Marco Soligo1, Stefania Livio2, Elena De Ponti3, Ileana Scebba2, Federica Carpentieri2, Maurizio Serati4, Enrico Ferrazzi2. 1. Department of Women, Mothers and Neonates, Buzzi Children's Hospital, ASST Fatebenefratelli Sacco, University of Milan, Milan, Italy. Electronic address: marcosoligo@fastwebnet.it. 2. Department of Women, Mothers and Neonates, Buzzi Children's Hospital, ASST Fatebenefratelli Sacco, University of Milan, Milan, Italy. 3. Medical Physics Department, ASST, Monza, Italy. 4. Department of Obstetrics and Gynaecology, Del Ponte Hospital, University of Insubria, Varese, Italy.
Abstract
OBJECTIVE: Pelvic floor dysfunction after delivery is quite common. New mothers deserve to receive targeted care for pelvic floor dysfunction, but how should women who are at risk be identified and selected for treatment? This study investigated risk factors and puerperal health-seeking behaviours to develop a restrictive patient selection model for postpartum pelvic floor dysfunction assessment. STUDY DESIGN: This prospective observational study involved women who were at ≥32 weeks gestational age when they delivered in a tertiary referral maternity hospital in Milan, Italy, between July and December 2014. Eligible women were scheduled for a 3-month postnatal pelvic floor clinic. The adherence rate to the pelvic floor clinic and the prevalence of pelvic floor dysfunctions at 3 months postpartum were recorded. Univariable and logistic multivariable analyses were performed to select risk factors for pelvic floor dysfunctions. Risk factors were then tested for sensitivity and specificity for 3-month postpartum pelvic floor dysfunctions. RESULTS: Of 1606 eligible women, 1293 (80.5%) were included in the analysis; 685 puerperal women (53.0%) adhered to the 3-month postnatal pelvic floor clinic; pelvic floor dysfunctions were detected in 238 women (34.7%). Four elements emerged as risk factors: symptoms before pregnancy (OR 1.72, 95% CI 1.15-2.56; p=0.008), symptoms during pregnancy (OR 2.13, 95% CI 1.49-3.06; p<0.0001), vacuum extractor use (OR 1.62, 95% CI 1.04-2.54; p=0.034), and severe perineal tears (OR 19.45, 95% CI 2.42-156.15; p=0.005). The combined sensitivity and specificity for the 4 risk factors were 82% and 39%, respectively. CONCLUSION: Internal risk factors analysis offers the potential to efficiently restrict patient selection for follow-up.
OBJECTIVE:Pelvic floor dysfunction after delivery is quite common. New mothers deserve to receive targeted care for pelvic floor dysfunction, but how should women who are at risk be identified and selected for treatment? This study investigated risk factors and puerperal health-seeking behaviours to develop a restrictive patient selection model for postpartum pelvic floor dysfunction assessment. STUDY DESIGN: This prospective observational study involved women who were at ≥32 weeks gestational age when they delivered in a tertiary referral maternity hospital in Milan, Italy, between July and December 2014. Eligible women were scheduled for a 3-month postnatal pelvic floor clinic. The adherence rate to the pelvic floor clinic and the prevalence of pelvic floor dysfunctions at 3 months postpartum were recorded. Univariable and logistic multivariable analyses were performed to select risk factors for pelvic floor dysfunctions. Risk factors were then tested for sensitivity and specificity for 3-month postpartum pelvic floor dysfunctions. RESULTS: Of 1606 eligible women, 1293 (80.5%) were included in the analysis; 685 puerperal women (53.0%) adhered to the 3-month postnatal pelvic floor clinic; pelvic floor dysfunctions were detected in 238 women (34.7%). Four elements emerged as risk factors: symptoms before pregnancy (OR 1.72, 95% CI 1.15-2.56; p=0.008), symptoms during pregnancy (OR 2.13, 95% CI 1.49-3.06; p<0.0001), vacuum extractor use (OR 1.62, 95% CI 1.04-2.54; p=0.034), and severe perineal tears (OR 19.45, 95% CI 2.42-156.15; p=0.005). The combined sensitivity and specificity for the 4 risk factors were 82% and 39%, respectively. CONCLUSION: Internal risk factors analysis offers the potential to efficiently restrict patient selection for follow-up.
Authors: Thomas G Gray; Holly Vickers; Swati Jha; Georgina L Jones; Steven R Brown; Stephen C Radley Journal: Int Urogynecol J Date: 2018-11-23 Impact factor: 2.894