International Journal of Clinical Case Reports, 2025, Vol.15, No.2, 52-58 http://medscipublisher.com/index.php/ijccr 54 different movement patterns. The International Continence Society (ICS) recognizes sEMG as an important indicator for the early diagnosis and prediction of PFD (Halski et al., 2017; Li et al., 2022). This study used the MLDB2 pelvic floor rehabilitation device produced by the Medlander company. The device incorporates the internationally recognized Glazer assessment protocol, which records pelvic floor muscle electrical activity in different fiber groups during pre-resting, fast-twitch, slow-twitch, and post-resting phases using electromyography. It then quantifies the surface EMG values of different pelvic floor muscle fibers to generate a composite score. All patients underwent a surface EMG assessment before and after treatment, with no statistically significant differences in baseline pre-treatment pelvic floor EMG scores. 2.3 Data collection methods Two researchers extracted data from the hospital information system for primiparous women who met the inclusion and exclusion criteria. The collected information included patient age, pregnancy weight gain (kg), perineal tear status, neonatal birth weight (kg), and pelvic floor electrophysiology assessment scores at 6 weeks to 6 months postpartum (both pre-treatment and post-treatment). 2.4 Statistical analysis Statistical analyses were performed using SPSS 22.0 software. Normal continuous variables were expressed as mean ± standard deviation (±s) and analyzed using descriptive statistics. Both compliance scores for pelvic floor therapy and electrophysiology scores were continuous variables that followed a normal distribution, allowing Pearson correlation analysis to be used for correlation assessment. Multivariate linear hierarchical regression analysis was performed to control for confounding factors and accurately determine the independent impact of compliance with pelvic floor electrical stimulation combined with biofeedback therapy on electrophysiology scores. 3 Results and Analysis 3.1 Basic characteristics of the study subjects A total of 184 primiparous women who underwent natural delivery were included in this study. The mean age ranged from 23 to 49 years, with an average of (33.40 ± 4.512) years. The average pregnancy weight gain was (11.522 ± 3.721) kg, and the mean neonatal birth weight was (3.263 ± 0.428) kg. Perineal wound conditions were classified as follows: no perineal tears in 16 cases (8.7%), first-degree perineal tears in 95 cases (51.6%), second-degree perineal tears in 42 cases (22.8%), third-degree perineal tears in 10 cases (5.4%), and episiotomy in 21 cases (11.4%). The mean compliance score for pelvic floor electrical stimulation combined with biofeedback therapy was (2.37 ± 1.377). Among the participants, 13 cases (7.1%) showed complete non-compliance (score=0), 42 cases (22.8%) scored 1 point, 45 cases (24.5%) scored 2 points, 51 cases (27.7%) scored 3 points, 14 cases (7.6%) scored 4 points, and only 19 cases (10.3%) fully adhered to the prescribed therapy. There was no statistically significant difference in baseline pelvic floor electrophysiology scores before treatment among all patients (P>0.05). 3.2 Analysis of differences in pelvic floor electrophysiology scores Since age, pregnancy weight gain, neonatal birth weight, and compliance were continuous variables, Pearson correlation analysis was used to determine their relationship with pelvic floor electrophysiology scores. The results indicated a significant negative correlation between pregnancy weight gain and pelvic floor electrophysiology scores (r=-0.367, P=0.000) and a significant positive correlation between compliance scores and pelvic floor electrophysiology scores (r=0.337, P=0.000). Other variables showed no statistically significant correlation with pelvic floor electrophysiology scores (P > 0.05). A one-way ANOVA was performed to analyze the association between perineal wound conditions and pelvic floor electrophysiology scores, showing no statistically significant difference (F=1.173, P=0.324). 3.3 Multivariate hierarchical linear regression analysis of pelvic floor electrophysiology To evaluate additional potential risk factors, all variables from the univariate analysis were included in a multivariate linear regression model. The pelvic floor electrophysiology score was set as the dependent variable.
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