The efficacy and tolerability of an antiretroviral regimen are important considerations for selection of HIV-1 infection maintenance therapy. Abacavir/lamivudine plus rilpivirine (ABC/3TC + RPV) has been shown in international studies to be effective and well-tolerated in virologically suppressed individuals. This study evaluated the effectiveness and safety of switching to ABC/3TC + RPV as maintenance therapy in virologically suppressed HIV-1 infected individuals in Singapore.In this retrospective, single-centre study, we included individuals who were prescribed ABC/3TC + RPV, had HIV-1 viral load (VL) < 50 copies/ml immediately pre-switch, and had no documented history of resistance mutations or virologic failure to any of the components. The follow-up period was 48 ± 12 weeks. The primary outcome was the proportion of individuals who maintained virologic suppression of HIV-1 VL < 50 copies/ml at the end of follow-up period based on on-treatment analysis. The secondary outcomes were the resistance profiles associated with virologic failure, changes in immunologic and metabolic parameters, and the safety profile of ABC/3TC + RPV.A total of 222 individuals were included in the study. The primary outcome was achieved in 197 individuals . There were 21 individuals (9.5%) who discontinued treatment for non-virologic reasons. The remaining 4 individuals experienced virologic failure, of whom, 3 of these individuals had developed emergent antiretroviral resistance and had HIV-1 VL > 500 copies/ml at the end of the 48 ± 12 weeks follow-up period. The remaining individual experienced sustained low level viremia and subsequently achieved viral suppression without undergoing resistance testing. A total of 49 adverse events were observed in 31 out of 222 individuals (14.0%), which led to 13 individuals discontinuing therapy. Neuropsychiatric adverse events were most commonly observed (53.1%). A statistically significant increase in CD4 was observed (p < 0.01), with a median absolute change of 31 cells/uL (interquartile range: − 31.50 to 140.75). No significant changes in lipid profiles were detected.ABC/3TC + RPV is a safe and effective switch option for maintenance therapy in virologically suppressed HIV-1 individuals with in Singapore.The online version contains supplementary material available at 10.1186/s12981-021-00402-7. Modern combination antiretroviral therapy (ART) regimens have generally demonstrated potency and efficacy in achieving virologic suppression . Owing tThe current standard for HIV treatment is combination ART, which comprise of two nucleos(t)ide reverse transcriptase inhibitors (NRTI) as backbone, paired with a third agent from another class, including integrase strand transfer inhibitors (INSTI), non-nucleoside reverse transcriptase inhibitors (NNRTI), or protease inhibitors (PI) . TenofovThe SIMRIKI retrospective study has demonstrated the long-term effectiveness and safety of ABC/3TC + RPV as a switch therapy with a follow-up period of up to 48 weeks . The resThe aim of this study was to evaluate the effectiveness and safety of switching to ABC/3TC + RPV as maintenance therapy for virologically suppressed HIV-1 infected individuals in Singapore.This study was a retrospective, single-centre evaluation conducted at National Centre for Infectious Diseases (NCID), which provides HIV care for the majority of HIV-infected individuals in Singapore. The study was conducted between June 2014 and September 2018. Approval from Domain Specific Review Board of the National Healthcare Group (Reference Number: 2012/00438-SRF0006) was obtained prior to study commencement.The inclusion criteria were as follows: (i) documented HIV-1 infection, (ii) age ≥ 18 years, (iii) use of combination of ABC/3TC (600/300 mg fixed dose combination once daily) plus RPV (25 mg once daily) as maintenance therapy between June 2014 and September 2018 inclusive, (iv) virologically suppressed  < 50 copies/ml) immediately before switching to ABC/3TC + RPV, and (v) no documented history of resistance mutations or virologic failure to ABC, 3TC, FTC or RPV. Exclusion criteria were CD4 count < 200 cells/uL and pregnancy. As adherence could not be determined for individuals who either obtained external supply of ART with no pharmacy dispensed records and/or with erratic clinic attendance, individuals with proportion of days covered (PDC) for adherence of < 95% were also excluded. PDC was calculated by the following formula: [Number of days with medication supply in study period / number of days in the study period] × 100, capped at 100%. PDC is a known, validated and stringent measure of adherence , 18. TheEligible individuals were identified from the NCID HIV Clinical Database, a standardised computerised database containing records of demographic information, HIV transmission route, and ART history. Data collected from electronic medical records included AEs attributed to ART, reasons for ART switch, and other laboratory readings which were not available on the Clinical Database. Data were anonymised upon extraction. Intervals for follow-up were determined by individual attending physicians per in-house clinical care guidelines.The primary outcome measured was the proportion of individuals who maintained virologic suppression on ABC/3TC + RPV after 48 ± 12 weeks of follow-up and had no therapy discontinuation due to non-virologic reasons such as adverse drug reactions. Individuals were considered to have maintained virologic suppression if they had no virologic failure. Virologic failure was defined as: (i) 2 consecutive HIV-1 VL readings of > 50 copies/ml, (ii) any HIV-1 VL > 50 copies/ml that resulted in discontinuation of ABC/3TC + RPV, or (iii) any HIV-1 VL reading of > 500 copies/ml. This definition for virological failure is similar to the SIMRIKI study, :35–57). Majority of the individuals were men (92.3%). The composition of pre-switch NRTI backbone (in combination with either 3TC or FTC) was as follows: TDF (60.8%), ABC (27.0%) zidovudine (10.3%), and stavudine (1.9%). The most common pre-switch third agents were efavirenz (42.3%) among the NNRTI, atazanavir/ritonavir (13.5%) among the PI, and raltegravir (6.8%) among the INSTI. Fifty-two (23.4%) individuals already had RPV as their third agent prior to switch. The most common pre-switch combination was TDF + 3TC + RPV, which accounted for 45/222 (20.3%) of all pre-switch regimens. Intolerance (52.7%), cost (29.7%), and simplification of regimen (23.4%) were the most common reasons cited for switching regimen. Thirty-one individuals (14.0%) had no documented reason for switch.The primary outcome was achieved in 197 out of 222 individuals . For patients with an immediate pre-switch history of PI or INSTI-based treatment, 47 out of 56 individuals  achieved the primary outcome. For patients with an immediate pre-switch history of NNRTI-based treatment, 150 out of 166 individuals  achieved the primary outcome.Four individuals 1.8%) had virologic failure . This individual later achieved virologic suppression without the need to change regimen after the study period.Of the 4 individuals who experienced virologic failure, 3 individuals had HIV-1 VL > 500 copies/ml at the end of the study period and developed emergent antiretroviral resistance. The first individual experienced virologic failure on the 52Among the 21 individuals who discontinued treatment for non-virologic reasons, 13/21 (61.9%) were due to AEs attributed to ABC/3TC + RPV. The details of these AEs that led to discontinuation are reported in Additional file 2 (IQR: − 14.06 to + 5.27), while no significant change was detected for eCrCl (p = 0.463), with a median absolute change of − 0.79 ml/min (IQR: − 8.81 to + 7.97). Additional details on the stratification of eGFR results at baseline and at the end of the follow up period are reported in Additional file Data obtained on changes in the selected laboratory values over the study duration are summarized in Table Our results showed that a high proportion of individuals (88.8%) who switched to ABC/3TC + RPV had maintained virologic suppression. The result is similar regardless of the type of pre-switch ART regimen. Virologic suppression was achieved in 83.9% of individuals with an immediate pre-switch history of PI or INSTI-based treatment, and 90.4% of individuals with an immediate pre-switch history of NNRTI-based treatment. In several studies in Spain, 86–88% of HIV-1 infected individuals maintained virologic suppression and avoided therapy discontinuation at 48 weeks or 12 months –15. The A local study found that 96% of treatment naïve HIV-1 infected individuals achieved virologic suppression at the end of 48 weeks of treatment with ABC/3TC + RPV,  which waAEs were observed amongst 31/222 individuals (14.0%) and resolved either spontaneously or upon discontinuation of the medication. These results were comparable to the favourable results of SIMRIKI study,  as well Our cohort had a significant improvement of absolute CD4 count at the end of the 48 ± 12 weeks follow-up. The increase in the CD4 count can possibly be attributed to maintained virologic suppression, and was also seen in other switch studies with increases ranging from + 48 to + 262 cells/uL –15.2 in eGFR or − 1 ml/min in eCrCl is unlikely to affect the staging of chronic kidney disease or acute kidney injury. We also observed a statistically significant decrease in ALT, but the magnitude of the change is clinically insignificant, [We observed a statistically significant decrease in eGFR but not in eCrCl. The median absolute changes in eGFR and eCrCl were deemed to be of little or no clinical relevance , 23, as ificant,  as the mificant, –16.While no statistically significant changes were detected for lipids, fasting blood glucose and HbA1c, the results warrant careful interpretation due to the small number of individuals with both baseline and follow-up values. Remarkably, the SIMRIKI study and the studies by Curran et al. and Palacios et al. all noted significant decreases in total cholesterol and LDL-C, as well as increases in HDL-C –14. HoweOur study has several limitations. The absence of a control group prevented us from comparing the effectiveness and safety in individuals who would have continued with the prior regimen. We did not have access to baseline resistance testing information for our study population. As we excluded individuals who were < 95% adherent by PDC, our findings may not be generalizable to individuals with suboptimal adherence or who are compliant to ART despite irregular clinic attendance or who purchase external supplies of ART. Compliance to these medications will remain a key clinical prerequisite to therapy success. In practice, it will be crucial to take into account the relatively low genetic barrier to resistance and the ability of the individual to adhere to the caloric requirements of RPV when selecting this regimen. The frequency of adverse events may also have been under-reported, as only adverse events that were reported and explicitly attributed to the regimen in clinical documentation were included in the study.In conclusion, this study shows that ABC/3TC + RPV is an effective and safe switch option for maintenance therapy in virologically suppressed HIV-1 individuals in Singapore.Additional file 1: Table S1. Details of 4 individuals who failed the primary outcome for virological reasons. Table S2. Details of 21 individuals who failed the primary outcome for non-virological reasons. Table S3. Breakdown of All AEs. Table S4. Changes in eGFR stratificationA from baseline to end of follow up period (n=139)


The HIV pandemic continues to cause a high burden of morbidity and mortality due to delayed diagnosis. Histoplasmosis is prevalent in Latin America and Colombia, is difficult to diagnose and has a high mortality. Here we determined the clinical characteristics and risk factors of histoplasmosis in people living with HIV (PLWH) in Pereira, Colombia.This was a retrospective cross-sectional study (2014–2019) involving two tertiary medical centers in Pereira, Colombia. People hospitalized with HIV were included. Histoplasma antigen detection was performed in urine samples. Probable histoplasmosis was defined according to European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group/National Institute of Allergy and Infectious Diseases Mycoses Study Group criteria.172 HIV-infected patients were analyzed. Histoplasmosis was confirmed in 29% (n = 50/172) of patients. The logistic regression analysis showed that the risk factors for histoplasmosis were pancytopenia , < 50 CD4 + cells/μL  and Aspartate transaminase (AST) levels > 46 IU/L .Histoplasmosis is highly prevalent in hospitalized patients with HIV in Pereira, Colombia. The clinical findings are nonspecific, but there are some clinical abnormalities that can lead to suspicion of the disease, early diagnosis and prompt treatment. Urine antigen detection is useful for diagnosis, but is not widely available. An algorithmic approach is proposed for low-resource clinical settings. Histoplasma capsulatum is found primarily in soil containing bird excreta or bat guano. The disease begins when microconidia or small hyphal elements are inhaled and convert to yeasts in the lungs, or when organisms in previous quiescent foci of infection are reactivated during immunosuppression [H. capsulatum may cause a disseminated and potentially fatal disease in immunosuppressed patients (Progressive Disseminated Histoplasmosis) [Endemic mycoses are frequently found in Latin America where they represent a silent threat to public health. In Colombia, histoplasmosis is not a mandatory reporting entity, so, the burden of the disease is unknown. Despite its importance, clinical and epidemiological data remain scarce . Histoplpression , 2. H. casmosis) , 3.The prevalence of histoplasmosis across the geography of Latin America is consistently high . The disProbable Histoplasmosis according to the Consensus Definitions of Invasive Fungal Disease from the European Organization for Research and Treatment of Cancer and the Mycoses Study Group (EORTC/MSG) [A retrospective cross-sectional study was carried out aimed at establishing the clinical/laboratory characteristics, the prevalence and the risk factors for histoplasmosis in PLWH who were hospitalized in two tertiary centers in the city of Pereira, Colombia. The city is located in the Andean natural region of Colombia . The patients in this study meet the criteria for RTC/MSG) , 13.Universidad Tecnológica de Pereira. Patients hospitalized with an HIV diagnosis between May 2014 and April 2019 were identified from the database of both centers, followed by review of electronic patient medical records. All adult (≥ 18 years old) patients with documented HIV infection were candidates for inclusion in the study, if they were hospitalized for a clinical suspicion of an AIDS-defining disease like histoplasmosis based on clinical manifestations and laboratory findings such as the following: fever and/or weight loss , cough, diarrhea, miliary opacities on thorax imaging, pancytopenia, lymphadenopathy, splenomegaly and/or hepatomegaly and abnormal liver function test, ferritin and lactic dehydrogenase (LDH) serum levels. The presence of co-infections and AIDS-defining conditions was established. Demographic and clinic information were extracted using standardized data collection sheets.This was a retrospective cross-sectional study conducted in two tertiary centers in the city of Pereira, Colombia: the “San Jorge” University Hospital (SJUH) and the “Los Rosales” Clinic (LRC). The SJUH is a major public hospital in Pereira. It is equipped with over 200-beds. The LRC is a tertiary clinic equipped with over 100-beds. The study was approved by the Ethics Committee of the H. capsulatum in tissue biopsies. The diagnosis of histoplasmosis was made based on the recommendations of the EORTC/MSG [no histoplasmosis group.A case of histoplasmosis was defined as an HIV-patient who had a urinary antigen elevated above the cut-off point of the reference laboratory and/or histological findings of mycotic forms compatible with ORTC/MSG , 13. PatCryptococcus spp was evaluated, when appropriate, by India ink stain and Cryptococcus latex agglutination test. Other laboratory tests included complete blood cell count, liver function tests, renal function tests, ferritin levels, CD4 + cell count, HIV viral load, and LDH levels. Chest X-rays and chest CT scans were performed, as well as abdominal ultrasound and abdominal CT scan, when appropriate.Specimens analyzed included blood, urine, lymphatic nodes or gastrointestinal biopsies depending on the patient’s presentation. All tissue biopsies were stained with Giemsa, Gram, and Ziehl–Nielsen and were cultured for bacteria, mycobacteria, and fungi. The culture medium for fungi used were Mycosel and Sabouraud. Histoplasma antigen detection in urine was performed, mostly, by IMMY's antigen enzyme immunoassay, in a reference laboratory. Mycobacterium tuberculosis was detected with Ziehl–Neelsen stain, culture or PCR. In some patients, the presence of T tests were performed. Non-parametric tests were used for those that did not fulfill the assumptions of normality (Wilcoxon or Man Whitney’s U). A logistic regression analysis was constructed. All associations were considered significant for a value of P < 0.05. Variables with P < 0.10 were included in the model and remained in the final model if P < 0.05. IBM SPSS Statistics software version 20 was used for all statistical analyses. The diagnostic performance of risk factors for histoplasmosis in PLWH was determined in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+ LR) and negative likelihood ratio (− LR).We used descriptive statistics to analyze and report data. The Kolmogorov–Smirnov test was performed to assess for normal distribution. Baseline characteristics were compared using Chi-square or Fisher’s exact tests, when appropriate, for categorical variables. For continuous data, the assumptions of normality were verified and for those that fulfilled them, Student’s H. capsulatum polysacharide antigen in urine and 29% (n = 50) of them were diagnosed as histoplasmosis based on the EORTC/MSG statements [H. capsulatum in peripheral blood smear. Another three patients had a report of fungal forms of H. capsulatum in colon biopsies. A total of 122 (70%) patients were negative for Histoplasma antigen in urine (no histoplasmosis group). PCR tests for histoplasmosis were not performed as they were not available in our area. Figure Histoplasmosis was suspected in 172 patients based on their clinical and laboratory characteristics. All inpatients were evaluated by an internal medicine physician or an infectious diseases physician. All patients underwent EIAs to detect atements , 13. Onegroup was more likely to receive antifungal therapy  primarily based on amphotericin B deoxycholate, without significant increase of episodes of acute kidney injury . There was no difference in terms of in-hospital death . The H-Score was higher in the histoplasmosis group , but there were no confirmed cases of hemophagocytic lymphohistiocytosis. There were no cases of viral hepatitis.The mean age was 41 years old, 76% were men, and 79% came from urban areas. Half of the patients had HIV de novo and only 16% of the patients had received antiretroviral treatment in the past. Most of the patients were in AIDS category 3 (87%) and C (77%). The CD4 + cell count was lower in the histoplasmosis group compared to the “no histoplasmosis” group . AIDS Category 3 was more frequent in the histoplasmosis group than in the no histoplasmosis group . Other AIDS-defining conditions were prevalent, mainly Tuberculosis and Toxoplasmosis. There was only one case of Cryptococcosis. Toxoplasmosis was more frequently found in the no histoplasmosis group . The histoplasmosis group compared to the no histoplasmosis group , probably explained by the higher prevalence of toxoplasmosis in the no histoplasmosis group. Some laboratory abnormalities were more common in the histoplasmosis The multivariable logistic regression analysis included the variables with P-value of < 0.10 (see Table 200 CD4 + cells/μL showed the highest sensitivity and a high NPV (> 90%) for the diagnosis of histoplasmosis. For these reasons we decided to explore the performance of two combined variables (in order to find simple strategies to reach a presumptive diagnosis of histoplasmosis in low-resource contexts). Elevated AST plus < 200 CD4 + cells/μL showed a sensitivity and NPV of 100%, with 0% false negatives, but the specificity was very low (11%) and the false positives very high (88%), implying that the combination of both tests are only useful to rule out histoplasmosis if the patient has > 200 CD4 + cells/μL and normal AST transaminase levels. The combination of Pancytopenia plus < 50 CD4 + cells/μL showed a sensitivity of 84%, but a low specificity (57%). None of the tests analyzed has a good balance between sensitivity and specificity. The only variable with a good + LR and good specificity was pancytopenia. See Tables A less than 200 CD4 + cells/μL (AIDS category 3) was more frequently found in histoplasmosis group than no histoplasmosis group . In an exploratory way, having < We had described the main characteristics of histoplasmosis in hospitalized PLWH. The incidence of histoplasmosis was very high, the patients included in the study had very low rates of self-awareness of their HIV status and prior anti-retroviral treatment. The viral load was very high in both groups and they were quite immunosuppressed, reflecting a very long course of HIV disease. It became clear that there is an inversely proportional relationship between the CD4 + cell count and the incidence of histoplasmosis , 15. ThiCaceres et al. showed that PLWH with histoplasmosis have increases in transaminases and a decrease in hemoglobin concentration [Samayoa et al. found that CD4 + cell count, platelet count and hemoglobin levels are significantly lower in histoplasmosis-cases than non-cases. On the other hand, LDH levels, serum AST levels, bilirubin levels and alkaline phosphatase (ALP) were significantly higher in histoplasmosis-cases than non-cases [Falci et al. in Brazil demonstrated that < 50 CD4 + cells/μL, pancytopenia, miliary pattern on thorax imaging, hepatomegaly, generalized lymphadenopathy and LDH > 1000 IU/L, are factors that may aim for the prediction of Probable/Proven histoplasmosis [The spectrum of symptoms and laboratory abnormalities that we found are similar to that reported elsewhere , 16, 17.ntration . Samayoalasmosis .Histoplasmosis must be recognized and treated promptly, unfortunately the main symptoms, signs and laboratory abnormalities that could raise its suspicion are nonspecific. The clinical and laboratory characteristics found by us are somewhat consistent with what has been reported elsewhere , 18, 19,Histoplasmosis is a common opportunistic infection in hospitalized PLWH and is associated with high mortality , 20, 21.Paracoccidioides brasiliensis, Blastomyces dermatitidis, Coccidioides immitis, and Penicillium marneffei [Penicillium marneffei are not endemic in Colombia and belong to other geographical areas [This study had some limitations. First, the results were obtained retrospectively from two centers in the same city, which may limit the generalization of the results to a more extensive geographic context, however our data are in line with other reported analyses. Second, we concentrate our analysis to a mainly AIDS population, therefore the extrapolation of the results to immunosuppressive diseases other than HIV may not be suitable. Third, the EORTC/MSG expert consensus , 13 warnarneffei . Howeveral areas , 24. Par


Besides its contribution in the treatment of Human Immunodeficiency Virus-infected patients, anti-retroviral drugs may also cause mild to serious adverse effects. It is the main causes for poor drug adherence, treatment discontinuation and changes in Anti-Retroviral Treatment (ART) regimens. Thus, the aim of this study was to assess the incidence and predictors of adverse drug reaction among adult Human Immunodeficiency Virus positive patients on anti-retroviral treatment from January 1, 2013 up to December 30, 2018 at Arba Minch town public health facilities, Southern Ethiopia.An institution based retrospective cohort study was conducted on 456 charts. Secondary data was collected by structured questionnaire. Data were entered in Epi-data version 4.4.2 software and exported to STATA Version 14 for analysis. The Kaplan-Meier survival curve with Log-rank was used to estimate survival time. Bi-variable and multivariable Cox proportional hazard regression models were fitted to identify predictors of adverse drug reaction. In the bi-variable analysis, the variables with p-value < 0.25 were eligible for multivariable analysis. Finally, variables with p-values less than 0.05 in the multivariable Cox regression were considered as independent predictors. The statistical significance was declared at p-value<0.05.Out of 456 patients observed for 14,903 person-months (pm), 79 experienced adverse drug reactions and the overall incidence density rate was 0.53/100 pm, CI: 0.42–0.66/100 person’s month or 6.36 per 100 Pearson year of observation. Females were at higher risk of experiencing adverse drug reactions (ADRs) compared to males . The risk of experiencing ADRs among patient with advanced WHO clinical stage (stage III and IV) was higher compared to stage I and II . The risk of experiencing an ADR was at any given time higher among AZT and NVP containing regimens compared to TDF and EFV containing regimens. Finally, the risk of ADR among those patients from the health center was reduced by 59% compared to hospital patients, .The incidence rate of ADRs was reduced among patients on ARVs compared to previous studies and it was high during the early years of ART initiation. HIV patients should be closely followed in the early years of ART initiation, since this is the time of highest risk ADRs and emphasis should be given for female and clinically advanced patients. According to The Joint United Nations Program on HIV and AIDS (UNAIDS), through 2018, 74.9 million people worldwide have been infected with HIV. Since the beginning of Human Immunodeficiency Virus (HIV) epidemic, around 74.9 million people have become infected and about 32 million people have died from the Acquired Immunodeficiency syndrome (AIDS) related illnesses. Globally, there were 37.9 million people living with HIV and 62% of people are on Antiretroviral Therapy (ART) in 2018 . Regarding WHO clinical stage, compared to non-advanced clinical stages (WHO stage I and II) at any given time, the risk of ADRs was 3 times higher among advanced clinical stages (WHO stage III and IV). The risk of experiencing an ADR was at any given time higher among AZT and NVP containing regimens compared to TDF and EFV containing regimens. Moreover, the risk of ADR reduced by 59% among those HIV patients who were on ART at the health center compared to those from the hospital .The aim of this retrospective cohort study was to determine the incidence and predictors of anti-retroviral drugs related ADRs among HIV positive adults on ART. The overall incidence density of ADRs was found 0.53/100 person’s month (CI: 0.42–0.66/100 person’s month), or 6.36 per 100 person-years of observation.This finding was slightly higher than a study done in Nigeria (4.6/100PY) ,32,37, aOn the other hand, this finding was lower than a study done in our country at seven teaching hospitals , where the incidence density was 9/100 PY . It was Concerning the time of ADRs, 2632.9%), 20(25.3%) and 16 (20.25%) of the ADRs occurred within the first 6th, 12th and 24th months of ART initiation respectively. This shows that the risk of ADRs were reduced as duration of ART increases and it was highest in the first six months of observation and more than three-fourth of incidents were happened in the first two years of observation. This finding is supported by previous studies conducted in our country at Bahir Dar and seven teaching hospitals and it is also agreed with a study done at Nigeria and India ,32,33,38.9%, 20Click here for additional data file.


The proportion of individuals with a history of exposure (‘pre-exposure’) to antiretrovirals (ARVs) prior to formal initiation into antiretroviral treatment (ART) is unknown.This study describes the detection of ARVs in plasma and/or hair, of persons who self-reported no pre-exposure to ART at their first-time initiation onto ART in three clinics in the province of Limpopo, South Africa (SA).Concentrations of tenofovir (TDF), emtricitabine (FTC) and efavirenz (EFV) in the plasma and hair of individuals initiating ART were analysed using a validated liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Next generation sequences of HIV polymerase gene were analysed with Geneious software 11.15, and drug resistance (DR) mutations were determined according to the Stanford HIV Drug-Resistance database. Participants’ demographic data were collected on a structured questionnaire. Data that describe prior exposure to ARV were also collected by this self-reporting method.n = 31/77, 40.3%) had TDF in either plasma or hair. Emtricitabine and EFV were found in the plasma or hair of 12/77 (15.6%) and 25/77 (32.4%) of participants respectively. Six  had all three ARVs in plasma or hair. Prevalence of DR mutations at the > 5% significance threshold level in those known to have had ARV-exposure determined by LC-MS/MS prior to ART-initiation was not significant , when compared to those who had no prior exposure but still showed DR.Paired blood and hair samples were collected from 77 individuals newly initiated onto ART from 2017 to 2019. We detected at least one of the drugs in the plasma or hair of 41/77 (53.2%) patients who responded with a ‘no’ to the question ‘have you received ARVs before initiation onto ART?’ Thirty-one participants  who deny ARV-use, requires an explanation. A larger study at multiple sites and regular DR surveillance of ART-naïve PLWH will be necessary to confirm the generalisability of these findings to the wider South African population. Non-disclosure has been reported in SA and elsewhere in Africa, Asia and in South America5 and carries the risk of treatment failure with subsequent antiretroviral (ARV) regimens. Non-disclosure frequently accompanies ART default and re-initiation. A ±42% probability of this has been noted in a SA study and linked to the female gender, the duration of elapsed-time since defaulting and age.6 Non-disclosure may also occur following ‘forgotten’ pre-exposure and post-exposure ARV prophylaxis.Several key assumptions are included in UTT. These include the fact that the tested person ‘newly’ diagnosed with HIV is naïve to antiretroviral therapy (ART) and is infected with a strain of HIV susceptible to the recommended first-line ART regimen. Further, it is assumed that the prevalence of circulating drug-resistant virus in the pre-treated population is negligible and will not impact treatment outcomes. The World Health Organization (WHO) categorises the pre-treatment -drug-resistance at the population level as low if the incidence of drug resistance < 5%; moderate if 5% – 15% and high if > 15%. In South Africa (SA), the level of drug resistance in the pre-treated population has increased over time but is heterogeneous across and within provinces. At least one pre-treated population with a moderate level of resistance has been reported in each province, except the Northern Cape.7 A 2019 study conducted amongst pregnant South African women attributed most virological failure (90%) to non-adherence.8 Non-adherence has also been associated with male gender, presentation at an advanced stage of HIV and with late/delayed access of ART.9 We have previously shown that adherence of more than 95% is required to achieve persistent viral load (VL) suppression.10Another important UTT assumption is that recipients of ART will be adherent to the treatment. Poor adherence leads to inadequate viral suppression, the development of drug-resistance, treatment-failure and an increased risk of death.In this study we explore the relationship of prior ARV exposure to subsequent resistance on reinitiating treatment by analysing the plasma and/or hair samples of individuals at baseline, and at 6 months post-initiation for the presence of drug-resistant virus and to confirm non-adherence.This was an exploratory study, involving the use of available plasma samples collected prior to initiation of treatment (baseline) and at 6 months post-initiation amongst persons living with HIV (PLWH) who were participants in an unpublished parent HIV drug resistance and treatment outcome study. Both at ART initiation and at the 6-month post-initiation visit, strands of hair were cut approximately 3 mm away from the scalp at the back of each participant’s head, and stored in a sterile container for subsequent analysis. Matched plasma samples were taken at the same time. Study participants were recruited from three HIV-screening and ART-initiating sites in the province of Limpopo, SA namely, the University of Venda Campus Health Clinic in Thohoyandou, the Rethabile Community Health Centre in Polokwane and the Seshego Community Clinic in Seshego. Participants provided informed consent before recruitment into the study. All participants were adults, aged ≥ 18 years and were reportedly taking ART for the first time. No additional inclusion or exclusion criteria were applied. All participants were started on a fixed-dose combination (FDC) of tenofovir (TDF) + emtricitabine (FTC) + efavirenz (EFV): TEE. All demographic data including sex and age were collected by means of a structured questionnaire. Data on prior ARV drug exposure relied on self-reporting by participants.CD4+ cell count and VL measurement of study participants is shown in 11 and analysed for drug resistance using the Calibrated Population Resistance protocol in the Stanford HIV Drug Resistance Database  and minority (> 5% and > 1%) thresholds, using the find variation/single nucleotide polymorphisms feature from the annotation and prediction menu in Geneious,base see .Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to quantify the individual components of TEE in the samples of hair and plasma, and was conducted at FARMOVS Bioanalytical Services Division, the University of the Free State, SA, a South African National Accreditation System accredited laboratory.For the plasma preparation, the run comprised eight standard (STD) levels over the range of 20.00 ng/mL – 2560 ng/mL, with six levels of quality control (QC) samples extending over this range. Two replicates were included per level for each STD and each QC sample. One blank sample and one zero sample were included in the sample run.The hair preparation run comprised eight STD levels over the ranges of 0.158 ng/mL – 20 ng/mL for EFV, 0.118 ng/mL – 15 ng/mL for FTC and 0.063 ng/mL – 8 ng/mL for TDF, with three levels of QC samples extending over this range. Two replicates were included per level for each STD and each QC sample. The STDs and QCs were interspersed amongst the study samples in a predetermined manner, with one blank sample and one zero sample included in the study sample run. See the detailed methodology for both matrices in R2) was used to determine the response to treatment by comparing baseline and post-treatment CD4 and HIV RNA data. Results generated by the LC-MS/MS run were calculated using Watson LIMS™ software. The drug concentrations of TDF, FTC or EFV in plasma or hair of ARV-unexposed participants should be zero. The detection at baseline of these ARVs confirmed prior exposure. Data from the literature of adherent PLWH on ARVs provided plasma drug-concentrations for comparison. Observed plasma concentrations in the range of 13 ng/mL – 397 ng/mL, 11 ng/mL – 5000 ng/mL and 1000 ng/mL – 4000 ng/mL for TDF, FTC and EFV, respectively were considered adherent.13 The expected range of drug concentrations in hair ranged from 0.002 to 0.4 ng/mg, 0.02 ng/mg to 4 ng/mg and 0.05 ng/mg to 20 ng/mg for TDF, FTC and EFV, respectively.16 Drug concentrations at 6 months in plasma or hair that indicated adherence to treatment were analysed for associations with CD4+ cell count and VL levels. Next generation sequences of the HIV polymerase gene were analysed with Geneious software 11.15. Drug resistance (DR) mutations were determined according to the Stanford HIV Drug-Resistance database.Data including the participants’ age, CD4 and HIV-RNA VL were calculated and reported as medians and interquartile ranges (IQR). The Spearman’s correlation coefficient , and permission to access public sector health facilities was granted by the National Health Research Ethics Committee (NHREC) and obtained from the Provincial Department of Health of South Africa, and the relevant district managers. Signed informed consent was obtained from all participants prior to collection of specimens and demographic data. Confidentiality and anonymity were maintained.N = 69/77 (89.6%) were females. The median age was 35 years, IQR, 27.25–42. The median baseline CD4+ cell count was 259 cells/µL, IQR, 137–382, and the median HIV-1 RNA VL level = 25 150 copies/mL, IQR, 64 275–84 514 (Paired blood and hair samples were collected from 77 PLWH newly started on ART between 2017 and 2019. 5–84 514 .n = 34) were females with a median age of 32.5 years (IQR 25.25–42) of whom 28/34 (80%), were aged < 45 years. Although the study included only eight males, seven (87.5%) were found to have prior exposure to ARVs. Their median age was 32 years, IQR 29.5–39.5. Considering the presence of TDF, FTC or EFV in the plasma or hair of participants, 41/77 (53.2%) were found to have been exposed to ARVs prior to treatment initiation. Thirty-four  had all three drugs (TDF/FTC/EFV) in plasma or hair.Emtricitabine and EFV were observed in the plasma or hair of 12/77 (15.6%) and 25/77 (32.4%) of participants, respectively. Six  in whom any of TDF, FTC or EFV, was detected in plasma or hair before the start of ART. Eight  participants had at least one DRM. The following mutations were present at respective threshold levels of > 20%, > 5% and > 1%: K103N only ; K103N, and V106A ; K65R, K219E, K103N, V106A, N88D and I50V . Details of the distribution of these mutations are given in Baseline drug resistance/mutation data were available for 13 of the 41 participants , who did not have ARVs in their plasma or hair. Data for this assessment were available for 18/36 (50%) participants. Seven participants 7/18 (38.9 %) had no DRMs. Of the 11 participants (61%) who harboured resistance mutations, the distribution was as follows: K65R (5.5%); D67N (5.6%); K65R, D67G, Y181C, G190E, V82A, I84V were observed in 11/18 (61%) participants at the > 20%, > 5% and > 1% threshold levels, respectively. Details of the distribution of these mutations are shown in 2 = 0.798; p = 0.372). In both groups, nucleoside reverse transcriptase inhibitor (NRTI)-associated resistance mutations were the most prevalent, regardless of thresholds.More DRMs were observed in participants who had prior exposure to ARV drugs compared to those who did not, although this difference was not significant . A significant decline in VL was observed at 6 months post-treatment initiation (20 RNA copies/mL – 20 RNA copies/mL), compared to values at treatment initiation (64275 RNA copies/mL – 84514 RNA copies/mL) . Details are shown in We looked at the adherence profile at 6 months post-treatment initiation. Of the 77 participants who were recruited at initiation, paired plasma and hair samples were available for only 21, at the 6 month assessment. The adherence-analysis using plasma and hair levels of TDF/FTC/EFV, was based on the 21 participants. The concentrations of these ARVs administered as a FDC tablet, were within an acceptable adherence-range level for all 21 at their 6 month assessment. This observation is supported by a significant increase in the median CD4 = 572 (IQR 347–781) cells/µL at 6 months after starting treatment, compared to the median ART-initiating CD4 count of 259 (137–382) cells/µL . Taking into account the presence of TDF alone, we observed that 31/77 (40.3%) of the participants had TDF in either their plasma or hair. The concentration of TDF detected in plasma or hair falls within the range of values described in the literature for individuals who are adherent to TDF.18 and this might agree with our observation of the K103N mutation present in women in the pre-treated population. This mutation confers resistance to nevirapine, a non-nucleoside reverse transcriptase inhibitor (NNRTI), and is likely to emerge in women who receive single-dose nevirapine in the PMTCT programme.19 Others, men and women, may have previously received ART through a private HIV treatment programme and wished to suppress this information (for whatever reason). Still others may have been ‘silent transfers’ that moved from one public sector health facility to another, without disclosure.20 Some participants may have been on treatment for hepatitis B virus (HBV) infection utilising the ARVs, TDF and lamivudine or FTC. Others may have been on pre-exposure or post-exposure prophylaxis in the past. There are also reports on the recreational use of ARVs in whoonga/nyaope amongst South Africans.22 Additionally, our research team has anecdotal reports of spouses using the ARV medications of others clandestinely, because of the fear of disclosing their status, as supported by literature.23 The question that this observation raises is whether individuals are being initiated onto the standard first-line ART without knowledge of prior exposure to ARV medications? And if this is the case, the sustainability of first-line ART and the expected goals of UTT might potentially be compromised with little impact (observed in 24 dolutegravir-based ART.The study participants had answered ‘no’ to a question on whether they had received ARV medications in any form or programme prior to their current diagnosis and treatment initiation. The detection then of ARV drugs in their tissues requires explanation: some of the women may have previously been on a prevention of mother-to-child transmission (PMTCT) programme,25 or it could be that the resistance mutations observed in both groups were largely due to transmitted resistance mutations. Transmitted drug resistance has been shown to be on the rise amongst the pre-treated population in SA with a moderate level of 5–15%. Although resistance is increasing, it is heterogeneous across and within provinces, with the Limpopo province also showing a moderate level.3 Of the 31 participants for whom drug resistance data were available at baseline, seven returned for follow-up: four of them had no DRM, whilst three had an NRTI-DRM at the 1% threshold – all of them attained virological suppression at 6 months. Four participants,  in whom dual-class NRTI/NNRTI or NRTI/PI resistance weas observed at baseline, could not be further investigated to ascertain the effect of these DRMs on virological suppression at 6 months, since they were lost to follow-up.Surprisingly, no significant difference in the prevalence of drug resistance mutations was observed between the participants in whom ARV drugs were detected and those in whom ARV drugs were not detected prior to initiation of treatment. However, mutation distribution amongst both groups was different. Possible explanations for this could be the exposure to TDF for a significant duration of time, or high frequency of minor variants detected using high-sensitivity sequencing technologies,26 These studies correlate with our findings, which demonstrated a significant increase in CD4+ cell counts with VL suppression.27A monotonic relationship was observed in the CD4+ cell count and viral copy number in all 21 study participants post-treatment. Several studies have established that VL below the level of detection at post-treatment initiation  indicates optimal viral suppression, and such observations are normal in successfully treated patients and do not predict virological failure.The data presented here should be considered in the context of some limitations. Firstly, the small sample size is unlikely to be representative of all who are initiated on ART in the Limpopo province. Secondly, drug resistance data were not available for all 21 participants, who were assessed for adherence based on CD4+ cell count, VL and ARV levels at 6 months post-treatment initiation. So, it was not possible to determine whether or not they harboured resistance mutations going into treatment, and to make the call regarding whether or not the benefits of adherence cancel out the potential impact of these mutations on treatment outcome . Despite these shortcomings, we have objectively shown, by detecting ARV drugs in plasma or hair, that clinicians may be unknowingly recruiting non-drug naïve individuals into HIV treatment programmes on the standard first-line regimen. These results suggest that reporting previous ARV drug exposure accurately is likely to be of benefit in identifying individuals at increased risk of harbouring resistant mutations, and who will require closer follow-up to ensure long-term viral suppression. Disclosure of prior exposure could also assist in the choice of the initial ARV drug regimen, or opting for intensive adherence for these individuals to achieve the desirable treatment outcomes.Non-disclosure of previous ART exposure is frequent. Measurement of hair and plasma ARV drugs in PLWH who are NOT yet on ART may identify a group at risk of subsequent treatment failure, and would therefore be a priority group with regard to ART management and follow-up. The presence of resistance related viral mutations and of ARVs in the plasma and hair of ‘ART-naive’ PLWH at the time of ART initiation, suggests the need of surveillance programmes to monitor primary drug-resistance and the establishment of an ‘early-warning’ system to monitor primary HIV-resistance in all areas where ART initiation is provided.


Antiretroviral therapy lowers viral load only when people living with HIV maintain their treatment retention. Lost to follow-up is the persistent major challenge to the success of ART program in low-resource settings including Ethiopia. The purpose of this study is to estimate time to lost to follow-up and its predictors in antiretroviral therapies amongst adult patients. Among registered HIV patients, 542 samples were included. Data cleaning and analysis were done using Stata/SE version 14 software. In multivariable Cox regression, a p-value < 0.05 at 95% confidence interval with corresponding adjusted hazards ratio (AHR) were statistically significant predictors. In this study, the median time to lost to follow-up is 77 months. The incidence density of lost to follow-up was 13.45  per 100 person-years. Antiretroviral therapy drug adherence [AHR: 3.04 ], last functional status [AHR: 2.74 ], and INH prophylaxis [AHR: 1.65  were significant predictors for time to lost to follow-up. The median time to lost was 77 months and incidence of lost to follow-up was high. Health care providers should be focused on HIV counseling and proper case management focused on identified risks. Globally, an estimated 37.7 million (30.2 million–45.1 million) people were living with HIV and around 4,000 new infections every day, 20206. Africa, Asia, and Latin America were the major affected continents by HIV infection8. In 2020, more than 680, 000 deaths and destroyed 21.5 US dollars for ADIS response in low and middle-income countries6. Anti-Retroviral Therapy (ART) lowers viral load only when people living with HIV (PLHIV) fully adhere to the treatment regimen continuously for life11. However, the viral suppression rate was 66% globally, 59% in western and central Africa, and 72% in Ethiopia in 20206. Optimal HIV care retention is very crucial to address HIV global 2030 goals12.Human Immunodeficiency Virus (HIV) which potentially leads to Acquired Immune Deficiency Syndrome (AIDS) is a global health problem15. Lost to follow-up is the persistent major challenge to the success of the ART programs in low-resource settings including Ethiopia17. This may increase treatment failure , morbidity, mortality, and drug resistance10. The patient retention status is an important measurement of ART program effectiveness10. In the previous finding in Asia, the trend of lost to follow-up among HIV- positive patients’ received ART was 9%18. In sub-Saharan Africa, public sector HIV treatment clinics five years retrospective follow-up revealed that 24.6% were lost to follow-up10. The proportion of lost to follow-up was found to range in different settings from 16.4%19 in South Africa, 28% in Nigeria, 12.4%20 in Malawi, and 3% in seven teaching hospitals, 11% in Wukro Hospital in Tigray Region, Ethiopia, and 21.3% in Oromia Region, Ethiopia23. In resource-limited settings of West Africa, males had a 14% higher rate of lost than females. The incidence rate of lost to follow-up was 9.2/100 person-years (PYs)23 in a large-scale ecological study in Sub-Saharan Africa. Other studies found rates of 12.8%/100 PYs15 in South Africa, 11.6/100PYs24 in Pawi General Hospital in Ethiopia, 8.2/100 PYs in Aksum Hospital13, and 12.26/100 PYs25 in Gondar Specialized Comprehensive Hospital in Ethiopia. The median time to lost to follow-up was three months, and 14% of them had lost in the first day of antiretroviral therapy26.Lost to follow-up is defined as a patient who has not received ART medication for more than 30 days of their last missed drug collection appointment15. Previous existing evidence revealed, patients who had hemoglobin (Hgb) markers, nutritional deficiencies, opportunistic infections, cancers, illiterate, unmarried, rural dweller, alcohol drank, tobacco smoking, CD4 level, WHO clinical stage, short HIV infection history, age, drug side effect, viral load, employment status, regimen change, TB infection, male gender, weight, mental illness, receiving INH therapy, functional status, and advanced HIV disease affecting the hematopoietic system were predictors of lost to follow-up34.The findings in Nigeria showed the incidence rate of treatment interruption was highest in the first six months of ART at 18.2/100 PYs but decreased after two years to 8.8/100 PYs. Lost to follow-up from treatment increased by 1.30 times for each calendar year in a study in South AfricaPreviously shared evidence, in Ethiopia, addresses adherence to ART and only a few studies were conducted to assess predictors of lost to follow-up. However, the data regarding time to lost to follow-up after ART initiation, incidence lost follow-up, and predictors were unsaturated. Therefore, this study aims to estimate the time to lost to follow-up and its predictors among adult patients receiving antiretroviral therapy in Amhara, Northwest Ethiopia.A total of 542 participants were included in the study. More than half (60.5%) of participants were females. The mean age of participants was 34.34 ± 10.49 years standard deviation. Two hundred sixty-six (49%) patients were married and 66 (12.2%) of the partners were known to be HIV-positive. In this study, two-third (66.8%) of study participants had disclosed their HIV-positive status. Almost one-fourth (27.5%) of study subjects had used family planning during the study period, with 37 (6.8%) of them using natural family planning methods and only 29 (8.8%) study participants had become pregnant in this follow-up period (Table 3 with IQR (106–328.25)  and 105 (19.4%) of participants had a history of diarrhea and fever respectively. Two hundred 36.9%) study participants had a history of opportunistic infection and 83 (15.3%) of participants had taken INH preventive therapy. Only (53%) of study participants had Hgb tested during their enrolment. The median CD4 level of study participants was 208cells/mm% and 1056.9% studOf the 542 study participants, 221 (40.8%)  were lost to follow-up, nearly one-third (32.5%) were on active treatment, 20.1% were transferred out, and 6.6% died in this retrospective follow-up cohort.The incidence density of lost to follow-up was 13.45  per 100 PYs. In this finding, half of the patients had lost to follow-up at 77 months follow-up  period ]. Similarly, those who had ambulatory or less last functional status were 2.74 times more at risk to lost to follow-up compared to working last functional status [AHR: 2.74 ]. Moreover, patients not receiving INH prophylaxis therapy were 1.65 times more at risk to lost to follow-up compared to counterparts taking INH therapy [AHR: 1.65 ]  per 100 PYs. The study finding is similar to previous evidence with 12.26/100PYs25 in Gondar Specialized Hospital in Ethiopia and 12.8/100PYs15 in South Africa. The current finding is greater than the 10.9/100 PYs in Gondar Specialized Hospital Ethiopia34, 11.6/100 PYs in Pawi Hospital (Northwest Ethiopia)24, and 9.2/100 PYs in a large scale ecological study in sub-Saharan Africa23. The possible reason for this variation might reflect differences in the study period, settings, sample size, adherence problem, drug-related side effects, and counseling barriers. As evidence revealed, the quality of clinical service care was different between different levels of health facilities this may have a role on lost to follow-up36. This study was conducted in a single health center that has poor health care service , poor health-seeking behaviors, lengthy travel distances to get health service, and low literacy levels this might be increase likely hood of lost to follow-up. Even though limited evidence existed in Ethiopia that was conducted at the hospital level, this study setting difference between hospital and health center might introduce variation service quality and level of care. There is also outcome measurement variation, one month and more missed in this study may increase the incidence. Unlikely, this evidence was lower than findings 21.4/100PYs in Asia–Pacific regions28. This difference may be due to variation of outcome measurement lost to follow-up as used patient not seen in the clinic more than 12 months.This study was designed to estimate time to lost to follow-up among adult HIV/AIDS patients. ART declines HIV/AIDS-related death, hence high retention in ART care is required to optimize treatment outcomes38. However, this finding lies in disagreement with a South African study15. The patients who stayed long periods on ART have had improved adherence, relief from drug-related side effects, less likelihood of opportunistic infections, progressively improved ART service quality in the facility, and establishing lost to follow-up tracing modalities by adherence supporters and volunteer networks in the community. This might have a direct effect on patient retention on antiretroviral therapy.The incidence rate of lost to follow-up is different across time with 3.32/100 person-months at the first month, 5.20/100 person-months at the second month, 3.11/100 person-months at 3 months, and 2.20/100 person-months at 6 months follow-up after ART treatment initiation. Although the incidence rate in the first-year follow-up (27.41/100 PYs) is high, it shows a slight decline over the first-six years follow-up with 13.87/100 PYs at 2nd year, 9.82/100 PYs at 3rd year, 8.45 PYs at 4th year, 6.04 PYs at 5th year, and 4.18 PYs 6th year. Despite this, the incidence was increased to 7.3/100 PY at the end of 9th-year follow-up. This finding is consistent with previous findings from Tigray, Southern, and Oromia regions in Ethiopia, and Nigeria42, 12.4% in Malawi20, 16.4% in South Africa19, 28% in Nigeria21, 24.6% in Sub-Saharan Africa10, and 243.9% in South-Eastern Nigeria Hospitals30. The possible explanation for this disparity may be settings , the difference in health center compared to most of the previous findings in hospitals, and poor health-seeking behavior, used measurement difference lost to follow-up, socioeconomic, and socio-demographic differences across facilities and countries impacting on lost to follow-up.The proportion of lost to follow-up is 40.8% in this study which is higher than previous reports which ranged from 2.87 to 25.3% in various regions of Ethiopia32. The possible reasons may be due to HIV patients’ hopelessness on treatment, conflicts with religious concerns, demanding traditional healers, lack of social support, fear of stigma and discrimination, drug side effects, and other socio-economic reasons that cause them to miss their medication.ART drug adherence was a statistically significant predictor of lost to follow-up; patients who had poor ART drug adherence were 3 times more at risk of lost to follow-up compared to good ART drug adherence. This is consistent with the study conducted in Gondar Comprehensive Specialized Hospital, Oromia region, Jima Specialized Hospital Ethiopia, sub-Saharan African, low and middle-income countries meta and systematic analysis, and Nigeria43. The possible reason for this finding might be ambulatory and less functional status patients were more likely to experience lost to follow-up due to inability to work or decrease productivity in all aspects of social, economic, and financial influences. They also need help and close supervision to ensure adherence to ART, which might have been a high probability to the drug side effects; hence, collectively these experiences may affect retention on ART care.Similarly, last functional status is statistically significant to lost to follow-up: Patients who had ambulatory and lower last functional status were 2.74 times more at risk to lost to follow-up compared to those with working as last functional status. This study finding is consistent with the studies conducted in Kimbata and Hadiya zone, Oromia region, Jinka hospital Ethiopia, and  meta and systematic analysis,41. INH prophylaxis therapy recommended by the national treatment guideline may direct effect on decrease lost to follow-up by strengthening retention of HIV patients on ART service since INH prophylaxis therapy controls one of the most common life-threatening co-morbidity and mortality threats  among HIV infected people3. This existing intervention to improve the health of the patient may encourage patients’ retention on ART care.Moreover, those who did not take INH prophylaxis therapy were found to be 1.65 times more at risk to lost to follow-up compared to counterparts who did take INH therapy. This finding supported previous findings in Gondar Comprehensive Specialized Hospital, Pawi General Hospital, Wukro Hospital, public hospitals Binishangul Gumuz, and in southern EthiopiaIn conclusion, the time to lost half of the patients was 77 months, and the incidence of lost to follow-up was high. Poor drug adherence, ambulatory & less last functional status, and not taken INH prophylaxis were predictors for lost to follow-up among adult HIV/AIDS patients. The government gives special attention to the quality of HIV care at the health center level. There is an imperative to design new initiatives to reduce lost follow-up at the national level including improving ART accessibility modalities, early reminder strategies through tell-medicine, and expansion of laboratory services at preferred sites.An institution-based retrospective follow-up study was conducted from January 1, 2008 to December 30, 2017. Data were collected from February 28–March 16, 2018. The study was conducted at the Bichena Health center. It is found 355 km (km) from Bahir Dar city of Amhara National Regional State and 265 km from Addis Ababa capital of Ethiopia. The health center started ART services in 2008, serving a 51,653 catchment population. It was the first high load ART site health center in the East Gojjam Zone, having 2,770 patients registered for ART service, among those 2,655 (95.8%) were adult ART users, which constituted the source population in this study.The study population was all HIV-infected adults (> 15 years) who enrolled at Bichena Health Center ART clinic from January 1, 2008–December 30, 2017. Adult HIV-infected patients who had at least-one ART follow-up visit were eligible to include. Those patients who had unknown ART initiation date, absence of baseline data record or follow-up form in the patient chart and transfer in with incomplete baseline data were excluded in this study Fig. .Figure 415.Lost to follow-up: A patient who has not received ART medication for more than 1 month of their last missed drug collection appointment44.Disclosure: If anyone knows the status of the patient/child at the workplace, school, family, and other community members44.Adherence: The level of adherence was assessed at every time the patient comes to clinical visit as good (> 95%) missed ≤ 2 doses in 30 doses or ≤ 3 doses of 60 doses, fair (85–94%) missed 3–5 doses in 30 doses or 4–8 doses of 60 doses, and poor (< 85%) missed ≥ 6 doses in 30 doses or ≥ 9 doses of 60 doses44.Risk behavior: If the patient has one or more of the following risks  were considered as a risk behavior44.Functional status: The functional status was assessed continuously to every clinical visit as 45.Regimen change: As an event, through the follow-up period was ascertained retrospectively when the patients are recorded as changed their regimen and started other ART drugs44.TB screening: The screening is done at the time of ART initiation and every clinical visit what every the screening is through using x-ray or clinically but not on any anti-TB medication15, the proportion of exposed  28.60%15, hazard ratio 1.51, and nonresponse rate 10%. Hence, a sample size of 559 was computed with the inclusion of a 10% non-response rate. The study participants were selected by computer-generated simple random sampling technique using their medical record numbers.The sample size was calculated by a double population formula using Epi Info™ version 7 software considering the following assumptions: level of precision 5%, confidence interval 95%, power 80%, the proportion of unexposed  22.87%A retrospective record review technique was used to collect the required data. All eligible medical recorded data were taken from the ART intake forms and follow-up charts. The data was collected by two diploma nurses and one public health officer as supervisor. The checklist was adapted from the standard Ministry of Health ART intake forms and follow-up charts. Socio-demographic data, past medical history, drug adherence, and clinical & laboratory results were the components of the checklist. Data quality was maintained starting during designing the checklist, training for data collectors’ ad supervisor, and close supervision held during the entire data collection period.EpiData version 4.2 Entry client was used for data entry and Stata/SE version 14.0 was used for data cleaning and analysis. Data were checked for completeness and inconsistencies before the analysis. Survival Kaplan Meier estimator was used to show the survival and failure estimate curve. Cox regression analysis was fitted to identify the association between dependent and independent variables. Model fitness was checked by Cox proportion hazard model, log–log plot graphically, and test proportional hazard assumptions by Scheonfeld residual. The goodness of fit was checked by running Cox-Snell residual analysis Fig. . DescripThis study was approved by the Debre Markos University, College of Health Science ethical review committee (#HSC/R/C/S/P/Co/696//11/10). The need of informed consent was waived by the Ethics committee of Debre Markos University. The information given was maintained strictly confidential and used for this study purpose only. All procedures were carried out in accordance with relevant guidelines and regulations.In this study, about 17 patient charts for those who had not or incomplete baseline data were not included. Since we are used secondary data important predictors like viral load, hemoglobin test, and other clinical factors were not included as they were not properly recorded. Also, the lost follow-up might be affected by length–time bias. Thus, this finding should be considered with these limitations.Supplementary Figures.


The CD4 cell count signifies the health of an individual’s immune system. The use of data-driven models enables clinicians to accurately interpret potential information, examine the progression of CD4 count, and deal with patient heterogeneity due to patient-specific effects. Quantile-based regression models can be used to illustrate the entire conditional distribution of an outcome and identify various covariates effects at the respective location.This study uses the quantile mixed-effects model that assumes an asymmetric Laplace distribution for the error term. The model also incorporated multiple random effects to consider the correlation among observations. The exact maximum likelihood estimation was implemented using the Stochastic Approximation of the Expectation–Maximization algorithm to estimate the parameters. This study used the Centre of the AIDS Programme of Research in South Africa (CAPRISA) 002 Acute Infection Study data. In this study, the response variable is the longitudinal CD4 count from HIV-infected patients who were initiated on Highly Active Antiretroviral Therapy (HAART), and the explanatory variables are relevant baseline characteristics of the patients.The analysis obtained robust parameters estimates at various locations of the conditional distribution. For instance, our result showed that baseline BMI (at CD4 cell recovery in response to post-HAART initiation across all fitted quantile levels was observed. Compared to HIV-infected patients with low viral load levels at baseline, HIV-infected patients enrolled in the treatment with a high viral load level at baseline showed a significant negative effect on CD4 cell counts at upper quantiles. HIV-infected patients registered with high BMI at baseline had improved CD4 cell count after treatment, but physicians should not ignore this group of patients clinically. It is also crucial for physicians to closely monitor patients with a low BMI before and after starting HAART.The online version contains supplementary material available at 10.1186/s12879-021-06942-7. Individuals living with HIV who have a CD4 cell count less than 200 cells/mm3 are at high risk of developing severe sickness” [CD4 cell counts indicate a sign of the wellbeing of the immune system for an individual. It also provides information about disease progression. The number of CD4 cells of an individual who does not have HIV could be somewhere in the range of 500 to 1500 cells/mmThe classical regression model about the mean has been the commonly applied statistical procedure to depict the effects of explanatory variables for continuous outcomes. Despite this, such results based on a fixed location of the response distribution may not be relevant in many areas, and sometimes the fields of application are diverse. Numerous investigators, economic experts, monetary stakeholders, clinicians, and legislators have revealed a growing interest in group differences across the whole population instead of relying solely on the average –6. AnothQuantile regression (QR) was popularized by Koenker and Bassett . It is aIn recent years, mixed quantile regression models have become a widely used technique in statistical studies. By using quantile-based regression model, it is possible to examine the location, scale, and shape of the distribution of responses to get an idea of how the covariates affect the distribution of responses. It is also more robust to outliers when compared to conventional mean regression and is invariant to monotonic transformations. There is no need to make any Gaussian assumptions concerning the response with quantile regression, and further it is capable of handling heavy-tailed and asymmetric data. As a result, CD4 count can be modeled very well using this method.Many longitudinal studies gather a great deal of information about repeated measures that are crucial for analyzing disease progression in clinical studies. For example, repeated counts of CD4 cells are vital to HIV/AIDS monitoring; for instance, low levels of CD4 counts are signs of serious viral load accumulation, disease progression, and the need for therapy intervention. Physicians also use them to identify the advantages of medical involvement and the risk factors that may lead to poor outcomes. In practical statistics, mixed-effects models have become quite popular. As a result of their ability to handle both between-subjects and within-subjects variability in longitudinal data, they are often used to analyze longitudinal data . Mixed-eMoreover, in some cases, it could be challenging to obtain appropriate transformation to normality for the response variable, or some strategy to account for outliers may be required. An adequate solution to all these issues is given by concentrating on the conditional quantiles of the longitudinal outcome . “Conditindependent estimating equations that ignore correlations between repeated measurements which leads to loss of efficiency [The QR method was initially developed in a univariate setting. However, the large amount of longitudinal data has recently dictated its extension into a mixed-effects modeling system by either the distribution-free way –17 or thficiency , 17, 20.ficiency  suggesteficiency  developeficiency . The appficiency –28. Follficiency , this stThis study used the Centre of the AIDS Programme of Research in South Africa (CAPRISA) 002 Acute Infection (AI) Study data conducted at the Doris Duke Medical Research Institute (DDMRI) at the Nelson R Mandela School of Medicine of the University of KwaZulu-Natal (UKZN) in Durban, South Africa –33. CAPRWhen an infected person’s body indicates symptoms of being incapable of adequately controlling the virus and their CD4 count drops below a specific cut point, they were initiated on therapy. A deficient level of CD4 count causes the weak immune system of an HIV-infected person. In the absence of treatment or without viral suppression, the person is susceptible to opportunistic infections (OIs). This increases the risk of the new and ongoing Coronavirus Disease 2019 (COVID-19) infections and underlying illnesses –33. HAARThe HIV/AIDS epidemic and other sexually transmitted diseases severely impact human health, especially the well-being of women and young girls –33. “TheQuantile regression (QR) is an advanced statistical technique to study the predictors’ heterogeneous effects at the conditional distribution of the outcome. Instead of modeling only the mean value like the conventional regression methods, quantile regression enables more fully to explore the data by modeling the conditional quantiles, for example, the 5th and 95th percentiles of the response distribution . For thelinear programming (LP) by minimizingith regressor) keeping all the other covariates constant.The quantile level is frequently signified by the Greek letter τεidεi=τ , 52. “Thestimate , 43, 53.cument}β . For thiLP methods can be used to obtain The objective function of the conditional quantile estimator, entclass1pt{minimaediction . Since tnt}H(βτ) , 54, 55.nt}H(βτ) , Konker nt}H(βτ) , Buchinsnt}H(βτ) , Koenkernt}H(βτ) , or Yu ent}H(βτ) .LP procedures are often used to achieve a relatively fast computation of As the check function entclass1pt{minimant}H(βτ) , 56. A nnt}H(βτ) , 57. A centclass1pt{minimant}H(βτ) . Other fnt}H(βτ)  and Kozunt}H(βτ) . ALD thant}H(βτ) , 57, 58.The conventional QR is based on the median, or other quantile levels, by assuming a continuous or Gaussian distribution. QR has been extended to count regression, which is a special case of the discrete variable model , 61–64. f counts . Detailef counts , 63, Camf counts , 56, andf counts  and Miraf counts .Mixed-effects models characterize an ordinary and conventional type of regression methods used to examine data coming from longitudinal studies. The general linear mixed-effects model is defined asd Bottai  as an exd Bottai , of a coThe random effects  , 52. TheBased on the likelihood of conditional quantile of d in Eq.  with resn in Eq. . Thus, wMore details regarding the estimation process of quantile mixed-effects models are available here , 24, 58.The study examines quantile regression for linear mixed-effects models (QR-LMM) of Galarza  that folr et al. , is a por et al. . There ar et al. . The detr et al. . A book r et al. . MoreoveEven though the EM algorithm is popular, Delyon et al.  pointed E-step: Consists computing of the conditional expectation of M-step: Computes the parameter values The SAEM algorithm, on the other hand replaces the E-step by stochastic approximation, presented by Galarza  summarizSimulation (E-step): Generate Stochastic approximation: Update M-step: Maximize Let nditions , 71, go this is equivalent to finding Lavielle , 73, andal to 20 . The cho Galarza  is givenqrLMM.For more points of interest, however, see Jank , Meza etCD4 cells are the utmost target of HIV infection, and the CD4 count is used as a health marker for an individual’s immune system. Hence, it is of interest to investigate the evolution of CD4 count and disease progression of an individual over time, especially for HIV-infected patients. Consequently, this study analyzes the repeated CD4 count of HIV-positive patients registered in the CAPRISA 002 AI study by employing a parametric quantile regression mixed-effects model based on the asymmetric Laplace distribution. The CAPRISA 002 AI study dataset consists of repeated CD4 count measurements and some other covariates of 235 individuals. There were a total of 7019 observations from the 235 women; each subject was measured several times, ranging from 2 to 61 months, with a median equal to 29. Table jth time point for the ith subject, The linear mixed-effects model form of the data can be specified as:The information criteria are used to compare four models. The models were compared based on the 0.5th quantile (median regression). The linear quantile mixed-effects model with random intercept and slopes (Model 4, see Table mentclass2pt{minimRandom effect models that were examined for the analysisAs can be observed from Table qrLMM sample outputs using CAPRISA 002 Acute Infection Study data across all fitted quantile levels can be found in Additional files R package The results in graphical representation following QR-LMM over the framework of quantiles mentclass2pt{minimmentclass2pt{minimThis study considered a quantile mixed-effects model with a likelihood-based function that adopts an ALD for the error term. We used the SAEM algorithm for determining exact ML estimates of the covariates effect and variance–covariance elements across a set of quantiles. We applied this methodology to the CAPRISA 002 AI Study data and illustrated how the procedure can be used to obtain robust parameters estimates when the interest is to get the estimation not only on the central location but also on the non-central locations of the conditional distribution, which brings a comprehensive and more complete picture of the effects. A series of QR-LMM at mentclass2pt{minimSince quantile inference for discrete longitudinal data cannot thus be carried out directly yet, we modeled a continuous approximation form of the quantile function by using square-root-transformed CD4 count as the response variable. Time since seroconversion, HAART initiation, and baseline characteristics of the patients such as BMI, age, and VL was included in the study. It was found that except age, all the studied variables were found to have a significant effect on CD4 cell counts of HIV-infected patients across all quantiles. Although significant CD4 cell recovery in response to post HAART initiation across all quantiles was recognized, HIV-infected patients who were enrolled in the treatment with a high level of VL showed a significant negative effect on CD4 cell counts at upper quantiles . Even thAdditional file 1. R package qrLMM sample output using CAPRISA 002 Acute Infection Study data across fitted quantile levels.Additional file 2. Graphic overview of convergence for model parameters across all fitted quantiles, produced from the qrLMM package using the CAPRISA 002 AI Study data.


Pulmonary tuberculosis (TB) in people living with HIV (PLH) frequently presents as sputum smear-negative. However, clinical trials of TB in adults often use smear-positive individuals to ensure measurable bacterial responses following initiation of treatment, thereby excluding HIV-infected patients from trials.In this prospective case cohort study, 118 HIV-seropositive TB patients were assessed prior to initiation of standard four-drug TB therapy and at several time points through 35 days. Sputum bacillary load, as a marker of treatment response, was determined serially by: smear microscopy, Xpert MTB/RIF, liquid culture, and colony counts on agar medium.By all four measures, patients who were baseline smear-positive had higher bacterial loads than those presenting as smear-negative, until day 35. However, most smear-negative PLH had significant bacillary load at enrolment and their mycobacteria were cleared more rapidly than smear-positive patients. Smear-negative patients’ decline in bacillary load, determined by colony counts, was linear to day 7 suggesting measurable bactericidal activity. Moreover, the decrease in bacterial counts was comparable to smear-positive individuals. Increasing cycle threshold values (Ct) on the Xpert assay in smear-positive patients to day 14 implied decreasing bacterial load.Our data suggest that smear-negative PLH can be included in clinical trials of novel treatment regimens as they contain sufficient viable bacteria, but allowances for late exclusions would have to be made in sample size estimations. We also show that increases in Ct in smear-positive patients to day 14 reflect treatment responses and the Xpert MTB/RIF assay could be used as biomarker for early treatment response.The online version contains supplementary material available at 10.1186/s12879-021-06133-4. Mycobacterium tuberculosis cultures in samples taken prior to initiation of TB treatment to ensure measurable treatment responses from a high baseline [In high tuberculosis (TB) burden settings HIV-infection confers markedly higher risk of TB infection and TB disease . In genebaseline , 9. Smeabaseline –13.M. tuberculosis detected results have Ct values from 15 to 28. In the automated Mycobacterial Growth Indicator Tube (MGIT) liquid culture system , the time-to-positive (TTP) signal occurs sooner when bacillary load is high [Four semi-quantitative methods are used to infer bacillary load - the concentration of mycobacteria - in a biological sample –20. Smea is high  by whichIn this study we followed a cohort of adult PLH with pulmonary TB, both smear-negative and smear-positive, and subjected their serial sputum specimens whilst on therapy to these four semi-quantitative methods to characterise their initial, and extended mycobacterial responses to TB treatment. Our overall objective was to assess if HIV-infected, smear-negative patients with pulmonary TB have demonstrable bacillary responses to therapy and could be included in clinical trials of novel treatment regimens.M. tuberculosis in the previous 10 days . Standard four-drug anti-TB therapy was initiated as soon as possible after: 2 months of isoniazid, rifampicin, pyrazinamide, and ethambutol, followed by 4 months of isoniazid and rifampicin (2HRZE/4HR). Patients were referred for antiretroviral therapy (ART) initiation if not already started, according to then-current national guidelines. Patients with drug resistant TB or in need of specialized TB treatment were not eligible, but were referred to an appropriate clinic. Socio-demographic data; prior episodes of TB; recent or current exposure to other anti-TB drugs; smoking and alcohol habits; occupational mining and dust exposure history; and antiretroviral treatment history were collected. Baseline patient measurements and investigations included: weight; height; chest x-ray; spot and/or overnight study sputum; CD4 count; viral load and full blood count. Sputum samples were collected from participants at baseline and then after initiation of drug therapy, at days 3, 7, 14, 28 and 35. In this analysis, data from day 28 (21 patients) and day 35 (84 patients) were combined, and designated as the “day 35” time point. For patients who missed time points due to loss to follow up, or for other reasons, earlier time points were included.This was a three site, prospective case cohort study, in which we purposively recruited HIV-infected adult TB patients irrespective of their antiretroviral therapy status. After obtaining informed consent, adult patients with an initial public sector Xpert positive result were recruited at Soweto, Klerksdorp and Cape Town - into two studies with almost identical design. Patients were included if they had not taken TB medications in the 1 year prior to enrolment and were eligible for standard four-drug first-line TB regimen for the current TB disease episode. Patients were excluded if they had received more than 5 days of TB treatment before the first study sputum was taken, and if they had received any antibiotics with activity against All specimens were processed and analysed in research laboratories. Standard diagnostic tests were performed on decontaminated sputum samples according to the South African National Health Laboratory Service (NHLS) guidelines: smear microscopy by auramine O stain, Xpert and MGIT. In addition the number of colony forming units were determined on Middlebrook 7H11 agar medium supplemented with 0.5% OADC  and documented as the logarithm of the colony forming units per millilitre (logCFU) , countinThis was an exploratory descriptive study and a sample of 118 patients was included, anticipating that baseline smear status of the entire group would be similarly represented. For each patient attending a study visit, all four semi-quantitative assays were performed on sputum and outputs were given as: auramine smear grade for microscopy, MTB grading and Ct values as supplied by standard Xpert documentation, TTP for MGIT and logCFU for viable counts. Continuous data were reported as medians and interquartile ranges for Xpert, MGIT and bacterial load. Negative results were documented for Xpert as a Ct of 40, for MGIT as a TTP of 42 days and for viable counts as logCFU = 0. For analysis of discrete data, positive results for microscopy were recorded according to auramine grading (AU): scanty (AUSC), one plus positive (AUP1+), two plus positive (AUP2+), or three plus positive (AUP3+); Xpert was given as MTB detected (MTBD) at a Ct of < 36; MGIT as TTP < 42 days and viable counts as logCFU > 0. Early bactericidal activity (EBA) is the fall in viable counts/ml sputum/day, calculated from colony forming units on solid medium at given time points. Data were analysed using GraphPad Prism 8. Comparison of continuous data was conducted by the Kruskal-Wallis method (non-parametric) or the students t-test (parametric). The difference in slope comparisons was estimated using linear mixed modelling.2 for body mass index (BMI) and 82 and 141 cells / mm3 for CD4 count, in smear-negative and smear-positive patients, respectively. They differed significantly only by proportion of cavitation on chest x-ray: 28.6% of the smear-negative and 63% of smear-positive patients  also had a baseline negative Xpert result. Importantly, all participants, irrespective of smear status had at least one positive culture result during the study (MGIT and/or colony count culture).Overall, at baseline, higher smear status reflected lower Ct values Fig. . Howeverp < 0.001 on each comparison). By day 35 sputum specimens were positive in smear-negative and smear-positive patients, respectively in 11.1 and 28.6% by smear, 47.2 and 59.3% by Xpert, 35.5 and 61.5% by MGIT, and 22.6% and 38.7 by viable colony counts , this was lower than in smear-positive patients (96.9% by MGIT and 90.8% by Xpert); baseline bacterial load of smear-negative patients was 1.61 fold lower than that of the smear-positive group and bacteria were cleared in less than half the time in smear-negative patients, compared to smear-positive. Indeed, by day 14 MGIT TTP values approached 42 days in smear-negative patients. Our data also suggest that smear-negative TB patients may benefit from shortened treatment regimens , 24. MorAs a group, most smear-negative patients included in this study had sufficient viable bacteria that could be analysed meaningfully up to day 14 but one third of the smear-negative patients were also Xpert negative at baseline. MGIT tests have been reported to be at least equally as sensitive as colony counts –27 and wThere were several limitations to our study. This was a three-site study from one country; we did not document adherence of tuberculosis treatment or antiretroviral therapy; missing laboratory values and losses to follow up may have biased our results. The Xpert Ultra has largely replaced the assay we used to determine declines in bacterial load in this study. The sample size was small and we had fewer smear-negative patients in our analyses than we originally anticipated, and thus were unable to model the site effect. Moreover, apart from documenting the proportion of culture negative smear-negative PLH, we did not model sample size and cost implications of late exclusions of smear-negative TB patients from clinical trials who are subsequently found to be culture negative.Our data suggest that treatment responses in smear-negative HIV-infected TB patients whose initial positive diagnostic test was Xpert are measurable in most patients, suggesting that smear-negative PLH could be included in trials of novel TB therapies. Serial Xpert testing reflects treatment responses and could be a useful real-time measure of treatment response, but more research is required to ascertain if this holds true with the Xpert Ultra and to determine if serial measures could predict long term TB treatment outcomes. HIV-infected smear-negative patients can be included in clinical trials provided sample sizes are adjusted upwards for those that are eventually found to be culture negative.Additional file 1: Supplementary Table S1.Additional file 2: Supplementary Table S2.


Despite sustained viral suppression with effective antiretroviral therapy (ART), HIV-infected patients with suboptimal immune recovery are still at high risk of both non-AIDS-related and AIDS-related events. The aim of this study was to investigate determinants potentially associated with suboptimal CD4 + T cell count recovery during free ART with sustained viral suppression among an HIV-infected Yi ethnicity population in Liangshan Prefecture, an area in China with high HIV prevalence.This retrospective study included HIV-infected Yi adults (≥ 18 years and baseline CD4 + T cell count less than 500 cells/μL) for whom ART supported by National Free Antiretroviral Treatment Program was initiated between January 2015 and December 2018 in Zhaojue County, Liangshan Prefecture. Virological suppression  was achieved within 12 months after ART initiation, and sustained virological suppression was maintained. Multivariate log-binomial regression analysis was used to assess determinants of suboptimal immune recovery.p < 0.001). Multivariable analysis demonstrated that low pre-ART CD4 + cell count and coinfection with HCV were associated with immune recovery of the HIV patients.There were 140 female and 137 male patients in this study, with a mean age of 36.57 ± 7.63 years. Most of the Yi patients were infected through IDU (48.7%) or heterosexual contact (49.8%), and the anti-HCV antibody prevalence was high . Of the 277 patients with a mean ART duration of 3.77 ± 1.21 years, complete immune recovery occurred in only 32.9%. The baseline CD4 + T cell count in patients with suboptimal and intermediate immune recovery was 248.64 ± 108.10 and 288.59 ± 108.86 cells/μL, respectively, which was much lower than the baseline 320.02 ± 123.65 cells/μL in patients who achieved complete immune recovery (Our study suggests that for HIV-infected Yi patients in Liangshan Prefecture, prompt ART initiation after diagnosis of HIV infection should be applied, and curative HCV treatment should be given to patients with HCV/HIV coinfection to improve the immunological effectiveness of ART.Trial registration NoneThe online version contains supplementary material available at 10.1186/s12879-022-07113-y. This was a retrospective study including 277 HIV-infected Yi ethnicity patients with sustained viral suppression in Liangshan Prefecture  to investigate potential determinants associated with suboptimal CD4 + T cell count recovery.All included patients were on NNRTI- or protease inhibitor-based ART regimens, precluding assessment of immune recovery in patients on integrase-based ART regimens.HCV RNA levels were not measured in this study; therefore, patients with anti-HCV antibody positivity but low HCV RNA viral load may have been included.https://www.unaids.org/en). In China, the number of people living with HIV surpassed 1 million by the end of 2020, with more than 12,000 people being newly infected (http://www.nhc.gov.cn/wjw/). Although the overall national prevalence of HIV/AIDS in China remains low, prevalence varies greatly in different regions and among different ethnic populations.Since its first report in 1981, HIV/AIDS has remained one of the world’s most serious public health challenges [In Liangshan Yi Autonomous Prefecture, which is located in Sichuan Province, Southwest China, and is a high epidemic area, 53.84% of the population is of Yi ethnicity (approximately 2.86 million). Currently, all six counties  in China with HIV/AIDS prevalence surpassing 1% are located within Liangshan Prefecture. Most of the HIV-infected individuals in Liangshan Prefecture are Yi, and the dominant transmission routes are injection drug use (IDU) and heterosexual contact [To effectively control the HIV/AIDS epidemic in Liangshan Prefecture, China’s National Free Antiretroviral Treatment Program (NFATP) –9 providThis retrospective study included all HIV-infected Yi adults (≥ 18 years and baseline CD4 + T cell count less than 500 cells/μL) who initiated ART supported by NFATP between January 2015 and December 2018 in Zhaojue County, Liangshan Prefecture , and HIV RNA in plasma was evaluated using the Roche Cobas TaqMan HIV-1 (HPS) test every 12 months until the end of 2020. Thus, the longest follow-up time was 72 months, and the shortest follow-up time was 24 months. Anti-hepatitis C virus (HCV) antibodies and hepatitis B surface antigen (HBsAg) were measured by ELISA with HCV antibody and HBsAg test kits, respectively . In addition, other routine follow-up tests, including haematology, urinalysis and blood liver function, were performed every 6 months; renal function for patients taking TDF was assessed every 6 months, as was the serum lipid level for patients taking LPV/r.2).Anaemia was defined as haemoglobin less than 120 g/L for men and 110 g/L for women. Liver function test abnormalities were defined as alanine aminotransferase (ALT) > 40 U/L, aspartate aminotransferase (AST) > 40 U/L or total bilirubin (TBil) > 17.1 µmol/L. Based on a recent study, the CD4/CD8 ratio was categorized into three groups: < 0·30, 0·30–0·45, and > 0·45 (> 0.45 as reference) . The bodThis study was approved by the Medical Ethics Committee of West China Hospital of Sichuan University . The study was performed by following the ethical guidelines expressed in the Declaration of Helsinki and the International Conference on Harmonization Guidelines for Good Clinical Practice. Informed consent was obtained from all subjects.p values were 2-sided, and p < 0.05 was considered statistically significant. Statistical analyses were performed using the statistical software SPSS .Data were extracted from NFATP Data System. Data were reported as the mean ± standard deviation for normal continuous variables and median (interquartile range) for non-normal continuous variables; frequency was used for discrete variables. Multivariate log-binomial regression models were used to assess determinants of immune recovery, with adjusted odds ratios (aORs) and confidence intervals (CIs). Confounders or predictors for each outcome were analysed as covariates according to their biological plausibility. The nonstatistical expert-based selection method was used to determine variables to include in the multivariate regression model , 15. VarBetween January 2015 and December 2018, 277 HIV-infected Yi patients (with baseline CD4 + T cell count less than 500 cells/μL) who initiated ART and achieved sustained virological suppression were included in this study to investigate the incidence of suboptimal immune recovery and associated determinants . In contrast, the prevalence of anti-HCV antibody positivity in patients with suboptimal and intermediate immune recovery was much higher than that in patients with complete immune recovery  . Most of the included Yi patients were in WHO clinical stages I and II , only 8 patients (2.9%) were in stages III and IV. The ART regimens were mostly based on EFV , followed by NVP  and LPV/r  in combination with TDF/3TC or AZT/3TC. Other variables, including the baseline CD4/CD8 ratio, HIV viral load, BMI, treatment duration, blood cell count, haemoglobin, and liver function, were comparable among the three groups of patients with different immune recoveries  to 63.9% (177/277), and the proportion of patients with CD4 + T cell count ≥ 200 cells/μL increased from 72.9% (202/277) to 90.3% (250/277) , 100–199 cells/μL , and < 100 cells/μL  had a lower chance of achieving a CD4 + cell count > 500 cells/μL (Table p = 0.005), > 350 cells/μL , and > 500 cells/μL . Taken together, we demonstrate that a low pre-ART CD4 + cell count and coinfection with HCV are associated with immune recovery in HIV patients.Multivariable analysis was carried out to further investigate potential determinants associated with suboptimal CD4 + count recovery in this population. A lower baseline CD4 + cell count was found to significantly influence achieving CD4 + cell recovery > 500 cells/mL. Specifically, compared with patients with a pre-ART CD4 + cell count ≥ 350 cells/μL, those with a pre-ART CD4 + cell count in the range of 200–350 cells/μL . Other variables, including age, male sex, baseline CD4/CD8 ratio, viral load, BMI, HBsAg, treatment duration, blood cell count, anaemia and liver function, were also not associated with immune recovery in this study.To avoid the unexpected bias from different ART regimens, we excluded the 26 patients on non-EFV-based regimen and only included the 251 patients on EFV-based ART in a newly generated multivariable analysis. Similarly, low pre-ART CD4 + cell count and coinfection with HCV were found to be associated with suboptimal immune recovery in this population  recently reported among HIV-infected patients in Guangxi Zhuang Autonomous Region . The HBVThe prevalence of anti-HCV antibody positivity among the 277 HIV-infected Yi patients included in this study was 43.7%, which may be explained by the fact that 48.7% of the patients were infected through IDU. Both HCV and HIV are blood-borne viruses, and the presence of HIV infection increases the transmission efficiency of HCV . It has Our study has limitations. First, all included patients were on NNRTI-based or protease inhibitor-based ART regimens, precluding assessment of immune recovery in patients on integrase-based ART regimens. Second, HCV RNA levels were not measured in this study; therefore, patients with anti-HCV antibody positivity but a low HCV RNA viral load may have been included. Third, there was a lack of data on smoking behaviour, which has been reported to play a role in suboptimal immune recovery , 47. FouIn summary, we demonstrate that a low pre-ART CD4 + cell count and HCV infection are associated with suboptimal CD4 + count recovery among HIV-infected Yi individuals on efficient ART in Liangshan Prefecture. Our study supports prompt ART initiation after HIV diagnosis and HCV eradication treatment in HCV/HIV coinfected patients by appropriate DAA regimens , not only for HCV cure per se but also for improving the immunological effectiveness of ART.Additional file 1: Table S1. Determinants associated with suboptimal CD4 + count recovery among 251 Yi patients with sustained HIV suppression on EFV-based ART.Additional file 2. Checklist for the appropriate reporting statement: STROBE.