Prediction model construction and application of recurrence of Trichomonal vaginitis in plateau area

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Methods A multicenter prospective cohort study was conducted from October 2023 to October 2024 at three hospitals in the Tibet Autonomous Region. Patients diagnosed with trichomonal vaginitis by saline wet mount microscopy received standard metronidazole treatment and were followed for 12 months. Baseline characteristics, parasite load, bacterial vaginosis status, treatment regimen, and partner treatment status were collected. Multivariate Cox regression identified independent risk factors for recurrence, which were used to construct an integer scoring prediction model. The primary outcome was microbiological recurrence within 12 months. Results A total of 268 patients were included, with a cumulative 12-month recurrence rate of 31.2%. Multivariate analysis identified four independent risk factors: high parasite load (hazard ratio = 2.01, 95% confidence interval 1.32–3.06), concomitant bacterial vaginosis (hazard ratio = 1.79, 95% confidence interval 1.18–2.72), receiving a single-dose treatment regimen (hazard ratio = 1.58, 95% confidence interval 1.04–2.40), and lack of concurrent partner treatment (hazard ratio = 1.85, 95% confidence interval 1.22–2.81). A four-factor risk score model stratified patients into low-risk (0–1 point) and high-risk (2–4 points) groups. The recurrence rate in the high-risk group was significantly higher than that in the low-risk group (52.3% vs. 15.6%, P < 0.001). The model showed good discrimination with a C-statistic of 0.74 (95% confidence interval 0.68–0.80), a bias-corrected C-statistic of 0.72 after internal validation, and good calibration (Hosmer–Lemeshow test P = 0.455). Conclusion A simple prediction model for trichomonal vaginitis recurrence comprising four indicators—parasite load, bacterial vaginosis status, treatment regimen, and partner treatment status—was constructed and validated using prospective data from Tibet. The model demonstrates good discrimination and can effectively identify high-risk populations. All indicators are obtainable through routine examinations in primary healthcare facilities, making the model practical for underdeveloped plateau regions. Trichomonal vaginitis Recurrence Prediction model Plateau area Multicenter study Figures Figure 1 Figure 2 Background Trichomonal vaginitis (TV) is one of the most common non-viral sexually transmitted infections worldwide and is closely associated with pelvic inflammatory disease, adverse pregnancy outcomes (including premature rupture of membranes, preterm birth, and secondary infertility), as well as an increased risk of HIV infection [ 1 , 2 ]. Although treatment with metronidazole or tinidazole is generally effective, the relatively high post-treatment recurrence rate (5%–30%) remains a major challenge in clinical practice [ 3 ]. Notably, the incidence of TV is relatively high in the Tibet region, and because it can lead to severe pelvic inflammation and pregnancy-related complications, it has become a substantial reproductive health concern in this area [ 4 ]. However, most existing studies on risk factors for TV recurrence are based on populations in low-altitude regions, and the applicability of these findings to high-altitude environments with distinctive ecological and physiological characteristics remains uncertain. The average altitude of the Shannan region in Tibet exceeds 3,700 meters. Unique environmental conditions such as plateau hypoxia and aridity may affect the vaginal immune microenvironment, microbial composition, and host drug metabolism, thereby influencing the disease course and treatment response of TV [ 5 ]. Compared with low-altitude areas, plateau regions also face practical limitations, such as inadequate healthcare resources and lower rates of barrier contraception use. These factors collectively contribute to the higher incidence of TV observed in plateau areas. Nonetheless, there remains a lack of prediction tools specifically developed to assess TV recurrence risk in resource-limited and environmentally distinct high-altitude regions. Accurate identification of patients at high risk of recurrence and implementation of targeted treatment and follow-up strategies are crucial to optimizing TV clinical management and reducing disease burden and associated complications. Therefore, this study, based on multicenter prospective cohort data from three medical institutions in the Shannan region, employed clinically accessible indicators available in primary healthcare settings to construct and preliminarily validate a clinical recurrence risk prediction model for TV in the high-altitude Tibetan region. This work provides a scientific foundation for individualized clinical decision-making, addresses a gap in existing research, and holds significant practical importance and applicability. Methods Study design and ethics This study was designed as a multicenter prospective observational cohort investigation and was approved by the Ethics Committee of Shannan Maternal and Child Health Hospital (Approval No.: SN–037). It was also reviewed and authorized by the research management departments of Shannan Maternal and Child Health Hospital and Shannan Naidong District People’s Hospital. All of the participants provided written informed consent prior to enrollment. Study participants Patients diagnosed with TV were consecutively enrolled from the gynecology outpatient clinics of Shannan City People’s Hospital, Shannan Maternal and Child Health Hospital, and Shannan Naidong District People’s Hospital between October 2023 and October 2025. Inclusion criteria: (1) Age 18–50 years; (2) Presence of motile Trichomonas vaginalis observed by saline wet mount microscopy; (3) Agreement to participate in the 12-month follow-up. Exclusion criteria: (1) Pregnancy or breastfeeding; (2) Use of anti-trichomonal agents or antibiotics within the preceding four weeks; and (3) Known allergy to metronidazole; or (4) Presence of severe systemic illness. Data collection and definitions Baseline assessment: Demographic data and clinical symptoms were recorded. Vaginal secretions were collected for the following tests: (1) Saline wet mount microscopy: Samples were examined immediately under a microscope maintained at 37°C. Trichomonas load was categorized by the number of organisms per high-power field (400×): low ( 20). (2) Gram staining: Evaluated according to the Nugent scoring system (scores ≥ 7 were classified as bacterial vaginosis (BV)). Treatment and follow-up: Participants received either a single oral 2 g dose of metronidazole or 400 mg orally twice daily for seven days. Follow-up visits were conducted at 4 weeks, 3, 6, and 12 months post-treatment to assess clinical symptoms and repeat microbiological testing. Recurrence was defined as the reappearance of symptoms with a positive pathogen test after initial cure (symptom resolution and a negative pathogen test at 4 weeks post-treatment). Prediction model construction, validation, and statistical analysis Model construction and validation Initially, all of the baseline variables potentially associated with recurrence, including demographic characteristics, clinical manifestations, laboratory parameters, and treatment regimen, were included in univariate Cox proportional hazards regression models for preliminary screening. Variables meeting the screening criterion of P < 0.10, together with clinically relevant variables, were subsequently entered into multivariate analysis. Independent risk factors were identified using multivariate Cox proportional hazards regression with stepwise variable selection. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated for each independent risk factor. Based on the independent risk factors identified in the multivariate analysis, a risk scoring model was established. Each binary independent risk factor (presence = 1 point, absence = 0 points) was assigned one point, and a cumulative risk score was calculated for each patient. According to the score distribution and its association with recurrence risk, a cutoff value was determined to stratify patients into high- and low-risk groups. Recurrence-free survival curves for different risk strata were generated using the Kaplan–Meier method, and intergroup comparisons were conducted with the log-rank test. Model discrimination was evaluated using Harrell’s C-statistic (calculated with the survival package in R software, with corresponding 95% CIs reported). Internal validation was performed through Bootstrap resampling (1,000 iterations) to obtain the bias-corrected C-statistic and assess model stability. Model calibration was evaluated using calibration plots and the Hosmer–Lemeshow goodness-of-fit test. Statistical analysis All of the statistical analyses were conducted using SPSS Statistics 26.0 and R software version 4.0.3. Continuous variables were expressed as mean ± standard deviation or median (interquartile range), depending on data distribution. Categorical variables were presented as frequencies and percentages. Comparisons between groups were performed using the χ 2 test or Fisher’s exact test, depending on data characteristics and validity requirements. All of the hypothesis tests were two-tailed, and P < 0.05 was considered to be statistically significant. Results Baseline characteristics of patients A total of 268 patients diagnosed with TV were included in this study, comprising 142 (53.0%) from Shannan City People’s Hospital, 78 (29.1%) from Shannan Maternal and Child Health Hospital, and 48 (17.9%) from Shannan Naidong District People’s Hospital. The mean patient age was 32.4 ± 8.1 years. Among them, 98 participants (36.6%) used barrier contraception (including condoms and intrauterine devices), whereas 170 (63.4%) did not use any barrier contraception. Regarding pathogenic characteristics, 94 patients (35.1%) had a high baseline Trichomonas load (> 20/HPF), and 131 (48.9%) presented with concomitant BV. In terms of treatment, 148 patients (55.2%) received a single 2 g oral dose of metronidazole (single-dose regimen), while 120 (44.8%) received metronidazole 400 mg twice daily for seven consecutive days (7-day regimen). Concerning partner management, 158 participants (59.0%) reported partners who received concurrent examination and treatment, whereas partners of 110 participants (41.0%) did not receive treatment. The demographic and clinical baseline characteristics of all of the patients are summarized in Table 1 . Table 1 Baseline characteristics of included patients ( N = 268) Characteristic Category Number ( n ) Proportion (%) Age (years) 20/HPF) 94 35.1 BV Co-infection Status No 137 51.1 Yes 131 48.9 Initial Treatment Regimen 7-day regimen 120 44.8 Single 2 g dose 148 55.2 Partner Concurrent Treatment Yes 158 59.0 No 110 41.0 Treatment response and recurrence outcomes All of the participants completed the 4-week post-treatment assessment. The overall cure rate, which was defined as the resolution of clinical symptoms and a negative pathogen test, was 86.9% (233/268). The median follow-up period was 11.5 months (range: 1–12 months). By the end of the follow-up period, 68 patients experienced microbiologically confirmed recurrence, yielding a cumulative 12-month recurrence rate of 31.2% (95% CI: 25.8%–36.6%). Univariate analysis of TV recurrence Baseline variables potentially influencing recurrence were analyzed using univariate Cox proportional hazards regression models. The results indicated that high Trichomonas load, concomitant BV, single-dose treatment regimen, and absence of concurrent partner treatment were significantly associated with increased risk of TV recurrence ( P < 0.05). Factors such as age and altitude of residence were not statistically significant in this analysis. Additionally, non-use of barrier contraception exhibited a borderline association with recurrence risk ( P = 0.062), suggesting a possible contributory effect. Detailed results are presented in Table 2 . Table 2 Univariate cox regression analysis of risk factors for TV recurrence Variable β Standard Error (SE) Wald χ 2 P -value Hazard Ratio (HR) 95% CI Age −0.021 0.014 2.25 0.134 0.98 0.96–1.01 No Barrier Contraception Use 0.382 0.205 3.47 0.062 1.47 0.98–2.19 High Trichomonas Load 0.745 0.214 12.11 < 0.001 2.11 1.39–3.21 Concomitant BV 0.635 0.212 8.97 0.003 1.89 1.25–2.86 Single-Dose Treatment 0.501 0.213 5.53 0.019 1.65 1.09–2.51 Partner Not Concurrently Treated 0.720 0.215 11.21 0.001 2.05 1.35–3.13 Residence Altitude > 4000 m 0.295 0.216 1.86 0.172 1.34 0.88–2.05 Multivariate analysis of TV recurrence and prediction model construction Variables with P < 0.10 from the univariate analysis were included in a multivariate Cox regression model. Forward stepwise selection (likelihood ratio test) was applied to identify independent risk factors. The final model (Table 3 ) demonstrated that high Trichomonas load (HR = 2.01, 95% CI 1.32–3.06, P = 0.001), concomitant BV (HR = 1.79, 95% CI 1.18–2.72, P = 0.006), single-dose treatment (HR = 1.58, 95% CI 1.04–2.40, P = 0.032), and absence of concurrent partner treatment (HR = 1.85, 95% CI 1.22–2.81, P = 0.004) were independent predictors of TV recurrence. Table 3 Multivariate cox regression analysis of risk factors for TV recurrence Variable β Standard Error (SE) Wald χ 2 P-value Hazard Ratio (HR) 95% CI High Trichomonas Load 0.700 0.215 10.61 0.001 2.01 1.32–3.06 Concomitant BV 0.583 0.214 7.44 0.006 1.79 1.18–72 Concomitant BV 0.458 0.214 4.59 0.032 1.58 1.04–2.40 Partner Not Concurrently Treated 0.615 0.214 8.26 0.004 1.85 1.22–2.81 Based on these four binary independent risk factors, a clinical recurrence risk prediction scoring model for TV was established. Each identified risk factor was assigned one point, yielding a total possible score of 0–4 points. The detailed scoring criteria are presented in Table 4 . Table 4 Clinical recurrence risk prediction scoring system for TV Predictor Condition Score Trichomonas Load High load (> 20/HPF) 1 Medium/Low load (≤ 20/HPF) 0 BV Status Concomitant BV (Nugent Score ≥ 7) 1 No concomitant BV 0 Treatment Regimen Single 2 g dose 1 7-day regimen (400 mg bid) 0 Partner Concurrent Treatment No 1 Yes 0 Establishment and performance evaluation of the risk stratification model Risk stratification and clinical distribution Based on the finalized risk prediction scoring system, risk assessment was conducted for all of the enrolled patients. Patients with a total score of 0–1 were categorized as the low-risk group ( n = 153, 57.1%), and those with scores of 2–4 were classified as the high-risk group ( n = 115, 42.9%). Comparison of baseline characteristics between the two groups revealed that patients in the high-risk group exhibited significantly higher frequencies of elevated Trichomonas load, BV co-infection, use of the single-dose regimen, and absence of partner concurrent treatment compared with those in the low-risk group ( P < 0.05). These findings indicate that the model effectively distinguishes between populations with differing clinical characteristics. Model discrimination and calibration Kaplan–Meier survival analysis demonstrated a significant difference in recurrence-free survival between the two risk groups (log-rank χ 2 = 35.42, P < 0.001) (Fig. 1 ). The cumulative 12-month recurrence rate in the high-risk group was 52.3% (95% CI: 43.0%–61.6%), substantially higher than 15.6% (95% CI: 9.8%–21.4%) in the low-risk group, yielding an absolute risk difference of 36.7%. Model Discrimination Assessment: Harrell’s C-statistic was applied to evaluate the discriminatory performance of the model. The initial C-statistic value was 0.74 (95% CI: 0.68–0.80), reflecting good discrimination and an ability to accurately distinguish between patients with and without recurrence. Following internal Bootstrap validation (1,000 iterations), the bias-corrected C-statistic was 0.72, with an optimism value of 0.02, indicating high model stability and minimal overfitting. Model Calibration Assessment: The calibration plot comparing predicted recurrence probabilities with observed recurrence rates demonstrated strong concordance between predicted and actual outcomes across risk strata (Fig. 2 ). The Hosmer–Lemeshow test indicated an adequate model fit (χ 2 = 6.83, P = 0.455), supporting the high predictive accuracy and calibration reliability of the model. Figure 2 Calibration curve of the prediction model. X-axis represents predicted 12-month recurrence probability, Y-axis represents observed recurrence rate. The ideal fit line (diagonal) closely aligns with the actual curve (solid line), with risk decile points (dots) all near the diagonal. Simplified validation of the risk score model When the total risk score was entered as a continuous variable in a Cox regression model, each one-point increase in score corresponded to an approximately 1.9-fold elevation in recurrence risk (HR = 1.92, 95% CI: 1.56–2.36, P < 0.001). Further stratified analyses for scores of 0, 1, 2, 3, and 4 points revealed a clear dose–response relationship in recurrence risk across score categories (trend test P < 0.001), confirming the validity and rationality of the scoring system. Discussion Pathophysiological mechanisms and evidence base for predictors The four predictors included in the model have strong pathophysiological underpinnings and are supported by evidence-based research. A high Trichomonas load reflects both the infectious burden and the pathogen’s proliferative capacity; prior studies have demonstrated a positive correlation between parasite load and the extent of mucosal inflammatory injury, as well as a reduced rate of pathogen clearance [ 6 , 7 ]. Concomitant BV represents an independent risk factor for TV treatment failure and recurrence. The underlying mechanism may involve metabolic symbiosis between BV-associated anaerobes and Trichomonas vaginalis , along with the formation of multispecies biofilms that impair metronidazole penetration and diminish its antimicrobial efficacy [ 8 , 9 ]. The treatment regimen variable, particularly the single-dose metronidazole protocol (2 g orally once), has undergone significant reevaluation. According to the 2024 WHO guideline, the treatment failure rate for the 7-day regimen (400 mg or 500 mg twice daily) is approximately 9%, notably lower than the 15% associated with the single-dose regimen. The guideline therefore recommends the 7-day course as the preferred first-line therapy, reserving the single-dose approach for cases in which treatment adherence cannot be ensured. Similarly, the U.S. CDC guidelines emphasize the use of the 7-day regimen as the first-line option, particularly for HIV-infected women [ 10 ]. The observed association between single-dose therapy and increased recurrence risk in this study is consistent with these updated international recommendations [ 11 , 12 ]. The absence of concurrent partner treatment, the sole behavioral predictor in the model, constitutes a primary cause of previous research indicates that a considerable proportion of male partners exhibit asymptomatic Trichomonas colonization within the urethra when their female partners are infected [ 13 , 14 ]. By integrating this behavioral determinant into the risk stratification framework, the present study provides a quantitative management basis for effectively interrupting the transmission chain and preventing recurrence. Clinical application value and promotional prospects of the model The four-factor risk score model developed in this study demonstrates substantial clinical applicability and promotional potential. First, ease of implementation: All of the predictive indicators can be obtained through routine examinations commonly available in primary healthcare settings—wet mount microscopy to determine Trichomonas load, Gram staining to diagnose BV, and medical history collection to identify treatment regimen and partner concurrent treatment status. These assessments do not rely on advanced molecular diagnostic techniques, such as Polymerase Chain Reaction (PCR), which is particularly important for healthcare institutions in plateau regions where laboratory resources are limited. Second, effectiveness of risk stratification: The model stratifies patients into two groups with significantly different recurrence risks—15.6% in the low-risk group versus 52.3% in the high-risk group—with an absolute risk difference of 36.7%. This provides a robust quantitative foundation for clinical decision-making and targeted management. Based on this stratification, the following clinical management approach is proposed: For low-risk patients (0–1 point), a single 2 g oral dose of metronidazole may be considered; however, health education regarding partner concurrent treatment should be strengthened, and a follow-up re-examination at 3 months post-treatment is recommended [ 15 ]. For high-risk patients (2–4 points), a 7-day metronidazole regimen (500 mg twice daily for 7 days) is strongly recommended. Concomitant BV should be treated simultaneously according to current clinical guidelines (e.g., vaginal metronidazole gel combined with oral clindamycin). Partner concurrent treatment should be regarded as a “mandatory management measure,” with strict implementation facilitated through interventions such as contacting male partners and providing expedited treatment services [ 16 , 17 ]. Active follow-up or microbiological re-examination is advised at both 3 and 6 months after treatment. This management strategy aligns with the U.S. CDC recommendation that “sexually active women should be rescreened 3 months after treatment” [ 12 ]. Through precise risk stratification, limited medical resources can be efficiently directed toward the highest-need, high-risk population, thereby enhancing treatment efficiency and reducing the overall recurrence burden of TV in plateau regions. Limitations First, although this study used a single-center design, the model demonstrated good internal stability based on Bootstrap validation (optimism = 0.02). Nevertheless, external validation in multicenter cohorts within the Tibet Autonomous Region and other plateau regions remains necessary to confirm the model’s generalizability. Second, due to laboratory constraints, metronidazole resistance gene detection and molecular susceptibility testing were not performed. Consequently, it was not possible to strictly distinguish between “true recurrence” (failure to eradicate the original strain), “re-infection” (introduction of a new strain), and “treatment failure due to drug resistance” [ 18 ]. Future research may consider the following directions: (1) Incorporating molecular typing techniques to differentiate between recurrence and re-infection [ 19 ]; (2) Investigating post-treatment vaginal microenvironment recovery dynamics (e.g., rate of Lactobacillus restoration and Nugent score trajectory) as potential dynamic predictors to enhance model accuracy [ 20 ]; (3) Conducting qualitative studies to explore determinants of partner treatment compliance and feasible intervention strategies in plateau regions; (4) Additionally, data on partner concurrent treatment were obtained primarily through self-reported information from female participants, which may be influenced by recall and social desirability biases. Future studies should attempt to include direct pathogen detection and treatment documentation from male partners to improve the accuracy and objectivity of this variable. Conclusions Using multicenter prospective cohort data from the Shannan region of Tibet, this study established and validated a concise clinical prediction model for TV recurrence incorporating four indicators: Trichomonas load, concomitant BV, treatment regimen, and partner concurrent treatment status. The model effectively identifies individuals at elevated risk of recurrence. All of the indicators are accessible through routine examinations in primary healthcare settings, are straightforward to assess, do not depend on advanced instrumentation, and can be reliably evaluated by primary healthcare personnel following a brief training period. Thus, the model possesses considerable potential for application and promotion in economically underdeveloped plateau regions. Although the study population was geographically limited to the Shannan area, the findings hold meaningful reference value for TV prevention and control across other plateau regions of Tibet and similar high-altitude areas nationwide, where health resources are limited and barrier contraception use remains low. Abbreviations Abbreviation Definition TV Trichomonal vaginitis BV Bacterial vaginosis HR Hazard ratio CI Confidence interval WHO World Health Organization CDC Centers for Disease Control and Prevention PCR Polymerase chain reaction HPF High-power field SE Standard error Declarations Ethical approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of Shannan Maternal and Child Health Hospital (Approval No.: SN-037). The study was also reviewed and authorized by the research management departments of Shannan City People's Hospital and Shannan Naidong District People's Hospital. All participants provided written informed consent prior to enrollment. For participants who were unable to provide consent themselves, consent was obtained from their legal guardians as per institutional guidelines. Consent for publication Not applicable. This manuscript does not contain any individual person's data in any form (including individual details, images or videos). All data presented are aggregated and anonymized, with no identifiable information of any participant. Competing interests The authors declare that they have no competing interests. Funding This study received no external funding. Author Contribution LZ: conceptualization, methodology, investigation, data curation, writing—original draft, and funding acquisition. YL: investigation, data curation, and project administration. NB: investigation, validation, and resources. BL: investigation, formal analysis, and visualization. YD: conceptualization, methodology, supervision, writing—review and editing, and funding acquisition. All authors read and approved the final manuscript. Acknowledgments The authors thank the medical staff of the Department of Obstetrics and Gynecology at Shannan City People's Hospital, Shannan Maternal and Child Health Hospital, and Naidong District People's Hospital for their assistance with patient recruitment and data collection. We also thank all the participants for their cooperation in this study. References World Health Organization. WHO guideline on the treatment of Trichomonas vaginalis infection. Geneva: WHO; 2024. World Health Organization. Global progress report on HIV, viral hepatitis and sexually transmitted infections, 2021: Accountability for the global health sector strategies 2016–2021: actions for impact. Geneva: World Health Organization; 2021. 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Mixed vaginal infection status in women infected with Trichomonas vaginalis: comparison of microscopy method and metagenomic sequencing analysis. Front Cell Infect Microbiol. 2025;15:1638464. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 28 Apr, 2026 Editor invited by journal 23 Apr, 2026 Editor assigned by journal 22 Apr, 2026 Submission checks completed at journal 22 Apr, 2026 First submitted to journal 18 Apr, 2026 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-9455817","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":634695727,"identity":"6bf17f1b-923e-4bcf-88e8-b8e7f0a6e76d","order_by":0,"name":"Lufang Zhang","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lufang","middleName":"","lastName":"Zhang","suffix":""},{"id":634695728,"identity":"cdf3f12f-1c6a-4053-93a3-c93cb6ae4ea5","order_by":1,"name":"Yixi Lamu","email":"","orcid":"","institution":"Shannan Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yixi","middleName":"","lastName":"Lamu","suffix":""},{"id":634695729,"identity":"0a885c22-95da-43b0-b23e-dff3b46c51c6","order_by":2,"name":"Nima Baizhen","email":"","orcid":"","institution":"Shannan City People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Nima","middleName":"","lastName":"Baizhen","suffix":""},{"id":634695730,"identity":"9737000a-3b8d-44f2-a089-3e17e57408fd","order_by":3,"name":"Baima Lamu","email":"","orcid":"","institution":"Naidong District People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Baima","middleName":"","lastName":"Lamu","suffix":""},{"id":634695731,"identity":"dc9f5d33-c121-4b7d-b88b-968cf5759b38","order_by":4,"name":"Ying Ding","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYDACZhBhYMPDxt7Y+PAD8VoK0uT4eQ43G0sQb9WHw8aSM9LbBHiIUczfzmP44YPB4cQNNx+2MUgw2MnpNhDQInGYB2iBQXrihtuJbQ8KGJKNzQ4QsuYwj4E0j4E1SEu7gQTDgcRthLTIA235zWPADHTYwTYJHmK0GBzmMQPa4gx0HSORWgwPs5VZzjAABXIiMJANiPCL3PnDm298+AOKyuMPH36osJMj7H0GDgNkdxJUDgLsD4hSNgpGwSgYBSMYAABGxEFRGC1ysAAAAABJRU5ErkJggg==","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ying","middleName":"","lastName":"Ding","suffix":""}],"badges":[],"createdAt":"2026-04-18 09:53:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9455817/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9455817/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108950305,"identity":"f300767e-bb14-497a-9fbb-387920c7c8a1","added_by":"auto","created_at":"2026-05-11 07:04:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106636,"visible":true,"origin":"","legend":"\u003cp\u003eRecurrence-free survival curves for patients in different risk strata\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9455817/v1/65be49e9f5b684cde737232a.png"},{"id":108977717,"identity":"f534a218-9188-4f8c-ada7-0106dc36895b","added_by":"auto","created_at":"2026-05-11 11:32:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56229,"visible":true,"origin":"","legend":"\u003cp\u003eCalibration curve of the prediction model. X-axis represents predicted 12-month recurrence probability, Y-axis represents observed recurrence rate. The ideal fit line (diagonal) closely aligns with the actual curve (solid line), with risk decile points (dots) all near the diagonal.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9455817/v1/f3a342eb2757585c1cf15db2.png"},{"id":108979866,"identity":"9d60cfd9-52ea-4063-a4a7-e64a379f8c09","added_by":"auto","created_at":"2026-05-11 12:02:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":487485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9455817/v1/66166acb-8a67-499f-8471-2eb6b15ec859.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prediction model construction and application of recurrence of Trichomonal vaginitis in plateau area","fulltext":[{"header":"Background","content":"\u003cp\u003eTrichomonal vaginitis (TV) is one of the most common non-viral sexually transmitted infections worldwide and is closely associated with pelvic inflammatory disease, adverse pregnancy outcomes (including premature rupture of membranes, preterm birth, and secondary infertility), as well as an increased risk of HIV infection [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although treatment with metronidazole or tinidazole is generally effective, the relatively high post-treatment recurrence rate (5%–30%) remains a major challenge in clinical practice [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]. Notably, the incidence of TV is relatively high in the Tibet region, and because it can lead to severe pelvic inflammation and pregnancy-related complications, it has become a substantial reproductive health concern in this area [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, most existing studies on risk factors for TV recurrence are based on populations in low-altitude regions, and the applicability of these findings to high-altitude environments with distinctive ecological and physiological characteristics remains uncertain.\u003c/p\u003e \u003cp\u003eThe average altitude of the Shannan region in Tibet exceeds 3,700 meters. Unique environmental conditions such as plateau hypoxia and aridity may affect the vaginal immune microenvironment, microbial composition, and host drug metabolism, thereby influencing the disease course and treatment response of TV [\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]. Compared with low-altitude areas, plateau regions also face practical limitations, such as inadequate healthcare resources and lower rates of barrier contraception use. These factors collectively contribute to the higher incidence of TV observed in plateau areas. Nonetheless, there remains a lack of prediction tools specifically developed to assess TV recurrence risk in resource-limited and environmentally distinct high-altitude regions.\u003c/p\u003e \u003cp\u003eAccurate identification of patients at high risk of recurrence and implementation of targeted treatment and follow-up strategies are crucial to optimizing TV clinical management and reducing disease burden and associated complications. Therefore, this study, based on multicenter prospective cohort data from three medical institutions in the Shannan region, employed clinically accessible indicators available in primary healthcare settings to construct and preliminarily validate a clinical recurrence risk prediction model for TV in the high-altitude Tibetan region. This work provides a scientific foundation for individualized clinical decision-making, addresses a gap in existing research, and holds significant practical importance and applicability.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy design and ethics\u003c/p\u003e\u003cp\u003eThis study was designed as a multicenter prospective observational cohort investigation and was approved by the Ethics Committee of Shannan Maternal and Child Health Hospital (Approval No.: SN–037). It was also reviewed and authorized by the research management departments of Shannan Maternal and Child Health Hospital and Shannan Naidong District People’s Hospital. All of the participants provided written informed consent prior to enrollment.\u003c/p\u003e\u003cp\u003eStudy participants\u003c/p\u003e\u003cp\u003ePatients diagnosed with TV were consecutively enrolled from the gynecology outpatient clinics of Shannan City People’s Hospital, Shannan Maternal and Child Health Hospital, and Shannan Naidong District People’s Hospital between October 2023 and October 2025. Inclusion criteria: (1) Age 18–50 years; (2) Presence of motile \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e observed by saline wet mount microscopy; (3) Agreement to participate in the 12-month follow-up. Exclusion criteria: (1) Pregnancy or breastfeeding; (2) Use of anti-trichomonal agents or antibiotics within the preceding four weeks; and (3) Known allergy to metronidazole; or (4) Presence of severe systemic illness.\u003c/p\u003e\u003cp\u003eData collection and definitions\u003c/p\u003e\u003cp\u003eBaseline assessment: Demographic data and clinical symptoms were recorded. Vaginal secretions were collected for the following tests:\u003c/p\u003e\u003cp\u003e(1) Saline wet mount microscopy: Samples were examined immediately under a microscope maintained at 37°C. \u003cem\u003eTrichomonas\u003c/em\u003e load was categorized by the number of organisms per high-power field (400×): low (\u0026lt; 5), moderate (5–20), and high (\u0026gt; 20).\u003c/p\u003e\u003cp\u003e(2) Gram staining: Evaluated according to the Nugent scoring system (scores ≥ 7 were classified as bacterial vaginosis (BV)).\u003c/p\u003e\u003cp\u003e Treatment and follow-up: Participants received either a single oral 2 g dose of metronidazole or 400 mg orally twice daily for seven days. Follow-up visits were conducted at 4 weeks, 3, 6, and 12 months post-treatment to assess clinical symptoms and repeat microbiological testing. Recurrence was defined as the reappearance of symptoms with a positive pathogen test after initial cure (symptom resolution and a negative pathogen test at 4 weeks post-treatment).\u003c/p\u003e\u003cp\u003ePrediction model construction, validation, and statistical analysis\u003c/p\u003e\n\u003ch3\u003eModel construction and validation\u003c/h3\u003e\n\u003cp\u003eInitially, all of the baseline variables potentially associated with recurrence, including demographic characteristics, clinical manifestations, laboratory parameters, and treatment regimen, were included in univariate Cox proportional hazards regression models for preliminary screening. Variables meeting the screening criterion of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10, together with clinically relevant variables, were subsequently entered into multivariate analysis. Independent risk factors were identified using multivariate Cox proportional hazards regression with stepwise variable selection. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated for each independent risk factor.\u003c/p\u003e \u003cp\u003eBased on the independent risk factors identified in the multivariate analysis, a risk scoring model was established. Each binary independent risk factor (presence\u0026thinsp;=\u0026thinsp;1 point, absence\u0026thinsp;=\u0026thinsp;0 points) was assigned one point, and a cumulative risk score was calculated for each patient. According to the score distribution and its association with recurrence risk, a cutoff value was determined to stratify patients into high- and low-risk groups.\u003c/p\u003e \u003cp\u003eRecurrence-free survival curves for different risk strata were generated using the Kaplan\u0026ndash;Meier method, and intergroup comparisons were conducted with the log-rank test. Model discrimination was evaluated using Harrell\u0026rsquo;s C-statistic (calculated with the \u003cem\u003esurvival\u003c/em\u003e package in R software, with corresponding 95% CIs reported). Internal validation was performed through Bootstrap resampling (1,000 iterations) to obtain the bias-corrected C-statistic and assess model stability. Model calibration was evaluated using calibration plots and the Hosmer\u0026ndash;Lemeshow goodness-of-fit test.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll of the statistical analyses were conducted using SPSS Statistics 26.0 and R software version 4.0.3. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range), depending on data distribution. Categorical variables were presented as frequencies and percentages. Comparisons between groups were performed using the χ\u003csup\u003e2\u003c/sup\u003e test or Fisher\u0026rsquo;s exact test, depending on data characteristics and validity requirements. All of the hypothesis tests were two-tailed, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to be statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline characteristics of patients\u003c/p\u003e \u003cp\u003eA total of 268 patients diagnosed with TV were included in this study, comprising 142 (53.0%) from Shannan City People\u0026rsquo;s Hospital, 78 (29.1%) from Shannan Maternal and Child Health Hospital, and 48 (17.9%) from Shannan Naidong District People\u0026rsquo;s Hospital. The mean patient age was 32.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.1 years. Among them, 98 participants (36.6%) used barrier contraception (including condoms and intrauterine devices), whereas 170 (63.4%) did not use any barrier contraception. Regarding pathogenic characteristics, 94 patients (35.1%) had a high baseline \u003cem\u003eTrichomonas\u003c/em\u003e load (\u0026gt;\u0026thinsp;20/HPF), and 131 (48.9%) presented with concomitant BV. In terms of treatment, 148 patients (55.2%) received a single 2 g oral dose of metronidazole (single-dose regimen), while 120 (44.8%) received metronidazole 400 mg twice daily for seven consecutive days (7-day regimen). Concerning partner management, 158 participants (59.0%) reported partners who received concurrent examination and treatment, whereas partners of 110 participants (41.0%) did not receive treatment. The demographic and clinical baseline characteristics of all of the patients are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of included patients (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;268)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber (\u003cem\u003en\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBarrier Contraception Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eTrichomonas\u003c/em\u003e Load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow/Medium (\u0026le;\u0026thinsp;20/HPF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh (\u0026gt;\u0026thinsp;20/HPF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBV Co-infection Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInitial Treatment Regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7-day regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle 2 g dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePartner Concurrent Treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003ch2\u003eTreatment response and recurrence outcomes\u003c/h2\u003e\u003cp\u003eAll of the participants completed the 4-week post-treatment assessment. The overall cure rate, which was defined as the resolution of clinical symptoms and a negative pathogen test, was 86.9% (233/268). The median follow-up period was 11.5 months (range: 1\u0026ndash;12 months). By the end of the follow-up period, 68 patients experienced microbiologically confirmed recurrence, yielding a cumulative 12-month recurrence rate of 31.2% (95% CI: 25.8%\u0026ndash;36.6%).\u003c/p\u003e \u003cp\u003eUnivariate analysis of TV recurrence\u003c/p\u003e \u003cp\u003eBaseline variables potentially influencing recurrence were analyzed using univariate Cox proportional hazards regression models. The results indicated that high \u003cem\u003eTrichomonas\u003c/em\u003e load, concomitant BV, single-dose treatment regimen, and absence of concurrent partner treatment were significantly associated with increased risk of TV recurrence (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Factors such as age and altitude of residence were not statistically significant in this analysis. Additionally, non-use of barrier contraception exhibited a borderline association with recurrence risk (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.062), suggesting a possible contributory effect. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate cox regression analysis of risk factors for TV recurrence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error (SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald χ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHazard Ratio (HR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.96\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Barrier Contraception Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98\u0026ndash;2.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh \u003cem\u003eTrichomonas\u003c/em\u003e Load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.39\u0026ndash;3.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcomitant BV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.25\u0026ndash;2.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle-Dose Treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.09\u0026ndash;2.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartner Not Concurrently Treated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.35\u0026ndash;3.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence Altitude\u0026thinsp;\u0026gt;\u0026thinsp;4000 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.88\u0026ndash;2.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultivariate analysis of TV recurrence and prediction model construction\u003c/p\u003e \u003cp\u003eVariables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10 from the univariate analysis were included in a multivariate Cox regression model. Forward stepwise selection (likelihood ratio test) was applied to identify independent risk factors. The final model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) demonstrated that high \u003cem\u003eTrichomonas\u003c/em\u003e load (HR\u0026thinsp;=\u0026thinsp;2.01, 95% CI 1.32\u0026ndash;3.06, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), concomitant BV (HR\u0026thinsp;=\u0026thinsp;1.79, 95% CI 1.18\u0026ndash;2.72, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), single-dose treatment (HR\u0026thinsp;=\u0026thinsp;1.58, 95% CI 1.04\u0026ndash;2.40, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.032), and absence of concurrent partner treatment (HR\u0026thinsp;=\u0026thinsp;1.85, 95% CI 1.22\u0026ndash;2.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) were independent predictors of TV recurrence.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate cox regression analysis of risk factors for TV recurrence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStandard Error\u003c/p\u003e \u003cp\u003e(SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWald χ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHazard Ratio\u003c/p\u003e \u003cp\u003e(HR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Trichomonas Load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.32\u0026ndash;3.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcomitant BV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.18\u0026ndash;72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcomitant BV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.04\u0026ndash;2.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartner Not Concurrently Treated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.22\u0026ndash;2.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on these four binary independent risk factors, a clinical recurrence risk prediction scoring model for TV was established. Each identified risk factor was assigned one point, yielding a total possible score of 0\u0026ndash;4 points. The detailed scoring criteria are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical recurrence risk prediction scoring system for TV\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eTrichomonas\u003c/em\u003e Load\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh load (\u0026gt;\u0026thinsp;20/HPF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium/Low load (\u0026le;\u0026thinsp;20/HPF)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBV Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcomitant BV (Nugent Score\u0026thinsp;\u0026ge;\u0026thinsp;7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo concomitant BV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment Regimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle 2 g dose\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7-day regimen (400 mg bid)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePartner Concurrent Treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEstablishment and performance evaluation of the risk stratification model\u003c/p\u003e \u003cp\u003eRisk stratification and clinical distribution\u003c/p\u003e \u003cp\u003eBased on the finalized risk prediction scoring system, risk assessment was conducted for all of the enrolled patients. Patients with a total score of 0\u0026ndash;1 were categorized as the low-risk group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;153, 57.1%), and those with scores of 2\u0026ndash;4 were classified as the high-risk group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;115, 42.9%). Comparison of baseline characteristics between the two groups revealed that patients in the high-risk group exhibited significantly higher frequencies of elevated \u003cem\u003eTrichomonas\u003c/em\u003e load, BV co-infection, use of the single-dose regimen, and absence of partner concurrent treatment compared with those in the low-risk group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings indicate that the model effectively distinguishes between populations with differing clinical characteristics.\u003c/p\u003e \u003cp\u003eModel discrimination and calibration\u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier survival analysis demonstrated a significant difference in recurrence-free survival between the two risk groups (log-rank χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;35.42, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cumulative 12-month recurrence rate in the high-risk group was 52.3% (95% CI: 43.0%\u0026ndash;61.6%), substantially higher than 15.6% (95% CI: 9.8%\u0026ndash;21.4%) in the low-risk group, yielding an absolute risk difference of 36.7%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eModel Discrimination Assessment: Harrell\u0026rsquo;s C-statistic was applied to evaluate the discriminatory performance of the model. The initial C-statistic value was 0.74 (95% CI: 0.68\u0026ndash;0.80), reflecting good discrimination and an ability to accurately distinguish between patients with and without recurrence. Following internal Bootstrap validation (1,000 iterations), the bias-corrected C-statistic was 0.72, with an optimism value of 0.02, indicating high model stability and minimal overfitting.\u003c/p\u003e \u003cp\u003eModel Calibration Assessment: The calibration plot comparing predicted recurrence probabilities with observed recurrence rates demonstrated strong concordance between predicted and actual outcomes across risk strata (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The Hosmer\u0026ndash;Lemeshow test indicated an adequate model fit (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;6.83, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.455), supporting the high predictive accuracy and calibration reliability of the model.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Calibration curve of the prediction model. X-axis represents predicted 12-month recurrence probability, Y-axis represents observed recurrence rate. The ideal fit line (diagonal) closely aligns with the actual curve (solid line), with risk decile points (dots) all near the diagonal.\u003c/p\u003e \u003cp\u003eSimplified validation of the risk score model\u003c/p\u003e \u003cp\u003eWhen the total risk score was entered as a continuous variable in a Cox regression model, each one-point increase in score corresponded to an approximately 1.9-fold elevation in recurrence risk (HR\u0026thinsp;=\u0026thinsp;1.92, 95% CI: 1.56\u0026ndash;2.36, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Further stratified analyses for scores of 0, 1, 2, 3, and 4 points revealed a clear dose\u0026ndash;response relationship in recurrence risk across score categories (trend test \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), confirming the validity and rationality of the scoring system.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePathophysiological mechanisms and evidence base for predictors\u003c/p\u003e \u003cp\u003eThe four predictors included in the model have strong pathophysiological underpinnings and are supported by evidence-based research. A high \u003cem\u003eTrichomonas\u003c/em\u003e load reflects both the infectious burden and the pathogen\u0026rsquo;s proliferative capacity; prior studies have demonstrated a positive correlation between parasite load and the extent of mucosal inflammatory injury, as well as a reduced rate of pathogen clearance [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Concomitant BV represents an independent risk factor for TV treatment failure and recurrence. The underlying mechanism may involve metabolic symbiosis between BV-associated anaerobes and \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e, along with the formation of multispecies biofilms that impair metronidazole penetration and diminish its antimicrobial efficacy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe treatment regimen variable, particularly the single-dose metronidazole protocol (2 g orally once), has undergone significant reevaluation. According to the 2024 WHO guideline, the treatment failure rate for the 7-day regimen (400 mg or 500 mg twice daily) is approximately 9%, notably lower than the 15% associated with the single-dose regimen. The guideline therefore recommends the 7-day course as the preferred first-line therapy, reserving the single-dose approach for cases in which treatment adherence cannot be ensured. Similarly, the U.S. CDC guidelines emphasize the use of the 7-day regimen as the first-line option, particularly for HIV-infected women [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The observed association between single-dose therapy and increased recurrence risk in this study is consistent with these updated international recommendations [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe absence of concurrent partner treatment, the sole behavioral predictor in the model, constitutes a primary cause of previous research indicates that a considerable proportion of male partners exhibit asymptomatic \u003cem\u003eTrichomonas\u003c/em\u003e colonization within the urethra when their female partners are infected [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. By integrating this behavioral determinant into the risk stratification framework, the present study provides a quantitative management basis for effectively interrupting the transmission chain and preventing recurrence.\u003c/p\u003e \u003cp\u003eClinical application value and promotional prospects of the model\u003c/p\u003e \u003cp\u003eThe four-factor risk score model developed in this study demonstrates substantial clinical applicability and promotional potential.\u003c/p\u003e \u003cp\u003eFirst, ease of implementation: All of the predictive indicators can be obtained through routine examinations commonly available in primary healthcare settings\u0026mdash;wet mount microscopy to determine \u003cem\u003eTrichomonas\u003c/em\u003e load, Gram staining to diagnose BV, and medical history collection to identify treatment regimen and partner concurrent treatment status. These assessments do not rely on advanced molecular diagnostic techniques, such as Polymerase Chain Reaction (PCR), which is particularly important for healthcare institutions in plateau regions where laboratory resources are limited.\u003c/p\u003e \u003cp\u003eSecond, effectiveness of risk stratification: The model stratifies patients into two groups with significantly different recurrence risks\u0026mdash;15.6% in the low-risk group versus 52.3% in the high-risk group\u0026mdash;with an absolute risk difference of 36.7%. This provides a robust quantitative foundation for clinical decision-making and targeted management. Based on this stratification, the following clinical management approach is proposed:\u003c/p\u003e \u003cp\u003eFor low-risk patients (0\u0026ndash;1 point), a single 2 g oral dose of metronidazole may be considered; however, health education regarding partner concurrent treatment should be strengthened, and a follow-up re-examination at 3 months post-treatment is recommended [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. For high-risk patients (2\u0026ndash;4 points), a 7-day metronidazole regimen (500 mg twice daily for 7 days) is strongly recommended. Concomitant BV should be treated simultaneously according to current clinical guidelines (e.g., vaginal metronidazole gel combined with oral clindamycin). Partner concurrent treatment should be regarded as a \u0026ldquo;mandatory management measure,\u0026rdquo; with strict implementation facilitated through interventions such as contacting male partners and providing expedited treatment services [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Active follow-up or microbiological re-examination is advised at both 3 and 6 months after treatment. This management strategy aligns with the U.S. CDC recommendation that \u0026ldquo;sexually active women should be rescreened 3 months after treatment\u0026rdquo; [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Through precise risk stratification, limited medical resources can be efficiently directed toward the highest-need, high-risk population, thereby enhancing treatment efficiency and reducing the overall recurrence burden of TV in plateau regions.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eFirst, although this study used a single-center design, the model demonstrated good internal stability based on Bootstrap validation (optimism\u0026thinsp;=\u0026thinsp;0.02). Nevertheless, external validation in multicenter cohorts within the Tibet Autonomous Region and other plateau regions remains necessary to confirm the model\u0026rsquo;s generalizability. Second, due to laboratory constraints, metronidazole resistance gene detection and molecular susceptibility testing were not performed. Consequently, it was not possible to strictly distinguish between \u0026ldquo;true recurrence\u0026rdquo; (failure to eradicate the original strain), \u0026ldquo;re-infection\u0026rdquo; (introduction of a new strain), and \u0026ldquo;treatment failure due to drug resistance\u0026rdquo; [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFuture research may consider the following directions: (1) Incorporating molecular typing techniques to differentiate between recurrence and re-infection [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]; (2) Investigating post-treatment vaginal microenvironment recovery dynamics (e.g., rate of \u003cem\u003eLactobacillus\u003c/em\u003e restoration and Nugent score trajectory) as potential dynamic predictors to enhance model accuracy [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; (3) Conducting qualitative studies to explore determinants of partner treatment compliance and feasible intervention strategies in plateau regions; (4) Additionally, data on partner concurrent treatment were obtained primarily through self-reported information from female participants, which may be influenced by recall and social desirability biases. Future studies should attempt to include direct pathogen detection and treatment documentation from male partners to improve the accuracy and objectivity of this variable.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eUsing multicenter prospective cohort data from the Shannan region of Tibet, this study established and validated a concise clinical prediction model for TV recurrence incorporating four indicators: \u003cem\u003eTrichomonas\u003c/em\u003e load, concomitant BV, treatment regimen, and partner concurrent treatment status. The model effectively identifies individuals at elevated risk of recurrence. All of the indicators are accessible through routine examinations in primary healthcare settings, are straightforward to assess, do not depend on advanced instrumentation, and can be reliably evaluated by primary healthcare personnel following a brief training period. Thus, the model possesses considerable potential for application and promotion in economically underdeveloped plateau regions.\u003c/p\u003e \u003cp\u003eAlthough the study population was geographically limited to the Shannan area, the findings hold meaningful reference value for TV prevention and control across other plateau regions of Tibet and similar high-altitude areas nationwide, where health resources are limited and barrier contraception use remains low.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAbbreviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDefinition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTrichomonal vaginitis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eBacterial vaginosis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHazard ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eConfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWorld Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCDC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePolymerase chain reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHigh-power field\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eStandard error\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was conducted in accordance with the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of Shannan Maternal and Child Health Hospital (Approval No.: SN-037). The study was also reviewed and authorized by the research management departments of Shannan City People's Hospital and Shannan Naidong District People's Hospital. All participants provided written informed consent prior to enrollment. For participants who were unable to provide consent themselves, consent was obtained from their legal guardians as per institutional guidelines.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable. This manuscript does not contain any individual person's data in any form (including individual details, images or videos). All data presented are aggregated and anonymized, with no identifiable information of any participant.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLZ: conceptualization, methodology, investigation, data curation, writing\u0026mdash;original draft, and funding acquisition. YL: investigation, data curation, and project administration. NB: investigation, validation, and resources. BL: investigation, formal analysis, and visualization. YD: conceptualization, methodology, supervision, writing\u0026mdash;review and editing, and funding acquisition. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors thank the medical staff of the Department of Obstetrics and Gynecology at Shannan City People's Hospital, Shannan Maternal and Child Health Hospital, and Naidong District People's Hospital for their assistance with patient recruitment and data collection. We also thank all the participants for their cooperation in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. WHO guideline on the treatment of Trichomonas vaginalis infection. Geneva: WHO; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global progress report on HIV, viral hepatitis and sexually transmitted infections, 2021: Accountability for the global health sector strategies 2016\u0026ndash;2021: actions for impact. Geneva: World Health Organization; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKampman CJG, Koedijk FDH, Bosma F, Hautvast J, Hoebe CJPA. Trends in prevalence of \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e among patients of an STI clinic in the Netherlands: a 9-year retrospective study. Sex Transm Infect. 2025:sextrans\u0026ndash;2025.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu X, Liu L, Yixi L, Yang Y, Zhang Y, Yang Z, et al. The prevalence and risk factors of \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e in Wuhan and the Tibetan area, China: a two-center study. Parasitol Res. 2023;122:265\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen M, Lhamo Y, Ch\u0026ouml;dr\u0026ouml;n K, Chen L. Cervical cytology-based screening identifies trichomonas vaginalis as a significant correlate of non-16/18 high-risk human papillomavirus infection in high-altitude tibetan agro-pastoral communities: a cross-sectional study of 62,657 women. Int J Infect Dis. 2025;160:108034.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeleke DG, Yemanebrhane N. \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e infection in Ethiopia: a systematic review and meta-analysis. Int J STD AIDS. 2022;33:232\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNijhuis RHT, Duinsbergen RG, Pol A, Godschalk PCR. Prevalence of \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e, \u003cem\u003eMycoplasma genitalium\u003c/em\u003e and \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e including relevant resistance-associated mutations in a single center in the Netherlands. Eur J Clin Microbiol Infect Dis. 2021;40:591\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSe\u0026ntilde;a AC, Goldstein LA, Ramirez G, Parish AJ, McClelland RS. Bacterial vaginosis and its association with incident \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e infections: a systematic review and meta-analysis. Sex Transm Dis. 2021;48:e192\u0026ndash;201.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorkowski KA, Bachmann LH, Chan PA, Johnston CM, Muzny CA, Park I, et al. Sexually transmitted infections treatment guidelines, 2021. MMWR Recomm Rep. 2021;70:1\u0026ndash;187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHazra A, Collison MW, Davis AM. CDC sexually transmitted infections treatment guidelines, 2021. JAMA. 2022;327:870\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGottlieb M, Moyer E, Buell KG, Fleegler M, Mehta S, Popovich KJ, et al. Diagnosis and treatment of sexually transmitted infections among emergency department patients. Am J Emerg Med. 2026;101:124\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarques-Silva M, Lisboa C, Gomes N, Rodrigues AG. \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e and growing concern over drug resistance: a systematic review. J Eur Acad Dermatol Venereol. 2021;35:2007\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMdingi MM, Gigi RMS, Babalola CM, Taylor C, Muzny CA, Medina Marino A et al. Association between partner treatment and repeat sexually transmitted infections positivity in pregnant women in East London, South Africa. Sex Transm Infect. 2026:sextrans-2025-056758.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Gerwen OT, Camino AF, Sharma J, Kissinger PJ, Muzny CA. Epidemiology, natural history, diagnosis, and treatment of \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e in men. Clin Infect Dis. 2021;73:1119\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnouar MM, Gomseu BED, Sharma N, Afreen S, Tsephel T, Hachim D et al. Prevalence and risk factors of \u003cem\u003eMycoplasma genitalium\u003c/em\u003e, \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e and \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e infections in pregnant women in seven hospitals in N'Djamena, Chad: a cross-sectional study. BMJ Open. 2025;15:e096775.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheeks ML, Schwartz R, Oleson EC, Cohen S, Drey EA, Seidman D. Offering routine trichomonas vaginalis testing to patients presenting for abortion at an urban hospital-based clinic. Contraception. 2021;103:423\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeyhan YE. A systematic review of \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e in Turkey from 2002 to 2020. Acta Trop. 2021;221:105995.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGentil LG, Cullum R, Zhang Y, Lucic D, Van Der Pol B. Evaluation of Alinity m STI assay for simultaneous detection of \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, \u003cem\u003eNeisseria gonorrhoeae\u003c/em\u003e, \u003cem\u003eTrichomonas vaginalis\u003c/em\u003e, and \u003cem\u003eMycoplasma genitalium\u003c/em\u003e in female urogenital specimens. Sex Transm Dis. 2026;53:249\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSonkar SC, Saluja D, Mittal P. A triplex PCR assay for simultaneous detection of non-viral STDs in both dry and wet swabs, offering a rapid and cost-effective diagnostic tool. Yale J Biol Med. 2025;98:431\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJun L, Wan X, Zhang D, Zheng Y, Chen X, Mi L, et al. 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Front Cell Infect Microbiol. 2025;15:1638464.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"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":"Trichomonal vaginitis, Recurrence, Prediction model, Plateau area, Multicenter study","lastPublishedDoi":"10.21203/rs.3.rs-9455817/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9455817/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aims to clarify the clinical characteristics of trichomonal vaginitis in the high-altitude region of Tibet and to construct a clinical recurrence risk prediction model based on indicators accessible in primary healthcare settings.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA multicenter prospective cohort study was conducted from October 2023 to October 2024 at three hospitals in the Tibet Autonomous Region. Patients diagnosed with trichomonal vaginitis by saline wet mount microscopy received standard metronidazole treatment and were followed for 12 months. Baseline characteristics, parasite load, bacterial vaginosis status, treatment regimen, and partner treatment status were collected. Multivariate Cox regression identified independent risk factors for recurrence, which were used to construct an integer scoring prediction model. The primary outcome was microbiological recurrence within 12 months.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 268 patients were included, with a cumulative 12-month recurrence rate of 31.2%. Multivariate analysis identified four independent risk factors: high parasite load (hazard ratio\u0026thinsp;=\u0026thinsp;2.01, 95% confidence interval 1.32\u0026ndash;3.06), concomitant bacterial vaginosis (hazard ratio\u0026thinsp;=\u0026thinsp;1.79, 95% confidence interval 1.18\u0026ndash;2.72), receiving a single-dose treatment regimen (hazard ratio\u0026thinsp;=\u0026thinsp;1.58, 95% confidence interval 1.04\u0026ndash;2.40), and lack of concurrent partner treatment (hazard ratio\u0026thinsp;=\u0026thinsp;1.85, 95% confidence interval 1.22\u0026ndash;2.81). A four-factor risk score model stratified patients into low-risk (0\u0026ndash;1 point) and high-risk (2\u0026ndash;4 points) groups. The recurrence rate in the high-risk group was significantly higher than that in the low-risk group (52.3% vs. 15.6%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The model showed good discrimination with a C-statistic of 0.74 (95% confidence interval 0.68\u0026ndash;0.80), a bias-corrected C-statistic of 0.72 after internal validation, and good calibration (Hosmer\u0026ndash;Lemeshow test P\u0026thinsp;=\u0026thinsp;0.455).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eA simple prediction model for trichomonal vaginitis recurrence comprising four indicators\u0026mdash;parasite load, bacterial vaginosis status, treatment regimen, and partner treatment status\u0026mdash;was constructed and validated using prospective data from Tibet. The model demonstrates good discrimination and can effectively identify high-risk populations. All indicators are obtainable through routine examinations in primary healthcare facilities, making the model practical for underdeveloped plateau regions.\u003c/p\u003e","manuscriptTitle":"Prediction model construction and application of recurrence of Trichomonal vaginitis in plateau area","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 07:04:56","doi":"10.21203/rs.3.rs-9455817/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-28T07:30:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-23T10:05:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-22T10:30:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-22T10:29:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-04-18T09:37:07+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":"2e76ff4a-31a1-466d-ba48-9b97955fd19e","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T07:04:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 07:04:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9455817","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9455817","identity":"rs-9455817","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}