Interstitial cystitis/bladder pain syndrome (ICBPS) may be related to an altered genitourinary microbiome. Our aim was to compare the vaginal and urinary microbiomes between premenopausal women with ICBPS and unaffected controls. This cross-sectional study screened premenopausal women with an O'Leary-Sant questionnaire (ICBPS if score ≥6 on either index; controls <6 on both). Women completed questionnaires on health characteristics, pelvic floor symptoms (OABq, PFDI-20), body image (mBIS), and sexual function (PISQ-IR). Bacterial genomic DNA was isolated from vaginal and clean-catch urinary specimens; the bacterial 16 rRNA gene was sequenced and analyzed using the QIIME pipeline. We performed UniFrac analysis (β-diversity) and generated Chao1 estimator (richness) and Simpson index (richness and evenness) values. We analyzed 23 ICBPS and 18 non-ICBPS patients. ICBPS patients had increased vaginal deliveries, BMI, and public insurance as well as worsened OAB-q, PFDI-20, mBIS, and PISQ-IR domain scores. Lactobacilli was the most abundant genus in both cohorts, and anaerobic or fastidious predominance was similar between groups ( p = 0.99). For both the urine and vagina specimens, Chao1 and Simpson indices were similar between ICBPS and unaffected women. Weighted and unweighted UniFrac analyses showed no differences between groups. A significant correlation existed between the urinary and vaginal Simpson indices in ICBPS women, but not in unaffected women. Premenopausal women with ICBPS, despite worsened socioeconomic indicators and pelvic floor function, were not found to have significantly different urinary and vaginal microbiomes compared to women without ICBPS.

For longitudinal data, the modeling of a correlation matrix R can be a difficult statistical task due to both the positive definite and the unit diagonal constraints. Because the number of parameters increases quadratically in the dimension, it is often useful to consider a sparse parameterization. We introduce a pair of prior distributions on the set of correlation matrices for longitudinal data through the partial autocorrelations (PACs), each of which vary independently over [−1,1]. The first prior shrinks each of the PACs toward zero with increasingly aggressive shrinkage in lag. The second prior (a selection prior) is a mixture of a zero point mass and a continuous component for each PAC, allowing for a sparse representation. The structure implied under our priors is readily interpretable for time-ordered responses because each zero PAC implies a conditional independence relationship in the distribution of the data. Selection priors on the PACs provide a computationally attractive alternative to selection on the elements of R or R−1 for ordered data. These priors allow for data-dependent shrinkage/selection under an intuitive parameterization in an unconstrained setting. The proposed priors are compared to standard methods through a simulation study and a multivariate probit data example. Supplemental materials for this article (appendix, data, and R code) are available online.

Summary In the modeling of longitudinal data from several groups, appropriate handling of the dependence structure is of central importance. Standard methods include specifying a single covariance matrix for all groups or independently estimating the covariance matrix for each group without regard to the others, but when these model assumptions are incorrect, these techniques can lead to biased mean effects or loss of efficiency, respectively. Thus, it is desirable to develop methods to simultaneously estimate the covariance matrix for each group that will borrow strength across groups in a way that is ultimately informed by the data. In addition, for several groups with covariance matrices of even medium dimension, it is difficult to manually select a single best parametric model among the huge number of possibilities given by incorporating structural zeros and/or commonality of individual parameters across groups. In this paper we develop a family of nonparametric priors using the matrix stick-breaking process of Dunson et al. (2008) that seeks to accomplish this task by parameterizing the covariance matrices in terms of the parameters of their modified Cholesky decomposition (Pourahmadi, 1999). We establish some theoretic properties of these priors, examine their effectiveness via a simulation study, and illustrate the priors using data from a longitudinal clinical trial.

No abstract

Women who remove their pessaries less often than once weekly have an increased prevalence of anaerobes at 3 months, but no difference in vaginal symptoms or pessary satisfaction.

Objectives This study aimed to determine if there are differences in (1) surgical procedures performed for pelvic organ prolapse (POP) and (2) rates of adverse events between racial groups. Methods We conducted a retrospective cohort study of women 18 years and older who underwent POP surgery using the 2005–2015 American College of Surgeons National Surgical Quality Improvement Program database. Race was categorized as Black, White, Hispanic, and other minority. Pelvic organ prolapse procedures were organized into 4 groups: (1) hysterectomy without concurrent POP procedures, (2) vaginal wall repair(s) only without apical suspension, (3) apical suspension with or without vaginal wall repair(s), and (4) obliterative procedures. Patient characteristics and rates of adverse events were noted. A multivariable logistic regression model was used to assess the association between patient race and surgical procedures performed for POP. Results We identified 48,005 women who met the inclusion criteria. Most women who underwent POP surgery were White (79.6% [n = 38,191]). Although only contributing to 4.7% (2,299) of the cohort, Black women experienced higher complication rates compared with White women (10.7% [246] for Black vs 8.9% [3,417] for White women, P < 0.01). Hispanic and other minority women were less likely to undergo an apical suspension than White women (adjusted odds ratios [aORs], 0.79 [0.75–0.84] for Hispanic women and 0.78 [0.71–0.86] for other minority women; P < 0.001 for both). Obliterative procedures were more likely to be performed in Black, in Hispanic, and especially in other minority women (aORs, 1.53 [1.20–1.92] for Black, 1.33 [1.12–1.58] for Hispanic, and 3.67 [3.04–4.42] for other minority women; P < 0.001 for all). Conclusions Racial differences exist among women who undergo POP surgery.

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The addition of a POP-based iPad™ application to the informed consent process for POP surgery did not improve patient comprehension immediately postcounseling and resulted in poorer retention of information 6 weeks after surgery compared with SVC alone.