratory parameters with second line ART, were unavailable. However, because LH and MPC outpatient HIV clinics are major public providers of second line ART in Malawi’s capital city of Lilongwe, the findings in this study could be generalizable for ART programs in Malawi and other regions with a generalized HIV epidemic in urban populations. Thirdly, pill count adherence may be misleading particularly in treatment-experienced patients in whom social desirability bias may encourage pill dumping and lead to overestimation of medication adherence (>105%). Pill count adherence was overestimated in 73 49.7%) of those with poor pill count adherence estimates. However, just like sub-optimal pill count adherence (<95%), overestimation of adherence has been associated with increased risk of VF  thus jus.7% of th3. Therefore, individuals with normal or low bilirubin levels and VF (VL >1000 copies/ml) while on ATV/r-based second line ART would benefit from intensive adherence counseling and support to help optimize the duration of second line treatment regimens. Drug resistance testing targeted for patients with virological failure despite persistently elevated bilirubin levels would facilitate timely switch to third line antiretroviral regimens whenever available.Given the limited access to VL monitoring, drug resistance testing and third line treatment regimens in sub-Saharan Africa, strategies for cost-effective delivery of ART services are needed. Bilirubin, as a surrogate marker for ATV/r adherence among patients receiving second line therapy, better predicted VF than pill count adherence. Strategic use of bilirubin and VL testing to target adherence counseling and support may be cost-effective in monitoring second line ART adherence and VF particularly for adults aged 25–40 years and those with CD4 cell count <100 cells/mm


Given their short plasma half-lives, such an effect may be transient and only apparent during ongoing exposure.Despite compelling evidence for activity against HIV-1 We studied all HIV infected US-Veterans who started HAART 1995–2011, had a documented HIV viral load (VL) >1000 copies/mL, reached an undetectable VL on HAART, and had ≥1 follow-up VL within 13 months. We defined virologic failure (VF) as the first VL >1,000 copies/mL or the first of 2 consecutive VL >200 copies/mL. We built a time-updated drug exposure model for antiretrovirals (ARVs), statins, and other cardiovascular drugs (CVMs), investigating current use (yes/no), recent use (proportion of days used), and categorical use (ever/never). We used both multiply adjusted and inverse-probability-weighted (IPW) Cox models to explore the association between statin and CVM use and VF.19,324 veterans met inclusion criteria. Median follow-up was 13 months (IQR: 5–32 months); 63% experienced VF after a median time of 9 months (IQR 4–21 months). Almost 1/3 patients ever used statins but exposure comprised only 41% of follow-up time covered after initial prescription. Unadjusted, current statin use was associated with a hazard ratio (HR) for VF of 0.60 (CI: 0.56–0.65). This remained statistically significant after multivariate adjustment (MVA) for demographics, HIV and HAART parameters  and IPW (truncation <1%/>99%) HR: 0.83 (CI: 0.75–0.92), p<0.001]. No independent association was observed for other CVMs. The association between categorical-statin use and VF after MVA was much weaker: HR 0.94 .Current statin exposure was associated with reduced risk of VF in univariate, multivariate, and inverse-probability-weighted models. Our results highlight the importance of time-updated medication exposure models for observational studies. They als effects , 3, most effects . The ant effects .in vitro [Even before the recognition of the high prevalence of HIV- and highly active antiretroviral therapy (HAART)-related dyslipidemia , statinsin vitro . Hypothein vitro –13in vitro data. In the absence of antiretroviral therapy (ART), statin use has not been associated with reduced HIV plasma viral load (VL) [Yet, clinical studies had never confirmed these oad (VL) –16. A Euoad (VL) , and a soad (VL) .Given the relatively short plasma half-lives of statins, the absence of a clinically relevant virologic effect in these studies could be explained by not accounting for ongoing statin use. We hypothesized that a potential inhibitory effect on HIV replication would only be apparent in patients recently or currently exposed to statins. Given the low prevalence of hyperlipidemia and lipid-lowering therapy before virologic suppression  and the We used the VA Clinical Case Registry (CCR), which contains all non-narrative clinical data for HIV-infected patients receiving care in the Veterans Health Administration network . It contWe studied all patients who had achieved virologic suppression on HAART from 1995–2011 meeting the following criteria: ≥ 1 detectable VL >1000 c/mL, followed by ≥ 1 undetectable VL, and ≥ 1 more subsequent VL measurement within 13 months after HAART initiation. Given that the threshold of lower limit of VL quantitation evolved of during the study period (from <500 in 1995 to <20 in 2011), patients were categorized as having undetectable VL according to the threshold in effect at the time of the measurement. For this purpose, ‘undetectable’ was defined as undetectable at any level <1000 copies/mL or <50 copies/mL. In a sensitivity analysis, we restricted inclusion to patients with ≥ 1 undetectable VL measurement after ≥ 6 months of viral suppression following HAART initiation. Virologic failure (VF) was defined analogous to current US guidelines  as the fBaseline was defined as the date of the first undetectable VL measurement after HAART initiation. Follow-up time ended at the day of VF, the last VL measurement before January 1 2012, or at death for the combined endpoint. We censored patients after 13 months without VL measurements to allow for one missed visit in patients with twice yearly monitoring. Premature or informative censoring was defined as censoring ≥13 months prior to January 1 2012.Time to VFTime to VF or death (within 13 months of last VL measurement).We stratified all analyses by time during which first VL suppression was achieved, choosing three time-periods, which approximately amounted to tertiles and represented different HAART eras: 1) 1995–2000, 2) 2001–2005, and 3) 2005–2011.We included the following baseline covariates: age, gender, race, history of drug abuse, time from HIV diagnosis to viral suppression, peak VL before baseline and duration of non-HAART ARV use prior to HAART initiation. We included the following time updated covariates: CD4 counts, ARV class experience, substance abuse, HCV status, and adherence to HAART components (see below). Most of these have been associated with VF . AdditioMedication exposure and adherence for this study was derived from the VA pharmacy benefit management database, which is integrated into the CCR and contains detailed information about all outpatient medication prescriptions and refills and inpatient medication orders. Based on the assumption that patients were continuously exposed to filled outpatient medications until they ran out of drug supply, we tabulated uninterrupted exposure episodes on a day-to-day basis for antiretrovirals (ARVs), statins, non-statin lipid lowering agents (ALP), antihypertensives (AHT), and cardio-protective aspirin (ASA). We accounted for increased drug supply because of early refills, changes of therapy, and unused outpatient drugs during hospitalizations. During hospitalizations, medication exposure was complemented with inpatient prescription data. A detailed description of this process which is analogous to a recently proposed method for estimation of time-varying drug adherence  is contaCurrent use defined as current exposure/use within the previous 7 daysproportion of days covered by drug exposure over the past 1 or 3 months.Proportion of days covered (PDC) measuring the extent of recent exposure, defined as Categorical use: all patients were classified as exposed after initial prescription.The PDC model was calculated by subtracting cumulative medication exposure at days -30 or -91 from the cumulative medication exposure at the day of VL measurement and dividing the result by the corresponding time interval –26. We uand zidovudine and (lamivudine or emtricitabine). For the purpose of comparative effectiveness, we grouped NRTI exposure into four complementary categories and anchor drug exposure into four mutually exclusive categories:We classified ARVs into nucleoside/nucleotide analogues (NRTIs) and anchor drugs . We defined HAART as either: ≥1 anchor drug with ≥2 NRTIs, triple-class therapy, a protease inhibitor (PI) with ritonavir (bPI) plus a non-nucleoside reverse transcriptase inhibitor, or triple NRTI therapy if it contained: (tenofovir or abacavir) NRTI: a) Tenofovir; b) Lamivudine or Emtricitabine; c) other NRTIs; d) no NRTIs;Anchor drug: a) Efavirenz, Ritonavir-boosted Darunavir, or Integrase Inhibitor (“modern anchor”); b) Ritonavir-boosted Protease Inhibitors (PI) other than darunavir; c) unboosted PI or Nevirapine or other; d) No anchor drug.We used VA National Laboratory Test codes and Logical Observation Identifier codes and custom text string searches to identify all relevant laboratory data. All laboratory values were handled as ‘last value carried forward’. We defined substance abuse at the time of virologic suppression as the presence of ≥ 2 indicative ICD9 codes. As statin initiation was likely guided by multiple and evolving criteria for hyperlipidemia, we created a unified parameter by calculating a low-density lipoprotein cholesterol (LDL) equivalent, which incorporated both LDL and non-high density (Non-HDL) cholesterol. This was defined as the maximum of LDL and (Non-HDL - 30mg/dL) for any cholesterol subclass measurement if the patient had been off lipid-lowering therapy >7 days.We fit Cox regression models with multivariate adjustment (MVA) for all medication exposure modes. We explored main effects of the stated covariates and retained all significant predictors (p<0.05) for the final models in which we also explored clinically plausible 2- and 3-way interactions between covariates  censoring. We first explored the main effects of all significant covariates from the MVA PDC model including time-updated age and retained only significant covariates for the final models in which we again included 2- and 3-way interactions including with time. The coefficients were then used to calculate propensity scores for current statin and CVM use and premature censoring. Based on current statin or CVM use or censoring we then calculated inverse proportional weights (IPW) for each time point with VL measurement which were stabilized by observed incidence and truncated at three different percentile levels: 5th, 1st and 0.1st percentile. IPW wasData extraction, cleaning, and compilation and statistical procedures were carried out with SPSS , Microsoft Excel for Mac and Windows 2011/2010, , and the survival package of R Version 3.31, .Eighty percent of 36,360 veterans who started HAART from 1995–2011 achieved an undetectable VL measurement. Of these 29,112 patients, 19,324 met inclusion criteria. Their characteristics, stratified by HAART era during which viral suppression was achieved, are shown in The median observation time  was 5.9 years, inter-quartile range (IQR):2.6–9.8 years. In contrast, the median follow-up time (time until VF or censoring) was only 15 months (IQR: 6–40 months)). More than half of patients  experienced VF after a median time of 9 months (IQR 4–21 months) while 12%  were prematurely censored. Twenty-two percent  of study patients died. The majority of deaths (75%) occurred after virologic failure or censoring. Only 1,065 patients (25%) died during follow-up. Of note, 74% of the patients with VF subsequently achieved another episode of virologic suppression.Almost three quarter of our patients  used statins or CVMs during the study period follow up, most commonly AHT , followed by statins , ASA , and ALP . The most commonly used statin was pravastatin (40%), followed by simvastatin (23%), fluvastatin (13%), rosuvastatin (13%), atorvastatin (9%), and lovastatin (2%). Statins use was uncommon before reaching viral suppression; 91% of all statin users started statins while on suppressive HAART. Exposure to statins and CVMs was discontinuous. After initial prescription, the proportion of observation time subsequently covered by the respective medication class was only 60% for AHT, 41% for statins, 32% for ALP, and 27% for ASA. Specifically, exposure to statins was frequently interrupted, with almost half of all statin users having ≥1 exposure interruption of >14 days and one quarter having ≥5 such interruptions.In univariate analysis, current statin or CVM use was statistically associated with a decreased risk of VF. This was most pronounced for statins with a hazard ratio (HR) of 0.60, 95% Confidence Interval (CI): 0.56–0.65. After MVA, only statin use remained a significant negative predictor for VF: the adjusted HR was 0.83 (CI: 0.76–0.90) in the PDC model, and 0.81 (CI: 0.75–0.88) in the current use model. Using IPW, only statins but not CVMs were associated with lower VF risk: HR: 0.83 . In coA total of 14,841 patients were included in the sensitivity analysis restricted to patients with a virologic suppression period of at least 6 months. In this group, the median follow-up was 32 months (IQR 18–59 months), the rate of VF was 42% , and the median time to VF was longer . The association between current statin use and reduced HR for VF was weaker but remained statistically significant after multivariate adjustment  and IPW with 5% truncation . The cuFor the combined endpoint of VF or death during viral suppression the effect of statin use was similar to the primary analysis , simvastatin (23%), and rosuvastatin (13%), remained statistically significant  Table E.Figs We examined whether statin use during stable virologic suppression on HAART was independently associated with a lower risk of initial HIV rebound. We stratified all analyses by time period during which viral suppression was achieved. The three time periods chosen approximately amounted to tertiles and also represented different HAART eras. The first time period was characterized by the predominant use of unboosted PIs as anchor drugs, while the next time period from 2001–2005 was marked by the emergence of boosted PIs and tenofovir. The final period after 2005 saw the dominance of tenofovir as NRTI backbone, the abandonment of unboosted PIs as anchor drugs, and the emergence of fixed dose ARV combinations.We found that current statin exposure was associated with a lower risk of VF in univariate and multivariate models and after inverse probability weighting. This was not seen with other CVMs, including ALPs, AHTs and ASA.As illustrated in Figs Because of the observational nature of our study and our strict definitions, virologic failure was common and often occurred early, leading to a short median follow-up time. This may have led to selection bias, as repeated confirmation of undetectable VL results may have often been a precondition for statin prescription. However, a sensitivity analysis restricted to patients with more than six months of virologic suppression also showed statistical significance, albeit with reduced effect size (HR 0.89 vs. 0.81). This may be related to the observation that the risk of virologic rebound declines with longer time of viral suppression, independent of HAART-adherence . PatientWhen statin exposure was used as a time-dependent categorical variable , the association between statin use and viral rebound was much weaker (current use model) or no longer significant (PDC model). The likely explanation for this is that after initial prescription, actual statin exposure covered only 41% of observation time. A modest and transient effect would thus likely weaken after cessation of the drug. This may also be the explanation why our results of current and recent statin use are different from previous observational studies when statin use was analyzed as a categorical variable.HAART adherence is the most important factor determining the risk of VF, and pharmacy refill data have emerged as a preferred mode of ARV adherence measurement , 32. OurThe mechanism(s) of the protective effect of statins on the chance HIV rebound are unclear. While anti-inflammatory properties are arguably the most often cited pleiotropic statin effect and could play an important role in explaining our findings, we also observed that the use of cardio-protective aspirin was independently associated with a moderately increased risk of VF. An ongoing large controlled prospective trial with pitavastatin (REPRIEVE)  may soonWhile a 17–19% relative risk reduction of VF would only translate into 3.5–4% absolute risk reduction in the context of a contemporary antiretroviral regimen with a virologic suppression rate of 80% of, our findings could have clinical importance in settings with sub-optimal adherence or limited options for a secondary ART regimen.The strengths of our analysis include the rigorous and sophisticated modeling of medication exposure, owing to the very granular pharmacy utilization data of a large, well-characterized observational cohort. This allowed us to model daily use of concurrent ARVs, statins, and other CVMs, including other lipid-lowering agents and to analyze their effects concomitantly. We explored different modes of medication exposure, applied several forms of bias correction (MVA and IPW), and tested the robustness of our findings with a sensitivity analysis and an alternative outcome.in vitro [Cyclooxygenase-2 inhibitors have previously been reported to decrease markers of immune activation and cell exhaustion and increase immunologic responses to vaccination in HIV-infected adults in vivo, and to in vitro . In our The limitations of our study include its retrospective and observational nature, the likely presence of unknown and/or unmeasured confounders, which we tried to address using IPW, and the lack of representation of women. In addition, our medication exposure model including the grouping of ARVs has not been validated and we did not have information on antiretroviral resistance for our models. The VA CCR is not an actively managed cohort and ARV exposure histories from outside the VA system are not captured within its pharmacy data, but the proportion of veterans obtaining antiretrovirals outside the system is very low. The precise time to virologic failure in clinical settings cannot be determined. Low medication adherence will affect the frequency of VL monitoring and patients with low HAART adherence may have been monitored more frequently and were thus likely to experience VF earlier in our model. While this would lead to an overestimation of the contribution of low medication adherence to VF, it may have been counterbalanced by delayed VL monitoring in other patients with poor adherence.In summary, we show that statin use is independently associated with a lower risk of virologic rebound on HAART. To our knowledge, this is the first demonstration of such an adjuvant anti-HIV effect for a non-antiretroviral class of medications and may be another reason beyond cardiovascular benefits to use statins in HIV-infected individuals.S1 Data(ZIP)Click here for additional data file.S1 FileText A: Describes the Medication Exposure Models in detail. Table A Legend: HR: none. Table B Legend: HR: Hazard Ratio . PDC: percentage of days covered: last 30 days for statins and CVMs, last, 90 days for ARVs, VF: Virologic Failure, Boosted PI: Ritonavir boosted Protease Inhibitor, 3TC: Lamivudine, FTC: Emtricitabine. Modern Anchor: Efavirenz, boosted Darunavir, or Integrase Inhibitor. Gray Shade: Baseline covariates (non-time dependent). Native LDL equivalent: LDL or Non-HDL cholesterol -30mg/dL, whichever was higher off lipid-lowering agents. Treatment Interruption: Time period without any ARVs. P-values: * 0.01–0.05, ** 0.001–0.01, *** <0.001. Table C Legend: HR: Hazard Ratio . PDC: percentage of days covered: last 30 days for statins and CVMs, last, 90 days for ARVs, VF: Virologic Failure, Boosted PI: Ritonavir boosted Protease Inhibitor, 3TC: Lamivudine, FTC: Emtricitabine. Modern Anchor: Efavirenz, boosted Darunavir, or Integrase Inhibitor. Gray Shade: Baseline covariates (non-time dependent). Native LDL equivalent: LDL or Non-HDL cholesterol -30mg/dL, whichever was higher off lipid-lowering agents. Treatment Interruption: Time period without any ARVs. P-values: * 0.01–0.05, ** 0.001–0.01, *** <0.001. Table D Legend: All hazard ratios (HR) are followed by 95% confidence intervals in parenthesis.PDC: percentage of days covered, IPW: Inverse Probability Weighting for treatment and censoring. *PDC interval 30 days for statins/CVMs and 90 days for ARVs. In PDC mode HR is for 100% use. Table E Legend: All hazard ratios (HR) are followed by 95% confidence intervals in parenthesis.(DOCX)Click here for additional data file.


The prevalence of high blood pressure (HBP) and hypertension (HTN), awareness of the diagnoses, and use of anti-hypertensive drugs were examined among human immunodeficiency virus (HIV)-infected individuals on antiretroviral therapy (ART) in Zambia’s capital Lusaka. Within a prospective cohort based at two public sector ART clinics, BP was measured at ART initiation and every 6 months thereafter as a routine clinic procedure. Predictors of HBP (systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg) during one year on ART were analyzed using logistic regression, and the proportion with HTN (2+ episodes of HBP >3 months apart) described. A phone survey was used to understand patient awareness of HBP, use of anti-hypertensive drugs, and history of cardiovascular events . Among 896 cohort participants, 887 (99.0%) had at least one BP measurement, 98 (10.9%) had HBP, and 57 (6.4%) had HTN. Increasing age , male sex , and overweight/obesity  were associated with HBP. Among 66 patients with HBP, 35 (53.0%) reported awareness of the condition, and nine (25.7%) of these reported having had a CVE. Only 14 (21.2%) of those reached reported ever taking an anti-hypertensive drug, and one (1.5%) was currently on treatment. These data suggest that major improvements are needed in the management of HBP among HIV-infected individuals in settings such as Zambia. Human immunodeficiency virus (HIV)-infected individuals have an increased risk of cardiovascular disease (CVD) compared to the general population . CVD-relA prospective HIV cohort was established in 2013 at two public-sector clinics in Lusaka to investigate viral hepatitis–HIV co-infection ,13. FromData collection mirrored that of the clinics, including baseline assessment of demographic characteristics, World Health Organization HIV clinical stage, and CD4+ count. At ART initiation, potential non-communicable disease (NCD) risk factors were assessed including body mass index, current smoking status (yes/no and pack-years among current smokers), alcohol consumption (based on the Alcohol Use Disorders Identification Test-Consumption), and BP. BP was measured once in the upper arm by a nurse or lay health worker using a battery-operated automated monitoring device  and medium-sized adult cuff after the patient was seated for 2–4 min. The preferred ART regimen at the time was fixed-dose combination of efavirenz, emtricitabine, and tenofovir disoproxil fumarate. At 24- and 48-week follow-up visits, BP was re-measured per clinic practice. Medications for HTN are free of charge in the outpatient departments of health facilities in Zambia. However, clinicians in ART clinic may also prescribe these drugs.During December 2015 to January 2016, a phone survey was conducted of all cohort participants with HBP, defined as elevated systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, during the first year on ART. HTN was defined as elevated systolic or diastolic BP measurements on two separate visits at least 3 months apart. Pharmacy records were also extracted for any anti-hypertensive, any diabetic drugs, or any documented CVD events. Using the phone number on file in the clinic, a nurse made up to five attempted calls to patients with HBP over several different days and times. If reached, using a standardized data collection tool, the nurse asked a series of questions in the local language  concerning patient awareness and history of HBP (including location of diagnosis). Prior or current receipt of anti-hypertensive drugs, history of other CVD risk factors (diabetes) or cardiovascular events , and family history of HTN were ascertained by patient report.Factors associated with having HBP in the cohort were assessed using a stepwise logistic regression model with a backward selection algorithm. The removal probability was set at 0.2 using likelihood ratio test. Among HBP patients who participated in the phone survey, the proportion with awareness of the condition and the proportion who ever took anti-hypertensive drugs were described, as well as the number who self-reported a history of CVE. Stata v13  was used for analysis. The University of Zambia Biomedical Research Ethics Committee approved the study .3 (IQR 118–337 cells/mm3). At baseline, 102 (11.6%) patients were overweight or obese, and this was more common among women than men . Men were more likely to report smoking  at baseline compared to women. Patient demographics were similar between 2013–2014 and 2014–2015. During the first year on ART, 60 (6.7%) were lost to follow-up.Among 896 cohort participants, the median age was 34 (interquartile range [IQR] 29–40 years), 467 (52.1%) were women, and the median CD4+ count at ART initiation was 227 cells/mmp = 0.29). Increasing age (for each 10-year increase in age [BP was measured for 883 (98.5%) at baseline, for 751 (97.9%) of the 767 with retention at the 6-month visit, and for 604 (84.8%) of the 712 with retention at the 12-month visit; 770 (85.8%) had at least two measurements. During the first year on ART, 98 (10.9%) patients had documented HBP on at least one occasion, and 57 (6.4%) had HTN. Retention at 1 year was similar between patients with HBP and normal BP at baseline , the line was inactive/invalid (n = 5), the patient had died (n = 3), or there was no documented phone number (n = 3). Thirty-five (53.0%) patients reported being aware of having HBP, and awareness increased with increased number of HBP measurements (35.3% for one and 60% for two to three elevated readings). Most patients (62.9%) became aware of HBP at the ART clinic (62.9%), while others were diagnosed at the clinic’s outpatient department (22.9%) or at a referral hospital (14.3%). The diagnosis of HBP was primarily communicated to patients by nurses (60.0%) and less commonly by a physician (25.7%) or a clinical officer (14.3%).During the phone survey, 92 patients with HBP were called. Of these, 66 (71.7%) were reached, and 26 were not reached because there was no answer (n = 4) and furosemide (n = 3) were the most commonly taken medicines for HBP, but the majority (n = 7) could not recall the names of the drugs they had taken. Review of the HIV clinic records for patients with HBP did not reveal any additional anti-hypertensive prescription or CVE information. Of the 66 patients reached by phone, 24 (36.4%) by either file review or self-report had at least one other known CVD risk factor, and nine (13.6%) self-reported a history of CVE.Although many patients were aware of having HBP, only 14 (21.2%) had ever taken an anti-hypertensive drug, and only one person was currently taking a drug for treatment of HTN . NifedipTo the authors’ knowledge, this is the first study on patient awareness of HBP and its management in an HIV care setting in Zambia. Routinely collected HIV data were augmented using a phone survey, which is an efficient way to assess and distribute public-health information . Approxi2) that were common in the cohort. HBP tends to become more common after ART initiation and may cause HTN [BP was measured regularly at clinic visits and documented in files, suggesting that screening for HTN in HIV care settings is feasible. The data on HBP build on other studies ,16 and wause HTN . Consistause HTN , only haause HTN , few patause HTN ,19.This study has several limitations. In the primary analysis, HBP was defined as a single elevated measurement, and BP was measured only once at each time point. This may have inflated the number of patients truly needing treatment, as only 58% of patients with HBP were confirmed to have HTN. Data on currently anti-hypertensive medications were not well documented in ART clinic. Therefore, HTN patients on treatment who did not have HBP during the cohort could have been overlooked. However, this would have been uncommon because so few patients in the phone survey reported taking BP-lowering drugs. Self-reported phone survey data were subject to recall bias and may have been inaccurate. Clinical adjudication of patient-reported CVEs would have strengthened the data, as it is acknowledged that in Zambia, health literacy is low, and reported CVEs may have been miscommunicated. Finally, an urban cohort was studied, and thus the data may not be generalizable to rural areas.CVD will surpass infectious diseases as the leading cause of death in Africa by 2030 [