Comparative Analysis of Sexually Transmitted Infections among People Living with HIV and Pre- exposure Prophylaxis Users

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Methods: A retrospective analysis was conducted using nucleic acid amplification techniques (NAAT) for Neisseria gonorrhoeae , Chlamydia trachomatis , and Mycoplasma genitalium in rectal, urine, and pharyngeal samples, as well as serological tests for syphilis. The samples were collected and analysed as part of routine clinical care and sent to the microbiology department between Jan 1 2023, and May 31 2023. Multivariable logistic regression was performed to identify factors associated with STI diagnosis; adjusted odds ratios (aOR) and 95% confidence intervals (CI) were reported. Results: A total of 459 samples from 450 participants (277 PWH and 173 on PrEP) were included in the analysis. Overall, 144 (32%) participants tested positive for at least one STI. PrEP users had a lower median age (35 vs. 42 years; p < 0.01), were more frequently born in Spain (77.5% vs. 57.6%; p < 0.01), had a higher level of education (university 62.4% vs. 48.4%; p < 0.01), and had a higher prevalence of chemsex use (18.4% vs. 12.9%; p < 0.01). The prevalence of STIs was significantly higher among the PrEP users (38.2% vs. 28.2%; p =0.027). However, this difference was insignificant after multivariable adjustment (aOR 1.09, 95% CI 0.6–1.7). Neisseria gonorrhoeae was the most common pathogen among PrEP users, while Chlamydia trachomatis and Mycoplasma genitalium were more frequent in PWH. Independent factors associated with STI diagnosis included chemsex use (aOR 1.9, 95% CI 1.1–3.3) and higher educational level (aOR 2.4, 95% CI 1.7–3.4). Conclusion: STIs were commonly diagnosed among PWH and PrEP users, particularly in individuals engaging in chemsex . The different bacterial profiles of STI between PWH and PrEP users underline the importance of continuous STI surveillance. Background Pre-exposure Prophylaxis (PrEP) has proven to be an effective strategy for preventing human immunodeficiency virus (HIV) infection in high-risk individuals (1-3). Extensive scientific evidence indicates that implementation of this strategy yields a risk reduction of nearly 90% when adherence is optimal. PrEP as part of combination prevention strategies has contributed to a gradual decrease in HIV incidence in recent years, where these strategies are widely available (3-7). In contrast to the decrease in the incidence of new HIV infections after PrEP use, diagnoses of sexually transmitted infections (STI) have experienced an upward trajectory over the past two decades, predominantly due to bacterial aetiology. Notably, the incidence of syphilis, gonorrhoea, and chlamydiahas escalated, with more than 80% of cases manifesting in young males, specifically among men who have sex with men (MSM) (8-10). In clinical trials and observational studies, including mainly MSM subjects, a notable proportion of PrEP users were diagnosed with one or more STI (11-14). Uncertainties persist regarding whether the utilisation of PrEP is directly linked to an elevated incidence of STI (15-18, 23-24). Several behavioural and testing policy strategies can influence the data. HIV and STI acquisition have the same risk factors, which are the conditions required to prescribe PrEP. Moreover, some studies have documented a significant decline in condom use among PrEP users (19). Finally, most PrEP programs incorporate systematic testing for STI that also detect asymptomatic infections (20,21). Furthermore, recent publications show that among PrEP users, there are different risk profiles for acquiring STI, being more frequent in subgroups with high-risk behaviours, such as younger age, a higher number of sexual partners, unprotected anal intercourse, and the use of chemsex stand out (19, 25). While many studies have explored STI trends among PrEP users, people living with HIV (PWH) also represent a population with ongoing risk of STI acquisition, especially among men who have sex with men (MSM), due to overlapping behavioural and biological factors (26). Although antiretroviral treatment suppresses HIV replication, it does not mitigate the risk of other STIs, and PWH often undergo less systematic STI screening compared to PrEP users. Given that both groups share several behavioural risk factors (such as condomless sex or chemsex ), and are followed in similar clinical settings, a comparative analysis of STI prevalence and patterns may reveal important differences that could inform tailored prevention strategies. However, to our knowledge, no previous study has addressed the differences in the frequency and type of STI among PrEP users and people with HIV (PWH). Therefore, this study aimed to compare the frequency and characteristics of STI between PWH and PrEP users. Methods Design and population We designed a retrospective observational study involving all individuals in the PrEP program at the internal medicine clinic (regular visits every 3 months) and PWH (regular visits every 6 months) who were tested for STI at the microbiology department between Jan 1and May 31 2023, regardless of the presence or absence of symptoms. This analysis incorporated data from both regular visits and unexpected events (such as symptomatic STI or recent sexual partners with STI). Screening for sexually transmitted infections was conducted, encompassing serological assessments for syphilis as well as nucleic acid amplification testing (NAAT) targeting sexually transmitted bacteria. According to national guidelines, prep users were seen every 3 months and PWH every 6 months (20). HIV and syphilis serology was performed every 3 months in Prep users and syphilis serology every 6 months in PWH. NAAT for sexually transmitted bacteria was performed every 6 months in Prep users. PWH are tested for STI only if symptomatic, but during the study, most PWH (59.2%) were screened with NAAT every 6 months. The study included first-void urine (FVU), rectal, and pharyngeal swabs to detect Neisseria gonorrhoeae , Chlamydia trachomatis , and Mycoplasma genitalium, among others, using the Allplex™ 7 STI Essential Assay (Seegene ® , Seoul, South Korea). Targets amplified with a cycle threshold (Ct) value £ 40 were classified as positive. C. trachomatis. Lymphogranuloma venereum serotype (LGV, only on rectal samples) was detected using Allplex™ Genital Ulcer Assay (Seegene ® ). Serological IgG testing for syphilis and HIV screening was performed by Atellica (Atellica TM , Siemens Healthcare Diagnostics ® , Germany) For each clinical episode, defined as a positive result for any microorganism in the aforementioned tests, the following details were documented: the anatomical location of the isolate (rectum, pharynx, FVU), the presence or absence of associated symptoms, and macrolide resistance in cases of M. genitalium using Allplex™ MG & AziR assay (Seegene®). N. gonorrhoeae isolated in culture on pharyngeal or rectal swabs, and resistance to quinolones, tetracycline, and cephalosporins by gradient diffusion using MIC Test Strip TM (Liofilchem ® , Roseto degli Abruzzi, Italy). Furthermore, each episode was explicitly designated as concurrent or non-concurrent with the diagnosis of any other STI. Outcomes The primary objective of this study was to compare the prevalence of STIs between people with HIV and pre-exposure prophylaxis users. In addition, as secondary objectives, we aimed to describe STIs' clinical characteristics and anatomical distribution, identify differences in the etiological agents involved, and assess the presence of co-infections and antimicrobial resistance. We also explored associations between STI episodes and behavioural factors, including alcohol use (defined as > 3 standard drinks per day or > 80 g on weekends), tobacco consumption (current smoker), and c hemsex (defined as the use of psychoactive substances such as GHB/GBL, mephedrone, or methamphetamine in a sexual context, based on patient self-report during clinical interviews). Data were extracted from the Hospital La Paz cohort of PWH and PrEP users, and the local ethics committee approved the study (CEIm Hospital Universitario La Paz, 2023.865). Due to the study's retrospective design, a waiver for written informed consent was obtained. The study was performed under Good Clinical Practices and the Declaration of Helsinki. Confidentiality was preserved according to institutional and data protection regulations. Statistical analysis Descriptive features of the patient population are reported as absolute numbers and percentages or as medians and interquartile ranges. Baseline characteristics were compared between PrEP users and PWH using the χ2 test, Fisher's exact test for categorical variables, and the Mann–Whitney test for continuous variables. Differences were considered statistically significant at p < 0.05. Univariable logistic regression analyses were performed to identify factors associated with STI diagnosis. Variables with a p-value < 0.10 in the univariable analysis and clinically relevant factors based on previous literature were included in the multivariable logistic regression model. The final model included age, country of origin (Spanish vs. non-Spanish), education level (university vs. non-university), and chemsex use. Adjusted odds ratios (ORs) with 95% confidence intervals (CI) were calculated. Statistical significance was set at p < 0.05. Analyses were performed using the SPSS software package (version 25.0, Chicago, IL, USA). Results Baseline characteristics The analysis included 459 episodes in 450 participants undergoing regular follow-up at our clinic during the study period, with 277 being PWH and 173 on PrEP. The baseline characteristics of PrEP users and PWH participants are summarised in Table 1. PrEP users were younger (35 vs . 42 years; p < 0.01), more frequently of Spanish origin (77.5% vs . 57.6%; p < 0.01), had a higher level of education (university 62.4% vs . 48.4%; p < 0.01), and a higher prevalence of chemsex use (18.4% vs. 12.9%; p < 0.01). Most patients in both groups (98.8% and 98.2%) were cis-men, and there were two transgender women among the PrEP users and five among the PWH. Most PWH had an undetectable viral load and a CD4+ T cell count above 500 cells/mm 3 . Sexually transmitted infections analysis Overall, 144 individuals (32%) were diagnosed with at least one STI, and 69 (47.9%) had symptoms. The frequency of STIs differed significantly between the PrEP and PWH participants, with rates of 38.2% and 28.2%, respectively ( p =0.027). There was no difference in the proportion of overall symptomatic STIs between PWH and PrEP users (55.1% vs. 39.4%, p =0.08). A total of 196 samples yielded positive results: 103 in PWH (52.5%) and 93 in PrEP users (47.5%). PWH exhibited more symptomatic episodes caused by C. trachomatis (65% vs . 28%, p =0.026), although this was not the case for N. gonorrhoeae (30% vs . 27%, p =0.7) or M. genitalium (41% vs . 29%, p =0.2). Regarding the type of microorganism involved (Table 2), N. gonorrhoeae was more frequently isolated among PrEP users (38 vs . 29 episodes, p < 0.01), whereas C. trachomatis , M. genitalium, and Treponema pallidum were more prevalent in PWH. These differences were not statistically significant (20 vs . 17 episodes, p =0.7; 27 vs . 17 episodes, p =0.29; and 16 vs . 8 episodes, p =0.17). N. gonorrhoeae was isolated by NAAT in 80 episodes (40.81%): 41 rectal, 30 pharyngeal swabs, and 9 FVU; in 12 episodes, it was isolated in more than one location simultaneously. Among these, 28 (35%) were cultured, with growth observed in eight (28.5%). Seven strains were resistant to quinolones (87.5%). No resistance to macrolides or cephalosporins was observed. One isolate was resistant to tetracycline. C. trachomatis was detected in 44 episodes (22.4%) by NAAT: 31 rectal samples (11 LGV), 7 FVU, and 6 pharyngeal swabs; in 5 episodes, it was isolated in multiple locations simultaneously. No difference was observed between PWH and PrEPin C. trachomatis LGV. Finally, M. genitalium was detected in 48 cases (24.5%): 25 in FVU and 23 in rectal swabs in four cases with more than one simultaneous location. Resistance to macrolides was detected in 27 (61.4%) samples. Macrolide resistance mutations are shown in Table 3. In the univariable analysis, STI diagnosis was significantly associated with younger age, Spanish origin, chemsex use, and having a university-level education (Table 4). In the multivariable logistic regression model, chemsex use (aOR 1.9, 95% CI 1.1–3.3) and higher education level (aOR 2.4, 95% CI 1.7–3.4) remained independently associated with an increased likelihood of having an STI. Use of PrEP was not independently associated with STI diagnosis (aOR 1.09, 95% CI 0.6–1.7; p = 0.7). Discussion The findings of our study revealed that STI diagnoses were more prevalent in PrEP users than in PWH. However, after multivariable adjustment for age, origin, chem sex , and education level, the use of PrEP was not significantly associated with an STI episode. To our knowledge, this is the first study to directly compare the STI frequency and characteristics in a cohort of PWH and PrEP users under clinical care in the same healthcare facility. We found that the frequency of bacterial STI was 28.2% in PWH and 38.2% in PrEP users. These numbers are consistent with those reported in recent studies. A meta-analysis by Ebrahimi et al. (26) showed that the prevalence of STI among PWH was 30.23% (95% CI, 26.1-34.4%). A Spanish study found a two-year stable 31-35% rate of STI among PrEP users (27). While the difference in STI between Prep users and PWH was statistically significant in the crude analysis, it did not persist after adjusting for behavioural and demographic factors. This suggests that the observed difference may be explained by underlying risk profiles rather than by using PrEP. Similar trends have been reported in other cohorts, where PrEP users often exhibit higher-risk sexual behaviours such as chemsex or a higher number of sexual partners (16, 21, 24). Different studies carried out in our same setting have demonstrated that chemsex use is an apparent risk factor for STI (28). A more frequent STI screening in the PreP group could also explain this result. Therefore, comparisons between these groups must be interpreted cautiously, especially when screening frequency differences exist. Apart from this, the 10% absolute increase in STI frequency between groups could not be clinically relevant enough to justify major policy changes. We found that Neisseria gonorrhoeae was the most frequently diagnosed STI among PrEP users, consistent with findings from some national studies (29), but differing from other cohorts such as SwissPrEPared, where Chlamydia trachomatis was more prevalent (16). Several factors may explain this discrepancy. Firstly, N. gonorrhoeae has a high rate of asymptomatic infection, particularly in the pharynx and rectum, which may lead to frequent detection in settings with systematic screening protocols. Secondly, variations in local epidemiology, sexual practices, and antimicrobial resistance patterns can influence the relative distribution of pathogens across populations (10, 21). Additionally, gonorrhoea may be more easily transmitted than chlamydia in some contexts, particularly through oral sex, which is less commonly protected by condom use. These nuances highlight the importance of local STI surveillance in informing targeted prevention strategies. A recent Dutch study, the AMPrEP project, demonstrated that the highest incidence of STI is concentrated in a subgroup of PrEP users characterised by younger age, higher condomless anal sex, and those involved in c hemsex use (22). In our multivariable analysis, chemsex use and higher educational level were independently associated with an increased likelihood of STI diagnosis. The association between chemsex and STI acquisition has been consistently documented (16, 21, 24), as the practice often involves prolonged sexual sessions, multiple partners, and reduced condom use. Interestingly, a higher level of education has also emerged as a risk factor, possibly reflecting greater access to PrEP and sexual health services, more frequent testing, or higher engagement in sexual networking environments (e.g., dating apps or saunas). This finding challenges traditional assumptions that lower education correlates with poorer health outcomes and highlights the complexity of behavioural risk patterns in MSM populations. It also underscores the need for nuanced prevention strategies beyond traditional demographic predictors. The association between higher educational level and STI diagnosis may seem counterintuitive, as education is generally linked to healthier behaviours. However, it is possible that individuals with higher education have greater access to information, healthcare resources, and preventive tools such as PrEP. In our context, access to PrEP and engagement with sexual health services may be more common among individuals with university-level education. Furthermore, this population may be more likely to participate in routine screening, thereby increasing the probability of STI detection. PWH had a significantly higher proportion of symptomatic C. trachomatis infections than PrEP users. The diagnostic approach may partially explain this difference: while PrEP users undergo systematic screening every six months, regardless of symptoms, STI testing in PWH is often symptom-driven unless they are part of a structured screening program. Nevertheless, a substantial proportion of PWH subjects included in this study (59.2%) were part of a specific program of systematic STI screening every 6 months. As a result, asymptomatic infections in PWH may be underdiagnosed, and detected cases may overrepresent symptomatic episodes. This distinction highlights a critical methodological consideration when comparing symptomatology between groups and suggests that differences in clinical presentation might reflect screening strategies rather than biological differences in disease expression. This study has several limitations. First, its retrospective design precludes causality and does not allow for intra-individual comparisons before and after PrEP initiation. Second, the difference in screening frequency between groups may have led to differential detection of asymptomatic infections. Third, we did not collect data on key behavioural variables such as condom use, number of sexual partners, or specific sexual practices, which may have influenced STI risk. Additionally, the short study period did not help assess possible seasonal variations in STI prevalence. Finally, the study population was composed predominantly of MSM attending a single urban clinic, limiting the generalizability of our findings to other settings or populations. Conclusion The diagnosis of STIs was common in PrEP users and young MSM living with HIV, with notably higher prevalence among individuals engaging in chemsex and those with higher educational levels. Our findings reveal distinct STI profiles between these two populations, highlighting the need for tailored prevention strategies and ongoing epidemiological surveillance. ABREVIATIONS HIV, human immunodeficiency virus; PWH, people with HIV; PrEP, pre-exposure prophylaxis; STI, sexually transmitted infections; MSM, men who have sex with men; NAAT, nucleic acid amplification techniques; IQR, interquartile range. Declarations Clinical trial number: not applicable Ethics approval and consent to participate The local ethics committee approved the study (CEIm Hospital Universitario La Paz. 2023.865). Due to the study's retrospective design, a waiver for written informed consent was obtained. Consent for publication: Not applicable Availability of data and material The data supporting this study's findings are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. Competing interests MAR received personal fees for lectures and travel grants from Gilead and Janssen. LRR has received personal fees for lectures and travel grants from Gilead, MSD and Janssen. CB has received personal fees for lectures and travel grants from Gilead, MSD, Janssen, and VIIV. AdGG receives personal fees for travel grants from Gilead. FFH receives personal fees for travel grants from Gilead. RM has received personal fees for lectures and travel grants from Gilead, MSD, Janssen, and VIIV. LMC received personal fees for lectures and advisory boards from Gilead, MSD, Janssen, and VIIV. JIB received personal fees for lectures from Gilead, MSD, Janssen, and VIIV. ADH, IQM, and AMB declare no conflict of interest. Funding: Not applicable Author’s contributions: MAR, LRR, and JIB conceptualised and designed the study. MAR, LRR, CB, AdGG, FFH, ADH, IQM, AMB, RM and LMC were involved in data acquisition, analysis, and interpretation. MAR: drafted the manuscript. All authors critically revised the manuscript. Acknowledgements We would like to thank all the participants and members of the HIV clinic and the microbiology department. References Grant RM, Lama JR, Anderson PL, et al. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363(27):2587-2599. McCormack S, Dunn DT, Desai M, Dolling DI, Gafos M, Gilson R, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): Effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2016;387(10013):53–60. 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Ebrahimi M, Mehdizad N, Yeganeh-Sefidan F, Safarpour H, Pagheh AS, Pouremamali A, Shiralizadeh S, Ghodrati A, Jafari S, Shahrivar F, Heidarzadeh S, Montazeri M, Yousef-Memar M, Rodrigues-Oliveira SM, de-Lourdes-Pereira M, Beloukas A, Hatam-Nahavandi K, Barac A, Shirvaliloo M, Ahmadpour E. Systematic review and meta-analysis of the global prevalence of sexually transmitted infections in people living with HIV and associated risk factors. AIDS Rev. 2023;26(3):105-126. doi: 10.24875/AIDSRev.23000008. Ugarte A, de la Mora L, García D, Martínez-Rebollar M, de Lazzari E, Torres B, Inciarte A, Ambrosioni J, Chivite I, Solbes E, de Loredo N, Del Carlo GF, González-Cordón A, Blanco JL, Martínez E, Mallolas J, Laguno M. Evolution of Risk Behaviors, Sexually Transmitted Infections and PrEP Care Continuum in a Hospital-Based PrEP Program in Barcelona, Spain: A Descriptive Study of the First 2 Years' Experience. Infect Dis Ther. 2023 Feb;12(2):425-442. doi: 10.1007/s40121-022-00733-6. Epub 2022 Dec 15. Ryan P, Dolengevich-Segal H, Ramos-Ruperto L, Cabello A, Sanchez-Conde M, Vergas J, Valencia J, Cuevas G, Sanz J, Curto-Ramos J, Pérez-Bootello J, Naharro-Rodriguez J, Ollero MJF, Garcia Fraile L, Pérez-Latorre L, Bisbal O, De la Fuente S, Losa JE, Cervero M, Estebanez M, Suarez-Garcia I, Gimeno A, Terrancle I, Mican R, González-Baeza A; U-Sex Gesida 9416 Study. Patterns of Sexualised Drug Use among Gay, Bisexual, and Other Men Who Have Sex with Men Living with HIV: Insights from a Comprehensive Study-The U-SEX-2 GESIDA 9416 Study. J Clin Med. 2023 Nov 24;12(23):7293. doi: 10.3390/jcm12237293. PMID: 38068345; PMCID: PMC10707460. HernandoV, IniestaC, del AmoJ, DíazA, JarrinI and SIPrEP group. Incidencia de ITS en usuarios de PrEP. Datos del sistema de información de programas de profilaxis pre-exposición (SIPrEP) al VIH en España. Congreso Gesida A Coruña del 26 al 29 de noviembre de 2023. Abstract CO-10. Tables Table 1. Baseline demographic and clinical characteristics. PWH (n=277) PrEP (n=173) p Age, median (IQR) 42 (35-52) 35 (30-40) <0.0001 Gender (cis male) n(%) 273 (98.2) 171(98.8) Origin (Spanish born) n(%) 160(57.6) 134 (77.5) <0.0001 Education level n(%) <0.0001 Primary 49 (17.6) 28 (16.2) Secondary 87 (31.4) 22 (12.7) University 134 (48.4) 108 (62.4) Unkown 7 (2.6) 15 (8.7) Alcohol n(%) 112(42.4) 83(48.8) Current smoking n(%) 102(38.2) 45(26.3) 0.01 Chemsex use n(%) 34(12.9) 26.9(18.4) <0.0001 STI episodes n(%) 78 (28.2) 66 (38.2) 0.027 Symptomatic STI n(%) 43 (55.1) 26 (39.4) 0.08 PWH variables HIV-RNA (<50cp/mL) n(%) 255 (92%) T-CD4+ cell count (cells/mm 3 ) n(%) 694 (549-874) PrEP modality Daily n(%) 140 (80) On demand n(%) 33 (20) Table 2. Descriptive analysis. PWH (n=103) PrEP (n=93) p Chlamydia trachomatis n, (%) 23 (22.3) 21 (22.5) 0.7 Pharyngeal n 4 2 0.6 Urine n 2 5 0.08 Rectal n 17 14 0.09 Symptomatic n, (%) 15 (65.2) 6 (65.2) 0.026 Lymphogranuloma venereum (rectal samples s creening) n 8 3 0.1 Neisseria gonorrhoeae n, (%) 33 (32) 47 (50.5) 0.006 Pharyngeal n 12 18 0.1 Urine n 3 6 0.1 Rectal n 18 23 0.3 Symptomatic n, (%) 10 (30.3) 13 (27.6) 0.7 Culture collected n 13 15 0.8 Culture growth n 4 4 0.7 Mycoplasma genitalium n, (%) 31 (30) 17 (18.3) 0.29 Urine n 13 12 0.38 Rectal n 18 5 0.019 Symptomatic n 13 5 0.2 Macrolid resistance n 17 10 0.7 Treponema pallidum n, (%) 16 (15.5) 8 (8.6) 0.17 First episode n 3 4 0.11 Table 3. Macrolides resistance mutations Mutations N = 27 A2058T 7 A2058G 3 A2059G 10 Inhibid NAAT 1 No data 6 Table 4. Univariable and multivariable logistic regression analyses of factors associate with STI diagnosis OR (95% CI) Univariable p-value Univariable aOR (95% CI) Multivariable p-value Multivariable PrEP use 1.6 (1.1–2.4) 0.027 1.09 (0.6–1.7) 0.7 Chemsex 2.5 (1.6–3.9) <0.001 1.9 (1.1–3.3) 0.024 Higher education 2.8 (1.9–4.1) <0.001 2.4 (1.7–3.4) <0.001 Spanish origin 1.3 (0.9–2.0) 0.12 — — Age (younger) 1.4 (0.9–2.2) 0.11 — — Additional Declarations No competing interests reported. Supplementary Files STROBEChecklist.docx Cite Share Download PDF Status: Published Journal Publication published 23 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 23 Oct, 2025 Reviews received at journal 22 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers invited by journal 02 Oct, 2025 Editor assigned by journal 15 Sep, 2025 Submission checks completed at journal 15 May, 2025 First submitted to journal 14 May, 2025 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. We do this by developing innovative software and high quality services for the global research community. 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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-5085129","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":533839920,"identity":"72095e74-ed7c-4913-951b-fef8846746c1","order_by":0,"name":"María del Mar Arcos-Rueda","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAoklEQVRIiWNgGAWjYPACGxk2UrWk8ZCs5TAP8Wp1288+YPi55zwPn0TyAYYfFdsIazE7k27A2PPsNg+bRFoCY8+Z20RoOZDGwMBzAKiF54wBM2MbMVrOP2Ng/HPgHFDL+Q9EarmRxsDMc+AADxt7DwOxWp4xHJY5kAzU0mZwkDi/nE9jfPjmgJ2cfDPzwwc/KojQAgIHMBijYBSMglEwCigEAK/aNZcrVjbgAAAAAElFTkSuQmCC","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":true,"prefix":"","firstName":"María","middleName":"del Mar","lastName":"Arcos-Rueda","suffix":""},{"id":533839923,"identity":"cd0ad4fc-c693-49dd-be5c-4cd6c8dbb0b6","order_by":1,"name":"Luis Ramos-Ruperto","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"","lastName":"Ramos-Ruperto","suffix":""},{"id":533839925,"identity":"fd992305-acb0-44fb-bcff-05a48972eee9","order_by":2,"name":"Carmen Busca","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"","lastName":"Busca","suffix":""},{"id":533839926,"identity":"9b4be4a2-7e6a-435e-bcde-745e1d728914","order_by":3,"name":"Alejandro de Gea Grela","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Alejandro","middleName":"de Gea","lastName":"Grela","suffix":""},{"id":533839930,"identity":"1d234fe5-5b53-4c44-90f9-b9dd792036f3","order_by":4,"name":"Fernando Fernández Hinojal","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"Fernández","lastName":"Hinojal","suffix":""},{"id":533839932,"identity":"e29d2ae4-922e-4c02-8352-5ea0c118170a","order_by":5,"name":"Ana Delgado Hierro","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Delgado","lastName":"Hierro","suffix":""},{"id":533839933,"identity":"f468616e-44f1-4dd7-8656-2e3745df9edd","order_by":6,"name":"Imnaculada Quiles-Melero","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Imnaculada","middleName":"","lastName":"Quiles-Melero","suffix":""},{"id":533839934,"identity":"30fa3696-91b8-4b5f-ab3d-d143066639d0","order_by":7,"name":"Alfredo Maldonado-Barrueco","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Alfredo","middleName":"","lastName":"Maldonado-Barrueco","suffix":""},{"id":533839935,"identity":"f996777e-a35e-43c2-bb80-0a29875ef17c","order_by":8,"name":"Rafael Mican","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"","lastName":"Mican","suffix":""},{"id":533839936,"identity":"a9da4887-8690-4e24-93cb-20251ce03cba","order_by":9,"name":"Luz Martin-Carbonero","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Luz","middleName":"","lastName":"Martin-Carbonero","suffix":""},{"id":533839937,"identity":"5488dd47-0c7b-4ab9-bc04-d3ac50aefe8c","order_by":10,"name":"Jose Ignacio Bernardino","email":"","orcid":"","institution":"Hospital Universitario La Paz-Carlos III, IdiPAZ","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"Ignacio","lastName":"Bernardino","suffix":""}],"badges":[],"createdAt":"2024-09-13 16:23:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5085129/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5085129/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-025-12395-z","type":"published","date":"2025-12-23T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99172218,"identity":"995d1374-182f-48b4-8412-e699a344ce55","added_by":"auto","created_at":"2025-12-29 16:02:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":780710,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5085129/v1/59a3e8f1-5f5e-4975-9124-a06769ae8be2.pdf"},{"id":94950051,"identity":"60d57ee0-b6b4-4470-b9ab-d0de2163d1f0","added_by":"auto","created_at":"2025-11-02 11:46:19","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29924,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEChecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-5085129/v1/6157dccb9f55e2c414aa2b55.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of Sexually Transmitted Infections among People Living with HIV and Pre- exposure Prophylaxis Users","fulltext":[{"header":"Background","content":"\u003cp\u003ePre-exposure Prophylaxis (PrEP) has proven to be an effective strategy for preventing human immunodeficiency virus (HIV) infection in high-risk individuals (1-3). Extensive scientific evidence indicates that implementation of this strategy yields a risk reduction of nearly 90% when adherence is optimal. PrEP as part of combination prevention strategies has contributed to a gradual decrease in HIV incidence in recent years, where these strategies are widely available (3-7).\u003c/p\u003e\n\u003cp\u003eIn contrast to the decrease in the incidence of new HIV infections after PrEP use, diagnoses of sexually transmitted infections (STI) have experienced an upward trajectory over the past two decades, predominantly due to bacterial aetiology. Notably, the incidence of syphilis, gonorrhoea, and chlamydiahas escalated, with more than 80% of cases manifesting in young males, specifically among men who have sex with men (MSM) (8-10).\u003c/p\u003e\n\u003cp\u003eIn clinical trials and observational studies, including mainly MSM subjects, a notable proportion of PrEP users were diagnosed with one or more STI (11-14). Uncertainties persist regarding whether the utilisation of PrEP is directly linked to an elevated incidence of STI (15-18, 23-24). Several behavioural and testing policy strategies can influence the data. HIV and STI acquisition have the same risk factors, which are the conditions required to prescribe PrEP. Moreover, some studies have documented a significant decline in condom use among PrEP users (19). Finally, most PrEP programs incorporate systematic testing for STI that also detect asymptomatic infections (20,21).\u003c/p\u003e\n\u003cp\u003eFurthermore, recent publications show that among PrEP users, there are different risk profiles for acquiring STI, being more frequent in subgroups with high-risk behaviours, such as younger age, a higher number of sexual partners, unprotected anal intercourse, and the use of\u0026nbsp;\u003cem\u003echemsex\u003c/em\u003e stand out (19, 25).\u003c/p\u003e\n\u003cp\u003eWhile many studies have explored STI trends among PrEP users, people living with HIV (PWH) also represent a population with ongoing risk of STI acquisition, especially among men who have sex with men (MSM), due to overlapping behavioural and biological factors (26). Although antiretroviral treatment suppresses HIV replication, it does not mitigate the risk of other STIs, and PWH often undergo less systematic STI screening compared to PrEP users. Given that both groups share several behavioural risk factors (such as condomless sex or \u003cem\u003echemsex\u003c/em\u003e), and are followed in similar clinical settings, a comparative analysis of STI prevalence and patterns may reveal important differences that could inform tailored prevention strategies.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;However, to our knowledge, no previous study has addressed the differences in the frequency and type of STI among PrEP users and people with HIV (PWH).\u003c/p\u003e\n\u003cp\u003eTherefore, this study aimed to compare the frequency and characteristics of STI between PWH and PrEP users.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eDesign and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe designed a retrospective observational study involving all individuals in the PrEP program at the internal medicine clinic (regular visits every 3 months) and PWH (regular visits every 6 months) who were tested for STI at the microbiology department between Jan 1and May 31 2023, regardless of the presence or absence of symptoms. This analysis incorporated data from both regular visits and unexpected events (such as symptomatic STI or recent sexual partners with STI).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eScreening for sexually transmitted infections was conducted, encompassing serological assessments for syphilis as well as nucleic acid amplification testing (NAAT) targeting sexually transmitted bacteria. According to national guidelines, prep users were seen every 3 months and PWH every 6 months (20). HIV and syphilis serology was performed every 3 months in Prep users and syphilis serology every 6 months in PWH. NAAT for sexually transmitted bacteria was performed every 6 months in Prep users. PWH are tested for STI only if symptomatic, but during the study, most PWH (59.2%) were screened with NAAT every 6 months. The study included first-void urine (FVU), rectal, and pharyngeal swabs to detect \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e, \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, and \u003cem\u003eMycoplasma genitalium,\u0026nbsp;\u003c/em\u003eamong others, using the Allplex\u0026trade; 7 STI Essential Assay (Seegene\u003csup\u003e\u0026reg;\u003c/sup\u003e, Seoul, South Korea). Targets amplified with a cycle threshold (Ct) value \u0026pound; 40 were classified as positive. \u003cem\u003eC. trachomatis.\u0026nbsp;\u003c/em\u003eLymphogranuloma venereum serotype (LGV, only on rectal samples) was detected using Allplex\u0026trade; Genital Ulcer Assay (Seegene\u003csup\u003e\u0026reg;\u003c/sup\u003e). Serological IgG testing for syphilis and HIV screening was performed by Atellica (Atellica\u003csup\u003eTM\u003c/sup\u003e, Siemens Healthcare Diagnostics\u003csup\u003e\u0026reg;\u003c/sup\u003e, Germany)\u003c/p\u003e\n\u003cp\u003eFor each clinical episode, defined as a positive result for any microorganism in the aforementioned tests, the following details were documented: the anatomical location of the isolate (rectum, pharynx, FVU), the presence or absence of associated symptoms, and macrolide resistance in cases of \u003cem\u003eM. genitalium\u003c/em\u003e using Allplex\u0026trade; MG \u0026amp; AziR assay (Seegene\u0026reg;). \u003cem\u003eN. gonorrhoeae\u0026nbsp;\u003c/em\u003eisolated in culture on pharyngeal or rectal swabs, and resistance to quinolones, tetracycline, and cephalosporins by gradient diffusion using MIC Test Strip\u003csup\u003eTM\u003c/sup\u003e (Liofilchem\u003csup\u003e\u0026reg;\u003c/sup\u003e, Roseto degli Abruzzi, Italy). Furthermore, each episode was explicitly designated as concurrent or non-concurrent with the diagnosis of any other STI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary objective of this study was to compare the prevalence of STIs between people with HIV and pre-exposure prophylaxis users. In addition, as secondary objectives, we aimed to describe STIs\u0026apos; clinical characteristics and anatomical distribution, identify differences in the etiological agents involved, and assess the presence of co-infections and antimicrobial resistance. We also explored associations between STI episodes and behavioural factors, including alcohol use (defined as \u0026gt; 3 standard drinks per day or \u0026gt; 80 g on weekends), tobacco consumption (current smoker), and c\u003cem\u003ehemsex\u003c/em\u003e (defined as the use of psychoactive substances such as GHB/GBL, mephedrone, or methamphetamine in a sexual context, based on patient self-report during clinical interviews).\u003c/p\u003e\n\u003cp\u003eData were extracted from the Hospital La Paz cohort of PWH and PrEP users, and the local ethics committee approved the study (CEIm Hospital Universitario La Paz, 2023.865). Due to the study\u0026apos;s retrospective design, a waiver for written informed consent was obtained. The study was performed under Good Clinical Practices and the Declaration of Helsinki. Confidentiality was preserved according to institutional and data protection regulations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive features of the patient population are reported as absolute numbers and percentages or as medians and interquartile ranges. Baseline characteristics were compared between PrEP users and PWH using the \u0026chi;2 test, Fisher\u0026apos;s exact test for categorical variables, and the Mann\u0026ndash;Whitney test for continuous variables. Differences were considered statistically significant at p \u0026lt; 0.05. Univariable logistic regression analyses were performed to identify factors associated with STI diagnosis. Variables with a p-value \u0026lt; 0.10 in the univariable analysis and clinically relevant factors based on previous literature were included in the multivariable logistic regression model. The final model included age, country of origin (Spanish vs. non-Spanish), education level (university vs. non-university), and \u003cem\u003echemsex\u003c/em\u003e use. Adjusted odds ratios (ORs) with 95% confidence intervals (CI) were calculated. Statistical significance was set at p \u0026lt; 0.05. Analyses were performed using the SPSS software package (version 25.0, Chicago, IL, USA).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis included 459 episodes in 450 participants undergoing regular follow-up at our clinic during the study period, with 277 being PWH and 173 on PrEP.\u003c/p\u003e\n\u003cp\u003eThe baseline characteristics of PrEP users and PWH participants are summarised in Table 1. PrEP users were younger (35\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 42 years;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), more frequently of Spanish origin (77.5%\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 57.6%;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), had a higher level of education (university 62.4%\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 48.4%;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), and a higher prevalence of\u0026nbsp;\u003cem\u003echemsex\u003c/em\u003e use (18.4% vs. 12.9%;\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). Most patients in both groups (98.8% and 98.2%) were cis-men, and there were two transgender women among the PrEP users and five among the PWH. Most PWH had an undetectable viral load and a CD4+ T cell count above 500 cells/mm\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSexually transmitted infections\u003c/strong\u003e \u003cstrong\u003eanalysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 144 individuals (32%) were diagnosed with at least one STI, and 69 (47.9%) had symptoms. The frequency of STIs differed significantly between the PrEP and PWH participants, with rates of 38.2% and 28.2%, respectively (\u003cem\u003ep\u003c/em\u003e=0.027). There was no difference in the proportion of overall symptomatic STIs between PWH and PrEP users (55.1%\u0026nbsp;\u003cem\u003evs.\u003c/em\u003e 39.4%,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.08).\u003c/p\u003e\n\u003cp\u003eA total of 196 samples yielded positive results: 103 in PWH (52.5%) and 93 in PrEP users (47.5%). PWH exhibited more symptomatic episodes caused by \u003cem\u003eC. trachomatis\u003c/em\u003e (65%\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 28%,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.026), although this was not the case for \u003cem\u003eN. gonorrhoeae\u0026nbsp;\u003c/em\u003e(30%\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 27%,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.7) or\u003cem\u003e\u0026nbsp;M. genitalium\u0026nbsp;\u003c/em\u003e(41%\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 29%,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.2).\u003c/p\u003e\n\u003cp\u003eRegarding the type of microorganism involved (Table 2), \u003cem\u003eN. gonorrhoeae\u003c/em\u003e was more frequently isolated among PrEP users (38\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 29 episodes,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), whereas \u003cem\u003eC. trachomatis\u003c/em\u003e, \u003cem\u003eM. genitalium,\u003c/em\u003e and \u003cem\u003eTreponema pallidum\u003c/em\u003e were more prevalent in PWH. These differences were not statistically significant (20\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 17 episodes,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.7; 27\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 17 episodes,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.29; and 16\u0026nbsp;\u003cem\u003evs\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e 8 episodes,\u0026nbsp;\u003cem\u003ep\u003c/em\u003e=0.17).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eN. gonorrhoeae\u003c/em\u003e was isolated by NAAT in 80 episodes (40.81%): 41 rectal, 30 pharyngeal swabs, and 9 FVU; in 12 episodes, it was isolated in more than one location simultaneously. Among these, 28 (35%) were cultured, with growth observed in eight (28.5%). Seven strains were resistant to quinolones (87.5%). No resistance to macrolides or cephalosporins was observed. One isolate was resistant to tetracycline.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eC. trachomatis\u003c/em\u003e was detected in 44 episodes (22.4%) by NAAT: 31 rectal samples (11 LGV), 7 FVU, and 6 pharyngeal swabs; in 5 episodes, it was isolated in multiple locations simultaneously. No difference was observed between PWH and PrEPin\u003cem\u003e\u0026nbsp;C. trachomatis\u003c/em\u003e LGV.\u003c/p\u003e\n\u003cp\u003eFinally, \u003cem\u003eM. genitalium\u003c/em\u003e was detected in 48 cases (24.5%): 25 in FVU and 23 in rectal swabs in four cases with more than one simultaneous location. Resistance to macrolides was detected in 27 (61.4%) samples. Macrolide resistance mutations are shown in Table 3.\u003c/p\u003e\n\u003cp\u003eIn the univariable analysis, STI diagnosis was significantly associated with younger age, Spanish origin, \u003cem\u003echemsex\u003c/em\u003e use, and having a university-level education (Table 4). In the multivariable logistic regression model, \u003cem\u003echemsex\u003c/em\u003e use (aOR 1.9, 95% CI 1.1–3.3) and higher education level (aOR 2.4, 95% CI 1.7–3.4) remained independently associated with an increased likelihood of having an STI. Use of PrEP was not independently associated with STI diagnosis (aOR 1.09, 95% CI 0.6–1.7; p = 0.7).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe findings of our study revealed that STI diagnoses were more prevalent in PrEP users than in PWH. However, after multivariable adjustment for age, origin, \u003cem\u003echem\u003c/em\u003e\u003cem\u003esex\u003c/em\u003e\u003cem\u003e,\u003c/em\u003e and education level, the use of PrEP was not significantly associated with an STI episode.\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first study to directly compare the STI frequency and characteristics in a cohort of PWH and PrEP users under clinical care in the same healthcare facility. We found that the frequency of bacterial STI was 28.2% in PWH and 38.2% in PrEP users. These numbers are consistent with those reported in recent studies. A meta-analysis by Ebrahimi\u0026nbsp;\u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e(26) showed that the prevalence of STI among PWH was 30.23% (95% CI, 26.1-34.4%). A Spanish study found a two-year stable 31-35% rate of STI among PrEP users (27). While the difference in STI between Prep users and PWH was statistically significant in the crude analysis, it did not persist\u0026nbsp;after adjusting for behavioural and demographic factors. This suggests that the observed difference may be explained by underlying risk profiles rather than by using PrEP. Similar trends have been reported in other cohorts, where PrEP users often exhibit higher-risk sexual behaviours such as \u003cem\u003echemsex\u003c/em\u003e or a higher number of sexual partners (16, 21, 24). Different studies carried out in our same setting have demonstrated that \u003cem\u003echemsex\u003c/em\u003e use is an apparent risk factor for STI (28). A more frequent STI screening in the PreP group could also explain this result. Therefore, comparisons between these groups must be interpreted cautiously, especially when screening frequency differences exist. Apart from this, the 10% absolute increase in STI frequency between groups could not be clinically relevant enough to justify major policy changes.\u003c/p\u003e\n\u003cp\u003eWe found that \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e was the most frequently diagnosed STI among PrEP users, consistent with findings from some national studies (29), but differing from other cohorts such as SwissPrEPared, where \u003cem\u003eChlamydia trachomatis\u003c/em\u003e was more prevalent (16). Several factors may explain this discrepancy. Firstly, \u003cem\u003eN. gonorrhoeae\u003c/em\u003e has a high rate of asymptomatic infection, particularly in the pharynx and rectum, which may lead to frequent detection in settings with systematic screening protocols. Secondly, variations in local epidemiology, sexual practices, and antimicrobial resistance patterns can influence the relative distribution of pathogens across populations (10, 21). Additionally, \u003cem\u003egonorrhoea\u003c/em\u003e may be more easily transmitted than chlamydia in some contexts, particularly through oral sex, which is less commonly protected by condom use. These nuances highlight the importance of local STI surveillance in informing targeted prevention strategies. A recent Dutch study, the AMPrEP project, demonstrated that the highest incidence of STI is concentrated in a subgroup of PrEP users characterised by younger age, higher condomless anal sex, and those involved in \u003cem\u003ec\u003c/em\u003e\u003cem\u003ehemsex\u003c/em\u003e use (22). In our multivariable analysis, \u003cem\u003echemsex\u003c/em\u003e use and higher educational level were independently associated with an increased likelihood of STI diagnosis. The association between \u003cem\u003echemsex\u0026nbsp;\u003c/em\u003eand STI acquisition has been consistently documented (16, 21, 24), as the practice often involves prolonged sexual sessions, multiple partners, and reduced condom use. Interestingly, a higher level of education has also emerged as a risk factor, possibly reflecting greater access to PrEP and sexual health services, more frequent testing, or higher engagement in sexual networking environments (e.g., dating apps or saunas). This finding challenges traditional assumptions that lower education correlates with poorer health outcomes and highlights the complexity of behavioural risk patterns in MSM populations. It also underscores the need for nuanced prevention strategies beyond traditional demographic predictors. The association between higher educational level and STI diagnosis may seem counterintuitive, as education is generally linked to healthier behaviours. However, it is possible that individuals with higher education have greater access to information, healthcare resources, and preventive tools such as PrEP. In our context, access to PrEP and engagement with sexual health services may be more common among individuals with university-level education. Furthermore, this population may be more likely to participate in routine screening, thereby increasing the probability of STI detection.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePWH had a significantly higher proportion of symptomatic \u003cem\u003eC. trachomatis\u003c/em\u003e infections than PrEP users. The diagnostic approach may partially explain this difference: while PrEP users undergo systematic screening every six months, regardless of symptoms, STI testing in PWH is often symptom-driven unless they are part of a structured screening program. Nevertheless, a substantial proportion of PWH subjects included in this study (59.2%) were part of a specific program of systematic STI screening every 6 months. As a result, asymptomatic infections in PWH may be underdiagnosed, and detected cases may overrepresent symptomatic episodes. This distinction highlights a critical methodological consideration when comparing symptomatology between groups and suggests that differences in clinical presentation might reflect screening strategies rather than biological differences in disease expression.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, its retrospective design precludes causality and does not allow for intra-individual comparisons before and after PrEP initiation. Second, the difference in screening frequency between groups may have led to differential detection of asymptomatic infections. Third, we did not collect data on key behavioural variables such as condom use, number of sexual partners, or specific sexual practices, which may have influenced STI risk. Additionally, the short study period did not help assess possible seasonal variations in STI prevalence. Finally, the study population was composed predominantly of MSM attending a single urban clinic, limiting the generalizability of our findings to other settings or populations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe diagnosis of STIs was common in PrEP users and young MSM living with HIV, with notably higher prevalence among individuals engaging in \u003cem\u003echemsex\u003c/em\u003e and those with higher educational levels. Our findings reveal distinct STI profiles between these two populations, highlighting the need for tailored prevention strategies and ongoing epidemiological surveillance.\u003c/p\u003e"},{"header":"ABREVIATIONS","content":"\u003cp\u003eHIV, human immunodeficiency virus; PWH, people with HIV; PrEP, pre-exposure prophylaxis; STI, sexually transmitted infections; MSM, men who have sex with men; NAAT, nucleic acid amplification techniques; IQR, interquartile range.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eClinical trial number: not applicable\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe local ethics committee approved the study (CEIm Hospital Universitario La Paz. 2023.865). Due to the study's retrospective design, a waiver for written informed consent was obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study's findings are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMAR received personal fees for lectures and travel grants from Gilead and Janssen. LRR has received personal fees for lectures and travel grants from Gilead, MSD and Janssen. CB has received personal fees for lectures and travel grants from Gilead, MSD, Janssen, and VIIV. AdGG receives personal fees for travel grants from Gilead. FFH receives personal fees for travel grants from Gilead. RM has received personal fees for lectures and travel grants from Gilead, MSD, Janssen, and VIIV. LMC received personal fees for lectures and advisory boards from Gilead, MSD, Janssen, and VIIV. JIB received personal fees for lectures from Gilead, MSD, Janssen, and VIIV. ADH, IQM, and AMB declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor’s contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMAR, LRR, and JIB conceptualised and designed the study. MAR, LRR, CB, AdGG, FFH, ADH, IQM, AMB, RM and LMC were involved in data acquisition, analysis, and interpretation. MAR: drafted the manuscript. All authors critically revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the participants and members of the HIV clinic and the microbiology department.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGrant RM, Lama JR, Anderson PL, et al. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363(27):2587-2599.\u003c/li\u003e\n \u003cli\u003eMcCormack S, Dunn DT, Desai M, Dolling DI, Gafos M, Gilson R, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): Effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2016;387(10013):53\u0026ndash;60.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMolina J-M, Capitant C, Spire B, Pialoux G, Cotte L, Charreau I, et al. 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PMID: 38068345; PMCID: PMC10707460.\u003c/li\u003e\n \u003cli\u003eHernandoV, IniestaC, del AmoJ, D\u0026iacute;azA, JarrinI and SIPrEP group. Incidencia de ITS en usuarios de PrEP. Datos del sistema de informaci\u0026oacute;n de programas de profilaxis pre-exposici\u0026oacute;n (SIPrEP) al VIH en Espa\u0026ntilde;a. Congreso Gesida A Coru\u0026ntilde;a del 26 al 29 de noviembre de 2023. Abstract CO-10.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Baseline demographic and clinical characteristics.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003ePWH (n=277)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003ePrEP (n=173)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;p\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e42 (35-52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e35 (30-40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eGender (cis male) n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e273 (98.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e171(98.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eOrigin (Spanish born) \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e160(57.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e134 (77.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eEducation level \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e49 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e28 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e87 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e22 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e134 (48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e108 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eUnkown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e7 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e15 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eAlcohol \u0026nbsp; n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e112(42.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e83(48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eCurrent smoking \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e102(38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e45(26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003e\u003cem\u003eChemsex\u003c/em\u003e use \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e34(12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e26.9(18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eSTI episodes \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e78 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e66 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eSymptomatic STI n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e43 (55.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e26 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePWH\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003evariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eHIV-RNA (\u0026lt;50cp/mL) \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e255 (92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eT-CD4+ cell count (cells/mm\u003csup\u003e3\u003c/sup\u003e) \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e694 (549-874)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrEP\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;modality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eDaily \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e140 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.7278%;\"\u003e\n \u003cp\u003eOn demand \u0026nbsp;n(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.3611%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.6597%;\"\u003e\n \u003cp\u003e33 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2514%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 2. Descriptive analysis.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003ePWH (n=103)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003ePrEP (n=93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eChlamydia trachomatis\u003c/em\u003e\u003c/strong\u003e n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e23 (22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e21 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003ePharyngeal\u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eUrine \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eRectal \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eSymptomatic \u0026nbsp;n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e15 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e6 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u003cem\u003eLymphogranuloma venereum\u003c/em\u003e\u003cem\u003e\u0026nbsp;(rectal samples s\u003c/em\u003e\u003cem\u003ecreening)\u003c/em\u003e n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeisseria gonorrhoeae\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e33 (32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e47 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003ePharyngeal \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eUrine \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eRectal \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eSymptomatic \u0026nbsp;n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e10 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e13 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eCulture collected \u0026nbsp;n\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eCulture growth n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMycoplasma genitalium\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e31 (30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e17 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eUrine \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eRectal \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eSymptomatic \u0026nbsp;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eMacrolid resistance n\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTreponema pallidum\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e n, (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e16 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e8 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003eFirst episode n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8589%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.2804%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.9295%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.9312%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3.\u0026nbsp;Macrolides resistance mutations\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eMutations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003eN = 27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eA2058T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eA2058G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eA2059G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eInhibid NAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70.9898%;\"\u003e\n \u003cp\u003eNo data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 29.0102%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4. Univariable and multivariable logistic regression analyses of factors associate with STI diagnosis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eOR (95% CI) Univariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003ep-value Univariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eaOR (95% CI) Multivariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003ep-value Multivariable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003ePrEP use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.6 (1.1\u0026ndash;2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.09 (0.6\u0026ndash;1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cem\u003eChemsex\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2.5 (1.6\u0026ndash;3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.9 (1.1\u0026ndash;3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2.8 (1.9\u0026ndash;4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2.4 (1.7\u0026ndash;3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eSpanish origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.3 (0.9\u0026ndash;2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003eAge (younger)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1.4 (0.9\u0026ndash;2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.7699%;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2301%;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5085129/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5085129/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective: This study aimed to compare the frequency and characteristics of sexually transmitted infections (STI) between people with HIV (PWH) and pre-exposure prophylaxis (PrEP) users.\u003c/p\u003e\n\u003cp\u003eMethods: A retrospective analysis was conducted using nucleic acid amplification techniques (NAAT) for \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e, \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, and \u003cem\u003eMycoplasma genitalium in \u003c/em\u003erectal, urine, and pharyngeal samples, as well as serological tests for syphilis. The samples were collected and analysed as part of routine clinical care and sent to the microbiology department between Jan 1 2023, and May 31 2023. Multivariable logistic regression was performed to identify factors associated with STI diagnosis; adjusted odds ratios (aOR) and 95% confidence intervals (CI) were reported.\u003c/p\u003e\n\u003cp\u003eResults: A total of 459 samples from 450 participants (277 PWH and 173 on PrEP) were included in the analysis. Overall, 144 (32%) participants tested positive for at least one STI. PrEP users had a lower median age (35 \u003cem\u003evs.\u003c/em\u003e 42 years; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), were more frequently born in Spain (77.5% \u003cem\u003evs.\u003c/em\u003e 57.6%; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), had a higher level of education (university 62.4% \u003cem\u003evs.\u003c/em\u003e48.4%; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01), and had a higher prevalence of \u003cem\u003echemsex\u003c/em\u003euse (18.4% vs. 12.9%; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01). The prevalence of STIs was significantly higher among the PrEP users (38.2% vs. 28.2%; \u003cem\u003ep\u003c/em\u003e=0.027). However, this difference was insignificant after multivariable adjustment (aOR 1.09, 95% CI 0.6–1.7). \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e was the most common pathogen among PrEP users, while \u003cem\u003eChlamydia trachomatis\u003c/em\u003e and \u003cem\u003eMycoplasma genitalium\u003c/em\u003ewere more frequent in PWH. Independent factors associated with STI diagnosis included \u003cem\u003echemsex \u003c/em\u003euse (aOR 1.9, 95% CI 1.1–3.3) and higher educational level (aOR 2.4, 95% CI 1.7–3.4).\u003c/p\u003e\n\u003cp\u003eConclusion: STIs were commonly diagnosed among PWH and PrEP users, particularly in individuals engaging in \u003cem\u003echemsex\u003c/em\u003e. The different bacterial profiles of STI between PWH and PrEP users underline the importance of continuous STI surveillance.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of Sexually Transmitted Infections among People Living with HIV and Pre- exposure Prophylaxis Users","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-02 11:46:14","doi":"10.21203/rs.3.rs-5085129/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-23T08:46:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-22T20:23:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2025-10-14T13:35:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-02T20:00:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T12:55:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-15T06:50:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-05-14T14:56:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63ab2295-fe14-4e4f-842a-0a3ae3c1f50a","owner":[],"postedDate":"November 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-29T15:59:03+00:00","versionOfRecord":{"articleIdentity":"rs-5085129","link":"https://doi.org/10.1186/s12879-025-12395-z","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-12-23 15:57:04","publishedOnDateReadable":"December 23rd, 2025"},"versionCreatedAt":"2025-11-02 11:46:14","video":"","vorDoi":"10.1186/s12879-025-12395-z","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12395-z","workflowStages":[]},"version":"v1","identity":"rs-5085129","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5085129","identity":"rs-5085129","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}