ART) is scaled up, more patients become eligible for routine viral load (VL) monitoring, the most important tool for monitoring ART efficacy. For HIV programmes to become effective, leakages along the VL cascade need to be minimized and treatment switching needs to be optimized. However, many HIV programmes in resource‐constrained settings report significant shortfalls.As antiretroviral therapy  on ART from the time of the first elevated VL (>1000 copies/mL) between January 2013 and June 2014 to treatment switching by December 2015. We additionally described HIV drug resistance for patients with virological failure. We used descriptive statistics and Kaplan–Meier estimates to describe the different steps along the cascade and regression models to determine factors associated with outcomes.From a public sector VL, 252 (30.4%) did not receive any enhanced adherence counselling (EAC). Six hundred and ninety‐six (84.1%) patients had a follow‐up VL measurement, and the predictors of receiving a follow‐up VL were being a second‐line patient (adjusted hazard ratio (aHR): 0.72; p = 0.051), Hlathikhulu health zone  and having received two EAC sessions . Four hundred and ten patients (58.9%) achieved VL re‐suppression. Predictors of re‐suppression were age 50 to 64 (adjusted odds ratio (aOR): 2.02; p = 0.015) compared with age 18 to 34 years, being on second‐line treatment  and two  or three  EAC sessions. Of 278 patients eligible to switch to second‐line therapy, 120 (43.2%) had switched by the end of the study. Finally, of 155 successfully sequenced dried blood spots, 144 (92.9%) were from first‐line patients. Of these, 133  had resistance patterns that necessitated treatment switching.Of 828 patients with a first elevated ART with high VLs were more likely to re‐suppress if they received EAC. Failure to re‐suppress after counselling was predictive of genotypically confirmed resistance patterns requiring treatment switching. Delays in switching were significant despite the ability of the WHO algorithm to predict treatment failure. Despite significant progress in recent years, enhanced focus on quality care along the VL cascade in resource‐limited settings is crucial.Patients on  The World Health Organization (WHO) recommends a VL test six and twelve months after starting ART and every twelve months thereafter Resource‐limited settings are scaling up routine VL monitoring. However, VL demonstration projects reported programmatic shortfalls and variability in quality of care along the VL cascade Understanding of the gaps along the VL cascade remains limited but is needed to inform VL scale‐up in resource‐limited settings. We evaluated the performance of the VL cascade in a public health sector programme and describe the ability of the WHO VL testing algorithm to predict the need for treatment switching.22.1In Swaziland, 31% of the adult population (aged 18 to 49 years) are HIV positive 2.2This retrospective cohort analysis included patients on first‐ and second‐line ART who were aged 18 years or over and had an elevated VL > 1000 copies/mL 2.3Patients with elevated VLs were identified through the laboratory‐based VL database. Clinical, counselling and demographic information were extracted from individual patient files and facility‐based registers.2.4Dried blood spots (DBS) were obtained consecutively from patients with virological failure in the same primary care clinics and from three secondary care facilities between August 2013 and September 2014, and sent to the Centers for Disease Control (Atlanta) for HIV DR testing DR mutations were analysed according to the HIVdb Stanford Genotypic Resistance Interpretation Algorithm, and DR was defined as low, intermediate or high resistance against the most commonly used antiretroviral drugs: nucleoside reverse transcriptase inhibitors (NRTIs) – zidovudine, lamivudine (3TC), abacavir (ABC), stavudine, didanosine and tenofovir (TDF); non‐nucleoside reverse transcriptase inhibitors (NNRTIs) – efavirenz (EFV) and nevirapine (NVP); and protease inhibitor (PI): ritonavir‐boosted lopinavir (LPV/r). DR requiring treatment switching was defined as any DR to both EFV and NVP for a patient on first‐line therapy and any LPV/r resistance for a patient on second‐line therapy. Owing to a long turnaround time in receiving the genotype results, the treatment switching decision was based on documented virological failure.2.5An elevated VL was defined as a VL > 1000 copies/mL Patients were followed‐up from the time of first recorded elevated VL until uptake of the second consecutive VL test and from the time of the second elevated VL test to treatment switching in time‐to‐event analysis. Censoring occurred at the date of last clinic visit for patients lost to follow‐up (LTFU) at the facility (three months without a recorded clinic visit) or at the end of the observation period on 31 December 2015.EAC was assumed to have been done if the adherence session was recorded in the patient's file or in the facility‐based EAC register.2.6We calculated counts and proportions of patients at every level of the cascade. A Pearson's chi‐square test was used to compare categorical variables, and the Kruskal–Wallis test was used for comparison of continuous variables. We used Kaplan–Meier survival curves to estimate cumulative probabilities of receiving a follow‐up VL test. LTFU was treated as a competing risk for switching to second‐line therapy after two consecutive elevated VLs. A Fine and Gray proportional subdistribution hazards model DR was determined for each individual first‐ and second‐line drug. Patients on first‐line therapy were considered eligible for switching (according to the genotype resistance testing results) if they had developed high‐, intermediate‐ or low‐level resistance to both NNRTIs (NVP and EFV), as were those on second‐line therapy if they had developed resistance to LPV/r. We calculated the positive predictive value (PPV) of the WHO treatment‐switching algorithm by using the number of people with genuine resistance requiring treatment switching over the total number of patients who received a genotype.Statistical analysis was performed with STATA 14.1 2.7Ethics approval was obtained from the MSF Ethics Review Board and the Scientific and Ethics Committee of the Ministry of Health of Swaziland.33.1A total of 828 patients Table  had at l3.2p = 0.007), were younger (p < 0.001), more likely to be on first‐line (p < 0.001) and less likely to have received any EAC (p < 0.001) but did not differ by sex or drug regimen. In the multivariable logistic regression, only EAC remained associated with LTFU.Of the 828 patients, 246 (29.7%) were LTFU. The proportion of patients LTFU differed by health zone  did not receive EAC, 133 (16.1%) received one session, 155 (18.7%) received two sessions and 288 (34.8%) received all three sessions. The median time from a first elevated VL to the first, second and third EAC session was 42 , 83  and 113  days respectively.In our cohort, patients who received EAC were more likely to re‐suppress VL, with an increased likelihood of re‐suppression with each additional EAC session. In total, 84.1% of patients with a first elevated VL received a follow‐up VL of whom 58.9% re‐suppressed.3.4Of the 828 patients, 696 (84.1%) received a follow‐up VL test by the end of the observation period. Of the 132 who did not have a follow‐up VL, 115 (87.1%) were LTFU, and 17 (12.9%) were retained on ART. The median time to the follow‐up VL test was 4.6 months , and VL test uptake at three and six months were 15.6% (95% CI: 13.3 to 18.3) and 62.1% (95% CI: 58.8 to 65.4).Compared with findings from the early rollout in this setting p = 0.012) compared with age 18 to 34 years and being on second‐line treatment . The odds of re‐suppression increased with each consecutive EAC compared with patients receiving no intervention, being 1.28 (p = 0.319), 1.40 (p = 0.152) and 1.51 (p = 0.045) for one, two and three EAC sessions. Only second‐line treatment remained significantly associated following sensitivity analysis.Overall, 410 (58.9%) of the 696 patients with a follow‐up VL had re‐suppressed: 321 (60.3%) of 532 patients who received at least one EAC and 89 (54.3%) of 164 patients without EAC. In multivariable logistic regression  patients eligible for treatment switching, only 43.2% had their first‐line treatment switched.Of the 696 patients with a follow‐up VL, 286 (41.1%) had presumptive virological failure. Eight (2.8%) were already on second‐line treatment before the VL result was available, leaving 278 (97.2%) eligible to be switched to a second‐line regimen after virological failure. Overall, 120 (43.2%) had switched by the end of the observation period, and the median time to treatment switching was 5.9 months  from the date the result was received back at the facility. Kaplan–Meier estimates showed that 12.6% (95% CI: 9.2 to 17.2) had switched regimens at three months after the date of blood sampling and 22.1% (95% CI: 17.6 to 27.4) had switched at six months.Thirty‐five patients were switched to second‐line after a single VL > 1000 copies/mL . A review of their VL history showed that 17 patients had an elevated VL at their most recent previous VL test.p < 0.001) was associated with increased probability of treatment switching, but only one patient was in this group. Receiving one, two or three EAC sessions showed a tendency towards increased treatment switching, but this was not statistically significant.In multivariable competing risk regression Table , an ABC‐Treatment switching remained low (43.0% at the end of follow‐up), higher compared with the early rollout The cascade is illustrated in Figure 3.6p = 0.881), and resistance to LPV/r ranged from 0% to 66.7% by regimen (p = 0.054)  were successfully sequenced, with 144 (92.9%) patients on first‐line ART, 10 (6.5%) on second‐line ART and 1 (0.6%) missing regimen information. Ninety‐three (60.0%) patients were female, sixty 38.7%) were male and two (1.3%) had missing sex information. Sixty‐seven (43.2%) patients were from primary care clinics, seventy‐nine (51.0%) were from secondary care facilities and nine (5.8%) had missing health facility information. Resistance to both EFV and NVP ranged from 87.5% to 100% by regimen  had low, intermediate or high resistance to both EFV and NVP and were eligible for switching to second‐line ART (PPV for the need for treatment switching). This equated to 61 (95.3%) of 64 patients from primary health clinics and 63 (88.7%) of 71 patients from secondary health facilities. Only two (20%) of the second‐line patients had resistance to LPV/r.The WHO algorithm had high accuracy for predicting failure of first‐line ART as also reported from other sub‐Saharan settings, where resistance ranged from 53% to 93% This study had several limitations. The use of routine data is prone to suboptimal data quality and completeness, and leakages in our cascade might bias our findings. We could not ascertain patients’ final outcome and differentiate between patients LTFU and deceased. Because of the small number of second‐line patients, any significant associations for this group should be interpreted with caution.4VL monitoring has the potential to improve ART programmes and to bolster treatment support. We showed that the WHO VL algorithm works well for patients on first‐line ART. However, the ramifications of any delay are serious given the number of patients LTFU between each cascade step. Finally, for patients with suspected virological failure, even in the face of ongoing adherence problems, treatment switching should be considered as our data show that they most likely do have resistant mutations.The authors declare that they have no competing interests.KJ, RT, GM, IC, BK and SMK conceptualized, designed and developed the protocol. GM, MP, DE, IZ, MN, BK, CGE, CY and SMK implemented the research. MN, DE and CY collected the data. DE, MN and BK statistically analysed the data. BK, DE, IC, MN, RT, SMK, JG and RT interpreted the findings of the data. DE, BK and IC wrote the first draft of the manuscript. All authors read and approved the final manuscript.


This study aimed to determine the impact of annual versus semi‐annual pVL monitoring on treatment outcomes in Asian CLWH.Recommendations on the optimal frequency of plasma viral load  were included from a regional cohort study; those exposed to prior mono‐ or dual antiretroviral treatment were excluded. Frequency of pVL monitoring was determined at the site‐level based on the median rate of pVL measurement: annual 0.75 to 1.5, and semi‐annual >1.5 tests/patient/year. Treatment failure was defined as virologic failure (two consecutive pVL >1000 copies/mL), change of antiretroviral drug class, or death. Baseline was the date of the second consecutive pVL <400 copies/mL. Competing risk regression models were used to identify predictors of treatment failure.Data on children with perinatally acquired pVL monitoring, 1042 (85%) and 178 (15%) were from sites performing annual (n = 6) and semi‐annual pVL monitoring (n = 4) respectively. Pre‐cART, 675 children (55%) had World Health Organization clinical stage 3 or 4, the median nadir CD4 percentage was 9%, and the median pVL was 5.2 log10 copies/mL. At baseline, the median age was 9.2 years, 64% were on nevirapine‐based regimens, the median cART duration was 1.6 years, and the median CD4 percentage was 26%. Over the follow‐up period, 258 (25%) CLWH with annual and 40 (23%) with semi‐annual pVL monitoring developed treatment failure, corresponding to incidence rates of 5.4 (95% CI: 4.8 to 6.1) and 4.3 (95% CI: 3.1 to 5.8) per 100 patient‐years of follow‐up respectively (p = 0.27). In multivariable analyses, the frequency of pVL monitoring was not associated with treatment failure .During January 2008 to March 2015, there were 1220 eligible children from 10 sites that performed at least annual pVL monitoring was not associated with an increased risk of treatment failure in our cohort of virally suppressed children with perinatally acquired HIV on first‐line NNRTI‐based cART.Annual compared to semi‐annual  This study aimed to determine the impact of annual versus semi‐annual pVL monitoring on treatment outcomes within a cohort of Asian children with perinatally acquired HIV infection who were stable on first‐line, non‐nucleoside reverse transcriptase inhibitor (NNRTI)‐based cART.22.1The TREAT Asia Pediatric HIV Observational Database (TApHOD) is a multinational, longitudinal observational cohort of CLWH in the Asia‐Pacific region that is part of the International Epidemiology Databases to Evaluate AIDS (IeDEA) Asia‐Pacific. The data collection methods have been previously described The study population consisted of CLWH enrolled in the cohort before March 2015. All children with perinatally acquired HIV aged <18 years on a virally suppressive first‐line NNRTI‐based cART regimen were included in the study. This was defined as having two or more consecutive pVL tests <400 copies/mL spanning a period of at least six months while on a first cART regimen containing one NNRTI and at least two nucleoside reverse transcriptase inhibitors (NRTIs). We included only CLWH on NNRTI‐based regimens as this is the predominant first‐line regimen combination in the region. CLWH exposed to a mono‐ or dual‐antiretroviral regimen for the purposes of treatment prior to cART initiation and those receiving care at sites without at least annual pVL monitoring were excluded .2.2The frequency of pVL monitoring, which was largely influenced by the national HIV programme policy of each site, was determined at the site‐level based on a median rate of routine pVL measurement over the cohort follow‐up period Table . Sites w2.3In this study, treatment failure was defined as either having two consecutive pVL >1000 copies/mL while on cART, a change of antiretroviral drug class (e.g. change from NNRTI‐based to protease inhibitor‐based regimens) which was considered as a surrogate parameter of treatment failure in our CLWH with established viral suppression over a six‐month period, or death . Loss to follow‐up was described as not presenting to the clinic for longer than 12 months without documentation of transfer to another clinic or death.2.4Clinical characteristics were extracted from the database. Baseline was considered the date of the second pVL measurement <400 copies/mL to meet criteria for viral suppression. The window periods for measurements of weight, height, CD4 and pVL were within plus or minus three months of the date of interest. The measurement taken closest to that date was used in the analysis. Weight‐for‐age z‐scores (WAZ) were calculated using the 1977 National Center for Health Statistics/WHO reference 2.5Since this was a retrospective observational cohort study, we did not conduct sample size and power calculations, according to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines. Clinical characteristics of CLWH were analysed using descriptive statistics. The incidence rates of treatment failure were calculated by dividing the number of participants with treatment failure by the total number of patient‐years of follow‐up (PYFU). Kaplan‐Meier estimates and the log‐rank test were used to describe and compare the cumulative probability of treatment failure by the frequency of pVL monitoring.p < 0.10 on univariable analysis, together with the predictors of interest identified a priori. Covariates were retained in the final model if one or more categories exhibited a p < 0.05. Associations of predictor and study outcome were summarized with subdistribution hazard ratios (HR) and adjusted subdistribution hazard ratios (aHR) for univariable and multivariable analyses respectively. CLWH with missing covariate data were included in all analysis, but HR and aHR for the missing categories were not reported. Stata statistical software, version 14.1  was used to perform all statistical analysis.Competing risk regression models were used to analyse independent factors associated with treatment failure. CLWH were censored at their last clinic visit if they did not demonstrate evidence of treatment failure over the follow‐up. Loss to follow‐up was considered a competing risk event. Covariates were included in the multivariable model if any category exhibited a 33.1Among 2413 children with perinatally acquired HIV infection who had started cART at one of the 10 sites performing at least annual pVL monitoring, 1220 (46.7%) children from Cambodia, Malaysia, and Thailand met eligibility criteria . The med10 copies/mL. At baseline, the median age (IQR) was 9.2 (6.3 to 12.0) years, and 786 (64.4%) were on nevirapine‐based regimens. The median cART duration and CD4 percentage (IQR) were 1.6 (1.0 to 3.0) years and 26% (20% to 31%) respectively  were male. Prior to cART initiation, 55.3% of children were classed as WHO clinical stage 3 or 4, 77.9% had a nadir CD4 percentage <15%, and 62.5% had pVL >5.0 log3.2Over the follow‐up, 298 (24.4%) children met criteria for treatment failure, including 77 (5.9%) with two consecutive pVL >1000 copies/mL while on cART, 211 (17.3%) with cART drug class change, and 10 (0.8%) deaths. The overall incidence rate for treatment failure was 5.2 (95% CI: 4.7 to 5.9) events per 100 PYFU.p log‐rank test = 0.27). The Kaplan‐Meier estimates of unadjusted cumulative probability for treatment failure by pVL monitoring frequency during the first four years of follow‐up are illustrated in Figure Treatment failure developed in 258 (24.8%) children at sites with annual pVL monitoring, corresponding to an incidence rate of 5.4 (95% CI: 4.8 to 6.1) events per 100 PYFU; failure was detected among 40 (22.5%) children at sites with semi‐annual monitoring, corresponding to an incidence rate of 4.3 (95% CI: 3.1 to 5.8) events per 100 PYFU  were male. At the time of treatment failure, the median age (IQR) was 12.6 (10.3 to 15.1) years and CD4 percentage was 26% (19 to 31%). Among 89 children who were performed pVL measurement when developing treatment failure, the pVL (IQR) was 4.2 (3.4 to 4.8) log3.4In the multivariable analysis, compared with semi‐annual pVL monitoring, annual monitoring was not associated with treatment failure. However, older age and WHO clinical stage 4 prior to cART initiation  significantly increased the risk of treatment failure. Additionally, longer duration of NNRTI‐based cART use was associated with a decreased risk of treatment failure  HIV treatment guidelines vary in how frequently pVL testing is recommended. The DHHS treatment guidelines and the International Diseases Society of America recommend that pVL testing should be performed at four to eight weeks intervals after cART initiation, but can be extended to semi‐annually for adherent, clinically stable adolescents and adults whose viral load has been suppressed (pVL < 20 copies/mL) for at least two years and whose immunologic status has been consistently stable on cART . There is also the potential for misclassification at the individual level if patients had more frequent testing due to clinical concerns relative to their site classification. The relatively small sample size, particularly in the semi‐annual group, might also bias our results towards the null effect. We excluded CLWH receiving care at sites with less than 0.75 tests/patient/year, which biases our results towards facilities with greater resources to perform pVL measurement. Specifically, our Indian, Indonesian and Vietnamese cohort sites were excluded, further limiting the generalizability of our data within the region. Furthermore, we restricted the treatment outcomes we assessed to virologic failure, change of cART drug class and death, and did not evaluate opportunistic infections, hospitalizations and HIV drug resistance mutations, which may be impacted by poor adherence and viral failure at levels below our definitions. Although we relied on pVL testing as our primary means of assessing treatment response and failure, we did not have self‐reported adherence data to compare pVL to as part of our analysis.5Among this cohort of Asian children with perinatally acquired HIV who were stable on suppressive first‐line NNRTI‐based cART, annual pVL monitoring was not associated with an increased risk of treatment failure compared with semi‐annual monitoring. Taking into consideration patient‐level factors when determining pVL monitoring frequency may help balance clinical needs and program costs.AHS has received travel and project funding to her institution from ViiV Healthcare. Other authors declare no conflict of interest related to this study.TS developed the conception of research, designed the study, and developed the protocol. TS, LVN, TJM, DKW, TB, RH, PSL, PL, RAN, MSF, KC, NNY, KHT and VCD performed the data collection. DCB and TS designed and conducted the statistical analyses. TS contributed to the interpretation of study results. TS wrote the first draft of manuscript. DCB, LVN, TJM, DKW, AHS and VS provided critical revisions to the manuscript. TS revised the manuscript. All authors reviewed and approved the final version of the manuscript.Figure S1. The schema of study participants.*Viral suppression after cART initiation was defined as having two or more consecutive pVL tests <400 copies/mL spanning a period of at least six months. cART, combination antiretroviral therapy; NNRTI, non‐nucleoside reverse transcriptase inhibitor; pVL, plasma viral load; TApHOD, TREAT Asia Pediatric HIV Observational Database.Click here for additional data file.


Minority drug resistance mutations (DRMs) that are often missed by Sanger sequencing are clinically significant, as they can cause virologic failure in individuals treated with antiretroviral therapy (ART) drugs.This study aimed to estimate the prevalence of minor DRMs among patients enrolled in a Malawi HIV drug resistance monitoring survey at baseline and at one year after initiation of ART.Forty-one plasma specimens collected from HIV-1 subtype C-positive patients and seven clonal control samples were analysed using ultra-deep sequencing technology.Deep sequencing identified all 72 DRMs detected by Sanger sequencing at the level of ≥20% and 79 additional minority DRMs at the level of < 20% from the 41 Malawian clinical specimens. Overall, DRMs were detected in 85% of pre-ART and 90.5% of virologic failure patients by deep sequencing. Among pre-ART patients, deep sequencing identified a statistically significant higher prevalence of DRMs to nucleoside reverse transcriptase inhibitors (NRTIs) compared with Sanger sequencing. The difference was mainly due to the high prevalence of minority K65R and M184I mutations. Most virologic failure patients harboured DRMs against both NRTIs and non-nucleoside reverse transcriptase inhibitors (NNRTIs). These minority DRMs contributed to the increased or enhanced virologic failures in these patients.The results revealed the presence of minority DRMs to NRTIs and NNRTIs in specimens collected at baseline and virologic failure time points. These minority DRMs not only increased resistance levels to NRTIs and NNRTIs for the prescribed ART, but also expanded resistance to additional major first-line ART drugs. This study suggested that drug resistance testing that uses more sensitive technologies, is needed in this setting. The quasi-species nature of HIV-1 makes the detection of drug resistant mutations (DRMs) more difficult, because the commonly-used Sanger sequencing for drug resistance testing is incapable of detecting these drug resistant HIV variants at a level of less than 20% of the viral population.5Rapid scale-up of antiretroviral therapy (ART) over the past decade has remarkably reduced the mortality and morbidity of HIV-positive patients and decreased HIV transmission. Seventeen million HIV-1-positive patients around the world were receiving ART by the end of 2015.9 Recent studies have demonstrated that particular drug resistant HIV mutant viruses are clinically significant at a level of 1% of the viral population, as the minority variants can replicate quickly and become the predominant viral population through the selective pressure of ART drugs, leading to treatment failure.10 However, in the absence of drug pressure in treatment-naïve patients, the stability of transmitted DRMs is different.11 For instance, a transmitted M184V mutation can quickly revert to wild-type due to diminished viral fitness.12 In patients on ART, minority DRMs may persist for months or years during and post-ART.15 These minority DRMs, not detected by Sanger sequencing, present a need for more sensitive methods to detect the minority DRMs in a clinical sample.Minority drug resistant variants  that are not detected by Sanger sequencing are clinically important, as they can cause virologic failure in patients treated with ART for the first time.21Deep sequencing or next-generation sequencing technologies are extensively used to examine HIV viral diversity and minority drug resistant variants. Next-generation sequencing is a highly sensitive and high-throughput sequencing platform. It can detect HIV variants that make up 0.05% to 1% of viral populations.22 The most common non-nucleoside reverse transcriptase inhibitor (NNRTI) mutations were K103N (58.1%), Y181C (41.9%) and G190A (6.5%), and the most frequent nucleoside reverse transcriptase inhibitor (NRTI) mutation was M184V (61.3%). The DRMs conferring resistance against NNRTI at baseline were associated with DRMs detected at 12–15 months on ART.22 The present study aimed to evaluate parallel tagged deep sequencing primers on clinical samples and to investigate the profile of minority DRMs and their association with virologic failure in the same Malawi ART monitoring cohort.As part of HIV drug resistance surveillance by the Malawi Ministry of Health, a prospective cohort study to monitor ART outcomes and drug resistance development was conducted among patients from ART initiation to one year later. In this 2008 ART patient monitoring survey, 6.1% of the patients on ART for 12–15 months harboured drug resistant HIV.The study protocol was approved by the National Health Sciences Research Committee of Malawi Institutional Review Board (#1001). The use of de-identified data and drug resistance testing using Sanger sequencing and Roche 454 deep sequencing at the Centers for Disease Control and Prevention’s (CDC) global HIV drug resistance laboratory, was determined to be non-human subjects research under CDC protocol #6501 by the Office of the Associate Director for Science at the Center for Global Health, CDC, Atlanta, Georgia, United States.22 In the present study, we selected plasma specimens that had enough volume available to evaluate the assay. These were 20 samples collected from participants before ART initiation with viral loads ranging from 10 471 to 2 041 738 copies/mL and 21 samples collected from ART patients at virologic failure  after 12–15 months on ART . In addition, six plasmid clones and one mixed clone containing 1% mutant (2495 copies/µL) under the background of a wild-type clone were prepared and used to verify sequence accuracy in this study. All of these plasmid clones were derived from the Malawian cohort samples. All plasmids were constructed using TOPOTM vectors in Escherichia coli . The six wild-type plasmid clones contained the HIV-1 pol gene without any DRMs, and the mutant clone contained DRMs at codons 103, 181, 184 and 190 of the HIV-1 pol gene.Between February and June 2008, HIV-1-positive patients aged 15 years or older, who initiated first-line ART at four ART clinics following the Malawi ART guidelines, were enrolled. Patients were treated with a first-line regimen combination of stavudine, lamivudine and nevirapine, or an alternative first-line regimen of stavudine to zidovudine substitutions in case of toxicity. Plasma specimens were collected before ART initiation and at 12–15 months on ART for viral load and HIV drug resistance testing.22 The viral RNA was subjected to one-step RT-PCR amplification as described previously.11RNA was extracted from plasma specimens using the automated Abbott™ Sample Preparation System (m2000sp) . The copy number of HIV-1 RNA was measured using RT-qPCR on the m2000rt Real Time Analyzer .pol gene sequences (www.hiv.lanl.gov)  . Six ove23 Additional mutations for those samples collected before ART initiation were analysed based on the 2009 World Health Organization surveillance DRM list.24Sequence files generated by Roche 454 deep sequencing were analysed using GS Amplicon Variant Analyzer pipeline from Roche Applied Science . The deep sequencing analysis process in the present study included quality restriction for base call setting at 60 for signal intensity. All amplicon reads of alignment and single nucleotide polymorphism (SNP), calling against the HXB2 reference sequence, were evaluated with a quality score ≥ 25 and read length ≥ 220 base pairs. Sequence accuracy of Roche 454 runs was evaluated using the sequences generated by Sanger sequencing of the seven plasmid clones. The minority variant was defined as a SNP detected at > 0.68% and < 20% of the frequency of mutations. For DRM analysis, mutations were called and grouped based on International AIDS Society (IAS)-USA 2011 recommendations.11 Raw sequencing data were analysed using the customised ReCall software, v.2.24 .25 The mixed mutation calling threshold was set at ≥ 20% of the main peak. The DRMs were analysed as stated above for parallel deep sequencing results.The standard genotyping of HIV drug resistance was performed on all plasma samples using an in-house population-based sequencing assay.P-value of < 0.05 was considered statistically significant.All statistical analysis was performed using SPSS Statistics v19 . The Wilcoxon Signed-Rank test was used to analyse the statistical differences in the number of DRMs detected between Sanger sequencing and deep sequencing. Fisher’s exact test was used to compare the prevalence of HIV drug resistance by these two methods. A RT gene. There was only one SNP showing an error rate of 0.68% at codon 17 of the PR gene in a polyG region  reads passed the quality restrictions with a mean read length of 270 nucleotides, while 4603 (1.9%) low-quality sequences were removed from the analysis pipeline. On average, 5490 reads per sample were obtained (range from 420 to 5673 reads). From the 1% mixed clone, K103N was not detected within the 520 sequence reads; Y181C and M184V were detected at the level of 1.03% with 1335 reads, while G190A was detected at 0.97% with 785 reads. The mean error rate plus two standard deviations was 0.43 from the six control plasmid clones. Sequence errors mostly occurred at the overlapping areas of amplicons in the p = 0.004) and NNRTIs (p = 0.0001). Further, the Cohen’s effect size value (d = 0.91 and 0.79) suggests a moderate to high practical significance. No significant difference was found in detection of protease inhibitor (PI) mutations (p = 0.083)  .p = 0.015), but not for NNRTI  or PI  when compared to Sanger sequencing. The most common minority NRTI mutation was K65R (6 of 20), followed by M184I  of the 20 pre-ART samples by deep sequencing. Minority NRTI were detected in 10 (50%) of these samples and NNRTI mutations in 14 (70%), while minority PI mutations were found in three (15%) of the 20 samples. In addition, the number of DRMs detected by deep sequencing was higher than Sanger sequencing. This increase of DRM numbers detected by deep sequencing was statistically significant for NRTI  when compared to Sanger sequencing. Among the minority NRTI mutations, M184I was detected in three samples, and M184V and K65R in two samples respectively. Other minority mutations including M41L, A62V, D67N, T69D, V75M, T215F and K219E were found in one sample each. Among the minority NNRTI mutations, V108I, V179T were detected in four samples and G190A, H221Y and K101E were detected in three samples. Other NNRTI mutations, such as V90I, K103N, V106A/M, E138A, V179E, Y181C, Y188C/L and G190E were also found in one or two samples.Overall, minority DRMs were detected by deep sequencing in 90.5% (19/21) of the patients failing ART. Of the 21 Malawian samples, minority NRTI mutations were detected in 8 (38%) samples, while minority NNRTI mutations were detected in 14 (66.7%) samples . Minorit26 Fourteen (73.7%) out of the 19 patients also had an enhanced resistance level to NNRTIs and 13 of these 14 patients had intensified or expanded resistance profiles against the second generation of NNRTIs (etravirine and rilpivirine)  or expansion of drug resistance to additional drugs or drug classes from those 21 ART-failure patients against NRTIs and NNRTIs using the Stanford HIV drug resistance database tool. Among 19 patients with the additional minority DRMs detected, we found that seven (36.8%) of the patients had enhanced resistance levels to NRTIs. More importantly, three of the seven patients had gained low- to high-level resistance against tenofovir , a key civirine) . FurtherThe present study has shown that massively parallel deep sequencing is capable of detecting minority HIV-1 variants from HIV-1 subtype C clinical samples. The higher prevalence of minority DRMs in pre-ART Malawian patients to NRTIs by deep sequencing was statistically significant compared to Sanger sequencing. The minority mutation profile revealed that the increased minority DRMs were associated with enhanced DR levels in virologically failing patients.27This study was designed to evaluate parallel tagged deep sequencing in detection of minority DRMs in samples collected from Malawi. We successfully amplified all 41 plasma specimens collected from the patients and seven plasmid DNA samples that generated 242 246 sequencing reads using the degenerate primers designed for HIV-1 group M subtypes and circulating recombinant forms. Our results not only showed 100% concordance of DRMs detected by Sanger sequencing and deep sequencing, but deep sequencing also detected over 50% minority DRMs in these clinical samples. At the lower detection level of 0.68%, set by the current study, minority DRMs were detected in a majority of samples collected from patients before ART initiation and at virologic failure. Although we only analysed HIV-1 subtype C-positive Malawian samples in this study, the primers were designed for all relevant HIV-1 group M subtypes and circulating recombinant forms. In fact, we were able to amplify subtype B, B/C, F and G samples using these primers which were confirmed by gel electrophoresis and successfully detect 5 of 5 subtype B samples using deep sequencing methods.29 A study by Dudley et al.20 evaluated a 454 GS Junior sequencer by multiplexing 48 samples collected from HIV-1 subtype B-positive individuals and obtained a sequencing success rate of 93% and an error rate of 0.71%. Our study using GS-FLX with multiplexing on 48 samples collected from HIV-1 subtype C-positive patients showed a 100% amplification rate and 0.265% mean error rate. Many studies have reported that the mean error rate of pyrosequencing techniques can be down to 0.05% to 1%.30 The error rates for deep sequencing not only affect the accuracy of base calling, but also impact the sensitivity of minority variant detection. It has been reported that factors, such as the input number of template molecules, sequence primers, amplicon length, nucleotide sequences, PCR errors and operational procedures, might contribute to deep sequencing assay sensitivity and accuracy.33 In addition, error rates are nucleotide position-dependent and Roche 454 deep sequencing methods are prone to have more errors at the homopolymeric regions.31 In the present study, cross-over errors of major DRMs between samples were not found. To balance the detection sensitivity with detection accuracy, we set up the base calling threshold for low-frequency mutations at > 0.68% (mean error rate + 2 standard deviations) which was calculated based on the error rates of individual nucleotide positions of six control plasmid samples. In the present study, the K103N mutation was not detected from the mixed clone at 1% of minority variant level of control plasmids from 520 reads. This was likely due to not having enough reads amplified for this mixed plasmid as a previous study demonstrated that at least 1950 reads are required for detecting a minority variant for K103N mutations at about the 1% level.17 One limitation of our study was that the primer pair for amplifying amplicons containing codon 103 of RT gene was not optimal for the depth of coverage. Some minority K103N mutations could have been missed in this study. Thus, the number of sequence reads obtained for each nucleotide position and errors at the homopolymeric regions played an important role in the depth of the next-generation sequencing.Previous studies reported the use of parallel tagged deep sequencing methods in detecting low levels of HIV-1 subtype B variants.35 and is more frequently identified in HIV-1 subtype C.36 Similar to previous studies, the K65R mutation was seen in both treatment-naïve patients and patients failing ART in this cohort. Several studies have reported that increased presence of K65R mutations is caused by pyrosequencing errors or by the nucleotide template of subtype C viruses (such as the ATA sequence at codon 63 of the RT gene).37 Even though no errors at codon 65 of the RT gene were found by deep sequencing in the current study, we did find a relatively higher error rate at codon 63 of the RT gene in the subtype C plasmid sequences. However, we did not find higher error rates for K65R compared with other DRM sites in these patients. The M184I mutations were only detected at low frequencies by deep sequencing in pre-ART patients and patients with treatment failure. M184I was considered to be a transient mutation before being replaced by M184V.39 No detectable levels of M184V mutations were found in pre-ART samples using deep sequencing, but M184V mutation was detected in over three-quarters of samples from patients failing ART. Taken together, the higher NRTI resistance mutations of M184V and K65R in patients failing ART were more likely acquired by selective drug pressure in this Malawian cohort treated with a regimen containing stavudine and lamivudine.22Our results from samples collected from patients failing ART and initiating ART demonstrate that deep sequencing has the added benefit of detecting low-frequency mutations in this Malawian cohort. Overall, deep sequencing detected significantly more DRMs than Sanger sequencing. Of those specimens collected from patients initiating ART, more DRMs against NRTI were detected by deep sequencing. Among the minority DRMs, detected by 454 deep sequencing, K65R and M184I were the most common and may compromise the effectiveness of both first- and second-line drugs used according to the Malawi ART guidelines. The K65R mutation can confer resistance to stavudine and cross-resistance to lamivudine, abacavir, emtricitabine and tenofovir,40 The H221Y mutation could also impact clinical outcomes as Y181C/H221Y along with the K103N or K101Q mutations could increase resistance levels to nevirapine over 100-fold (K103N) or 3000-fold (K101Q).41 The drug resistance profile generated by deep sequencing revealed that these mutations were associated with the first-line regimen . The DRMs to NNRTI in pre-ART samples were also relatively high in these patients and were likely due to single-dose nevirapine used in the prevention of mother-to-child transmission program in Malawi.22 However, our results could not rule out the presence of transmitted drug resistance to NNRTI in these pre-ART patients.In this study, most samples collected from virologic failure patients had detectable DRMs to NNRTI by both Sanger sequencing and deep sequencing. The mutations K101E, K103N, V106A/M, V179D/T, Y181C, G190A/E and H221Y to NNRTI were the most common minority mutations detected in these patients. Virus with K101E/Y181C/G190A and other mutations could increase levels of resistance to nevirapine 893-fold.42 Because no PI drugs were used in the first-line ART in this cohort, these PI mutations were likely natural polymorphisms of HIV-1. The natural polymorphism of M46I has been reported to have a replicative advantage for subtype B,43 while the impact of M46I/L natural polymorphisms on the development of drug resistance in patients is unknown. As Malawi has started to use lopinavir/ritonavir for second-line regimens,44 the emergence of DRMs to PIs should be closely monitored.Although DRMs against PIs were not detected using Sanger sequencing, they were detected by deep sequencing in this cohort. M46I/L is considered a major PI mutation and would increase drug resistance levels to PIs along with other mutations.Evidence is lacking in understanding the real clinical impact of minority DRMs. Clinical trials are needed to accurately evaluate the clinical consequences of these DRMs. However, our results indicate that minority mutations detected by barcoded deep sequencing show an increased or expanded level of resistance to NRTIs and NNRTIs (see mutation scores in This study had its limitations. First, the sample size was small due to the availability of remnant samples and budget constraints. A statistically-appropriate sample size should be used for population-level estimations of DRMs in order to make a meaningful statement. Second, although significantly increased minority DRMs were observed in the samples collected from pre-ART and patients with virologic failure using Roche 454 barcoded deep sequencing, lack of proper plasmid mutant K65R control in the test might have compromised the accuracy of calculating the K65R mutation rate. Third, some methods in the current study could not be applied further as a result of the 454 platform and technologies being discontinued due to high cost and errors at some homopolymeric regions. However, the designed primers and barcoded strategy in the current study could be applied to other deep sequencing platforms for HIV drug resistance testing or studies.In conclusion, our study confirmed that barcoded parallel deep sequencing technology is capable of detecting minority DRMs from clinical patient samples. These minority DRMs not only increased resistance levels to the antiretroviral drugs that are being prescribed, but they also expanded resistance to additional major first-line antiretroviral drugs such as tenofovir. The minority DRMs detected by deep sequencing may be helpful for selecting the optimal regimens for patients initiating ART and for patients who fail first-line regimens.


Zimbabwe is on track towards achieving viral suppression among adults (87%). However, adolescents have only achieved 44% by 2016. In Harare city, 57% of adolescents had attained viral suppression after 12 months on ART compared to 88% among adults. We determined factors associated with virological failure among adolescents (age 10–19 years) on antiretroviral therapy (ART) in Harare city.p-values at 95% CI.We conducted a one to one unmatched case control study among 102 randomly recruited case: control pairs at the two main infectious disease hospitals in Harare. A case was any adolescent who presented with VL > 1000c/ml after at least 12 months on ART. A control was any adolescent who presented with VL < 1000c/ml after at least 12 months on ART. Interviewer administered questionnaires were used to collect data. Epi Info 7 was used to generate frequencies, means, proportions, ORs and We interviewed 102 case-control pairs. Poor adherence to ART , taking alcohol  and non- disclosure of HIV status  were independent risk factors for virological failure. Always using a condom , being on second line treatment  and belonging to a support group  were protective.Poor adherence, alcohol consumption and non-disclosure increased the odds of virological failure. Based on these findings support should focus on behavior change and strengthening of peer to peer projects to help address issues related to disclosure and adherence. Further operational research should aim to define other components of effective adherence support for adolescents with virological failure. Virological monitoring through plasma viral load (PVL) quantification is an essential part of clinical monitoring of HIV patients undergoing antiretroviral treatment therapy (ART), and for detecting treatment failure. In addition to showing how effective the ART is in suppressing the virus, it gives room for treatment to be modified to suite the strain of the virus in one’s body . HIV virThe World Health Organization (WHO) recommends routine annual viral load (VL) monitoring for all patients on ART, as the most accurate available measure of treatment response . This isVirological failure is classified as a Plasma viral load above 1000 copies/ ml based on two consecutive viral load measurements after 3 months, with adherence support. If using dry blood spot technology, a viral load above 3000 copies/ml based on two consecutive viral load measurements after 3 months, with adherence support is also classified as virological failure . The ZimOther studies have shown that comorbidities like having TB on ART, lower baseline weight and drug to drug reactions are associated with virological failure . Being oIn 2014, a new global strategy was launched with the aim to end the AIDS epidemic by 2030. The Joint United Nations Programme on HIV/AIDS (UNAIDS) and partners set ambitious global targets for the year 2020. These include diagnosing 90% of all people living with HIV (PLWHIV), initiating antiretroviral treatment (ART) for 90% of those diagnosed with HIV infection and achieving an undetectable viral load in 90% of those on ART . In viewIn Zimbabwe, viral load testing remains a challenge due to lack of viral load testing machines at hospitals . In HaraThe National Aids Council (NAC) 2017 report revealed that about 35% of the estimated one million people on ARVs are on second line treatment. While having people living with HIV on second line treatment is proving to be expensive for Zimbabwe, quite a sizeable number are failing this line as well and are being moved to a third line regimen.According to the Zimbabwe Populations Based HIV Impact Assessment (ZIMPHIA - 2016), 87% of those on ART (15–64 years old) are virally suppressed. However, nationally, viral load suppression remains a challenge among adolescents (10–19 years) with viral load suppression of 48.6% among adolescent females and 40.2% among adolescent males being reported . ZimbabwWe conducted a 1:1 unmatched case control study among adolescents on ART in Harare city. A 102 case- control pair was recruited into the study. A case was an adolescent (10-19 years) from Harare city who presented with a viral load more than 1000 copies/ml after at least 12 months on ART in Harare city, from January 2017 to June 2017. A control was an adolescent (10–19 years) from Harare city who presented with viral load below 1000 copies/ml after at least 12 months on ART in Harare city, from January 2017 to June 2017.Beatrice Road Infectious Diseases Hospital (BRIDH) and Wilkins hospital being the main infectious diseases’ hospitals that manage both first and second line clients on ART in Harare city, were purposively selected. The OI/ART VL tests register was used as the sampling frame. Proportional sampling was done in accordance with the number of adolescents that received VL tests at each facility from January 2017 to June 2017. The entire cohort had a total of 392 adolescents and all received their due VL tests. BRIDH had 200 adolescents while Wilkins had 192. Fifty two cases were randomly selected from BRIDH viral load test register into the study, and 50 cases were also randomly selected from Wilkins VL test register. Random selection of cases was done using computer statistical randomizer that generated 102 numbers randomly after each unit had been sequentially numbered on the sampling frame. Controls from the same hospitals and age range were randomly selected using computer generated numbers.Five key informants were purposively selected according to their knowledge on HIV/AIDS programming, management and performance monitoring and evaluation.We used the structured pre tested interviewer-administered questionnaires to collect data. The questionnaires were designed in English language then translated into Shona language which is the local language for this population. Review of the hospital medical records provided baseline pre-ART data before initiation of HIV treatment as well as current treatment and clinical status. Cases and controls were interviewed either on their review dates or when they would have come for their support group meetings which were done on Thursdays, after every 2 weeks. Those who did not belong to any support group and did not come for review during study time, were interviewed at their homes. Contact details were found in the VL tests registers. Adherence was objectively assessed by doing a physical pill count of dose units taken between the supply date and the review date. Good adherence was defined as adherence necessary to achieve full and durable viral suppression, thus taking (= or > 95%) of the pills. Non adherence was defined as taking < 95% of the pills.An interview guide for key informants was used to elicit information on the Harare city’s HIV program. Key informants interviews were also used to triangulate data collected from the clients on health service related factors.p-value of < 0.05 was deemed statistically significant in this analysis. Multivariate analysis by way of a stepwise forward logistic regression model was performed on significant variables that were found in bivariate analysis.Data were analysed using Epi Info 7 to generate frequencies, means proportions and odds ratios. Using 95% confidence interval, we performed a bivariate analysis to assess associations between different exposures and virological failure. A Permission to conduct the study was obtained from the Harare city ethical review board, Joint Research Ethical Committee (Ref: JREC/164/16), and Medical Research Council of Zimbabwe (Ref: MRCZ/ B/1314). Written informed consent was sought and obtained from study participants who were 18 years and above. For participants aged below 18 years assent was obtained and written informed consent was obtained from their parents or guardians. Confidentiality was assured and maintained through no use of names on questionnaires and keeping questionnaires under lock and key.The dependent variable (outcome of interest) was virological failure. It was defined as a plasma viral load of > 1000copies/ ml blood.Independent variables included the demographic characteristics of the study participants. Some of these include the age (Number of completed years), marital status (married or not married), gender , alcohol intake ), residence was categorical (high/medium/low), caregiver HIV status (positive or negative), caregiver employment status (employed or not employed), disclosure status (disclosed HIV status or not), WHO staging (WHO stage at ART initiation at ART initiation), CD4 count (CD4 count at ART initiation at ART initiation), Correct and consistent use of condoms, chronic illness (having a chronic disease or not), second line treatment or not), and adherence (poor< 95% or good adherence > 95%).The study recruited 102 case–control pairs giving us a recruitment rate of 100%  were five times more likely to develop virological failure as compared to those who started ART with CD4 > 350 cells/μl  were less likely to have virological failure as compared to the first liners. Adolescents on ART for less than 18 months were less likely to develop virological failure compared to those with more than 18 months on ART . ART regimen was also associated with virological failure. Being on TDF +3TC + EFV was protective.Multivariate analysis by way of a stepwise forward logistic regression model was performed on significant variables that were found in bivariate analysis Table . Poor adThe study investigated the factors associated with virological failure among adolescents on ART and revealed that poor adherence to treatment, taking alcohol and non-disclosure of HIV status increased the odds of virological failure. The less likelihood factors included having a support group and being on 2nd line treatment. Correct and consistent use of a condom was a protective factor.The study demonstrated that adolescents who were not adhering to ART were less likely to achieve viral suppression as compared to those who were adhering to ART. This is biologically plausible as poor adherence result in drug dosages below the level necessary to produce a therapeutic effect, thereby enabling development of drug resistance . Our resIn this study, adolescents who reported being on other medications apart from ART were more likely to develop virological failure as compared to those who were on ART only. Although the study did not assess why adolescents on other medications were more likely to develop virological failure, this could be due to several explanations like by the pill burden that would be encountered by adolescents that would be on other medications. Other studies demonstrated that pill burden among adolescents is associated with poor adherence . This co3). This shows delay in ART initiation among adolescents. Chimbetete et al., 2011 also found that patients initiated on ART after developing AIDS related illness (WHO stage 3 & 4), and those who had low baseline CD4 counts had higher risk of treatment failure as compared to those in WHO stage 1 or 2 and those with high CD4 [The odds of virological failure increased with disease severity at ART initiation. Virologic failure was more likely in advanced disease (WHO stage 3 and 4, CD4 < 350 cells/mmhigh CD4 . Howeverhigh CD4 , 20.The independent association of alcohol consumption and virological failure is not surprising since alcohol use among adolescents has been associated with lower treatment adherence, disease progression and failed viral suppression. One study by Matare et al., 2014 examined the association of alcohol with viral suppression and found that those who consumed alcohol were more likely to develop virological failure compared to those who did not . In anotDisclosure has been shown to be a protective factor as far as viral suppression is concerned. This could be due to the association between disclosure of HIV status and adherence. Some studies have found delayed or nondisclosure of HIV status to be associated with virological failure . AttentiIn this study, belonging to a support group was a less likelihood factor. Ayer et al., 2016 also found that belonging to a support group was associated with viral suppression . Our stuThose who were on second line treatment were less likely to develop virological failure as compared to those on first line treatment regimen. However, the additional counselling among adolescents on second-line treatment might have somewhat biased this study finding. Those who are on second line treatment receive enhanced adherence unlike those on first line treatment.The strengths of this study included the triangulation of information given by the study participants with the information included in the clinical records. However, our study had some limitations. The Information provided on exposure differed between cases and controls. Cases could accurately recall past exposures better than controls resulting in recall bias. However some of the given information were verified with medical records. Some of the questions included in the questionnaires were sensitive and this could have introduced social desirability bias. Also adherence was assessed using pill count method which not a perfect method of assessing adherence. Despite these shortcomings, this study fills a gap in research on factors associated with virological failure in Harare city, Zimbabwe.The study demonstrated that poor adherence was strongly associated with virological failure among adolescents on ART in Harare city. Although consistent and correct use of condoms, second line ART regimens and belonging to a support group were protective against virological failure, taking alcohol and non-disclosure also increased the odds of virological failure. Following this, findings of this study were used by Harare city to lobby for supply of more ARV drugs to maintain the 3 months minimum stock from the ministry of health. The program manager also used these findings to improve on adolescent friendly services through rehabilitation of one of the two non-functional adolescent treatment corners that were in place. An awareness campaign on ART adherence and behavioral change was also conducted. Based on these findings support should focus on behavior change and strengthening of peer to peer projects to help address issues related to disclosure and adherence. Further operational research should aim to define other components of effective adherence support for adolescents with virological failure.


HIV viral load (VL) of people living with HIV (PLHIV) on anti‐retroviral therapy (ART) facilitates intensive adherence counselling and faster ART regimen switch when treatment failure is indicated. Yet standard VL‐testing in centralized laboratories can be time‐intensive and logistically difficult in low‐resource settings. This paper evaluates the outcomes of the first four years of routine VL‐monitoring using Point‐of‐Care technology, implemented by Médecins Sans Frontières (MSF) in rural clinics in Malawi.Routinely monitoring the VL‐ testing between 2013 and 2017 in four decentralized ART‐clinics and the district hospital in Chiradzulu, Malawi. We assessed VL‐testing coverage and the treatment failure cascade (from suspected failure (first VL>1000 copies/mL) to VL suppression post regimen switch). We used descriptive statistics and multivariate logistic regression to assess factors associated with suspected failure.We conducted a retrospective cohort analysis of patients eligible for routine VL‐testing coverage was 85% and VL suppression was found in 89% of those tested. In the decentralized clinics, 88% of test results were reviewed on the same day as blood collection, whereas in the district hospital the median turnaround‐time for results was 85 days. Among first‐line ART patients with suspected failure (N = 1544), 30% suppressed (VL<1000 copies/mL), 35% were treatment failures (confirmed by subsequent VL‐testing) and 35% had incomplete VL follow‐up. Among treatment failures, 80% (N = 540) were switched to a second‐line regimen, with a higher switching rate in the decentralized clinics than in the district hospital  and a shorter median time‐to‐switch . Similarly, the post‐switch VL‐testing rate was markedly higher in the decentralized clinics . Overall, 79% of patients with a post‐switch VL‐test were suppressed.Among 21,400 eligible patients, POC‐based VL‐testing. Nevertheless, gaps were identified along all steps of the failure cascade. Regular staff training, continuous monitoring and creating demand are essential to the success of routine VL‐testing.Viral load testing at the point‐of‐care in Chiradzulu, Malawi achieved high coverage and good drug regimen switch rates among those identified as treatment failures. In decentralized clinics, same‐day test results and shorter time‐to‐switch illustrated the game‐changing potential of  It is, to our knowledge, the first published report of outcomes of routine viral load monitoring from real‐world clinical sites in sub‐Saharan Africa using a POC‐based approach.22.1et al. MSF introduced the SAMBA I technology  at point‐of‐care in decentralized clinics and in the district hospital (DHOS) of the rural, resource‐limited Chiradzulu District, in southern Malawi  2.2This was a retrospective, descriptive analysis of an ART patient cohort accessing HIV VL‐testing for the first‐time using SAMBA I VL. The analysis included all VL‐eligible patients . “Date of VL‐eligibility” was the date of the first scheduled visit in the study period. Patients with prior VL test results or on third‐line regimens were excluded.2.3Plasma was prepared from venous blood and tested with SAMBA I VL according to the manufacturer's instructions. The 2011 MoH guidelines WHO defines treatment failure as two sequential VL ≥1000 copies/mL with enhanced adherence support provided between tests 2.4We defined “VL‐coverage” as the proportion of VL‐eligible patients receiving a first VL test during the study period. Result turnaround‐time (TAT) was the number of days between blood collection and test result review by clinicians with a patient. For the failure cascade, we reported the number and proportion of suspected failure patients: (1) receiving follow‐up VL tests, (2) failing treatment, (3) switching regimens and (4) receiving post‐switch testing within 18 months of a first VL‐test. Failure cascade sensitivity analysis included patients whose first VL‐test was <18 months from the date of analysis censorship. Retention in care was assessed 18 months after suspected failure and is defined as those alive, not transferred, or not missing a scheduled appointment by >2 months as per MOH definition of lost‐to‐follow‐up 2.5Patient‐level data were captured on paper forms at each visit  and entered into an individual patient follow‐up database  Descriptive analyses used medians with interquartile ranges (IQR) or counts with proportions. Pearson chi‐squared or Kruskall Wallis tests assessed differences in patient characteristics at date VL‐eligible  and outcomes. Data unavailable in the patient database were reported as missing. Analyses were conducted using STATA v.13 2.6Routine VL‐monitoring using SAMBA I POC‐VL obtained the approval and support of the Malawian Ministry of Health. Implementation and retrospective analyses were approved by the MSF Ethics Review Board as part of an overall multi‐country UNITAID‐funded proposal. A waiver from individual informed consent was granted for the collection and analysis of routine monitoring data. Unique alphanumeric codes were used to identify individual patients, and no patient identifiers were included in the analysis database.3In total, 22,168 VL‐eligible patients were identified, of whom 21,400 (97%) were included in the analysis . VL coverage was similar among first and second‐line patients, but higher coverage was found for those on ART ≥24 months. Children and younger adults had slightly lower coverage than those ≥40 years old. Coverage was lowest among patients with no CD4, of which 44% (n = 1029) initiated ART under the treatment‐for‐all‐policy (after June 2016). This sub‐group was followed for a median of 2.8 months [IQR: 0.9‐5.6] between VL‐eligibility and last visit and had 40% VL‐coverage.During the study period, 85%  of eligible patients received a POC‐VL test. Namitambo and Bilal clinics had 89% VL coverage, whereas the DHOS coverage was 82%, similar to Mbulumbuzi and Namadzi clinics that implemented POC‐VL later  were identified as virally suppressed (VL < 1000 copies/mL) and 11% as suspected failures (VL ≥ 1000 copies/mL). Factors associated with suspected failure were longer duration on ART, male, younger age (children and young adults) and immune‐suppression Table .3.2p < 0.01), where the median TAT was 85 days [IQR: 83‐93].Turnaround‐time could be analysed for 97% of tests requested in the decentralized clinics and for 68% of tests at DHOS Figure . Missing3.3p < 0.01) .Among first‐line suspected failures (n = 1544), 83% received a follow‐up test, of whom 29% (376/1277) had a VL < 1000 copies/mL (“suppressed”). Among those who had VL ≥ 1000 copies/mL on their follow‐up test (considered treatment failures per WHO definition) 70% (633/901) received a third test per the adapted MOH guidelines. Among those with follow‐up tests, 15% (93/633) were suppressed. Of those failing treatment (per adapted MOH guidelines), 80% (434/540) were switched to second‐line ART. A further 234 were switched prior to completing the failure algorithm; 54 were switched after the initial VL ≥ 1000, and 180 were switched after their first follow‐up test. Of all patients who switched, 52% (347/668) had a VL test post‐switch, among whom 79% (275/347) were suppressed. Switching rates and post‐switch VL‐testing coverage were significantly higher in the decentralized clinics compared to DHOS  Figure . RetentiAmong second‐line patients with an initial VL ≥ 1000 copies/mL, 76% (37/49) received a follow‐up test, of which 46% (17/37) suppressed. Among the non‐suppressed, 70% (14/20) received a third test and 64% (9/14) remained unsuppressed. None of the nine treatment failures were switched to a third‐line regimen during the study period due to limited access to resistance testing and third‐line ART. Both have since been introduced in the Chiradzulu cohort by MSF for second‐line failure patients.Among all suspected failures, the median time between first and follow‐up VL‐tests or regimen switch was significantly shorter in the decentralized clinics Table . As a re4This analysis presents the first programmatic outcomes of routine VL‐monitoring using a POC‐based approach in Malawi. In four years of implementation, encouraging VL‐testing coverage and efficient TATs were achieved, especially in decentralized clinics. Notably, despite no prior access to routine VL‐monitoring, 89% of patients tested had VL < 1000 copies/mL, nearly meeting the UNAIDS 90% viral suppression target for patients on ART Previous estimates paint a variable picture of the success of expanding VL‐testing in sub‐Saharan Africa, with 10%‐95% early uptake in national programmes , and 40‐86% coverage achieved after 1 to 2 years of VL‐implementation in MSF supported facilities Even when high VL‐testing coverage is achieved, good HIV treatment outcomes will remain out of reach if effective follow‐up of suspected failure patients does not occur. Our follow‐up testing rate among suspected failures (83%) was similar to recent findings in Lesotho (85%) and notably higher than rates reported previously in Swaziland (70%), Malawi (30%), Mozambique 35%) or Siaya County, Kenya (35%), % or SiayPrevious reports from sub‐Saharan African settings have consistently shown low and delayed switching from first‐ to second‐line ART (even when VL‐monitoring is present), which have been linked to poorer treatment outcomes, increased mortality and the risk of the development and transmission of resistance It remains critical to increase VL‐uptake and to ensure efficient use of VL results, including timely results and empowerment of clinicians and patients to make use of VL results 4.1Our analysis used real‐life programmatic data from a largely decentralized HIV programme, with a mature ART cohort that is typical of a high prevalence, sub‐Saharan African setting. We used a tailored data collection system that allowed reporting on every step of the VL‐testing cascade. Yet some limitations are present. Six percent of VL tests had to be excluded, possibly somewhat underestimating coverage and switching rates. Introduction to POC‐VL was staggered over a 15‐month period. Parallel introduction may have achieved higher coverage. The routine monitoring database did not capture EAC and we cannot describe the role of counselling on VL cascade outcomes. Longer term outcomes of suppressed patients, the impact of continuous VL‐monitoring on suppression rates, as well as further description of the feasibility of POC VL‐ testing are of interest but were outside the scope of our report. Successes and challenges experienced by MSF during routine VL implementation  have been reported elsewhere 5Our findings indicate that routine point‐of‐care VL‐monitoring can achieve high testing coverage, same day results in decentralized clinics, and comparably good switching rates for first‐line failures. However, gaps at every step in the VL‐testing cascade remain a concern, including incomplete failure follow‐up and regimen switching. Close monitoring is recommended to identify potential gaps and directly guide programmes. VL technologies used at point‐of‐care can play a key role in bridging the gaps in access to VL‐monitoring and effective regimen switch in resource‐limited settings.The authors declare that they have no competing interests.SN, EP and BS designed the monitoring and analysis plan; MG and ES participated in the development of the monitoring and analysis plan; MG initiated and was the laboratory lead for POC‐VL implementation. AR supervised electronic data capture. MG, LW, JW and AR monitored and assured data quality; SN and EP provided technical support to monitoring and data quality; SN conducted the data management and undertook the analysis; SN and BS wrote the initial draft of the manuscript; All authors interpreted the findings and critically reviewed the manuscript and provided comments which were incorporated into subsequent drafts by SN and BS.Table S1. Association between patient characteristics at eligibility and suspected failureTable S2. The failure cascade among first‐line ART patients with suspected failureClick here for additional data file.


Residual HIV-1 replication among individuals under antiretroviral therapy (ART) relates to HIV micro-inflammation.To determine the levels of residual HIV replication markers among distinct subgroups of antiretroviral-treated individuals.One hundred sixteen patients were distributed into 5 treatment groups: first-line suppressive ART with a non-nucleoside analog reverse-transcriptase inhibitor (NNRTI) (n = 26), first-line suppressive ART with boosted protease inhibitors (PI-r) (n = 25), salvage therapy using PI-r (n = 27), salvage therapy with PI-r and raltegravir (n = 22) and virologic failure (n = 16). Episomal and total DNA quantitation was evaluated. ELISA was used for HIV antibody and LPS quantitation.Episomal DNA was positive in 26% to 38% of individuals under suppressive ART, and it was higher among individuals experiencing ART virologic failure (p = 0.04). The HIV proviral load was higher among patients with detectable episomal DNA (p = 0.01). Individuals receiving initial PI-r treatment presented lower HIV antibody (p = 0.027) and LPS (p = 0.029) levels than individuals receiving NNRTI. There was a negative correlation between episomal DNA quantitation and the duration of suppressive ART (p = 0.04), CD4+ T-cell count (p = 0.08), and CD8+ T-cell count (p = 0.07).Residual HIV replication has been inferred among individuals under suppressive ART according to episomal DNA detection. Residual replication may decrease with longer periods of suppressive ART and higher levels of CD4+ and CD8+ T cells. The relationship between episomal DNA and total DNA suggests there is a replenishment of the proviral reservoir with impacts on HIV persistence. Lower antibody and LPS levels among patients with initial PI-r ART suggest these regimens may more effectively suppress HIV and have a higher capacity to decrease the HIV antigenic component. The deleterious effects of HIV are directly related to viral replication, which leads to inflammatory processes, such as the activation of CD4+ and CD8+ T lymphocytes . MaintaiPatients were chosen between 2011 to 2013 in São Paulo Brazil according to their current antiretroviral treatment . Individ1) patients treated with two nucleoside-analogue reverse-transcriptase inhibitors (NRTI) associated with the non-nucleoside analog reverse-transcriptase inhibitors (NNRTI) Efavirenz or Nevirapine as the first ART regimen; (2) patients treated with two NRTIs and a protease inhibitor boosted with ritonavir (PI-r) as the first ART regimen; (3) patients on salvage therapy with two NRTIs and a PI-r; (4) patients under salvage therapy containing two NRTIs, PI-r and the integrase inhibitor raltegravir; and (5) patients under antiretroviral virologic failure with the confirmed presence of HIV ART resistant strains. Peripheral blood samples were collected, and clinical data on the patients were analyzed, including CD4+ and CD8+ T-cell counts, the duration of treatment with undetectable viral loads and the number of ART schemes previously used by the patient.One hundred sixteen patients were allocated to five treatment subgroups as follows:  isolated using density gradient centrifugation were extracted using a QIAprep Spin Miniprep commercial kit . After extraction, qPCR amplification was performed in a single round of 45 qPCR cycles to amplify extrachromosomal DNA as previously described , 9. The 6 PBMC .GCCTCAATAAAGCTTGCCTTGA, R626-43 GGGCGCCACTGCTAGAGA and Probe CCAGAGTCACACAACAGACGGGCACA) and 5 μl of extracted DNA. CCR5 was also used to quantify genomes to express the measurements as copies per 106 PBMC  according to the manufacturer’s instructions. Total HIV DNA was qPCR amplified using a mix containing 1x TaqMan Universal PCR Master Mix (Applied Biosystems), 0.4 μM primers/probe  according to the manufacturer’s instructions. The optical density values of the samples were normalized based on the controls  using the spreadsheet available at The quantitation of endotoxin was performed using a Limulus Amebocyte Lysate (LAL) QCL-1000  kit according to the manufacturer’s instructions. The absorbance was determined spectrophotometrically at 405–410 nm. Since this absorbance is in direct proportion to the amount of endotoxin present, the concentration of endotoxin was calculated from a standard curve. The background color of the sample was subtracted.The Statistical Program for the Social Sciences, version 18.0 (SPSS 18.0) was used for data analysis. Descriptive analyses, ANOVA using z-score normalized data, and chi-squared tests, at a confidence level of 5%, were performed.The general patient data including age, gender, CD4+ and CD8+ T-lymphocyte counts, treatment time, number of regimens and number of medications used were compiled and are shown in 2-LTR circles were detected in 39 (34%) of the patients in the study. The treatment group had no effect on the quantitation of episomal HIV DNA  = 1.263, p = 0.289). The prevalence of detectable 2-LTR (n = 39) was not different between the groups  = 1.014, p = 0.414).There was no difference in the quantitation of 2-LTR circles among groups with first treatment  = 1.429, p = 0.23, 2 (3) = 5.412, p = 0.248). Comparing the number of positive episomal DNA samples between the subjects with virologic suppression (30%) and individuals experiencing virologic failure (56%), there was an increase in the number of episomal DNA-positive samples in the failure group (χ2 (3) = 4.259, p = 0.039, We then transformed episomal DNA quantitation into a categorical variable for detection and named samples LTR positive when detection was possible and LTR negative when there was no detection. Based on this categorization, we performed a chi-square test. The results showed no statistically significant association between the received treatment and the detection of circular DNA  of the patients included in the study. An ANOVA tests showed no differences between the treatment groups for quantitation of total HIV DNA  = 2.015, p = 0.098; There was no statistical significance between total HIV DNA and the other tested variables.In this test, we considered samples with normalized optical densities (ODn) higher or equal to 0.8 as positive.. ANOVA showed no differences in the HIV antibody levels between the groups  = 1.675, p = 0.161, 2 (1) = 9.600, p = 0.007) compared to the first treatment group using NNRTI as well as an increase in positivity when compared to salvage therapy with PI (χ2 (1) = 4.038, p = 0.044) (2 (1) = 0.360, p = 0.34) nor any difference when comparing groups with or without virologic failure (χ2 (1) = 1.945, p = 0.13).Considering ODn as a categorical variable in which positive samples had an ODn ≥ 0.8, there was a decreased number of positive samples in the first treatment group using PI-r (χ= 0.044) . There w2 (1) = 1.889, p = 0.119) or with the episomal DNA quantitation  = 0.112, P = 0.738). Patients with positive antibody quantitation showed slightly higher HIV total DNA  = 2.787, p = 0.09).Positive antibody quantitation was not associated with the positivity of episomal DNA  = 2.947, p = 0.029, Spearman correlation tests were performed only with samples in which episomal DNA was detected. There was a negative correlation between the quantitation of episomal DNA and the CD8+ T-cell count  and the CD4+ T-cell count , LPS quantitation in plasma  and treatment time with an undetectable viral load .Spearman correlation between total HIV DNA showed positive correlation with episomal DNA quantitation , and also a negative correlation with CD8+ T-cell count .As mentioned before, antiretroviral treatment is not fully suppressive in all individuals, as shown by the detection of viremia in individuals evaluated with ultrasensitive viral load assays  or withtFurthermore, continuous suppressive therapy is able to decrease the number of latent HIV infected cells over time , bringinTo learn more about residual HIV-1 replication among individuals under ART, we used different surrogate markers of HIV replication. The presence and quantitation of episomal HIV DNA has been considered one accurate marker to infer active HIV replication and its entrance into the cell environment , 15. TotWe also wanted to investigate the relationship between different HIV ART schemes or strategies. The main questions were: is initial treatment more suppressive when two distinct steps of reverse transcription are inhibited, such as schemes using NRTIs with an NNRTI, or is the inhibition of pre- and post-integration more effective, such as schemes using NRTIs and boosted PI? A number of clinical trials comparing NNRTI with boosted PIs as the second antiretroviral class show one advantage of NNRT, which relies mainly on tolerance and adherence issues, since boosted PI schemes do not present antiretroviral resistance upon failure . The othWe were able to confirm the relationship between HIV-1 replication and the detection of episomal DNA, which was higher among individuals experiencing virologic failure compared to individuals with viral loads below detection, even with the smaller sample size of the virologic failure group.We also detected a negative correlation between episomal DNA quantitation and the time of treatment with undetectable viral loads as well as a negative correlation between episomal DNA and CD8+ T-cell counts. It is conceivable that lower CD8 levels enable HIV-1 viral replication, as has been seen in animal models; the elimination of CD8+ T cells using monoclonal antibodies was associated with the return of detectable viremia in SIV-infected monkeys in spite of the use of suppressive ART . LikewisInterestingly, the levels of total HIV DNA were found to be higher among individuals with evidence of residual HIV replication as inferred by the presence of episomal DNA. This association suggests that the pool of infected cells is being replenished or maintained in association with residual HIV replication.We were not able to detect any differences between episomal or total DNA levels between first-line regimens and successful salvage therapy regimens, nor between NNRTI versus PI-r regimens or salvage therapy using two or three classes . However, the levels of antibodies were lower in first-line PI-r ART compared to the NNRTI group as the number of negative antibody results were higher among the initial PI-r treatment group. Furthermore, the levels of LPS were higher among the NNRTI first-line treatment group compared to the first-line PI-r or other salvage therapy groups that also have a PI-r in the treatment scheme. Notably, the proportion of patients taking tenofovir, abacavir or zidovudine was similar in the PI-r and NNRTI groups . AlthougWe recognize that the retrospective cross-sectional nature of this study may preclude more definite conclusions. The evaluation of only one time point in this group prevents us from understanding the dynamics of these surrogate markers for HIV replication. Unfortunately, we also do not have precise information of length of the HIV infection/diagnosis before treatment initiation or the CD4+ T cells nadir, which could potentially affect the pool size of HIV infected cells and influence other laboratory markers evaluated here. Furthermore, other sensitive assays measuring residual HIV replication, such as cell-associated RNA or inflammatory markers, have not been evaluated here, and the use of PBMCs and not CD4s in order to access the HIV DNA quantitation can make results less accurate.However, we were able to clearly demonstrate that episomal DNA was present in 26% to 38% of individuals with “successful” antiretroviral treatment, thus suggesting that residual HIV replication is occurring despite the scheme analyzed here. We were also able to demonstrate the association of PI-r schemes with lower antibody and LPS levels, which deserves further confirmation to better understand the related mechanisms involved that can explain these findings.S1 TableThe number in brackets indicates the number of patients in each scheme.(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.


Cryptococcal meningitis is most commonly found in HIV-infected patients. In HIV-negative patients, its low incidence can lead to prolonged time to diagnosis. Detailed case reports of chronic cryptococcal meningitis are scarce, but could provide clues for earlier diagnosis in this patient category.Cryptococcus neoformans was cultured from CSF. The patient was treated with the standard antifungal regimen which resulted in resolution of his headaches. In retrospect, the cryptococcal antigen test was already positive on a serum sample from June 2015. Interestingly, post-treatment immunological analysis revealed both a low mannose-binding lectin (MBL) concentration and low naïve CD4 counts.A 60-year old man presented June 2015 with intermittent headaches for several months without any fever. Initial work-up showed a leukocytosis, raised CSF opening pressure and raised leukocytes and protein in the CSF. An MRI revealed leptomeningeal contrast enhancement and cerebellar oedema. While malignancy and various infectious causes were excluded, the patient had a spontaneous clinical and radiological recovery. One year later, the patient returned with complaints of headaches. Also, cerebellar oedema and leptomeningeal contrast enhancement had recurred. Eventually in March 2017, the novel cryptococcal antigen lateral flow assay (CrAg LFA) was positive on CSF, and one colony of We present a patient with cryptococcal meningitis in an HIV-negative patient with low MBL and low naïve CD4 count suffering a chronic relapsing meningo-encephalitis with relatively mild symptoms for around 2 years. In patients with an unexplained meningo-encephalitis such as this case, early performance of CrAg LFA on serum and/or CSF is an inexpensive and rapid method to reduce time-to diagnosis. Cryptococcal meningitis is most often diagnosed in patients infected with HIV, and is considered rare in immunocompetent patients. A recent study in HIV-negative patients with cryptococcal meningitis in China showed that almost 10 % had a delayed time to treatment of > 90 days [2O) and elevated protein (990 mg/L) were detected . Serology was performed which excluded HIV, At his 3- and 9 months follow up visits, the patient was in a very good clinical condition, and MRIs (September 2015 and February 2016) showed a remarkable normalization of previously abnormal findings. Due to the spontaneous remission, no further attempts were made for a definitive diagnosis.However, in August 2016 the patient returned to our outpatient clinic with persisting mild headaches, disorientation and dizziness as well as palpitations. The patient had no pulmonary or skin abnormalities upon physical examination. Neurologic examination did not reveal significant abnormalities, but MRI revealed new pathological contrast enhancement, mostly leptomeningeal. His headaches persisted during subsequent months. Further tests included a PET-scan which still revealed no focal FDG uptake, and an MRI which revealed a slight increase in abnormal meningeal contrast enhancement  [C. neoformans serotype A, mating-type α, which was previously found to be the most common type among Dutch immunocompetent cryptococcosis patients [3/ μl), lymphocyte (1.9 × 103/μl) and CD4 T-cell (760/μl) counts.There was still a leukocytosis and elevated protein concentration in the CSF, but no malignant cells were observed and PCRs and antibody tests for a range of pathogens were negative. However, a new test had just been introduced in our laboratory: the cryptococcal antigen lateral flow assay . This simple and inexpensive test was positive on the CSF and serum, confirming a diagnosis of cryptococcal meningitis. A fungal culture of CSF was performed, which yielded only a single colony, which by MALDI-TOF analysis  was identified to be a  grubii) . Molecul grubii) , revealipatients . The iso6/ml) and normal counts of total T-cells (1.95 × 106/ml), CD4 cells (1.05 × 106/ml) and CD8 cells (0.77 × 106/ml), with a normal CD4/CD8 ratio of 1.4. Memory CD4 count was high (CD45RO+: 0.90 × 106/ml), while the naïve CD4 count was relatively low  of which only 47% CD31+ cells. B-cell count was normal (0.27 × 106/ml) as was the NK cell count (0.48 × 106/ml).Retrospective analysis on the only available sample, serum from June 2015, resulted in a positive CrAg LFA test which uniquely demonstrates that the patient had a chronic relapsing pattern of cryptococcal meningitis for approximately 2 years. We treated the patient with an induction course of 2 weeks of L-amphotericin B (3 mg/kg 1x/d) and 5-flucytosine (25 mg/kg 4x/d), after which cryptococcal culture on CSF remained negative [C. neoformans, revealing a diagnostic delay of almost 2 years. Diagnosis was hampered by the relatively mild symptoms and a spontaneous recovery after extensive (negative) diagnostic work-up. In retrospect, the elevated CSF opening pressure in May 2015, combined with a leukocytosis, elevated protein and unexplained leptomeningeal abnormalities on MRI should have raised suspicion of cryptococcal meningitis. However, due to its relative low incidence in immunocompetent patients, cryptococcal meningitis is easily overlooked. In a Chinese study, only 11 out of 126 (9%) HIV-negative patients with cryptococcal meningitis had an underlying immune system disease. In the same study, while diagnostic delays of 30–90 days were common (66 out of 126 patients), only 12 out of 126 (10%) patients had a diagnostic delay > 90 days [We present an HIV-negative patient with a chronically relapsing cryptococcal meningitis caused by The importance of CD4 cells for immunity against cryptococci is known from the extensive experience in HIV-positive patients, while the role of MBL against cryptococcal meningitis is less described. In one study, the concentration of MBL was found to be elevated in CSF of HIV-negative patients with cryptococcal meningitis, while its plasma concentrations were normal . WhetherThe mild symptoms and spontaneous remission have in our case limited the extent of diagnostics performed. Only one colony was eventually cultured, suggesting a low load, and only the recently introduced CrAg LFA has a sensitivity and specificity > 99%, offering superior sensitivity over culture, microscopy and latex agglutination . In thisAdditional file 1 : Table S1. Imaging findings. Table S2. Laboratory findings.


Tenofovir alafenamide (TAF) has similar efficacy compared to tenofovir disoproxil fumarate (TDF), but a less favorable effect on lipids. Aim of this retrospective multicentre study was to evaluate the impact on lipids of switching from rilpivirine (RPV)/ emtricitabine (FTC)/TDF to RPV/FTC/TAF in a cohort of HIV-1 infected patients. Total cholesterol (TC), high density lipoproteins (HDL) and low density lipoproteins (LDL) were compared at the moment of the switch and at the first following evaluation, by using paired t-test. Overall, 573 patients were considered, 99% with HIV-RNA <50 copies/ml, with mean age of 49.7 (±0.4) years and median 13.4 (6.9–22.5) years of HIV infection. In the study population with available data , mean TC changed from 173 ±1.7 to 188 ±1.8 mg/dl; mean HDL from 46 ±0.7 to 51± 0.7 mg/dl; mean LDL from 111 ±1.5 to 120 ±1.8 mg/dl . Neither LDL/HDL nor TC/HDL ratio changed significantly, with LDL/HDL from 2.6 ±0.5 to 2.5 ±0.5 (p = 0.12) and TC/HDL from 4.0 ±0.6 to 3.9 ±0.6 (p = 0.11). In patients with baseline diagnosis of hypercholesterolemia , there was no significant change in TC  or LDL , while HDL increased from 51 ±1.6 to 55 ±1.7 mg/dl (p<0.0001) and both LDL/HDL and TC/HDL ratio decreased significantly, from 3.2±0.1 to 3.0 ±0.1 (p = 0.025) and from 4.7±0.1 to 4.4 ±0.1 (p = 0.004). In this real life study, a slight increase in lipids was found after switching from RPV/FTC/TDF to RPV/FTC/TAF, but these results were not confirmed in people with hypercholesterolemia, in which lipids did not change and LDL/HDL and TC/HDL ratio decreased. Tenofovir disoproxil fumarate (TDF) has demonstrated high efficacy in all stages of HIV infection and in different drug combination regimens . However3.This is a retrospective, observational, multicentre study, conducted in two Infectious Disease Centres in Northern Italy, ASST Papa Giovanni XXIII Hospital in Bergamo and Policlinico S. Martino Hospital in Genoa. Data for Policlinico S. Martino were retrieved from MedInfo, an online database for anonymous and automatic data collection . Data frBaseline was considered the day of the switch or the nearest blood exam preceding that date. The second timepoint was the first available evaluation immediately successive to the switch. Repeated evaluation performed after less than 6 weeks were excluded. Missing LDL were calculated with Friedewald equation . HIV-1 R3).Continue variables were expressed as mean  or median , while categorical variables were expressed as frequencies. At baseline, a comparison between patients with or without HC was performed using unpaired two-samples t-test for variables with normal distribution  and by using Mann-Whitney U test for skewed variables . Categorical variable were compared at baseline between non-HC and HC patients by Chi squared test  or by Fisher’s exacts test  were subsequently compared in the same subjects at baseline and follow up through paired t-test, while data with skewed distribution  were compared using paired samples Wilcoxon test. Changes in TC, LDL, HDL, LDL/HDL and TC/HDL were compared in patients with and without HC by using unpaired two-samples t-test, while changes of TG were compared in patients with or without HT by using Mann-Whitney U test.A linear regression model was used to evaluate correlations between baseline values of TC, LDL, HDL and TG and their changes at follow up, that were expressed with regression coefficients, R, and 95% Confidence Intervals, 95%CI. Chi squared test was used to compare the frequencies of HC and HT before and after the switch.All data were collected from December 2017 to April 2018. All patients followed in both Policlinico S. Martino Hospital and ASST Papa Giovanni XXIII Hospital signed an informed consent form in which they agreed use of their clinical data, in anonymous form, for scientific purposes. The use of the Ligurian HIV Network database for scientific purposes was approved by the Ligurian Ethics Committee . The study has been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments and in accordance with Italian national laws.3, and HIV-RNA was < 50 copies/ml in 99.5%. The general characteristics of the study population are given in Overall, 573 patients had switched from RPV/FTC/TDF to RPV/FTC/TAF, of whom 145 (25%) were females. Patients had mean age of 49.7 (±0.4) years and a history of median 13.4 (6.9–22.5) years of HIV infection. Risk factors for HIV acquisition were sexual intercourse in 374 (65%) patients , intravenous drug use in 181 (32%) and other/unknown factors in 18 (3%). In the whole population who switched from RPV/FTC/TDF to RPV/FTC/TAF, baseline mean CD4 were 777 ±13.7 cells/mm3, p = 0.4 and CD8 from 920 ±19.0 to 916 ±20.0 cells/mm3, p = 0.6, respectively), mean CD4/CD8 ratio slightly increased . When limiting the analysis to patients with baseline CD4<500 cells/mm3 , both CD4 and CD8 increased significantly from 368 ±9.2 to 412 ±12.8 cells/mm3 (p<0.0001) and, from 747 ±35.5 to 787 ± 39.5 cells/mm3, p = 0.037, respectively. CD4/CD8 ratio increased slightly, but significantly, in this group, from mean 0.6 ±0.03 to 0.7 ±0.04, p = 0.038.After a median follow up of 12 (8–24) weeks, although mean CD4 and CD8 remained stable, (CD4 from 777 ±13.7 to 787 ±14.5 cells/mmThree patients (0.5%) with baseline HIV-RNA >50 copies/mL  achieved HIV-RNA < 50 copies/mL at follow up. Conversely, nine patients (1.5%) with baseline undetectable viremia had HIV-RNA >50 copies/mL at follow up .In the same time frame the serum creatinine levels slightly but significantly decreased, from 0.96 (± 0.01) to 0.92 (± 0.01) mg/dL, p<0.0001.The evaluation of TC at both baseline and follow up was available for 431 out of the 573 patients (75%), HDL for 426 (74%), LDL for 423 (74%), TG for 430 (75%). At baseline, 45 patients were on statin therapy, and no patient added or stopped a lipid-lowering agent during the observation period. All lipids increased significantly : mean TCDuring the study period, the proportions of subjects with HC and HT increased, the first one from 20.1 to 36.4% (p<0.0001) and the second from 11.4 to 13.0% (p<0.0001).Patients who developed HC had baseline TC levels slightly higher compared to patients who maintained normal TC levels .When analyzing separately patients with baseline diagnosis of hypercholesterolemia , the change in TC and LDL resulted significantly different from that of other patients , p<0.0001 for both, Both LDL/HDL ratio  and TC/HDL ratio  reduced significantly in patients with HC, and the reduction of both was more marked than that seen in other patients , while LDL/HDL ratio  and TC/HDL ratio  did not change significantly.The variation in TC resulted inversely correlated to baseline TC value  did not experience significant change in TG levels during the study period, from median 238.5 (215–310) mg/dl to 212 (163–292) mg/dl, p = 0.088. TG trend was opposite to that seen in non-HT patents, with median -25  mg/dl in HT vs. + 0  mg/dl in non-HT patients Click here for additional data file.