Aetiology of vaginal discharge, urethral discharge, and genital ulcer in sub-Saharan Africa: A systematic review and meta-regression.

BACKGROUND: Syndromic management is widely used to treat symptomatic sexually transmitted infections in settings without aetiologic diagnostics. However, underlying aetiologies and consequent treatment suitability are uncertain without regular assessment. This systematic review estimated the distribution, trends, and determinants of aetiologies for vaginal discharge, urethral discharge, and genital ulcer in sub-Saharan Africa (SSA). METHODS AND FINDINGS: We searched Embase, MEDLINE, Global Health, Web of Science, and grey literature from inception until December 20, 2023, for observational studies reporting aetiologic diagnoses among symptomatic populations in SSA. We adjusted observations for diagnostic test performance, used generalised linear mixed-effects meta-regressions to generate estimates, and critically appraised studies using an adapted Joanna Briggs Institute checklist. Of 4,418 identified records, 206 reports were included from 190 studies in 32 countries conducted between 1969 and 2022. In 2015, estimated primary aetiologies for vaginal discharge were candidiasis (69.4% [95% confidence interval (CI): 44.3% to 86.6%], n = 50), bacterial vaginosis (50.0% [95% CI: 32.3% to 67.8%], n = 39), chlamydia (16.2% [95% CI: 8.6% to 28.5%], n = 50), and trichomoniasis (12.9% [95% CI: 7.7% to 20.7%], n = 80); for urethral discharge were gonorrhoea (77.1% [95% CI: 68.1% to 84.1%], n = 68) and chlamydia (21.9% [95% CI: 15.4% to 30.3%], n = 48); and for genital ulcer were herpes simplex virus type 2 (HSV-2) (48.3% [95% CI: 32.9% to 64.1%], n = 47) and syphilis (9.3% [95% CI: 6.4% to 13.4%], n = 117). Temporal variation was substantial, particularly for genital ulcer where HSV-2 replaced chancroid as the primary cause. Aetiologic distributions for each symptom were largely the same across regions and population strata, despite HIV status and age being significantly associated with several infection diagnoses. Limitations of the review include the absence of studies in 16 of 48 SSA countries, substantial heterogeneity in study observations, and impeded assessment of this variability due to incomplete or inconsistent reporting across studies. CONCLUSIONS: In our study, syndrome aetiologies in SSA aligned with World Health Organization guidelines without strong evidence of geographic or demographic variation, supporting broad guideline applicability. Temporal changes underscore the importance of regular aetiologic re-assessment for effective syndromic management. PROSPERO NUMBER: CRD42022348045.

Predictive Performance of 1 H-NMR Metabolomics-Derived Biomarkers of Bacterial Vaginosis.

ABSTRACT: 1 H-NMR metabolomics-derived biomarkers maltose, acetate, formate, and lactate have excellent potential as predictive biomarkers for bacterial vaginosis with an area under curve of 0.97 (95% confidence interval, 0.88-1.00), sensitivity of 0.90, and specificity of 0.95.

Alterations in gut and genital microbiota associated with gynecological diseases: a systematic review and meta-analysis.

BACKGROUND: Increasing number of studies have demonstrated certain patterns of microbial changes in gynecological diseases; however, the interaction between them remains unclear. To evaluate the consistency or specificity across multiple studies on different gynecological diseases and microbial alterations at different sites of the body (gut and genital tract), we conducted a systematic review and meta-analysis. METHODS: We searched PubMed, Embase, Web of Science, and Cochrane Library up to December 5, 2022(PROSPERO: CRD42023400205). Eligible studies focused on gynecological diseases in adult women, applied next-generation sequencing on microbiome, and reported outcomes including alpha or beta diversity or relative abundance. The random-effects model on standardized mean difference (SMD) was conducted using the inverse-variance method for alpha diversity indices. RESULTS: Of 3327 unique articles, 87 eligible studies were included. Significant decreases were found in gut microbiome of patients versus controls (observed species SMD=-0.35; 95%CI, -0.62 to -0.09; Shannon index SMD=-0.23; 95%CI, -0.40 to -0.06), whereas significant increases were observed in vaginal microbiome (Chao1 SMD = 1.15; 95%CI, 0.74 to 1.56; Shannon index SMD = 0.51; 95%CI, 0.16 to 0.86). Most studies of different diagnostic categories showed no significant differences in beta diversity. Disease specificity was observed, but almost all the changes were only replicated in three studies, except for the increased Aerococcus in bacterial vaginosis (BV). Patients with major gynecological diseases shared the enrichment of Prevotella and depletion of Lactobacillus, and an overlap in microbes was implied between BV, cervical intraepithelial neoplasia, and cervical cancer. CONCLUSIONS: These findings demonstrated an association between alterations in gut and genital microbiota and gynecological diseases. The most observed results were shared alterations across diseases rather than disease-specific alterations. Therefore, further investigation is required to identify specific biomarkers for diagnosis and treatment in the future.

Prospective Cohort Study of Treatment Outcomes of Vaginal Discharge Syndrome in Women in Windhoek, Namibia.

BACKGROUND: Syndromic treatment is the standard of care for vaginal discharge syndrome (VDS) in resource-constrained settings. However, the outcomes of VDS treatment have not been well documented. This study aimed to determine the incidence, risk factors, and microbial etiology of treatment failure in women with VDS. METHODS: This prospective cohort study of women with VDS was conducted between September 2021 and March 2022 at Katutura Intermediate Hospital in Windhoek, Namibia. Microbiological analyses of sexually transmitted infections (STIs; Chlamydia trachomatis , Neisseria gonorrhoeae , Trichomonas vaginalis , Mycoplasma genitalium ), bacterial vaginosis, and vulvovaginal candidiasis (VVC) were performed. Treatment outcomes were assessed at 7 and 30 days after treatment, followed by microbial investigation in case of treatment failure. RESULTS: One hundred nine women were enrolled, and 94 (86%) completed the follow-up. At baseline, 58 of 109 women (53%) were diagnosed with STI, 47 of 109 (43%) with bacterial vaginosis, and 45 of 109 (41%) with VVC. Candida albicans (33 of 45; 73%) was the main pathogen in VVC, with fluconazole resistance detected in 8 of 33 isolates (24%); 10 of 12 (80%) of non- albicans Candida species showed resistance. The incidence of treatment failure was 3.6 per 100 person-years at 7 days and 1.0 per 100 person-years at 30 days of follow-up; 17 of 94 women (18%) had recurrent VDS, and 12 of 94 women (13%) had persistent VDS. Vulvovaginal candidiasis (odds ratio, 4.3; 95% confidence interval, 1.7-11; P = 0.002) at baseline was associated with treatment failure. CONCLUSIONS: Treatment failure after syndromic management of VDS is common in resource-constrained settings. Access to diagnostic testing, including fungal culture and susceptibility testing, is recommended to improve outcomes.

Sexually transmitted infections and the vaginal microbiome after vaginoplasty.

PURPOSE OF REVIEW: Transgender and gender-diverse individuals (TGD) are at risk for sexually transmitted infections. Gender affirmation surgery is a cornerstone of care for many TGD individuals. For genital gender affirmation, the surgical creation of a vagina may be performed through a number of techniques. Those who have undergone vaginoplasty have unique anatomical and biopsychosocial considerations, which we discuss. RECENT FINDINGS: While sexually-transmitted infections including HPV, HSV, HIV, gonorrhea, and chlamydia, have been described in TGD individuals after vaginoplasty, the reports are very rare, and the provider should maintain an index of suspicion and maintain a broad differential for symptoms including neovaginal discharge. We discuss the association of the neovaginal microbiota composition with bacterial vaginosis, and how its modulation could potentially reduce bacterial vaginosis and sexually transmitted infection risk. SUMMARY: We examine the literature regarding sexually-transmitted infections following vaginoplasty, and the neovaginal microbiome and its similarities and differences relative to the natal vaginal microbiome.

Establishment and Validation of a Mouse Bacterial Vaginosis Model.

BACKGROUND: Bacterial vaginosis (BV) is a common vaginal infection without a reliable animal model. To establish a novel mouse BV model, we evaluated multiple parameters of various identified bacteria-infected mice, including Staphylococcus aureus (SA), Escherichia coli (EC), Streptococcus agalactiae, ß-Hemolytic streptococcus, and Gardnerella vaginalis (GV). METHODS: Mature female KM mice were randomly allocated to a vehicle group (group A, without any treatment) and experimental groups. After vaginal secretions were harvested, experimental groups were divided into phosphate buffer solution group (PBS, group B), control group including SA, and EC with a 1:1 ratio (group C), SA, EC, and Streptococcus agalactiae with a 1:2:1 ratio group (group D), SA, EC, and ß-Hemolytic streptococcus with a 1:2:1 ratio group (group E), and GV group (group F). The vaginal secretions of experimental mice were collected by flushing with 100 mL sterile PBS on days 2, 4, and 6. Vaginal secretions were examined by Gram staining, sialidase assay, ammonia test, and pH value measurement. IL-6 and IL-10 levels in mouse serum were detected by enzyme-linked immunosorbent assay. Hematoxylineosin staining and mouse cervicovaginal tissue histopathological scores were observed. The diagnostic test results were analyzed by logistic regression analysis and receiver operating characteristic curves. The Shapiro-Wilk analysis of variance, or rank-sum test, was used for normal distribution analysis. Pearson's correlation and chi-squared test determined the correlation and comparison data expressed as a percentage or frequency. RESULTS: There was less severe vaginal morphology in GV-infected mice compared to other bacteria-infected mice. The sialidase assay, the ammonia test, and the pH values of vaginal secretions showed significant differences between GV-infected and uninfected mice. Serum IL-6 and IL-10 levels and vaginal histological scoring increased in other bacteria-infected mice, but GV-infected mice showed only a mildly increasing trend of IL-10 levels and vaginal histological scoring compared to control mice. CONCLUSIONS: GV-infected mice showed clinical features similar to human BV infection, including vaginal anatomical and pathological indices, and biochemical and immune parameters. Serum IL-10 level has potential for use in BV diagnosis.

Analysis of the Spectrum of Common Pathogens and the Resistance of Mycoplasma in Sialidase-Positive Bacterial Vaginosis.

BACKGROUND: The objective of this study is to understand the characteristics of the common spectrum of pathogen and the resistance of Mycoplasma in Sialidase-positive bacterial vaginosis. METHODS: The vaginal secretion specimens collected from August 2018 to October 2018 for the analysis of bacterial vaginosis (BV) were subjected to various techniques. These included routine leukorrhea examination, bacterial vaginosis sialidase testing, routine culture for common pathogens, mass spectrometry identification, and Mycoplasma resistance testing. RESULTS: A total of 238 patients with BV were identified. The cleanliness grading was mostly clean (+) and clean (2+), accounting for 38.24% and 30.67%, respectively. The bacterial vaginosis test for vaginal secretions showed leukocyte esterase positivity in 220 cases, resulting in a positivity rate of 92.44%. The spectrum of routine culture was analyzed and divided into four groups: A, B, C, and D. Group A consisted of Candidal vaginitis (13.45%); group B consisted of Gardnerella vaginalis vaginitis (32.77%); group C consisted of gram-negative bacillus vaginitis (46.22%); and group D consisted of Streptococcus agalactiae vaginitis (7.56%). The identification and antimicrobial susceptibility testing results for Mycoplasma showed a high detection rate of BV, with a positivity rate of 86.13%. There was a high sensitivity to tetracyclines for Ureaplasma urealyticum and Mycoplasma hominis, but a high resistance to macrolides and quinolones. CONCLUSIONS: Bacterial vaginosis existed in various complex forms, including Candida, Gardnerella vaginalis, Gram-negative bacillus, and Streptococcus agalactiae types. Moreover, there was an increasing trend of multi-drug resistance in Mycoplasma hominis. Therefore, it is crucial to pay attention to this condition and make accurate judgments based on the etiological characteristics and common antimicrobial susceptibility tests. This will enable the implementation of effective therapeutic interventions.

Functional testing is a complementary tool for the diagnosis of vaginitis.

OBJECTIVE: Vaginal microbiota evaluation is a methodology widely used in China to diagnose various vaginal inflammatory diseases. Although vaginal microbiota evaluation has many advantages, it is time-consuming and requires highly skilled and experienced operators. Here, we investigated a six-index functional test that analyzed pH, hydrogen peroxide (H2O2), leukocyte esterase (LEU), sialidase (SNA), ß-glucuronidase (GUS), and acetylglucossidase (NAG), and determined its diagnostic value by comparing it with morphological tests of vaginal microbiota. MATERIALS AND METHODS: The research was conducted using data extracted from the Laboratory Information System of Women and Children's Hospital. A total of 4902 subjects, ranging in age from 35.4 ± 9.7 years, were analyzed. During the consultation, a minimum of two vaginal swab specimens per patient were collected for both functional and morphological testing. Fisher's exact was used to analyze data using SPSS. RESULTS: Of the 4,902 patients, 2,454 were considered to have normal Lactobacillus morphotypes and 3,334 were considered to have normal dominant microbiota. The sensitivity and specificity of H2O2-indicating Lactobacillus morphotypes were 91.3% and 25.28%, respectively, while those of pH-indicating Lactobacillus morphotypes were 88.09% and 59.52%, respectively. The sensitivity and specificity of H2O2-indicating dominant microbiota were 91.3% and 25.3%, respectively, while those of pH-indicating dominant microbiota were 86.27% and 64.45%, respectively. The sensitivity and specificity of NAG for vulvovaginal candidiasis were 40.64% and 84.8%, respectively. For aerobic vaginitis, GUS sensitivity was low at 0.52%, while its specificity was high at 99.93%; the LEU sensitivity and specificity values were 94.73% and 27.49%, respectively. Finally, SNA sensitivity and specificity for bacterial vaginosis were 80.72% and 96.78%, respectively. CONCLUSION: Functional tests (pH, SNA, H2O2, LEU) showed satisfactory sensitivity for the detection of vaginal inflammatory diseases. However, these tests lacked specificity, making it difficult to accurately identify specific pathologies. By contrast, NAG and GUS showed excellent specificity in identifying vaginal inflammatory diseases, but their sensitivity was limited. Therefore, functional tests alone are not sufficient to diagnose various vaginal inflammatory diseases. When functional and morphological tests are inconsistent, morphological tests are currently considered the preferred reference method.

Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.

BACKGROUND: Bacterial vaginosis (BV) is a common clinical manifestation of a perturbed vaginal ecology associated with adverse sexual and reproductive health outcomes if left untreated. The existing diagnostic modalities are either cumbersome or require skilled expertise, warranting alternate tests. Application of machine-learning tools to heterogeneous and high-dimensional multi-omics datasets finds promising potential in data integration and may aid biomarker discovery. OBJECTIVES: The present study aimed to evaluate the potential of the microbiome and metabolome-derived biomarkers in BV diagnosis. Interpretable machine-learning algorithms were used to evaluate the utility of an integrated-omics-derived classification model. METHODS: Vaginal samples obtained from reproductive-age group women with (n = 40) and without BV (n = 40) were subjected to 16S rRNA amplicon sequencing and LC-MS-based metabolomics. The vaginal microbiome and metabolome were characterized, and machine-learning analysis was performed to build a classification model using biomarkers with the highest diagnostic accuracy. RESULTS: Microbiome-based diagnostic model exhibited a ROC-AUC (10-fold CV) of 0.84 ± 0.21 and accuracy of 0.79 ± 0.18, and important features were Aerococcus spp., Mycoplasma hominis, Sneathia spp., Lactobacillus spp., Prevotella spp., Gardnerella spp. and Fannyhessea vaginae. The metabolome-derived model displayed superior performance with a ROC-AUC of 0.97 ± 0.07 and an accuracy of 0.92 ± 0.08. Beta-leucine, methylimidazole acetaldehyde, dimethylethanolamine, L-arginine and beta cortol were among key predictive metabolites for BV. A predictive model combining both microbial and metabolite features exhibited a high ROC-AUC of 0.97 ± 0.07 and accuracy of 0.94 ± 0.08 with diagnostic performance only slightly superior to the metabolite-based model. CONCLUSION: Application of machine-learning tools to multi-omics datasets aid biomarker discovery with high predictive performance. Metabolome-derived classification models were observed to have superior diagnostic performance in predicting BV than microbiome-based biomarkers.

The efficacy of vaginal treatment for non-Lactobacillus dominant endometrial microbiota-A case-control study.

AIM: Reduced Lactobacillus occupancy in the uterine microflora has been associated with implantation failure. This study aimed to evaluate a treatment for improving the uterine microflora. METHODS: This study included patients diagnosed with repeated implantation failure-defined as failure to achieve pregnancy after two or more transfers of viable embryos-who were classified as non-Lactobacillus dominant. Treatment A comprised oral administration of antibiotics for 1 week, followed by oral probiotic butyrate tablets (3 g/day) for approximately 30 days. Treatment B comprised a 1-week course of oral (750 mg/day) and vaginal (250 mg/day) metronidazole, followed by a 1-week intravaginal administration of probiotic capsules (1 capsule/day) and continued oral administration of probiotics (1 capsule/day). Both treatments were compared in terms of efficacy in improving vaginal flora. Improvement was defined as Lactobacillus occupancy >90% or an increase in Lactobacillus occupancy >20%. RESULTS: Seven (41.2%) of 17 patients in the Treatment A group improved in response to the treatment. Contrastingly, 9 (90.0%) of 10 patients improved in the Treatment B group (p = 0.0127). Following treatment, Lactobacillus occupancy in the Treatment B group (62.9% ± 12.7%) was significantly higher than that in the Treatment A group (5.7% ± 9.8%) (p = 0.0242). CONCLUSIONS: This study demonstrates the effectiveness of combining antibiotics and probiotics in vaginal formulations for treating abnormal uterine microflora. However, its potential impact on in vitro fertilization outcomes remains unclear and warrants further investigation through larger, more comprehensive studies.

Testing on bacterial vaginosis in a subfertile population and time to pregnancy: a prospective cohort study.

PURPOSE: This study aimed to investigate the influence of bacterial vaginosis on time to pregnancy in subfertile couples. METHODS: Couples attending a teaching hospital in the Netherlands having an initial fertility assessment (IFA) between July 2019 and June 2022 were included in this prospective study, with follow-up of pregnancies until June 2023. Vaginal samples at IFA were analyzed on pH, qPCR BV, and 16S rRNA gene microbiome analysis of V1-V2 region. Main outcome measures were time from initial fertility assessment to ongoing pregnancy at 12 weeks and live birth, analyzed by Kaplan-Meier and Cox regression with adjustment for potential confounders. RESULTS: At IFA, 27% of 163 included participants tested positive for BV. BV status had no influence on time to ongoing pregnancy (HR 0.98, 0.60-1.61, aHR 0.97, 0.58-1.62). In persons with unexplained subfertility, positive BV status had a tendency of longer time to pregnancy. When persons had an indication for fertility treatment, positive BV status (HR 0.21, 0.05-0.88, aHR 0.19, 0.04-0.85) and microbiome community state type III and type IV had significant longer time to pregnancy. CONCLUSION: This study indicates that BV may have a potential negative impact on time to live birth pregnancy in subfertile persons with an indication for fertility treatment. This study did not find an association between BV and time to live birth pregnancy in a general group of subfertile couples or in unexplained subfertility. More research should be done in persons with unexplained subfertility and if treatment improves time to pregnancy.

Using unsupervised machine learning to classify behavioral risk markers of bacterial vaginosis.

INTRODUCTION: This study used an unsupervised machine learning algorithm, sidClustering and random forests, to identify clusters of risk behaviors of Bacterial Vaginosis (BV), the most common cause of abnormal vaginal discharge linked to STI and HIV acquisition.  METHODS: Participants were 391 cisgender women in Miami, Florida, with a mean of 30.8 (SD = 7.81) years of age; 41.7% identified as Hispanic; 41.7% as Black and 44.8% as White. Participants completed measures of demographics, risk behaviors [sexual, medical, and reproductive history, substance use, and intravaginal practices (IVP)], and underwent collection of vaginal samples; 135 behavioral variables were analyzed. BV was diagnosed using Nugent criteria. RESULTS: We identified four clusters, and variables were ranked by importance in distinguishing clusters: Cluster 1: nulliparous women who engaged in IVPs to clean themselves and please sexual partners, and used substances frequently [n = 118 (30.2%)]; Cluster 2: primiparous women who engaged in IVPs using vaginal douches to clean themselves (n = 112 (28.6%)]; Cluster 3: primiparous women who did not use IVPs or substances [n = 87 (22.3%)]; and Cluster 4: nulliparous women who did not use IVPs but used substances [n = 74 (18.9%)]. Clusters were related to BV (p < 0.001). Cluster 2, the cluster of women who used vaginal douches as IVPs, had the highest prevalence of BV (52.7%). CONCLUSIONS: Machine learning methods may be particularly useful in identifying specific clusters of high-risk behaviors, in developing interventions intended to reduce BV and IVP, and ultimately in reducing the risk of HIV infection among women.

Aerobic vaginitis: antibiotic resistance trend and future actions of antimicrobial diagnostic stewardship.

The study objective is to examine epidemiological and microbiological aspects of aerobic vaginitis in female patients admitted to University Hospital of Campania "L. Vanvitelli" over five years. The most represented strains were E. coli (n = 153), Citrobacter spp. increasing from 2020, E. faecalis (n = 149), S. haemolitycus (n = 61), and Candida albicans (n = 87). The susceptibility patterns of a selection of gram-negative and gram-positive representative bacterial isolates were examined. Carbapenems, aminoglycosides, and fosfomycin were most effective against gram-negative bacteria, whereas vancomycin, daptomycin, and linezolid exhibited greater efficacy against gram-positive bacteria. None of the E. coli and Citrobacter spp. isolates produced extended-spectrum beta-lactamases, and the S. haemolyticus strains were methicillin-resistant. In gram-positive isolates, gentamicin susceptibility increased in 2020 and 2021 compared to clindamycin; erythromycin showed high resistance rates in 2020. Our findings indicate that integrating proper microbiological cultures into clinical practice could improve the management of aerobic vaginitis. Moreover, they highlight the necessity of establishing a nationwide surveillance guideline to mitigate antimicrobial resistance. Improvement actions in antimicrobial diagnostic stewardship must be considered when seeking the appropriate diagnosis and treatment for aerobic vaginitis.

Cracking the Code: Investigating the Correlation between Aerobic Vaginitis and Preterm Labor.

Aerobic vaginitis (AV) is a distinct clinical entity characterized by inflammation and abnormal vaginal microflora. Often mistaken for bacterial vaginosis, AV remains relatively unknown and underdiagnosed. AV's understanding is evolving, with some experts suggesting it may primarily be an immunological disorder, the prevalence of which has a range of 7-13% in non-pregnant women and 4.1-8.3% during pregnancy. Pregnancy can affect susceptibility to vaginal infections, leading to adverse outcomes for the woman and the newborn. This review summarizes the correlation between AV and adverse pregnancy outcomes, particularly preterm birth, the leading cause of morbidity and mortality among neonates. An improved understanding of AV's impact on pregnancy outcomes can lead to early recognition, proper management, and effective interventions. While some studies support an association between AV and preterm labor, the existing knowledge of this relationship remains limited. The evidence suggests that AV may contribute to adverse pregnancy outcomes, mainly preterm birth, but further research is needed to establish a definitive link. Further studies are needed to investigate the underlying mechanisms and clarify AV's role in premature labor. A comprehensive understanding of AV's impact on pregnancy outcomes is crucial for early recognition, appropriate management, and effective interventions.

[Preliminary Study on the Identification of Aerobic Vaginitis by Artificial Intelligence Analysis System]. / 人工智能分析系统对需氧菌性阴道炎的判读方法初探.

Objective: To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis (AV). Methods: In this study, the vaginal secretion samples of 3769 patients receiving treatment at the Department of Obstetrics and Gynecology, West China Second Hospital, Sichuan University between January 2020 and December 2021 were selected. Using the results of manual microscopy as the control, we developed the linear kernel SVM algorithm, an artificial intelligence (AI) automated analysis software, with Python Scikit-learn script. The AI automated analysis software could identify leucocytes with toxic appearance and parabasal epitheliocytes (PBC). The bacterial grading parameters were reset using standard strains of lactobacillus and AV common isolates. The receiver operating characteristic (ROC) curve analysis was used to determine the cut-off value of AV evaluation results for different scoring items were obtained by using the results of manual microscopy as the control. Then, the parameters of automatic AV identification were determined and the automatic AV analysis scoring method was initially established. Results: A total of 3769 vaginal secretion samples were collected. The AI automated analysis system incorporated five parameters and each parameter incorporated three severity scoring levels. We selected 1.5 µm as the cut-off value for the diameter between Lactobacillus and common AV bacterial isolates. The automated identification parameter of Lactobacillus was the ratio of bacteria ≥1.5 µm to those <1.5 µm. The cut-off scores were 2.5 and 0.5, In the parameter of white blood cells (WBC), the cut-off value of the absolute number of WBC was 103 µL－1 and the cut-off value of WBC-to-epithelial cell ratio was 10. The automated identification parameter of toxic WBC was the ratio of toxic WBC toWBC and the cut-off values were 1% and 15%. The parameter of background flora was bacteria<1.5 µm and the cut-off values were 5×103 µL－1 and 3×104 µL－1. The parameter of the parabasal epitheliocytes was the ratio of PBC to epithelial cells and the cut-off values were 1% and 10%. The agreement rate between the results of automated microscopy and those of manual microscopy was 92.5%. Out of 200 samples, automated microscopy and manual microscopy produced consistent scores for 185 samples, while the results for 15 samples were inconsistent. Conclusion: We developed an AI recognition software for AV and established an automated vaginal secretion microscopy scoring system for AV. There was good overall concordance between automated microscopy and manual microscopy. The AI identification software for AV can complete clinical lab examination with rather high objectivity, sensitivity, and efficiency, markedly reducing the workload of manual microscopy.

Analysis of bacterial vaginosis, the vaginal microbiome, and sexually transmitted infections following the provision of menstrual cups in Kenyan schools: Results of a nested study within a cluster randomized controlled trial.

BACKGROUND: Nonhygienic products for managing menstruation are reported to cause reproductive tract infections. Menstrual cups are a potential solution. We assessed whether menstrual cups would reduce bacterial vaginosis (BV), vaginal microbiome (VMB), and sexually transmitted infections (STIs) as studies have not evaluated this. METHODS AND FINDINGS: A cluster randomized controlled trial was performed in 96 Kenyan secondary schools, randomized (1:1:1:1) to control, menstrual cup, cash transfer, or menstrual cup plus cash transfer. This substudy assessing the impact of menstrual cups on BV, VMB, and STIs, included 6 schools from the control (3) and menstrual cup only (3) groups, both receiving BV and STI testing and treatment at each visit. Self-collected vaginal swabs were used to measure VMB (16S rRNA gene amplicon sequencing), BV (Nugent score), and STIs. STIs were a composite of Chlamydia trachomatis and Neisseria gonorrhoeae (nucleic acid amplification test) and Trichomonas vaginalis (rapid immunochromatographic assay). Participants were not masked and were followed for 30 months. The primary outcome was diagnosis of BV; secondary outcomes were VMB and STIs. Intention-to-treat blinded analyses used mixed effects generalized linear regressions, with random effects term for school. The study was conducted between May 2, 2018, and February 7, 2021. A total of 436 participants were included: 213 cup, 223 control. There were 289 BV diagnoses: 162 among control participants and 127 among intervention participants (odds ratio 0.76 [95% CI 0.59 to 0.98]; p = 0.038). The occurrence of Lactobacillus crispatus-dominated VMB was higher among cup group participants (odds ratio 1.37 [95% CI 1.06 to 1.75]), as was the mean relative abundance of L. crispatus (3.95% [95% CI 1.92 to 5.99]). There was no effect of intervention on STIs (relative risk 0.82 [95% CI 0.50 to 1.35]). The primary limitations of this study were insufficient power for subgroup analyses, and generalizability of findings to nonschool and other global settings. CONCLUSIONS: Menstrual cups with BV and STI testing and treatment benefitted adolescent schoolgirls through lower occurrence of BV and higher L. crispatus compared with only BV and STI testing and treatment during the 30 months of a cluster randomized menstrual cup intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03051789.

Clinical Evaluation of a New Molecular Test for the Detection of Organisms Causing Vaginitis and Vaginosis.

In this prospective, observational, method comparison clinical study, the Xpert Xpress MVP test (MVP) was evaluated using both clinician-collected (CVS) and self-collected vaginal swabs (SVS) collected in a clinical setting. The study was conducted at 12 sites, including point-of-care (POC) settings, from geographically diverse locations in the United States. Participants were biologically female patients ≥ 14 years old with signs and/or symptoms of vaginitis/vaginosis. MVP test results for BV were compared to the BD MAX Vaginal Panel (BDVP). Results for Candida group and Candida glabrata and Candida krusei targets (species not differentiated) were assessed relative to yeast culture followed by mass spectrometry for species identification. Trichomonas vaginalis (TV) results were compared relative to a composite method that included results from the BDVP and InPouch TV culture. The investigational test demonstrated high positive percent agreement ranging from 93.6 to 99.0%, and negative percent agreement ranging from 92.1% to 99.8% for both CVS and SVS specimens, indicating it may be a valuable tool for the diagnosis of vaginitis/vaginosis in laboratory and POC settings.

State of the Art for Diagnosis of Bacterial Vaginosis.

Bacterial vaginosis (BV) is the most common cause of vaginal discharge among reproductive-age women. It is associated with multiple adverse health outcomes, including increased risk of acquisition of HIV and other sexually transmitted infections (STIs), in addition to adverse birth outcomes. While it is known that BV is a vaginal dysbiosis characterized by a shift in the vaginal microbiota from protective Lactobacillus species to an increase in facultative and strict anaerobic bacteria, its exact etiology remains unknown. The purpose of this minireview is to provide an updated overview of the range of tests currently used for the diagnosis of BV in both clinical and research settings. This article is divided into two primary sections: traditional BV diagnostics and molecular diagnostics. Molecular diagnostic assays, particularly 16S rRNA gene sequencing, shotgun metagenomic sequencing, and fluorescence in situ hybridization (FISH), are specifically highlighted, in addition to multiplex nucleic acid amplification tests (NAATs), given their increasing use in clinical practice (NAATs) and research studies (16S rRNA gene sequencing, shotgun metagenomic sequencing, and FISH) regarding the vaginal microbiota and BV pathogenesis. We also provide a discussion of the strengths and weaknesses of current BV diagnostic tests and discuss future challenges in this field of research.

The vaginal microbiota among the different status of human papillomavirus infection and bacterial vaginosis.

Although human papillomavirus (HPV) infection plays a decisive role in causing tumors, its infection is insufficient for independently promoting cancer development and other co-factors facilitate the carcinogenic process. The objective of this study was to demonstrate the association between vaginal microbiota and high-risk human papillomavirus (HR-HPV) infection in women with and without bacterial vaginosis (BV). The study included 1015 women aged 21-64 who participated in cervical cancer screening in two areas of China from 2018 to 2019. Women were collected cervical exfoliated cell specimens and reproductive tract secretions samples for HR-HPV, BV and microbial composition testing. From the non-BV & HPV- group (414 HPV-negative women without BV) to the non-BV & HPV+ group (108 HPV-positive women without BV), to the BV & HPV-group (330 HPV-negative women with BV) and then to the BV & HPV+ group (163 HPV positive-women with BV), microbial diversity increased. The relative abundance of 12 genera, including Gardnerella, Prevotella, and Sneathia increased, while Lactobacillus declined. Correlation networks of these genera and host characteristics were disrupted in the non-BV & HPV+ group, and the network trended more disordered in the BV & HPV+ group. Besides, multiple HPV infection, certain HPV genotype infection and cervical intraepithelial neoplasia (CIN) status were associated with some microbes and higher microbial diversity. HPV shifted the composition and diversity of vaginal microbiota, and BV further reinforced the trend. The relative abundance of 12 genera increased and 1 genus decreased on account of BV and HPV infection, and some genera including Lactobacillus, Prevotella, and Sneathia were associated with some specific HPV genotypes infection and CIN.

Sociodemographic and Behavioral Predictors of Recurrent Bacterial Vaginosis Among Sexual Health Clinic Patients in New York City From 2014 to 2018.

OBJECTIVE: Bacterial vaginosis (BV) is associated with adverse reproductive outcomes, and recurrence is common. We examined factors associated with BV recurrence using electronic medical record data for patients attending New York City Department of Health and Mental Hygiene sexual health clinics from 2014 to 2018. METHODS: Clinician-diagnosed BV was defined using a clinical BV diagnosis code based on Amsel criteria. Recurrent BV was defined as any BV diagnosis occurring more than 30 days after the previous diagnosis. Adjusted hazard ratios (AHRs) for the relationship between potential risk factors and recurrent BV were estimated using conditional gap-time models. RESULTS: The data set contained 14,858 patients with at least one BV diagnosis. Of these, 46.3% (n = 6882) had at least 1 follow-up visit to a sexual health clinic between January 2014 and December 2018. Of those with a follow-up visit, 53.9% (n = 3707) had ≥1 recurrent BV episode, with 33.7% (n = 2317) experiencing recurrence within 3 months. In the multivariable model, using a hormonal intrauterine device (IUD; AHR, 1.31; 95% confidence interval [CI], 1.14-1.49) or copper IUD (AHR, 1.17; 95% CI, 1.01-1.37), having a history of trichomonas (AHR, 1.23; 95% CI, 1.12-1.36), and being non-Hispanic Black (AHR, 1.11; 95% CI, 1.04-1.18) were associated with a higher risk of BV recurrence, whereas using non-IUD hormonal contraception was associated with reduced risk (AHR, 0.88; 95% CI, 0.80-0.98). CONCLUSIONS: Risk of BV recurrence was increased among patients using an IUD, whereas it was reduced in patients using non-IUD hormonal contraception.