This study is to investigate the difference in HIV-1 RNA pol gene expression in AIDS patients before and after antiviral treatment and its effect on the expression level of CD4 The participants included 200 AIDS patients who had undergone antiviral medication, and the quantity of HIV-1 RNA pol gene was determined using nested polymerase chain reaction (nPCR). The levels of CD3+, CD4+, and CD8+ T lymphocytes in peripheral blood were measured by flow cytometry before and after therapy. The receiver operating characteristics (ROC) curve was used to assess the impact of HIV-1 RNA pol gene expression and the CD4+/CD8+ ratio on the prognosis of AIDS patients. P < 0.05). Logistic analysis revealed that patients' viral loads were positively correlated with HIV-1 RNA and negatively correlated with CD4+/CD8+ (P < 0.05). The alanine aminotransferase (ALT), white blood cell (WBC) count, Serum creatinine (Cr), total cholesterol (TC), triglyceride (TG), and platelet (PLT) levels significantly increased following a 24-month therapy, while no significant changes were observed in the level of aspartate aminotransferase (AST), red blood cell (RBC), and neutrophil (NEU) (%). (P > 0.05).  After three months of therapy, the levels of HIV-1 RNA and viral load in the patients showed a drastic decline, while the levels of CD4+/CD8+ were markedly elevated (+/CD8+ T cells in peripheral blood. Antiviral drugs significantly inhibit the HIV-1 RNA POL gene expression and viral load in AIDS patients but upregulate the expression level of CD4 AIDS is a systemic disease caused by the HIV virus infection . It is cCurrently, antiviral therapy is a major approach to AIDS management. Combination antiretroviral treatment (cART) has reduced HIV from a potentially fatal illness to a manageable infection. The current regimen consists of two or three antiretroviral medicines. Several antiretroviral medication classes have been created and classified based on their mechanism of action in the blockage of the HIV replication cycle . In geneThe research work on the treatment of AIDS by traditional Chinese medicine (TCM) can be traced back to the 1980s. Studies have confirmed that TCM has significant effects in regulating immunity, enhancing the body's antiviral ability, improving clinical symptoms, and reducing the toxic and side effects of antiviral drugs. AIDS is classified as either an internal or external cause or a combination of internal and external causes. The specific treatment adopts the method of nourishing qi and nourishing yin, strengthening the righteousness and eliminating pathogenic factors, and treating the symptom [+/CD8+ T cells could better reflect the immune function of AIDS patients, compared to the expression of CD4+ T lymphocytes only [+/CD8+ T cells, the expression of the HIV-1 RNA pol gene, and viral load of AIDS patients after antiviral therapy.AIDS can impede or destroy immune function by targeting the primary immune cells, specifically CD4+ T cells and CD8+ T lymphocytes . Some retes only , 12. CD4tes only , 14. How+/CD8+ T cells, and viral load among 200 AIDS patients after antiviral treatment. The findings in this study are expected to provide more references for the antiviral therapy of AIDS.Thus, to bridge this gap in the AIDS study, the present study attempted to compare the expression of the HIV-1 RNA pol gene, the levels of CD4A total of 200 AIDS patients that received antiviral treatment from January 2016 to January 2020 were selected as the research subjects. The original sample size calculation estimated that 200 patients in each group would be needed to detect a 3-point difference between groups in a 2-sided significance test with a power of 0.8 and an alpha error level of 0.05.There were 106 males and 94 females, aged from 18 to 69 (42.59 ± 5.13) years. Permission and written informed consent were obtained from all the subjects and their relatives before commencement.All patients were over 18 years old and were eligible for receiving antiviral treatment .Meet the above-mentioned HIV/AIDS diagnostic criteria, confirmed by the Center for Disease Control and Prevention of our hospital to be positive for HIV antibodies by Western Blot test, and issue a confirmation reportAge over 18Those who meet the antivirus standardsVoluntarily signed the patient's informed consent, and can ensure regular follow-up and specimen collectionPatients with severe hepatic and renal insufficiency, or concurrent severe cardiovascular and cerebrovascular, pulmonary and hematopoietic system, nervous system and other diseasesPatients with autoimmune diseasesPregnant or breastfeeding womenPatients who have participated in clinical trials of other AIDS-related drugs within 1 year before the study drug treatmentThose who are allergic to the drugs taken by the institute during the experimentAll patients were treated under the HARRT regimen. Drugs used for the therapy included lamivudine , stavudine , nevirapine , and/or Efavirenz .+/CD8+ T cells in peripheral blood was determined. 3 mL of fasting venous blood of the patients were collected and transferred into an EDTA tube one day before the treatment or 3 months, 6 months, 12 months, and 24 months after the treatment. Subsequently, 0.5 mL of CD4+ antibody  and CD8+ antibody  was added, mixed gently, and incubated at 4°C for 30 minutes in the dark. The amounts of CD4+ and CD8+ T cells were analyzed by FACS . The CD4+/CD8+ ratio was calculated.The ratio of CD4μL containing 10 μL of RealQ Plus Master mix for Probe , 0.4 μM of each HIV primer, 0.2 μM of each internal control (IC) primer, 0.25 μM HIV probe, 0.125 μM IC probes, and 5 μl of cDNA. The amplification profile consisted of a single cycle of enzyme activation at 95°C for 15 min followed by 45 cycles of denaturation at 95°C for 10 s, annealing at 54°C for 30 s, and 72°C for 30 s with a single fluorescence acquisition at channel FAM/HEX. A nontemplate control was included in each qPCR assay. All the procedure was performed according to MIQE guidelines [For the determination of viral load, 3 mL of fasting venous blood was collected from the patients and transferred into an EDTA tube and then centrifuged for 30 minutes at 2000 r/min. Viral load was detected by quantitative Real-time PCR (RT-qPCR). RT-qPCR was performed using the ABI StepOne™ instrument. The reaction was set up in 20 idelines , 17.For the HIV-1 RNA pol gene expression, 5 mL of fasting venous blood was collected from the patients and transferred into an anticoagulant tube, and centrifuged through the Ficoll gradient for the isolation of monocytes. Specifically, 5 mL of peripheral blood were added into 0.6 mL of heparin and mixed with an equal volume of Hank's solution. Ficoll was carefully overlaid with blood in a new tube and centrifuged at 1500 r/min for 10 min. After centrifugation, an opaque band that contained monocytes at the interface between blood and Ficoll was collected and transferred into another tube. Thereafter, the band was mixed with an equal volume of the Hank's solution and centrifuged at 1000 r/min for 10 min. After centrifugation, the supernatant was removed and the cell pellets were washed twice with an equal volume of the Hank's solution. Finally, the cell pellets were re-suspended in 1 mL of RPMI-1640 culture medium and stored at 4°C for future use. The nested polymerase chain reaction (nPCR) was used to detect the HIV-1 RNA pol gene expression. The PCR reaction volume for both outside HIV-1 DNA primer and inner HIV-1 DNA primer was 25 PL. The amplification parameters of the outside HIV-1 primer were the same as that of the inner HIV-1 primer. The former was carried out for a total of 43 cycles, in contrast to 35 cycles for the latter. The positive and negative controls were set up for PCR amplification to obviate the false positive or negative results of PCR amplification.Biochemical indicators , white blood cell (WBC) count, Serum creatinine (Cr), total cholesterol (TC), triglyceride (TG), and platelet (PLT), aspartate aminotransferase (AST), red blood cell (RBC), and neutrophil (NEU)) in the venous blood collected 1 day before the treatment or 24 months after the treatment was also determined by an automatic biochemical analyzer (Beckman Coulter).The patients in both groups received 148 mg of Shenling Fuzheng capsules (37 g/capsule) thrice daily.μl) were measured at enrollment and at the completion of treatment using a FACS Calibur flow cytometer from BD, USA. One follow-up test was performed 6 months after treatment. Detection of CD+3, CD4+, CD+8 cell percentage and CD4+/CD+8 in peripheral blood was performed using BECKMAN Cytomics FC500 Flow Cytometry Analyzer and BFCKMAN COULTER reagents from USA; (4) the correlation between the HIV-1 RNA gene and the viral load using logstic regression analysis; and (5) ALT, WBC, Cr, TC, TG, PLT, AST, RBC and NEU% before and after treatment.For all the 200 participants in the present study, the observant indexes included (1) the expression level of the HIV-1 RNA pol gene before and after treatment; (2) the viral load before and after treatment; (3) peripheral blood CD+3, CD4+, and CD+8 cell counts  and comparisons between two groups were analyzed by the Chi-squared Test. Logstic regression analysis was used to study the correlations of relevant indexes. Differences between samples were examined using paired two-sided Student's t-test. If the p value is less than 0.05, it means that there is a statistically significant difference. The Gradpad Prism version 7.0 was used for generation of graphs.Statistical analysis was performed with SPSS software version 25.0 and quantitative data were presented as mean ± standard deviation (SD). The transformed data were tested for normality using Shapiro-Wilk, and all log-transformed variables were normally distributed. The Mann–Whitney P < 0.001)  .P < 0.001, The peripheral CD4+/CD8+ T cell levels of 200 patients elevated considerably after therapy, suggesting that antiviral medication could successfully activate the immune system and boost AIDS patients' immunity . Thus, antiviral therapy may be harmful to AIDS patients' hepatic and renal functioning, as well as lower plasma lipid levels.After 24 months' treatment, levels of ALT, WBC, Cr, TC, TG, and PLT significantly increased  This experiment is a short-term observational study of the curative effect, which cannot systematically observe the long-term clinical outcomes, and the relatively small sample size and short observation period of this study will bias the study results. (2) Due to the overall high level of CD4+ T lymphocyte counts in HIA/AIDS patients enrolled in this trial, and there are many types of HAART regimens, the enrolled HIV/AIDS patients failed to maintain consistent treatment regimens. This may be one of the factors compromising the test results. Therefore, in the subsequent research, the consistency of the experimental conditions between the groups should be maintained as much as possible, and the factors that may affect the experimental results should be excluded.HIV-1 RNA pol gene expression and viral load in AIDS patients decreased considerably after antiviral treatment, but peripheral CD4+/CD8+ T cells rose dramatically. The present study showed that antiviral medications effectively reduce HIV-1 RNA POL gene expression and viral load in AIDS patients while increasing the expression level of CD4+/CD8+ T cells in peripheral blood. Furthermore, the sensitivity and specificity of relevant indicators may be used to assess the prognostic impacts of AIDS patients.A large number of clinical trials have confirmed that TCM combined with HAART can alleviate the symptoms, improve the quality of survival and enhance the immune function of HIV patients. However, there is no standardized understanding of the etiology and pathogenesis of HIV in TCM, and the mechanism of action of TCM used for the treatment of HIV remains unknown. The benefits of holistic, diverse, and multitargeted TCM treatment still require further investigation.


Adherence to antiretroviral (ARV) therapy is critical in order to achieve and maintain viral suppression and improve immune function. Clinical pharmacists and pharmacies focused on human immunodeficiency virus (HIV) have demonstrated the ability to increase ARV medication adherence and subsequently have a positive effect on these lab markers.To evaluate the effect of an integrated health system specialty pharmacy service with a clinic-embedded, HIV-trained pharmacist and pharmacy technician on ARV medication adherence rate, viral load, and CD4 count.This was a single-center, retrospective cohort study conducted from August 7, 2017, to June 30, 2018, at an indigent outpatient infectious disease clinic within Atrium Health (AH), a not-for-profit health system based in Charlotte, NC. The intervention group (opt-in group) received HIV patient care that involved the health system specialty pharmacy service. Once a patient was enrolled in the specialty pharmacy service, medication reconciliation was completed by the pharmacist, financial assistance and prior authorizations were completed if needed; prescriptions were delivered to the patient; and monthly refills calls were conducted to assess adherence, tolerability, and medication changes. The control group (opt-out group) received HIV patient care that did not incorporate the health system specialty pharmacy. The primary endpoints were medication adherence, viral suppression, and CD4 counts. Within-group comparisons from baseline to follow-up were made along with group-to-group comparisons. Adherence was calculated using medication possession ratio.P < 0.01). All but 3 patients  using AH SPS reached viral suppression, and all but 1 had improved immune function with a CD4 count of 200 or greater by the end of the observation period (P = 0.03). The change in viral suppression and CD4 count of 200 or greater was not statistically improved between baseline and follow-up in those opting out of using AH SPS. When comparing the 2 groups at reaching these endpoints, there was no statistically significant difference in viral suppression and CD4 count.For those patients using Atrium Health Specialty Pharmacy Service , the overall median adherence rate was higher at 100% versus only 94% for those patients (n = 50) that opted out of the service (AH SPS was able to demonstrate improved ARV adherence in those patients using an integrated specialty pharmacy with an embedded pharmacy team, coordinated monthly medication delivery, and refill reminder and adherence calls. This in turn led to improved viral suppression and immune markers by the end of the observation window for patients using AH SPS. What is already known about this subjectHuman immunodeficiency virus (HIV) continues to be a serious health issue in the United States, with an estimated 1,122,900 adults and adolescents living with HIV at the end of 2015, of which approximately 46% are living within the southern United States.Optimal adherence to HIV therapy is critical to achieve and maintain viral suppression, which in turn improves immune function and reduces the risk of transmission and new infections.HIV-focused pharmacies and clinical pharmacists, as experts in medication management, have been shown to play a key role in helping to promote and assist with medication adherence.What this study addsThis study demonstrated that an integrated health system specialty pharmacy within an outpatient infectious disease clinic increases adherence to antiretroviral therapy, as well as improves viral suppression rates and CD4 counts among those patients using its services.Because the management of HIV-infected patients is a highly specialized area of practice, these patients may especially benefit from the high-touch care that is provided by this type of integrated practice model.2Human immunodeficiency virus (HIV) continues to be a serious health issue, with more than 36 million people worldwide infected. Within the United States, more than 1.1 million adults and adolescents were living with HIV at the end of 2015, including an estimated 15% who were undiagnosed. In 2015, of all HIV-infected adults, only 48% were retained in continuous HIV care, and 49% were virally suppressed. While HIV infection is still a national issue, the epicenter of the epidemic has now shifted to the South. The southern states have experienced the greatest burden of HIV infection of any U.S. region, with an estimated 46% of all HIV infected patients residing in the South. This region also accounts for more than half of all new HIV diagnoses.5 Previous research has reported that adherence at a rate of 95% or greater is necessary for optimal ARV efficacy. While in other disease states, lower adherence rates of 80% are considered reasonable, adherence of less than 95% in patients with HIV can be correlated to increased resistance, as well as to poorer outcomes.8 For example, in a study at a free HIV clinic, it was found that when adherence levels were below 95%, the percentage of patients with viral loads consistently below 400 copies per mL (copies/mL) fell below 60%.9A key component in helping to alleviate the burden of HIV in the South is to ensure that patients are adherent to treatment regimens. Nearly all patients who adhere to antiretroviral (ARV) therapy are able to achieve and maintain viral suppression, which is critical to restoring immune function, improving survival, preventing the development of resistance, and reducing transmission.P < 0.0 01).10 A study by Cocohoba et al. (2012) compared 4,254 patients using HIV-focused community pharmacies with 11,679 patients using traditional pharmacies and found that patients using an HIV-focused pharmacy had significantly higher regimen refill adherence as measured by median MPR .11Pharmacists have specialized knowledge of medication use and can play a key role in helping to promote and assist with adherence in HIV-infected patients. Several studies have shown that community pharmacies with specially trained and educated HIV pharmacists had higher ARV refill adherence. More specifically, Hirsch et al. (2009) found that patients using HIV medication therapy management programs in place at 10 community pharmacies in California were more likely to be classified as adherent with a medication possession ratio (MPR) of 80%-120% over those using nonspecialized community pharmacies  at 6 months.12 Another study that was conducted by Kaiser Permanente Northern California demonstrated that in clinics with embedded clinical pharmacists, patients tended to be more likely to achieve a viral load < 500 copies/mL at 12 months.13To correlate pharmacist-directed adherence counseling with improved clinical outcomes, a 2018 study from an infectious disease (ID) clinic in New Mexico demonstrated that embedded clinic pharmacists conducting adherence counseling for ARV not only increased adherence but also improved CD4 counts and decreased viral loads.14While there is plenty of evidence to suggest that specialized community/dispensing pharmacies and clinic-embedded pharmacist involvement in HIV care promote positive outcomes, there is a lack of data evaluating the effect of integrating a health system specialty pharmacy, which combines the dispensing and clinical components, into an ID clinic. An integrated health system specialty pharmacy is unique because it has the ability to connect the patient, provider, pharmacist, and pharmacy at the point of care. Also, all involved members of the care team have access to the electronic medical record (EMR), which provides all relevant patient data such as laboratory test values, progress notes, and clinic appointments. EMR messaging allows the specialty pharmacy to easily communicate with the rest of the team if there are concerns about compliance, financial hardship, or adverse drug events.15 Northwestern Medicine specialty pharmacy created an HIV service line in 2014 that connected its specialty pharmacy to existing clinical pharmacists embedded within an ID clinic. This integration has allowed for closed-loop medication management in HIV-infected patients by providing medication education, prescription fulfillment, assistance with medication access, medication delivery, refill reminder calls, identification of barriers to adherence, side effect management, reduction of drug-drug interactions, and treatment monitoring.15To our knowledge, there is only 1 other study that has specifically evaluated and described this concept.Atrium Health (AH), a health system based in Charlotte, NC, currently cares for over 5,000 HIV-infected patients across 6 different counties through 3 urban outpatient ID clinics. Of these patients, approximately 3,000 have a gross family income that is equal to or less than 300% of the federal poverty guidelines. In August 2017, AH Specialty Pharmacy Service (SPS) integrated care by embedding a 2-person team that consisted of an HIV clinical pharmacist and pharmacy technician within 1 of the 3 health system outpatient ID clinics. The Myers Park ID clinic was selected as the first location to integrate the SPS model, since it is a safety net clinic serving underinsured patients, many of whom are impoverished and have low literacy, along with adherence issues and concomitant mental health and substance abuse disorders. Our study aimed to assess the effect that an integrated health system specialty pharmacy has made on clinical outcomes for HIV-infected patients with insurance billable by AH SPS.This was a single-center, retrospective cohort study conducted in the Myers Park ID Clinic from August 7, 2017, to June 30, 2018. The evaluation received quality improvement exemption from the AH Institutional Review Board. The Myers Park ID Clinic currently cares for HIV-infected patients through 5 full-day clinics per week from 3 different HIV-trained physicians. Before August 2017, there was no specialty pharmacy integration. The intervention group included all HIV-infected patients with contracted insurance plans who agreed to enroll in AH SPS between August 7, 2017, and December 31, 2017. The control group consisted of patients with contracted insurance plans who opted out of using AH SPS during this same period and continued to manage their own refills through nonintegrated, external pharmacies. Their response to opt in or opt out of using our health system specialty pharmacy was tracked in an encrypted Excel spreadsheet .During clinic appointments, the SPS technician performed a benefits investigation to determine whether a patient’s individual insurance plan was contracted with AH SPS. If contracted, the specialty pharmacy team (pharmacist and/or pharmacy technician) offered the service. Patients who used our specialty pharmacy could have their ARV and other maintenance medications dispensed and delivered to their homes (intervention group). For patients with contracted insurance who opted out (control group) of our pharmacy services, they continued to manage their own medication refills through nonintegrated external pharmacies. Individuals without insurance used the Ryan White HIV Medication Assistance Program through the state-contracted pharmacy  or manufacturer assistance through the indigent pharmacy at the Myers Park Clinic. For patients with noncontracted insurance plans or no insurance, the SPS team was still available to help  and could offer financial assistance in the form of grants or copay cards, prior authorization completion, and medication or adherence counseling. Patients without insurance or noncontracted insurance plans were not included in the scope of this study.Once the patient agreed to enroll, prior authorizations were completed and financial assistance for medication copays were obtained, if necessary, by the SPS technician. The HIV specialty pharmacist then completed a comprehensive medication review (CMR). In addition, during the CMR, the pharmacist evaluated the antiretroviral dose and regimen appropriateness by reviewing kidney and liver function, past therapeutic successes and failures, resistance profiles, comorbidities, and interactions with other medications. If any clinical issues were identified, the pharmacist consulted directly with the prescribing physician face-to-face while in clinic or via EMR messaging. If necessary, the pharmacist ordered and evaluated labs pertinent to ARV treatment.After the CMR was complete, the pharmacist offered education that included initial counseling on ARV medication administration, importance of strict adherence, drug interactions, and common side effects. During this time, all non-ARV maintenance medications were synced to the ARV medications to ensure that the patients’ prescriptions were due at the same time each month. Once all of this was complete, medications were delivered directly to patients’ homes (or to the clinic).The patient was contacted by our specialty pharmacy each month for refill reminders and to assess adherence, medication changes, and regimen tolerability. If the patient missed doses, had side effects, or had medication changes during a monthly refill call, the HIV specialty pharmacist was notified and followed up with the patient. An annual clinical assessment was also completed by the HIV specialty pharmacist. A specialty pharmacy patient management software program was used to facilitate scheduling of all refill calls, annual clinical assessments, and documentation of patient encounters and interventions in a standardized format .Data were collected from August 7, 2017, to June 30, 2018, through chart review and phone calls. Baseline patient characteristics were collected to include age, gender, race, insurance type, regimen type/complexity, education, mental health conditions, and substance abuse disorders. Prescription refill history was reviewed through pharmacy claim data from the date of entry or declination to the program up to the end of the follow-up. Adherence rate was calculated using MPR. For collection of external pharmacy refill data, manual phone calls were made to each pharmacy to inquire about refill histories. For purposes of this evaluation, refill history included the date that the prescription was filled. Baseline viral load and CD4 count at time of entry or declination to the program was recorded, as well as at the end of the observation period. Three main clinical endpoints included (1) ARV adherence rate, (2) number of patients with a suppressed viral load of < 20 copies/mL, and (3) number of patients with CD4 counts of 200 or greater.16 If MPR was greater than 100%, it was truncated to 100%. Either the parametric 2-sample t-test or the nonparametric Wilcoxon rank sum test for continuous variables was performed to evaluate between-group differences. Fisher’s exact test was used to compare group percentages. McNemar’s test was performed to compare binary data at baseline and the end of follow-up within groups. To better evaluate robustness of the results, sensitivity analyses were conducted by including censored patients with less than 6 months of follow-up. A P value of < 0.05 was considered statistically significant. All analyses were conducted using SAS Enterprise Guide version 7.1 .Summary statistics for continuous (mean ± standard deviation) and categorical variables (count and percentage) were used to describe the study populations and outcomes. MPR was defined as the total number of days that antiretroviral drugs were dispensed by the pharmacy to each patient, divided by the patient’s total follow-up time in days  since ARV initiation.A total of 59 patients opted to use AH SPS. Complete data were unable to be collected for 13 patients because of failure to reach the end of observation period. Thus, 46 patients using AH SPS completed the full observation period up to June 30, 2018. Between August 7, 2017, and December 31, 2017, 164 patients with contracted insurance plans were offered the service but opted out of using AH SPS. The main reasons for declination to enroll with AH SPS were loyalty to current pharmacy, use of pill packing services (AH SPS currently does not offer), and fear of medication delivery. Of these 164 patients, 58 were selected from the encrypted Excel spreadsheet using a random generator to serve as the control (opt-out) group. Complete data were unable to be collected on 8 patients because of failure to reach the end of the observation period. Thus, 50 patients using nonintegrated external pharmacies completed the full observation period.Within both groups, the main reasons for failure to complete the observation period included violation of clinic follow-up policy (greater than 6 months since last clinic visit), loss of insurance, relocation, and incarceration. For purposes of this study, we did not include patients who failed to complete the observation period in the main analysis but did conduct sensitivity analyses by including those censored patients.P = 0.04), and there was a similar ratio of males to females. The majority of patients were black, making up 80.4% of opt-in patients compared with 96.0% within the opt-out group (P = 0.03). There were nearly twice as many insured through Medicaid in the opt-out group (32.0%) versus the opt-in group (17.4%). The majority (80%-90%) of patients in each group had either Medicare or Medicaid as their payer source. Although some distributional variations were present in factors such as education, employment status, homelessness, substance disorders, mental comorbidity, type of regimen, daily dosing, and number of pills in regimen, these factors were not statistically significant.Baseline characteristics of all patients are shown in P < 0.01. Furthermore, the total number of patients within the opt-in group with an MPR of 90% or greater was significantly higher when compared with the opt-out group . The opt-in group also had more patients with a higher MPR of 95% or greater .For those patients using AH SPS, the median MPR was higher at 100%  versus only 94% (Q1-Q3: 82%-99%) for those patients who opted out of the service . This diFor the opt-in group, an average of 238 days (8 months) lapsed between baseline labs and follow-up labs by the end of the observation period. For the opt-out group, slightly more time passed, with an average of 263 days (8.8 months) between baseline labs and follow-up labs by the end of the observation period. This difference in follow-up did not have any meaningful effect on the results.P = 0.03; Within the opt-in group, 10 of the 46 patients had a detectable viral load of 20 copies/mL or greater at baseline. By the end of the observation period, all but 3 reached viral suppression of < 20 copies/mL .When looking at change in viral suppression from baseline to follow-up, patients using AH SPS had statistical improvement in this lab marker, while those opting out did not. Overall, a larger number of patients reached viral suppression within the opt-in group at 93.5% versus 82.0% of those within the opt-out group . HoweverP = 0.03; Of the 6 patients in the opt-in group who had CD4 counts < 200 at baseline, all but 1 had improved immune function with a CD4 count of 200 or greater by the end of the observation period (P = 0.36).In the opt-in group, 97.8% of patients had improved immune function with a CD4 count of 200 or greater versus 92% of the opt-out patients at follow-up. While there was statistically significant improvement in immune function within the opt-in group from baseline to follow-up, when the 2 groups were compared, the difference in reaching the endpoint of CD4 of 200 or greater did not meet statistical significance  compared with 94% (Q1-Q3: 81%-99%) in the group that opted out of the service (P < 0.01). Within the opt-in group, the number of patients who had a detectable viral load of 20 copies/mL or greater decreased from 19 (32.2%) at baseline to 7 (11.9%) at the end of study . Multivariable logistic regression models showed similar results after adjusting for age, race, and insurance types.The opt-in group achieved a higher percentage of MPR as 95% or greater compared with the opt-out group , while only 94% (IQR: 82%-99%) for those opting out of the service. As demonstrated in current literature, this has clinical relevance, since high adherence rates are correlated with viral load reduction, transmission reduction, and improved CD4 counts.18The MPR calculation was chosen as a marker for adherence because it provides a way to review pharmacy data claims, objectively determine patient adherence rates, and in turn eliminate bias in the form of patient-reported self-adherence.This association with high adherence was further substantiated by our study because improvements in viral suppression, as well as CD4 counts, from baseline to follow-up were observed for patients using AH SPS. Nearly 94% of enrolled patients had a suppressed viral load of < 20 copies/mL, and 98% had CD4 counts of 200 or greater with no treatment failure or HIV drug resistance by observation end. For those patients within the opt-out group, there was an overall lower adherence rate and no statistically significant improvement in viral load suppression or in immune function from baseline to follow-up.While improvement in viral suppression and immune function from baseline to follow-up was observed for AH SPS patients, when compared with the opt-out group, there was no statistically significant difference between the 2 at reaching these clinical endpoints. This is important to note, since the within-group before/after changes are short-term indicators of the benefit of pharmacy involvement and do not conclusively prove a difference exists between the 2 groups in terms of improved virologic or immunologic markers. Future studies are needed to assess the full effect of integrated specialty pharmacies.This evaluation is certainly not without limitation. While a retrospective chart review of specialty pharmacy involvement at a single clinic provided valuable insight, a controlled prospective study would be ideal to better assess the effect of AH SPS. A longer evaluation with a larger sample size would provide more robust results, as well as longer-term clinical outcomes such as increased clinic retention, improved quality of life, decreased drug resistance, and reduction of drug-drug interactions with AH SPS interventions. In addition, our study was not randomized, which can introduce potential selection bias between 2 groups.In regard to adherence calculations, MPR may be over- or understated, since dispensing of a medication does not always entail its use. Also, the fill dates collected from the external pharmacies are subject to the accuracy of the individual at the pharmacy location providing the information.For baseline characteristics, we did not compare the 2 groups for complexity of other medications or comorbidities (outside of psychiatric diagnoses/substance abuse disorders). Patients with multiple comorbidities may be less adherent, given the layer of complexity this adds to the number of medications that they may be required to take on a daily basis. In addition, there were significantly more elderly patients within the opt-out group, although the reasons for this are not entirely clear.While this study did compare the opt-in (intervention) group to a control group that did not have AH SPS intervention, it should be noted that 27 of the opt-out patients were using external nonintegrated specialty pharmacies instead of regular retail/community  pharmacies. While these external specialty pharmacies were not integrated within the health system as with our model, this disparity could skew results in favor of more positive outcomes for the opt-out group, given the higher standard of care, training, and service required of specialty pharmacies versus retail pharmacies. On the other hand, results could be skewed in favor of more positive outcomes for the opt-in patients, since these individuals agreed to enroll in our service, potentially indicating that they may have been more highly engaged in their own health care, more likely to have been adherent, and anticipated a higher degree of follow-up.Finally, while the endpoints of suppressed viral load and improved immune function reached statistical significance within the opt-in group from baseline to follow-up, the difference in proportion of patients reaching these endpoints was not significant when compared with the opt-out group. The lack of statistical significance in the group-to-group comparison may be attributed to the small sample sizes or residual confounding.AH used a practice model that fully integrated a specialty pharmacy service within an outpatient ID clinic. The goal of this study was to improve clinical outcomes for enrolled patients. Ultimately, this approach to patient care clearly demonstrated higher adherence rates to ARV medication for those enrolled within the program compared with those opting out. Statistically significant improvements in virologic and immunologic markers were also observed for enrolled patients from baseline to follow-up.While adherence rates were significantly better in the internal specialty pharmacy group, in order to identify a true difference between internal and external pharmacy services in regards to viral load suppression and CD4 count, larger sample sizes may be needed. Further studies with more robust sample sizes are warranted to fully quantify and describe the effect an integrated health system specialty pharmacy can have on HIV clinical outcomes.


The present study aimed to build and validate a new nomogram-based scoring system for the prediction of HIV drug resistance (HIVDR).Totally 618 patients with HIV/AIDS were included. The predictive model was created using a retrospective set (N = 427) and internally validated with the remaining cases (N = 191). Multivariable logistic regression analysis was carried out to fit a model using candidate variables selected by Least absolute shrinkage and selection operator (LASSO) regression. The predictive model was first presented as a nomogram, then transformed into a simple and convenient scoring system and tested in the internal validation set.The developed scoring system consisted of age (2 points), duration of ART (5 points), treatment adherence (4 points), CD4 T cells (1 point) and HIV viral load (1 point). With a cutoff value of 7.5 points, the AUC, sensitivity, specificity, PLR and NLR values were 0.812, 82.13%, 64.55%, 2.32 and 0.28, respectively, in the training set. The novel scoring system exhibited a favorable diagnostic performance in both the training and validation sets.The novel scoring system can be used for individualized prediction of HIVDR patients. It has satisfactory accuracy and good calibration, which is beneficial for clinical practice. Initialnce 2016 . Howevernce 2016 . In addince 2016 .HIV drug resistance (HIVDR) is one of the problems in combating the HIV epidemic, elevating the risk of PLHIV whose disease continues to be infectious. In 2021, the Joint United Nations Programme on HIV/AIDS (UNAIDS) released the “Fast-Track strategy” initiative with the following goals. By the year 2030, there is a global consensus to aim for 95% of all PLWH knowing this diagnosis, 95% of those diagnosed receiving treatment, and 95% of those on treatment achieving sustained virologic suppression . For theAt present, there are many methods for drug resistance gene detection, including Illumina NGS, Sanger population sequencing, AS-PCR, 454 pyrosequencing, and other new approaches . However+ T cell count and viral load  due to prolonged ART exposure and poor adherence, leading to viral rebound and treatment failure . In addiral load . As provTherefore, our main objective was to generate a multivariable logistic regression prediction model based on a mixture of clinical factors to predict HIVDR. Then, a unique scoring system was build using the primary prediction model’s modified nomogram for easy clinical application. Additionally, in the retrospective analysis, we internally verified the diagnostic value of the improved scoring model.22.1http://hivdb.stanford.edu) to be evaluated for antiretroviral resistance using the list of major HIV-1 resistance mutations (major HIV-1 drug resistance mutations) standardized by the Stanford HIV Database (http://hivdb.stanford.edu/assets/media/resistance-mutation-handout feb2019.b0204a57.pdf). We defined patients who were potentially resistant or differentially resistant to any of the antiretroviral drugs as the drug-resistant (DR) group, and patients who were drug-sensitive as the drug-sensitive (DS) group.The study was a retrospective HIV/AIDS cohort collected from the AIDS Prevention and Control Information System (AIDS-PCIS). We incorporated patients with HIV/AIDS registered in four regions of Hubei province, including Wuhan, Huangshi, Jingmen and Xianning, from June 2017 to June 2022. Totally, 618 PLWH were enrolled and divided into two groups. 70% of participants (N=427) were randomly allocated to the training set and the remaining 30% (N=191) in the validation set. We performed genotypic drug resistance testing in all participants. The sequences were sent to the Stanford HIV Drug Resistance Database (Inclusion criteria were: (1) confirmed as a PLWH; and (2) ≥18 years old. Exclusion criteria were: (1) pregnancy and lactation in women; (2) refusal of drug resistance testing. Variables of PLWH including age, sex, body mass index (BMI), transmission route, duration of ART, adherence, CD4 T-cell count, HIV viral load and laboratory parameters were collected before the drug resistance testing. Treatment adherence was assessed by the proportion of days covered, which is the sum of days during follow-up. Poor adherence was defined as the proportion of days covered less than 80%. HIV viral load was logarithmically transformed before being included. The Wuhan Jinyintan Hospital’s ethics committee approved the study protocol, and all participant data were obtained anonymously.2.2http://cran.r-project.org). Two-sided p<0.05 was considered statistically significant.Although we did not officially compute sample size, we evaluated the data sufficiency using the event per variable method . We used33.1In this study, of the 618 patients included, most were male , and mean patient age was 39.5 years (IQR: 24.0-55.0 years). HIV drug resistance testing were performed in 303 patients before starting ART therapy, while the remaining 315 patients were tested after more than 6 months of ART therapy. The major infection route was sexual transmission: heterosexual transmission (50.2%) and MSM (48.1%). Among the DRMs detected, antiretroviral resistance was observed in 47.4% (293/618) of PLWH undergoing ART therapy Table 1.3.2In the training set, 33.5% (207/618) were HIV-DR patients, and most of the variables included in this study were significantly different between the DR and DS groups Figure 2And then, a nomogram , duration of ART (5 points), adherence (4 points), CD4 T cells (1 point) and HIV viral load (1 point) Table 2.3.3Based on a cutoff value of 7.5 points, PLWH were more likely to be diagnosed with DR in the training set with a total number of points greater than 7.5, whereas they were less likely with a total number of points below 7.5. The corresponding sensitivity, specificity, PLR and NLR values for 7.5 points as the ideal cutoff were 82.13%, 64.55%, 2.32, and 0.28, respectively Table 3.4Although ART has achieved great progress in recent history , the incA first-line regimen for adults and adolescents was proposed in 2016 by World Health Organization, containing two nucleoside reverse-transcriptase inhibitors (NRTIs) with either a non-nucleoside reverse-transcriptase inhibitor (NNRTI) or an integrase inhibitor (INSTI) . In 2021Furthermore, most of the methods used to predict HIVDR are not sufficiently generalized for normal clinical practice due to inconvenience. Therefore, it is crucial to design a feasible and simple method to diagnose drug resistance. Based on several major parameters, we constructed a predictive model by selecting the most important indicators by the LASSO regression. This nomogram for predicting HIVDR in PLWH patients incorporated 5 variables, including age, duration of ART, adherence, CD4 T cells and HIV viral load, was built. In the training and validation sets, this nomogram had good calibration, diagnostic performance, and clinical utility. We transformed the nomogram into a scoring system for clinical application; this scoring system also demonstrated excellent diagnostic performance in the training and validation sets. It is important to note that our scoring method was based on a variety of clinical and laboratory indicators that are readily available in most hospitals, even community hospitals, with an acceptable overall cost.In addition, we analyzed the clinical significance of these predictors. Regarding “duration of ART”, it is widely admitted that the longer the ART administration, the higher the risk of DRM. Nicholas  found thInterestingly, there were strong correlations (P<0.01) between drug resistance and some factors such as delayed treatment, Hb and BMI (Our study has several advantages. Firstly, individual indicators either have low sensitivity or low specificity, and the combined indicators have better comprehensive predictive ability. Secondly, the indicators selected for the model are simple, convenient, rapid and inexpensive, which can be promoted and used in primary hospitals. Thirdly, a scoring model for facilitates clinical application is established to help clinicians identify HIV drug resistance high-risk groups and thus to determine them for gene testing, the gold standard of drug resistance. This way could reduce treatment failure and avoids wasting medical resources.However, the patient selection in our study was biased and not randomized. To gain high-level evidence for the potential clinical applicability of the scoring system in the future, multicenter validation of the scoring system with a sizable research population is urgently required.In conclusion, the novel scoring system is based on five easily accessible clinical parameters and shows excellent diagnostic performance and favorable calibration in determining the susceptibility to DRM in PLHIV. We recommend the widespread application of this novel scoring model in HIV-designated hospitals to identify patients at increased risk of DRM quickly and cost-effectively.The original contributions presented in the study are included in the article/LR and XW conceived and designed the experiments. JY and WZ wrote the article. JY, WZ, HL collected and analyzed the data. All authors contributed to the article and approved the submitted version.


Antiretroviral therapy (ART) is a lifesaving intervention for people living with HIV infection, reducing morbidity and mortality; it is likewise essential to reducing transmission. The “Treat all” strategy recommended by the World Health Organization has dramatically increased ART eligibility and improved access. However, retaining patients on ART has been a major challenge for many national programs in low- and middle-income settings, despite actionable local policies and ambitious targets. To estimate retention of patients along the HIV care cascade in Liberia, and identify factors associated with loss-to-follow-up (LTFU), death, and suboptimal treatment adherence, we conducted a nationwide retrospective cohort study utilizing facility and patient-level records. Patients aged ≥15 years, from 28 facilities who were first registered in HIV care from January 2016 –December 2017 were included. We used Cox proportional hazard models to explore associations between demographic and clinical factors and the outcomes of LTFU and death, and a multinomial logistic regression model to investigate factors associated with suboptimal treatment adherence. Among the 4185 records assessed, 27.4% (n = 1145) were males and the median age of the cohort was 37 (IQR: 30–45) years. At 24 months of follow-up, 41.8% (n = 1751) of patients were LTFU, 6.6% (n = 278) died, 0.5% (n = 21) stopped treatment, 3% (n = 127) transferred to another facility and 47.9% (n = 2008) were retained in care and treatment. The incidence of LTFU was 46.0 (95% CI: 40.8–51.6) per 100 person-years. Relative to patients at WHO clinical stage I at first treatment visit, patients at WHO clinical stage III  or IV  had increased risk of LTFU; whereas at registration, age category 35–44  and 45 years and older  had a decreased risk. For death, patients assessed with WHO clinical stage II , III , and IV  had an increased risk, while non-pregnant females  and pregnant females  had a decreased risk when compared to males. Suboptimal adherence was strongly associated with the experience of drug side effects–average adherence [adjusted odds ratio (aOR) 1.45, 95% CI: 1.06–1.99, p = 0.02) and poor adherence , and attending rural facility decreased the odds of average adherence  and poor adherence . Loss-to-follow-up and poor adherence remain major challenges to achieving viral suppression targets in Liberia. Over two-fifths of patients engaged with the national HIV program are being lost to follow-up within 2 years of beginning care and treatment. WHO clinical stage III and IV were associated with LTFU while WHO clinical stage II, III and IV were associated with death. Suboptimal adherence was further associated with experience of drug side effects. Active support and close monitoring of patients who have signs of clinical progression and/or drug side effects could improve patient outcomes. The World Health Organization (WHO) estimated in 2020 that 37.7 million people worldwide were living with HIV (PLHIV), of whom a significant majority of 25.4 million are living in the WHO African region . By the Studies have shown that an adherence rate of no less than 95% is required for treatment success –9. SeverCountries are now adopting differentiated care models which involves several strategies that can help mitigate health system-level and individual-level barriers to accessing care, enhancing retention and achieving viral suppression . South ASince the establishment of its National AIDS and STI Control Program (NACP) in 1986, Liberia has been making strides to reduce the incidence of HIV in the population. Early initiation of ART, irrespective of WHO clinical stage and CD4 cell count, and decentralization of services to primary health facilities have resulted in unprecedented access to treatment services across the country. As part of this expansion of ART, the NACP also adopted the ‘Treat All’ recommendations in WHO’s 2015 Consolidated HIV guidelines . This exThe HIV/AIDS context in Liberia—a low-income country in West Africa—reflects a low-level generalized epidemic with an estimated 35000 (29000–43000) people living with HIV (PLHIV), corresponding to an estimated prevalence of 1.1 (0.9–1.4) in adults aged 15–49 years and about 19,000 people on antiretroviral therapy (ART) in 2020 . When coi.e., poor retention) in care and understand context-specific factors associated with it to adequately plan interventions that maximizes efficiency and cost-effectiveness. In Liberia, a previous cross-sectional study examining the impact of the 2014–2015 Ebola virus Disease epidemic on HIV services demonstrated an increase in HIV testing and care enrolment in the population between 2014 and 2015 [Despite ambitious targets and actionable local policies to promote early and accessible ART initiation, retention in care is recognized by healthcare providers as a major challenge to Liberia’s attainment of improved treatment outcomes, yet limited evidence around the care cascade and actual rates of retention exists. It is important for national programs to quantify the prevalence of attrition , Institutional Review Board (IRB). The IRB waived the requirement for informed consent for use of data from medical records. Data analyzed were anonymized prior to analysis.i.e., were recently diagnosed and were receiving HIV care for the first time) at selected treatment facilities across Liberia between 1 January 2016–31 December 2017. Date of diagnosis for patients is typically the same as the date of registration in care. Routinely collected data pertaining to HIV care from medical records for 24 months from the date of registration for HIV care were collected. The study was conducted in strict adherence to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.This retrospective cohort study involved patients ≥15 years, who newly registered for HIV care , who were confirmed HIV-positive and were newly registered at the 28 facilities providing HIV care and treatment services between 1 January 2016 and 31 December 2017. Patients who were restarting ART in the study enrolment period after being lost to follow-up previously were excluded. Any patients whose charts contained inaccurate, incomplete, or missing records on the date of ART initiation were excluded. The records of all eligible patients were included up to 24 months post-registration or until death, LTFU, or transfer out of NACP care, if within 24 months of registration.i.e., “passports”) and in the national program issued paper registers. The timing and frequency are determined based on the number of tablets dispensed, the number remaining from the previous visit, and the general health status of the patient [HIV testing services in Liberia have been made readily accessible and differentiated; testing is available at program-supported voluntary counselling and testing centers, antenatal clinics, health facilities (provider- and self-initiated testing), including in-patient and out-patient departments and blood donation centers across the country . In 2016 patient . PatientAll health facilities that were registered as HIV service provider sites before 2016 were considered. Purposive sampling was used to select facilities with high PLHIV volume. Urban and rural sites with yearly mean registration rates of ≥150 and ≥50 newly diagnosed individuals, respectively, were selected, comprising twenty-eight facilities from the five sub-regions of Liberia. All but three of the 28 selected facilities are supported by non-governmental (faith-based) organizations. One was supported by both public and private funds. All facilities provide free ART services sponsored by the Global Fund under the auspices of the NACP. Furthermore, all 28 facilities were using a paper-based patient record system at the time of the study.At each of the 28 selected facilities, data were collected from the Pre- ART and ART registers, patient care and treatment charts (files), viral load and CD4 sample collection and reporting forms, and the NACP’s viral load database. Data were entered from the source forms/registers into an electronic KoBoToolbox data extraction form by data clerks between February–June 2020 .Pre-ART and ART registers were used to identify eligible patients at each health facility. Patient care and treatment records and viral load and CD4 sample collection and reporting forms were used to collect baseline and follow-up data from the date of enrolment through 24 months for individual patients. Pre-ART patients in the transition period had data collected for both Pre-ART and ART follow-up periods. Time-at-risk observations were analyzed from the time the patient was registered in care and treatment. For all patients, ‘Time-at-risk’ observations for LTFU ended when one of these outcomes was recorded: LTFU, transfer to another facility, death, or retention at 24 months. Data for analyses were extracted from a Microsoft Access  database generated by KoBoToolbox into Microsoft Excel  format.To reduce misclassification bias of LTFU and other key outcomes, we encouraged strict adherence to protocol (variable definitions) as recorded by care providers in patients’ records. Data enumerators worked closely with providers to ascertain outcomes that were ambiguous or discordant or not recorded accurately in ledgers and charts. Additionally, enumerators were not allowed to diagnose and assign outcomes based on the protocol to prevent the introduction of observer bias.e.g., relative risk of 1.5 to 3, respectively), and assuming an overall 25% event rate, we found that enrolling 1000–4000 individuals gave us about 80% power to detect an association between the covariates and the endpoint. Thus, we targeted a minimum sample size of 4000 patients for inclusion in the sample.The sample was drawn from a total sampling frame or study population of 7136 newly registered HIV-infected individuals in Liberia in 2016 and 2017, according to HMIS data. To account for rare covariates with less strong to very strong signals , fair adherence (missed 5–8 doses per month), and poor adherence (missed >9 doses per month). To quantify “consistent adherence” to treatment, the following variables were generated based on visits and adherence measured in patients’ records (i) good adherence (still on treatment after 12 months of ART initiation) and adherence degree during the last four visits is “good”; (ii) average adherence (still on treatment after 12 months of ART initiation) and adherence degree for at least 2 of last four visits is “good” and (iii) poor adherence (still on treatment after 12 months of ART initiation) and adherence degree during last four visits was either “poor” or “fair”. Suboptimal adherence was defined as those with average or poor adherence. Other variables of interest among those with viral load testing were virological failure, defined as detectable level of viral load with test results >1000 HIV RNA copies/ml and viral suppression, defined as viral load test results <1000 HIV RNA copies/ml or undetectable (<40 HIV RNA copies/ml).Liberia has a viral load testing coverage below 50% of people attending antiretroviral therapy. For the cohort, we assumed virologic suppression among patients evaluated for viremia in the cohort to be the same as in those without access to viral load testing services–that is, those tested were representative of the population of HIV-positive individuals on ART in the cohort. We used as numerator, the total number of patients suppressed (<1000 HIV RNA copies/ml) and the total number of patients tested as the denominator. We multiplied the proportion of patients suppressed by the total number of patients retained in care in the sample .Data were checked for completeness and consistency and exported to Stata 16 IC  and R version 4.0.5  for cleaning, coding, and analyses. Variables with >25% missingness were excluded from univariable and multivariable analyses. The proportion of participants who had reached each step of the HIV care cascade by 24 months were calculated and graphed. Summary statistics were calculated to provide a description of patients’ demographic, clinical, virologic, and immunologic characteristics, as well as attrition rates from treatment. The frequencies and percentages or medians and interquartile ranges of categorical and continuous demographic, clinical, virologic, and immunologic variables, respectively, were determined for the overall cohort as well as for strata of participants based on sex  and facility location . Incidence rates and corresponding 95% confidence intervals for LTFU in the cohort were calculated . Next, CPatient records are manually captured in paper registers and charts. Data were extracted from these sources into an electronic format for storage and analyses. External data checks for consistency in data collection and entry were carried out through random selection of 140 study unique identification records from 15 facilities in 8 counties. Also, a comparison of the study data with the District Health Information System 2 (DHIS2) data was done for concordance. The number of HIV cases registered at each facility was compared with the reported number of newly registered HIV cases obtained through the DHIS2 system. It was found that the number of newly registered HIV-positive patients were over reported by 15%. Over reporting was common among females due to double registration during prevention of mother-to-child transmission (PMTCT) program and in the general clinic visits.Records from a total of 4185 HIV-positive patients registered in care at 28 health facilities were analyzed; of these patients, 1905 and 2280 were registered in 2016 and 2017 respectively. 3 (IQR: 160–550). At care and treatment initiation, more than one-half (55.7%) of the patients registered were categorized under WHO clinical stage I at initial assessment, irrespective of facility location.Among patients enrolling in care, less than a tenth (8.8%) of the cohort had CD4+ cell count assessed at either of the first two visits, with no tests performed in a rural facility. For those who had been tested within the first two visits, the median CD4+ count was 345 cells/mmOf the 2177 (52%) patients who departed from treatment during follow-up, 1751 (80.2%) were categorized as LTFU, with the highest proportion (86.5%) occurring among women who were pregnant at registration. The median times to LTFU from initial assessment and ART initiation were 9.3 (IQR: 4.4–17.3) months and 9 (IQR: 5.2–16.9) months, respectively. Deaths accounted for 12.8% (n = 278) of departure from care, with a higher proportion  occurring among males relative to among non-pregnant or pregnant females. Among the deaths, the median time for those initiating ART was shorter  months compared to patients just initiating care services .The 4185 patients registered for care and treatment generated 5625.3 person-years of follow-up. The incidence rate of LTFU was 46.0 (95% CI: 40.8–51.6) per 100 person years.In the unadjusted analysis, average adherence, WHO stages II, III and IV, and treatment side effects were associated with increased risk of LTFU, relative to people with good adherence, baseline clinical staging at WHO stage I, and no treatment side effects . On the Analysis of suboptimal adherence included, age, sex, facility setting, WHO clinical stage, TB assessment and drugs side effects as covariates . UnadjusWe found that the rate of LTFU among people living with HIV after 2 years on ART was high. Being classified with advanced WHO clinical stage at the initial assessment was associated with increased risks of LTFU and death among the cohort, relative to classification at WHO stage I during enrollment in care. Compared to those without side effects, patients experiencing side effects had an increased likelihood of sub-optimal ART adherence. In contrast, there was a decreased odds of suboptimal adherence among patients attending rural facilities as compared to those attending urban facilities. Our study found no significant differences between males and females (non-pregnant or pregnant) being LTFU and sub-optimal adherence, although both pregnant and non-pregnant women were at decreased risk of death relative to male patients. Overall, the findings highlight patient characteristics that challenge efforts to retain patients in care and treatment.Timely initiation of patients on ART through the ‘test and treat” policy aims to enroll patients early in the course of the natural history of HIV infection, to reduce morbidity, mortality and onward transmission through viral suppression. As a motivation behind adoption of the ‘Treat All’ policy, the NACP recognized that there was low retention of patients in care and treatment and suboptimal adherence to ART, despite limited quantification as the extent of the problem. The overall LTFU among those registered in care in 2016 and 2017 and followed for 24 months was 41.8%. Our results were similar to previous findings from Liberia that demonstrated 46% retention after 2 years of follow-up . A retroMaintaining high retention of recipients of care is critical to the national program’s success in ensuring viral suppression and better quality of life. Our study demonstrated a retention of 48% after 24 months of follow-up. These findings are markedly lower than the 71% retention rate for a similar period of follow-up after ART initiation seen in other low and middle income countries . This fuSeveral contextual factors could help to explain the finding of no change in LTFU rates before and after the ‘Treat All’ policy change in Liberia. Unlike countries such as South Africa which has a higher burden of HIV than Liberia but also has widespread as well as targeted efforts to reduce stigma , 30, LibWe also found higher risk of LTFU among patients who were classified as WHO clinical stage III or IV at their initial assessment, as compared to patients who were classified as WHO clinical stage I. These findings were corroborated by previous studies assessing rates and predictors of LTFU and outcomes of patients receiving ART in Zimbabwe, Malawi, Ethiopia, and South Africa , 31, 32.On the contrary, our study also found that among the cohort, age groups, 35–44 years and 45 years and above had significantly lower risks of LTFU than the age group 15–24 years. These results were consistent with findings in Zimbabwe and Tanzania , 33. OneInconsistent with our findings, evidence from Malawi, Haiti and Nigeria has shown that non-pregnant females  and pregIt is of interest that our overall mortality rate (6.6%) was similar to findings of Bernard et al, who reported a mortality rate of 5.9% across nine West African Countries (excluding Liberia) over 3-year periods between 2006 and 2016 . Our finFurthermore, among the cohort, crude estimates did not show a strong independent association of mortality with patients suspected or confirmed TB. This contrasted with other findings in Africa , 43. TheOptimal adherence to ART is important to achieve and sustain viral suppression. Because in Liberia adherence is mainly self-reported and is graded on a 3-point scale ranging from poor to good, and varies from one clinic appointment to the next, we estimated the risk of sub-optimal adherence for patients on ART for at least a year. A comparative analysis of ART adherence of cohorts in Africa and Asia have shown that low- and lower-middle-income countries had a higher risk of suboptimal adherence, with key determinants being male, younger age, concomitant medication, and attending public facility . Our finConversely, our study demonstrated a significantly decreased risk of suboptimal adherence among patients attending rural facilities, unlike findings in Nigeria and Uganda , 53. TheThere have been several causes of low ART adherence in Africa . One keyThe strengths of our study include the use of patient-level and facility-level datasets across multiple facilities in both rural and urban settings within the 5 subregions of Liberia. Also, our study followed patient records over a 2-year period to describe characteristics of patients newly registered in care and treatment services and provide operational outcomes of the HIV care cascade. Our study also used a large sample size with adequate statistical power to generate estimates of the incidence and factors associated with LTFU, death, and suboptimal adherence to ART.The limitations of our study include the exclusion of records with missing or inaccurately captured registration dates, thus introducing a selection bias. We found considerable missing data additionally from appointment visits. For example, data on CD4 measurements, viral load, opportunistic infections, weight, and height were more than 25% missing and could not be assessed in the analysis. LTFU may have been overestimated by providers due to the lack of resources to track patients, leading to the possibility that patients classified as LTFU may have self-referred or transferred to other facilities to continue ART, or died. There is no gold standard to measure medication adherence. Providers relied on self-reports  and pill count . A more robust qualitative approach, using a multi-method Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Second-generation integrase strand transfer inhibitors (INSTIs) are preferred treatment options worldwide, and dolutegravir (DTG) is the treatment of choice in resource-limited settings. Nevertheless, in some resource-limited settings, these drugs are not always available. An analysis of the experience with the use of INSTIs in unselected adults living with HIV may be of help to make therapeutic decisions when second-generation INSTIs are not available. This study aimed to evaluate the real-life effectiveness and safety of dolutegravir (DTG), elvitegravir/cobicistat (EVG/c), and raltegravir (RAL) in a large Spanish cohort of HIV-1-infected patients.Real-world study of adults living with HIV who initiated integrase INSTIs DTG, EVG/c, and RAL-based regimens in three settings . The primary endpoint was the median time to treatment discontinuation after INSTI-based regimen initiation. Proportion of patients experiencing virological failure (VF)  ≥200 copies/mL at 24 weeks or as a single determination of VL ≥1,000 copies/mL while receiving DTG, EVG/c or RAL, and at least 3 months after INSTI initiation) and time to VF were also evaluated.Virological effectiveness of EVG/c- and RAL-based regimens was similar to that of DTG when given as first-line and salvage therapy. Treatment switching for reasons other than virological failure was more frequent in subjects receiving EVG/c and, in particular, RAL. Naïve patients with CD4+ nadir <100 cells/μL were more likely to develop VF, particularly if they initiated RAL or EVG/c. In the ART switching population, initiation of RAL and EVG/c was associated with both VF and INSTI discontinuation. There were no differences in the time to VF and INSTI discontinuation between DTG, EVG/c and RAL. Immunological parameters improved in the three groups and for the three drugs assessed. Safety and tolerability were consistent with expected safety profiles.Whereas second-generation INSTIs are preferred treatment options worldwide, and DTG is one of the treatment of choices in resource-limited settings, first-generation INSTIs may still provide high virological and immunological effectiveness when DTG is not available. Antiretroviral therapy (ART) coverage for people living with HIV had reached 28 million people as of mid-2021 . ConsistThe effectiveness of therapy in daily clinical practice usually differs from what is observed in clinical trials. Factors like different nucleoside reverse-transcriptase inhibitor (NRTI) backbones, the impact of polymorphic mutations on INSTIs , gender,This study aimed to evaluate the real-life effectiveness and safety of DTG-, EVG/c-, and RAL-based regimens in a large Spanish cohort of HIV-1-infected patients before BIC became commercially available.The INSTINCT study is a multicentre, prospective, observational 96-week study including a cohort of HIV-positive patients who initiated a RAL-, EVG/c-, or DTG- based regimen between 1 April 2015 and 5 October 2016 in 19 Spanish HIV care centres. The study included ART-naïve, ART-switching, and ART-salvage patients initiating an INSTI for the first time.Adults over 18 years old with confirmed HIV-1 infection starting antiretroviral treatment with RAL, EVG/c or DTG for any reason at the time of study initiation, were enrolled. Two-drug regimen initiation was allowed. Exclusion criteria included previous INSTI-based regimen initiation as part of chemoprophylaxis (post- and pre-exposure). BIC was not included in this study because it was not commercially available when it started.Patients who fulfilled inclusion criteria were allocated to one of the following groups: (a) ART-naïve, i.e., previously untreated patients at the time of INSTI initiation; (b) ART-switching, i.e., ART-experienced patients initiating the new INSTI with viral load (VL) ≤500 copies/mL; and (c) ART-salvage, i.e., ART-experienced patients initiating the new INSTI with VL >500 copies/mL due to virological failure (VF) and patients who were on voluntary ART interruption.Data were collected at the date of the INSTI initiation (baseline) and every 24 weeks up to 96 weeks, according to the study protocol. In addition to demographic characteristics, other variables recorded were: HIV-1 RNA levels, CD4+ T-cell counts, CD4+ nadir, haematological and biochemical parameters, previous ART history, ART adherence , reasons for initiating INSTI-based regimens and ART following INSTI discontinuation, and previous genotypic test results . Adverse events (AEs) were classified according to MedDRA (version 25.0) standard terminology.The primary endpoint was the median time to treatment discontinuation after INSTI-based regimen initiation. In addition, the proportion of patients experiencing VF and time to VF for each regimen were also evaluated. VF was defined as two consecutive VL ≥200 copies/mL at 24 weeks, or as a single determination of VL ≥1,000 copies/mL while receiving RAL, EVG/c or DTG, and at least 3 months after INSTI initiation. The first date of confirmed VL ≥200 copies/mL was used to define the time at which VF had occurred. Secondary endpoints were time to the composite endpoint of VF or INSTI discontinuation due to adverse events, factors associated with VF and INSTI-based regimens discontinuation due to any reason, development of INSTI resistance in cases of VF, and changes in CD4+ T-cell counts. A restrictive secondary effectiveness analysis was performed defining VF as two consecutive VL ≥50 copies/mL at 24 weeks. In addition, safety variables, including AEs leading to INSTI discontinuation, AIDS progression, death for any reason, and changes in haematological and biochemical parameters in patients receiving INSTI regimens were evaluated.Continuous variables were summarized as the mean and standard deviation (SD) and the median and interquartile range (IQR), as required, and categorical variables were described as frequencies and percentages. Variables were transformed and/or results stratified according to data distribution. Differences were compared using the chi-squared test for categorical variables and nonparametric tests for continuous variables.Given the real-world nature of this study, no formal sample size calculation was performed. A two-year recruitment period was planned, resulting in an estimated study sample of 1,000 patients (500 patients/year).The Kaplan–Meier survival analysis was used to determine the median time to VF and the proportion of patients who experienced VF within the 96 weeks from INSTI-based regimen initiation. Treatments were compared using the log-rank test. A Cox proportional hazard regression model was used to identify factors associated with each of the three considered outcomes. Multivariable models were fitted using 0.05 as the significance level in univariable analysis for a covariate to be included in the final multivariable model. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated. The relationship between the final set of included covariates was assessed, and those showing collinearity were removed from the model. Effectiveness was evaluated with an intention-to-treat (ITT) analysis ignoring treatment switches of INSTI . Sensitivity analyses were performed counting any INSTI discontinuation [ITT: switching = failure (S=F)] and any loss to follow-up [ITT: missing = failure (M=F)] as failures. All statistical analyses were performed using R software (version 4.0).The study was conducted in accordance with the Helsinki Declaration and the local Personal Data Protection Law (LOPD 15/1999). The study protocol was approved by the local or regional (autonomous community) ethics committee of each participating centre, and all patients gave their written informed consent prior to participation . The transmission route was injection drug use in 212 (21.3%) and men who have sex with men (MSM) in 477 (47.9%). At entry, median age was 46 years (IQR: 37–52), median CD4+ T-cell count was 566 cells/μL (IQR: 357–822), and 202 (20.3%) patients had a history of AIDS diagnosis. Baseline characteristics were generally balanced among the three INSTI treatment groups within each ART regimen strategy Table 1.p=0.17) and between groups on one-to-one comparisons  (p=0.007) . Similar results were observed in the ITT: M=F sensitivity analysis  (p=0.002) and EVG/c vs. RAL (p=0.007), but not for DTG vs. EVG/c (p=0.474).In the ART-naïve group, 150, 80, and 11 patients initiated their first-line regimen with DTG, EVG/c, and RAL, respectively. Based on the primary pre-specified analysis, of 241 ART-naïve patients, 63 (26.1%) reached the composite endpoint of VF or INSTI discontinuation. Of those, 14 (5.8%) patients experienced VF (HIV-1 RNA ≥200 copies/mL) during follow-up and INSTI discontinuation was observed in 49 (77.8%). In comparison with EVG/c and DTG, a limited number of patients initiated RAL as a first-line ART, of whom 18.2% (n=2) experienced VF. Nevertheless, in the genuine ITT analysis, mean time to VF was similar among the three groups  (p<0.001) and EVG/c vs. RAL (p=0.001), but not for DTG vs. EVG/c (p=0.827), whereas time to failure in the ITT: S=F sensitivity analysis differed between all treatments: DTG vs. RAL (p<0.001), DTG vs. EVG/c (p=0.011), and EVG/c vs. RAL (p<0.001). Similar results were observed in the ITT: M=F sensitivity analysis  .In the ART-switching group, 438, 175, and 58 patients initiated DTG-, EVG/c-, and RAL-based regimens, respectively. Out of 671 patients included in this group, 17 (2.5%) experienced VF during follow-up. In addition, INSTIs were discontinued in 117 (17.4%). In the genuine ITT analysis and in the ITT: S=F sensitivity analysis, effectiveness differed among patients who initiated RAL-, EVG/c- or DTG-based regimens  and in the ITT: S=F sensitivity analysis  (p=0.66)  patients with the composite endpoint of VF or INSTI discontinuation, 23 (27.7%) experienced VF during follow-up and INSTIs were discontinued in 12 (34.2%). There were no differences between patients who initiated the three INSTI regimens in the genuine ITT analysis  gene and initiated DTG-based treatment, but had no genotyping data after interrupting treatment voluntarily at week 24. Two other patients with no genotyping data at baseline had mutations at week 24. One patient treated with EVG/c/tenofovir/emtricitabine had mutations in the IN and reverse transcriptase (RT) genes at VF after discontinuing ART. One patient treated with DTG failed to achieve viral suppression at week 24  and had mutations in the protease (PR) and RT genes. The remaining four patients had no genotyping data at baseline or VF, although genotyping was attempted in some of them.In the ART-switching group, one patient had mutations in the RT gene, detected after VF at week 48. In the ART-salvage group, two patients had mutations at baseline, but no data after experiencing VF at week 48: one patient with a mutation in the IN gene had received EVG/c/emtricitabine/tenofovir, and another patient with mutations in the RT gene had received DTG. One patient with mutations in the PR and RT genes received DTG, and after 48 weeks of poor adherence, additional mutations were found in the IN gene. One patient with no mutations at baseline  received ART with EVG/c/emtricitabine/tenofovir, and after voluntarily interrupting treatment at 24 weeks, the genotyping procedure failed.One patient in the ART-salvage group had new acquired mutations in the IN gene (E92Q and E157Q) at VF with DTG-based treatment during 48 weeks. In this case, virological resuppression was achieved at week 96 without changes in ART. In the remaining three patients in this group, there were no genotyping tests available.p<0.0001) (n=768) at week 96 of follow-up. Differences in CD4+ T-cell count at 96 weeks were not significant in the ART-switching and salvage groups, whilst they reached statistical significance in the ART-naïve group. DTG- and EVG/c-based regimens resulted in greater improvements in the ART-naïve group (The median CD4+ T-cell count ( ± SD) in the whole sample increased from 622.2 ± 363.7 cells/μL (n=951) at baseline to 765.8 ± 374.3  after adjustment for confounding variables . In both ITT: S=F and ITT: M=F sensitivity analyses, CD4+ nadir <100 cells/µL and RAL- and EVG/c-based regimens were associated with increased risk of VF.In ART-naïve patients, a multivariable Cox proportional hazard model showed that CD4+ nadir <100 cells/µL was associated with VF  compared to DTG in the ART-switching group . However, in the ITT: S=F analysis, both patients who switched to EVG/c  and those who switched to RAL  had increased HR of VF or INSTI discontinuation. Similarly, these factors were also associated with an increased HR of failure in the M=F sensitivity analysis.Switching to RAL was associated with a higher risk of VF  in the genuine ITT analysis, while we did not find factors associated with failure in the ITT: S=F and ITT: M=F analyses.In the ART-salvage group, the HIV-1 RNA >100,000 copies/mL was the only factor associated with VF . In addition, 18 (18.5%), 68 (15.3%), and 8 (16%) drug-related AEs were observed in the ART-naïve, ART-switching, and ART-salvage groups, respectively (p<0.001).During the study, 590 AEs were reported in 270 (27.1%) patients, of which 97 (16.4%) were observed in the ART-naïve, 443 (75.1%) in the ART-switching, and 50 (8.5%) in the ART-salvage groups. In addition, 496 (84.1%) AEs were considered non-drug related and 94 (15.9%) were considered drug-related. Of the non-drug related AEs, 79 (81.4%), 375 (84.7%), and 42 (84.0%) were observed in the ART-naïve, ART-switching, and ART-salvage groups, respectively (p=0.830), ART-switching (p=0.945), and ART-salvage (p=0.923) groups. Diarrhoea, infections, and psychiatric, musculoskeletal and soft tissue disorders were the most common AEs in the three treatment groups, with no differences between drugs in the three groups (p>0.05). AEs leading to discontinuation were also similar for drugs in each group. AEs are summarized in There were no differences observed between DTG, EVG/c, and RAL treatments in drug-related AEs in the ART-naïve  were reported; 2 (66.7%) for EVG/c in the ART-naïve group, and 20 (51.3%) and 4 (50.0%) for DTG in the ART-switching and ART-salvage groups, respectively. Overall, deaths were observed in 1 (0.4%) patient in the ART-naïve group, 15 (2.2%) in the ART-switching group and 4 (4.8%) in the ART-salvage group Table 3.Laboratory parameters according to treatment in the different study groups throughout the study are summarized in In this multicentre, real-life cohort of HIV-infected patients who initiated INSTIs between April 2015 and October 2016, DTG was always the top performer in all three scenarios . However, the virological effectiveness of EVG/c- and RAL-based regimens was similar to that of DTG when given as first-line and salvage therapy. Treatment switches for reasons other than VF were more frequent in patients receiving EVG/c and, in particular, RAL. This likely reflects evolving treatment policies during the study period, when many patients were switched to DTG due to its increased genetic barrier to resistance and convenience. Patients with CD4+ nadir <100 cells/μL  were morAlthough few head-to-head comparisons between the three drugs are available , our finSafety and tolerability were similar between all three INSTIs in the three scenarios. Reported AEs were consistent with the known safety profiles of the different INSTIs. Diarrhoea, infections, and psychiatric, musculoskeletal, and soft tissue disorders were the most common AEs in all three treatment settings with no differences between drugs . This prFrom the limited sample dataset with INSTI genotypic information, emergent INSTI resistance was only observed in two out of 12 patients, one ART-naïve patient with VF to EVG/c and one ART-salvage patient after 48 weeks of poor adherence to treatment with DTG. While EVG/c resistance selection is expected during VF , our finINSTIs have shown great utility as part of ART regimens in both treatment-naïve and treatment-experienced patients since they were introduced . DTG, wiOur study has some limitations. Due to the observational nature of this study’s cohort, treatment allocation was not controlled. Thus, the results from this study are potentially affected by several biases, including treatment and channelling biases, precluding control for unmeasured confounders. Moreover, the real-world nature of this study with a consecutive recruitment strategy resulted in the uneven distribution of participants across study groups and treatments, which was small for some groups and treatments . Also, BIC was not included in the comparison because it only became widely available towards the end of the study. There were few samples available for genotyping sequencing at failure. A formal neuropsychological evaluation was beyond the scope of this multicentre project; thus, only neuropsychiatric events leading to ART discontinuation were reported. Finally, changes in body weight and composition had not emerged as a concerning complication of INSTI therapy when the cohort was created. Despite these limitations, this study adds to the existing body of real-world evidence of INSTI effectiveness that second-generation INSTIs, such as DTG, are highly efficacious, have a higher genetic barrier to resistance, are well tolerated and convenient, and are generally preferable to treat ART-naïve patients. However, when these drugs are unavailable due to regional or country policies or drug stock-outs in resource-limited settings, first-generation INSTIs achieve high virological effectiveness with a comparable safety profile.In summary, whereas second-generation INSTIs are preferred treatment options worldwide, and DTG is the treatment of choice in resource-limited settings, first-generation INSTIs may still provide high virological and immunological effectiveness when DTG is, unfortunately, not available.IrsiCaixa AIDS Research Institute: MC, MN-J, Mariona Perera. Fight Infections Foundation, Service of Infectious Diseases, Hospital Universitari Germans Trias i Pujol: JRS, RP, Anna Chamorro, Cristina Miranda, Néstor Sánchez, Anna García, Nùria Pérez. University Hospital La Paz: RM-R, Juan González García. Infectious Diseases Unit, Hospital de la Santa Creu i Sant Pau: PD, María del Mar Gutiérrez and María Gracia Mateo. Infectious Diseases Unit, Santiago de Compostela Clinical University Hospital: AA, Elena Losada. Hospital General Universitario Dr. Balmis de Alicante: JP, Sergio Reus, Vicente Boix, Diego Torrús and Esperanza Merino. University Hospital de La Princesa: Jesús Sanz, Ángela Gutiérrez Liarte. Infectious Diseases Unit, La Fe University and Polytechnic Hospital: MM-A. Infectious Diseases Department, Hospital Universitari Vall d’Hebron: JN, Adrià Curran. Infectious Diseases Unit, Elche University General Hospital. MM, Félix Gutiérrez. Infectious Diseases Unit, Complexo Hospitalario Universitario de Ferrol (CHUF): NV-P, Ana Mariño Callejo and Hortensia Álvarez Díaz. HIV Unit, Hospital Álvaro Cunqueiro, Vigo, Spain: Antonio Ocampo Hermida, Celia Miralles, Laura Labajo Leal, Guillermo Pousada. Biomedical Research Center of La Rioja (CIBIR), Logroño, Spain: LP-M, José Ramón Blanco, José Antonio Oteo, Valvanera Ibarra, Mercedes Sanz and Luis Metola. University Hospital Virgen de las Nieves: CG-V, Juan Pasquau. Infectious Diseases Unit, Ramón y Cajal Hospital: MV. HIV and STI Unit, Infectious Diseases Department, Bellvitge University Hospital, Bellvitge Biomedical Research Institute (IDIBELL): AI, Daniel Podzamczer, Camila Piatti. Department of Infectious Diseases, Donostia University Hospital, IIS BioDonostia, Universidad del País Vasco: JI, Maialen Ibarguren, Pilar Carmona-Oyaga. University Hospital San Cecilio: JH-Q. Infectious Diseases Department, Hospital del Mar - IMIM. JV-G. Infectious Diseases Unit, Mataró Hospital: PB, Laia Arbones.The datasets from this study are available upon reasonable request. Requests to access these datasets should be directed to the corresponding author JRS, jrsantos@lluita.org.The study protocol was approved by the local ethics committee of each participating centre, and all patients gave their written informed consent prior to participation. See JRS and RP designed the INSTINCT study and wrote the manuscript, which was reviewed and approved by all concerning authors. MC performed the laboratory and sequencing data analyses. The remaining authors contributed by collecting clinical data, sampling and Sanger sequencing data (when required) and followed the study subjects. All authors contributed to the article and approved the submitted version.We are grateful to the i2e3 team and especially to Marta Ruiz, MD, PhD, and Sara Cervantes, PhD, for their medical writing assistance, Anna Garcıa, Nestor Sánchez, and Nuria Pérez-Alvarez for their support in the statistical analysis, and Helena Pera and Jessica Toro for their assistance in coordinating and recording all data.