Pelvic floor muscle strength and influencing factors based on vaginal manometry among healthy women at different life stages: A multicentre cross-sectional study.

OBJECTIVE: To assess pelvic floor muscle (PFM) strength and influencing factors among healthy women at different life stages. DESIGN: Multicentre cross-sectional study. SETTING: Fourteen hospitals in China. POPULATION: A total of 5040 healthy women allocated to the following groups (with 1680 women per group): premenopausal nulliparous, premenopausal parous and postmenopausal. METHODS: The PFM strength was evaluated by vaginal manometry. Multivariate logistic regression was used to determine the influencing factors for low PFM strength. MAIN OUTCOME MEASURES: Maximum voluntary contraction pressure (MVCP). RESULTS: The median MVCP values were 36, 35 and 35 cmH2O in premenopausal nulliparous (aged 19-51 years), premenopausal parous (aged 22-61 years), and postmenopausal (aged 40-86 years) women, respectively. In the premenopausal nulliparous group, physical work (odds ratio, OR 2.05) was the risk factor for low PFM strength, which may be related to the chronic increased abdominal pressure caused by physical work. In the premenopausal parous group, the number of vaginal deliveries (OR 1.28) and diabetes (OR 2.70) were risk factors for low PFM strength, whereas sexual intercourse (<2 times per week vs. none, OR 0.55; ≥2 times per week vs. none, OR 0.56) and PFM exercise (OR 0.50) may have protective effects. In the postmenopausal group, the number of vaginal deliveries (OR 1.32) and family history of pelvic organ prolapse (POP) (OR 1.83) were risk factors for low PFM strength. CONCLUSIONS: Physical work, vaginal delivery, diabetes and a family history of POP are all risk factors for low PFM strength, whereas PFM exercises and sexual life can have a protective effect. The importance of these factors varies at different stages of a woman's life.

New model for predicting preterm delivery during the second trimester of pregnancy.

In this study, a new model for predicting preterm delivery (PD) was proposed. The primary model was constructed using ten selected variables, as previously defined in seventeen different studies. The ability of the model to predict PD was evaluated using the combined measurement from these variables. Therefore, a prospective investigation was performed by enrolling 130 pregnant patients whose gestational ages varied from 17+0 to 28+6 weeks. The patients underwent epidemiological surveys and ultrasonographic measurements of their cervixes, and cervicovaginal fluid and serum were collected during a routine speculum examination performed by the managing gynecologist. The results showed eight significant variables were included in the present analysis, and combination of the positive variables indicated an increased probability of PD in pregnant patients. The accuracy for predicting PD were as follows: one positive - 42.9%; two positives - 75.0%; three positives - 81.8% and four positives - 100.0%. In particular, the combination of ≥2× positives had the best predictive value, with a relatively high sensitivity (82.6%), specificity (88.1%) and accuracy rate (79.2%), and was considered the cut-off point for predicting PD. In conclusion, the new model provides a useful reference for evaluating the risk of PD in clinical cases.