Gut dysbiosis and antimicrobial resistance among women living with HIV, with recurrent urinary tract infections in Uganda: a cross-sectional study

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Considering the increasing rates of Antimicrobial Resistance (AMR), rUTIs are still on the rise and are a big health burden among WLHIV. Understanding bacterial aetiologies, antimicrobial susceptibility patterns, risk factors for recurrent UTIs among WLHIV, and the role of gut microbiota in uropathogenesis is therefore essential in developing appropriate treatment and prevention guidelines to tackle this public health burden. We conducted a cross-sectional study among WLHIV attending care at an HIV clinic in Uganda. Participants were grouped into two categories: Isolated UTI and Recurrent UTI, based on evidence of UTI episodes within the last 12 months. Voided clean catch midstream urine was collected for culture and sensitivity testing to identify bacterial uropathogens and their antimicrobial resistance profiles. Stool samples were also collected for gut microbiome analysis through 16s rRNA sequencing. Urine culture positivity rate was 19.8%, with Escherichia coli accounting for over 80% of isolates. E.coli exhibited high resistance to Ampicillin, Trimethoprim-Sulfamethoxazole, 3rd-generation cephalosporins, and Ciprofloxacin but complete Susceptibility to Nitrofurantoin and Imipenem. Prior antibiotic use within the last six months emerged as the most significant clinical factor associated with UTI occurrence (p < 0.001). Gut microbiome analysis showed reduced diversity and altered microbial composition among women with recurrent UTIs compared to those with isolated UTIs, with specific taxa being differentially abundant in the recurrent group. Biological sciences/Microbiology/Microbial communities/Microbiome Biological sciences/Microbiology/Clinical microbiology Gut microbiome Gut dysbiosis Urinary Tract Infections Human Immunodeficiency Virus recurrent urinary tract infections Antimicrobial resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Globally, UTIs are one of the most common bacterial infections affecting over 400 million people annually (1). Recurrent UTIs (rUTIs), defined as recurrence of 3 or more times in a 1 year or more than two times in 6 months (2), are presumed to be caused by three mechanisms, i.e., an intestinal bloom of uropathogenic bacteria with consequent bladder colonization, reinfection of the urinary tract from an external source, and bacterial persistence within the urinary tract (3). It is well-known that the composition of gut microbiota and gut dysbiosis can influence the health of distant body organs (4). Similar to the gut-brain axis, a close relationship also exists between the gut and the kidney. Organisms that comprise the gut microbiota are known to be common uropathogens, with E.coli responsible for over 80% of the rUTIs (4). While the gut is a known reservoir for uropathogenic bacteria, the role of the microbiota in recurrent urinary tract infections (rUTI) remains unclear. Numerous studies suggest that rUTI susceptibility is in part mediated through the gut–bladder axis, comprising gut dysbiosis and differential immune response to bacterial bladder colonisation, manifesting in symptoms (5). Gut dysbiosis has been found in many patients with rUTIs, characterized by depletion in microbial richness and diversity, with lower levels of Firmicutes and elevated levels of Bacteroidetes (5). HIV itself has also been linked with gut dysbiosis through impairment of the epithelial lining and disruption of intestinal homeostasis. This leads to immune activation and increased inflammation, thereby increasing the translocation of microbes from the intestinal lumen to the systemic circulation. This microbial translocation leads to HIV progression and exposure to opportunistic infections like UTIs, further worsening the problem (6). Moreover, frequent use of antibiotics for prophylaxis and treatment of rUTIs can contribute to the development of multidrug-resistant bacteria within a few weeks (2). E. coli, for example, was identified in about 90% of patients who had previously received prophylactic antibiotics (2). Studies have revealed that most E. coli organisms exhibit more than 50% resistance to most penicillins and cephalosporins (7-9). Drug resistance to Ciprofloxacin at 44.4%, Ceftriaxone at 35.0% as well as Ampicillin, Cotrimoxazole, and Gentamicin was 9.1% in Ugandan PLHIV with UTI (10). PLHIV are most exposed to antibiotics as they are more prone to bacterial infections compared to other populations. Antibiotics are used in opportunistic infection prophylaxis, TB prophylaxis, and treatment, as well as treatment of many other opportunistic infections among PLHIV. This higher risk of inappropriate antibiotic use further increases the risk of antimicrobial drug resistance and gut dysbiosis. Understanding of the common causative pathogens of recurrent and isolated UTIs among WLHIV, their antimicrobial susceptibility profiles and factors associated with recurrent UTIs among WLHIV is essential in refining guidelines for the treatment of recurrent UTIs among WLHIV. The data collected from this study are critical in informing scientists about the potential benefits of non-pharmacologic methods for preventing recurrent UTIs among WLHIV, highlighting differences in microbiomes among WLHIV. This will pave the way for future research into the use of microbiome restoration techniques, such as the use of probiotics, to prevent or control recurrent UTIs. Therefore, understanding bacterial aetiologies, antimicrobial susceptibility patterns, risk factors for recurrent and isolated UTIs among WLHIV and the role of gut microbiota in Uropathogenesis is essential in developing appropriate treatment guidelines to tackle this public health concern. Methods This was a clinic-based cross-sectional study conducted from February to June 2025 among 62 adult women living with HIV receiving HIV care at TASO Mulago HIV clinic.Participants were screened, and enrolled into the study and then provided samples at the TASO Mulago HIV clinic. Urine culture and sensitivity was conducted at the Makerere University, Department of Microbiology teaching laboratory. Stool samples underwent DNA extraction at Makerere University Molecular Biology Laboratory and then sequencing at Inqaba Biotec Laboratory, South Africa. We included adult WLHIV (including pregnant women), who presented with two or more symptoms of Cystitis, of any duration as per the European Medicines Agency (EMA) and US Food and Drug Administration (11) and a Positive Urine dipstick. We excluded WLHIV who had been diagnosed with any form of cancer. WLHIV were screened for UTIs through medical history and clinical examination, as well as on-site urinalysis. Enrolled participants then provided clean-catch midstream urine samples, underwent a questionnaire, and had their medical records reviewed. Participants then provided stool samples. Both urine and stool specimens were transported under cold chain to the laboratories. In the microbiology laboratory, urine samples underwent macroscopy, microscopy, biochemical tests, and culture on Blood Agar and MacConkey agar, with incubation for 18-24 hours. Significant growth was further identified to species level using Gram stain and biochemical methods, and antimicrobial susceptibility testing was performed using the Kirby-Bauer disc diffusion method following CLSI guidelines (12). Quality control measures, including ATCC reference strains, were applied throughout sample collection, transport, processing, and interpretation. Stool DNA was extracted using the FastDNA™ SPIN Kit for Soil, with samples preserved in DNA/RNA Shield to stabilise nucleic acids. Up to 500 mg of stool was homogenized in Lysing Matrix E tubes using a FastPrep instrument, followed by centrifugation, protein precipitation, DNA binding to the Binding Matrix, ethanol washes with SEWS-M solution, and elution with DES, with DNA stored at -20 °C. Quality checks included NanoDrop™ spectrophotometry(OD260/OD280: 1.8-2.0; OD260/OD230: 2.0-2.2) and concentration verification (>5 ng/µL) before cold-chain shipment to Inqaba Biotechnical Industries Laboratory. Samples were then unshielded, purified with AMPure PB magnetic beads, quantified with the Qubit™ dsDNA High Sensitivity Assay Kit, and integrity confirmed by agarose gel electrophoresis. Full-length 16S rRNA (V1-V9) was amplified using 27F/1492R universal primers with barcoded adapters and Takara LA Taq® Hot Start polymerase, purified with AMPure PB beads, and prepared with the SMRTbell® Express Template Prep Kit 2.0, followed by size selection with BluePippin™. Sequencing was performed on the PacBio Revio™ platform, generating HiFi reads via circular consensus sequencing. Post-sequencing, data were processed using SMRT Link™ v11, with demultiplexing, adapter trimming, and chimera removal via USEARCH/VSEARCH, retaining only high-quality full-length reads (Q ≥ 30, ~1,500 bp) for downstream analysis. Bioinformatics analysis of 16S rRNA sequencing data involved quality inspection of raw FASTQ reads using FastQC, followed by denoising, ASV inference, and taxonomy assignment with the DADA2 (v1.20.0) pipeline in R. Outputs (ASV tables, sequences, and taxonomy) were integrated with sample metadata in phyloseq for diversity assessment, differential abundance testing, microbial typing, and network analyses, with statistical comparisons conducted using non-parametric tests (Wilcoxon, Kruskal-Wallis, Spearman) and multiple testing correction via Benjamini-Hochberg FDR. Questionnaire and urine microbiology data were analyzed in Stata 16, with continuous variables summarized as means or medians, and categorical variables as proportions. Comparisons were made using Wilcoxon rank-sum or Fisher’s exact tests. Antimicrobial resistance patterns were reported as proportions, and factors associated with recurrent UTIs were examined using exact logistic regression, yielding crude odds ratios (cOR) with 95% CIs; no multivariable models were built as only one variable met the inclusion threshold. Variables with p < 0.05 were considered statistically significant. Results Characteristics of the study population. The median (IQR) age of the 62 participants was 36 years (IQR 32, 46), with a median (IQR) body mass index of 25.7 kg/m 2 (IQR 23.1, 31.8) ( Table 1 ). Eighty-seven percent of the population had been on ART for more than five years, 87.1% (54), on the Tenofovir/Lamivudine/Dolutegravir (TDF/3TC/DTG) regimen 87.1% (54). The majority of the study population had a CD4 count above 200 cells/microlitre, 93.5% (58) and 80.7% (50) had an undetectable viral load less than 50 copies per millilitre. At the time of study enrolment, 79% (49) of the study population had experienced their first UTI episode in the previous six months, thus isolated a UTI episode, and 21% (13) had experienced other episodes within 12 months prior to enrolment, thus had recurrent UTI episodes. Twenty-four percent 24.2% (15) of the study population had gastrointestinal symptoms at the time of enrolment, with the majority of these reporting bloating 60% (9) and diarrhoea 26.7% (4). Forty percent (25) of the population reported having used an antibiotic in the last six months, with only 22.6% (14) having used Cotrimoxazole. The other sociodemographic and clinical characteristics are in Table 1 . Table 1: Socio-demographic and Clinical characteristics of study population. Characteristic N (%) or Median (IQR) Socio-demographic characteristics Age , years 36 (32, 46) Highest educational attainment None 3 (4.8) Primary 34 (54.8) Secondary 21 (33.9) Vocational 4 (6.5) Marital status Single 19 (30.7) Married 33 (53.2) Separated 10 (16.1) Body Mass Index , kg/m 2 25.7 (23.1, 31.8) Income level Less than 100,000UGX 22 (35.5) Between 100,000 - 500,000UGX 38 (61.3) Above 500,00 UGX 2 (3.2) Diet -Eats a balanced diet 60 (96.8) Currently using family planning method Yes 13 (21.0) Type of family planning method currently being used Combined Oral Contraceptives 2 (15.4) Implant 10 (76.9) Tubal ligation 1 (7.7) Sexually active -Yes 44 (71.0) Sexual partner Casual (only sexual encounter/no relationship) 10 (22.7) Steady (1 to 4 years' relationship) 11 (25.0) Long-term (relationship of 5 or more years) 23 (52.3) Vaginal hygiene practices Washing with clean water only 55 (88.7) Washing with soap and water 11 (17.7) Steaming/ inserting herbs 10 (16.1) Douching 12 (19.4) Clinical Characteristics Duration on ART 5 years 54 (87.1) Current ART regimen ABC/3TC/DTG 2 (3.2) AZT/3TC/DTG 3 (4.8) TDF/3TC/ATV/r 2 (3.2) TDF/3TC/DTG 54 (87.1) TDF/3TC/EFV 1 (1.6) CD4 count > 200 cells/mm3 58 (93.5) Recent viral load Not detected/Detected, below limit of quantification 50 (80.7) History of chronic disease (other than HIV) Yes 13 (21.3) Chronic diseases Hypertension 7 (53.8) Number of UTIs in the past 6 months (including current episode) 1 50 (80.7) 2 10 (16.1) 3 2 (3.2) Recurrent UTIs No 49 (79.0) Yes 13 (21.0) Current symptoms of GI disorder Yes 15 (24.2) GI disorder Abdominal pain 9 (60.0) Bloating 2 (13.3) Diarrhea 4 (26.7) Antibiotic use in the past 6 months -Yes 25 (40.3) Cotrimoxazole use in the past 6 months -Yes 14 (22.6) Indication for cotrimoxazole High viraemia 3 (21.4) Newly initiated on ART and pregnant 1 (7.1) Pregnancy 7 (50.0) Stage III or IV event 3 (21.4) Currently on CTX prophylaxis- Yes 10 (16.1) Escherichia coli was the most isolated pathogen on urine culture Following urine culture and sensitivity, 19.3% (12/62) of cultures had significant bacterial growth and had bacterial pathogens isolated ( Table 2 ). Of the isolates that had significant bacterial growth, 83.3% (10/12) grew Escherichia coli . Antimicrobial susceptibility testing on the Escherichia coli isolates demonstrated 100% susceptibility to Imipenem (10/10) and Nitrofurantoin (10/10). Resistance to Ampicillin was at 80% (8/10), 70% to Nalidixic acid (7/10), and SXT , as well as 60% resistance to Cefixime and Cefotaxime. All E. coli that were resistant to at least one third-generation cephalosporin were screened for Extended Spectrum Beta Lactamase (ESBL) production and only one isolate (10%) was confirmed positive for ESBL production. Table 2: Bacterial pathogens isolated and their resistance profiles Organism Ampicillin Augmentin Cefepime Cefotaxime Ceftazidime Cefuroxime (Oral) Ciprofloxacin Gentamicin Imipenem Nalidixic acid Nitrofurantoin PISA SXT Citrobacter spp (N=1) S 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) I 1 (100.0) 1 (100.0) 1 (100.0) Escherichia coli (N=10) S 1 (10.0) 5 (50.0) 3 (37.5) 4 (40.0) 5 (50.0) 1 (100.0) 5 (50.0) 10 (100.0) 10 (100.0) 3 (30.0) 10 (100.0) 8 (88.9) 3 (30.0) I 1 (10.0) 5 (50.0) 1 (12.5) 2 (20.0) 1 (11.1) R 8 (80.0) 6 (60.0) 6 (60.0) 3 (30.0) 5 (50.0) 7 (70.0) 7 (70.0) Klebsiella pneumoniae (N=1) S 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) I 1 (100.0) 1 (100.0) 1 (100.0) 1 (100.0) R 1 (100.0) 1 (100.0) 1 (100.0) S-Sensitive, I-Intermediate, R-Resistant. Recent antibiotic use was significantly associated with recurrent UTI acquisition. A significant association was observed between recent antibiotic use in the past six months and recurrent UTI ( p =0.001, CI 7.58-+Inf) ( Table 3 ). All participants with recurrent UTI (100%) had used antibiotics, compared to only 12 (24.5%) among those with isolated UTI ( p < 0.001). Cotrimoxazole use was not significantly associated with recurrent UTI ( p = 0.466). Table 3: Factors associated with recurrent UTIs Characteristic Recurrent UTI, n (%) or Mean (SE) cOR (95% CI) p value Age (Mean, SE), years 41.1 (3.9) 1.01 (0.96-1.07) 0.571 Educational level Vocational/Secondary 4 (16.0) 0.60 (0.12-2.51) 0.534 Body Mass Index (Mean, SE), kg/m 2 27.7 (2.1) 1.01 (0.91-1.11) 0.839 Recent viral load done Detected 2 (16.7) 0.71 (0.07-4.15) 0.728 Current GIT symptoms Yes 5 (33.3) 2.40 (0.50-10.70) 0.272 Antibiotics use in the past 6 months Yes 13 (52.0) 50.45 (7.58-+Inf) <0.001 Cotrimoxazole use in the past 6 months Yes 4 (28.6) 1.72 (0.32-7.93) 0.466 Sexually active Yes 8 (18.2) 0.58 (0.14-2.69) 0.495 Vaginal hygiene practices Uses clean water only 37.1 (6.0) 1.02 (0.99-1.06) 0.222 Uses water and soap 2.3 (2.3) 0.97 (0.86-1.03) 0.442 Frequently used vaginal steaming 0.1 (0.2) 0.73 (0.16-1.16) 0.470 Frequently douches 4.6 (3.1) 0.99 (0.93-1.05) 0.912 History of chronic disease other than HIV Yes 2 (15.4) 0.69 (0.06-4.05) 0.725 cOR-Corrected Odds Ratio, GIT-Gastrointestinal tract, UTI-Urinary Tract Infection. Gut microbiome richness and evenness were subtly reduced in the recurrent UTI group. Alpha diversity metrics were assessed across stool samples from individuals with either isolated or recurrent UTIs using Shannon, Simpson, Observed Species, Chao1, and ACE indices ( Figure 1 ). Visual inspection of boxplots showed a trend toward reduced microbial richness and diversity among recurrent UTI patients. Specifically, recurrent UTI samples exhibited lower median values across the richness-based indices; Observed, Chao1, and ACE, indicating a potential contraction in the number of distinct microbial taxa. The Shannon index, which integrates richness and evenness, also trended lower in recurrent UTI samples, suggesting a broader reduction in ecological complexity. In contrast, the Simpson index, which emphasizes community evenness, showed minimal differences between groups, implying that dominant taxa were similarly distributed in both cohorts. A statistical comparison using the Wilcoxon rank-sum test with the Benjamini-Hochberg correction revealed that, although the observed differences were consistent with biological trends, they did not reach statistical significance (adjusted p-value > 0.05). These findings suggest that gut microbiota richness is modestly reduced in recurrent UTI patients, potentially reflecting ecological stress or subclinical dysbiosis that does not uniformly affect all individuals. No distinct clustering by UTI phenotype on Beta diversity analysis. Beta diversity analysis was performed using Bray-Curtis dissimilarity followed by Principal Coordinates Analysis (PCoA) to assess overall community-level dissimilarity. As shown in Figure 2 , samples from both groups exhibited substantial overlap in ordination space, with no distinct clustering by UTI phenotype. PERMANOVA testing ( Table 4 ) confirmed the lack of significant community-level divergence (F = 0.991, p = 0.809, R² = 0.021), indicating that UTI status explained only 2.1% of the total variation in microbial composition. This finding highlights the relatively subtle ecological distinctions between recurrent and isolated UTI microbiota at the genus level, suggesting that global taxonomic restructuring is not a dominant feature distinguishing these phenotypes. Nevertheless, broader inter-individual heterogeneity possibly shaped by host genetics, antibiotic exposure, or behavioural differences may be obscuring finer microbial signatures of UTI recurrence. Table 4: UTI status PERMAMOVA results Df Sum Of Sqs R2 F Pr(>F) Model 1 0.50 0.02 0.99 0.81 Residual 47 23.48 0.98 NA NA Total 48 23.97 1 NA NA DMM revealed one microbial cluster with differential enrichment of genera. Dirichlet Multinomial Mixture (DMM) modeling was applied to identify discrete gut microbiota configurations across the UTI groups. The optimal model, determined via minimum- Laplace approximation, supported multiple clusters representing distinct ecological states or “enterotypes” within the sample set ( Figure 3 ). The model revealed one DMM cluster that was defined by the differential enrichment of a unique set of microbial genera. Taxa contributing most strongly to cluster loadings included Bacteroides, Alistipes, Veillonellaceae, Catenibacterium, Bifidobacterium, and Streptococcus. Interestingly, DMM clusters did not align strictly with UTI phenotype but revealed compositional heterogeneity within both recurrent and isolated UTI groups. The recurrent UTI group showed a reduction in Short-Chain Fatty Acid-producing genera. To examine compositional patterns in more detail, we generated stacked bar plots and alluvial diagrams of phylum- and genus-level relative abundances ( Figure 4 ). Both groups were dominated by core gut phyla Bacteroidota and Bacillota, reflecting a conserved enteric signature. Pseudomonadota and Actinomycetota made minor contributions. At the genus level, both UTI groups harbored a high relative abundance of Bacteroides, Faecalibacterium, Bifidobacterium, and Segatella. However, the recurrent UTI group demonstrated a relative depletion of beneficial genera such as Faecalibacterium and Ruminococcus, both of which are butyrate producers linked to anti-inflammatory activity and gut homeostasis. Concurrently, an increased proportion of “unknown” or unclassified taxa was noted in recurrent samples, suggesting either greater ecological instability or limitations in taxonomic resolution. Collectively, these data indicate that while the phylum-level structure is preserved, recurrent UTI cases may experience a subtle loss of key commensal functions and an increase in taxonomic entropy. The genus Weisella was significantly enriched in the recurrent UTI group. To identify genus-level taxa associated with UTI recurrence status, we applied a differential abundance analysis using the limma-voom framework on TMM-normalized genus-level count data. The volcano plot (Figure 5) presents genera plotted by log2fold change (Recurrent vs. Isolated) and –log10 FDR (significance threshold of log2fold change < –1 and FDR < 0.05). Only a single genus, Weissella , emerged as significantly differentially abundant between groups with a log2fold of -2.5 and -log10FDR of -10, indicating it was depleted in the Isolated UTI group and enriched in Recurrent UTI patients. No other genera reached the significance thresholds of FDR < 0.05 and an absolute log2 fold change (log2FC) of≥ 1. Pathobiont genera were more abundant in the recurrent UTI group. To further dissect taxonomic contributors to UTI recurrence, we identified the 20 most variable genera across the cohort based on coefficient of variation and visualized their abundance patterns using hierarchical clustering heatmaps ( Figure 6 ). Samples largely segregated by UTI phenotype, with recurrent and isolated cases forming distinct blocks. Several genera, including Weissella, Enterococcus, Escherichia-Shigella, and Lactococcus, were more abundant in isolated UTI individuals, potentially reflecting post-infection recovery or probiotic dominance. Conversely, Fusobacterium, Treponema, Oxalobacter, and unclassified Lachnospiraceae were more abundant in recurrent UTI samples, possibly representing low-abundance pathobionts or environmental contaminants associated with dysbiosis. The recurrent UTI concurrence network was more modular and centralized. To examine ecological interactions between taxa, we constructed genus-level co-occurrence networks using Spearman correlation (r ≥ 0.6, p < 0.05), stratified by UTI status ( Figure 7 ). Networks were visualised with nodes representing genera and edge weights representing positive correlations. The Isolated UTI network displayed a loosely connected structure with dispersed nodes and multiple independent modules, suggesting greater ecological redundancy and resilience. In contrast, the Recurrent UTI network was more modular and centralized, with higher node density and fewer but tightly connected modules. Taxa such as Faecalibacterium, Bacteroides, and Ruminococcus remained prominent hubs in both networks. However, the Recurrent UTI network featured a greater number of unidentified or low-confidence nodes. Discussion We enrolled 62 WLHIV into this study to describe the bacterial pathogens causing UTIs, their drug susceptibility profiles, factors associated with UTIs, the gut microbiome of WLHIV with UTIs, and its relationship with recurrent UTIs. The majority of our participants were young, overweight, consumed a balanced diet and utilized clean water only to clean their genitals. They had been on antiretroviral therapy (ART) for over five years, predominantly on Tenofovir/Lamivudine/Dolutegravir regimen. They were immunologically stable and virologically suppressed. This finding is consistent with the World Health Organization (WHO) guidelines that recommend TDF/3TC/DTG as a first-line regimen for adults living with HIV due to its potency, tolerability, and high barrier to resistance (13). The stability of this population, indicated by virologic suppression and CD4 counts above 200 cells/μL, aligns with expectations for individuals on long-term ART, supporting evidence from Uganda and other sub-Saharan African settings that demonstrate improved immunologic and virologic outcomes with TLD (14) (15). About one-quarter of the participants had gastrointestinal (GI) symptoms, mainly abdominal pain and diarrhoea. GI complaints are common in PLHIV, even in the era of effective ART, and may reflect subclinical inflammation, opportunistic infections, or gut microbiota dysbiosis (16, 17). These symptoms may also serve as a proxy for intestinal permeability and microbial translocation, which have been implicated in persistent immune activation despite viral suppression (18). Notably, nearly half of the study population reported antibiotic use within the last six months, with pregnancy cited as the most common indication. While antibiotic use during pregnancy is sometimes necessary (e.g., for urinary tract infections), overuse can significantly alter the gut microbiota, potentially increasing the risk of dysbiosis-associated conditions, such as recurrent urinary tract infections (rUTIs) (19). This aligns with prior findings that recent antibiotic exposure is a significant risk factor for recurrent urinary tract infections (rUTIs ) and multidrug-resistant infections (20, 21). Interestingly, only 16% of participants were on cotrimoxazole prophylaxis, which is in line with national guidelines that recommend discontinuation in virologically suppressed individuals with CD4 >200 and no other significant comorbidities (22). Cotrimoxazole has been found to have beneficial effects on the gut microbiome and immune system through dampening inflammatory cytokine production and therefore withdrawal of cotrimoxazole therapy may have negative gut microbiota effects (23). Compared to similar cohorts in sub-Saharan Africa, this study population demonstrates high ART adherence and treatment success, consistent with the scale-up of Dolutegravir-based regimens and improved HIV program outcomes (24). However, the prevalence of antibiotic exposure and GI symptoms is notable and suggests that clinical stability does not preclude microbiome disturbances. Prior research from South Africa and Kenya has similarly documented persistent GI symptoms and altered microbiota profiles among PLHIV despite ART (24-26). Furthermore, the comorbidity burden reflects findings from large HIV cohort studies, which underscore the double burden of communicable and non-communicable diseases in African HIV clinics (27). Bacterial aetiologic agents of UTI Following urine culture and sensitivity testing, we had a positivity rate of nearly 20%, with over 80% of the isolated organisms being Escherichia coli . This is similar to culture positivity results obtained in recent (2024-2025) studies, such as a systematic review of multiple studies conducted among PLHIV on the African continent, where the UTI culture positivity rate was 23.6%, with Escherichia coli also being the most commonly isolated pathogen across all those studies (28). Another recent study conducted in central Ethiopia, among PLHIV, also obtained a prevalence of 20.9%, with the most prevalent bacterial pathogen being E.coli at 43% (29). Another recent study, also done in Ethiopia, reported a culture positivity rate of 21.7%, with the most predominant bacterial pathogen isolated being Escherichia coli (30). This positivity rate, however, is higher than the culture positivity rates identified in previous (2020-2023) UTI studies among PLHIV in Africa. Netsanet had a culture positivity rate of 10.3% though Escherichia coli was still the most prevalent bacterial pathogen at 69.6% (9). Molla et al obtained a similarly lower prevalence of 12.8% (31). Admasu et. Al reported a positivity rate of 14.1%, with the commonest pathogen isolated being E.coli at 44.8% (32). However, there are older studies (earlier than 2020) that reported a similar prevalence to that obtained in our study, such as Agata et al, who obtained a culture positivity rate of 23.2% (33). In conclusion, the culture positivity rate of nearly 20% observed in our study aligns with more recent studies (2024-2025) conducted among PLHIV across Africa, which consistently report similar prevalence rates and a predominance of Escherichia coli as the main uropathogen. While our findings contrast with lower positivity rates documented in earlier studies (2020-2023), they mirror older data, such as that from (33), suggesting a possible resurgence or evolving trend in UTI prevalence among PLHIV. This consistency in pathogen profile across time underscores the persistent role of E.coli in urinary tract infections in this population and highlights the continued need for routine urine culture and sensitivity testing to guide targeted antimicrobial therapy. Antimicrobial susceptibility profiles of bacterial agents isolated. The E.coli isolates in this study exhibited high susceptibility to Imipenem and Nitrofurantoin , consistent with findings from multiple global and regional studies. Imipenem and other carbapenems continue to demonstrate near-universal efficacy against E. coli , including multidrug-resistant and ESBL-producing strains, reinforcing their critical role in treating urinary tract infections (UTIs) (34, 35). Nitrofurantoin's sustained activity is also well-documented, especially for lower UTIs, due to its minimal impact on gut flora and low propensity for resistance development (36, 37). Moderate susceptibility to third-generation cephalosporins such as Ceftazidime (60%) and Cefotaxime (30%), as well as high resistance to Ampicillin (80%), raises concerns about declining efficacy. Similar patterns of intermediate resistance have been reported in Uganda (38) Kenya (39), and India (40), likely driven by widespread and often unregulated use of beta-lactams in both community and hospital settings. This trend diminishes the reliability of cephalosporins for empirical treatment and necessitates sensitivity-guided therapy. Resistance to Ampicillin (80%), SXT (70%), and Nalidixic acid (70%) aligns with global data showing high resistance rates to these traditionally first-line antibiotics. Studies from Nigeria, Ethiopia, and Brazil have similarly documented resistance rates exceeding 70%, which is largely attributed to the long-standing overuse and availability without prescription (41, 42). Other studies have also reported resistance rates of over 50% to Ciprofloxacin and Nalidixic acid, 93.8% to Ampicillin, and 62.5% to Cotrimoxazole, with some reporting up to 100% resistance to Ampicillin and Ciprofloxacin among participants with UTIs (9, 29, 32). The high resistance to SXT and nalidixic acid is particularly problematic in resource-limited settings where they are frequently used due to affordability. The ESBL prevalence among E. coli isolates in this study was 10%, which is lower than rates reported in many parts of Africa and Asia. For instance, studies in Ethiopia and Kenya have reported ESBL-producing E. coli rates of 25-45% (43, 44), while South Asian countries often report rates exceeding 50% (Rawat & Nair, 2010). The relatively low prevalence in this cohort could reflect local antibiotic use patterns, reduced nosocomial exposure, or the specific demographic (women living with HIV) under study. Nonetheless, even a single ESBL-producing isolate is clinically relevant due to its association with multidrug resistance and treatment failure if unrecognized (45). These findings underscore the importance of regular surveillance and antimicrobial stewardship, especially in high-risk populations such as women living with HIV, who may have altered immune responses and frequent antibiotic exposure. Targeted microbiological testing and individualized therapy can help preserve the efficacy of remaining active agents and prevent the development of further resistance. In this study, ESBL production was detected using the disc approximation method, which, while practical, may have missed some true ESBL producers due to limitations in sensitivity, particularly in cases where low-level enzyme expression or co-existing AmpC β-lactamases masked ESBL activity. The study did not assess for AmpC genes, which may further limit the accuracy of ESBL detection. More robust confirmatory methods, such as the double disc synergy test (DDST) or molecular techniques like PCR targeting bla_CTX-M , bla_SHV , and bla_TEM genes, are recommended for future studies to improve diagnostic accuracy and better characterize resistance mechanisms. Factors associated with recurrent and isolated UTIs among WLHIV. In this study, antibiotic use within the past six months was significantly associated with UTI in both groups, consistent with existing literature that identifies recent antibiotic exposure as a major risk factor for recurrence. Antibiotics, especially broad-spectrum agents, disrupt the gut and urogenital microbiota, leading to dysbiosis and colonization by resistant or uropathogenic strains (46, 47). A systematic review by (48) highlighted prior antibiotic use as one of the most consistently reported risk factors for recurrent UTI in women. Similarly, research in the Netherlands and the United States found that repeated antibiotic exposure increased the risk of both reinfection and resistance (49, 50). Age, BMI, and educational level were not significantly associated with recurrent UTI in this cohort. This finding is similar to studies in sub-Saharan Africa and Southeast Asia, where demographic variables were not consistently predictive of recurrence after accounting for clinical risk factors (37, 39). However, some studies have shown that older women, particularly postmenopausal women, are more prone to rUTIs due to reduced estrogen and changes in the vaginal microbiome (51), though this was not evident in the relatively younger cohort in this study. Gastrointestinal symptoms and viral load detectability were not significantly linked to recurrence, although prior literature suggests that gastrointestinal dysbiosis and immunosuppression may predispose to UTI recurrence in women living with HIV (52, 53). The absence of a significant association here may be due to the small sample size or effective antiretroviral therapy controlling viral replication in most participants. Interestingly, no vaginal hygiene practice, including the use of clean water, soap, douching, or steaming, was significantly associated with recurrence. This contrasts with studies in Nigeria and Kenya, where frequent douching or use of antiseptics in vaginal hygiene was found to disrupt protective flora and increase UTI risk (54, 55). However, the methods, frequency, and types of substances used in hygiene practices vary widely, which may explain discrepancies. Cotrimoxazole prophylaxis, commonly used in people living with HIV, was not significantly associated with recurrence, despite its antimicrobial activity. This finding aligns with results from a South African cohort, where cotrimoxazole prophylaxis did not reduce UTI recurrence, possibly due to resistance or sub-therapeutic dosing (56). Most abundant bacterial taxa & relationship between gut microbiome and UTI. Our alpha diversity analysis showed a consistent trend of reduced species richness (Observed, Chao1, ACE indices) in individuals with recurrent UTIs compared to those with isolated episodes. While statistical significance was not uniformly achieved after multiple testing correction, this directional trend aligns with existing evidence linking reduced microbial diversity to impaired gut resilience and increased risk of infections (57). Richer microbial communities are thought to enhance colonization resistance via nutrient competition, niche exclusion, and modulation of host immunity (58). Therefore, diminished diversity may create an ecological vacuum favoring the persistence or reemergence of uropathogens. Contrary to alpha diversity trends, beta diversity analysis revealed no significant separation of microbial communities based on UTI phenotype, as evidenced by Bray-Curtis dissimilarity and PERMANOVA testing. This finding suggests that overall gut microbial composition remains broadly similar between groups, and that wholesale shifts in community membership may not drive recurrent UTI. This is consistent with prior observations that subtle functional or strain-level differences, rather than broad taxonomic changes, may underlie recurrent infection risk (59). Such findings underscore the importance of functional metagenomic profiling in capturing nuanced microbial signatures that may be overlooked by taxonomy alone. Dirichlet Multinomial Mixture (DMM) modeling revealed distinct gut microbial community types among participants, characterized by variable dominance of genera such as Bacteroides, Veillonellaceae, and Catenibacterium. These genera are well-recognized components of a healthy gut microbiota and are frequently implicated in immune modulation, the production of short-chain fatty acids, and maintaining the integrity of the gut barrier. These genera have been previously implicated in gut–urogenital axis interactions and uropathogen colonization dynamics (60). Notably, the presence of taxa like Streptococcus and Alistipes in distinct community clusters may reflect niche adaptation, with some strains facilitating mucosal immunity. In contrast, others are associated with inflammation or antibiotic resistance, hence suggesting that inter-individual differences in community structure may influence disease risk or resilience beyond binary groupings (61). The identification of discrete enterotypes echoes broader efforts to stratify the human gut microbiome into ecologically and clinically relevant configurations. Although both UTI groups were dominated by common gut phyla (Bacteroidota and Bacillota), subtle but noteworthy compositional trends emerged. Patients with recurrent UTIs exhibited lower relative abundances of anti-inflammatory genera such as Faecalibacterium and Ruminococcus, which are key producers of short-chain fatty acids (SCFAs) involved in maintaining gut barrier function and immune regulation (62). Simultaneously, a rise in poorly annotated or “unknown” genera in recurrent cases may reflect increased taxonomic entropy, a hallmark of microbial dysbiosis (63). These trends collectively point toward ecological destabilization in the gut of recurrent UTI patients. Among the differentially abundant taxa, Weissella was significantly enriched in the recurrent UTI group. This finding was unexpected given that Weissella spp., a group of facultative anaerobic lactic acid bacteria, are often considered protective commensals with roles in bacteriocin production, mucosal colonization, and modulation of host immunity (64). Some Weissella species have been associated with opportunistic infections, particularly in immunocompromised individuals (65). Their increased abundance in recurrent UTI cases may therefore reflect ecological selection pressures such as prior antibiotic use or indicate a potential role as a low-grade pathobiont or bystander taxa in dysbiotic gut environments. This finding, while singular, underscores the importance of deeper strain-level or functional analyses to determine whether Weissella ’s enrichment represents an adaptive shift or contributes causally to UTI recurrence. The absence of additional significant taxa supports the notion that compositional differences between groups are subtle and possibly masked by inter-individual heterogeneity. Heatmap analysis of the top 20 most variable genera reinforced earlier observations. Certain genera, such as Enterococcus, Escherichia-Shigella, and Lactococcus, were more abundant in subsets of isolated UTI patients, possibly reflecting acute inflammation or recent antimicrobial exposure. Conversely, genera such as Treponema and Fusobacterium were more prevalent in recurrent UTI cases, possibly representing low-abundance pathobionts or environmental contaminants associated with dysbiosis. These results underscore the potential utility of genus-level microbial signatures as discriminators of UTI recurrence risk, warranting functional validation and longitudinal follow-up. The co-occurrence network analysis uncovered stark structural differences between the microbiota of recurrent versus isolated UTI patients. The recurrent UTI network was denser and more modular, with genera forming tighter hubs. In contrast, the isolated UTI network exhibited a more distributed topology, suggestive of greater microbial heterogeneity and redundancy. These findings point to altered microbial assembly and reduced network robustness in recurrent UTI patients, potentially diminishing microbial community resilience against perturbations like antibiotic exposure or pathogen invasion (66). The loss of peripheral taxa and the dominance of tightly clustered hubs in the recurrent UTI group may thus signal a dysbiotic core with diminished adaptability. Limitations. The study faced several limitations, including a small sample size that may have reduced statistical power and generalizability. However, standardised procedures and uniform data collection preserved internal consistency across participants. Stool samples were collected at a single time point, which may not have captured temporal shifts in microbiome composition, but all were obtained under the same conditions, reducing within-group variability and ensuring comparability. The use of machine learning models carries the risk of overfitting due to the high dimensionality of microbiome data and limited sample size. To address this, cross-validation and careful feature selection were employed to support valid pattern recognition and maintain analytical integrity. As an observational study, causal inferences between gut microbiota and recurrent UTIs could not be established. Nonetheless, the internal validity of observed associations was strengthened through confounder control and a clearly defined analytic approach. The possibility that some participants had received antibiotics before urine sampling posed a risk of altering urinary bacterial pathogen profiles, but this was mitigated by documenting antibiotic use and sample timing. Additionally, while HIV-related immune alterations could have influenced microbiome composition in unmeasured ways, limiting generalizability, the inclusion of only women living with HIV and diagnosed with UTI minimised inter-group variability, reinforcing internal validity within the study population. Conclusions and Recommendations. In this study, Escherichia coli was the most commonly isolated uropathogen among women living with HIV (WLHIV), followed by Citrobacter spp. and Klebsiella pneumoniae . The antimicrobial susceptibility profile of E. coli isolates in this study highlights high resistance to multiple readily available agents such as Ampicillin, SXT, and Nalidixic acid, while Gentamicin, imipenem, and nitrofurantoin retained full activity and remain reliable choices for treating UTIs in this population. The low prevalence of ESBL-producing E. coli (10%) is encouraging; however, it does not preclude the need for vigilance, especially given the potential for the rapid dissemination of ESBL genes. Recent antibiotic use was the only factor significantly associated with UTI among women living with HIV, underscoring the importance of cautious antibiotic prescription. Whereas we noted subtle shifts in the gut microbiome of individuals with recurrent UTIs, they were consistent, particularly with respect to microbial richness, genus-level composition, and network structure. While global taxonomic composition remains broadly stable, the enrichment of Weissella , loss of Butyrate/Short Chain Fatty Acid producers, and emergence of denser microbial hubs may reflect ecological disruptions (gut dysbiosis) that predispose individuals to infection recurrence. These results pave the way for future mechanistic studies incorporating longitudinal designs, functional metagenomics, and host immunophenotyping to clarify causal pathways and develop microbiome-based diagnostics or interventions. For WLHIV presenting with UTI symptoms, routine urine culture and drug susceptibility testing should be conducted rather than relying solely on empirical treatment, to ensure targeted and effective therapy. Antibiotics such as Ampicillin, Cephalosporins, Trimethoprim-Sulfamethoxazole, and Nalidixic acid should be avoided as first-line agents due to high resistance rates; instead, clinicians should adhere to the Uganda Clinical Guidelines, which recommend Nitrofurantoin as the preferred first-line treatment for uncomplicated UTI, making it a safe empirical option while awaiting culture results. Furthermore, larger longitudinal studies are needed to investigate the causal links between gut microbiome alterations, host immunity, and UTI recurrence among WLHIV. Declarations This study was conducted according to the GCP and GCLP guidelines. Ethical approval was obtained from the Makerere University School of Biomedical Sciences Research and Ethics Committee, proposal number SBS-2024-637, and administrative clearance was obtained from The AIDS Support Organization (TASO REC/ADMC04/2025-UG-REC-009). Female PLHIV aged 18+ years were recruited voluntarily after providing written informed consent to participate in the study. The study presented no more than moderate risks to the participants. Privacy and Confidentiality were ensured by using unique study numbers, and research forms were kept under lock and key, with only the principal investigator having access to them, to date. Consent for publication N/A Availability of data and materials- The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Microbiome data analysis code is available via this link. Competing interests The authors declare that they have no competing interests Authors contributions Conceptualisation: F.M.M, E.K, and M.L. Analysis: G.O, I.S. Data curation: F.M.M, E.K, I.S, G.O and M.L. Investigation: F.M.M, L.K, I.T, A.K, M.Y, A.L, A.R.N, M.L and E.K. Writing-original draft: F.M.M. Writing-review and editing: E.K, M.L, P.K, S.K, H.K and G.O. Visualisation: F.M.M, E.K, I.S and G.O. Supervision: E.K, M.L and M.L.J Acknowledgements and funding. We would like to thank the TASO Uganda management team, the staff and clients of TASO Uganda CoE for all the support rendered to us during this study. This original research article was funded by grants supported by the US National Institutes of Health through the Fogarty International Centre, NIH Award number D43TW010319 . The content is solely the authors' responsibility and does not necessarily represent the official views of the National Institutes of Health. References Yang X, Chen H, Zheng Y, Qu S, Wang H, Yi F. Disease burden and long-term trends of urinary tract infections: A worldwide report. Frontiers in public health. 2022;10:888205. Kim A, Ahn J, Choi WS, Park HK, Kim S, Paick SH, et al. What is the cause of recurrent urinary tract infection? Contemporary microscopic concepts of pathophysiology. International neurourology journal. 2021;25(3):192. 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Identification and significance of Weissella species infections. Frontiers in Microbiology. 2015;6:1204. Silago V, Keenan K, Mushi MF, Kansiime C, Asiimwe B, Sunday B, et al. Patterns of antibiotic resistance in urinary tract infections before and during the COVID-19 pandemic in Uganda and Tanzania. JAC-Antimicrobial Resistance. 2025;7(2):dlaf038. Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryinformationGutmicorbiome.docx Additional tables of results from questionaire data and urine microbiology data analysis as well as additional microbiome results images. Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7593174","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":513741283,"identity":"b21538c7-b201-400e-8e69-52b41c3c481c","order_by":0,"name":"Fiona 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Olweny","email":"","orcid":"","institution":"Makerere University Lung Institute","correspondingAuthor":false,"prefix":"","firstName":"Geoffrey","middleName":"","lastName":"Olweny","suffix":""},{"id":513741286,"identity":"e9862884-9897-40ff-a86d-820634909ebe","order_by":3,"name":"Ivan Segawa","email":"","orcid":"","institution":"Family Health International FHI360","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Segawa","suffix":""},{"id":513741287,"identity":"2ea1bcda-e01e-4387-9fd7-9682f46fdadc","order_by":4,"name":"Leymon Kalema","email":"","orcid":"","institution":"Makerere University, Department of Immunology and Molecular Biology","correspondingAuthor":false,"prefix":"","firstName":"Leymon","middleName":"","lastName":"Kalema","suffix":""},{"id":513741288,"identity":"f01596b6-4fb6-4781-a73f-7a6ddf732932","order_by":5,"name":"Isaac Turyasingura","email":"","orcid":"","institution":"Makerere University Department of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Turyasingura","suffix":""},{"id":513741289,"identity":"4df3cc59-b0b1-48db-bcd6-e1f881a12d8b","order_by":6,"name":"Lorna Atikoro","email":"","orcid":"","institution":"Makerere University Department of Microbiology","correspondingAuthor":false,"prefix":"","firstName":"Lorna","middleName":"","lastName":"Atikoro","suffix":""},{"id":513741290,"identity":"7332002f-22d6-477b-a383-8d810cb6c1c4","order_by":7,"name":"Allen Rhoda Nankya","email":"","orcid":"","institution":"Makerere University Department of Microbiology","correspondingAuthor":false,"prefix":"","firstName":"Allen","middleName":"Rhoda","lastName":"Nankya","suffix":""},{"id":513741291,"identity":"9c72f1e7-55eb-4f26-9b0a-2432bf5f6e32","order_by":8,"name":"Andrew Kazibwe","email":"","orcid":"","institution":"The AIDS Support Organization","correspondingAuthor":false,"prefix":"","firstName":"Andrew","middleName":"","lastName":"Kazibwe","suffix":""},{"id":513741292,"identity":"e67ff57e-6c0a-4cd8-9333-af9bc60b47d4","order_by":9,"name":"Yunus Miya","email":"","orcid":"","institution":"The AIDS Support Organization","correspondingAuthor":false,"prefix":"","firstName":"Yunus","middleName":"","lastName":"Miya","suffix":""},{"id":513741293,"identity":"7b795b19-6bb1-4c87-bbf6-9baf4f2c9dfa","order_by":10,"name":"Paul Katongole","email":"","orcid":"","institution":"Makerere University Department of Microbiology","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Katongole","suffix":""},{"id":513741294,"identity":"6cf290f1-7677-40d9-96b7-b430d9db29f9","order_by":11,"name":"Samuel Kyobe","email":"","orcid":"","institution":"Makerere University Department of Microbiology","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Kyobe","suffix":""},{"id":513741295,"identity":"df59e5c3-33ed-4e23-b773-b9ef29510d8f","order_by":12,"name":"Henry Kajumbura","email":"","orcid":"","institution":"Makerer University","correspondingAuthor":false,"prefix":"","firstName":"Henry","middleName":"","lastName":"Kajumbura","suffix":""},{"id":513741296,"identity":"339cb641-e9ca-4788-98c8-3b6bb17b7954","order_by":13,"name":"Moses Joloba","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Moses","middleName":"","lastName":"Joloba","suffix":""},{"id":513741297,"identity":"a6ff8da5-d4d7-4926-9de0-0698e1c2bcda","order_by":14,"name":"Eric Katagirya","email":"","orcid":"","institution":"Makerere University Department of Immunology and Molecular Biology","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"","lastName":"Katagirya","suffix":""}],"badges":[],"createdAt":"2025-09-11 15:03:58","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7593174/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7593174/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91199430,"identity":"ca9815f7-8daa-4f6f-b071-18e6da7d87b9","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138039,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha Diversity Indices Comparing Recurrent and Isolated UTI Cases\u003c/p\u003e\n\u003cp\u003eBoxplots depicting five alpha diversity metrics (Shannon, Simpson, Observed species, Chao1, and ACE) for stool microbiota from individuals with recurrent (orange) and isolated (blue) urinary tract infections (UTIs). Wilcoxon rank-sum tests were used to assess group differences, with p-values adjusted for multiple comparisons using the Benjamini-Hochberg procedure. While trends suggest lower richness and diversity in recurrent UTI samples, differences did not reach statistical significance after correction.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/7327217c483646ecfb4bb0f0.png"},{"id":91199425,"identity":"e616c874-f065-4d37-a133-a28565cf3cb5","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":130460,"visible":true,"origin":"","legend":"\u003cp\u003eBeta Diversity of Gut Microbiota in Recurrent vs. Isolated UTIs\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePrincipal Coordinates Analysis (PCoA) of Bray-Curtis dissimilarity metrics showing overall microbial community structure in stool samples stratified by UTI phenotype. Each point represents a sample; ellipses denote 95% confidence intervals. PERMANOVA analysis (F = 0.991, p = 0.809, R² = 0.021) indicated no significant clustering between groups, suggesting limited global compositional divergence.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/c89c8f86845d076fbca36680.png"},{"id":91200574,"identity":"b197614f-f4a9-4815-83f2-b43e13a12de0","added_by":"auto","created_at":"2025-09-12 15:27:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":44929,"visible":true,"origin":"","legend":"\u003cp\u003eDirichlet Multinomial Mixture (DMM) clustering of genus-level gut microbiota\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBarplot illustrating the top contributing genera in the Dirichlet Multinomial Mixture (DMM) cluster derived from genus-level abundance data. DMM modelling identified one distinct community type (microbial “enterotypes”), with model selection guided by minimum Laplace approximation. The top taxa contributing to cluster separation include Bacteroides, Veillonellaceae, Alistipes, Streptococcus, and Catenibacterium, indicating distinct ecological signatures across subjects.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/72fe284bd01cb9c83a4cc86b.png"},{"id":91199428,"identity":"51faef23-e552-44b2-be1e-9f2b6d1f2ba0","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57685,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic Composition of Gut Microbiota by UTI Status\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStacked bar plots and alluvial diagrams showing the relative abundance of bacterial taxa at the phylum and genus levels in recurrent versus isolated UTI samples. Dominant phyla included Bacteroidota and Bacillota, with no major phylum-level shifts. Notable genus-level differences included relative depletion of Faecalibacterium and Ruminococcus in recurrent UTIs and increased presence of low-abundance or unclassified genera, suggesting potential taxonomic instability or dysbiosis.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/156208a4a56c3be8d4674e12.png"},{"id":91199429,"identity":"6f467777-51a2-43ce-97e0-940c515c3b7c","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":51669,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential Abundance of Gut Genera Between UTI Groups\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eVolcano plot displaying differentially abundant genera between recurrent and isolated UTI groups, based on TMM-normalized counts analyzed via the limma-voom pipeline. Each point denotes a genus plotted by log₂ fold change (x-axis) and –log₁₀ FDR (y-axis). Positive values indicate enrichment in isolated UTI samples. The genus Weissella was significantly depleted in isolated UTIs (log₂FC \u0026lt; –1, FDR \u0026lt; 0.05), while no genera were significantly enriched in this group.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/088f6ca45ee66116a593d0a6.png"},{"id":91199427,"identity":"35212d4c-e898-4594-92c6-467a436886fa","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":124954,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the Top 20 Most Variable Genera Across UTI Phenotypes\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHeatmap visualizing relative abundances of the 20 most variable genera (based on coefficient of variation) across all samples. Samples are annotated by UTI status (top bar: red = Isolated, blue = Recurrent). Hierarchical clustering reveals phenotype-associated genera, including enrichment of Escherichia-Shigella, Enterococcus, and Weissella in isolated UTIs, and Fusobacterium, Treponema, and Oxalobacter in recurrent cases. The adjacent barplot shows mean genus abundance, highlighting key contributors to microbial variance\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/99ae4f0d2e5306acbc9d63c7.png"},{"id":91199431,"identity":"c1abbb1f-fc16-4db6-8631-4bdf0eef84e4","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":366282,"visible":true,"origin":"","legend":"\u003cp\u003eMicrobial Co-Occurrence Networks in Recurrent and Isolated UTIs\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCo-occurrence network plots of gut microbial genera constructed using Spearman correlation (r ≥ 0.6, p \u0026lt; 0.05), stratified by UTI status. Nodes represent genera; edges represent significant positive correlations. Node size reflects degree centrality. The recurrent UTI network is more modular and tightly connected, while the isolated UTI network exhibits greater dispersion and diversity.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/1773a3d0d09e195ef21262a4.png"},{"id":91208272,"identity":"4adcd0cd-555e-49d2-8586-e2e71bdfb7f2","added_by":"auto","created_at":"2025-09-12 17:09:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2434924,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/d2fdb28f-0eac-4029-9de7-50be2bf8460e.pdf"},{"id":91199432,"identity":"a58f463a-881e-4aa3-bfd9-3e1d32e21948","added_by":"auto","created_at":"2025-09-12 15:19:35","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":9481877,"visible":true,"origin":"","legend":"Additional tables of results from questionaire data and urine microbiology data analysis as well as additional microbiome results images.","description":"","filename":"SupplementaryinformationGutmicorbiome.docx","url":"https://assets-eu.researchsquare.com/files/rs-7593174/v1/bc3a354a0cf81cad66be3ee6.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Gut dysbiosis and antimicrobial resistance among women living with HIV, with recurrent urinary tract infections in Uganda: a cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlobally, UTIs are one of the most common bacterial infections affecting over 400 million people annually (1). Recurrent UTIs (rUTIs), defined as recurrence of 3 or more times in a 1 year or more than two times in 6 months (2), are presumed to be caused by three mechanisms, i.e., an intestinal bloom of uropathogenic bacteria with consequent bladder colonization, reinfection of the urinary tract from an external source, and bacterial persistence within the urinary tract (3). It is well-known that the composition of gut microbiota and gut dysbiosis can influence the health of distant body organs (4). Similar to the gut-brain axis, a close relationship also exists between the gut and the kidney. Organisms that comprise the gut microbiota are known to be common uropathogens, with \u003cem\u003eE.coli\u003c/em\u003e responsible for over 80% of the rUTIs (4). While the gut is a known reservoir for uropathogenic bacteria, the role of the microbiota in recurrent urinary tract infections (rUTI) remains unclear. Numerous studies suggest that rUTI susceptibility is in part mediated through the gut–bladder axis, comprising gut dysbiosis and differential immune response to bacterial bladder colonisation, manifesting in symptoms\u0026nbsp;(5).\u0026nbsp;Gut dysbiosis has been found in many patients with rUTIs, characterized by depletion in microbial richness and diversity, with lower levels of Firmicutes and elevated levels of Bacteroidetes (5).\u0026nbsp;HIV itself has also been linked with gut dysbiosis through impairment of the epithelial lining and disruption of intestinal homeostasis. This leads to immune activation and increased inflammation, thereby increasing the translocation of microbes from the intestinal lumen to the systemic circulation. This microbial translocation leads to HIV progression and exposure to opportunistic infections like UTIs, further worsening the problem\u0026nbsp;(6).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMoreover, frequent use of antibiotics for prophylaxis and treatment of rUTIs can contribute to the development of multidrug-resistant bacteria within a few weeks (2). \u003cem\u003eE. coli,\u003c/em\u003e for example, was identified in about 90% of patients who had previously received prophylactic antibiotics (2). Studies have revealed that most E. coli organisms exhibit more than 50% resistance to most penicillins and cephalosporins (7-9). Drug resistance to Ciprofloxacin at 44.4%, Ceftriaxone at 35.0% as well as Ampicillin, Cotrimoxazole, and Gentamicin was 9.1% in Ugandan PLHIV with UTI (10). PLHIV are most exposed to antibiotics as they are more prone to bacterial infections compared to other populations. Antibiotics are used in opportunistic infection prophylaxis, TB prophylaxis, and treatment, as well as treatment of many other opportunistic infections among PLHIV. This higher risk of inappropriate antibiotic use further increases the risk of antimicrobial drug resistance and gut dysbiosis. Understanding of the common causative pathogens of recurrent and isolated UTIs among WLHIV, their antimicrobial susceptibility profiles and factors associated with recurrent UTIs among WLHIV is essential in refining guidelines for the treatment of recurrent UTIs among WLHIV. The data collected from this study are critical in informing scientists about the potential benefits of non-pharmacologic methods for preventing recurrent UTIs among WLHIV, highlighting differences in microbiomes among WLHIV. This will pave the way for future research into the use of microbiome restoration techniques, such as the use of probiotics, to prevent or control recurrent UTIs. Therefore, understanding bacterial aetiologies, antimicrobial susceptibility patterns, risk factors for recurrent and isolated UTIs among WLHIV and the role of gut microbiota in Uropathogenesis is essential in developing appropriate treatment guidelines to tackle this public health concern.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis was a clinic-based cross-sectional study conducted from February to June 2025 among 62 adult women living with HIV receiving HIV care at TASO Mulago HIV clinic.Participants were screened, and enrolled into the study and then provided samples at the TASO Mulago HIV clinic. Urine culture and sensitivity was conducted at the Makerere University, Department of Microbiology teaching laboratory. Stool samples underwent DNA extraction at Makerere University Molecular Biology Laboratory and then sequencing at Inqaba Biotec Laboratory, South Africa. We included adult WLHIV (including pregnant women), who presented with two or more symptoms of Cystitis, of any duration as per the European Medicines Agency (EMA) and US Food and Drug Administration (11) and a Positive Urine dipstick. We excluded WLHIV who had been diagnosed with any form of cancer.\u003c/p\u003e\n\u003cp\u003eWLHIV were screened for UTIs through medical history and clinical examination, as well as on-site urinalysis. Enrolled participants then provided clean-catch midstream urine samples, underwent a questionnaire, and had their medical records reviewed. Participants then provided stool samples. Both urine and stool specimens were transported under cold chain to the laboratories. In the microbiology laboratory, urine samples underwent macroscopy, microscopy, biochemical tests, and culture on Blood Agar and MacConkey agar, with incubation for 18-24 hours. Significant growth was further identified to species level using Gram stain and biochemical methods, and antimicrobial susceptibility testing was performed using the Kirby-Bauer disc diffusion method following CLSI guidelines (12). Quality control measures, including ATCC reference strains, were applied throughout sample collection, transport, processing, and interpretation.\u003c/p\u003e\n\u003cp\u003eStool DNA was extracted using the\u0026nbsp;FastDNA™ SPIN Kit for Soil, with samples preserved in\u0026nbsp;DNA/RNA Shield\u0026nbsp;to stabilise nucleic acids. Up to 500 mg of stool was homogenized in\u0026nbsp;Lysing Matrix E tubes\u0026nbsp;using a\u0026nbsp;FastPrep instrument, followed by centrifugation, protein precipitation, DNA binding to the\u0026nbsp;Binding Matrix, ethanol washes with\u0026nbsp;SEWS-M solution, and elution with\u0026nbsp;DES, with DNA stored at -20 °C. Quality checks included\u0026nbsp;NanoDrop™ spectrophotometry(OD260/OD280: 1.8-2.0; OD260/OD230: 2.0-2.2) and concentration verification (\u0026gt;5 ng/µL) before cold-chain shipment to\u0026nbsp;Inqaba Biotechnical Industries Laboratory. Samples were then unshielded, purified with\u0026nbsp;AMPure PB magnetic beads, quantified with the\u0026nbsp;Qubit™ dsDNA High Sensitivity Assay Kit, and integrity confirmed by\u0026nbsp;agarose gel electrophoresis. Full-length\u0026nbsp;16S rRNA (V1-V9)\u0026nbsp;was amplified using\u0026nbsp;27F/1492R universal primers\u0026nbsp;with barcoded adapters and\u0026nbsp;Takara LA Taq® Hot Start polymerase, purified with AMPure PB beads, and prepared with the\u0026nbsp;SMRTbell® Express Template Prep Kit 2.0, followed by size selection with\u0026nbsp;BluePippin™. Sequencing was performed on the\u0026nbsp;PacBio Revio™ platform, generating HiFi reads via circular consensus sequencing. Post-sequencing, data were processed using\u0026nbsp;SMRT Link™ v11, with demultiplexing, adapter trimming, and chimera removal via\u0026nbsp;USEARCH/VSEARCH, retaining only high-quality full-length reads (Q ≥ 30, ~1,500 bp) for downstream analysis.\u003c/p\u003e\n\u003cp\u003eBioinformatics analysis of 16S rRNA sequencing data involved quality inspection of raw FASTQ reads using FastQC, followed by denoising, ASV inference, and taxonomy assignment with the DADA2 (v1.20.0) pipeline in R. Outputs (ASV tables, sequences, and taxonomy) were integrated with sample metadata in phyloseq for diversity assessment, differential abundance testing, microbial typing, and network analyses, with statistical comparisons conducted using non-parametric tests (Wilcoxon, Kruskal-Wallis, Spearman) and multiple testing correction via Benjamini-Hochberg FDR. Questionnaire and urine microbiology data were analyzed in Stata 16, with continuous variables summarized as means or medians, and categorical variables as proportions. Comparisons were made using Wilcoxon rank-sum or Fisher’s exact tests. Antimicrobial resistance patterns were reported as proportions, and factors associated with recurrent UTIs were examined using exact logistic regression, yielding crude odds ratios (cOR) with 95% CIs; no multivariable models were built as only one variable met the inclusion threshold. Variables with p \u0026lt; 0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003e\u003cstrong\u003eCharacteristics of the study population.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe median (IQR) age of the 62 participants was 36 years (IQR 32, 46), with a median (IQR) body mass index of 25.7 kg/m\u003csup\u003e2\u003c/sup\u003e (IQR 23.1, 31.8) (\u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e). Eighty-seven percent of the population had been on ART for more than five years, 87.1% (54), on the Tenofovir/Lamivudine/Dolutegravir (TDF/3TC/DTG) regimen 87.1% (54). The majority of the study population had a CD4 count above 200 cells/microlitre, 93.5% (58) and 80.7% (50) had an undetectable viral load less than 50 copies per millilitre. At the time of study enrolment, 79% (49) of the study population had experienced their first UTI episode in the previous six months, thus isolated a UTI episode, and 21% (13) had experienced other episodes within 12 months prior to enrolment, thus had recurrent UTI episodes. Twenty-four percent 24.2% (15) of the study population had gastrointestinal symptoms at the time of enrolment, with the majority of these reporting bloating 60% (9) and diarrhoea 26.7% (4). Forty percent (25) of the population reported having used an antibiotic in the last six months, with only 22.6% (14) having used Cotrimoxazole. The other sociodemographic and clinical characteristics are in \u003cstrong\u003e\u003cem\u003eTable 1\u003c/em\u003e\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eTable 1: Socio-demographic and Clinical characteristics of study population.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN (%) or Median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 79.91%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio-demographic characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e36 (32, 46)\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 79.91%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest educational attainment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e3 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e34 (54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e21 (33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Vocational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e4 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Single\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e19 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e33 (53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e10 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody Mass Index\u003c/strong\u003e, kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e25.7 (23.1, 31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Less than 100,000UGX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e22 (35.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Between 100,000 - 500,000UGX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e38 (61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Above 500,00 UGX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eDiet\u003c/strong\u003e -Eats a balanced diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e60 (96.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 79.91%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently using family planning method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e13 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 79.91%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of family planning method currently being used\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Combined Oral Contraceptives\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e2 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Implant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e10 (76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Tubal ligation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e1 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eSexually active\u003c/strong\u003e -Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e44 (71.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexual partner\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Casual (only sexual encounter/no relationship)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e10 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Steady (1 to 4 years\u0026apos; relationship)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e11 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Long-term (relationship of 5 or more years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e23 (52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 79.91%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaginal hygiene practices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Washing with clean water only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e55 (88.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Washing with soap and water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e11 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Steaming/ inserting herbs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e10 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Douching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 25.1247%;\"\u003e\n \u003cp\u003e12 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 87.4798%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration on ART\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt; 1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; 1-5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e7 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e54 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent ART regimen\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; ABC/3TC/DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; AZT/3TC/DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e3 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; TDF/3TC/ATV/r\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; TDF/3TC/DTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e54 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; TDF/3TC/EFV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e1 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCD4 count\u0026nbsp;\u003c/strong\u003e\u0026gt; 200 cells/mm3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e58 (93.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecent viral load\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Not detected/Detected, below limit of quantification\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e50 (80.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 87.4798%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of chronic disease (other than HIV)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e13 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic diseases\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e7 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 87.4798%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of UTIs in the past 6 months\u0026nbsp;\u003c/strong\u003e(including current episode)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e50 (80.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e10 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e2 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecurrent UTIs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e49 (79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e13 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 87.4798%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent symptoms of GI disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e15 (24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGI disorder\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Abdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e9 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Bloating\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e2 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Diarrhea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e4 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eAntibiotic use in the past 6 months\u003c/strong\u003e -Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e25 (40.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eCotrimoxazole use in the past 6 months\u003c/strong\u003e -Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e14 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 87.4798%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndication for cotrimoxazole\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; High viraemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Newly initiated on ART and pregnant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e1 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e7 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; Stage III or IV event\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e3 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 54.7854%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eCurrently on CTX prophylaxis-\u0026nbsp;\u003c/strong\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 32.6945%;\"\u003e\n \u003cp\u003e10 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003e\u003cstrong\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;was the most isolated pathogen on urine culture\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFollowing urine culture and sensitivity, 19.3% (12/62) of cultures had significant bacterial growth and had bacterial pathogens isolated (\u003cstrong\u003eTable 2\u003c/strong\u003e). Of the isolates that had significant bacterial growth, 83.3% (10/12) grew \u003cem\u003eEscherichia coli\u003c/em\u003e. Antimicrobial susceptibility testing on the \u003cem\u003eEscherichia coli\u003c/em\u003e isolates demonstrated 100% susceptibility to Imipenem (10/10) and Nitrofurantoin (10/10). Resistance to Ampicillin was at 80% (8/10), 70% to Nalidixic acid (7/10), and SXT , as well as 60% resistance to Cefixime and Cefotaxime. All \u003cem\u003eE. coli\u003c/em\u003e that were resistant to at least one third-generation cephalosporin were screened for Extended Spectrum Beta Lactamase (ESBL) production and only one isolate (10%) was confirmed positive for ESBL production.\u003c/p\u003e\n\u003cp\u003eTable 2: Bacterial pathogens isolated and their resistance profiles\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"166%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOrganism\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmpicillin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAugmentin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCefepime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCefotaxime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCeftazidime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCefuroxime (Oral)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCiprofloxacin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGentamicin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImipenem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNalidixic acid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNitrofurantoin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePISA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSXT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCitrobacter spp (N=1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEscherichia coli (N=10)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e4 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e10 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e10 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e10 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e8 (88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e8 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e6 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e7 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e7 (70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKlebsiella pneumoniae (N=1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;S-Sensitive, I-Intermediate, R-Resistant.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eRecent antibiotic use was significantly associated with recurrent UTI acquisition.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eA significant association was observed between recent antibiotic use in the past six months and recurrent UTI (\u003cem\u003ep\u003c/em\u003e=0.001, CI 7.58-+Inf) (\u003cstrong\u003eTable 3\u003c/strong\u003e). All participants with recurrent UTI (100%) had used antibiotics, compared to only 12 (24.5%) among those with isolated UTI (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Cotrimoxazole use was not significantly associated with recurrent UTI (\u003cem\u003ep\u003c/em\u003e = 0.466).\u003c/p\u003e\n\u003cp\u003eTable 3: Factors associated with recurrent UTIs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecurrent UTI,\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003en (%) or Mean (SE)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e(Mean, SE), years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e41.1 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e1.01 (0.96-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Vocational/Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e4 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.60 (0.12-2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.534\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBody Mass Index\u0026nbsp;\u003c/strong\u003e(Mean, SE), kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e27.7 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;1.01 (0.91-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.839\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecent viral load done\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Detected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e2 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.71 (0.07-4.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent GIT symptoms\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e5 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e2.40 (0.50-10.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 606px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotics use in the past 6 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e13 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e50.45 (7.58-+Inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 606px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCotrimoxazole use in the past 6 months\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e4 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e1.72 (0.32-7.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSexually active\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e8 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.58 (0.14-2.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaginal hygiene practices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Uses clean water only\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e37.1 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e1.02 (0.99-1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Uses water and soap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e2.3 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.97 (0.86-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Frequently used vaginal steaming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e0.1 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.73 (0.16-1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Frequently douches\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e4.6 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.99 (0.93-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of chronic disease other than HIV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 321px;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 153px;\"\u003e\n \u003cp\u003e2 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 131px;\"\u003e\n \u003cp\u003e0.69 (0.06-4.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ecOR-Corrected Odds Ratio, GIT-Gastrointestinal tract, UTI-Urinary Tract Infection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGut microbiome richness and evenness were subtly reduced in the recurrent UTI group.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlpha diversity metrics were assessed across stool samples from individuals with either isolated or recurrent UTIs using Shannon, Simpson, Observed Species, Chao1, and ACE indices (\u003cstrong\u003eFigure 1\u003c/strong\u003e). Visual inspection of boxplots showed a trend toward reduced microbial richness and diversity among recurrent UTI patients. Specifically, recurrent UTI samples exhibited lower median values across the richness-based indices; Observed, Chao1, and ACE, indicating a potential contraction in the number of distinct microbial taxa. The Shannon index, which integrates richness and evenness, also trended lower in recurrent UTI samples, suggesting a broader reduction in ecological complexity. In contrast, the Simpson index, which emphasizes community evenness, showed minimal differences between groups, implying that dominant taxa were similarly distributed in both cohorts. A statistical comparison using the Wilcoxon rank-sum test with the Benjamini-Hochberg correction revealed that, although the observed differences were consistent with biological trends, they did not reach statistical significance (adjusted p-value \u0026gt; 0.05). These findings suggest that gut microbiota richness is modestly reduced in recurrent UTI patients, potentially reflecting ecological stress or subclinical dysbiosis that does not uniformly affect all individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNo distinct clustering by UTI phenotype on Beta diversity analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBeta diversity analysis was performed using Bray-Curtis dissimilarity followed by Principal Coordinates Analysis (PCoA) to assess overall community-level dissimilarity. As shown in \u003cstrong\u003eFigure 2\u003c/strong\u003e, samples from both groups exhibited substantial overlap in ordination space, with no distinct clustering by UTI phenotype. PERMANOVA testing (\u003cstrong\u003eTable 4\u003c/strong\u003e) confirmed the lack of significant community-level divergence (F = 0.991, p = 0.809, R\u0026sup2; = 0.021), indicating that UTI status explained only 2.1% of the total variation in microbial composition. This finding highlights the relatively subtle ecological distinctions between recurrent and isolated UTI microbiota at the genus level, suggesting that global taxonomic restructuring is not a dominant feature distinguishing these phenotypes. Nevertheless, broader inter-individual heterogeneity possibly shaped by host genetics, antibiotic exposure, or behavioural differences may be obscuring finer microbial signatures of UTI recurrence.\u003c/p\u003e\n\u003cp\u003eTable 4: UTI status PERMAMOVA results\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eSum Of Sqs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003ePr(\u0026gt;F)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidual\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e23.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e23.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 148px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDMM revealed one microbial cluster with differential enrichment of genera.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDirichlet Multinomial Mixture (DMM) modeling was applied to identify discrete gut microbiota configurations across the UTI groups. The optimal model, determined via minimum- Laplace approximation, supported multiple clusters representing distinct ecological states or \u0026ldquo;enterotypes\u0026rdquo; within the sample set (\u003cstrong\u003eFigure 3\u003c/strong\u003e). The model revealed one DMM cluster that was defined by the differential enrichment of a unique set of microbial genera. Taxa contributing most strongly to cluster loadings included Bacteroides, Alistipes, Veillonellaceae, Catenibacterium, Bifidobacterium, and Streptococcus. Interestingly, DMM clusters did not align strictly with UTI phenotype but revealed compositional heterogeneity within both recurrent and isolated UTI groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe recurrent UTI group showed a reduction in Short-Chain Fatty Acid-producing genera.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine compositional patterns in more detail, we generated stacked bar plots and alluvial diagrams of phylum- and genus-level relative abundances (\u003cstrong\u003eFigure 4\u003c/strong\u003e). Both groups were dominated by core gut phyla Bacteroidota and Bacillota, reflecting a conserved enteric signature. Pseudomonadota and Actinomycetota made minor contributions. At the genus level, both UTI groups harbored a high relative abundance of Bacteroides, Faecalibacterium, Bifidobacterium, and Segatella. However, the recurrent UTI group demonstrated a relative depletion of beneficial genera such as Faecalibacterium and Ruminococcus, both of which are butyrate producers linked to anti-inflammatory activity and gut homeostasis. Concurrently, an increased proportion of \u0026ldquo;unknown\u0026rdquo; or unclassified taxa was noted in recurrent samples, suggesting either greater ecological instability or limitations in taxonomic resolution. Collectively, these data indicate that while the phylum-level structure is preserved, recurrent UTI cases may experience a subtle loss of key commensal functions and an increase in taxonomic entropy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe genus\u003cem\u003e\u0026nbsp;Weisella\u003c/em\u003e was significantly enriched in the recurrent UTI group.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify genus-level taxa associated with UTI recurrence status, we applied a differential abundance analysis using the limma-voom framework on TMM-normalized genus-level count data. The volcano plot (Figure 5) presents genera plotted by log2fold change (Recurrent vs. Isolated) and \u0026ndash;log10 FDR (significance threshold of log2fold change \u0026lt; \u0026ndash;1 and FDR \u0026lt; 0.05). Only a single genus, \u003cem\u003eWeissella\u003c/em\u003e, emerged as significantly differentially abundant between groups with a log2fold of -2.5 and -log10FDR of -10, indicating it was depleted in the Isolated UTI group and enriched in Recurrent UTI patients. No other genera reached the significance thresholds of FDR \u0026lt; 0.05 and an absolute log2 fold change (log2FC) of\u0026ge; 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePathobiont genera were more abundant in the recurrent UTI group.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further dissect taxonomic contributors to UTI recurrence, we identified the 20 most variable genera across the cohort based on coefficient of variation and visualized their abundance patterns using hierarchical clustering heatmaps (\u003cstrong\u003eFigure 6\u003c/strong\u003e). Samples largely segregated by UTI phenotype, with recurrent and isolated cases forming distinct blocks. Several genera, including Weissella, Enterococcus, Escherichia-Shigella, and Lactococcus, were more abundant in isolated UTI individuals, potentially reflecting post-infection recovery or probiotic dominance. Conversely, Fusobacterium, Treponema, Oxalobacter, and unclassified Lachnospiraceae were more abundant in recurrent UTI samples, possibly representing low-abundance pathobionts or environmental contaminants associated with dysbiosis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe recurrent UTI concurrence network was more modular and centralized.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo examine ecological interactions between taxa, we constructed genus-level co-occurrence networks using Spearman correlation (r \u0026ge; 0.6, p \u0026lt; 0.05), stratified by UTI status (\u003cstrong\u003eFigure 7\u003c/strong\u003e). Networks were visualised with nodes representing genera and edge weights representing positive correlations. The Isolated UTI network displayed a loosely connected structure with dispersed nodes and multiple independent modules, suggesting greater ecological redundancy and resilience. In contrast, the Recurrent UTI network was more modular and centralized, with higher node density and fewer but tightly connected modules. Taxa such as Faecalibacterium, Bacteroides, and Ruminococcus remained prominent hubs in both networks. However, the Recurrent UTI network featured a greater number of unidentified or low-confidence nodes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe enrolled 62 WLHIV into this study to describe the bacterial pathogens causing UTIs, their drug susceptibility profiles, factors associated with UTIs, the gut microbiome of WLHIV with UTIs, and its relationship with recurrent UTIs. The majority of our participants were young, overweight, consumed a balanced diet and utilized clean water only to clean their genitals. They had been on antiretroviral therapy (ART) for over five years, predominantly on Tenofovir/Lamivudine/Dolutegravir regimen. They were immunologically stable and virologically suppressed. This finding is consistent with the World Health Organization (WHO) guidelines that recommend TDF/3TC/DTG as a first-line regimen for adults living with HIV due to its potency, tolerability, and high barrier to resistance (13). The stability of this population, indicated by virologic suppression and CD4 counts above 200 cells/μL, aligns with expectations for individuals on long-term ART, supporting evidence from Uganda and other sub-Saharan African settings that demonstrate improved immunologic and virologic outcomes with TLD (14) (15).\u0026nbsp;About one-quarter of the participants had gastrointestinal (GI) symptoms, mainly abdominal pain and diarrhoea. GI complaints are common in PLHIV, even in the era of effective ART, and may reflect subclinical inflammation, opportunistic infections, or gut microbiota dysbiosis\u0026nbsp;(16, 17). These symptoms may also serve as a proxy for intestinal permeability and microbial translocation, which have been implicated in persistent immune activation despite viral suppression\u0026nbsp;(18). Notably, nearly half of the study population reported antibiotic use within the last six months, with pregnancy cited as the most common indication. While antibiotic use during pregnancy is sometimes necessary (e.g., for urinary tract infections), overuse can significantly alter the gut microbiota, potentially increasing the risk of dysbiosis-associated conditions, such as recurrent urinary tract infections (rUTIs)\u0026nbsp;(19). This aligns with prior findings that recent antibiotic exposure is a significant risk factor for recurrent urinary tract infections (rUTIs ) and multidrug-resistant infections\u0026nbsp;(20, 21). Interestingly, only 16% of participants were on cotrimoxazole prophylaxis, which is in line with national guidelines that recommend discontinuation in virologically suppressed individuals with CD4 \u0026gt;200 and no other significant comorbidities\u0026nbsp;(22). Cotrimoxazole has been found to have beneficial effects on the gut microbiome and immune system through dampening inflammatory cytokine production and therefore withdrawal of cotrimoxazole therapy may have negative gut microbiota effects\u0026nbsp;(23). Compared to similar cohorts in sub-Saharan Africa, this study population demonstrates high ART adherence and treatment success, consistent with the scale-up of Dolutegravir-based regimens and improved HIV program outcomes\u0026nbsp;(24). However, the prevalence of antibiotic exposure and GI symptoms is notable and suggests that clinical stability does not preclude microbiome disturbances. Prior research from South Africa and Kenya has similarly documented persistent GI symptoms and altered microbiota profiles among PLHIV despite ART\u0026nbsp;(24-26). Furthermore, the comorbidity burden reflects findings from large HIV cohort studies, which underscore the double burden of communicable and non-communicable diseases in African HIV clinics\u0026nbsp;(27).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBacterial aetiologic agents of UTI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing urine culture and sensitivity testing, we had a positivity rate of nearly 20%, with over 80% of the isolated organisms being \u003cem\u003eEscherichia coli\u003c/em\u003e. This is similar to culture positivity results obtained in recent (2024-2025) studies, such as a systematic review of multiple studies conducted among PLHIV on the African continent, where the UTI culture positivity rate was 23.6%, with \u003cem\u003eEscherichia coli\u003c/em\u003e also being the most commonly isolated pathogen across all those studies (28). Another recent study conducted in central Ethiopia, among PLHIV, also obtained a prevalence of 20.9%, with the most prevalent bacterial pathogen being \u003cem\u003eE.coli\u003c/em\u003e at 43% (29). Another recent study, also done in Ethiopia, reported a culture positivity rate of 21.7%, with the most predominant bacterial pathogen isolated being \u003cem\u003eEscherichia coli\u003c/em\u003e (30). This positivity rate, however, is higher than the culture positivity rates identified in previous (2020-2023) UTI studies among PLHIV in Africa. Netsanet had a culture positivity rate of 10.3% though \u003cem\u003eEscherichia coli\u003c/em\u003e was still the most prevalent bacterial pathogen at 69.6% (9). Molla et al obtained a similarly lower prevalence of 12.8% (31). Admasu et. Al reported a positivity rate of 14.1%, with the commonest pathogen isolated being E.coli at 44.8% (32). However, there are older studies (earlier than 2020) that reported a similar prevalence to that obtained in our study, such as Agata et al, who obtained a culture positivity rate of 23.2% (33).\u003c/p\u003e\n\u003cp\u003eIn conclusion, the culture positivity rate of nearly 20% observed in our study aligns with more recent studies (2024-2025) conducted among PLHIV across Africa, which consistently report similar prevalence rates and a predominance of \u003cem\u003eEscherichia coli\u003c/em\u003e as the main uropathogen. While our findings contrast with lower positivity rates documented in earlier studies (2020-2023), they mirror older data, such as that from (33), suggesting a possible resurgence or evolving trend in UTI prevalence among PLHIV. This consistency in pathogen profile across time underscores the persistent role of \u003cem\u003eE.coli\u003c/em\u003e in urinary tract infections in this population and highlights the continued need for routine urine culture and sensitivity testing to guide targeted antimicrobial therapy.\u003c/p\u003e\n\u003ch2 id=\"_Toc203646798\"\u003e\u003cstrong\u003eAntimicrobial susceptibility profiles of bacterial agents isolated.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe \u003cem\u003eE.coli\u003c/em\u003e isolates in this study exhibited high susceptibility to \u003cstrong\u003eImipenem\u003c/strong\u003eand\u003cstrong\u003eNitrofurantoin\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e consistent with findings from multiple global and regional studies. Imipenem and other carbapenems continue to demonstrate near-universal efficacy against \u003cem\u003eE. coli\u003c/em\u003e, including multidrug-resistant and ESBL-producing strains, reinforcing their critical role in treating urinary tract infections (UTIs) (34, 35). Nitrofurantoin's sustained activity is also well-documented, especially for lower UTIs, due to its minimal impact on gut flora and low propensity for resistance development (36, 37). Moderate susceptibility to third-generation cephalosporins such as \u003cstrong\u003eCeftazidime\u003c/strong\u003e (60%) and \u003cstrong\u003eCefotaxime\u003c/strong\u003e (30%), as well as high resistance to Ampicillin (80%), raises concerns about declining efficacy. Similar patterns of intermediate resistance have been reported in Uganda (38) Kenya (39), and India (40), likely driven by widespread and often unregulated use of beta-lactams in both community and hospital settings. This trend diminishes the reliability of cephalosporins for empirical treatment and necessitates sensitivity-guided therapy.\u003c/p\u003e\n\u003cp\u003eResistance to \u003cstrong\u003eAmpicillin\u003c/strong\u003e(80%),\u003cstrong\u003eSXT\u003c/strong\u003e (70%), and \u003cstrong\u003eNalidixic acid\u003c/strong\u003e (70%) aligns with global data showing high resistance rates to these traditionally first-line antibiotics. Studies from Nigeria, Ethiopia, and Brazil have similarly documented resistance rates exceeding 70%, which is largely attributed to the long-standing overuse and availability without prescription (41, 42). Other studies have also reported resistance rates of over 50% to Ciprofloxacin and Nalidixic acid, 93.8% to Ampicillin, and 62.5% to Cotrimoxazole, with some reporting up to 100% resistance to Ampicillin and Ciprofloxacin among participants with UTIs (9, 29, 32). The high resistance to SXT and nalidixic acid is particularly problematic in resource-limited settings where they are frequently used due to affordability.\u003c/p\u003e\n\u003cp\u003eThe ESBL prevalence among \u003cem\u003eE. coli\u003c/em\u003e isolates in this study was 10%, which is lower than rates reported in many parts of Africa and Asia. For instance, studies in Ethiopia and Kenya have reported ESBL-producing \u003cem\u003eE. coli\u003c/em\u003e rates of 25-45% (43, 44), while South Asian countries often report rates exceeding 50% (Rawat \u0026amp; Nair, 2010). The relatively low prevalence in this cohort could reflect local antibiotic use patterns, reduced nosocomial exposure, or the specific demographic (women living with HIV) under study. Nonetheless, even a single ESBL-producing isolate is clinically relevant due to its association with multidrug resistance and treatment failure if unrecognized (45). These findings underscore the importance of regular surveillance and antimicrobial stewardship, especially in high-risk populations such as women living with HIV, who may have altered immune responses and frequent antibiotic exposure. Targeted microbiological testing and individualized therapy can help preserve the efficacy of remaining active agents and prevent the development of further resistance. In this study, ESBL production was detected using the disc approximation method, which, while practical, may have missed some true ESBL producers due to limitations in sensitivity, particularly in cases where low-level enzyme expression or co-existing AmpC β-lactamases masked ESBL activity. The study did not assess for AmpC genes, which may further limit the accuracy of ESBL detection. More robust confirmatory methods, such as the double disc synergy test (DDST) or molecular techniques like PCR targeting \u003cem\u003ebla_CTX-M\u003c/em\u003e, \u003cem\u003ebla_SHV\u003c/em\u003e, and \u003cem\u003ebla_TEM\u003c/em\u003e genes, are recommended for future studies to improve diagnostic accuracy and better characterize resistance mechanisms.\u003c/p\u003e\n\u003cp id=\"_Toc203646799\"\u003e\u003cstrong\u003eFactors associated with recurrent and isolated UTIs among WLHIV.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, antibiotic use within the past six months was significantly associated with UTI in both groups, consistent with existing literature that identifies recent antibiotic exposure as a major risk factor for recurrence. Antibiotics, especially broad-spectrum agents, disrupt the gut and urogenital microbiota, leading to dysbiosis and colonization by resistant or uropathogenic strains (46, 47). A systematic review by (48) highlighted prior antibiotic use as one of the most consistently reported risk factors for recurrent UTI in women. Similarly, research in the Netherlands and the United States found that repeated antibiotic exposure increased the risk of both reinfection and resistance (49, 50).\u003c/p\u003e\n\u003cp\u003eAge, BMI, and educational level were not significantly associated with recurrent UTI in this cohort. This finding is similar to studies in sub-Saharan Africa and Southeast Asia, where demographic variables were not consistently predictive of recurrence after accounting for clinical risk factors (37, 39). However, some studies have shown that older women, particularly postmenopausal women, are more prone to rUTIs due to reduced estrogen and changes in the vaginal microbiome (51), though this was not evident in the relatively younger cohort in this study. Gastrointestinal symptoms and viral load detectability were not significantly linked to recurrence, although prior literature suggests that gastrointestinal dysbiosis and immunosuppression may predispose to UTI recurrence in women living with HIV (52, 53). The absence of a significant association here may be due to the small sample size or effective antiretroviral therapy controlling viral replication in most participants.\u003c/p\u003e\n\u003cp\u003eInterestingly, no vaginal hygiene practice, including the use of clean water, soap, douching, or steaming, was significantly associated with recurrence. This contrasts with studies in Nigeria and Kenya, where frequent douching or use of antiseptics in vaginal hygiene was found to disrupt protective flora and increase UTI risk (54, 55). However, the methods, frequency, and types of substances used in hygiene practices vary widely, which may explain discrepancies. Cotrimoxazole prophylaxis, commonly used in people living with HIV, was not significantly associated with recurrence, despite its antimicrobial activity. This finding aligns with results from a South African cohort, where cotrimoxazole prophylaxis did not reduce UTI recurrence, possibly due to resistance or sub-therapeutic dosing (56).\u003c/p\u003e\n\u003ch2 id=\"_Toc203646800\"\u003e\u003cstrong\u003eMost abundant bacterial taxa \u0026amp; relationship between gut microbiome and UTI.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eOur alpha diversity analysis showed a consistent trend of reduced species richness (Observed, Chao1, ACE indices) in individuals with recurrent UTIs compared to those with isolated episodes. While statistical significance was not uniformly achieved after multiple testing correction, this directional trend aligns with existing evidence linking reduced microbial diversity to impaired gut resilience and increased risk of infections (57). Richer microbial communities are thought to enhance colonization resistance via nutrient competition, niche exclusion, and modulation of host immunity (58). Therefore, diminished diversity may create an ecological vacuum favoring the persistence or reemergence of uropathogens.\u003c/p\u003e\n\u003cp\u003eContrary to alpha diversity trends, beta diversity analysis revealed no significant separation of microbial communities based on UTI phenotype, as evidenced by Bray-Curtis dissimilarity and PERMANOVA testing. This finding suggests that overall gut microbial composition remains broadly similar between groups, and that wholesale shifts in community membership may not drive recurrent UTI. This is consistent with prior observations that subtle functional or strain-level differences, rather than broad taxonomic changes, may underlie recurrent infection risk (59). Such findings underscore the importance of functional metagenomic profiling in capturing nuanced microbial signatures that may be overlooked by taxonomy alone.\u003c/p\u003e\n\u003cp\u003eDirichlet Multinomial Mixture (DMM) modeling revealed distinct gut microbial community types among participants, characterized by variable dominance of genera such as Bacteroides, Veillonellaceae, and Catenibacterium.\u0026nbsp;These genera are well-recognized components of a healthy gut microbiota and are frequently implicated in immune modulation, the production of short-chain fatty acids, and maintaining the integrity of the gut barrier.\u0026nbsp;These genera have been previously implicated in gut–urogenital axis interactions and uropathogen colonization dynamics (60). Notably, the presence of taxa like Streptococcus and Alistipes in distinct community clusters may reflect niche adaptation, with some strains facilitating mucosal immunity. In contrast, others are associated with inflammation or antibiotic resistance, hence\u0026nbsp;suggesting that inter-individual differences in community structure may influence disease risk or resilience beyond binary groupings\u0026nbsp;(61). The identification of discrete enterotypes echoes broader efforts to stratify the human gut microbiome into ecologically and clinically relevant configurations.\u003c/p\u003e\n\u003cp\u003eAlthough both UTI groups were dominated by common gut phyla (Bacteroidota and Bacillota), subtle but noteworthy compositional trends emerged. Patients with recurrent UTIs exhibited lower relative abundances of anti-inflammatory genera such as Faecalibacterium and Ruminococcus, which are key producers of short-chain fatty acids (SCFAs) involved in maintaining gut barrier function and immune regulation (62). Simultaneously, a rise in poorly annotated or “unknown” genera in recurrent cases may reflect increased taxonomic entropy, a hallmark of microbial dysbiosis (63). These trends collectively point toward ecological destabilization in the gut of recurrent UTI patients.\u003c/p\u003e\n\u003cp\u003eAmong the differentially abundant taxa, Weissella was significantly enriched in the recurrent UTI group. This finding was unexpected given that Weissella spp., a group of facultative anaerobic lactic acid bacteria, are often considered protective commensals with roles in bacteriocin production, mucosal colonization, and modulation of host immunity (64).\u0026nbsp;Some Weissella species have been associated with opportunistic infections, particularly in immunocompromised individuals\u0026nbsp;(65).\u0026nbsp;Their increased abundance in recurrent UTI cases may therefore reflect ecological selection pressures such as prior antibiotic use or indicate a potential role as a low-grade pathobiont or bystander taxa in dysbiotic gut environments. This finding, while singular, underscores the importance of deeper strain-level or functional analyses to determine whether \u003cem\u003eWeissella\u003c/em\u003e’s enrichment represents an adaptive shift or contributes causally to UTI recurrence. The absence of additional significant taxa supports the notion that compositional differences between groups are subtle and possibly masked by inter-individual heterogeneity.\u003c/p\u003e\n\u003cp\u003eHeatmap analysis of the top 20 most variable genera reinforced earlier observations. Certain genera, such as Enterococcus, Escherichia-Shigella, and Lactococcus, were more abundant in subsets of isolated UTI patients, possibly reflecting acute inflammation or recent antimicrobial exposure. Conversely, genera such as Treponema and Fusobacterium were more prevalent in recurrent UTI cases,\u0026nbsp;possibly representing low-abundance pathobionts or environmental contaminants associated with dysbiosis. These results underscore the potential utility of genus-level microbial signatures as discriminators of UTI recurrence risk, warranting functional validation and longitudinal follow-up.\u003c/p\u003e\n\u003cp\u003eThe co-occurrence network analysis uncovered stark structural differences between the microbiota of recurrent versus isolated UTI patients. The recurrent UTI network was denser and more modular, with genera forming tighter hubs. In contrast, the isolated UTI network exhibited a more distributed topology, suggestive of greater microbial heterogeneity and redundancy.\u0026nbsp;These findings point to altered microbial assembly and reduced network robustness in recurrent UTI patients, potentially diminishing microbial community resilience against perturbations like antibiotic exposure or pathogen invasion\u0026nbsp;(66). The loss of peripheral taxa and the dominance of tightly clustered hubs in the recurrent UTI group may thus signal a dysbiotic core with diminished adaptability.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eLimitations.\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe study faced several limitations, including a small sample size that may have reduced statistical power and generalizability. However, standardised procedures and uniform data collection preserved internal consistency across participants. Stool samples were collected at a single time point, which may not have captured temporal shifts in microbiome composition, but all were obtained under the same conditions, reducing within-group variability and ensuring comparability. The use of machine learning models carries the risk of overfitting due to the high dimensionality of microbiome data and limited sample size. To address this, cross-validation and careful feature selection were employed to support valid pattern recognition and maintain analytical integrity.\u003c/p\u003e\n\u003cp\u003eAs an observational study, causal inferences between gut microbiota and recurrent UTIs could not be established. Nonetheless, the internal validity of observed associations was strengthened through confounder control and a clearly defined analytic approach. The possibility that some participants had received antibiotics before urine sampling posed a risk of altering urinary bacterial pathogen profiles, but this was mitigated by documenting antibiotic use and sample timing. Additionally, while HIV-related immune alterations could have influenced microbiome composition in unmeasured ways, limiting generalizability, the inclusion of only women living with HIV and diagnosed with UTI minimised inter-group variability, reinforcing internal validity within the study population.\u003c/p\u003e"},{"header":"Conclusions and Recommendations.","content":"\u003cp\u003eIn this study, \u003cem\u003eEscherichia coli\u003c/em\u003e was the most commonly isolated uropathogen among women living with HIV (WLHIV), followed by \u003cem\u003eCitrobacter\u003c/em\u003e spp. and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e. The antimicrobial susceptibility profile of \u003cem\u003eE. coli\u003c/em\u003e isolates in this study highlights high resistance to multiple readily available agents such as Ampicillin, SXT, and Nalidixic acid, while Gentamicin, imipenem, and nitrofurantoin retained full activity and remain reliable choices for treating UTIs in this population. The low prevalence of ESBL-producing \u003cem\u003eE. coli\u003c/em\u003e (10%) is encouraging; however, it does not preclude the need for vigilance, especially given the potential for the rapid dissemination of ESBL genes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecent antibiotic use was the only factor significantly associated with UTI among women living with HIV, underscoring the importance of cautious antibiotic prescription. Whereas we noted subtle shifts in the gut microbiome of individuals with recurrent UTIs, they were consistent, particularly with respect to microbial richness, genus-level composition, and network structure. While global taxonomic composition remains broadly stable, the enrichment of \u003cem\u003eWeissella\u003c/em\u003e, loss of Butyrate/Short Chain Fatty Acid producers, and emergence of denser microbial hubs may reflect ecological disruptions (gut dysbiosis) that predispose individuals to infection recurrence. These results pave the way for future mechanistic studies incorporating longitudinal designs, functional metagenomics, and host immunophenotyping to clarify causal pathways and develop microbiome-based diagnostics or interventions.\u003c/p\u003e\n\u003cp\u003eFor WLHIV presenting with UTI symptoms, routine urine culture and drug susceptibility testing should be conducted rather than relying solely on empirical treatment, to ensure targeted and effective therapy. Antibiotics such as Ampicillin, Cephalosporins, Trimethoprim-Sulfamethoxazole, and Nalidixic acid should be avoided as first-line agents due to high resistance rates; instead, clinicians should adhere to the Uganda Clinical Guidelines, which recommend Nitrofurantoin as the preferred first-line treatment for uncomplicated UTI, making it a safe empirical option while awaiting culture results. Furthermore, larger longitudinal studies are needed to investigate the causal links between gut microbiome alterations, host immunity, and UTI recurrence among WLHIV.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis study was conducted according to the GCP and GCLP guidelines. Ethical approval was obtained from the Makerere University School of Biomedical Sciences Research and Ethics Committee, proposal number SBS-2024-637, and administrative clearance was obtained from The AIDS Support Organization (TASO REC/ADMC04/2025-UG-REC-009). Female PLHIV aged 18+ years were recruited voluntarily after providing written informed consent to participate in the study. The study presented no more than moderate risks to the participants. Privacy and Confidentiality were ensured by using unique study numbers, and research forms were kept under lock and key, with only the principal investigator having access to them, to date.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials-\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Microbiome data analysis code is available via this link.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualisation: F.M.M, E.K, and M.L. Analysis: G.O, I.S. Data curation: F.M.M, E.K, I.S, G.O and M.L. Investigation: F.M.M, L.K, I.T, A.K, M.Y, A.L, A.R.N, M.L and E.K. Writing-original draft: F.M.M. Writing-review and editing: E.K, M.L, P.K, S.K, H.K and G.O. Visualisation: F.M.M, E.K, I.S and G.O. Supervision: E.K, M.L and M.L.J\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements and funding.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the TASO Uganda management team, the staff and clients of TASO Uganda CoE for all the support rendered to us during this study. This original research article was funded by grants supported by the US National Institutes of Health through the Fogarty International Centre, NIH Award number\u0026nbsp;\u003cstrong\u003eD43TW010319\u003c/strong\u003e. The content is solely the authors\u0026apos; responsibility and does not necessarily represent the official views of the National Institutes of Health.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYang X, Chen H, Zheng Y, Qu S, Wang H, Yi F. Disease burden and long-term trends of urinary tract infections: A worldwide report. Frontiers in public health. 2022;10:888205.\u003c/li\u003e\n\u003cli\u003eKim A, Ahn J, Choi WS, Park HK, Kim S, Paick SH, et al. What is the cause of recurrent urinary tract infection? Contemporary microscopic concepts of pathophysiology. International neurourology journal. 2021;25(3):192.\u003c/li\u003e\n\u003cli\u003eTh\u0026auml;nert R, Reske KA, Hink T, Wallace MA, Wang B, Schwartz DJ, et al. Comparative genomics of antibiotic-resistant uropathogens implicates three routes for recurrence of urinary tract infections. 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JAC-Antimicrobial Resistance. 2025;7(2):dlaf038.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gut microbiome, Gut dysbiosis, Urinary Tract Infections, Human Immunodeficiency Virus, recurrent urinary tract infections, Antimicrobial resistance","lastPublishedDoi":"10.21203/rs.3.rs-7593174/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7593174/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe relationship between the gut microbiome and recurrent urinary tract infections (rUTIs) among women living with HIV (WLHIV) remains underexplored, despite growing evidence that gut dysbiosis may play a critical role in uropathogen colonisation and recurrence of UTIs, let alone treatment outcomes of these patients. Considering the increasing rates of Antimicrobial Resistance (AMR), rUTIs are still on the rise and are a big health burden among WLHIV. Understanding bacterial aetiologies, antimicrobial susceptibility patterns, risk factors for recurrent UTIs among WLHIV, and the role of gut microbiota in uropathogenesis is therefore essential in developing appropriate treatment and prevention guidelines to tackle this public health burden. We conducted a cross-sectional study among WLHIV attending care at an HIV clinic in Uganda. Participants were grouped into two categories: Isolated UTI and Recurrent UTI, based on evidence of UTI episodes within the last 12 months. Voided clean catch midstream urine was collected for culture and sensitivity testing to identify bacterial uropathogens and their antimicrobial resistance profiles. Stool samples were also collected for gut microbiome analysis through 16s rRNA sequencing. Urine culture positivity rate was 19.8%, with \u003cem\u003eEscherichia coli\u003c/em\u003e accounting for over 80% of isolates. E.coli exhibited high resistance to Ampicillin, Trimethoprim-Sulfamethoxazole, 3rd-generation cephalosporins, and Ciprofloxacin but complete Susceptibility to Nitrofurantoin and Imipenem. Prior antibiotic use within the last six months emerged as the most significant clinical factor associated with UTI occurrence (p \u0026lt; 0.001). Gut microbiome analysis showed reduced diversity and altered microbial composition among women with recurrent UTIs compared to those with isolated UTIs, with specific taxa being differentially abundant in the recurrent group.\u003c/p\u003e","manuscriptTitle":"Gut dysbiosis and antimicrobial resistance among women living with HIV, with recurrent urinary tract infections in Uganda: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-12 15:19:31","doi":"10.21203/rs.3.rs-7593174/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-medicine","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsmed","sideBox":"Learn more about [Communications Medicine](http://www.nature.com/commsmed)","snPcode":"43856","submissionUrl":"https://mts-commsmed.nature.com/cgi-bin/main.plex","title":"Communications Medicine","twitterHandle":"@commsmedicine","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"49a778e4-27fa-4993-bf23-37de3323a118","owner":[],"postedDate":"September 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":54581043,"name":"Biological sciences/Microbiology/Microbial communities/Microbiome"},{"id":54581044,"name":"Biological sciences/Microbiology/Clinical microbiology"}],"tags":[],"updatedAt":"2026-03-16T17:41:00+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-12 15:19:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7593174","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7593174","identity":"rs-7593174","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}