Bacterial vaginosis diagnosed from first void urine specimens

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1 JCM Accepts, published online ahead of print on 6 November 2013 J. Clin. Microbiol. doi: /jcm Copyright 2013, American Society for Microbiology. All Rights Reserved. 1 Full length paper Bacterial vaginosis diagnosed from first void urine specimens Running title: Bacterial vaginosis diagnosis from urine Raluca Datcu 1, Dionne Gesink 2, Gert Mulvad 3, Ruth Montgomery-Andersen 4, Elisabeth Rink 5, Anders Koch 1, Peter Ahrens 1, Jørgen Skov Jensen #1 1 Statens Serum Institut, Copenhagen, Denmark, 2 University of Toronto, Dalla Lana School of Public Health, Toronto, Ontario, Canada, 3 Centre for Primary Care, Nuuk Greenland, 4 University of Greenland, Nuuk, Greenland, 5 Montana State University, Bozeman, Montana, USA. # Corresponding author: Jørgen Skov Jensen, MD, PhD, and DMedSci Statens Serum Institut Artillerivej 5 DK 2300 Copenhagen S, Denmark Microbiology and Infection Control STI, Research and Development Phone jsj@ssi.dk 1

2 Abstract Bacterial vaginosis (BV) is traditionally diagnosed using vaginal samples. The aim of this study was to investigate whether BV can be diagnosed from first void urine (FVU) Self-collected vaginal smears, vaginal swabs and FVU were obtained from 176 women. BV was diagnosed by Nugent s criteria. The FVU and vaginal swabs were analysed by quantitative PCRs (qpcrs) for selected vaginal bacteria (Atopobium vaginae, Prevotella spp., Gardnerella vaginalis, Bacterial Vaginosis-Associated Bacterium 2, Eggerthella-like bacterium, Leptotrichia amnionii, Megasphaera type 1) and all had an area under Receiver Operating Characteristic (ROC) curve >85%, suggesting good prediction of BV according to Nugent score. All seven bacteria in FVU were significantly associated with BV in univariate analysis. An accurate diagnosis of BV from urine was obtained in this population by a combination of qpcr for Megasphaera type 1 and/or Prevotella spp. The same two bacteria remained significantly associated with BV in a multivariate model after adjusting for the other five species. No statistically significant difference was found between the sensitivity and specificity of BV diagnosis by molecular methods performed on swabs and FVU samples. A linear regression analysis showed good agreement between bacterial load from swabs and FVU, but Prevotella spp. could be detected in high numbers in a few FVU samples without being present in swabs. This method will allow diagnosis of BV in studies where only urine has been collected and where detection of BV is considered relevant. 2

3 Introduction Bacterial vaginosis (BV) is an alteration of the normal Lactobacillus spp. dominated vaginal flora towards a more diverse bacterial flora with disappearance of the lactobacilli. The BV flora include anaerobes such as Gardnerella vaginalis, Prevotella spp., Peptostreptococcus spp., Mobiluncus spp., and several uncultured species e.g. bacterial vaginosis-associated bacteria (BVAB) 1, 2, 3, and TM7, Megasphaera spp., and Eggerthella-like uncultured bacterium (8,10). The classical and most commonly used algorithms for diagnosing BV are represented by clinical and microscopic classification criteria. The former were established by Amsel (1) and consist of a set of four characteristics including a homogenous, white vaginal discharge, a fishy odour of the vaginal discharge before or after addition of 10% potassium hydroxide, ph of the vaginal fluid elevated above 4.5 and the presence of clue-cells (squamous epithelial cells covered with adherent bacteria). At least three of the four criteria must be present to diagnose BV. Different microscopy scores to diagnose BV have been established, some of them based on Gram stained vaginal smears (15,18,25) and others based on wet-smear microscopy (9,22). Among these, the criteria published by Nugent are the most widely used and considered the gold standard of diagnosing BV. Several studies on the diagnosis of BV using PCR have been published recently (4,6,11,17,23), but all these have used PCR for BV-associated bacteria in vaginal swabs. In some studies, vaginal swabs are not collected, and first-void-urine (FVU) may be the only material from which BV can be diagnosed. In most settings, pregnant women are traditionally screened for glucose and leucocytes in urine, and thus, urine would be easy to collect for BV studies. Therefore, we aimed to determine whether BV can be diagnosed from FVU by PCR using a panel of BV- 3

4 associated bacteria that were the most sensitive and specific in predicting BV in vaginal swabs when compared to Nugent score after applying Receiver Operating Characteristic (ROC) curve analysis (6). ROC curve analysis establishes threshold/cut-off for optimal diagnosis of BV by qpcr by analysing samples with known normal and BV flora as determined by Nugent score. We refer to results that consider cut-offs as quantitative detection, while positive/negative (presence versus absence) results are referred to as qualitative detection. Materials and Methods Study population and specimens The population used in the present study was selected from Inuulluataarneq (the Greenland Sexual Health Project), which included 314 residents (196 women and 118 men) from Nuuk and Sisimiut between July 2008 and November Participants were recruited from the general population via the population registry and by direct contact via telephone calls and by advertising in local media as previously described (12).The initial objective of this study was to determine the epidemiology of STIs (12) and BV in Greenland (6). Each participant completed an interviewer-administered sexual health survey in either Greenlandic or Danish and provided a self-obtained vaginal smear, a vaginal swab sample collected with a flocked swab in Copan UTM (Copan, Brescia, Italy) and a FVU collected in GeneLock transport medium (Sierra Molecular Corp., Sonora, CA, USA) as previously described (12). 4

5 Ethics The study was approved by the Greenland Ethics Committee and by the University of Toronto Research Ethics Board in Canada. Study subjects provided written informed consent before participating in the study Microscopy Vaginal smears were Gram stained and diagnosed by Nugent score (18). Nugent scores 0-3 were considered representative of normal flora (Nugent grade I), 4-6 were considered intermediate (Nugent grade II), whereas scores of 7-10 were classified as BV (Nugent grade III). All slides were scored by the same investigator (RD) blinded to any clinical or laboratory results. DNA extraction and positive controls for PCR assays DNA from FVU was extracted as previously described (16). In brief, 1.9 ml of FVU was centrifuged at 30,000 x g for 15 min, and the pellet re-suspended in a 20% w/v Chelex slurry (BioRad, Hercules, CA, USA) in TE buffer (10 mm Tris-HCl [ph 8.0], 1 mm EDTA). The samples were placed in a heating block at 95ºC for 10 minutes and condensation droplets were collected by a brief centrifugation. Positive controls for the PCRs were obtained by DNA extraction from cultures of Atopobium vaginae (CCUG T ), Leptotrichia amnionii (DSM 16630) (not a validly described species but referred to by this name in accordance with the DSM designation), G. vaginalis (ATCC 3717 T ) and P. bivia (clinical isolate identified by biochemical properties and MALDI-TOF). For the uncultured bacteria BVAB 2, Megasphaera type 1 and Eggerthella-like bacterium, the 16S rrna gene PCR product from a positive clinical sample was used as positive control after gelpurification and DNA sequencing for verification (6). Standard curves for quantitative 5

6 PCRs were generated using 10-fold dilutions from 10 7 genome equivalents (geq)/µl to 1 geq/µl in TE buffer containing 1 µg/ml of calf thymus DNA (D-8661; Sigma- Aldrich) PCR analyses qpcrs for A. vaginae, L. amnionii, BVAB 2, Megasphaera type 1, Eggerthella-like bacterium, G. vaginalis and Prevotella spp. were performed using primers and reaction conditions as previously described (6). Statistical Methods ROC curve analysis was used to calculate the bacterial load that provided the optimal cut-off for diagnosing BV in FVU weighing sensitivity and specificity equally and considering normal flora and BV as diagnosed by Nugent score as gold standard. Fisher s exact test (univariate analysis) with odds ratios and confidence intervals was used to evaluate whether each studied bacterium in the FVU sample was significantly associated with BV (before and after applying ROC curve analysis). Spearman correlation analysis was used to examine the correlation between detection of bacteria in swabs and from FVU samples. Cohen s kappa (weighted) was used to measure the agreement between methods for diagnosing BV (Nugent score and molecular methods performed on swabs and FVU samples). McNemar test for matched pairs was used to compare differences in sensitivity and specificity between diagnosing BV from swabs and urines. These statistical analyses were performed in StatsDirect version (StatsDirect Ltd., Cheshire, UK) Logistic regression analysis was applied in an adjusted model with seven variables with each bacterial species representing a variable with the purpose of determining the bacterial species optimally predicting BV. Data was used as log 10 of the copy 6

7 number plus one, and the outcome was represented by BV (as diagnosed by Nugent score). Logistic regression analysis, linear regressions, comparisons between slopes and Cochran-Armitage trend test were performed in SAS version 9.2 (SAS Institute Inc. Cary, NC, USA) Results Scatter plots and graphs illustrating linear regressions were created in GraphPad Prism version The correlation between the presence of the seven studied species in FVU determined by Spearman correlation coefficients and a co-occurrence heat-map of bacterial taxa was created by using the standard correlation orders in the R program package version (The R Foundation for Statistical Computing). Significance level was 5 %, two-sided throughout. From a total of 196 women enrolled in the The Greenland Sexual Health Survey, 176 participants were included in the present analysis, as they provided vaginal swabs, suitable vaginal smears and FVU. Seventy-three women (42%) had normal vaginal flora, 25 (14%) had intermediate flora and 78 (44%) had BV by Nugent s criteria. Median age was 24 years (range 15-65). STI prevalence was 12 % M. genitalium, 7 % C. trachomatis, 1 % N. gonorrhoeae, and 0.5 % T. vaginalis (12). No questions were asked about contraceptive use, douching or recent antibiotic use. However, douching is not considered to be a common practice in Greenland (Ruth Montgomery-Andersen, personal communication). Six participants were in the age range years, presumably post-menopausal women, but no questions about age of menopause were asked. Twelve women were registered as having no history of male or female sex partners and four of them were diagnosed with BV by Nugent. 7

8 Seven women reported having STIs symptoms, but only 89 answered this question and 15 of them did not know (6) Determination of bacterial load cut-off in urine for optimal BV prediction The sensitivity and specificity of the seven assays for BV associated bacteria in urine (A. vaginae, Prevotella spp., G. vaginalis, BVAB2, Eggerthella-like bacterium, L. amnionii, Megasphaera type 1) were estimated using Nugent score. The assays showed sensitivities between %, but specificities of only 7 78 % by qualitative detection (+/- presence, Table 1). Intermediate flora was excluded from the evaluation. ROC curve analysis was used to determine the optimal cut-off for the number of gene copies/ml urine for women with and without BV, weighing sensitivity and specificity equally. For all seven bacteria, the sensitivity and specificity before and after ROC (qualitative and quantitative detection, respectively) were calculated for 78 participants with BV and 73 participants without BV. All seven bacterial species had area under the curve (AUC) 88 % suggesting a good diagnostic performance (19). In descending order, their AUC was: G. vaginalis (98%), A. vaginae (97%), Prevotella spp. (96%), BVAB2 (95%), Eggerthella-like bacterium (94%), Megasphaera type 1 (91%) and L. amnionii (88%). In quantitative detection, G. vaginalis had a sensitivity of 92% followed by A. vaginae with 91% and Prevotella spp. with 90% whereas the highest specificities were found for Eggerthella-like bacterium (100%), Megasphaera type 1 (99%), and A. vaginae (99%). Differences in sensitivities or specificities of PCRs using swabs versus the use of FVU samples were not significant. 8

9 Each of the seven bacteria were significantly associated with BV in univariate analysis (Table 1), but the odds for BV increased dramatically when quantitative detection was introduced, reaching an OR of 730 (95% CI: ) for A. vaginae Diagnostic characteristics of different combinations of PCR assays for detection of vaginal bacteria are presented in Table 2. Relationship between PCR results from urine and swabs and microscopy For all seven bacteria, the bacterial load in urines increased significantly with the progression from normal to BV flora (p < ) (Figure 1). Women with BV had significantly higher bacterial load in swabs than in urines, except for Prevotella spp. (Figure 1). Considering all women regardless of BV-status, the bacterial load was significantly higher in swabs than in urines for L. amnionii, Eggerthella-like bacterium, and G. vaginalis, but the difference was not statistically significant for the remaining four bacteria analyzed. A significantly increasing trend in the positive rate was found with increasing BV grade in qualitative detection for all species except G. vaginalis, and in quantitative detection for all seven bacteria (Table 3). The proportion of women with each of the seven species detected in urine according to the Nugent grade is shown in Table 3 for both qualitative and quantitative detection. G. vaginalis, Prevotella spp. and A. vaginae were present in almost all women with BV (100 %, 100 % and 97 %, respectively) in qualitative detection and in the highest proportions in quantitative detection (92 %, 90 % and 91 %, respectively) (Table 3). This is in good agreement with their AUCs which were also the highest when calculated according to Nugent score (Table 1). 9

10 In order to correlate the bacterial load in vaginal swabs and urine, linear regression analysis was performed for each species after log transformation of the bacterial load with vaginal bacterial load as the predictor (Figure 2, Table 4). When comparing the slopes pairwise, most were similar, however ten comparisons had slopes which were statistically different (marked with a star in Table S1 supplementary) and all were comparisons involving Prevotella spp. or BVAB2. The slope for Prevotella spp. was significantly different from all other bacteria. The slope for BVAB2 was different from A. vaginae, Megasphaera type 1, Eggerthella-like bacterium and G. vaginalis (Table 5). Prevotella spp. and BVAB2 differed mainly by the presence of these taxons in high numbers in some FVU samples from women with negative results from swabs (Figure 2). The highest correlation between bacterial load in swabs and FVU samples was found for A. vaginae with r=0.84, while the lowest correlation of 0.71 was found for Prevotella spp. (Table 4). Co-occurrence of bacterial taxa in urine was investigated by calculating Spearman correlation coefficients (Figure 3, Dataset S2, supplementary). The lowest correlation coefficient was 0.57 between Megasphaera type 1 and Prevotella spp. The highest positive correlation was found between A. vaginae and G. vaginalis with a value of 0.88 (Dataset S2, supplementary, Figure 3). Generally, a good or very good agreement was found between Nugent scoring and molecular diagnosis of BV by each bacterial species both from FVU (Cohen s kappa (weighted) ), and swabs (kappa ) and also between FVU and swabs ( ) and a very good agreement was found when all three diagnostic methods were compared (Table 6)

11 Associations between different vaginal bacteria in urine and BV In a multivariate logistic regression model considering the seven bacteria as variables, only Megasphaera type 1 and Prevotella spp. remained statistically significantly associated with BV, with p- values of 0.01 and 0.04 and odds-ratios of 3.6 and 4.3, respectively (Table 5) after adjusting for the other bacteria. Discussion To the best of our knowledge, this is the first study to investigate the possibility of diagnosing BV from first void urine by using species/genus specific, qpcr. A study using fluorescent in-situ hybridisation (FISH) of G. vaginalis biofilm in cells harvested from urine was recently reported (24), but a detailed validation of this approach was not presented. In the present study, seven BV-associated bacteria (A. vaginae, Prevotella spp., G. vaginalis, BVAB2, Eggerthella-like bacterium, L. amnionii, and Megasphaera type 1) were selected, as they had demonstrated good discriminatory power in diagnosing BV from swabs (6,23), with areas under ROC curves > 85%. A Prevotella spp. assay was chosen in order to limit the number of assays needed to cover this species as several species of this genus can be found in the vagina. With the high sensitivity of this assay, this approach appeared successful. qpcrs for these bacteria were performed on paired vaginal swabs and first void urine specimens and all seven AUCs were > 85% in ROC curve analysis, when considering normal flora and BV by Nugent s criteria. None of the assays had a perfect sensitivity and specificity and mainly the specificity was the limiting factor. Consequently, combinations of assays were tried in order to maximise both parameters. However, increasing sensitivity by combining assays 11

12 always led to a decrease in specificity. One of the best combinations was detection of Megasphaera type 1 or Prevotella spp., which improved the sensitivity to 99 %, while maintaining a good specificity of 95 %. Thus, performing only these two qpcrs can diagnose BV from urine with a very high precision in this particular population. It is important to note, however, that cut-off levels as well as optimal combinations of assays may vary in different populations and depending on DNA extraction method and other assay related factors. The finding that combinations of assays were needed to obtain optimal sensitivity also suggest that BV can be classified into subgroups dominated by different BV associated bacteria (6) Compared to the diagnosis of BV by molecular methods from swab samples, first void urine had a similar diagnostic performance with kappa values reaching 0.89 for A. vaginae and G. vaginalis All seven bacteria in urine were significantly associated with BV both in qualitative and quantitative detection in univariate analysis, while only Megasphaera type 1 and Prevotella spp. remained significantly associated with BV in a multivariate logistic regression model. This was in contrast to the findings in swabs from the same women where A. vaginae and Prevotella spp. were associated with BV in the multivariate analysis. The reason for this discrepancy remains unclear, but may be explained by the relatively higher load of Prevotella spp. in FVU from women without BV as compared to the paired vaginal swab specimens. The bacterial load of each species in FVU increased with increasing Nugent score and the highest median load in urine was found for Prevotella spp. for women with BV. For determination of the optimal cut-off quantity by ROC curve analysis, samples with intermediate (Nugent grade II) were excluded. Whether the possibility to dichotomize intermediate flora will make disease associations clearer in future 12

13 studies remains to be seen. As expected, the median DNA load in swabs was higher than the corresponding load in FVU specimens for all seven species, but for all the assays a linear correlation between the vaginal and urine bacterial load could be found. It seems likely, therefore, that the DNA load detected in the FVU specimen mainly represent vaginal secretions washed out by the urine more than a urinary tract infection, although the latter possibility should be considered in future studies on mid-stream urine. With DNA loads for all seven species exceeding 10 8 copies per ml of FVU in some specimens, the possibility that colonization of the bladder epithelium may occur should not be excluded. Swidsinsky et al. recently reported that G. vaginalis biofilm could be demonstrated in the endometrium, and even in the fallopian tubes of one out of four women with BV (24). In that study, the BV diagnosis was based on the detection of vaginal epithelial cells in FVU, carrying a typical G. vaginalis biofilm as demonstrated by FISH with a species specific probe. However, the presence of other cell morphologies was not reported. The possibility of colonization of the bladder was supported in our study by the finding of five women having negative swab samples for Prevotella spp. but still having high DNA loads in the FVU with a median of 1.8 x 10 5 copies/ml (range 1.8 x 10 3 to 10 7 copies / ml). Unfortunately, no information about leucocyturia was collected, and no symptoms were recorded. It has earlier been shown that BV is associated with an increased risk of urinary tract infections (14) and urinary tract infections caused by G. vaginalis afflict women more often than men (5). Systemic infections caused by BV-associated bacteria, such as G. vaginalis are described far more often in women (21) than in men (26,27). Similarly, pigmented Prevotella sp. and L. amnionii have been isolated by culture or detected by PCR in urine specimens (2,7). It has been suggested that lactobacillus 13

14 probiotics such as vaginal suppositories may be effective in reducing the recurrence of UTIs following antimicrobial therapy and in maintaining a normal microflora (3,20); however, in a recent meta-analysis (13) it was concluded that the number of trials was small and that more studies are needed before recommendations can be given. In conclusion, BV can be diagnosed with high accuracy from FVU using cut-offs as determined by ROC curve analysis. However, a combination of qpcr results for two bacteria such as Megasphaera type 1 and/or Prevotella spp. increases sensitivity or specificity depending on the combination. The possibility of using FVU as a diagnostic specimen may not gain widespread use, as vaginal swabs are very easy to obtain, even as a self-collected sample, but in particular settings it may prove useful. This may also allow analysis of stored FVU specimens collected as part of studies on classical STI pathogens where BV was not considered initially. Acknowledgments Christina Nørgaard, Birthe Dohn and Susanne Cramer Larsson are thanked for valuable technical assistance. No author had any conflict of interest, either financial or personal. 14

15 332 Figure legends Figure 1. Bacterial load expressed as 16S rrna gene copies/ml in swabs and urines from 73 women with normal flora, 25 women with intermediate flora and 78 women with BV as diagnosed by Nugent s score. The median bacterial load is marked with a horizontal bar for each group. Figure 2. Correlation between the bacterial load in swabs and urines. For each bacterium a regression line for the correlation between the log10 of 16S rrna gene copies per ml plus one in swabs versus FVU. Nugent grades of vaginal smears are shown in color. The lower right graph shows the 7 regression lines in the same graph for easier comparison. Figure 3. Hierarchically clustered Spearman correlation coefficients between bacterial species in urine showing co-occurrence of species. Correlation coefficients range from 0.57 to 1. A table with the coefficients is available in Table S2 (supplementary material). Conclusion and discussion Reference List 1. Amsel, R., P. A. Totten, C. A. Spiegel, K. C. Chen, D. Eschenbach, and K. K. Holmes Nonspecific vaginitis. Diagnostic criteria and microbial and epidemiologic associations. Am J Med 74: Brook, I Urinary tract and genito-urinary suppurative infections due to anaerobic bacteria. Int.J Urol. 11: Bruce, A. W. and G. Reid Intravaginal instillation of lactobacilli for prevention of recurrent urinary tract infections. Can.J.Microbiol. 34: Cartwright, C. P., B. D. Lembke, K. Ramachandran, B. A. Body, M. B. Nye, C. A. Rivers, and J. R. Schwebke Development and validation of a semiquantitative, multitarget PCR assay for diagnosis of bacterial vaginosis. J.Clin.Microbiol. 50: Catlin, B. W Gardnerella vaginalis: characteristics, clinical considerations, and controversies. Clin.Microbiol.Rev. 5:

16 Datcu, R., D. Gesink, G. Mulvad, R. Montgomery-Andersen, E. Rink, A. Koch, P. Ahrens, and J. S. Jensen Vaginal microbiome in women from Greenland assessed by microscopy and quantitative PCR. BMC Infectious Diseases 13: Domann, E., G. Hong, C. Imirzalioglu, S. Turschner, J. Kuhle, C. Watzel, T. Hain, H. Hossain, and T. Chakraborty Culture-independent identification of pathogenic bacteria and polymicrobial infections in the genitourinary tract of renal transplant recipients. J Clin Microbiol. 41: Donders, G Diagnosis and management of bacterial vaginosis and other types of abnormal vaginal bacterial flora: a review. Obstet.Gynecol.Surv. 65: Donders, G. G Microscopy of the bacterial flora on fresh vaginal smears. Infect.Dis.Obstet.Gynecol. 7: Fredricks, D. N., T. L. Fiedler, and J. M. Marrazzo Molecular identification of bacteria associated with bacterial vaginosis. N Engl J Med 353: Fredricks, D. N., T. L. Fiedler, K. K. Thomas, B. B. Oakley, and J. M. Marrazzo Targeted PCR for detection of vaginal bacteria associated with bacterial vaginosis. J Clin Microbiol 45: Gesink, D. C., G. Mulvad, R. Montgomery-Andersen, U. Poppel, S. Montgomery-Andersen, A. Binzer, L. Vernich, G. Frosst, F. Stenz, E. Rink, O. R. Olsen, A. Koch, and J. S. Jensen Mycoplasma genitalium presence, resistance and epidemiology in Greenland. Int.J.Circumpolar.Health 71: Grin, P. M., P. M. Kowalewska, W. Alhazzan, and A. E. Fox-Robichaud Lactobacillus for preventing recurrent urinary tract infections in women: meta-analysis. Can J Urol. 20: Harmanli, O. H., G. Y. Cheng, P. Nyirjesy, A. Chatwani, and J. P. Gaughan Urinary tract infections in women with bacterial vaginosis. Obstet.Gynecol. 95: Ison, C. A. and P. E. Hay Validation of a simplified grading of Gram stained vaginal smears for use in genitourinary medicine clinics. Sex Transm.Infect 78: Jensen, J. S., E. Björnelius, B. Dohn, and P. Lidbrink Use of TaqMan 5' nuclease real-time PCR for quantitative detection of Mycoplasma genitalium DNA in males with and without urethritis who were attendees at a sexually transmitted disease clinic. J.Clin.Microbiol. 42: Menard, J. P., F. Fenollar, M. Henry, F. Bretelle, and D. Raoult Molecular quantification of Gardnerella vaginalis and Atopobium vaginae loads to predict bacterial vaginosis. Clin.Infect.Dis. 47: Nugent, R. P., M. A. Krohn, and S. L. Hillier Reliability of diagnosing bacterial vaginosis is improved by a standardized method of gram stain interpretation. J Clin Microbiol 29: Obuchowski, N. A Receiver operating characteristic curves and their use in radiology. Radiology 229: Reid, G., A. W. Bruce, and M. Taylor Influence of three-day antimicrobial therapy and lactobacillus vaginal suppositories on recurrence of urinary tract infections. Clin.Ther. 14: Reimer, L. G. and L. B. Reller Gardnerella vaginalis bacteremia: a review of thirty cases. Obstet Gynecol 64:

17 Schmidt, H. and J. G. Hansen Diagnosis of bacterial vaginosis by wet mount identification of bacterial morphotypes in vaginal fluid. Int.J STD AIDS 11: Shipitsyna, E., A. Roos, R. Datcu, A. Hallen, H. Fredlund, J. S. Jensen, L. Engstrand, and M. Unemo Composition of the vaginal microbiota in women of reproductive age - sensitive and specific molecular diagnosis of bacterial vaginosis is possible? PLoS.One. 8:e Swidsinski, A., H. Verstraelen, V. Loening-Baucke, S. Swidsinski, W. Mendling, and Z. Halwani Presence of a polymicrobial endometrial biofilm in patients with bacterial vaginosis. PLoS.One. 8:e Verhelst, R., H. Verstraelen, G. Claeys, G. Verschraegen, L. Van Simaey, C. De Ganck, E. De Backer, M. Temmerman, and M. Vaneechoutte Comparison between Gram stain and culture for the characterization of vaginal microflora: Definition of a distinct grade that resembles grade I microflora and revised categorization of grade I microflora. BMC Microbiology 5: Wilson, J. A. and A. J. Barratt An unusual case of Gardnerella vaginalis septicaemia. Br.Med.J. 293: Yoon, H. J., J. Chun, J. H. Kim, S. S. Kang, and D. J. Na Gardnerella vaginalis septicaemia with pyelonephritis, infective endocarditis and septic emboli in the kidney and brain of an adult male. Int.J STD AIDS 21: Downloaded from on December 27, 2018 by guest 17

18 419 TABLE 1. Sensitivity (Se) and specificity (Sp) before (qualitative detection) and after ROC curve analysis (quantitative 420 detection). 421 Species Qualitative detection Quantitative detection Area under ROC curve Se (%) 95%CI Sp (%) 95%CI OR a 95%CI b P- value Se (%) 95%CI Sp (%) 95%CI Cut-off copies/ml urine OR 95% CI P-value Size 95%CI Atopobium vaginae < < Leptotrichia amnionii < < BVAB < < Megasphaera type < < Eggerthella-like bacterium < < Gardnerella vaginalis < Prevotella spp < a Odds-ratios (OR) and b 95% confidence intervals (CI) for each bacterial species for BV detection in FVU by Fisher's exact test after qualitative or quantitative detection. A total of 78 urine samples from women with Nugent grade III (BV) and 73 urines from women with Nugent grade I (normal flora) were used for the evaluation. Intermediate flora not included. 18

19 TABLE 2. Diagnostic performance for quantitative detection (cut-off determined by ROC curve analysis) for combinations of bacteria. Combination of bacteria Sensitivity (%) Specificity (%) A. vaginae and Prevotella spp A. vaginae or Prevotella spp Megasphaera type 1 and Prevotella spp Megasphaera type 1 or Prevotella spp A. vaginae and Megasphaera type 1 and Prevotella spp A. vaginae or Megasphaera type 1 or Prevotella spp A. vaginae and Megasphaera type 1 and Eggerthella-like bacterium A. vaginae or Megasphaera type 1 or Eggerthella-like bacterium

20 434 TABLE 3. Rate of detection of seven bacterial species in urine. 435 Nugent I (0-3) Nugent II (4-6) Nugent III (7-10) P-values for trend n=73 n=25 n c = a Qualitative detection n(%) b Quantitative detection n(%) Qualitative detection n(%) Quantitative detection n(%) Qualitative detection n(%) Quantitative detection n(%) Qualitative detection Quantitative detection A. vaginae 54 (74) 1 (1) 20 (80) 10 (40) 76 (97) 71 (91) < L. amnionii 23 (32) 3 (4) 12 (48) 6 (24) 65 (83) 61 (78) < < BVAB 2 16 (22) 2 (3) 15 (60) 9 (36) 72 (92) 69 (88) < < Megasphaera type 1 35 (48) 1 (1) 15 (60) 10 (40) 70 (90) 63 (81) < < Eggerthellalike 17 (23) 0 (0) 16 (64) 8 (32) 71 (91) 68 (87) < < bacterium G. vaginalis 68 (93) 2 (3) 22 (88) 11 (44) 78 (100) 72 (92) 0.11 < Prevotella spp. 67 (92) 3 (4) 25 (100) 10 (40) 78 (100) 70 (90) < a Before applying cut-offs (presence versus absence). b After applying cut-offs as determined by ROC curve analysis by Nugent s criteria (positive cut-off, negative < cut-off). c n indicates number of participants 20

21 TABLE 4. Spearman correlation coefficient a with 95% confidence intervals (CI) b for seven species in swabs and urines. Species Correlation Coefficient a 95% CIb P-value Intercept c Slope d Atopobium vaginae < Leptotrichia amnionii < BVAB < Megasphaera type < Eggerthella-like uncultured bacterium < Gardnerella vaginalis < Prevotella spp < c Intercept and d slope on regression lines using log data. Downloaded from on December 27, 2018 by guest 21

22 TABLE 5. Adjusted odds-ratios with 95 % confidence intervals (CI) and p-values after multivariate logistic regression analysis a for seven bacterial species b. Logistic Regression Model Species Adjusted OR 95% CI p-value Atopobium vaginae Leptotrichia amnionii BVAB Megasphaera type Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp a Analysis based on 78 women with BV and 73 women with normal vaginal flora by Nugent score. b Data are log 10 of number of 16S rrna gene copies per ml plus one. 22

23 TABLE 6. Cohen s kappa a for agreement between BV diagnosis by Nugent scoring b and molecular methods using quantitative results. Cohen s kappa Species (weighted) Cohen s kappa Nugent-Urine Nugent-Swab Urine-Swab Nugent-Urine-Swab Atopobium vaginae Leptotrichia amnionii BVAB Megasphaera Eggerthella-like bacterium Gardnerella vaginalis Prevotella genus a Kappa > is considered good agreement between observations. Kappa > 0.8 is considered very good agreement between observations. b Intermediate flora is excluded from these analyses. Downloaded from on December 27, 2018 by guest 23

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26 Correlation coefficient Eggerthella BVAB2 G.vaginalis A.vaginae L.amnionii Megasphaera 1 spp. Prevotella A.vaginae G.vaginalis BVAB2 Eggerthella Downloaded from Prevotella spp. Megasphaera 1 L.amnionii on December 27, 2018 by guest