Early combination antiretroviral therapy (cART), as recommended in WHO’s universal test-and-treat (UTT) policy, is associated with improved linkage to care, retention, and virologic suppression in controlled studies. We aimed to describe UTT uptake and effect on twelve-month non-retention and initial virologic non-suppression (VnS) among HIV infected adults starting cART in routine HIV program in Kenya. Individual-level HIV service delivery data from 38 health facilities, each representing 38 of the 47 counties in Kenya were analysed. Adults (>15 years) initiating cART between the second-half of 2015 (2015HY2) and the first-half of 2018 (2018HY1) were followed up for twelve months. UTT was defined based on time from an HIV diagnosis to cART initiation and was categorized as same-day, 1–14 days, 15–90 days, and 91+ days. Non-retention was defined as individuals lost-to-follow-up or reported dead by the end of the follow up period. Initial VnS was defined based on the first available viral load test with >400 copies/ml. Hierarchical mixed-effects survival and generalised linear regression models were used to assess the effect of UTT on non-retention and VnS, respectively. Of 8592 individuals analysed, majority (n = 5864 [68.2%]) were female. Same-day HIV diagnosis and cART initiation increased from 15.3% (2015HY2) to 52.2% (2018HY1). The overall non-retention rate was 2.8 (95% CI: 2.6–2.9) per 100 person-months. When compared to individuals initiated cART 91+ days after a HIV diagnosis, those initiated cART on the same day of a HIV diagnosis had the highest rate of non-retention . Of those included in the analysis, 5986 (69.6%) had a first viral load test done at a median of 6.3  months after cART initiation. Of these, 835 (13.9%) had VnS. There was no association between UTT and VnS . Our findings demonstrate substantial uptake of the UTT policy but poor twelve-month retention and lack of an association with initial VnS from routine HIV settings in Kenya. These findings warrant consideration for multi-pronged program interventions alongside UTT policy for maximum intended benefits in Kenya. Benefits of early combination antiretroviral therapy (cART) as a public health intervention in the management of HIV infection are indisputable. Early cART has been associated with reduced HIV associated morbidity and mortality –4. With If well implemented, the UTT policy may play a pivotal role in attaining the UNAIDS 95-95-95 targets toward ending the epidemic by 2030 . By mid-A pooled meta-analysis of four randomized controlled trials (RCTs) reported increased virologic suppression and improved 12-months retention amongst individuals on rapid cART initiation (defined as cART initiation within 14 days of HIV diagnosis) . SimilarWhile data from controlled clinical trial settings report better early cART uptake, improved retention and higher virologic suppression amongst individuals started on immediate cART compared to delayed cART, evidence from observational studies are conflicting. A pooled meta-analysis of eleven observational cohorts reported a tendency towards increased risk of being lost to follow up (LTFU) and a decreased likelihood of virologic suppression amongst individuals on rapid or early cART . FurtherImportantly, there is a dearth of evidence to describe uptake and effect of early cART on retention and virologic suppression in routine programmatic settings from LMIC. Data from 32 rural and urban facilities from a district in Malawi reported 6% higher 12-month retention after the introduction of UTT compared to the pre-UTT period . ConversThus, while early cART has been shown to improve retention and virologic suppression in controlled clinical trials, evidence from observational studies are conflicting. Much less is known about the uptake of UTT and its effect on retention and virologic suppression in routine ‘real life’ program settings. We aimed to describe the uptake and effect of UTT on twelve-month retention and initial virologic suppression amongst HIV infected individuals starting cART in a routine HIV program setting in Kenya.A longitudinal analysis of data archived at the national data warehouse (NDW) was done. In brief, the NDW is a repository of individual-level routine HIV program data hosted at the National AIDS and STI Control Program (NASCOP) site in Nairobi, Kenya. The NDW infrastructure consists of electronic records stemming from health facilities offering HIV care and treatment services in the country and documenting the same in electronic medical record (EMR) systems. Routinely collected service delivery data from EMR systems are periodically auto-extracted and uploaded onto the NDW. Data uploaded onto the NDW undergoes de-duplication, de-identification and generation of a patient key value identifier using a data warehouse application programming interphase (DWAPI). By the end of 2019, the NDW hosted individual level longitudinal data from ~1.7 million HIV-infected individuals ever enrolled into an EMR system from 1,209 facilities covering 44 of the 47 counties in Kenya.In Kenya, the UTT policy was implemented from July 2016. The policy recommends initiation of cART for all HIV-infected individuals as soon as possible, but preferably within two weeks of an HIV diagnosis. For the purpose of this analysis, data from HIV infected adults  starting cART between July 2015 –June 2018 were considered eligible. Individuals starting cART during the year preceding UTT implementation were included in the analysis to serve as a reference population. All individuals were followed up for 12-months after cART initiation.While routine service delivery data holds tremendous potential towards assessing impact of programmatic interventions in real-life settings, an innate challenge includes incomplete and/or missing data. For this reason, a convenient sampling approach was used. In brief, of the 1209 facilities transmitting data to the NDW, we sampled one facility from each of the 47 counties in Kenya based on the following criteria: (i) facilities with >50 and <1000 individuals starting cART during the study period (to control for under- or over-representation of the study population at the county level), and (ii) facilities that uploaded EMR data to the NDW after June 2019 , and (iii) facilities with the lowest proportion of individuals with missing HIV diagnosis date and viral load test . Thirty-eight facilities, representing 38 counties, were eligible . All indUptake of UTT was defined as time from the date of an HIV positive diagnosis to the date of cART initiation, categorized as follows: same day, 1–14 days, 15–90 days and 91+ days. Non-retention was defined as individuals who were either reported dead or determined LTFU by the end of the twelve-months follow up period. LTFU was defined as individuals missing a clinic visit more than 3 months after their last clinic appointment date. Individuals who transferred care to other facilities were included in the analysis and follow-up time censored at the last clinic visit date before the transfer. Initial virologic non-suppression (VnS) was determined based on the first available viral load test done within 12-months of cART initiation and defined as individuals with HIV RNA of >400 copies/ml.Other indicators included gender, age at cART initiation, initial ART regimen, baseline CD4 T-cell count and calendar half-year of cART initiation. Initial ART regimen was defined based on antiretroviral drugs prescribed at the date of cART initiation. Baseline CD4 T-cell count was determined based on documented results from tests done within 6 months prior to cART initiation. Calendar half-year (HY) of cART initiation was defined based on the date of cART initiation and was categorized as follows: Jul-Dec 2015 , Jan-Jun 2016 , Jul-Dec 2016 , Jan-Jun 2017 , Jul-Dec 2017  and Jan-Jun 2018 .Descriptive statistics were used to describe the study population. Proportion  of UTT uptake, non-retention and VnS were presented. Because same-day HIV diagnosis and cART initiation was not a rare endpoint, univariable and multivariable generalized linear models (glm) were to identify factors associated with UTT uptake. Hierarchical mixed effects modeling was also applied to control for within-and-between health facility (and county) variations. Crude and adjusted risk ratios (RR), 95% CIs and p-values were reported.Time-to-event analysis was applied to determine time from cART to non-retention over a 12-months follow up period and was presented using Kaplan Meier survival curves stratified by UTT uptake. Non-retention rates at 12-months were reported per 100 person-months observations (pmo). Univariable and multivariable hierarchical mixed effects survival models were applied to determine the independent effect of UTT on non-retention after controlling for within-and-between health facility (and county) variations. Crude and adjusted hazard ratios (HR), 95% CIs and p-values were reported.The analysis was then restricted to individuals with initial viral load test results . Proportions (95% CI) of individuals with initial VnS stratified by UTT uptake were presented. Similarly, and because VnS was not a rare endpoint, univariable and multivariable hierarchical mixed effects generalized linear models were applied to determine the independent effect of UTT on initial VnS after controlling for within-and-between facility (and county) variations. Crude and adjusted risk ratios (RR), 95% CIs and p-values were reported.This retrospective analysis was considered part of a National HIV program evaluation exercise using routinely collected service delivery data archived at the NDW repository. As such, it was not possible to obtain informed consent from individuals. Rather, ethics approval to use data from the repository and to waive the need for informed consenting was obtained from the Africa Medical Research Foundation (AMREF) Ethics Review Committee, Kenya (AMREF-ESRC P716/2019). The analysis was also reviewed in accordance with the U.S. Centers for Disease Control and Prevention (CDC) human research protection procedures and was determined to be non-research. The investigators did not interact with human subjects or have access to identifiable data or specimens for research purposes. All the data shared for analysis were fully anonymized.3, 10.4% vs. 8.8%) respectively  were adults started on treatment between 2015HY2 and 2018HY1 and 9744 were sampled from facilities that met the eligibility criteria . Of thesectively .Overall, 8592 individuals from 38 facilities representing 38 of the 47 administrative counties in Kenya were included in the analysis. Of these, 1305 (15.2%), 1351 (15.7%), 1862 (21.7), 1318 (15.3%), 1249 (14.5%) and 1507 (17.5%) initiated cART in 2015HY2, 2016HY1, 2016HY2, 2017HY1, 2017HY2 and 2018HY1, respectively. The overall median age at cART initiation was 35.1 (IQR: 28.5–43.5) years. The majority of individuals were female (68.2%) and initiated on an EFV-based first-line regimen (72.6%). As expected, a majority of the participants were missing baseline CD4 T-cell count, increasing from 52.7% in 2015HY2 to 85.6% in 2018HY1 .Overall, 3070 (35.7%) of individuals started cART on the same day of an HIV diagnosis. Same day HIV diagnosis and cART start increased from 15.3% prior to UTT policy implementation in 2015HY2 to 52.2% in 2018HY1. Using the 14-day threshold as per the Kenyan national guidelines, UTT uptake increased from 32.1% in 2015HY2 to 68.4% in 2018HY1 .Individuals started cART in 2018HY1 were three-fold more likely to have same day HIV diagnosis and cART initiation compared to those started cART in 2015HY2 , with the highest jump observed immediately after implementation of the UTT policy in mid-2016 . Female Overall, 8592 individuals contributed 72,815 person-months observation (pmo). Of these, 2004 (23.3%) were either reported dead  or LTFU  after 12-months of follow up, contributing an overall non-retention rate of 2.8 (95% CI: 2.6–2.9) per 100 pmo. Individuals initiated cART on the same day as a HIV diagnosis had the highest non-retention rate (4.0/100 pmo), followed by 1–14 days (2.7/100 pmo), 15–90 days (2.1/100 pmo) and 91+ days (1.9/100 pmo) .When compared to individuals initiated cART 91+ days after a HIV diagnosis, those initiated cART on the same day of a HIV diagnosis had the highest rate of non-retention , followed by those initiated cART 1–14 days after a HIV diagnosis  and those initiated cART 15–90 days after a HIV diagnosis  . Other fOf the 8592 individuals included in the analysis, 5986 (69.6%) had an initial viral load test done over a median of 6.3  months after cART initiation. There were no significant differences in follow up time from cART initiation to initial viral load testing by UTT uptake; same day (6.3 [IQR: 5.7–7.5] months), 1–14 days (6.4 [IQR: 5.8–7.4] months), 15–90 days (6.3 [5.6–7.6] months) and 91+ days (6.2 [4.3–7.7] months). Of these, 835 (13.9%) had an initial viral load >400 copies/ml. Initial VnS for same day, 1–14 days, 15–90 days and 91+ days HIV diagnosis and cART start were 14.1%, 14.3%, 14.4% and 13.2% respectively .There was no association between UTT uptake and initial VnS. Individuals who started cART on the same day as an HIV diagnosis had the same likelihood of VnS compared to those started cART 91+ days after an HIV diagnosis  . FactorsPatterns of UTT uptake and its effect on non-retention and initial VnS were similar in the general population, when compared to those observed from the sampled population. In brief and in the general population, same-day HIV diagnosis and cART start increased between 2015HY2 and 2018HY1, with the highest jump observed immediately after implementation of the UTT policy in mid-2016 . IndividWhile early cART has been shown to improve retention and virologic suppression in controlled clinical trials, much less is known about the uptake of UTT and its effect on retention and virologic suppression in ‘real life’ programmatic settings. Routine national level HIV service delivery data from Kenya suggest commendable uptake of the WHO recommended UTT policy, with a three-fold increased likelihood for same day HIV diagnosis and cART initiation over two calendar years of implementation. These findings are consistent with reports suggesting a strong impact of the UTT policy on increased uptake of early cART in Kenya and other LMIC , 27. HowFirst, our data demonstrates that the steady increase in UTT uptake over calendar half-years was associated with an increase in non-retention rates over the same duration. Implementation of UTT in Kenya resulted in increased numbers of people in need of cART which, in turn, may have exerted a strain on health systems and service delivery. These inherent implementation challenges, including potential inadequate human resource, were anticipated , 28, 29,Second, and despite evidence from randomized controlled trials (RCTs) demonstrating improved retention and virologic suppression amongst individuals on early cART , our finThird and notably, while young adults (15–24 years) had the highest odds of early cART uptake, they were also associated with the highest rates of non-retention and highest odds of initial VnS. These findings are consistent with results from other studies suggesting a high non-retention and low virologic suppression amongst the youth and young adults from HIV programs in resource limited settings. Modelling estimates suggest that youth and young adults contribute up to 40% of all new HIV infections in Kenya . Our finA major strength of our analysis is the use of routine service delivery data from health facilities located in 38 of the 47 counties in Kenya. However, use of routine service delivery data does have innate limitations. First, our convenient sampling strategy may have potentially introduced selection bias. However, a supplementary analysis of data from the general population, when compared to the sampled population, demonstrates comparable patterns on uptake of UTT, non-retention and initial VnS endpoints. The sampling strategy may also have resulted to inclusion of sites that are better functioning. Possibility that the lack of difference in initial VnS may be due to well-functioning program prior to implementation of UTT can therefore not be ruled out. Second, additional individual level data  and facility level data  would have enabled control for possible confounding. However, this was not possible as these variables were not systematically and consistently documented. Third, more than half the individuals were missing baseline CD4 T-cell count data, which made it impossible to completely control for disease severity at cART initiation in this analysis. While a limitation, this is not surprising as CD4-T cell count monitoring was discouraged after the introduction of the UTT policy in Kenya. Last, our definition of initial VnS was based on the first available viral load test result. As per the Kenyan guidelines, the first viral load test is recommended at 6–12 months after cART initiation. As such, we were not able to compare timing of virologic suppression achieved after UTT uptake. However, we were able to stratify VnS by duration from cART into 3-month follow up periods. Compared to those with a viral load test done >9 months, individuals tested <3 months after cART had higher likelihood of VnS; likely because shorter follow up time was not sufficient to achieve virologic suppression.Limitations above not-withstanding, our findings suggest commendable uptake of the UTT policy in Kenya. However, despite evidence from controlled studies suggesting that early cART improves retention and virologic suppression, our findings suggest poor twelve-months retention and lack of an association with initial VnS in routine real-life program settings. This difference in observations may largely be attributed to multiple other interventions co-implemented alongside early cART in controlled studies. Our findings therefore warrant consideration for multi-component program interventions targeting individuals, service providers and health systems, to complement implementation of the UTT policy towards achieving epidemic control in Kenya.S1 Table(TIF)Click here for additional data file.S2 Table(TIF)Click here for additional data file.S3 Table(TIF)Click here for additional data file.S4 Table(TIF)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.


Switching dual therapy with dolutegravir (DTG) plus rilpivirine (RPV) was assessed in the SWORD-1 and SWORD-2 studies. Real-life data regarding the immunological impact of this approach on CD4+ and CD8+ T lymphocyte counts and the CD4/CD8 ratio are scarce. We evaluated this strategy on the basis of clinical practice data.A multicentric retrospective cohort study.Treatment-experienced virologically suppressed HIV-1-infected patients who were switched to DTG plus RPV were included. Using different models for paired data, we evaluated the efficacy and immune status in terms of CD4+ and CD8+ T-cell counts and CD4/CD8 ratio at 24 and 48 weeks of treatment.P = .0038), but no significant changes in the CD8+ T-cell count . No differences were found in the CD4/CD8 ratio between the acquired immunodeficiency syndrome subgroup and sex or age.The study population comprised of 524 patients from 34 centers in Spain. Men accounted for 76.9% of patients, with a median age of 53 years. Patients receiving DTG plus RPV reached weeks 24 and 48 in 99.4% and 83.8% of cases, respectively, with only three (0.57%) virological failures. We found a significant decrease in CD8+ T-cell count (log OR –40) at week 24 and an increase in CD4+ T-cell count at week 48 (log OR +22.8). In acquired immunodeficiency syndrome-diagnosed patients, we found a significant increase in the CD4+ T-cell count at week 48 (log OR = 41.7, In patients with controlled treatment, dual therapy with DTG plus RPV slightly improved the immune status during the first 48 weeks after switching, not only in terms of CD4+ T-cell count but also in terms of CD8+ T-cell count, with persistently high rates of viral control. Restoration of the immune system was defined as an increase in the CD4+ T-cell count to normal values and an improved CD4/CD8 ratio >0.9.Antiretroviral therapy with three active drugs has been recognized as the standard of care for the treatment of human immunodeficiency virus type 1 (HIV-1) infection for the last 25 years. This therapeutic strategy, based on the combination of a backbone of 2 nucleos(t)ide reverse transcriptase inhibitors (NRTIs) and a third agent that could be a non-nucleoside reverse transcriptase inhibitor (NNRTI), a boosted protease inhibitor (PI), or an integrase strand transfer inhibitor (INSTI), and better tolerability and safety, the currently used NRTI backbones are not entirely free of potential tolerability and toxicity issues.,6 The increased potency of new third drugs, mainly INSTIs, together with the persistent toxicity of NRTIs, has led to the study and approval of therapeutic strategies based on 2 drugs , which makes it possible to avoid classic NRTIs. These combinations have been approved for use in both naïve and experienced patients. They guarantee not only undetectability, but also better tolerability and safety profiles, with less risk of developing potential short or long-term toxicities, especially in patients with comorbidities. Moreover, adherence may improve in some patients, and the costs are reduced.Despite improvements in triple therapy in terms of potency, efficacy, ease of dosing with single-tablet-a-day regimens,–11 Dual therapy with DTG and lamivudine (3TC) or rilpivirine (RPV) has been approved for treatment-naïve (DTG/3TC) and experienced patients (DTG/3TC and DTG/RPV). The combination of DTG plus RPV was studied as a switching strategy in SWORD-1 and SWORD-2 studies and small real-world cohorts, which showed very favorable efficacy, safety, and tolerability.–16 Data regarding the impact of dual therapy on CD4+ and CD8+ T lymphocyte counts and CD4/CD8 ratio in treatment-experienced patients are scarce. CD8+ T-cell count and CD4/CD8 ratio are indirect markers of immune activation and inflammation.–20 Improvement in these laboratory markers with dual therapy is controversial and uncertain because data are scarce, and some clinicians doubt that dual therapy is as potent as triple therapy in restoring the immune system and reducing immune activation.Dolutegravir (DTG) is a highly potent and effective INSTI that has become the gold standard treatment for naïve patients.This study aimed to provide data on the impact of this strategy in real-life patients regarding changes in immune status. We explored efficacy and immune status based on CD4+ and CD8+ T lymphocyte counts in a cohort of 524 patients from 34 hospitals in Spain.22.1  HIV-1 infection with age ≥18 years, b) switching from three-drug combination antiretroviral treatment (cART) to dual therapy with DTG+RPV, c) HIV RNA viral load <50 copies/ml in the previous 24 weeks before switching, and d) switching to DTG plus RPV at least 48 weeks before the start of the study in May 2020. Data were collected from medical records, anonymized, and entered into an online electronic database, REDCapThe study protocol was approved by the Ethics Committee of Complejo Hospitalario de Avila in August 2020 (code 3/20) and was re-approved or registered by other local ethics committees. Given the retrospective nature of the study and the fact that data were obtained from routine clinical records, written informed consent was not necessary.2.23) and CD4+/CD8+ ratio, b) safety profiles at weeks 24 and 48, and c) reasons for switching to DTG+RPV.The primary outcome was efficacy analysis to determine the proportion of patients with undetectable viral loads (<50 copies/ml) at weeks 24 and 48. Secondary outcomes included the following: a) changes in the immune status of patients in terms of CD4+ and CD8+ T lymphocyte counts  and three different third agents ;2.at 24 weeks after switching to dual therapy with DTG+RPV; and3.at 48 weeks after switching to dual therapy with DTG plus RPV Fig. .3.Given that the experimental design requires a study to compare CD4+ and CD8+ T lymphocyte counts in individuals at different stages, these data points must be considered paired. A series of variables that can interact with lymphocyte count was also obtained, including sex, age, and previous antiretroviral treatment. We also recorded a diagnosis of AIDS and a CD4 nadir below 200 cells/mm2.3t-test or paired t-test with n/2–1 degrees of freedom. Using this approach, we tested the differences in lymphocyte counts between the groups  without correcting for covariates or considering the effect of the backbone and third agents.The statistical methods applied in this study were specific to the paired data. Our main objective was to assess differences in the lymphocyte counts of individuals receiving cART at baseline versus 24 and 48 weeks after the administration of dual therapy. Thus, we started by applying a simple paired sample To include covariates and address the effect of the drugs used at baseline, we applied a multiple generalized linear mixed model. By considering the individual as a random effect, this model enabled us to address the paired nature of the data:p,0p is the random effect of each individual, β1Xi is the fixed effect of the different treatments to be tested , β2Xj is the fixed effect of the backbone drug, β3Xk is the fixed effect of the third agent, β4Xl is the fixed effect of sex, and β4Xm is the fixed effect of age.where b3The study population was comprised of 524 patients from 34 centers in Spain. The baseline characteristics are summarized in Table P = .1803 or Fisher exact test: OR = 0.6301 (0.28–1.5); P = .279. At week 48, discontinuations due to reasons other than virologic accounted for 16.2% of cases, with 2.3% due to toxicity issues.The percentages of patients with undetectable HIV viral load who reached weeks 24 and 48 with this switching strategy were 99.4% and 83.8%, respectively. Virological failure was recorded in only 3 patients (0.57%). Resistance mutations were not detected. No differences were found in terms of efficacy between the AIDS and non-AIDS subgroups using the general linear model (GLM): –0.536, P = .6177).Immune status, assessed through the median baseline CD4+ and CD8+ T lymphocyte counts, was shown to change in the complete dataset. A simple analysis of paired data showed an increase in CD4+ T-cells  at week 48 after switching treatment to dual therapy, and a decrease in CD8+ T-cells  at week 24 after switching . Patients diagnosed with AIDS also showed a statistically significant increase in CD4+ T-cell counts. The mean difference between baseline cART and 48 weeks after switching was 46.34 (95% CI = 90.5–2.12) . This effect was also significant in the multiple mixed models at 48 weeks (log OR = 41.78). No differences were found in the CD8+ T-cell count, effect of the baseline antiretroviral backbone, or third drug.Adverse events (AEs) were reported in 20 patients (3.8%), including renal toxicity in 6 patients (35%), central nervous system toxicity in 6 (30%), and gastrointestinal issues in 4 (20%). No severe AEs were observed. Twelve patients (2.3%) discontinued treatment because of mild-to-moderate toxicity issues.P = 6.47E-06; eGFR log OR = –4.37, P = 1.17E-10. Week 48: creatinine: log OR = 0.069, P = 1.42E-04 and eGFR log OR = –3.79; P = 1.85E-07). We did not find significant differences in the subgroup of 395 patients who used tenofovir disoproxil fumarate (TDF) as part of their previous treatment, apart from those who also used boosted PIs .Changes in laboratory values included an increase in creatinine and estimated glomerular filtration rate (eGFR) at weeks 24 and 48  and toxicity of baseline cART (24.6%). Clinicians indicated this dual therapy with DTG plus RPV as a transition to future injectable treatments with RPV in 4.5% of the patients.4–16 In our cohort, these rates align with published data, around 100% at week 24, with only three virological failures due to poor adherence during the first 48 weeks, even in patients diagnosed with AIDS and those treated with multiple regimens. Similar results have been reported in previous real-life cohorts of patients undergoing dual therapy.,22 These high rates of virological response make this regimen a valid alternative to triple therapy in virologically controlled HIV-1-infected patients without NNRTI resistance mutations, even in those with long-term disease, multiple previous treatments, and a prior diagnosis of AIDS.The efficacy rates of the DTG plus RPV strategy are high in clinical trials and real-life cohort studies.,18,19 and CD8+ T-cell count and, more specifically, the CD4/CD8 ratio, are indirect markers of immune activation and inflammation, both of which affect prognosis. Some retrospective and observational cohort studies have suggested that dual therapy could lead to less powerful control of HIV replication, with a subsequent negative impact on immune status in the form of increased activation, inflammation, and lower CD4/CD8 ratios.,19 In our cohort, no significant changes were observed in the CD4/CD8 ratio (0.85 at baseline) during the first 48 weeks after switching to DTG plus RPV. Similar findings have been reported in patients diagnosed with AIDS. Our data contrast with other published real-life cohort studies, which reported a slight increase in the CD4/CD8 ratio, possibly because of the lower baseline CD4/CD8 ratio (0.71) and smaller study population (91 patients in the DTG/RPV group).Immune activation and biomarkers of inflammation improve within the first year after cART-induced HIV-1 suppression; however, some residual immune activation is present, In our cohort of 524 patients, we observed a significant decrease in the CD8+ T-cell count at week 24 and an increase in the CD4+ T-cell count at week 48, with a switching baseline count >700 cells/mm3. It is mandatory to note this aspect in our cohort, because, despite a general low nadir of CD4+ T-cell count or a long-term HIV infection, the CD4+ T-cell count at the switching time was over 500 cells/mm3, and the CD4/CD8 ratio was 0.85, in contrast with published data. This suggests that most patients fail to normalize their ratio if they start treatment during chronic HIV infection, even after a decade of viral suppression.Some authors reported an increase in the CD8+ T-cell count after switching 104 patients to dual therapy with boosted PIs. Moreover, the impact of dual therapy on the restoration of the immune system could differ depending on the antiretrovirals used, including INSTIs, boosted PIs, and NNRTIs. Nevertheless, long-term follow-up would probably be necessary to account for changes in immune status with DTG plus RPV.Our findings suggest that in treatment-experienced patients with virologically controlled HIV infection and a high CD4+ T-cell count, especially those with a long history of HIV infection, more than 48 weeks are needed to evaluate the significant changes in the CD4/CD8 ratio after switching.Co-infection with other viruses may play an important role in immune activation. In our cohort, we found no difference in patients with active HCV infection, but we were unable to determine the potential impact of other viruses, such as cytomegalovirus due to the retrospective nature of the study.,16 This observation is of great interest because toxicity continues to be one of the main reasons for switching antiretrovirals, although only 2.3% of patients in our cohort discontinued treatment due to mild or moderate issues. The main reasons for withdrawal were physicians’ decisions or clinical conditions other than HIV infection, which prevented continuation of DTG plus RPV. Good safety and tolerability profiles make this regimen a simplified option for patients with significant comorbidities who need drugs that are readily metabolized and for patients who have or are predisposed to toxicities.The DTG plus RPV strategy was well-tolerated and safe, with AEs registered in only 3.8% of the patients. These results correlate with published data from clinical trials and cohort studies. This result contrasts with data from clinical trials and real-life cohort studies,,16,22 which found significant changes in renal function after discontinuing TDF. This may be explained by chronic damage to renal function in patients with long-term exposure to TDF. DTG plus RPV have a good renal profile and constitute a favorable option for this group of patients.In our cohort, no improvement in renal function (creatinine or eGFR) was observed in patients whose previous regimen included TDF except when boosted PIs were present. Remarkably, the combination of boosted PIs and TDF is associated with renal problems.Our study was limited by its retrospective design and the absence of a control group. In addition, the clinical protocols and visit timetables differed between the participating hospitals. Nevertheless, the strength of this study is its large sample size (>500 patients), which is greater than that of other real-life cohorts (approximately ≤100 patients). Further investigations are needed to elucidate this aspect in clinical trials and prospective observational studies.In conclusion, administration of dual therapy with DTG plus RPV to treatment-experienced and virologically controlled patients was highly effective and slightly improved the immune status during the first 48 weeks after switching, in terms of not only the CD4+ T-cell count but also the CD8+ T-cell count. The low tolerability and safety issues, together with the low number of discontinuations owing to these toxicity issues, make this regimen a good switching strategy for aging patients, those with several comorbidities, and those with previous or potential long-term toxicities.We thank the patients, investigators, and participating institutions for enabling this study possible.Conceptualization: Carlos Dueñas, Jesús Troya, Luis Buzón.Data curation: Carlos Dueñas, Jesús Troya, Luis Buzón.Formal analysis: Francisco Ceballos, Jesús Troya.Investigation: Ana Pelaez, Elisabeth Delgado, Jesús Troya, Luis Buzón, María Garcinuño, María José Galindo, Marta Montero, Miguel Ángel Morán, Miguel Cervero, Sara de la Fuente, Teresa Aldamiz, Carlos Dueñas, Guillermo Posada, Idoia Irazola, Ignacio Santos, Javier Fuente, Josean Uribaren, Josefa Galindo, Julia Gomez.Methodology: Carlos Dueñas, Jesús Troya, Luis Buzón.Project administration: Jesús Troya.Supervision: Jesús Troya.Writing – original draft: Carlos Dueñas, Luis Buzón, Jesús Troya.Writing – review & editing: Ana Pelaez, Luis Buzón, Carlos Dueñas, Carlos Galera, Cristina Hernández, Desiré Gil, Elisabeth Delgado, Estela Moreno-García, Francisco Ceballos, Guillermo Posada, Idoia Irazola, Ignacio Santos, Javier Fuente, Jesús Troya, Jose Antonio Iribarren, Jose Manuel Guerra, Josean Uribaren, Josefa Galindo, Julia Gomez, María Garcinuño, María José Galindo, Marta Montero, Miguel Ángel Morán, Miguel Cervero, Sara de la Fuente, Teresa Aldamiz.


People living with HIV/AIDS are enrolled in lifelong Anti-Retroviral Treatment (ART) irrespective of their clinical staging as well as CD4 cell count. Although this “Universal Test and Treat” strategy of ART was found to have numerous benefits, loss from follow-up and poor retention remained a long-term challenge for the achievement of ART program targets. Hence, this study is aimed at addressing the much-needed effect of the test and treat strategy on the incidence of loss to follow-up (LTFU) in Ethiopia.An institution-based follow-up study was conducted on 513 adults (age ≥15) who enrolled in ART at a public health institution in Bahir Dar City, Northwest Ethiopia. Data were extracted from the charts of selected patients and exported to Stata 14.2 software for analysis. Basic socio-demographic, epidemiological, and clinical characteristics were described. The Kaplan–Meier curve was used to estimate the loss to follow-up free  probability of HIV-positive adults at 6, 12, 24, and 48 months of ART therapy. We fitted a multivariable Cox model to determine the statistically significant predictors of LTFU.P = 0.004), in males , in singles , in non-disclosed HIV-status . Patients with poor/fair ART adherence were also identified as another risk group of LTFU .The incidence density of LTFU was 9.7 per 100 person-years of observation (95% CI: 7.9–11.9 per 100 PYO). Overall, LTFU is higher in the rapid ART initiation (24% in rapid initiated vs. 11.3% in lately initiated, AHR 2.08, The incidence of LTFU in this universal test and treat era was high, and the highest figure was observed in the first 6 months. Immediate initiation of ART in a universal test and treat strategy shall be implemented cautiously to improve patient retention and due attention shall be given to those high-risk patients. HIV/AIDS is a major global public health concern, having claimed the lives of 36.3 million people so far . DespiteLoss to follow-up (LTFU) which is defined as the absence of an ART refill or follow-up for 3 months or longer from the last follow-up schedule continues to be a significant public health concern on ART programs , 9, 10. Moreover, studies conducted in Ethiopia before UTT have shown that both the proportion and incidence of LTFU greatly vary across regions and health institutions. For instance, in Debre Markos, Gondar, Pawi, Hadiya, and Jigigia (Eastern Ethiopia), it reaches 10.5 per 100 PYO, 11.6 per 100 PYO, 11.9 per 100 PYO, and 26.6 per 100 PY, respectively –20. The LTFU is the leading cause of morbidity, mortality, hospitalization, treatment failure, high burden of opportunistic infections (OIs), the emergence of drug resistance to HIV, and transmission of the virus to uninfected sexual partners among patients with HIV/AIDS , 15–17. To decrease the incidence of LTFU, interventions such as expanding ART service sites, monitoring patients through frequent phone calls, offering a client-centered appointment system, and lowering the pill burden have been suggested and are being implemented both regionally and worldwide , 10. DesAn institution-based cohort study was conducted on adults enrolled in ART in Felegehiwot Comprehensive Specialized Hospital (FHCSH), Northwest Ethiopia, from November 2016 to October 2020. It is one of the earliest comprehensive specialized hospitals in Amara regional state, located in Bahia Dar town, 565 km from Addis Ababa, the capital city of Ethiopia . The hosThis study took a 9-month duration starting from research question identification to the accomplishment of the overall work of the research. Data for the study were collected from 15 March 2020 to 15 April 2021 by three BSc nurse professionals. The advisors strongly participated in reviewing this work and providing constructive feedback from 29 October 2021 till 02 June 2021.The source population for this study was all HIV-positive adults who were newly enrolled in ART at FHCSH following the implementation of the UTT strategy. All HIV-positive adults who were newly enrolled on ART from November 2016 to October 2020 at FHSCH and who had at least one active follow-up visit were included. On the contrary, HIV-positive adults whose charts were lost during the data collection period (six) and who had incomplete records of age, ART initiation date, and HIV confirmation date (25) were excluded from the study.The minimum sample size required to conduct this study was calculated by STATA (V.14.2) software using a Log-rank test comparing two survival rate methods. By considering the following parameters, such as 0.05% level of significance, 80% power, 95% confidence interval, a 1:1 ratio of exposed to unexposed, and significant predictors of LTFU from a previous study , a 513 sThe outcome variable for this study is the occurrence of loss to follow-up at some point in time. The main exposure variable is the time to initiation of ART (within 7 or beyond 7 days). The other predictor variables were categorized as socio-demographic variables  and Clinical and treatment-related factors including functional status, baseline body mass index (BMI) status, baseline CD4 count, presence or absence of OI, utilization of Isoniazid prophylaxis therapy (IPT), use of Cotrimoxazole preventive therapy (CPT), baseline WHO clinical stage, ART regimen type, history of ART regimen change and treatment failure, HIV disclosure status, and ART drug adherence status.The outcome status of the patient was dichotomized into LTFU or censored. A patient is categorized as LTFU when an individual has failed to visit ART clinics more than 90 days after the last appointment date and has not been classified as either “died” or “transferring out” . CensoreThe data abstraction checklist was adapted from the Federal Ministry of Health (FMOH) ART follow-up form, the patient intake, and monitoring formats after reviewing different articles. Three BSc Nurse Professionals collected the data while being closely supervised by a master of public health professional with experience in monitoring and supervising ART programs. Both data collectors and supervisors received one-day training about the purpose of the study, how to extract relevant data, and how to guarantee the confidentiality of patient information to ensure the quality of the data. Supervisors also reviewed the consistency and completeness of the data every day.After the data were coded, it was entered into Epi_data version 4.6 and simultaneously exported to STATA 14.2 software to undergo further statistical analysis. Missing data were handled and managed by the multiple imputations technique after checking the missing at random (MAR) patterns of the variables with the missing record. The imputation was computed with Multivariate Chained Equation (MVCE) model . Finallyp < 0.05 in the multivariable analysis were considered significant predictors of loss to follow-up.After fitting the model, its goodness of fit was checked by the Cox–Snell residual plot. Indeed, the proportional hazard (PH) assumption of the model was verified by both graphical tests  and the Schoenfeld residual PH test. Both bivariable and multivariable Cox regression models were fitted to identify the predictors of loss to follow-up, and those variables with a Since the study was conducted retrospectively using a patient's medical record, the need for informed consent was waived by the Institutional Review Board (IRB) of Bahir Dar University, College of Medicine and Health Science with a protocol number of 058/2021. Instead, a supportive letter was sent from the IRB to the study setting. Then, a permission letter was obtained from the directors, followed by the ART clinic focal person of Felegehiwot Comprehensive Specialized Hospital (FHCSH). Besides, information in the data extraction tool was kept anonymous. The confidentiality of information was kept throughout the entire study process, and the information was used only for the study purpose.From a total of 513 calculated samples of HIV-positive adults, 507 (98.8%) were included for final analysis. Six (06) participants were dropped from being studied due to the loss of the patient's medical chart and ambiguity of records inside the chart. Slightly more than half 268 (52.86%), 246 (51.3%) of the individuals were females and married, respectively. The median age of the study participants was 32 years, with an interquartile range (IQR) of 27–40 = 13 years. Regarding the residence of the study participants, more than two-thirds  were from urban areas, whereas more than one-fourth  did not attend formal education .3. In terms of OI, around 108 (21.3%) of those individuals had TB/HIV co-infection. Regarding ART drug adherence, more than two-thirds  had good adherence levels  of study participants were initiated to ART within 7 days of confirmation of diagnosis, of which 112 (39%) were initiated within the same day of diagnosis. According to the WHO clinical staging, nearly two-thirds (66.3%) of them were in clinical stage I or II diseases at baseline. The median BMI and CD4 values of the study participants were 20.07 (IQR 18–22) and 278 (IQR 121–451), respectively. Altogether, nearly 37% (90) of HIV-positive adults had a baseline CD4 values < 200 cell/mme levels .The study participants were followed for a minimum of 1 month to a maximum of 48 months which provides a total of 11,493 person month (957.76 Person years of observation/PYO). The median follow-up time for the study participants was 23 months (IQR 9–36 months). Upon the compilation of the follow-up period, nearly one-fourth  of patients were LTFU, which yields the incidence density of LTFU as 9.7 per 100 (95% CI:7.9–11.9) PYO. Additionally, the incidence density of LTFU was 20.6 per 100 PYO (95% CI: 15.5–27.3), 13.6 per 100 PYO (95% CI: 10.5–17.7), 10.7 per 100 PYO (95% CI: 8.5–13.3), and 9.7 per 100 PYO (95% CI: 7.9–11.9), in the first 6, 12, and 48 months, respectively. Moreover, the estimated cumulative LTFU-free survival probability was 92% (95% CI: 88.8–93.7%) for the first 6 months, 87.9%  at the end of 12 months, 82%  at the end of 2 years, 76.6% (95% CI: 71.7–80.7%) at the end of 3 years, and 74.2% (95% CI: 68.6–88.8%) at the end of 4 years of follow-up period .Both the incidence of LTFU- and LTFU-free survival probability vary across categories of each independent variable. For instance, the LTFU-free survival probability of patients who were initiated into ART within 7 days  was much lower than those who were initiated after 7 days of diagnosis . Additionally, the LTFU-free survival probability among patients who disclosed their status  was significantly higher than their counterparts  at the end of the follow-up period .p < 0.25 were selected for multivariable Cox-regression regression analysis. In the final analysis, the following five variables namely time to ART initiation, sex, marital status ART disclosure status, taking CPT status, and ART drug adherence level were identified as the major of LTFU at p < 0.05. In this regard, HIV-positive adults who commenced ART within 7 days were almost two times more likely to be lost from their routine care than those who initiated later . Additionally, male HIV-positive adults have a nearly two-fold higher risk of LTFU than females . The hazard of LTFU among unmarried/single HIV-positive patients was also approximately two times that of married individuals .During bi-variable Cox-proportional regression analysis, 12 variables that had P = 0.001). The risk of LTFU was 4.36 times greater in patients with fair/poor adherence than in those with good ART adherence . In the end, HIV-positive adults who did not receive CPT were nearly two times at higher hazard of being lost from their follow-up compared to their counterparts   .P-value of the PH test for all variables in the final model was >0.05. Additionally, the yields of graphical tests  illustrate that the effect of each predictor on the outcome was constant throughout time.The goodness of fit of the Cox proportional hazard regression model was checked by the Cox–Snell residual plot. Based on the Cox–Snell residuals plot, the Nelson_aelon hazard line has a 45-degree alignment with the reference line, indicating that the model is well-fitting . The proThis institution-based retrospective cohort study was carried out to assess the incidence and predictors of LTFU following the implementation of the Test and Treat strategy at FHCSH, Northwest Ethiopia. In this study, the overall incidence density of LTFU among HIV-positive adults on ART at FHCSH was found to be 9.7 per 100 person-year of observation. The finding was in line with previous studies conducted in Gondar , Pawi 1, Hadiya Socio-demographic characteristics such as sex and marital status were identified as important predictors of LTFU. For instance, it was observed that male HIV-positive adults had a nearly two-fold increased risk of LTFU compared to females. The findings were comparable to other studies conducted in eastern Ethiopia and India , 20, 30.In the current study, patients enrolled in ART rapidly were at an increased risk of being LTFU than their counterparts. This finding was supported by studies conducted in Uganda , South AHIV-positive patients who did not disclose their status to at least one individual were shown to be two or more times more at risk of being lost from their routine care than their counterparts. This finding is parallel with studies conducted in Jigiga  and a syThis study also demonstrated that adherence to ART drugs was a significant predictor of LTFU. People with poor or fair ART adherence levels were more likely to become LTFU than people with high rates. This observation is consistent with research carried out in LMICs, and Malawi, Gondar, and Hadiya Zone Public Hospitals , 19, 26.Finally, patients who did not receive CPT through their follow-up period are more likely to experience LTFU than their peers. This finding was also comparable with a study conducted in Gondar and Nigeria , 23. TheThis study has some limitations. Initially, due to the secondary nature of the data, it was initially quite challenging to examine the relationships between key crucial variables, including the mental status of the patient, provider and system-related issues, distance from the institution, and loss to follow-up. Second, due to poor tracing systems, patients who were leveled as LTFU might be died or self-transferred to other health facilities, which will overestimate the finding in this study. Additionally, since there are a lot of patients in this study who are referred to other health institutions with inadequate tracing, the finding of LTFU will be underestimated if those patients might be lost from care.The incidence of loss to follow-up was relatively high and it was higher among patients who start ART within 7 days. Moreover, a higher incidence of loss to follow-up was noted in the first 6 months of ART initiation. Additionally, not disclosing status, having poor/fair drug adherence, having ambulatory functional status, and not receiving CPT were identified as the predictors of loss to follow-up. Therefore, we strongly recommend the cautious implementation of the UTT strategy by complementing it with frequent follow-up, intensive counseling, and close monitoring for patients initiated rapidly. Health care providers would assure patient's willingness and emotional readiness before initiating ART.All the data needed for this study are available in the manuscript, further inquiries can be directed to the corresponding author(s).The studies involving human participants were reviewed and approved by Institutional Board of Bahir Dar University. However, since the study uses secondary data  as a source of information, informed consent was waived by IRB of the university with the protocol number of 058/2021.BB: formulating research problem, design of study, data collection, analysis, interpretation, conclusion, and preparing initial manuscript draft. GD, AS, AA, and GK: actively participated in data collection, analysis and interpretation, and writing up the manuscript. All authors had thoroughly read and approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Adolescents and young adults with HIV consistently account for about one-fifth of new infections in the United States. YLWH have lower rates of testing, diagnosis, treatment engagement, and viral suppression than adults with HIV. YLWH are particularly challenged with missing medical appointments. Few studies have been published on youth living with HIV (YLWH)’s missed clinic visits and risk factors. Therefore, this study was designed to explore:1). if the missed visits have significant associations with HIV treatment outcomes  in YLWH; 2). What factors are associated with missed visits for YLWH? 3) Are these factors different from the risk factors of all PLWH?st 2020 to August 31st, 2021. Patients aged 16-24 were considered as YLWH. The primary outcomes are missed visits and treatment outcomes. CD4 change, Viral suppression and VL change during the study period were investigated for identifying the association between missed visit and treatment outcome. Age, gender, race, HIV transmission mode, insurance type and the viral suppression in index record were used as factors to predict missed visits. Chi-square test and logistic regression have been conducted in SAS 9.4.A retrospective study using data records from UAB Family Clinic was designed. The study used the records from March 1YLWH with missed visits had more viral load rebound compared to those without missed visits (p=0.04).For YLWH, gender and viral suppression in the index record have significant associations with missed visits .In tests among all PLWH, Race (p=0.03), Insurance type (p=0.01) and viral suppression in index record (p=0.001) are associated with missed visits.Missed visits are significantly associated with viral load maintenance, and missed visits have adverse effects on treatment outcomes. Also, the risk factors for YLWH of missed visits are not identical with the risk factors for PLWH from the same cohort.All Authors: No reported disclosures.


Background: Integrase strand-transfer inhibitor (INSTI)-containing regimens have gradually been administered in Guangdong Province, China beginning in 2016, and INSTI-related drug resistance (DR) may occur and should be monitored among HIV-1-infected patients. Objective: To investigate the prevalence of INSTI-related resistance among HIV-1-infected individuals in Guangdong and provide evidence for the optimal administration of INSTIs. Methods: This study recruited 1208 HIV-1-infected patients (including 404 ART-naive and 804 ART-experienced patients) between June 2021 and April 2022. The entire integrase gene was amplified from blood plasma. Demographic and epidemiological information were collected. INSTI mutations and susceptibility were interpreted using the Stanford HIV Drug Resistance Database HIVdb program. Results: Of the 1208 enrolled individuals, 2.65% (32/1208) carried at least one INSTI major or accessory drug resistance mutation (DRM), with 1.49% (6/404) being from ART-naive individuals and 3.23% (26/804) from ART-experienced individuals. Among them, seven polymorphic major mutations were detected. Although no INSTI drug resistance was found among treatment-naive patients, seven ART-experienced patients  carried mutations conferring resistance to INSTIs. Conclusion: The overall prevalence of INSTI DRMs and DR was comparatively low among ART-naive and ART-treated populations in Guangdong; however, INSTI-related polymorphic mutations were observed. Surveillance should be reinforced before transfer to INSTI-containing regimens. The HIV epidemic remains one of the most serious global health threats ,2. The WCombined antiretroviral therapy (cART) suppresses HIV replication, allowing immune reconstitution to occur, dramatically decreasing HIV/AIDS-related morbidity and mortality as well as the risk of further HIV transmission ,7. By thOverall, increased use of reverse transcriptase inhibitor-based regimens has been accompanied by the emergence of drug resistance, which leads to treatment failure and can be transmitted to those with new infections ,9,10,11.Integrase strand-transfer inhibitors (INSTIs) are the latest class of drugs available that target the HIV integrase enzyme; they offer novel treatment options for patients with both ART-naive and acquired or transmitted drug resistance (ADR or TDR) to protease inhibitors (PIs) and NNRTIs ,14. The Although INSTIs have been proven to be an effective antiretroviral drug against HIV infection ,19, the HIV-1-infected individuals were eligible for inclusion in this study if they were 16 years old or older, treatment-naive, or ART-experienced with HIV-1 viral load above 1000 copies/mL. We recruited 1208 individuals from Guangdong between June 2021 and April 2022, comprising 804 ART-experienced and 404 ART-naive individuals. Epidemiological data for the patients  were downloaded from the National Free Antiretroviral Treatment Database for Disease Control and Prevention.https://comet.lih.lu/index.php, accessed on 8 November 2022) and confirmed using a maximum likelihood (ML) phylogenetic tree based on protease (PR) and partial reverse transcriptase (RT) sequences.Anticoagulant EDTA peripheral blood samples were collected and plasma was separated after centrifugation. Real-time molecular beacon detection was applied to detect HIV-1 viral load . HIV-1 genotypes were determined using the online tool COMET HIV  according to the manufacturer’s instructions. Amplification of the entire Integrase (IN) gene  was performed with an in-house RT–PCR procedure, as previously described . Positivhttps://hivdb.stanford.edu/hivdb/by-sequences/, accessed on 2 June 2022) was employed to identify INSTI mutations and sensitivity to BIC, CAB, DTG, EVG, and RAL. Sequences associated with low-level, intermediate, or high-level categories of resistance were defined as conferring INSTI drug resistance.The obtained sequences were assembled and cleaned with Sequencher DNA sequence analysis software (Version 5.4.6) and then aligned using BioEdit software (Version 7.2). The Stanford HIV-1 drug resistance database  under accession numbers OP032752-OP033959.All IN sequences from the 1208 HIV-1 individuals were submitted to the GenBank website  with the GTR model [The ML phylogenetic tree was generated using PhyML version 3.0 . The chi-square test was applied for comparisons between two groups, and the level of significance for the evaluation of two-sided In total, 1208 individuals were included in this study, including 404 ART-naive and 804 ART-experienced individuals. The age of the participants ranged from 16 to 87 years, with a median age of 43 years. Among them, 50.99% (616/1208) were recruited in 2021 and 49.01% (592/1208) in 2022. Approximately 44.04% of the individuals had confirmed infections before 2019. Most of the subjects  were male. Heterosexual (HET) contact comprised the predominant risk group , followed by men who have sex with men (MSM)  and intravenous drug users (IDU) . The median HIV-1 RNA viral load at the time of the drug resistance test and the CD4+ T-cell count at baseline were 4.15  and 199 (cells/µL), respectively. The demographic characteristics of the HIV-1-infected individuals are summarized in Complete IN sequences were obtained from all 1208 enrolled participants. There were no duplicate samples from the same subject at different time points. According to COMET HIV-1 analysis based on PR/RT sequences, CRF01_AE was the most frequently occurring genotype, with a proportion of 40.81% (493/1208), followed by CRF07_BC  and CRF55_01B . A total of six subtypes or circulating recombinant forms (CRFs) were confirmed  according to the ML phylogenetic tree based on 1104 PR/RT sequences A, which Of the 1208 individuals, 2.65% (32/1208) carried at least one INSTI major or accessory DRM. Among them, 1.49% (6/404) were obtained from ART-naive individuals, whereas 3.23% (26/804) were from ART-experienced individuals .A total of 38 INSTI-related DRMs were detected among the enrolled individuals. Approximately 2.32% (28/1208) harboured only INSTI accessory DRMs ; ART naive, 1.49% (6/404)), 0.25% (3/1208) harboured only INSTI major DRMs ), and 0.08% (1/1208) harboured both INSTI major and accessory DRMs ).E138K and Q148R  were the most frequent mutations among INSTI major DRMs, and E157Q  was the most frequent mutation among INSTI accessory DRMs. Moreover, INSTI major and accessory DRMs both varied among ART-naive and ART-experienced individuals .According to the HIVdb program, 0.58% (7/1208) of the enrolled individuals carried INSTI-related DRMs associated with low-level, intermediate, or high-level resistance . The chaSeven patients with INSTI-related drug resistance were observed among the ART-experienced patients. Among them, four HIV-1 genotypes were identified . Six individuals were male, and the dominant transmission route was HET (4/7), with a median age of 52 years (IQR: 29–73 years). Four individuals received INSTI-containing ART regimens , while the other three  were not recorded as utilizing INSTIs.Conversely, no drug resistance to INSTIs was observed among treatment-naive patients. The prevalence of drug resistance to INSTIs among ART-experienced patients was 0.87% (7/804) . As showINSTIs, a novel class of anti-HIV agents, show high activity in inhibiting HIV-1 replication and play a critical role in therapy for infection with this virus . However2 = 0.002, p = 1.00 > 0.05). With the increasing number of patients using INSTI-containing regimens in Guangdong , surveillance should be reinforced with respect to the further choice of or transfer to INSTI-containing regimens.HIV-1 has a high degree of natural variability due its lack of gene expression proofreading and high frequency of genetic recombination . We obse5 IU/mL at baseline to 7.99 × 102 IU/mL at DR test. The treatment failure in this case may have been due to the H51Y mutation, which needs to be confirmed by further phenotypic analysis.Regarding ART-experienced individuals, most of the INSTI resistance mutations detected were accessory . The most frequent mutations were E157Q  and A128T , followed by G163R , H51Y , Q146R , Q146V , and G149A  . Except For the ART-experienced individuals, 28.13% (9/32) of the INSTI resistance mutations detected are major resistance mutations. The most frequent major INSTI resistance mutations were E138K and Q148R , followed by T66I, E92Q, G118R, G140A, and S147G . All these major INSTI resistance mutations were detected in four patients (three of them had ever used regimens containing integrase), though the frequency of these major INSTI resistance mutations was very low (from 0.12% to 0.25%). E138K is a non-polymorphic mutation occurring in patients receiving RAL, EVG, and DTG . In thisAccording to previous studies ,38, drugAccording to previous studies ,41,42,432 = 3.188, p = 0.088), and seven INSTI-related polymorphic major mutations were detected among HIV-1 patients in Guangdong, emphasizing the importance of monitoring drug resistance prior to administration of INSTI-containing regimens.The overall prevalence of INSTI DR in Guangdong remains low , which suggests that INSTIs currently have good applicability and that the use of INSTIs results in ideal viral suppression. Nevertheless, the proportion of DR in ART-experienced individuals was higher than that in ART-naive individuals (χ


With the global push towards universal access to Antiretroviral Treatment (ART), patient numbers are increasing, further straining already under-resourced healthcare systems in sub-Saharan Africa. A simple scoring tool could be useful in optimizing differentiated service delivery by identifying individuals likely to have unsuppressed viral load.Using existing data of patients accessing ART at public health facilities that were extracted from the Kenya Electronic Medical Record (KenyaEMR) and standard methods of developing a clinical prediction tool; we created and validated a risk scoring tool to identify persons likely to be virally unsuppressed at 18 months post-ART initiation. Data from the KenyaEMR were cleaned, merged and reviewed for completeness. We utilized multivariate modelling to determine key predictors of viral load suppression that could be measured in clinical settings.We assessed clinical reports of 3,968 patients on ART who had been on ART for at least 18 months and had at least one viral load result and were ≥ 18 years old. Of these, the majority (81%) were virally suppressed 18 months post-ART initiation. The final risk score included age, sex, body mass index at HIV diagnosis, number of years of formal education, disclosure status, and duration of time between HIV diagnosis and initiating ART. The maximum risk score was 78; a risk score of ≥22 was associated with unsuppressed viral load (>1000copies/mL). The area under the curve (AUC) for the probability of the risk score to correctly predict unsuppressed viral load was 0.55 (95% CI: 0.52 to 0.56). Internal and external validation showed similar predictive ability.Routinely collected variables in a public HIV clinic medical record predicts, with modest accuracy, individuals likely to have unsuppressed HIV viremia 18 months after they initiate ART. The use and application of this tool could improve and complement efficiency in differentiated care models for patients on ART. Approximately 1.5 million people in Kenya were living with HIV at the end of 2020 and the majority were using antiretroviral therapy (ART). Sustained adherence to ART with subsequent viral suppression has community HIV prevention benefits, health benefits for the person living with HIV, and HIV prevention benefits for HIV-negative sexual partners . DeliverIn Kenya, PLHIV are typically offered ART and are taken through ART counselling sessions at the first visit after HIV diagnosis. They are then reviewed 2 weeks following ART initiation and then every 1–3 months thereafter based on their adherence patterns. Differentiated care models (DCM) have been introduced to provide scheduling options, with increased time interval between visits from 3 to 6 months with multi-month ART dispensing either at the healthcare facility or community sites. These models have been invaluable in reducing the burden on HIV treatment centers while maximizing the use of available human resource capacities . Less frWe used individual-level data from PLHIV accessing care from HIV treatment centers within Kenya whose clinical records were available in the KenyaEMR system. We created a prediction model and scorecard to identify people most likely to be virally unsuppressed 18 months after ART initiation, for whom more frequent clinic visits may be recommended.The KenyaEMR system is implemented in more than 300 HIV treatment centers within Kenya by the National AIDS and STI Control Program (NASCOP). Typically, some facilities key in data directly into the KenyaEMR while some collect records on paper forms and abstract them into the system. Records are then uploaded weekly onto the NASCOP data warehouse where they are stored. The purpose of the system is to create digital clinical records for patients accessing HIV care through these facilities. Through standardized electronic forms, the KenyaEMR collects a comprehensive set of variables that are captured in the Ministry of Health comprehensive care visit card (MOH247 form) which is used in all HIV treatment centers countrywide.For this analysis, medical record data captured between January 2015 and August 2017 were used. De-identified data were received from the National AIDS and STI control Program (NASCOP) KenyaEMR system as two datasets: a) socio-demographic data which were captured through client intake forms at the HIV treatment centers, and b) viral load data including dates when samples were drawn and corresponding results captured through the MOH247 form. The datasets were merged to create one master dataset and duplicates were removed. Records were excluded if they did not have at least one viral load measurement ≤18 months post-ART initiation. Data were collected up to 19 months post-initiation to account for programmatic delays at month 18 visit which are common in clinical practice. In addition, the analysis was restricted to people aged ≥18 years because younger populations may need a different set of monitoring criteria due to child/adolescent dosing schedules and other features of childhood and adolescence. Analysis was restricted to records after January 2015 when routine viral load testing was scaled up nationally and no longer limited to use in cases suspected of treatment failure.External validation was conducted using data from the Partners Demonstration Project, an open label evaluation of PrEP effectiveness among 1013 HIV serodiscordant couples that ran from November 2012 to December 2015 . CouplesOur goal was to design a risk scoring tool that delineates between people likely and unlikely to be virally suppressed 18 months after ART initiation using 3 to 10 predictors routinely captured during client intake appointments. The primary outcome was unsuppressed viral load, defined as ≥1000 copies/mL, at 18 months after ART initiation. For persons with multiple viral load results, we used the first viral load documented within the 18-month window. We used univariate logistic regression models to identify enrollment characteristics, medical and HIV treatment characteristics, and family characteristics associated with unsuppressed viral load after 18 months on ART. These included demographic characteristics , clinical factors , and behavioural factors . The list of variables considered were derived from data routinely collected during clinic visits of HIV patients, particularly focusing on data collected at enrollment into the ART clinic. Continuous variables were grouped into categories based on clinically relevant cutoffs. All factors associated with unsuppressed viral load in univariate analysis with a p-value of <0.10 were combined into a multivariate logistic regression model and a stepwise sequence selection procedure used to identify the combination of variables that best predicted unsuppressed viral load with the lowest Akaike Information Criterion (AIC). To derive the score value for each level of each predictor, each coefficient from the final multivariate logistic model was divided by the lowest coefficient among all predictors and rounded to the nearest integer. To improve the precision of the predictive score, we ran the model through multiple iterations using adjusted grouped categories for continuous variables and tested various cutoff points for each predictor. We used receiver operating curves to estimate the area under the curve (AUC) and to analyze the predictability of the final multivariate model and score and determine the score cutoff that best balances sensitivity and specificity.We used a 10-fold cross validation technique to internally validate our model. External validation was done by applying the risk scoring tool to baseline data from each participant living with HIV in the Partners Demonstration Project and calculating their score. We then looked across scores to determine if the score accurately predicted unsuppressed viral load among individuals in the Partners Demonstration Project. All analyses were conducted using STATA version 13.1 .The Kenyatta National Hospital Ethics Review Committee approved the study protocol (P66/7/09/2016). The Partners Demonstration Project protocol was approved by the Kenya Medical Research Institute ethical review board and the University of Washington Human Subjects Review Committee.The datasets were cleaned to remove duplicates and merged to exclude records of persons who did not have viral load data or biodata resulting in a total of 28,113 people retained. Of these, records were excluded if the person was aged <18 years (632 people) or had their first viral load measurement conducted more than 18 months post-ART initiation . The final dataset for score derivation included data from 3,968 individuals . Of thesUnivariate analysis identified seven variables for inclusion in the multivariate analysis . Of thesWe calculated the total risk score of each individual by summing the individual parameter scores determined in the final risk model. The AUC for the probability of the risk score to correctly predict unsuppressed viral load was 0.55 (95% CI: 0.52 to 0.56). Internal cross-validation showed the average AUC for 10 subsets analyzed was 0.55 (95% CI: 0.49–0.57), similar to the AUC of the full data set and indicating robust generalizability of the risk algorithm within the data set. A cutoff of 22 was determined to be optimal for balancing sensitivity and specificity when identifying persons with unsuppressed viral load. Using the cutoff risk score of ≥22, we identified 55% of people who were not virally suppressed from 63% of the population. For external validation, we applied our risk score to the Partners Demonstration Project. The AUC for the risk score applied to participants of the Partners Demonstration Project was 0.56 (95% CI: 0.48 to 0.57).Results from this analysis have shown that baseline empirical data collected routinely in treatment centers within the Kenya public health system can be used with modest accuracy to predict unsuppressed viral load among individuals accessing ART 18 months after initiation. The predictors selected for our score are well-established variables that are routinely collected in clinical settings: age, sex, BMI, number of years of school, HIV disclosure status, and duration of time between HIV diagnosis and starting ART. These variables, in combination, were more predictive of unsuppressed viral load than each individual factor alone. Viral load suppression is mostly influenced by adherence to ART thus our risk score is likely to be useful in determining differentiated care models for persons who may be challenged with sustained ART adherence.Similar risk scores have been established for patients accessing care in developed countries using a combination of self-reported adherence, clinical and bio-behavioural predictors ,13. HoweBefore the COVID-19 pandemic, patients with good ART adherence during the first year of ART use were seen with the same frequency as those experiencing adherence challenges and could only be switched to less frequent visits after one year of consistent ART use and confirmed viral load suppression, an approach that fails to maximize clinic resources and patients’ time. During COVID-19, however, DCM was more widely implemented in response to recommendations to reduce person-to-person contact. Patient appointment schedules were revised to include >3 months between clinic visits and to minimize contact with healthcare providers by distributing at least 3 months of ART for all patients regardless of their viral load or duration on treatment . Thus, tWe did not specifically investigate the causes of delay in viral load testing beyond 18 months for individuals whose data were excluded from this analysis as it was beyond the scope of this work. However, based on other published reports, delays are likely related to individual and systemic issues, with individual reasons including lack of treatment literacy leading to poor adherence to visit schedule, long distance to medical facility, lack of time off from work, and limited financial resources –18. SystThough our study was derived from a large dataset of individuals from across Kenya, the AUC was 0.55, which is only a modest level of prediction. A limitation of our analysis was that behaviour, lifestyle and other factors known to influence adherence were not available to use since these are not collected on the MOH247 form. These factors may be important for the healthcare providers to consider in complement to the prediction adherence tool to select patients for differential visit scheduling. Understanding that adherence to ART is a nuanced behaviour, further work needs to include qualitative research to explore psychosocial factors influencing adherence and acceptability of our prediction tool. Another limitation of our study is that the dataset provided from the KenyaEMR had a high level of incompleteness in some variables resulting in high drop-off of total records available for use, which is similar to other studies using routinely collected national data, and an inherent source of bias. However, our validation models were based on a dataset with a very low level of missing data and thus was ideal in determining whether our scoring tool accurately identified individuals who fail to become virally suppressed within 18 months after initiating ART.In summary, approaches that restructure ART delivery with a focus on the likelihood of adherence are needed to minimize clinic-based bottlenecks and improve patient care. Our risk score modestly predicts unsuppressed viral load and can be used to tailor patient visit schedules, counseling and adherence monitoring. Use of the model would yield a more efficient clinic system that identifies individuals early on who would benefit from more frequent interactions with healthcare providers, while supporting those with predicted suppression to maintain less frequent interactions and for the clinic to benefit from reduced clinic volume, decreased waiting time, and improved patient flow. However, further research would be needed to determine the feasibility and effectiveness of this score in clinical settings as well as the cost implications.


On the basis of all tests performed during the study period, persistently undetectable plasma HIV RNA (PUD) was found in 66 patients, low-level viremia (LLV) in 57 and ongoing viremia (OV) in 61. Serum levels of IgG antibodies against a trimeric S-protein antigen were tested with DiaSorin Liaison SARS-CoV-2 TrimericS IgG and the response was classified as optimal (>75th percentile), intermediate (50th–25th percentile) and low (<25th percentile). The frequencies of the three different patterns of plasma HIV viremia  were comparable in patients with low, intermediate and optimal IgG response evaluated at T2, with no difference in overall CD4+ cell count or nadir count. At T3, 92.9% of patients achieved an optimal response: T2 response proved to be the most important factor in predicting T3 optimal response in patients with LLV and OV.A nadir value ≤ 330 cells/mm3 had 100% sensitivity in predicting a non-optimal response. In conclusion, we demonstrated the persistence of anti-spike IgG, with high serum levels occurring in most patients six months after the third dose of the BNT162b2 mRNA vaccine and a predictive role of humoral response at T2 in subjects with detectable plasma HIV viremia. Immunological alterations related to past immunodeficiency may persist despite immune reconstitution, and the nadir value could be a useful tool for elaborating personalized vaccine schedules.We investigated the spike IgG levels of HIV+ patients on antiretroviral therapy six months after they received their second dose (T2) and six months after the third dose (T3) of the BNT162b2 mRNA vaccine, as well as the influence of different levels of plasma HIV viremia of overall CD4+ cell count and nadir value on the humoral time course. One hundred eighty-four patients were enrolled. The median age was 55 years, the median CD4+ cell count was 639 cells/mm For three years, the world has been challenged by the coronavirus disease 2019 (COVID-19) pandemic, and a tremendous global effort has been made to tackle it. At the same time, we face other major health threats, such as infection with the human immunodeficiency virus (HIV), which is a disease affecting approximately 38 million people [3 and as <350 cells/mm3) [3 [3 is described only in the case of detectable plasma HIV viremia (>50 copies/mL) [The complexity of HIV infection may explain its multifaceted influence on SARS-CoV-2 infection outcome. HIV infection is an independent risk factor for both severe COVID-19 at admission and in-hospital mortality , and it /mm3) [3  and the /mm3) [3  and are /mm3) [3 , and thepies/mL) . Taken tpies/mL) ,12. Resipies/mL) ,14,15.The aims of the study were to evaluate the time course of the response of IgG antibodies to SARS-CoV-2 spike protein six months after the second and third vaccine doses in HIV patients in a real-life setting and to describe possible correlations with CD4 + cell count and plasma HIV viremia.Eligible patients were HIV-1-positive adults on successful antiretroviral therapy (ART) who had been vaccinated with three doses of the BNT162b2 mRNA vaccine. Individuals with a prior laboratory-confirmed COVID-19 or anamnestic data suggesting a possible SARS-CoV-2 infection not further evaluated were excluded. No other exclusion criteria were applied.Parameters evaluated at enrollment (before the first vaccine dose) were gender, age, age at the diagnosis of HIV infection, CD4+ cell count at nadir (the person’s lowest CD4+ cell count) and ongoing ART.CD4+ cell count and plasma HIV viremia were evaluated at three study points: before the first vaccine dose, 6 months after the second vaccine dose (T2) and 6 months after the third vaccine dose (T3). CD4+ cell count was analyzed using two variables; the first corresponded to the mean CD4+ count values evaluated before the first vaccine dose, at T2 and at T3 and it was defined overall CD4+ cell count, and the second variable corresponded to the difference between overall CD4+ cell count and CD4+ cell count at nadir, and it was called delta CD4+ count.Patients were classified as having persistently undetectable (PUD) plasma HIV viremia if the plasma value was undetectable in all tests performed; low-level viraemia (LLV) if no plasma HIV-RNA value was >20 copies/mL; and ongoing viremia (OV) if at least one plasma value was >20 copies/mL. In this last category of patients, the occurrence of blips : 50–499 copies/mL between measurements <50 copies/mL) was also evaluated .The study received approval from the Comitato per la Sperimentazione Clinica di Treviso e Belluno (protocol code 812/2020), and written informed consent was obtained from all the patients enrolled.Serum levels of IgG antibodies against a trimeric S-protein antigen were tested 6 months after the second and third vaccine dose with DiaSorin Liaison SARS-CoV-2 TrimericS IgG , an indirect chemiluminescence immunoassay, in accordance with the manufacturer’s instructions .The IgG titers were expressed in binding antibody units (BAUs). Samples with values < 33.8 BAU/mL were considered negative. The lower limit of detection was 4.81 BAU/mL, which was scored as 2 for statistical analysis, while a value > 2080 BAU/mL (the higher limit of quantification) was scored as 2080 for statistical analysis.The patients were classified according to IgG value after the second vaccine dose, as follows: optimal responders , intermediate responders  and low responders . The value limit applied for the second dose was also applied to the serum IgG values tested six months after the third vaccine dose.p < 0.05. Statistical analyses were performed with MedCalc® Statistical Software version 20.111  and with Stata v. 17.0. .Continuous variables  were evaluated as the median and interquartile ranges. The Mann–Whitney U test was used to test the significance of differences in the median between groups of patients. Differences in proportions were calculated with the chi-squared test and Fisher’s exact test as appropriate. Sensitivity and specificity of continuous variables were determined by receiver operating characteristic curve analysis. Among the categorical variables, IgG responses at T2 and T3 (as defined in 3 (IQR 486–845 cells/mm3). A total of 118 subjects (64.1%) were on triple therapy. HIV viremia control was equally distributed in the study population . In total, 15 (24.6%) of the 61 patients with OV had at least 1 plasma HIV RNA value > 50 copies/mL, while only 4 subjects (6.6%) had a value higher than 100 copies/mL. Viral blips occurred in 18 subjects . The frequency of patients with an IgG serum level > 2080 BAU/mL was significantly higher at T3 . A complete description is reported in One hundred eighty-four patients were included in the study. The median age at enrollment was 55 years and the median overall CD4+ cell count was 639 cells/mm3 .Seroconversion was achieved in almost all patients at T2 and at T3 . Of note, all three subjects negative at T2 had an overall CD4+ cell count lower than 500 cells/mmAt T2, the higher limit for the first quartile was 148 BAU/mL and the lower limit for the fourth quartile was 651 BAU/mL. Median values and IQR were 102 BAU/mL (69–119 BAU/mL) in low responders, 285 BAU/mL (228–418 BAU/mL) in intermediate responders and 1650 BAU/mL (1000–2080 BAU/mL) in optimal responders. 3 was found only in patients with OV and a low response. The data are detailed in The frequencies of the three different patterns of plasma HIV viremia  were comparable in patients with low, intermediate and optimal IgG responses at T2. No difference in median CD4 cell count at nadir or in median overall CD4 cell count was found between patients with low, intermediate or optimal IgG responses at T2 within the same plasma HIV RNA figure: A median value of overall CD4 lower than 500 cells/mmLogistic regression analysis was performed to investigate if CD4+ cell count, CD4+ cell count at nadir and the CD4+ delta value could predict IgG response at T2. No predictor emerged in this phase. Data are summarized in p = 0.011 with respect to none in patients with intermediate response at T2). An optimal response was confirmed at T3 in 100% of the patients with an optimal response at T2, in 95.7% of the patients with an intermediate response at T2 and in only 80.4% in the case of patients with a low response at T2 (0.002536) . A low response was found in only four patients, all of whom had a low response at T2 (.002536) .3 and an overall CD4+ count of 150 cells/mm3 and LLV, and he was on treatment with dolutegravir and lamivudine.Only one patient did not achieve seroconversion at T3; he was a 72-year-old male with a nadir cell count of 34 cells/mm3, IQR 376–820 cells/mm3 vs. 644 cells/mm3, IQR 382–1019 cells/mm3, p = 0.4058 and 178 cells/mm3, IQR 91–300 cells/mm3 vs. 305 cells/mm3, IQR 165–424 cells/mm3, p = 0.0592, respectively).The median value of overall mean CD4 cell count and CD4 count at nadir were lower in the 9 patients with a low response at T2 that did not achieve an optimal response compared to the 37 patients who had succeeded ; the corresponding logistic model describes the probability of optimal T3 response in these patients.  and an optimal response . The relative frequency of an IgG value >2080 BAU/mL with respect to the other IgG values included in the 75th percentile was 54% in subjects with a previously low response, 70.5% in the case of a previously intermediate response and 78.3% when an optimal response was confirmed at T3 (p = 0.02 with respect to low response)  was found in patients with an optimal response at T2. Conversely, the lowest frequency was found in patients with a low response at T2 (43.5%), being significantly lower than the frequency in patients with an intermediate response at T2  .The frequency of patients with PUD, LLV and OV was comparable in patient cohorts with different longitudinal evolutions of IgG response at T3; the numerosity of each group is extremely different, but patients with OV were included in all cohorts with a frequency ranging from 25% to 50% .3 and/or a previous AIDS diagnosis at the first vaccine dose per protocol in the work of Vergori et al. [3 in the other studies [In this study, we investigated the spike IgG levels of HIV+ patients on antiretroviral therapy six months after they received their second dose (T2) and six months after the third dose (T3) of the BNT162b2 mRNA vaccine, as well as the influence of different levels of plasma HIV viremia of overall CD4+ cell count and nadir value on the humoral time course. First, we observed high IgG serum levels in 92.9% of patients six months after the third dose, and only one subject confirmed failed seroconversion at T2. A few works reported data for HIV patients receiving mRNA-based vaccines; the efficacy of the third dose was confirmed in all reports, but the study designs differed from ours in terms of patient characteristics, the interval between third dose, and antibody testing. HIV patients had a median CD4+ cell count <200 cell/mmi et al.  and a me studies . The tim studies ,20,21, a studies ,20.Previous studies reported no correlation between undetectable plasma HIV viremia, conventionally defined as plasma HIV RNA lower than 20 copies/mL  or 30 coInterestingly, we observed that serum IgG level at T2 proved to be the most important factor predicting optimal response at T3 in patients with LLV and with OV but not in patients with PUD; this is the second main result of the study. Detectable plasma HIV viremia played a role in counteracting the peak antibody response even in the case of minimal viral burden; this result may be explained by the expansion of functionally exhausted tissue-like memory B cells, which is associated with chronic HIV viremia . These cThe interplay between plasma HIV viremia and humoral response was also studied with a focus both on vaccine-related immunological activation and vaccine efficacy; potential vaccine-related viral blips were reported with a frequency of up to about 9% ,29,30 ; however, they had a median value of 427 cells/mm3, which is more than double the threshold of 200 CD4+ cells/mm3 associated with a low humoral response to the COVID-19 vaccine [The overall CD4+ cell did not influence evolution of humoral response from T2 to T3. The CD4+ cell count reflects the immunocompetence level , and the vaccine ,33. 3 had 100% sensitivity in predicting a non-optimal response after the last vaccine dose. The significance of the nadir value as a factor predicting response to the COVID-19 vaccine is crucial because it expresses past immunodeficiency and could be the only routine clinical data available for this evaluation in high-income countries, where almost all patients have a current CD4 count >500 cells/mm3 due to ongoing ART. The generation of a vaccine-induced humoral response requires cooperation between antigen-primed B cells and T-follicular helper cells; advanced HIV disease is associated with alterations in B cells and T-helper cells, and immune reconstitution post-ART would be incomplete with the presence of activated and immature B cells in peripheral blood, apoptotic B cells in lymph nodes and circulating T-helper follicular cells with poor survival and function [Conversely, the CD4 cell count at nadir was lower in subjects with a low response after the second dose, evolving to a low or intermediate response after the following dose , and a nadir value ≤330 cells/mmfunction ,35. Nadifunction  found nofunction  or El Mofunction  after anfunction , but cauOur study has three main limitations. Firstly, previous SARS COV-2 infection was excluded on clinical basis and not by testing anti N SARS-CoV-2–specific test. However, not only was this approach already used in other works , but alsWe demonstrated HIV patients’ persistence of anti-spike IgG, with high serum levels being demonstrated in most patients, six months after the third dose of the BNT162b2 mRNA vaccine and the predictive role of the humoral response after the second dose in patients with LLV and OV. Our results may help to formulate more stringent recommendations and motivate patients to accept further vaccine doses. Immunological controls are needed to check the persistence of responses and could help in designing vaccination strategies for selected patients, who could be better identified by multiple plasma HIV viremia tests. Further studies evaluating the IgG time course after the fourth dose or in the case of breakthrough COVID-19 may help elucidate the influence of HIV viremia detectability.