Nomograma para predecir la disfunción del suelo pélvico posparto basado en ecografía y biomarcadores séricos FGF2 y...

To evaluate the utility of pelvic floor ultrasound combined with serum fibroblast growth factor 2 (FGF2) and heparin-binding protein (HBP) in assessing postpartum pelvic floor dysfunction (PFD), and to construct a nomogram model for prognostic prediction.

A retrospective study included 149 primiparous women at 42 days postpartum who underwent pelvic floor ultrasound at Wenzhou Central Hospital from January 2020 to December 2021. Participants were divided into a control group (cesarean section, 68 cases) and an observation group (vaginal delivery, 81 cases). Baseline characteristics, ultrasound parameters, and serum FGF2 and HBP levels were recorded. Incidence of PFD, defined as pelvic organ prolapse or stress urinary incontinence, was documented during 3-year follow-up. Correlations were analyzed, and univariate and multivariate logistic regression identified independent predictors. A nomogram was constructed and validated using ROC, calibration, and decision curve analyses.

Abnormal pelvic floor ultrasound findings were more frequent after vaginal delivery (64.2% vs. 52.9%). Quantitative ultrasound indices were significantly higher in the observation group, while serum FGF2 and HBP levels were significantly lower (all P < 0.05). Ultrasound indicators were negatively correlated with biomarker levels. During follow-up, 61 PFD cases occurred in the observation group and 22 in the control group. Independent risk factors included age ≥ 30 years, prenatal BMI ≥ 27 kg/m², vaginal delivery, no pelvic floor training, constipation during pregnancy, episiotomy, and neonatal birth weight ≥ 4 kg. The nomogram showed excellent discrimination (AUC=0.931, 95% CI: 0.892-0.970) and good calibration, with clinical benefit confirmed by decision curve analysis.

Ultrasound combined with serum FGF2 and HBP enables comprehensive assessment of postpartum pelvic floor function. The nomogram model provides accurate risk prediction and may guide early identification and intervention in high-risk women.