New guidelines for the treatment of human immunodeficiency virus (HIV) suggest that morbidity and mortality could be reduced if antiretroviral therapy (ART) was initiated immediately after diagnosis, regardless of CD4 cell count.To assess real-world time to ART initiation and describe medical, pharmacy, and total health care costs in the 6-, 12-, 24-, and 36-month periods after HIV diagnosis based on time to ART initiation among Medicaid-covered patients.Multistate Medicaid data (January 2012-March 2017) was used to identify adults with HIV-1 initiating ART ≤ 360 days of initial HIV-1 diagnosis. People living with HIV (PLWH) were sorted into mutually exclusive cohorts based on time from diagnosis to ART initiation . ART regimen had to include a protease inhibitor, an integrase strand transfer inhibitor, or a non-nucleoside reverse transcriptase inhibitor, with ≥ 2 nucleoside reverse transcriptase inhibitors. Medical, pharmacy, and total health care costs in the 6, 12, 24, and 36 months following HIV diagnosis were stratified by timeliness of ART initiation.Of 974 patients, 347 (35.6%) initiated ART > 360 days after diagnosis and were excluded. Among the remaining 627 eligible patients, mean age was 39.9 years, 42.7% were female, and 53.9% were black. Among them, 128 (20.4%) were treated ≤ 14 days, 228 (36.4%) between > 14 and ≤ 60 days, 163 (26.0%) between > 60 and ≤ 180 days, and 108 (17.2%) between > 180 and ≤ 360 days. Among patients treated ≤ 180 days, 4.6% had ≥ 1 opportunistic infection in the 6-month period before ART initiation; this proportion reached 5.6% for patients treated >180 and ≤ 360 days. Over the 6-, 12-, 24-, and 36-month periods after diagnosis, per-patient-per-month (PPPM) medical costs were lower for patients who initiated ART ≤ 14 days than for those who initiated > 180 and ≤ 360 days after diagnosis . Over the same periods, medical costs generally accounted for > 50% of total health care costs for patients who initiated ART between > 60 and ≤ 180 days and > 180 and ≤ 360 days and for 30%-40% of total health care costs for patients treated ≤ 14 days and between > 14 and ≤ 60 days. Total PPPM health care costs increased with delay of ART initiation in the 36-month period after diagnosis .In this study from 2012 to 2017 of Medicaid PLWH treated with ART, 20.4% initiated ART ≤14 days of HIV diagnosis. Patients with delayed ART initiation accumulated more total health care costs in the 36-month period after HIV diagnosis than those initiated within 14 days, highlighting the long-term benefit of rapid ART initiation. An important opportunity remains to engage PLWH in care more rapidly. What is already known about this subjectWith the success of highly active antiretroviral therapy (ART) in decreasing mortality and morbidity, human immunodeficiency virus (HIV) is now a manageable chronic condition.Guidelines for the treatment of HIV were updated following results from 2 landmark clinical trials suggesting that morbidity and mortality could be further reduced if ART was initiated early after diagnosis.When ART should be started before HIV drug resistance results are available , the U.S. Department of Health and Human Services guidelines recommend using regimens that include pharmacologically boosted darunavir  or dolutegravir .What this study addsIn this observational study of a more vulnerable Medicaid population from 2012 to 2017, rapid initiation of ART was relatively infrequent: 20.4% of ART-treated, Medicaid-covered patients initiated ART within 14 days of HIV-1 diagnosis.Patients with delayed ART initiation accumulated more medical costs than those with rapid initiation in the 6, 12, 24, and 36 months following initial HIV diagnosis.Patients accumulated more total health care costs in the 36 months after diagnosis, highlighting the potential long-term economic benefits of rapid ART initiation.1 making Medicaid the insurance provider for 25% of all individuals living with HIV in the United States. In 2013, people living with HIV (PLWH) covered by Medicaid received annual insurance payments of $23,500 U.S. dollars (USD),1 representing approximately 7 times the average annual insurance payment per Medicaid adult beneficiary.2 Because rapid antiretroviral therapy (ART) initiation has been shown to reduce HIV-associated morbidity and mortality,3 implementation of this strategy could contribute to reducing Medicaid spending on HIV and improve overall patient health.In the United States, the Henry J. Kaiser Family Foundation estimates that 55 million individuals had Medicaid health care coverage in 2013. Among Medicaid enrollees, 284,500 were living with human immunodeficiency virus (HIV),5 However, factors such as poor ART adherence and acquired ART resistance may lead to virologic failure.9 Patients on ART who do not achieve or maintain virologic suppression may develop ART resistance requiring a change to second-line ART and limiting future ART options.10Although HIV cannot be cured, appropriate use of ART can prevent HIV replication and disease progression and make it a manageable chronic condition.12 In 2015, the Strategic Timing of AntiRetroviral Treatment (START) and TEMPRANO trials showed that early ART initiation leads to reductions in morbidity and mortality.13 HIV treatment guidelines were updated to recommend ART initiation following HIV diagnosis for all patients who are willing to start ART, regardless of CD4 count.15 Subsequent studies, 2 of which were conducted in the United States,17 investigated the potential benefits of initiating ART on the same day as HIV testing or shortly after.24 These invariably found rapid ART to be associated with improved clinical outcomes, improved retention in care, or both.23Before 2012, most HIV treatment guidelines suggested that ART should be initiated only when CD4 counts were below a certain threshold, ranging from 200 to 850 cells/μL.14 The U.S. Department of Health and Human Services (DHHS) recommends that pharmacologically boosted darunavir with tenofovir alafenamide (TAF) and emtricitabine or dolutegravir with TAF and emtricitabine be used when ART must be started before HIV drug resistance results are available .14 Despite changes in treatment recommendations, only 50% of HIV-positive patients in the U.S. who are linked to care are on an ART.25Despite this evidence, current practice guidelines in the United States only recommend rapid initiation in certain clinical scenarios, and only specific ART regimens are recommended for this purpose.22 could eventually make rapid initiation the standard of care for PLWH. This could potentially reduce Medicaid spending related to HIV. Therefore, this study sought to assess real-world time to ART initiation among Medicaid-covered patients and to describe medical, pharmacy, and total health care costs during the 6-, 12-, 24-, and 36-month periods after HIV diagnosis based on time to ART initiation.Reducing barriers to rapid initiation, such as time waiting for test results and counseling,International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification [ICD-9-CM/ICD-10-CM]; Current Procedural Terminology codes; physician specialty; and type of provider); prescription drug claims ; and eligibility . Additionally, because Medicaid covers 25% of all individuals with HIV in the United States, describing the relationship between time to ART initiation and Medicaid costs is of particular interest and could help identify ways of reducing total health care costs for HIV patients. All data collected were deidentified in compliance with the patient confidentiality requirements of the Health Insurance Portability and Accountability Act.26 As this was a retrospective analysis of existing claims data and no patient-identifiable information was included in the claims dataset available for the analysis, institutional review board approval was not required.Medicaid databases from 6 states  were available for use in this study. Medicaid databases contain information on medical claims  to evaluate trends over time.A retrospective longitudinal study design was used to analyze PLWH between January 2012 and March 2017 , and have no claim for an antiretroviral (other than pre-exposure prophylaxis) at any time before the first HIV diagnosis. Of note, eligible patients with hepatitis B, a virus that can be treated using antiretrovirals also used to treat HIV, were not excluded. Patients were excluded if their first ART regimen following the first HIV diagnosis was nonstandard .Patients diagnosed with HIV-2  at any time and patients whose first HIV diagnosis was recorded during an inpatient stay that lasted ≥ 10 days were excluded. The latter criterion was added to account for services received in an inpatient setting that may have been unrecorded. As such, patients may have initiated an ART regimen during a long stay, but that information could be missing from the data.Eligible patients were classified into mutually exclusive cohorts based on time of ART initiation after HIV diagnosis . To be included in each post-index period analysis, patients were required to have ≥ 36 months of continuous Medicaid coverage post-index.Time to ART initiation was evaluated with descriptive statistics of the proportions of patients on ART at each time point. Demographic characteristics were assessed at the time of the first HIV diagnosis and included age, gender, race, state, region, type of insurance eligibility , and location where patients received their first HIV diagnosis. Clinical characteristics were assessed during the 6-month pre-ART initiation period and included diagnosis of opportunistic infections, most commonly ordered laboratory tests and procedures, and presence of mental and behavioral disorders affecting ≥ 10% of patients . This period was chosen to assess the relationship between clinical characteristics and timeliness of ART initiation and to have similar observation periods for all cohorts. The type of ART regimen initiated  was assessed at the time of ART initiation.29All-cause accumulated and per-patient-per-month (PPPM) medical, pharmacy, and total health care costs were evaluated during the 6-, 12-, 24- and 36-month periods after HIV diagnosis among patients with ≥ 36 months of continuous insurance eligibility after HIV diagnosis. Total health care costs included amounts paid by Medicaid for pharmacy and medical services; the latter included emergency room visits, inpatient stays, outpatient visits, and other services . All costs were inflated to 2017 USD using the medical care component of the Consumer Price Index.Descriptive statistics were used to report demographics, clinical characteristics, as well as medical, pharmacy, and total health care costs. Means, standard deviations (SDs), medians, and interquartile ranges (IQRs) were reported for continuous variables and frequencies and percentages were reported for categorical variables. For demographic and clinical characteristics, statistical significance between cohorts was assessed using the chi-square test for categorical variables or the t-test for continuous variables. A 5% threshold was used to establish statistical significance.A total of 64,255 patients had ≥ 1 claim with an HIV diagnosis . Of 17,0Among these 627 patients, 24.1%, 34.1%, and 41.8% were initiated on a PI-, INSTI-, or NNRTI-based regimen, respectively . There wAge, gender, race, and insurance eligibility were similar across all cohorts; no statistically significant differences were found between patients treated ≤ 14 days of diagnosis and other cohorts . Mean agDuring the 6-month period before ART initiation, 4.6% and 5.6% of patients treated ≤ 180 days and between > 180 and ≤ 360 days had ≥ 1 diagnosis of opportunistic infection within that time period, respectively . During The proportion of patients with anxiety disorders was generally higher with delay of ART initiation , with statistically significant differences found between those treated ≤ 14 days and those treated between > 60 and < 180 days and > 180 and ≤ 360 days. The proportion of patients with depressive disorders was similar across all cohorts: 12.5%, 16.7%, 17.2%, and 17.6% for patients treated ≤ 14 days, > 14 and ≤ 60 days, > 60 and ≤ 180 days, and > 180 and ≤ 360 days, respectively. The proportion of patients with substance-related and addictive disorders was generally higher with delay of ART initiation , with statistically significant differences found between patients treated ≤ 14 days and between > 60 and ≤ 180 days only.During the 6- and 12-month periods after HIV diagnosis, accumulated medical costs were generally higher with delay of ART initiation. In the 6-month period, medical costs were $9,665, $12,818, $14,422, and $18,048 for patients treated ≤ 14 days, > 14 and ≤ 60 days, > 60 and ≤ 180 days, and > 180 and ≤ 360 days, respectively. In the 12-month period, medical costs ranged from $14,256 for patients treated ≤ 14 days to $25,317 for those treated between > 180 and ≤ 360 days.Increasing the observation period to 24 or 36 months after HIV diagnosis yielded similar results. Medical costs ranged from $18,086 to $32,841 for patients treated ≤ 14 days and between > 180 and ≤ 360 days, respectively, in the 24-month period. During the 36-month period, the same costs ranged from $23,447 to $43,067 for the first and last cohorts, respectively.Lower medical costs for patients who initiated treatment ≤ 14 days and between > 14 and ≤ 60 days were driven by generally lower combined costs for inpatient stays, emergency room visits, and other services .During the first 6-month period after HIV diagnosis, total health care costs were lower with increasing delay of ART initiation . SimilarIn the 12-, 24-, and 36-month periods, medical costs accounted for approximately 35% of total health care costs for patients initiating an ART ≤ 14 days of diagnosis, and for 36% to 83% of total health care costs for those who initiated between > 14 and ≤ 360 days.Patients initiated on an ART ≤ 14 days and between > 14 and ≤ 60 days of their first HIV diagnosis experienced greater reductions in PPPM total health care costs over time than those who initiated later . For patPatients who initiated ART ≤ 14 days and between > 14 and ≤ 60 days of diagnosis experienced reductions in both PPPM medical and PPPM pharmacy costs from 6 to 36 months after HIV diagnosis. Patients who initiated ART between > 60 and ≤ 180 and > 180 and ≤ 360 days experienced increases in pharmacy costs from 6 to 36 months after diagnosis.In the 6- and 12-month periods, total health care costs PPPM were smaller for the 2 cohorts who initiated treatment later, because of delays in ART initiation resulting in reduced pharmacy-related costs. In the 24- and 36-month periods, patients who initiated treatment ≤ 14 days of diagnosis had lower PPPM total health care costs than those who initiated between > 14 and ≤ 360 days. This result was driven by lower PPPM medical costs that offset higher pharmacy costs over longer time periods. Lower medical costs for the ≤ 14 days cohort compared with other groups were driven by lower combined costs for inpatient stays, emergency room visits, and other services.This study showed that, among Medicaid-covered adult PLWH prescribed ART within 1 year of their HIV diagnosis, 20.4% of patients initiated an ART regimen ≤ 14 days. A significant proportion of patients delayed treatment beyond 6 months, and even more patients delayed treatment beyond 1 year and were excluded from this analysis.14 DHHS guidelines recommend initiating boosted darunavir with TAF/emtricitabine or dolutegravir with TAF/emtricitabine. However, most patients included in the present study were initiated on other regimens. More specifically, 48.4% of rapid initiators used NNRTI-based regimens even though this class of agent is more susceptible to drug resistance. However, it cannot be excluded that some patients may have received an NNRTI-based regimen after negative resistance test results were obtained for this drug class. The high proportion of nonconformity to optimal ARTs can be partially explained by the fact that our study period (2012-2017) preceded the publication of new guidance to initiate ART at any given CD4 cell count, though other factors, such as patients’ willingness to pay and the addition/removal of guideline-recommended regimens over time,14 may also play a role. Thus, patients could have received their first ART at a time when the experimental evidence on early ART initiation, such as the results of the START and TEMPRANO trials,14 and therapeutic guidance to rapidly initiate patients were more limited.In cases where ART must be started before HIV drug resistance results are available ,11 A study of PLWH in France and the United Kingdom found that among patients who initiated ART ≤ 6 months after diagnosis, those who initiated ART ≥ 30 days after diagnosis had shorter hospital stays (estimated over a 6-month period).30 Conversely, the current study showed that over the 6-, 12-, 24-, and 36-month periods following diagnosis, medical costs were lower for rapid initiators. Furthermore, total health care costs were lower for rapid initiators (treated ≤ 14 days) in the 24- and 36-month periods. This is explained by initially higher pharmacy costs that were offset by lower medical costs over longer time periods for rapid initiators.To the best of our knowledge, this is the first real-world evaluation of the relationship between rapid initiation and medical, pharmacy, and total health care costs. Studies that have analyzed the relationship between time to ART initiation and health care resource utilization found mixed results. The START clinical trial, which assigned patients with CD4 + levels > 500 cells/μL to either immediate or deferred ART initiation , found that over an average follow-up period of 3 years, unscheduled hospitalizations were similar in both groups.33 Results from our study show that patients with delayed ART had higher levels of anxiety and substance-related and addictive disorders than those who initiated treatment ≤ 14 days. Although DHHS and other treatment guidelines advocate for treatment of all individuals regardless of CD4 + cell count, they also acknowledge the importance of adherence to ART as a lifelong treatment. Our findings represent an opportunity to educate health care providers that mental illness, substance use, and some psychosocial challenges are not reasons to withhold ART. However, it is recommended to delay ART initiation until the patient demonstrates willingness to initiate ART.14 Because treatment nonadherence is more likely in patients with mental health issues and may be associated with drug-resistance mutations,37 clinicians should recognize potential interventions that can improve adherence and prevent drug resistance from occurring. DHHS guidelines recommend avoiding efavirenz- and rilpivirine-based regimens for patients with psychiatric illnesses because they can exacerbate symptoms and lead to increased neuropsychological adverse events.14 Prior studies have found that patients initiated on STRs were 80% more adherent than those initiated on MTRs,38 suggesting that the availability of an STR regimen might help guide the choice of ART regimen when rapid initiation is warranted. Additionally, patients with historically poor adherence or patients who are likely to be less engaged in care may be more at risk to develop resistance and should be treated with a boosted PI, dolutegravir and TAF/emtricitabine, or bictegravir, because these agents have a higher genetic barrier to resistance .14Prior evidence suggests that higher CD4 cell count, drug use, and psychological distress are associated with delayed ART initiation or poor adherence.39 which is not recorded in Medicaid data. Of note, 347 of 974 (35.6%) patients were excluded from the study because they initiated an ART regimen > 360 days after the first HIV diagnosis; therefore, the proportion of patients on rapid ART initiation  has been overestimated.This study has some limitations to consider. As with all claims data sources, Medicaid data may contain inaccuracies or omissions in diagnoses, billing, and other variables, although this is not expected to differ between cohorts. The Medicaid data used in this study came from 6 states and may not be generalizable to the overall Medicaid population, other states, non-Medicaid patients, or noninsured patients. Furthermore, Medicaid PLWH may be different and could receive different types of ART compared with non-Medicaid PLWH. In addition, antiretroviral claims were assumed to indicate their use. However, patients might not have adhered to the ART regimen as prescribed. Although patients were excluded if they had an antiretroviral claim other than pre-exposure prophylaxis before the first HIV diagnosis, some patients may have received an antiretroviral from another source, such as the Ryan White HIV/AIDS Program,14 patients were not required to have received tests to be included in this study. Cost analyses were performed over 6, 12, 24, and 36 months following the first HIV diagnosis using an intent-to-treat approach. In the present study, many patients received ART before the DHHS recommendation to initiate ART immediately in all PLWH regardless of CD4 cell counts. Because of this, the contemporary proportion of patients with rapid initiation may be higher than that reported here. Moreover, cost results should be interpreted as reflecting the payer’s perspective. Amounts paid by other insurers, such as Medicare for patients with dual Medicare/Medicaid eligibility, were not captured using Medicaid data.Although DHHS guidelines recommend performing several laboratory tests before ART initiation ,Finally, given the descriptive nature of the study, no adjustments were made for changes in ART regimen in the study or for differences in characteristics before and after ART initiation within each cohort. Additionally, no adjustments were made for differences in characteristics across cohorts.This study showed that among ART-treated adult patients diagnosed with HIV and insured by Medicaid, approximately two thirds were prescribed ART within 1 year of diagnosis; among them, only 1 in 5 initiated ART rapidly (≤ 14 days). Therefore, a clinical and economic opportunity remains to treat and initiate patients on ART more rapidly. Accumulated medical costs were considerably lower for patients who initiated ART rapidly versus those who delayed ART. This was observed as early as 6 months after diagnosis and continued up to 36 months after diagnosis. The lower total accumulated health care costs  for rapid initiators in the 24- and 36-month periods after HIV diagnosis highlight the long-term benefits of rapid ART initiation. Finally, the decrease in medical costs may suggest an important clinical benefit of rapid initiation.


The Makerere University Infectious Diseases Institute (IDI) reported cases of patients presenting with accelerated hyperglycemia following switching to dolutegravir-anchored anti-retroviral therapy (ART) . We sougThe glucose metabolism changes in Ugandan HIV patients on dolutegravir (GLUMED) study was a prospective cohort study of 303 HIV-positive anti-retroviral therapy (ART) naive patients recruited between January and October 2021 and followed up for 48 weeks. Serial OGTTs were performed at 0.12 and 36 weeks.The study nurse counselor called patients in advance to remind them of adhering to an overnight fast of 8-12 hours which was confirmed on arrival at the clinic. Venous access was established with 16-to-18-gauge venous cannulae. Portions of 75g of glucose were pre-packed into disposable cups on site and diluted in 300ml of water on study days, to be taken by the patient within 5 minutes after fasting blood samples were drawn. Serial 5ml blood samples were drawn at 30, 60, 90 and 120 minutes after the 75g glucose load with immediate measurement of blood glucose using ACCU-CHECK™ glucometers from Roche diagnostics. Blood samples were centrifuged in real time and serum samples stored temporarily in duplicate cryovials at -5 to -20°C in the HIV clinic laboratory freezer. At the end of the clinic day, frozen serum samples were transported in cooler boxes with ice packs to be stored at -80°C at the Makerere University Infectious Diseases Institute about fifteen minutes from the study clinic by a laboratory rider. Stored samples were to be used to run C-peptide and insulin assays at the end of the study.We encountered various challenges in execution of the laboratory processes. There was lack of space to keep patients comfortable during the procedure as well as accommodate the laboratory equipment and personnel. To overcome this, a temporary tent had to be erected to house the study clinician, nurse and laboratory. Additionally, vascular access was hard to establish for some patients. There were occasional blockages of intravenous cannulae with consequent repeated cannulation which was an inconvenience to patients. On a few occasions, patients complained of dizziness and nausea after taking the glucose solution that the test had to be stopped. Despite the challenges, the acceptance rate for the laboratory procedures was high with only one patient dropping out of the study because they had become uncomfortable with the repeated blood draws.Funding: the GLUMED study was funded by: National Institutes of Health (NIH)-Fogarty University of California (UCSF) global health fellowship program, grant number: 2D43TW009343-06; National Institutes of Health, UCSF-Gladstone Center for AIDS Research, grant number: P30AI027763; and the Fogarty International Centre, National Institute of Health (grant# 2D43TW009771-06 “HIV and co-infections in Uganda”).Performance of OGTT insulin kinetic studies is feasible even in busy routine ART clinic settings in limited resource settings so long as there is space, trained staff and facilities to ensure proper blood sample handling and storage.


To curb HIV infection rate in Tanzania, antiretroviral therapy (ART) has been scaled up since 2006, and in 2019, the country shifted to regimen including dolutegravir as a default first line. We assessed the success of ART and the contribution of HIV drug resistance (HIVDR) to unsuppressed viral loads. Between February and May 2023 a cross-sectional survey with random sampling was conducted in the six clinics in an urban cohort in Dar es Salaam. Patients with unsuppresed viral loads  ≥ 1000 copies/mL) were tested for HIVDR mutations using the WHO adapted protocol for plasma samples. Mutations were interpreted using the Stanford HIVDR database. In total 600 individuals participated in this survey, the majority were female (76.83%), mean age ( The 2021 national HIV survey ranked Dar es Salaam region among the top three with the highest HIV prevalence. Mbeya region had the highest prevalence (14%), followed by Iringa region (13%) and Dar es Salaam region (11%)2. To curb the HIV epidemic, UNAIDS put forward the 95–95–95 targets for 2025: 95% of all people living with HIV are diagnosed, 95% of diagnosed are treated, with 95% of them achieving viral load suppression3. Worldwide, 75% of all people living with HIV have currently access to antiretroviral therapy (ART) and more than 1.3 million in Tanzania (76% of diagnosed) are receiving ART4.As of 2021, 38.4 million people were infected with the human immunodeficiency virus (HIV) globally5. Criteria to start and change therapy are currently following the country-wide policy to test and treat with a default first line therapy and move to a default second line therapy when viral load rises above 1000 copies/ml for two consecutive tests, amounting to therapy failure in the Tanzanian context2. The country adopted a triple drug first-line ART regimen, consisting of two nucleoside reverse transcriptase inhibitors (NRTIs) combined with either a non-nucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor. The initial default first-line ART regimen included nevirapine based regimen 6. Later, nevirapine was replaced by efavirenz, and in 2019, the country shifted to using an integrase inhibitor (dolutegravir)7. This shift was for all patients, whether they were starting treatment or whether they were already on a first line regimen. Shifting to integrase inhibitors was influenced by the reported high-level drug resistance to, and poor virologic outcomes associated with the use of NNRTIs8.In 2006, Tanzania scaled-up the use of ART for treatment of HIV-1 infection9. DTG-based regimen, specifically the combination of tenofovir, lamivudine and DTG (TLD) is now the preferred first-line regimen for adults living with HIV in Tanzania7. This regimen has demonstrated high effectiveness in suppressing viral load, is cost-effective, well-tolerated by patients12 and has high genetic barrier to resistance13. TLD is described to be an important milestone for treated patients in suppressing the viral replication12. However, the transition to DTG is now facing challenges of emerging HIV resistance to INSTIs15 and circulating HIV integrase genotypes linked to drug resistance16. Resistance to DTG has emerged in various settings13. Common dolutegravir resistance mutations, such as R263K, G118R, H51Y, and N155H, diminish drug effectiveness by reducing its binding affinity to the integrase enzyme17.Dolutegravir (DTG), an integrase strand transfer inhibitor (INSTI), has proven highly effective in suppressing HIV replication when used in combination ART4. This unsuppressed viral load can be attributed to not correctly taking the therapy , or to HIV drug resistance (HIVDR) which could be pre-existing or newly emerging drug resistance mutations19.The national HIV survey conducted in 2021 revealed that approximately 17%  of those on ART did not achieve VL suppression defined as having two consecutive viral loads ≥ 1000 copies/mL20, in addition to the viral load testing for routine therapy follow up, in order to provide timely data on the emerging and timing of dolutegravir resistance21. This monitoring and surveillance may not only help to inform treatment algorithms for patients whose dolutegravir-based ART may fail, but it can also provide crucial information to inform future HIV treatment guidelines22 and prevent possible emergence of dolutegravir resistance. Furthermore, monitoring of emerging HIVDR could help protect the long-term efficacy of available treatment regimens23.To protect the current and future activity of regimens with INSTI inhibitors, the scale of the problem needs to be assessed. This calls for regular monitoring and surveillance of drug resistance24 indicated three main loops contributing to HIVDR in sub-Saharan Africa. One of these is that overreliance on new drugs with a high genetic barrier to resistance contributes to an increase in HIVDR. To avoid this to come true, a systems approach is needed and quantitative data need to be collected. HIVDR surveillance data and its association with other factors will contribute to assess the problem of HIVDR at a systems level and uncover potential leverage points that could be addressed with intervention25. In this study we used the Dar es Salaam urban cohort of patients from the Ilala district to determine the virologic suppression rate and the prevalence of HIVDR as well as the circulating resistance patterns. We also determined the factors associated with unsuppressed viral loads. With this information, a baseline for intervention studies at the study site will be available.In a conceptual systems map, Kiekens et al.26. DUCS area (Ukonga and Gongolamboto administrative wards) has a total of six HIV care and treatment clinics (CTCs); three of which are public owned facilities, two are military owned while one is privately owned (faith-based). All adults (18 years and above) living with HIV and resident in the DUCS platform area and receiving antiretroviral therapy in CTCs found in the DUCS area were eligible to participate in the study. Patients who had received ART for less than one year were excluded from the study.A cross-sectional survey was conducted between February and May 2023 in the Dar es Salaam Urban Cohort Study (DUCS) platform of the Ilala district in Dar es Salaamn = N(z2) p(1-p)/d2(N-1) + (z2) p(1-p)27 based on the assumption of an estimated prevalence (p) of 0.68%15 for detecting any HIVDR in adult Tanzanian patient taking ART. Using type I error of 5% (z = 1.96) and a margin of error (d) of ± 0.55%, a minimum sample size of 565 patients was required. With an oversampling of 20%, to allow for non-responders, drop outs and failures in testing, 720 from the 1651 eligible patients were selected using a simple random sampling 28. Furthermore, a proportional sampling method was used to obtain a representative sample from all six HIV CTCs found in the DUCS platform area.The sample size (n) was computed using a cross sectional formulae for a finite patient; Phone contacts were extracted from patient files, with up to three call attempts. Patients visiting the clinic were informed about the study, provided informed consent, completed a questionnaire on electronic tablets, and had venous blood drawn. Regardless of consent status, patients received reimbursement for transport costs and a one-kilogram sugar incentive. This process ensured an organized and incentive-driven approach to patient recruitment and study participation.30. It consisted of questions about patient social demographic information such as; age, sex, employment status, place of residence and marital status, questions designed to reflect on factors associated with HIVDR such as HIV status disclosure and health insurance. Patient clinical information such as regimen used, treatment line and duration on ART were collected from the record files of the patients  was kept at − 20 °C with a maximum of 3 times of freeze–thaw cycles.Blood sample collection, transportation and storage were treated according to the Temeke Regional Referral Hospital- Specialized Laboratory protocol32  with a lower limit of detection of 15 copies/mL. Given that we followed the current Tanzania national HIV treatment guidelines2, only samples with viral load count ≥ 1000 copies/mL were subjected to analysis of HIVDR mutations. We used Management and Development for Health (MDH) WHO adapted protocol (Unpublished) to perform HIVDR testing using the 3500xL genetic analyser (Applied Biosystems), a capillary sequencer using Sanger-style sequencing. Analysis of mutations were performed using Stanford University HIVDR database version 9.4. Moreover, calibrated patient resistance tool (CPR version 8.1) was used to determine proportion of mutation suggestive of transmitted HIVDR resistance33. Before importing the generated sequences (fasta format) to Stanford University HIVDR database, the raw sequence (abi format) was assembled, aligned and edited using a RECall (v2.32)- web based sequence analysis then saved as fasta file34. The sequenced codons were 6–99, 1–251, and 1–288, for protease, reverse transcriptase and integrase proteins, respectively. We used Stanford HIVDR33 and COMET35 to assign the HIV sub-types, and Rega HIV sub-typing tool 3.46 database36 was consulted to resolve any disagreements between Stanford and COMET. The VL testing and the genotyping data were linked to the questionnaire information in the DUCS database for analysis.Viral load testing was performed using Roche cobas® 6800/8800 systems7, which was adapted from the WHO37 guidelines, patients were considered to have a suppressed viral load when the count was < 1000 copies/mL, while ≥ 1000 copies/mL was considered unsuppressed viral load. In addition, in some analysis, viral load counts were stratified into three categories: < 50 copies/mL, 50–999 copies/mL, and ≥ 1000 copies/mL. The viral suppression was calculated by dividing the number of patients with viral load count below 1,000 copies/mL over successfully viral load tested patients. In this study we estimated the prevalence of HIVDR as the proportions of patients’ samples which harboured surveillance drug resistance mutations to those patients’ with successfully genotyped sequences.Descriptive statistics of the socio-demographic characteristics were summarized using frequencies (n) and percentages (%). In accordance with the Tanzania national HIV treatment guideline38. We used mean and standard deviations or median and interquartile range (IQR) to estimate the measure of central tendencies for symmetrical and asymmetrical continuous data, respectively. Factors associated with unsuppressed viral loads (1000 copies/mL and above) were determine using binary logistic regression model. Crude and adjusted odds ratios (cOR and aOR) were the effect measures for univariate and multivariate for regression analysis, respectively. All variables in univariate analysis were used in the multivariate analysis. We used the confidence interval of 95% (95%CI), and the p-value We determined the 95% CI for viral suppression and proportion of patients with any major HIVDR mutations using the binomial approximation39. The interpretations of these tests were categorized as 'susceptible', 'possible resistance', and 'resistance', which were assigned scores of 1, 0.5, and 0, respectively40. Possible resistance included potential low-level resistance, low-level resistance, and intermediate resistance. Patient was considered susceptible to the regimen if the GSS was Statistics were done using SPSS software  and Excel spreadsheet 2022 . The Genotypic Susceptibility Score (GSS) for the combination antiretroviral therapy (regimen) was determined by adding the score of each drug used in the regimen, using the Stanford HIVDB scoring systemThe study was approved by Muhimbili University of Health and Allied Sciences (MUHAS)-Ethical Review Board (Ref No. MUHAS/REC/2020/243) and the National Committee on Medical Research Ethics (Ref No. NIMR/HQ/R.8c/Vol.1/1870). Permissions to access the CTCs were requested from the President's Office—Regional Administration and Local Government and CTC managers, Dar es Salaam Regional Medical Officer, Ilala District Medical Officer and CTCs managers. This study complied with the Declaration of Helsinki for medical research involving human subjects.Between February and May 2023, 7083 treated patients were screened from the HIV care and treatment clinics in the DUCS platform for eligibility criteria and 1651 patients were found eligible for inclusion  94.48%  were successfully treated, which comes close to 95%, the goal of UNAIDS for 2025. Those with a viral load count < 50 copies/mL accounted for 83.95% (502/598), those with 50–999 copies/mL made up 10.54% (63/598), while those with ≥ 1000 copies/mL constituted 5.52% (33/598).Both univariate and multivariate analysis found an association between unsuppressed viral loads and time since first HIV-positive test, patients diagnosed since less than 2 years had lower odds of having unsuppressed viral load  as compared to those with at least 10 years since diagnosis. However, patients with self-reported other underlying chronic disease conditions also had lower odds of unsuppressed viral load  as compared to their counterparts (Table The mean age (± standard deviation) of participants was 42.97 (± 13.16) years, while the mean duration on ART was 6.79 (± 3.67) years  despite taking ART, 30 (90.91%) were using a DTG-based regimen, mostly TDF + 3TC + DTG, two patients were using ABC + 3TC + LPV/r, and one was taking ABC + 3TC + ATV/r. Of those patients, one had never used a DTG-based regimen but had a history of using TDF and 3TC drugs. Patient MC-243 was already receiving a second line PI-containing regimen, when switching to DTG, suggesting this patient had failed TDF + 3TC + EFV, and might have already accumulated TDF and 3TC resistance. This makes the DTG-containing regimen TLD particularly vulnerable when used after failure of a first line therapy in Tanzania, where first line failure may not have been diagnosed at the time of the switch. The risk of using functional monotherapy is then too high. One patient, CR-063, had not yet been on a dolutegravir-based regimen. Two patients, CR-119 and MC-400, failed their DTG-containing regimen and were already switched to a protease inhibitor-containing therapy when sampled  samples were successfully genotyped in at least one genomic region, while 66.67% (22/33) were successfully genotyped in all genomic regions tested, protease, reverse transcriptase and integrase  mutations Table . Of whicThe drug susceptibility assessment based on the patterns of mutations per patient is illustrated in Fig. To assess whether the estimated susceptibility was relevant for the concurrent treatment regimen, a GSS to the concurrant regimen was calculated for the 22 for whom the full PRRT and INSTI genotype was available Table . This rementclass2pt{minim3 .This study aimed at determining the prevalence of viral suppression and HIV drug resistance (HIVDR) among a random sample of 600 HIV treatment-experienced adults (18 years and above) living in Ukonga and Gongolamboto, Dar es Salaam, three years after the introduction of dolutegravir (DTG)-based antiretroviral therapy (ART). The survey constitutes a baseline at the study site, in order to inform and evaluate upcoming intervention studies. In this survey the prevalence of viral suppression  < 1000 copies/ml) was 94.48%, this is a substantial milestone on the last Joints United Nations AIDS Programme on HIV/AIDS15. The national survey was conducted 18 months after DTG introduction, while patients in our survey were on average already three years on a DTG-containing regimen. Prior to DTG, viral suppression rate was 87.7% among patients with age between 15 and 64 years, as documented in the Tanzania national survey of 2016–201741, the last survey before introduction of DTG-based regimen in 20197. This shows that the introduction of DTG-based regimen successfully managed to bring treatment success to the majority of treated patients. Previously, Kiekens et al.24 described that on a broader scale, the accessibility of highly potent ART combined with second-generation integrase inhibitors, which possess a robust genetic resistance barrier, presents a novel and encouraging avenue for treatment24. The dependence on new ART options should be addressed, especially considering that there are currently limited new ART medications in development. The focus should be on optimizing the use of existing ART regimens and exploring alternative strategies to manage HIV and prevent HIVDR, rather than anticipating the introduction of new drugs in the near future. As Kiekens et al. posit, overreliance on new drugs is one of the drivers of HIVDR.The high virological suppression rate in the studied area is probably linked to the policy change of replacing non-nucleoside reverse transcriptase (NNRTI)-based regimen by DTG-based regimen (tenofovir + lamivudine + DTG or TLD) in first line. This policy change resulted in 99% of the surveyed patients taking the TLD regimen. The treatment success rate in our survey is consistent with the recent national representative survey carried out in 2021, in which viral suppression among adults was 96.16%2 compared to Western countries45 (which aim for VL < 50 instead of 1000 copies/mL). In addition, Tanzanian guidelines allow HIVDR testing2 only for samples with unsuppressed viral load. This study adhered to Tanzanian guidelines to ensure that the study followed local protocols, as the current survey is intended to be repeated in the context of local interventions consistent with the healthcare practices and infrastructure in the region. The high proportion of SDRM is therefore not surprising. Resistance was most commonly observed against NNRTIs (52.1%) and NRTIs (34.88%) similar as in other studies in Tanzanian43. The analysis of PRRT mutations in 23 sequences revealed SDRMs in 56.5% of the studied patients, while no protease SDRMs were detected. This is consistent with the history of treatment guidelines in Tanzania. In the period 20065–2018, the first treatment line included 2NRTIs plus one NNRTI. PIs were, and still are, mainly used for patients who failed the first line regimen7. Comparatively, the examination of integrase sequences from 30 samples revealed that 10% contained INSTI SDRMs. The detected INSTI mutations, T66I, G118R, E138K, G140A, and Q148K are associated with reduced susceptibility to DTG. E138K and G140A also affect elvitegravir and cabotegravir, in combination with Q148A, G140A reduces the susceptibility to raltegravir and elvitegravir by more than 100-fold while susceptibility to dolutegravir and bictegravir could be reduced by up to fivefold. T66I mainly affects the susceptibility of EVG by tenfold, with a minimal effect to other INSTIs33.While treatment success was high, the proportion of those harbouring any SDRMs among those with unsuppressed viral load (VL ≥ 1000 copies/mL) was also high (41.39%). Treatment success viral load thresholds are much higher in Tanzania15. This indicates a potential increase in the occurrence of INSTI resistance mutations, which could have significant implications for the effectiveness of integrase-targeting antiretroviral therapies. However, it is important to consider the scope and context of both studies when interpreting and comparing these findings. We found that HIV-1 subtype was A: 45.16% (14/31), followed by C 35.0% (11/31) then D 9.58% (3/31). Our results agree with the findings from the neighbouring country Kenya which reported subtype A (70.3%) as the dominant subtypes47. The Tanzanian study revealed subtype C (60.87%), followed by subtype A (41.30) were the commonly prevailing subtypes among adolescents and young adults48. A national representative survey found that C was the predominant circulating HIV-1 subtype in adults, 45.3% followed by A, 35.7%15. Globally, subtype C accounts for 48% of worldwide HIV infections, primarily clustered in eastern and southern Africa, while subtype A (12%) and subtype D (2%) constitute subsequent proportions49.The proportion with INSTI mutations is higher than the previously documented prevalence of 5.8% by Kamori et al50. The most worrying is that in our study, 13.63% of successfully sequenced patients’ samples for PRRT and integrase had triple class resistance; NRTI and NNRTI and INSTI. Given that patients had been switched to DTG because of the policy change and not because of treatment failure, the high levels of NRTI and NNRTI resistance would indicate that these patients may not have been followed up closely enough to timely switch therapy. This may have contributed to the surprisingly high rate of unsuppressed viral load under the DTG-regimen, some with but most without DTG resistance, after only three years of DTG-containing therapy. This was anticipated in our previous research when considering the drivers of HIVDR at systems level24.Our data substantiate the ongoing concern regarding the development of drug resistance mutations in reverse transcriptase, which can compromise the efficacy of antiretroviral therapies given that nucleoside reverse transcriptase inhibitors (NRTIs) are the backbone of any regimen, including24. This multifaceted perspective on treatment failure emphasizes the need for a holistic approach to understanding and managing HIV treatment outcomes25. Those with a low GSS but an active DTG face the risk of developing DTG resistance. This underscores the significance of continuous monitoring and timely treatment adjustments to prevent virologic failure and subsequent resistance escalation13. In addition, knowledge about drug resistance development and treatment adherence25 are also important. The patients with DTG resistance also exhibited resistance to reverse transcriptase (RT) inhibitors. We may speculate here that DTG resistance mainly developed in patients that had already failed their first line regimen with reverse transcriptase inhibitors, a failure that might have gone undiagnosed. These patients might have accumulated DTG resistance because they had in fact been receiving functional monotherapy. In countries that switch all first line patients to TLD, this DTG-containing regimen may be at risk when first line failure went undiagnosed.Unique in our study is that we had treatment information, this helped to assess the relevance of the resistance profile for the therapy that the patients were receiving, we examined their GSS to the concurrent regimen. Surprisingly, 68.18% of patients with unsuppressed viral load exhibited GSS values of ≥ 2.5 for their concurrent regimen, implying that factors other than their drug resistance profiles might be contributing to the unsuppressed viral load. This underscores the complex interplay of multiple factors beyond resistance mutations, including issues related to adherence, healthcare access, and psychosocial aspects16. In high-income countries with well-established healthcare systems and access to a diverse range of antiretroviral drugs, the prevalence of dolutegravir resistance remains relatively low even years after its introduction (below 3%)51. This can be attributed to regular treatment monitoring, early detection of resistance, and the availability of alternative treatment options, which collectively contribute to a more controlled resistance landscape. However, in low and middle-income countries, where healthcare resources and treatment options may be limited, the prevalence of dolutegravir resistance becomes more concerning ranging from 1 to 20%52. Factors such as delayed diagnosis, restricted access to resistance testing, and suboptimal adherence to treatment can facilitate the development and dissemination of resistance mutations in these settings17. This shows how development of HIVDR is context dependent, and battling HIVDR has to be done at a systems level.Despite its effectiveness, the emergence of dolutegravir resistance poses a significant concern in HIV treatment7. This finding aligns with expectations in resource-constrained settings, where recently diagnosed individuals might receive more focused attention and support (unpublished data). Surprisingly, patients self-reporting other underlaying chronic disease conditions also had lower odds (0.18) of unsuppressed viral load as compared to their counterparts. This finding suggests that patients with coexisting chronic diseases might be receiving more comprehensive medical care and support, which inadvertently contributes to better HIV treatment outcomes. This observation underscores again that HIVDR has to be addressed at systems level.In the regression analysis, we found that patients diagnosed since less than 2 years had lower odds (0.13) of having an unsuppressed viral load as compared to those with at least 10 years since diagnosis. This could be attributed to various factors, such as closer monitoring, more accessible healthcare services, and timely interventions during the early stages of diagnosis for patients that were diagnosed under the test and treat strategyWhile interpreting the results of our study, it is crucial to acknowledge certain limitations that might affect the generalizability of the findings. Firstly, our research was limited to the urban patient, potentially excluding valuable insights from rural or suburban areas, where healthcare access and disease patterns may differ. Secondly, we excluded patients who were not living in the study area, while attending clinics in the study area. This points to a subset of patients (60%) who attend clinics away from the area they live in, also for our study area, we are aware of patients attending clinics in other areas, mostly to avoid stigma. The absence of these patients in our survey may affect the results. It is not clear whether this may underestimate (those experiencing or fearing more stigma are absent in our survey) or overestimate (attending clinics away from where you live may reduce the consequences of stigma) treatment success in our survey.Our study focused on patients who were on treatment for at least one year (13% had less than 1 year of ART in our study area), which might overlook potential differences in disease progression and treatment response among those with shorter treatment durations. Additionally, by only considering participants aged 18 years and above, we may have missed important aspects of the condition's impact on younger age groups, for whom treatment approaches and outcomes could vary significantly. Given the low success rate of PRRT genotyping, caution should be exercised when interpreting the genotyping results and drawing conclusions based solely on the genotyped data. Our interpretation, mostly considered the samples successfully genotyped for PPRT and integrase. Another limitation was that our dataset included information on the previous treatment regimen only for patients with unsuppressed viral loads. In addition, as per Tanzanian guidelines, we were not able to assess the presence of HIVDR mutations in patients with a detectable viral load below 1000 copies/mL. As a result, we were unable to ascertain the confounding effect of potential pre-existing HIVDR mutations in patients who transitioned to DTG-containing regimen from a different first line regimen. Whether and how much this could have influenced the observation that patients diagnosed since less than 2 years had lower odds of unsuppressed viral load can therefore not be estimated.This study represents a foundational baseline investigation conducted in a designated intervention site, providing comprehensive insights into viral suppression, HIVDR and assessing GSS as a multifaceted metric to evaluate treatment effectiveness. In our study site, approximately 95% of patients achieved viral suppression under therapy, successfully reaching the last of the 95–95–95 UNAIDS targets. This achievement was attributed to the replacement of NNRTIs with DTG in the first-line treatment, which played a significant role. However, it is essential to note that HIVDR mutations, including INSTIs resistance mutations, were detected in this survey. Given that the overall viral suppression rate is high, the prevalence of dolutegravir resistance remains low but concerning, reaching already 10% of genotyped patient, all with triple class resistance. Without appropriate interventions, HIVDR could potentially threaten the effectiveness of the currently available treatment regimen with INSTIs. Therefore, it is crucial to maintain high patient levels of viral suppression and continually survey for HIVDR to integrase inhibitors. The fact that in most of those with unsupressed viral load, the estimated activity of the treatment was still sufficient to suppress viral replication, shows how important other factors are for treatment success, and that a systems approach is needed.We strongly recommend the design and implementation of high-impact interventions to prevent any further increase in HIVDR in both the study area and Tanzania as a whole. This action is vital to safeguard the potency and effectiveness of this new class of INSTIs. To ensure successful interventions, a transdisciplinary human-centered approach should be adopted, examining the problem at a systems level. A systems approach offers a holistic vision on the complex issue of HIVDR, recognizing the interconnected nature of medical, social, and systemic factors that contribute to treatment effectiveness. This comprehensive strategy will help address the challenges associated with HIVDR and secure the long-term success of treatment efforts.


Treatment with effective antiretroviral therapy (ART) reduces viral load as well as HIV-related morbidity and mortality in HIV-positive patients. Despite the expanded availability of antiretroviral therapy around the world, virological failure remains a serious problem for HIV-positive patients. Thus, Machine learning predictive algorithms have the potential to improve the quality of care and predict the needs of HIV patients by analyzing huge amounts of data, and enhancing prediction capabilities. This study used different machine learning classification algorithms to predict the features that cause virological failure in HIV-positive patients.An institution-based secondary data was used to conduct patients who were on antiretroviral therapy at the University of Gondar Comprehensive and Specialized Hospital from January 2020 to May 2022. Patients’ data were extracted from the electronic database using a structured checklist and imported into Python version three software for data pre-processing and analysis. Then, seven supervised classification machine-learning algorithms for model development were trained. The performances of the predictive models were evaluated using accuracy, sensitivity, specificity, precision, f1-score, and AUC. Association rule mining was used to generate the best rule for the association between independent features and the target feature.Out of 5264 study participants, 1893 (35.06%) males and 3371 (64.04%) females were included. The random forest classifier  outperformed in predicting virological failure among all selected classifiers. Random forest feature importance and association rules identified the top eight predictors  of virological failure based on the importance ranking, and the CD-4 count was recognized as the most important predictor feature.The random forest classifier outperformed in predicting and identifying the relevant predictors of virological failure. The results of this study could be very helpful to health professionals in determining the optimal virological outcome. According to the Global HIV/AIDS Statistics, around 38 million individuals are living with HIV, 28.7 million people were accessing antiretroviral therapy, 1.5 million persons are newly infected with HIV, and 650,000 people died from AIDS-related illnesses around the world in 2021 .Furthermore, Ethiopia is one of the most affected countries in Sub-Saharan Africa by the HIV epidemic, with an estimated 617,921 people living with HIV, 78% of adults and children receiving ART. More than 60% of new infections occur in the Amhara, Oromia, SNNP, and Tigray regions, with the Amhara region having the highest number of HIV patients at around 191,480. The prevalence of HIV among adults in Ethiopia is 0.9% –7. AccorIn Sub-Saharan African countries, HIV viral load testing has been used and scaled up to monitor patients on antiretroviral therapy (ART). However, more than 24% of patients receiving first-line ART experience virologic failure within 1 year of starting therapy , 17. FaiUnderstanding the causes that lead to virological failure in HIV patients on antiretroviral therapy (ART) is essential for HIV/AIDS prevention and control programs Also minimize these adverse outcomes, clinical prediction models that use patient-level evidence can be used in medical decision-making . MeanwhiThis study used a quantitative research method with a machine learning approach and an institution-based cross-sectional study was conducted at the University of Gondar Comprehensive and Specialized Hospital.This study was conducted at the University of Gondar Comprehensive and Specialized Hospital using secondary data from January 2020 to May 2022. The University of Gondar Comprehensive and Specialized Hospital is located in the Amhara National Regional State, Gondar City Administration. It is located 748 km northwest of Ethiopia’s capital, Addis Ababa. The hospital, which is Ethiopia’s oldest academic institution, is a teaching hospital that provides teaching activities to medical and health science students. The hospital provides medical education, training, medical services, and many other services to more than 7 million people in Gondar province and neighboring areas. One of the services provided is the ART service, and through its service, both children and adults can get a free diagnosis, treatment, and monitoring. The hospital started a free ART service in March 2005. At the University of Gondar hospital, the ART clinic reported that 15,933 patients were enrolled for ART. Of those, 5523 patients are actively taking the treatment.All adult (≥ 18 years) HIV-positive patients on antiretroviral therapy (ART) who attend ART clinics at the University of Gondar Comprehensive and Specialized Hospital were the source population, while all adult HIV-positive patients who have been on antiretroviral therapy (ART) for at least 6 months at the University of Gondar Comprehensive and Specialized Hospital were the study population.All adult HIV-positive patients who have been on antiretroviral therapy (ART) for at least 6 months, have had viral load tests, and have records in the ART computerized database at the University of Gondar Comprehensive and Specialized Hospital were included. However, the records that had significant missing feature values  were excluded.Out of all the ART patients who received treatment at the time this study was undertaken, 5264 adult HIV-positive patients from the University of Gondar Comprehensive Specialized Hospital’s ART clinic were included for the model building and prediction of virological failure.In this study, the dependent variable was a virological failure while the independent variables were sociodemographic factors , clinical-related factors , hematologic and immunological factors (CD4 count) and treatment-related factors .Virological failure is defined as a viral load greater than 1000 copies/ml based on two consecutive viral load tests within three months, with better adherence support after the first viral load test [oad test . Using tTreatment adherence is defined as the percentage of a person’s medication-taking behavior that conforms to agreed-upon recommendations from a healthcare practitioner. Good adherence is defined as more than 95%, fair adherence is defined as between 85% and 94%, and poor adherence is defined as less than 85% adherence [dherence .The main source of data for this study was the ART clinic at the University of Gondar Comprehensive and Specialized Hospital, which had existing record data on an electronic database that contained information on HIV-positive patients. It is identified by unique ART numbers and MRN. From all ART patients, a total of 5,264 adult HIV-positive patients’ data were extracted from the electronic database using a structured checklist that was prepared in English. It was adapted from the Ethiopian Federal Ministry of Health ART clinic intake and follow-up form . MultiplData quality assurance is an important step for determining the quality of data. During the initial stage of data collection from the electronic database, the principal investigator provided one day of training to the ART data clerk and observed each step of deidentified record extraction for the feature range value consistency and correctness of the collective data. The principal investigator repeatedly checked the data completeness and randomly cross-checked the patient charts to ensure data similarity and consistency.Patients’ data were extracted from the electronic database in Microsoft Excel format and then converted to comma-separated values (CSV) to make the dataset easier to pre-process in Python version 3. Machine learning needs a high-quality dataset for prediction. Due to this, handling the missing data during the pre-processing of the dataset is a crucial phase. An imputation technique was applied to handle the missing values in the dataset. As a result, this study handled the missing values using simple imputation techniques. The Simple Imputer class of the scikit-learn module was used for imputing the missing values in the dataset . Data prIn this study, descriptive statistics were used to describe the socio-demographic characteristics using frequency and percentage. Some of the data analysis parts were data pre-processing, feature selection, data split, imbalanced data handling, building the model, and testing the performance of the model. In this study, Python version 3 software was used. It is commonly used in data analysis and interactive computing. It has also been a popular choice for data analysis tasks in recent years and It has libraries for data loading, visualization, statistics, natural language processing, and image processing , 53.Feature selection is one of the main processes of data dimensionality reduction in machine learning. It is the method of extracting the necessary beneficial factors from a dataset to improve the accuracy of machine learning predictions . A datasIn this study, different feature selection methods such as recursive feature elimination (RFE), random forest feature importance, and the Boruta feature selection method were used to select the relevant predictive feature. RFE is a feature selection technique that starts with all the features in the training dataset and removes features until the target number of the feature remains. Furthermore, it is a relatively efficient technique for decreasing model complexity and speeding up the processing of machine-learning algorithms .A typical strategy in machine learning is to split the data into training and testing sets. K-fold cross-validation is commonly used for improved model selection in classification prediction (50 ). This study used the stratified tenfold cross-validation method, which partitioned the entire dataset into ten folds. Nine folds were used to train the model and then the remaining one fold was used to test the model. The procedure is repeated ten times with the testing fold , 58. In Many real-world applications, including medical diagnosis, pattern recognition, and fraud detection, rely on imbalanced data learning. The problem occurs when there is a big gap in numbers between the majority and minority classes, which is particularly common in classes having binary values, and frequently occurs in supervised machine learning . The outPredictive accuracy is commonly used to evaluate the performance of machine learning algorithms, but the imbalance of data affects accuracy and machine learning prediction, making it difficult to determine the cause of virological failure. In this study, the Synthetic Minority Oversampling Technique (SMOTE) . AdaptivADASYN is the adaptive generation of minority data samples per their distributions. More synthetic data is generated for minority class samples that are harder to learn compared to those minority samples that are easier to learn and can minimize the bias introduced by the imbalanced data distribution . The figPredictive modeling is defined as “the process of developing a mathematical tool or model that generates an accurate prediction” . ClassifAfter model training, the model’s performances are evaluated and compared to each other. The performance of the prediction models was evaluated based on the confusion matrix. This study used precision, sensitivity, specificity, F1-score, and the area under the receiver-operating characteristic (AUC-ROC) to assess the model performance. AUC-ROC is a popular and powerful performance metric for assessing the performance of binary classifiers and is used to evaluate the model’s predictive classification capacity. A range of 0.5 indicated no ability to predict, while 1.0 indicated exceptional or perfect predictive ability , 70. TheEquations used to calculate Recall (sensitivity), (specificity), precision, and accuracy are given below.In summary, the machine learning pipeline in this study is depicted in Fig. The association rule mining technique, which examines the concurrent correlations between several variables in a grouping, was first created by Agarwaland Srikanth . TherefoTo produce association rules, this study primarily focused on features that are implied by the target features (Antecedent = > Consequent), which is a way to classify all the variables that contribute to virological failure. These rules are often referred to as classification association rules . The reaSupport, Confidence, and Lift can be represented as follows for a certain rule: Here, the sets of features represented by X and Y are mutually exclusive.From the total number of HIV patients who had ever started antiretroviral therapy, this study includes 5,264 patients who were on antiretroviral therapy. 64% (3371) were females, and 39.31%  were between the ages of 38 and 47. More than half of HIV patients 57.26% (3014) were married and 77.79% (4095) lived in Gondar city. Almost half of the patients had secondary educational status, and 91.76% (4830) of all patients were orthodox  of the observations were classified as suppressed and 141 (2.68%) were unsuppressed. This work used under-resampling, SMOTE, and ADNYSN as balanced sampling methods to apply the classification algorithm to a balanced dataset. Each balanced sampling method used a different sampling technique to balance the unequal dataset by either maximizing the minority class or decreasing the majority class. This study compared the balancing technique with the accuracy and AUC using selected supervised classification machine learning algorithms. In the unbalanced dataset, logistic regression performed with a higher AUC of 0.915 as compared to another classifier, and random forest achieved a higher accuracy of 97.42%. In the ADASYN, the XGBoost classifier had a higher accuracy of 96.24% and an AUC of 0.994. Additionally, support vector machines performed better in under-sampling techniques, with training accuracy and AUC values of 84.60% and 0.94, respectively  of 0.999. ADASYN was the second most important balanced resampling method, next to the SMOTE balanced method, with accuracy and an AUC of 95.51% and 0.991, respectively. However, of the balancing imbalanced data handling methods, the under-sampling balanced method was the least important for this study, with an AUC of 0.917 and an accuracy of 83.3% .The ROC curve in Fig. 5The second half of this work was mainly concentrated on building the classification algorithm with a balanced dataset by utilizing different balancing techniques, including under-resampling, SMOTE, and ADASYN. As shown in Table The performance evaluation results with the balanced dataset in Fig. Generally, from the performance metrics shown in Fig. This experiment was developed to evaluate how well different classifiers predicted virological status. The objective of this analysis is to evaluate the accuracy of the predictions provided by the selected classifier. From the balanced dataset, the random forest classifier’s performance was quite strong compared to other selected classifiers. The hyper-parameter tuning and feature selection were carried out after the best model had been chosen. The important predictor of viral failure was established to compare the model’s performance.After selecting the best classifier, this study applied the hyperparameter tuning or optimation to compare it with the default hyperparameter tuning. Figure This experiment was performed to examine the random forest classifier’s ability to predict virological failure and the impact of feature selection. Different Features selection methods were applied to compare the performance of the random forest classifier. Figure Using these findings as a reference, for this study, random forest feature importance was chosen as the most appropriate method to select the features that most accurately predict virological failure. From the selection method, both Boruta feature selection and recursive feature elimination were less outperformed than random forest feature importance. As a result, this study used a random forest classifier as the feature importance selection method. Of all the features, CD4 count, ART regimen, age group, educational level, marital status, TPT discontinued, body mass index, regimen types, TPT started, duration of ART, sex, and CPT were highly significant for virological failure Fig. .Fig. 10R, sensitivity (100%), precision (98.65%), f-1-score (99.32%), and AUC (0.999). As the result, this classifier was selected in our study for the prediction of virological failure. Despite the availability of limited research on virological failure with a random forest classifier, we have attempted to compare some related research on predicting HIV/AIDS status and virological response. The results showed that the random forest classifier had a better prediction performance on virological failure. This result is supported by the previous research study conducted in Switzerland in 2020 . HoweverThis study determined the significant influencing factors for virological failure using the relevance values of independent features for the random forest classifier. Using the random forest feature selection method, the most important predictors that contribute to better performance in virological failure prediction were identified. Among all independent features, sex, age, CPT use, ART regimen used, duration of ART, TPT discontinued, educational status, and CD4 count were the significant predictors of virological failure.Sex was a highly significant factor in predicting virological failure. Accordingly, male HIV patients were more likely to develop virological failure as compared to females. This study is in line with the research studies conducted in Kumasi, Ghana , MoroccoThe machine learning classifier identified that age was a highly important feature for predicting virological failure. Accordingly, younger HIV patients are more likely to develop virological failure than their counterparts. This finding is similar to the studies conducted in Mozambique , in locaDuration on ART was an important feature for predicting virological failure. Patients who had a longer duration of stay on ART had a higher risk of developing virological failure. similarly, previous studies conducted in Waghimra, Northern Ethiopia, and Mettu, South West Ethiopia , 86 reveBased on the finding of this study, the CD4 count of the respondent was found another relevant feature for predicting virological failure. As a result, patients who had low CD4 counts were more likely to develop virological failure. This finding is supported by research conducted in the Waghimra zone, Northern Ethiopia , KombolcOther relevant features of virological failure were co-trimoxazole preventive therapy and Tb preventive therapy. This study showed that patients who had not taken the Cotrimoxazole preventive therapy had a high chance of developing virological failure. The finding of this study is in line with the research conducted in Kenya  and the The ART regimen was highly important for predicting virological failure. This research study showed that patients who were taking the first-line ART regimen of TDF-3TC-EFV were more likely to develop virological failure. Findings from a research study which was conducted in Nepal  and NamiIn conclusion, our study demonstrates the feasibility of using machine learning methods to identify HIV patients at high risk of virologic failure and to determine predictive factors associated with virologic failure. Machine learning algorithms seem to work effectively for risk prediction and classification of ART treatment failure, but further refinements are needed. Nevertheless, our study model may contribute to the important public health issue of reaching and treating HIV-infected patients.Machine learning can be a great help to clinicians who care for HIV patients. The proposed algorithm can predict viral failure in HIV patients with optimal ROC, accuracy, precision, sensitivity, and specificity. This prediction helps to optimize the use of hospital resources to treat high-risk patients, provide better quality care, and reduce medical errors caused by fatigue and long work hours in ART clinics. Designing effective predictive models may improve the quality of care and improve patient survival. Therefore, our study of predictive models of viral failure can make a significant contribution to identifying HIV patients at high risk of viral failure and adopting the most effective supportive and therapeutic regimens. This may reduce ambiguity by providing quantitative, objective, and evidence-based models for risk stratification, prediction, and ultimately care planning. In addition, the findings of this study may provide clinicians with better strategies to reduce complications and improve the chances of survival of HIV patients.One of the strengths of this work is that it incorporates seven supervised machine-learning classification algorithms. Despite its strength, this study is not without limitations. This study was performed in a single-site ART treatment registry database, which may limit the generalizability of the developed model. However, the dataset used in this study is a database collected at Gondar University Hospital, which provides specialized ART treatment services for HIV patients. Data were collected retrospectively, some data were incomplete or missing, and behavioral data such as smoking, alcohol consumption, exercise, and dietary habits were not analyzed in the study. For handling missing data, this study used simple imputation techniques. Moreover, this study used data that was unbalanced, meaning that the majority class and the minority class of dependent features were unequally distributed.This study suggests that the random forest classifier outperformed based on the performance evaluation metrics. Male, younger age, longer time on ART, not taking CPT, not taking TPT, secondary educational level, TDF-3TC-EFV, and low CD4 counts were significant features for predicting virological failure.


We sought to evaluate the impact of antibiotic selection and duration of therapy on treatment failure in older adults with catheter-associated urinary tract infection (CA-UTI).We conducted a population-based cohort study comparing antibiotic treatment options and duration of therapy for non-hospitalized adults aged 66 and older with presumed CA-UTI (defined as an antibiotic prescription and an organism identified in urine culture in a patient with urinary catheterization documented within the prior 90 d). The primary outcome was treatment failure, a composite of repeat urinary antibiotic prescribing, positive blood culture with the same organism, all-cause hospitalization or mortality, within 60 days. We determined the risk of treatment failure accounting for age, sex, comorbidities, and healthcare exposure using log-binomial regression.Of 4,436 CA-UTI patients, 2,709 (61.1%) experienced treatment failure. Compared to a reference of TMP-SMX (61.9% failure), of those treated with fluoroquinolones, 56.3% experienced failure  and 60.9% of patients treated with nitrofurantoin experienced failure . Compared to 5–7 days of therapy (treatment failure: 59.4%), 1–4 days was associated with 69.5% failure , and 8–14 days was associated with a 62.0% failure .Although most treatment options for CA-UTI have a similar risk of treatment failure, fluoroquinolones, and treatment durations ≥ 5 days in duration appear to be associated with modestly improved clinical outcomes. From a duration of therapy perspective, this study provides reassurance that relatively short courses of 5–7 days may be reasonable for CA-UTI. Chronic urinary catheter use is common in long-term care residents with a prevalence of 5%–15%. CA-UTI is particularly burdensome in older long-term care residents given the high risk of bacteremia with a urinary organism and the increased risk of adverse events due to antibiotic therapy. Beyond the negative impact on individual patient outcomes associated with CA-UTI, catheterized patients frequently receive antimicrobial treatment and as such may act as reservoirs of antimicrobial resistance and a source of outbreaks, affecting the broader population.Catheter-associated urinary tract infection (CA-UTI) is the most common healthcare-acquired infection. Indwelling urethral catheters are frequently used for patients in healthcare settings. However, there remain opportunities to optimize antimicrobial use in patients with established CA-UTI. There is a lack of data to support optimal antibiotic selection in patients with CA-UTI. For example, while Infectious Diseases Society of America CA-UTI guidelines do not specifically recommend nitrofurantoin as treatment for CA-UTI, the United Kingdom’s National Institute for Health and Care Excellence guidelines recommend this agent as first-line therapy. Similarly, although guidelines commonly recommend a minimum of 7 days of antibiotic therapy for CA-UTI, there are limited high-quality data to support this recommendation. However, individual studies suggest that durations as short as 3 to 5 days may be reasonable. Additional evidence in support of narrower spectrum therapy and shorter courses of therapy can help advance antimicrobial stewardship efforts for these patients.Reduction in unnecessary catheter use and appropriate urine culturing practices are important antimicrobial stewardship initiatives to prevent CA-UTI and unnecessary treatment for catheter-associated asymptomatic bacteriuria.We sought to evaluate the impact of antibiotic selection and duration of therapy on treatment failure in older non-hospitalized adults with CA-UTI.We conducted a population-based retrospective cohort study comparing antibiotic treatment options and duration of therapy for non-hospitalized patients aged 66 and older with CA-UTI using administrative data.This study took place in Ontario, Canada’s most populous province (15.1 million in 2022). Health care is provided in Ontario via a universal single-payer health insurance model.We obtained study data from linked population-wide administrative datasets housed at ICES . ICES is an independent, non-profit research institute whose legal status under Ontario’s health information privacy law allows it to collect and analyze healthcare and demographic data, without consent, for health system evaluation and improvement. We collected antibiotic use data from the Ontario Drug Benefit (ODB) database, which includes outpatient medication dispensing data for adults over 65 years. Previous validation of ODB has shown 99.3% accuracy compared with chart abstraction of the actual prescription. Demographics and patient outcomes data were collected from the Registered Persons Database, the Ontario Health Insurance Plan (OHIP) Database, and Canadian Institute for Health Information (CIHI) National Ambulatory Care Recording System, CIHI Discharge Abstract Database (DAD), and Continuing Care Reporting System-Long-Term Care (CCRS-LTC). These datasets are linked using unique encoded identifiers and analyzed at ICES and have been widely used for studies of antimicrobial harms and benefits.Urine culture and susceptibility data were collected from the Ontario Laboratories Information System (OLIS), which is a province-wide repository for laboratory results.Adults aged 66 years (aged 65 yr plus 1 yr to ensure an adequate look back) and older residing in the community or long-term-care setting were eligible for inclusion. Those hospitalized within the prior 30 days, with evidence of complicated or upper UTI, including pyelonephritis, renal and perinephric urethral abscess, prostatitis, acute and chronic prostatitis, orchitis/epididymitis (see codes in supplement) or a positive blood culture within 3 days prior to the index date, were excluded. In order to identify patients that were likely catheterized at the time of the index UTI with a high sensitivity, we included anyone with a catheterization code (codes provided in supplement) within 90 days prior to an index antibiotic prescription. Patients with (1) a first positive urine culture collected during the period from 1 January 2016 to 31 December 2020 (2) prescribed an eligible antibiotic either empiric or targeted treatment to which the culture was susceptible or not reported and (3) within +/– 3 days of urine culture finalization were included in the cohort.Eligible antibiotics included amoxicillin, amoxicillin-clavulanate, cephalexin, cefadroxil, nitrofurantoin, trimethoprim-sulfamethoxazole (TMP-SMX), ciprofloxacin, levofloxacin, and fosfomycin prescribed for 1–14 days in duration. The first day of dispensation was considered the index date. Patients were excluded if more than one type of antibiotic was prescribed within 1 day of the index prescription. Since some long-term care patients receive scheduled dispensing , consecutive prescriptions for the same antibiotic for 7 days were combined into a single course if the end date was within 1 days of the start date of the subsequent prescription. Secondary outcomes included components of the primary outcome as well as positive urine culture with the same organism, and cause-specific hospitalization or ED visit for pyelonephritis, sepsis, or bloodstream infection, within 60 days of index prescription. Antibiotic harms were evaluated using a composite outcome comprised of C. difficile, antibiotic allergy, diarrhea, and general medication adverse events.The primary outcome was treatment failure which was a composite of repeat urinary antibiotic prescribing (from antibiotics listed above), all-cause hospitalization, positive blood culture with the same organism, or all-cause mortality, within 60 days of index prescription. Although less specific, all-cause hospitalization and mortality ensure that patient important, objective, and clinically meaningful events are included as part of the primary outcome, and such metrics have been used to evaluate antimicrobial stewardship initiatives.E. coli vs non-E.coli), number of cultures, and number of antibiotics in previous year.Several patient characteristics were collected including age, sex, geographical region, comorbidities, healthcare exposure, time from catheterization to index prescription, time from culture finalization to index prescription, organism category  where appropriate. The relationship between antibiotic selection, antibiotic duration, and treatment failure was evaluated in a log-binomial regression model with antibiotics grouped by class, and antibiotic duration grouped into 1–4, 5–7, 8–14-day courses. We developed an unadjusted (including only selection and duration variables) and adjusted model . We also performed a stratified analysis to evaluate any differences between patients residing in community versus LTC settings. Risk of treatment failure was compared between treatment regimen options and expressed as a risk ratio (RR) with 95% confidence intervals (CI). All analyses were conducted in SAS version 9.4 .We performed two sensitivity analyses to test the robustness of our findings. Firstly, to ensure the treatment failure outcome was not driven by early changes due to culture and susceptibility results, we excluded any patient in which antibiotics were altered within +/– 3 days of culture finalization. A second sensitivity analysis used a threshold of 30 days, rather than 90 days, to look back for catheterization to increase the specificity and likelihood patients were catheterized at the time of the index prescription.E. coli was the causative organism in 33.7%  of patients.During the study period, after exclusions, there were 347,097 eligible older Ontario residents with positive urine cultures receiving antibiotics to treat a presumed urinary tract infection. Of these patients, 4,436 had documented urinary catheterization in the past 90 days and were considered presumed CA-UTI Figure . The medThe median age of CA-UTI patients was 81 (IQR 74 to 88) and 62.6%  were male. The most common Charlson comorbidity score was 0 . Median days spent in acute care in the past 12 months was 1 (IQR 0 to 11) and 38.9% (n = 1727) were long-term care residents. Fluoroquinolones were most commonly prescribed , followed by nitrofurantoin , and TMP-SMX . Patient characteristics varied by antibiotic selection. For example, patients receiving nitrofurantoin were slightly younger  and a greater proportion were female  than those receiving other agents  followed by 8–10 days , then 5–6 days . Male patients received longer courses of antibiotic therapy. For example, those receiving 11–14 days were predominantly male  (Table 1(a) and 1(b)).Of 4,436 CA-UTI patients, 2,709 (61.1%) patients experienced the primary outcome of treatment failure within 60 days of antibiotic dispensing. Repeat urinary antibiotic prescription was the most common component outcome driving treatment failure, occurring in 2,514 (56.7%). All-cause hospitalization occurred in 306 (6.9%) and mortality in 223 (5.0%) patients . Other antibiotics were not associated with a statistically significant difference in risk for treatment failure: amoxicillin-clavulanate RR 1.08 (95% CI: 0.98–1.19); nitrofurantoin RR 1.02 (95% CI: 0.94–1.10); fosfomycin RR 1.04 (95% CI: 0.92–1.18) compared to TMP-SMX. Patients receiving very short courses (1–4 d) were more likely to experience treatment failure  compared to those receiving 5–7 days of therapy. The longest range of duration of therapy of 8–14 days was not associated with a statistically significantly better outcome  than treatment for 5–7 days Table .2).Patients residing in community at the time of the index prescription had a more pronounced reduction in treatment failure with fluoroquinolone use  and a more pronounced increase in treatment failure for ultra-short courses . However, patients in LTC were more likely to experience treatment failure with first-generation cephalosporins  (Supplementary Table A positive urine culture for the same organism within 60 days of antibiotic prescription was more common in patients treated with fosfomycin RR 1.47 (95% CI: 1.13–1.91), amoxicillin-clavulanate RR 1.22 (95% CI 0.99–1.51) and nitrofurantoin RR 1.16 (95% CI: 0.99–1.36). On the other hand, fluoroquinolones were associated with a statistically significantly lower risk for positive culture with the same organism within 60d RR 0.74 (95% CI: 0.62–0.88).Our findings were robust to two sensitivity analyses, showing similar estimates when excluding patients who had more than one antibiotic prescription within 3 days of positive urine culture, and when shortening the threshold for prior catheterization to 30 days.C. difficile , and general medication adverse events  were the most commonly captured adverse outcomes (Supplementary Tables 1(a) and 1(b)). No statistically significant differences were detected between different treatment regimens.Harms of antibiotic treatment regimens were infrequently detected. Overall, 44 (1.0%) were detected to have the composite outcome of antibiotic harm within 60 days of index prescription. Diarrhea , In non-hospitalized older adults with presumed CA-UTI, we identified differences in the effectiveness of antibiotic treatment regimens. Fluoroquinolones were associated with a marginally lower risk of treatment failure. Treatment regimens of ≤ 4 days were associated with worse outcomes compared to > 4 days of treatment. We did not identify significant differences for durations longer than 7 days, compared to 5–7 days, or between non-fluoroquinolone antibiotic classes. perhaps due to their high urinary and tissue concentrations leading to eradication of pathogens both in the urinary tract as well as in vaginal and colonic flora. This concept is supported by our findings that fluoroquinolones were associated with a lower rate of repeat positive urine cultures after treatment. Further, E. coli represented only 1/3 of urinary organisms in our study, which may lend fluoroquinolones an advantage due to their broad spectrum of activity against non-E. coli pathogens such as Proteus spp., Klebsiella spp., and Pseudomonas aeruginosa. On the other hand, the primary outcome is driven by repeat antibiotic use, so reduction in treatment failure with fluoroquinolones may reflect less antibiotic use for asymptomatic bacteriuria, an indication for which antibiotics should not be prescribed in older adults. Regardless of the reason for the lower risk of treatment failure, any benefits of fluoroquinolone use must be weighed against their potential risks. Although our study was not powered to identify differences in adverse events, fluoroquinolones have been associated with rare but severe harms including collagen-associated toxicity, retinal detachment, peripheral neuropathy, and perturbations of gut microbiota including elevated risk of C. difficile infection. Additionally, population-level risks of high fluoroquinolone consumption and resistance to these agents have been established.Our findings echo those of previous studies indicating high rates of clinical cure when using fluoroquinolones for uncomplicated UTI. Some analyses have identified superiority of fluoroquinolones when compared to non-fluoroquinolones for UTI, and nitrofurantoin, we found similar effectiveness for these agents when compared to TMP-SMX. This may be due to differences in population or differences in definitions used, given our outcomes are based on administrative data and do not account for symptom resolution. Notably, fosfomycin and nitrofurantoin appear to be associated with a higher risk of positive urine culture within 60 days of treatment, which may not necessarily equate to repeat infection in the absence of symptoms.Although previous studies have identified a potentially higher risk of treatment failure in patients with cystitis treated with fosfomycin However, courses ≤ 4 days appear to be less effective suggesting ultra-short courses may not be sufficient to eradicate pathogens in CA-UTI. Courses of antibiotic therapy for CA-UTI > 4 days in length may be needed due to a longer time to eradicate bacteria given the formation of biofilm. Alternatively, this could reflect lower efficacy with agents typically used in short courses .Our findings suggest that 5–7 days is an appropriate duration of therapy for CA-UTI. This range of duration appears to be similarly effective to longer courses for CA-UTI aligns with most recent recommendations and supports avoidance of unnecessarily prolonged durations of therapy for this indication.This study benefits from a large sample of province-wide administrative data from almost 100 laboratories, thereby improving generalizability. Antibiotic use is based on dispensed data, as such duration is intention to treat, and limits the likelihood of immortal time bias. Due to dispensing practices in LTC, we allowed for two consecutive 7-day prescriptions with the same antibiotic to be considered a full 14-day course. Although this approach allows us to evaluate LTC patients, it could introduce bias as patients that failed prior to 7 days may not receive their second part of the prescription. However stratified results by setting do not illustrate any differences in outcomes between 5 and 7 days or 8 and 14 days for community compared to LTC. Given the observational nature of the data, there is the possibility for unmeasured confounding across treatment regimens. However, our adjusted estimates after accounting for age, sex, comorbidities, and healthcare exposure did not significantly alter the crude estimates for treatment failure, suggesting minimal confounding. Secondly, treatment failure was driven largely by repeat antibiotic use, and it was not possible to ascertain whether initial treatment or repeat antibiotic use was for symptomatic UTI, asymptomatic bacteriuria, or for an unrelated non-urinary infection as indications for prescribing are not available for all patients. Prescribing for asymptomatic bacteriuria is highly likely given the high percentage (88%) of antibiotics initiated after culture finalization. It was not possible to ascertain if catheter use was indwelling at the time of infection for all patients, but a sensitivity analysis evaluating catheterization closer to the index event showed similar findings. Future research should incorporate an assessment for symptomatology, which is not available in administrative datasets, given the potential harms associated with treating asymptomatic bacteriuria.This research generates hypotheses for future prospective trials of CA-UTI, including an evaluation of which populations can receive agents with lower collateral damage and whether longer courses of therapy mitigate potentially reduced effectiveness. This work highlights the challenges of achieving antimicrobial stewardship in patients with CA-UTI and reinforces the importance of preventing CA-UTI in the first place through appropriate catheter stewardship, diagnostic stewardship to reduce urine culturing in the absence of symptoms, and avoidance of treating asymptomatic bacteriuria.In conclusion, there is an apparent difference in real-world effectiveness between antibiotic treatment regimens for CA-UTI. Although most treatment options for CA-UTI have a similar risk of treatment failure, fluoroquinolones, and treatment durations ≥ 5 days in duration appear to be associated with modestly improved clinical outcomes. However, any difference in effectiveness with fluoroquinolone use should be weighed against potential harms of therapy. From a duration of therapy perspective, this study provides reassurance that relatively short courses of 5–7 days may be reasonable for CA-UTI.