Development of a Predictive Model for Maternal Satisfaction with Epidural Analgesia Based on Perinatal Complications

Development of a Predictive Model for Maternal Satisfaction with Epidural Analgesia Based on Perinatal Complications | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Development of a Predictive Model for Maternal Satisfaction with Epidural Analgesia Based on Perinatal Complications Yihan Zheng, Haiping Zhang, Xizhu Wu, Wenqiang You, Chuantao Lin, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7354374/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Maternal satisfaction with epidural analgesia (MSEA) is influenced by multiple factors. This study aimed to develop and validate a predictive model for MSEA based on perinatal complications associated with epidural analgesia, providing a tool for personalized analgesia protocols and enhanced childbirth experiences. We retrospectively analyzed clinical data from 2,221 parturients admitted to Fujian Maternity and Child Health Hospital (July 2023–March 2024). The cohort was randomly divided into training (1,555 cases) and internal validation (666 cases) sets at a 7:3 ratio. In the training set: Statistically significant variables were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Collinearity diagnostics assessed variable relationships. Univariate and multivariate logistic regression identified independent predictors of MSEA and constructed a nomogram. Validation: Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curves, Hosmer-Lemeshow test, and decision curve analysis (DCA) for clinical net benefit. The prevalence of maternal dissatisfaction with epidural analgesia was 15.80% (351/2,221). Independent risk factors included fever (OR = 1.83, 95% CI: 1.26–2.62, P = 0.001), nausea and vomiting (OR = 1.79, 95% CI: 1.23–2.58, P = 0.002), puncture pain (OR = 1.78, 95% CI: 1.31–2.43, P < 0.001), lumbar soreness (OR = 10.89, 95% CI: 6.74–18.64, P < 0.001), and lower limb motor impairment (OR = 9.70, 95% CI: 4.95–21.96, P < 0.001). The nomogram showed strong discrimination, with AUCs of 0.789 (95% CI: 0.764–0.814; training) and 0.764 (95% CI: 0.720–0.809; validation). Calibration curves and Hosmer-Lemeshow test ( P = 0.205) indicated excellent agreement between predicted and observed outcomes. DCA confirmed clinical utility. Fever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment independently predict maternal dissatisfaction with epidural analgesia ( P < 0.05). The validated nomogram based on perinatal complications effectively predicts MSEA, demonstrating robust discrimination and calibration. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Neurology Health sciences/Risk factors Epidural Analgesia Perinatal Complications Maternal Satisfaction Risk Factors Nomogram Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Pain management during labor has become a critical issue in modern obstetrics, significantly impacting maternal satisfaction and overall childbirth experience. The development and application of labor analgesia techniques emerged earlier in international practice, with widespread adoption globally. In developed nations such as those in Europe and North America, rates of labor analgesia utilization are substantially higher, exceeding 80% in some countries 1 . In recent years, China has intensified efforts to promote and implement labor analgesia techniques nationwide. Despite these advancements, the penetration rate of labor analgesia in China still lags behind that of developed countries, with the current national average standing at approximately 50% 2 . Enhancing maternal satisfaction with labor analgesia and optimizing childbirth experiences are thus imperative for advancing Chinese labor analgesia adoption rates. Epidural analgesia remains the primary method for labor pain management in clinical practice due to its demonstrated analgesic efficacy and safety 3 . Compared to opioid-based alternatives, women receiving epidural analgesia report significantly lower pain intensity (as measured by pain scores) and higher satisfaction levels 4 . The determinants of maternal satisfaction with epidural analgesia (MSEA) are multifaceted, encompassing maternal individual differences, psychological stress responses, anesthetic techniques, and pharmacological strategies. Notably, the psycho-emotional dimension of the childbirth experience exerts a significant influence on satisfaction. Studies indicate prevalent irrational cognitive biases among parturients during analgesia, including: concerns about neonatal health (fear of adverse effects on newborns), anxiety regarding motor/sensory impairment, lack of confidence in vaginal delivery and fear of chronic complications (e.g., headache, back pain). Critically, these negative psychological responses show no significant correlation with maternal education level 5 . Furthermore, multiple facets of anesthesia management—including technique selection, pharmacological protocols, and infusion methods—directly impact epidural efficacy and maternal satisfaction 6 – 9 . Humanistic factors also play a pivotal role: the technical transparency of anesthesiologists, quality of clinician-patient communication, and personalized analgesia design help bridge gaps between maternal expectations and actual experiences, substantially shaping MSEA 10 . Perinatal complications constitute another crucial determinant of MSEA. While studies have established associations between post-spinal anesthesia complications and patient satisfaction 11 , the correlation between epidural-related perinatal complications and maternal satisfaction remains underexplored. This represents an unaddressed gap in predictive modeling research within the field. Complications associated with epidural analgesia include post-dural puncture headache, intrapartum fever, puncture pain, nausea and vomiting, pruritus, urinary retention, lumbar backache, and lower limb motor block. Rare but serious complications encompass meningitis, spinal cord compression from hematoma or abscess, and nerve root injury causing paresthesia or weakness. The incidence of accidental dural puncture is approximately 1%, with 50–80% of these patients developing post-dural puncture headache 12 . Epidural blood patch (20 mL autologous blood administered within 48 hours) effectively alleviates this complication 13 . Although the etiology of intrapartum fever remains unclear, epidural analgesia increases risks of perinatal fever and maternal antibiotic treatment 14 . Puncture pain during epidural placement frequently induces maternal fear and anxiety. Studies indicate that intranasal low-dose dexmedetomidine as an adjunct to programmed intermittent epidural bolus may provide faster analgesia onset and reduced puncture pain, with significantly higher maternal satisfaction compared to conventional techniques 15 . Nausea and vomiting, pruritus, and urinary retention—common opioid-induced side effects showing dose-dependent relationships—can be managed through antihistamines, opioid antagonists (e.g., naloxone) in severe cases, or alternative analgesic strategies 16 . Back pain represents the most frequently reported concern among parturients receiving epidural analgesia, adversely affecting sleep quality and daily activities 17 . Lower limb motor block, resulting from local anesthetic effects on spinal nerve roots' motor fibers, manifests as muscle weakness or paralysis. A meta-analysis indicates a 14% incidence in women receiving ropivacaine-fentanyl epidural analgesia, showing significant association with instrument-assisted delivery 18 . This motor impairment may reduce maternal satisfaction by limiting mobility and increasing fall risk. Minimization strategies—such as reducing local anesthetic concentration or employing alternative analgesic techniques—can enhance both maternal satisfaction and safety. Maternal satisfaction constitutes a multidimensional construct influenced by factors spanning the pre-, intra-, and post-analgesia phases. Crucially, satisfaction extends beyond mere pain relief quality, representing only one component of the parturient experience. A comprehensive understanding requires elucidating relationships between satisfaction and diverse elements—including preprocedural expectations, postoperative pain control, neonatal outcomes, and complications 19 . Although accurate assessment necessitates multidimensional surveys, current evaluations of patient satisfaction in regional anesthesia predominantly rely on single-dimension instruments. Addressing limitations in existing prediction models—such as incomplete complication indicators and insufficient validation samples—this study leverages the distinctive characteristics of Fujian's birthing population to: Systematically analyze the epidural complication spectrum (encompassing procedure-related, pharmacological, and physiological compensatory categories); Develop a maternal satisfaction prediction model using machine learning algorithms; Establish clinical applicability through future multicenter validation. This approach aims to provide evidence-based guidance for personalized analgesia protocol development. Materials and Methods Study Population This retrospective study included parturients who received elective epidural analgesia at Fujian Maternity and Child Health Hospital between July 2023 and March 2024. The standardized analgesic regimen comprised: 0.08% ropivacaine + 0.4 µg/ml sufentanil administered via programmed intermittent epidural bolus (PIEB) combined with patient-controlled epidural analgesia (PCEA). Participants were selected according to predefined inclusion and exclusion criteria. The study protocol received ethical approval from the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022). Informed consent was waived due to the retrospective, observational, and anonymous nature of data collection. The flowchart was showed in Fig. 1 . Inclusion and Exclusion Criteria Inclusion Criteria: (1) Primiparous or multiparous women receiving epidural analgesia during labor; (2) Aged 18–45 years; (3) Singleton pregnancy at term (37–42 gestational weeks). Exclusion Criteria: (1) Contraindications to epidural analgesia; (2) Severe obstetric or medical comorbidities (e.g., preeclampsia, placenta previa, or major fetal abnormalities); (3) Communication barriers or inability to comprehend study procedures and comply with follow-up; (4) Incomplete primary data on epidural complications and/or satisfaction metrics. Definitions (1) Premature Rupture of Membranes (PROM): Spontaneous membrane rupture before labor onset (prior to regular uterine contractions), resulting in amniotic fluid leakage 20 . (2) Dural Puncture Epidural (DPE): A technique involving intentional dural micro-perforation, allowing anesthetic seepage from the epidural to subarachnoid space to achieve continuous spinal anesthesia-like effects 21 . (3) Puncture Pain: Discomfort experienced during epidural needle insertion or residual pain at the puncture site. (4) Fever: Defined as temperature ≥ 38.0°C during the perinatal period. For this study, fever included all post-epidural temperatures exceeding normal (≥ 37.3°C) per nursing records. (5) Urinary Retention: Inability to void spontaneously post-epidural or requiring catheterization by obstetric staff. (6) Lower Limb Motor Impairment: Assessed using the Modified Bromage Scale 22 : 0: No block (full leg raise, hip/knee/ankle/toe flexion); 1: Unable to raise extended leg or flex hip (preserved knee/ankle/toe movement); 2: Unable to flex knee (preserved ankle/toe movement); 3: Complete lower limb paralysis. Operational Definition: Impairment was confirmed if Bromage score > 0 OR ambulatory dysfunction (numbness, pain, weakness) was documented. (7) Maternal Satisfaction: Scored 1–5 post-delivery: 1: Very dissatisfied 2: Dissatisfied 3: Neutral 4: Satisfied 5: Very satisfied Note Despite high satisfaction rates in literature, social desirability bias may inflate scores 19 , 23 , 24 . Classification: Satisfied: Score 4–5 without documented negative feedback. Dissatisfied: Score 1–3 OR score 4 with negative feedback. Sample Size Estimation A primary objective of this study was to quantify associations between perinatal complications and maternal satisfaction. Sample size calculation for the predictive model was performed using PASS 2021 software (Power Analysis and Sample Size, NCSS LLC) based on the following parameters: Maternal dissatisfaction prevalence: 15.80% (derived from Fujian Maternity and Child Health Hospital data) Significance level (α): 0.05 (two-tailed) Statistical power (1-β): 0.90 Coefficient of determination (R²) between complications and other covariates: 0.03 Expected odds ratio (OR): 3.0 Multivariable logistic regression analysis indicated a minimum requirement of 1,154 cases for the training set. Accounting for an estimated 20% attrition rate, the adjusted target sample size was 1,385 cases. The final cohort comprised 2,221 eligible parturients, with 1,555 cases allocated to the training set—exceeding the calculated minimum requirement and ensuring robust model development. Methods Data Collection Following comprehensive literature review, clinical data were retrieved from electronic medical records and anesthesia information systems, including: (1) Demographics: Name, medical record ID, age, height, weight, gravidity, parity, gestational age. (2) Epidural Analgesia Parameters: Cervical dilation at analgesia initiation, presence of PROM, DPE technique utilization, initial analgesic bolus dose, PIEB interval settings, total PCEA duration, conversion to cesarean delivery. (3) Perinatal Complications: Fever, nausea and vomiting, urinary retention, puncture pain, lumbar soreness, lower limb motor impairment. Maternal satisfaction scores were concurrently collected. Quality Control To ensure scientific validity and methodological rigor: A standardized data collection protocol was established through comprehensive literature review. Patient screening strictly adhered to predefined inclusion/exclusion criteria. Dual-independent verification was implemented during data entry to guarantee completeness and accuracy. Postpartum satisfaction assessments were conducted within 24 hours of delivery by blinded research assistants using structured questionnaires. These personnel had: No involvement in clinical care No access to study data Sole responsibility for objective documentation Statistical Analysis The dataset collected from Fujian Maternity and Child Health Hospital was randomly partitioned into training and validation sets at a ratio of 7:3 using MSTATA software, and variables were compared. Continuous variables were assessed for normality using Shapiro-Wilk tests and Q-Q plots. Normally distributed data were expressed as mean ± standard deviation( \(\:\overline{X}\) ±S)and compared using Welch's t-test. Categorical variables were presented as frequencies and percentages, with between-group comparisons analyzed by chi-square (χ²) tests. In the training set, LASSO regression was first employed for preliminary variable screening. The "ggplot2" package in R was then used to generate collinearity diagnostic heatmaps, evaluating potential multicollinearity among variables. Univariate and multivariate logistic regression analyses were subsequently performed to identify determinants of maternal satisfaction, utilizing stepwise selection with entry/removal criteria set at P < 0.05. Effect sizes in logistic models were expressed as odds ratios (ORs) with 95% confidence intervals (95% CIs). The nomogram for predicting maternal satisfaction with epidural analgesia (MSEA) was constructed using the "rms" package. Model discrimination was assessed through receiver operating characteristic (ROC) curves generated with the "pROC" package, where the area under the curve (AUC) ranges from 0.5 (no discrimination) to 1.0 (perfect discrimination). The concordance index (C-index) was simultaneously computed via the "caret" package to further evaluate discriminatory performance. Calibration was verified using the Hosmer-Lemeshow goodness-of-fit test ("ResourceSelection" package) supplemented with calibration curves plotted through "rms". Decision curve analysis (DCA) ultimately quantified the model's clinical net benefit. To facilitate clinical implementation, a web-based interactive application was developed using the "Shiny" package. All analyses considered P-values < 0.05 statistically significant. Statistical computations were performed using R software (version 4.4.3) and MSTATA ( www.mstata.com ). Results Baseline Clinical Characteristics Comparative Analysis of Training and Validation Sets Demographic and clinical characteristics of the study cohort are presented in Table 1 . The 2,221 eligible parturients were randomly allocated into training (n = 1,555) and internal validation (n = 666) sets at a 7:3 ratio. Overall maternal dissatisfaction with epidural analgesia was observed in 15.80% of the cohort. Table 1 Comparison of maternal clinical data between training and validation sets Characteristics Overall Training set Validation set P 2 N = 2,221 1 N = 1,555 1 N = 666 1 Age 29.68 ± 3.95 29.78 ± 3.90 29.45 ± 4.05 0.078 Height(cm) 160.59 ± 5.21 160.60 ± 5.12 160.57 ± 5.41 0.897 Weight(kg) 67.04 ± 8.61 67 .09 ± 8.66 66.92 ± 8.48 0.669 Gravidity 0.679 1 1,266 (57.00%) 877 (56.40%) 389 (58.41%) 2 619 (27.87%) 439 (28.23%) 180 (27.03%) ≥ 3 336 (15.13%) 239 (15.37%) 97 (14.56%) Parity 0.902 0 1,623 (73.06%) 1,133 (72.86%) 490 (73.57%) 1 516 (23.23%) 363 (23.34%) 153 (22.97%) ≥ 2 82 (3.69%) 59 (3.79%) 23 (3.45%) Gestational age 38.48 ± 2.77 38.52 ± 2.71 38.40 ± 2.92 0.378 Cervical dilation(cm) 0.273 <2 537 (24.18%) 379 (24.37%) 158 (23.72%) 2–3 1,388 (62.49%) 958 (61.61%) 430 (64.56%) ≥ 3 296 (13.33%) 218 (14.02%) 78 (11.71%) PROM 0.116 No 1,518 (68.35%) 1,047 (67.33%) 471 (70.72%) Yes 703 (31.65%) 508 (32.67%) 195 (29.28%) DPE 0.907 No 803 (36.15%) 561 (36.08%) 242 (36.34%) Yes 1,418 (63.85%) 994 (63.92%) 424 (63.67%) Initial dose (ml) 8.73 ± 1.29 8.73 ± 1.28 8.73 ± 1.32 0.977 Time interval (min) 50.48 ± 5.56 50.39 ± 5.40 50.68 ± 5.90 0.265 PCEA duration (min) 552.62 ± 311.92 552.23 ± 315.97 553.54 ± 302.48 0.927 Cesarean delivery 0.428 No 2,151 (96.85%) 1,503 (96.66%) 648 (97.30%) Yes 70 (3.15%) 52 (3.34%) 18 (2.70%) Fever 0.484 No 1,830 (82.40%) 1,287 (82.77%) 543 (81.53%) Yes 391 (17.60%) 268 (17.23%) 123 (18.47%) Nasuse and vomiting 0.915 No 1,858 (83.66%) 1,300 (83.60%) 558 (83.78%) Yes 363 (16.34%) 255 (16.40%) 108 (16.22%) Urinary retention 0.543 No 1,299 (58.49%) 903 (58.07%) 396 (59.46%) Yes 922 (41.51%) 652 (41.93%) 270 (40.54%) Puncture pain 0.302 No 1,237 (55.70%) 855 (54.98%) 382 (57.36%) Yes 984 (44.30%) 700 (45.02%) 284 (42.64%) Lumbar soreness 0.147 No 919 (41.38%) 628 (40.39%) 291 (43.69%) Yes 1,302 (58.62%) 927 (59.61%) 375 (56.31%) Lower limb 0.514 motor impairment No 337 (15.17%) 241 (15.50%) 96 (14.41%) Yes 1,884 (84.83%) 1,314 (84.50%) 570 (85.59%) Satisfaction No 351 (15.80%) 256(16.46%) 95(14.26%) 0.216 Yes 1,870 (84.20%) 1299(53.54%) 571(85.74%) 1 \(\:\stackrel{-}{X}\) ±S; n (%) 2 Welch Two Sample t-test; Pearson's Chi-squared test Comparisons between training and validation sets demonstrated no statistically significant differences in any baseline variables (all P > 0.05), confirming balanced demographic/clinical distributions and validating the randomization suitability for predictive modeling. Comparative Analysis of Satisfied vs. Dissatisfied Groups in Training Set The training cohort comprised 1,555 parturients, with 1,299 (83.54%) classified as satisfied and 256 (16.46%) dissatisfied. Among continuous variables, body weight significantly differed between groups ( P = 0.013), with lower values observed in the dissatisfied group. No significant differences were detected for age, height, gestational age, initial analgesic bolus, PIEB intervals, or total analgesia duration (all P > 0.05). Categorical variables revealed significant intergroup disparities (all P < 0.05): Higher complication rates in dissatisfied parturients: fever, nausea and vomiting, urinary retention, puncture pain, lumbar soreness, and motor impairment. Pronounced differences in puncture pain (65.63% vs. 40.95%) and lumbar soreness (92.97% vs. 53.04%). Gravidity, parity, cervical dilation, PROM, DPE utilization, and cesarean delivery rates showed no statistical differences ( P > 0.05). Complete data are presented in Table 2 . Table 2 Comparison of maternal clinical data between satisfied and unsatisfied groups in the training set Characteristics Satisfied Dissatisfied P 2 N = 1,299 1 N = 256 1 Age 29.80 ± 3.93 29.69 ± 3.74 0.682 Height(cm) 160.71 ± 5.16 160.06 ± 4.85 0.056 Weight(kg) 67.32 ± 8.76 65.93 ± 8.06 0.013 Gravidity 0.282 1 735 (56.58%) 142 (55.47%) 2 358 (27.56%) 81 (31.64%) ≥ 3 206 (15.86%) 33 (12.89%) Parity 0.500 0 939 (72.29%) 194 (75.78%) 1 309 (23.79%) 54 (21.09%) ≥ 2 51 (3.93%) 8 (3.13%) Gestational age 38.51 ± 2.74 38.57 ± 2.57 0.713 Cervical dilation(cm) 0.424 <2 322 (24.79%) 57 (22.27%) 2–3 791 (60.89%) 167 (65.23%) ≥ 3 186 (14.32%) 32 (12.50%) PROM 0.208 No 866 (66.67%) 181 (70.70%) Yes 433 (33.33%) 75 (29.30%) DPE 0.737 No 471 (36.26%) 90 (35.16%) Yes 828 (63.74%) 166 (64.84%) Initial dose (ml) 8.74 ± 1.30 8.70 ± 1.14 0.661 Time interval (min) 50.47 ± 5.47 49.98 ± 5.06 0.167 PCEA duration (min) 550.62 ± 316.61 560.43 ± 313.23 0.648 Cesarean delivery 0.831 No 1,255 (96.61%) 248 (96.88%) Yes 44 (3.39%) 8 (3.13%) Fever 0.004 No 1,091 (83.99%) 196 (76.56%) Yes 208 (16.01%) 60 (23.44%) Nasuse and vomiting 0.003 No 1,102 (84.83%) 198 (77.34%) Yes 197 (15.17%) 58 (22.66%) Urinary retention 0.006 No 774 (59.58%) 129 (50.39%) Yes 525 (40.42%) 127 (49.61%) Puncture pain < 0.001 No 767 (59.05%) 88 (34.38%) Yes 532 (40.95%) 168 (65.63%) Lumbar soreness < 0.001 No 610 (46.96%) 18 (7.03%) Yes 689 (53.04%) 238 (92.97%) Lower limb motor impairment < 0.001 No 233 (17.94%) 8 (3.13%) Yes 1,066 (82.06%) 248 (96.88%) 1 \(\:\stackrel{-}{X}\) ±S; n (%) 2 Welch Two Sample t-test; Pearson's Chi-squared test Factors influencing maternal satisfaction with epidural analgesia​ Variable Selection via LASSO Regression LASSO regression was employed to identify determinants of maternal satisfaction with epidural analgesia (MSEA). All variables presented in Table 1 were included in the analysis using the training cohort (n = 1,555). This approach refined the predictors to five optimal variables: fever, nausea and vomiting, puncture pain, lumbar soreness and lower limb motor impairment. The model utilized 10-fold cross-validation with the one-standard-error rule to select the regularization parameter λ. This criterion identifies the most parsimonious model within one standard error of the minimum cross-validation error (largest λ value: λ = 0.025), as illustrated in Fig. 2 a. Variable coefficient trajectories across λ values are depicted in Fig. 2 b, with final LASSO coefficients shown in Fig. 2 c. The five predictors identified by LASSO regression underwent collinearity diagnostics. A correlation heatmap (Fig. 2 d) visualized pairwise Pearson correlation coefficients among variables, these results confirm the suitability of included predictors for multivariable modeling, though cautious interpretation is warranted to mitigate potential multicollinearity bias. Univariate Analysis of Predictors for MSEA The five variables selected by LASSO regression were subsequently analyzed using univariate logistic regression. All predictors demonstrated statistically significant associations with dissatisfaction after epidural analgesia (all P < 0.05): fever ( P = 0.004), nausea and vomiting ( P = 0.003), puncture pain ( P < 0.001), lumbar soreness ( P < 0.001) and lower limb motor impairment ( P < 0.001). These results confirm each variable as a significant risk factor for maternal dissatisfaction, with detailed odds ratios and confidence intervals presented in Table 3 . Table 3 Univariate Logistic Regression Analysis of Maternal Satisfaction with Epidural Analgesia Complications Satisfied Dissatisfied OR 1 95% CI 1 P Fever No 1091 196 — — Yes 208 60 1.61 1.15, 2.21 0.004 Nasuse and vomiting No 1,102 198 — — Yes 197 58 1.64 1.17, 2.27 0.003 Puncture pain No 767 88 — — Yes 532 168 2.75 2.08, 3.66 < 0.001 Lumbar soreness No 610 18 — — Yes 689 238 11.71 7.37, 19.80 < 0.001 Lower limb motor impairment No 233 8 — — Yes 1,066 248 6.78 3.53, 15.13 < 0.001 1 OR = Odds Ratio, CI = Confidence Interval Multivariable Analysis of Independent Risk Factors Variables identified as significant in LASSO regression were included as predictors in a multivariable logistic regression model, with maternal satisfaction as the outcome. After adjusting for potential confounders, five independent risk factors for dissatisfaction were confirmed (all P < 0.05): Fever: Increased dissatisfaction odds by 83% (OR = 1.83, 95% CI: 1.26–2.62; P = 0.001) Nausea/vomiting: 79% higher odds of dissatisfaction (OR = 1.79, 95% CI: 1.23–2.58; P = 0.002) Puncture pain: 78% elevated dissatisfaction risk (OR = 1.78, 95% CI: 1.31–2.43; P < 0.001) Lumbar soreness: 10.89-fold higher odds vs. unaffected parturients (OR = 10.89, 95% CI: 6.74–18.69; P < 0.001) Motor impairment: 9.70-fold increased odds vs. unimpaired women (OR = 9.70, 95% CI: 4.95–21.96; P < 0.001) Complete multivariate regression results are provided in Table 4 . Table 4 Multivariable Logistic Regression Analysis of Determinants of Dissatisfaction with Epidural Analgesia in Parturients Complications Satisfied Dissatisfied OR 1 95% CI 1 P Fever No 1091 196 — — Yes 208 60 1.83 1.26, 2.62 0.001 Nasuse and vomiting No 1,102 198 — — Yes 197 58 1.79 1.23, 2.58 0.002 Puncture pain No 767 88 — — Yes 532 168 1.78 1.31, 2.43 < 0.001 Lumbar soreness No 610 18 — — Yes 689 238 10.89 6.74, 18.69 < 0.001 Lower limb motor impairment No 233 8 — — Yes 1,066 248 9.70 4.95, 21.96 < 0.001 1 OR = Odds Ratio, CI = Confidence Interval Development and Validation of the MSEA Nomogram Prediction Model Development of the Nomogram Based on multivariable logistic regression results, five independent predictors were incorporated into the nomogram for predicting maternal dissatisfaction with epidural analgesia (MSEA; Fig. 3 a). The model was constructed using R software, assigning weighted points to each variable proportional to its regression coefficient. Nomogram Interpretation: For each predictor, draw a vertical line to the Points axis to determine its individual score. Sum all variable scores to obtain the Total Points value. Project a vertical line downward from Total Points to the Risk of Dissatisfaction axis. The resulting value represents the predicted probability of maternal dissatisfaction with epidural analgesia. Validation and Evaluation of the Nomogram Model Model Discrimination Assessment The nomogram's discriminatory power was evaluated using ROC curves and corresponding AUC values. Predictive performance was interpreted as: poor discrimination (AUC 0.750). In the training set, the model achieved an AUC of 0.789 (95% CI: 0.764–0.814) with 57.74% sensitivity and 91.02% specificity. The validation set yielded an AUC of 0.764 (95% CI: 0.720–0.809), demonstrating 59.72% sensitivity and 88.42% specificity (Fig. 3 b). These results indicate robust discrimination capacity for MSEA prediction. Concordance indices further validated ranking consistency: Training set C-index: 0.789 Validation set C-index: 0.764 The model effectively prioritized dissatisfied parturients with stable ranking performance. The final logistic regression model was translated into an accessible nomogram. To enhance clinical utility, a complementary web-based tool was developed for real-time risk calculation at: https://zhp1999.shinyapps.io/dynnomapp . This interactive platform dynamically generates dissatisfaction probabilities based on predictor inputs, as demonstrated in Fig. 3 c. Model Calibration Assessment Calibration was evaluated using calibration curves and the Hosmer-Lemeshow goodness-of-fit test. Calibration curves visualize agreement between predicted probabilities (x-axis) and observed outcomes (y-axis), where: Blue dashed line (Ideal): Perfect prediction reference Red solid line (Apparent): Model's actual performance Green solid line (Bias-corrected): Bootstrap-corrected curve (1,000 resamples) reflecting true population performance Closer alignment between solid and dashed lines indicates superior calibration. As shown in Fig. 4 a and b, both training and validation sets demonstrated excellent curve concordance with the ideal line. The Hosmer-Lemeshow test confirmed good fit (χ² = 4.58, P = 0.205), indicating no significant deviation between predicted and observed dissatisfaction probabilities ( P > 0.05). These results align with the calibration curve findings. Clinical Utility via Decision Curve Analysis Figure 4 c and d presents decision curves for the nomogram in training and validation sets. The horizontal axis denotes the threshold probability, while the vertical axis represents net benefit – quantifying clinical value after accounting for false positives. The high-risk threshold indicates the probability level where clinicians would consider intervention despite potential trade-offs. The model demonstrated clinical utility across threshold probabilities of: Training set: 3–40% Validation set: 3–30% Within these ranges, the nomogram provided superior net benefit compared to "treat-all" or "treat-none" strategies, confirming its value for guiding individualized clinical decisions. Discussion Epidural analgesia represents a pivotal advancement in modern obstetric care, significantly enhancing the childbirth experience. However, maternal satisfaction remains influenced by multifaceted factors including analgesic efficacy, complication profiles, and individual variability. While epidural analgesia continues to serve as the primary method for labor pain management due to its established effectiveness and safety profile 25 , procedure-related complications directly impact satisfaction levels 26 , 27 , subsequently affecting overall birth experiences and postpartum recovery trajectories. Current research predominantly focuses on technical aspects (e.g., infusion modes, drug selection, concentration optimization) or labor parameters (e.g., second-stage duration) 28 , 29 , with limited systematic investigation into perinatal complications. Consequently, our integrated analysis of associations between perinatal complications and epidural satisfaction provides a framework for optimizing personalized analgesic management. This approach enables targeted reduction of complication incidence, thereby enhancing maternal satisfaction while improving childbirth experiences. Our analysis incorporated comprehensive perinatal clinical data, utilizing LASSO regression for initial variable screening followed by univariate and multivariate logistic regression. Results confirmed fever, nausea/vomiting, puncture pain, lumbar soreness, and lower limb motor impairment as significant risk factors for maternal dissatisfaction with epidural analgesia. Crucially, multivariate analysis established these perinatal complications as independent predictors of dissatisfaction. Clinical observations indicate that procedural pain during epidural placement triggers stress responses and heightens patient anxiety 30 . Our findings quantitatively demonstrate that puncture pain increases dissatisfaction risk by 78% (OR = 1.78). Lv et al. 31 reported intranasal low-dose dexmedetomidine significantly improved Ramsay sedation scores and reduced puncture-related pain. Sun et al. 15 confirmed analogous outcomes, noting procedural pain directly compromises labor analgesia experiences. These collective findings underscore that mitigating puncture pain through targeted interventions—such as adjuvant sedation protocols—holds demonstrated clinical significance for optimizing analgesia efficacy and enhancing maternal satisfaction. Intrapartum fever occurs in up to 15.8% of parturients receiving labor analgesia 32 . Two predominant hypotheses explain its etiology: One implicates thermoregulatory dysregulation from analgesic agents, initially evidenced by Fusi et al. (1989) who documented significantly elevated mean temperatures in epidural recipients 33 . Another proposes maternal-fetal inflammatory processes, exemplified by Curtin et al.'s finding that histologic chorioamnionitis and epidural analgesia were independently associated with intrapartum fever 34 . Compared to afebrile counterparts, febrile parturients face increased risks of instrumental delivery and cesarean section 35 . Maternal fever directly impacts obstetric decision-making, while consequent interventions indirectly endanger neonates. Epidural analgesia constitutes the strongest independent risk factor for intrapartum fever (over 10-fold increase) 32 . Although neonatal consequences remain debated 36 , 37 , maternal concerns about potential fetal risks inevitably heighten perinatal anxiety. This mechanistic and psychological burden substantiates fever as a critical determinant of epidural satisfaction – a finding aligning with our multivariate results (OR = 1.83). Evidence indicates that postoperative nausea and vomiting (PONV) following elective cesarean delivery correlates with maternal dissatisfaction regarding pre-anesthesia assessment practices 38 . Proactive perioperative evaluation by anesthesiologists and prophylactic antiemetics demonstrably improve satisfaction 39 . Echoing this, Ida et al.'s study on spinal anesthesia for cesarean sections confirmed that intraoperative antiemetic use positively influenced satisfaction (AOR = 0.71; 95% CI: 0.53–0.94) 40 . While our study identified nausea and vomitting as an independent risk factor for reduced epidural satisfaction (OR = 1.79), the inclusion of both vaginal and cesarean deliveries limited our ability to analyze prophylactic antiemetic administration—a variable warranting future investigation. Divergent findings exist regarding back pain etiology: Prospective studies implicate multiple spinal needle attempts, PONV, and postoperative back pain as predictors of spinal anesthesia dissatisfaction, with refusal of repeat procedures linked primarily to back pain and prior negative experiences 11 . Conversely, epidural analgesia shows no increased risk of early or 6-month postpartum back pain compared to unmedicated deliveries, despite a 30% prevalence across both groups 17 . This paradox suggests lumbar soreness likely stems from multifactorial origins—including labor fatigue, physical exertion, immediate postpartum postural stress, and later musculoskeletal strain from infant care 41 . Notably, while lumbar soreness affected only 7% of dissatisfied parturients in our training cohort, these women demonstrated a striking 10.89-fold increased dissatisfaction risk compared to unaffected counterparts (P < 0.001). This profound impact necessitates multifaceted interventions: implementing targeted strategies for postpartum back pain management alongside structured education programs demystifying epidural procedures—both critical for rectifying misconceptions about obstetric complications and alleviating procedure-related anxieties. Furthermore, technical optimization through minimizing puncture attempts by experienced anesthesiologists reduces tissue trauma, potentially mitigating lumbar soreness incidence and collectively enhancing maternal satisfaction with epidural analgesia. A systematic review and meta-analysis indicates that programmed intermittent epidural bolus (PIEB) combined with patient-controlled epidural analgesia (PCEA) enhances maternal satisfaction, potentially attributable to reduced local anesthetic consumption, decreased incidence of lower limb motor impairment, and higher spontaneous vaginal delivery rates 42 . While conventional wisdom suggests PCEA alone improves satisfaction by augmenting maternal control over pain management 43 , evidence demonstrates that standalone PCEA fails to increase satisfaction or perceived control compared to continuous epidural infusion (CIEA) or intermittent bolus techniques (IBEA) 7 . This paradox underscores that optimizing drug delivery regimens to minimize motor impairment critically influences satisfaction—a finding corroborated by our multivariate analysis identifying motor impairment as a high-risk dissatisfaction factor (OR = 9.70). The apparent discrepancy between our motor impairment incidence (84.8%) and prior meta-analytical reports (14.36%) 18 primarily stems from definitional variations: our operational criteria encompassed ambulatory dysfunction (numbness, paresthesia) reflecting real-world perinatal experiences. Pharmacological strategies—such as using 0.125% ropivacaine-sufentanil over bupivacaine equivalents—may reduce motor block incidence, though lower concentrations (e.g., 0.1% ropivacaine) risk inadequate analgesia without eliminating impairment 44 . Mitigating motor impairment remains imperative for facilitating postpartum functional rehabilitation; preserved mobility fosters positive psychological states and accelerates recovery, directly enhancing childbirth experiences and indirectly reinforcing epidural satisfaction through demonstrable functional benefits. The predictive model for maternal satisfaction with epidural analgesia (MSEA) leveraged LASSO regression with 10-fold cross-validation (λ = 0.025) to identify five core predictors from perinatal complications: fever, nausea and vomiting, puncture pain, lumbar soreness, and motor impairment. This approach effectively mitigated overfitting (cross-validation error within one standard error) while preserving clinically synergistic variables. Collinearity diagnostics revealed a moderate positive correlation between puncture pain and lumbar soreness (r = 0.37), potentially attributable to combined tissue irritation and positional compression during epidural procedures. Critically, LASSO regularization compressed redundant information rather than eliminating collinear variables—retaining clinical authenticity by acknowledging their pathological interdependence (e.g., puncture trauma potentiating neuropathic compression). Other variables exhibited near-zero correlations, confirming controlled multicollinearity risk. Univariate analysis identified extreme initial effects for lumbar soreness (OR = 11.71) and motor impairment (OR = 6.78), but multivariable adjustment attenuated these to OR = 10.89 and OR = 9.70, respectively, indicating that 7.0%-43.1% of univariate effects stemmed from confounding synergies. Notably, puncture pain's OR reduction (2.75→1.78) suggests partial mediation through lumbar pathways, warranting future mediation analysis. The modest ORs for fever (1.83) and nausea and vomiting (1.79) reflect their nonspecific pathophysiology (inflammatory cascades and opioid effects). The resultant nomogram demonstrated robust generalizability: discrimination consistency between training (AUC = 0.789) and validation sets (AUC = 0.764) was high, with minimal C-index divergence (3.2%). Calibration accuracy was confirmed by Hosmer-Lemeshow testing (χ²=4.58, P = 0.205) and curve alignment. Decision curve analysis affirmed net clinical benefit across 3%-40% threshold probabilities versus default strategies. The web-based dynamic nomogram ( https://zhp1999.shinyapps.io/dynnomapp/ ) enables instant risk visualization, surpassing traditional scoring systems in clinical utility. This study pioneers the first perinatal complication-based nomogram for predicting maternal satisfaction with epidural analgesia (MSEA), offering dual innovations: clinical interpretability through regression coefficient-weighted risk quantification (e.g., lumbar soreness contributing 38.6% predictive weight), and operational accessibility via an online scoring tool providing real-time decision support. Limitations warrant consideration: First, single-center data introduces selection and admission biases; second, retrospective design with internal validation necessitates external verification to assess generalizability; third, 24-hour follow-up misses delayed complications (e.g., post-dural puncture headache peaking at 72 hours) 45 ; fourth, satisfaction’s multidimensional nature—encompassing sociodemographic, psychosocial, and care-quality factors—remains partially unexplored. Nevertheless, this model identifies validated independent risk factors with robust discrimination (AUC 0.764–0.789) and calibration accuracy (χ²=4.58, P = 0.205), establishing a clinically actionable reference. Conclusion Fever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment were identified as independent risk factors for maternal dissatisfaction with epidural analgesia. The perinatal complication-based nomogram demonstrated strong discriminative capability and calibration accuracy, providing a validated tool for clinical implementation. Declarations Author contributions Yihan Zheng and Haiping Zhang contributed equally to this work (co-first authors). Yihan Zheng designed the study protocol, collected and analyzed the clinical data, and drafted the initial manuscript. Haiping Zhang assisted in data analysis, performed statistical modeling for the predictive nomogram, and revised the manuscript critically for important intellectual content. Xizhu Wu participated in clinical data collection, conducted preliminary data sorting, and ensured the accuracy of raw data. Wenqiang You provided insights into the association between obstetric clinical practices and perinatal complications during the initial study conceptualization phase. Chuantao Lin (co-corresponding author) supervised the entire process of data quality control, particularly for perinatal complication indicators (e.g., fever, lumbar soreness, lower limb motor impairment), participated in the validation of the nomogram model, and revised the manuscript to refine the interpretation of anesthetic-related outcome data. Li Zhang (corresponding author) conceived and supervised the overall study design, provided expert guidance on statistical analysis and clinical significance interpretation of results, and finalized the manuscript for submission. All authors have read and approved the final version of the manuscript, and confirm that no relevant contributions have been omitted. The co-corresponding authors (Chuantao Lin and Li Zhang) are responsible for the overall direction of the study, handling editorial correspondence, ensuring the integrity of the work, and responding to post-publication queries. Competing interests The author(s) declare no competing interests. Data availability The datasets generated and analyzed during the current study are available from the corresponding authors upon reasonable request. The data are not publicly available due to privacy and ethical restrictions related to the inclusion of patient clinical information, as specified by the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022). Acknowledgments We would like to express our sincere gratitude to all the parturients who participated in this study and contributed their clinical data, without which this research would not have been possible. We are deeply thankful to the medical staff of Fujian Maternity and Child Health Hospital, especially those from the Departments of Anesthesiology, Obstetrics, and related units, for their invaluable assistance in data collection, patient care, and logistical support throughout the study process. Funding We would like to express our sincere gratitude to the funds of Joint Funds for the innovation of science and Technology, Fujian province (Grant number:2023Y9390). Ethics declarations This retrospective study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022). 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10:01:12","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":179560,"visible":true,"origin":"","legend":"","description":"","filename":"e6b275d3d227472d8899d030434df48d1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/781fb153ff98db22511ff4f5.xml"},{"id":97966989,"identity":"3d18a796-3c23-4bbc-8ee2-de0baaa2273b","added_by":"auto","created_at":"2025-12-11 10:01:12","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":194897,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/5c91d18856497bcce8b8b52c.html"},{"id":97966970,"identity":"3622725e-ee7c-4660-95e6-f42fdbbd1192","added_by":"auto","created_at":"2025-12-11 10:01:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":458046,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart depicting the process of selecting parturients with epidural analgesia, splitting into training/validation sets, developing and validating the MSEA nomogram model.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/753b2678ba545867c8a21976.jpg"},{"id":98423011,"identity":"08c7bb03-5ca2-46c2-8f8a-9125141f5f21","added_by":"auto","created_at":"2025-12-17 16:31:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":233035,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Flowchart of LASSO Regression Variable Selection Using 10-Fold Cross-Validation; (b) Variable Selection Path Diagram of LASSO Regression; (c) Coefficient histogram of the LASSO filter variable; (d) Correlation Heatmap for Collinearity Diagnostics.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/10ae675d3962f94cfb59cd6a.jpg"},{"id":98423509,"identity":"1fbacc78-0f46-40ad-a521-706629efcdfa","added_by":"auto","created_at":"2025-12-17 16:32:18","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":187666,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Development of a Nomogram Predictive Model Based on Multivariable Analysis of Maternal Satisfaction with Epidural Analgesia; (b) ROC Curves of the MSEA Nomogram Predictive Model in the Training and Validation Sets; (c) Dynamic Nomogram.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/daf8ba90df88eeb531397fc9.jpg"},{"id":97966974,"identity":"0192c0ba-4b5e-452d-a211-85ad40cd9a3b","added_by":"auto","created_at":"2025-12-11 10:01:11","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":388740,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Calibration Curves of the MSEA Predictive Model in the Training Set; (b) Validation Set; (c) Clinical Decision Curves of the MSEA Predictive Model in the Training Set; (d) Validation Set.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/b9b0bca02f31900ac80b4324.jpg"},{"id":107928496,"identity":"0437e5d6-fc0b-48c5-a25b-8c994698f848","added_by":"auto","created_at":"2026-04-27 16:11:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2046973,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7354374/v1/b92e530a-5243-4eb7-8ff9-b82e32024205.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Development of a Predictive Model for Maternal Satisfaction with Epidural Analgesia Based on Perinatal Complications","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePain management during labor has become a critical issue in modern obstetrics, significantly impacting maternal satisfaction and overall childbirth experience. The development and application of labor analgesia techniques emerged earlier in international practice, with widespread adoption globally. In developed nations such as those in Europe and North America, rates of labor analgesia utilization are substantially higher, exceeding 80% in some countries\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In recent years, China has intensified efforts to promote and implement labor analgesia techniques nationwide. Despite these advancements, the penetration rate of labor analgesia in China still lags behind that of developed countries, with the current national average standing at approximately 50%\u003csup\u003e2\u003c/sup\u003e. Enhancing maternal satisfaction with labor analgesia and optimizing childbirth experiences are thus imperative for advancing Chinese labor analgesia adoption rates.\u003c/p\u003e\u003cp\u003eEpidural analgesia remains the primary method for labor pain management in clinical practice due to its demonstrated analgesic efficacy and safety\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Compared to opioid-based alternatives, women receiving epidural analgesia report significantly lower pain intensity (as measured by pain scores) and higher satisfaction levels\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The determinants of maternal satisfaction with epidural analgesia (MSEA) are multifaceted, encompassing maternal individual differences, psychological stress responses, anesthetic techniques, and pharmacological strategies. Notably, the psycho-emotional dimension of the childbirth experience exerts a significant influence on satisfaction. Studies indicate prevalent irrational cognitive biases among parturients during analgesia, including: concerns about neonatal health (fear of adverse effects on newborns), anxiety regarding motor/sensory impairment, lack of confidence in vaginal delivery and fear of chronic complications (e.g., headache, back pain). Critically, these negative psychological responses show no significant correlation with maternal education level\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Furthermore, multiple facets of anesthesia management\u0026mdash;including technique selection, pharmacological protocols, and infusion methods\u0026mdash;directly impact epidural efficacy and maternal satisfaction \u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Humanistic factors also play a pivotal role: the technical transparency of anesthesiologists, quality of clinician-patient communication, and personalized analgesia design help bridge gaps between maternal expectations and actual experiences, substantially shaping MSEA\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Perinatal complications constitute another crucial determinant of MSEA. While studies have established associations between post-spinal anesthesia complications and patient satisfaction \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, the correlation between epidural-related perinatal complications and maternal satisfaction remains underexplored. This represents an unaddressed gap in predictive modeling research within the field.\u003c/p\u003e\u003cp\u003eComplications associated with epidural analgesia include post-dural puncture headache, intrapartum fever, puncture pain, nausea and vomiting, pruritus, urinary retention, lumbar backache, and lower limb motor block. Rare but serious complications encompass meningitis, spinal cord compression from hematoma or abscess, and nerve root injury causing paresthesia or weakness. The incidence of accidental dural puncture is approximately 1%, with 50\u0026ndash;80% of these patients developing post-dural puncture headache\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Epidural blood patch (20 mL autologous blood administered within 48 hours) effectively alleviates this complication\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Although the etiology of intrapartum fever remains unclear, epidural analgesia increases risks of perinatal fever and maternal antibiotic treatment\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Puncture pain during epidural placement frequently induces maternal fear and anxiety. Studies indicate that intranasal low-dose dexmedetomidine as an adjunct to programmed intermittent epidural bolus may provide faster analgesia onset and reduced puncture pain, with significantly higher maternal satisfaction compared to conventional techniques\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Nausea and vomiting, pruritus, and urinary retention\u0026mdash;common opioid-induced side effects showing dose-dependent relationships\u0026mdash;can be managed through antihistamines, opioid antagonists (e.g., naloxone) in severe cases, or alternative analgesic strategies\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Back pain represents the most frequently reported concern among parturients receiving epidural analgesia, adversely affecting sleep quality and daily activities\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Lower limb motor block, resulting from local anesthetic effects on spinal nerve roots' motor fibers, manifests as muscle weakness or paralysis. A meta-analysis indicates a 14% incidence in women receiving ropivacaine-fentanyl epidural analgesia, showing significant association with instrument-assisted delivery\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This motor impairment may reduce maternal satisfaction by limiting mobility and increasing fall risk. Minimization strategies\u0026mdash;such as reducing local anesthetic concentration or employing alternative analgesic techniques\u0026mdash;can enhance both maternal satisfaction and safety.\u003c/p\u003e\u003cp\u003eMaternal satisfaction constitutes a multidimensional construct influenced by factors spanning the pre-, intra-, and post-analgesia phases. Crucially, satisfaction extends beyond mere pain relief quality, representing only one component of the parturient experience. A comprehensive understanding requires elucidating relationships between satisfaction and diverse elements\u0026mdash;including preprocedural expectations, postoperative pain control, neonatal outcomes, and complications\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Although accurate assessment necessitates multidimensional surveys, current evaluations of patient satisfaction in regional anesthesia predominantly rely on single-dimension instruments. Addressing limitations in existing prediction models\u0026mdash;such as incomplete complication indicators and insufficient validation samples\u0026mdash;this study leverages the distinctive characteristics of Fujian's birthing population to: Systematically analyze the epidural complication spectrum (encompassing procedure-related, pharmacological, and physiological compensatory categories); Develop a maternal satisfaction prediction model using machine learning algorithms; Establish clinical applicability through future multicenter validation. This approach aims to provide evidence-based guidance for personalized analgesia protocol development.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population\u003c/h2\u003e\u003cp\u003eThis retrospective study included parturients who received elective epidural analgesia at Fujian Maternity and Child Health Hospital between July 2023 and March 2024. The standardized analgesic regimen comprised: 0.08% ropivacaine\u0026thinsp;+\u0026thinsp;0.4 \u0026micro;g/ml sufentanil administered via programmed intermittent epidural bolus (PIEB) combined with patient-controlled epidural analgesia (PCEA). Participants were selected according to predefined inclusion and exclusion criteria. The study protocol received ethical approval from the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022). Informed consent was waived due to the retrospective, observational, and anonymous nature of data collection. The flowchart was showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eInclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eInclusion Criteria:\u003c/h2\u003e\u003cp\u003e(1) Primiparous or multiparous women receiving epidural analgesia during labor;\u003c/p\u003e\u003cp\u003e(2) Aged 18\u0026ndash;45 years;\u003c/p\u003e\u003cp\u003e(3) Singleton pregnancy at term (37\u0026ndash;42 gestational weeks).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eExclusion Criteria:\u003c/h3\u003e\n\u003cp\u003e(1) Contraindications to epidural analgesia;\u003c/p\u003e\u003cp\u003e(2) Severe obstetric or medical comorbidities (e.g., preeclampsia, placenta previa, or major fetal abnormalities);\u003c/p\u003e\u003cp\u003e(3) Communication barriers or inability to comprehend study procedures and comply with follow-up;\u003c/p\u003e\u003cp\u003e(4) Incomplete primary data on epidural complications and/or satisfaction metrics.\u003c/p\u003e\n\u003ch3\u003eDefinitions\u003c/h3\u003e\n\u003cp\u003e(1) Premature Rupture of Membranes (PROM): Spontaneous membrane rupture before labor onset (prior to regular uterine contractions), resulting in amniotic fluid leakage\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e(2) Dural Puncture Epidural (DPE): A technique involving intentional dural micro-perforation, allowing anesthetic seepage from the epidural to subarachnoid space to achieve continuous spinal anesthesia-like effects\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e(3) Puncture Pain: Discomfort experienced during epidural needle insertion or residual pain at the puncture site.\u003c/p\u003e\u003cp\u003e(4) Fever: Defined as temperature\u0026thinsp;\u0026ge;\u0026thinsp;38.0\u0026deg;C during the perinatal period. For this study, fever included all post-epidural temperatures exceeding normal (\u0026ge;\u0026thinsp;37.3\u0026deg;C) per nursing records.\u003c/p\u003e\u003cp\u003e(5) Urinary Retention: Inability to void spontaneously post-epidural or requiring catheterization by obstetric staff.\u003c/p\u003e\u003cp\u003e(6) Lower Limb Motor Impairment: Assessed using the Modified Bromage Scale\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e\u003cp\u003e0: No block (full leg raise, hip/knee/ankle/toe flexion);\u003c/p\u003e\u003cp\u003e1: Unable to raise extended leg or flex hip (preserved knee/ankle/toe movement);\u003c/p\u003e\u003cp\u003e2: Unable to flex knee (preserved ankle/toe movement);\u003c/p\u003e\u003cp\u003e3: Complete lower limb paralysis.\u003c/p\u003e\u003cp\u003eOperational Definition: Impairment was confirmed if Bromage score\u0026thinsp;\u0026gt;\u0026thinsp;0 OR ambulatory dysfunction (numbness, pain, weakness) was documented.\u003c/p\u003e\u003cp\u003e(7) Maternal Satisfaction: Scored 1\u0026ndash;5 post-delivery:\u003c/p\u003e\u003cp\u003e1: Very dissatisfied\u003c/p\u003e\u003cp\u003e2: Dissatisfied\u003c/p\u003e\u003cp\u003e3: Neutral\u003c/p\u003e\u003cp\u003e4: Satisfied\u003c/p\u003e\u003cp\u003e5: Very satisfied\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003cp\u003eDespite high satisfaction rates in literature, social desirability bias may inflate scores\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eClassification:\u003c/p\u003e\u003cp\u003eSatisfied: Score 4\u0026ndash;5 without documented negative feedback.\u003c/p\u003e\u003cp\u003eDissatisfied: Score 1\u0026ndash;3 OR score 4 with negative feedback.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSample Size Estimation\u003c/h2\u003e\u003cp\u003eA primary objective of this study was to quantify associations between perinatal complications and maternal satisfaction. Sample size calculation for the predictive model was performed using PASS 2021 software (Power Analysis and Sample Size, NCSS LLC) based on the following parameters:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMaternal dissatisfaction prevalence: 15.80% (derived from Fujian Maternity and Child Health Hospital data)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSignificance level (α): 0.05 (two-tailed)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStatistical power (1-β): 0.90\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eCoefficient of determination (R\u0026sup2;) between complications and other covariates: 0.03\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eExpected odds ratio (OR): 3.0\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eMultivariable logistic regression analysis indicated a minimum requirement of 1,154 cases for the training set. Accounting for an estimated 20% attrition rate, the adjusted target sample size was 1,385 cases.\u003c/p\u003e\u003cp\u003eThe final cohort comprised 2,221 eligible parturients, with 1,555 cases allocated to the training set\u0026mdash;exceeding the calculated minimum requirement and ensuring robust model development.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMethods\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eData Collection\u003c/h2\u003e\u003cp\u003eFollowing comprehensive literature review, clinical data were retrieved from electronic medical records and anesthesia information systems, including:\u003c/p\u003e\u003cp\u003e(1) Demographics: Name, medical record ID, age, height, weight, gravidity, parity, gestational age.\u003c/p\u003e\u003cp\u003e(2) Epidural Analgesia Parameters: Cervical dilation at analgesia initiation, presence of PROM, DPE technique utilization, initial analgesic bolus dose, PIEB interval settings, total PCEA duration, conversion to cesarean delivery.\u003c/p\u003e\u003cp\u003e(3) Perinatal Complications: Fever, nausea and vomiting, urinary retention, puncture pain, lumbar soreness, lower limb motor impairment.\u003c/p\u003e\u003cp\u003eMaternal satisfaction scores were concurrently collected.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eQuality Control\u003c/h2\u003e\u003cp\u003eTo ensure scientific validity and methodological rigor:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eA standardized data collection protocol was established through comprehensive literature review.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePatient screening strictly adhered to predefined inclusion/exclusion criteria.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDual-independent verification was implemented during data entry to guarantee completeness and accuracy.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003ePostpartum satisfaction assessments were conducted within 24 hours of delivery by blinded research assistants using structured questionnaires. These personnel had:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eNo involvement in clinical care\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eNo access to study data\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSole responsibility for objective documentation\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThe dataset collected from Fujian Maternity and Child Health Hospital was randomly partitioned into training and validation sets at a ratio of 7:3 using MSTATA software, and variables were compared. Continuous variables were assessed for normality using Shapiro-Wilk tests and Q-Q plots. Normally distributed data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation(\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\overline{X}\\)\u003c/span\u003e\u003c/span\u003e\u0026plusmn;S)and compared using Welch's t-test. Categorical variables were presented as frequencies and percentages, with between-group comparisons analyzed by chi-square (χ\u0026sup2;) tests.\u003c/p\u003e\u003cp\u003eIn the training set, LASSO regression was first employed for preliminary variable screening. The \"ggplot2\" package in R was then used to generate collinearity diagnostic heatmaps, evaluating potential multicollinearity among variables. Univariate and multivariate logistic regression analyses were subsequently performed to identify determinants of maternal satisfaction, utilizing stepwise selection with entry/removal criteria set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Effect sizes in logistic models were expressed as odds ratios (ORs) with 95% confidence intervals (95% CIs).\u003c/p\u003e\u003cp\u003eThe nomogram for predicting maternal satisfaction with epidural analgesia (MSEA) was constructed using the \"rms\" package. Model discrimination was assessed through receiver operating characteristic (ROC) curves generated with the \"pROC\" package, where the area under the curve (AUC) ranges from 0.5 (no discrimination) to 1.0 (perfect discrimination). The concordance index (C-index) was simultaneously computed via the \"caret\" package to further evaluate discriminatory performance. Calibration was verified using the Hosmer-Lemeshow goodness-of-fit test (\"ResourceSelection\" package) supplemented with calibration curves plotted through \"rms\". Decision curve analysis (DCA) ultimately quantified the model's clinical net benefit. To facilitate clinical implementation, a web-based interactive application was developed using the \"Shiny\" package.\u003c/p\u003e\u003cp\u003eAll analyses considered P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 statistically significant. Statistical computations were performed using R software (version 4.4.3) and MSTATA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.mstata.com\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eBaseline Clinical Characteristics\u003c/h2\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003eComparative Analysis of Training and Validation Sets\u003c/h2\u003e\u003cp\u003eDemographic and clinical characteristics of the study cohort are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The 2,221 eligible parturients were randomly allocated into training (n\u0026thinsp;=\u0026thinsp;1,555) and internal validation (n\u0026thinsp;=\u0026thinsp;666) sets at a 7:3 ratio. Overall maternal dissatisfaction with epidural analgesia was observed in 15.80% of the cohort.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of maternal clinical data between training and validation sets\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTraining set\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eValidation set\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c6\" namest=\"c5\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;2,221\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,555\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;666\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.68\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.78\u0026thinsp;\u0026plusmn;\u0026thinsp;3.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.45\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight(cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e160.59\u0026thinsp;\u0026plusmn;\u0026thinsp;5.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160.60\u0026thinsp;\u0026plusmn;\u0026thinsp;5.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e160.57\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.897\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight(kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67 .09\u0026thinsp;\u0026plusmn;\u0026thinsp;8.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.92\u0026thinsp;\u0026plusmn;\u0026thinsp;8.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGravidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.679\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,266 (57.00%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e877 (56.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e389 (58.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e619 (27.87%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e439 (28.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e180 (27.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e336 (15.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e239 (15.37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (14.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,623 (73.06%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,133 (72.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e490 (73.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e516 (23.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e363 (23.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e153 (22.97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82 (3.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59 (3.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (3.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38.52\u0026thinsp;\u0026plusmn;\u0026thinsp;2.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38.40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical dilation(cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e537 (24.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e379 (24.37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e158 (23.72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,388 (62.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e958 (61.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e430 (64.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e296 (13.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e218 (14.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (11.71%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePROM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,518 (68.35%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,047 (67.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e471 (70.72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e703 (31.65%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e508 (32.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e195 (29.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDPE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e803 (36.15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e561 (36.08%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e242 (36.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,418 (63.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e994 (63.92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e424 (63.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial dose (ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime interval (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.48\u0026thinsp;\u0026plusmn;\u0026thinsp;5.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.39\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50.68\u0026thinsp;\u0026plusmn;\u0026thinsp;5.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCEA duration (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e552.62\u0026thinsp;\u0026plusmn;\u0026thinsp;311.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e552.23\u0026thinsp;\u0026plusmn;\u0026thinsp;315.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e553.54\u0026thinsp;\u0026plusmn;\u0026thinsp;302.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.927\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCesarean delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,151 (96.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,503 (96.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e648 (97.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70 (3.15%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (3.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (2.70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.484\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,830 (82.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,287 (82.77%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e543 (81.53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e391 (17.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e268 (17.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e123 (18.47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNasuse and vomiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.915\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,858 (83.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,300 (83.60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e558 (83.78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e363 (16.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e255 (16.40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e108 (16.22%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrinary retention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,299 (58.49%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e903 (58.07%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e396 (59.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e922 (41.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e652 (41.93%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e270 (40.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuncture pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,237 (55.70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e855 (54.98%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e382 (57.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e984 (44.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e700 (45.02%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e284 (42.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLumbar soreness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e919 (41.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e628 (40.39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e291 (43.69%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,302 (58.62%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e927 (59.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e375 (56.31%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower limb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.514\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emotor impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e337 (15.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e241 (15.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96 (14.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,884 (84.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,314 (84.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e570 (85.59%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSatisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e351 (15.80%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e256(16.46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95(14.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,870 (84.20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1299(53.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e571(85.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c6\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{X}\\)\u003c/span\u003e\u003c/span\u003e\u0026plusmn;S; n (%)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003eWelch Two Sample t-test; Pearson's Chi-squared test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eComparisons between training and validation sets demonstrated no statistically significant differences in any baseline variables (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), confirming balanced demographic/clinical distributions and validating the randomization suitability for predictive modeling.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eComparative Analysis of Satisfied vs. Dissatisfied Groups in Training Set\u003c/h2\u003e\u003cp\u003eThe training cohort comprised 1,555 parturients, with 1,299 (83.54%) classified as satisfied and 256 (16.46%) dissatisfied. Among continuous variables, body weight significantly differed between groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013), with lower values observed in the dissatisfied group. No significant differences were detected for age, height, gestational age, initial analgesic bolus, PIEB intervals, or total analgesia duration (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eCategorical variables revealed significant intergroup disparities (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05):\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eHigher complication rates in dissatisfied parturients: fever, nausea and vomiting, urinary retention, puncture pain, lumbar soreness, and motor impairment.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePronounced differences in puncture pain (65.63% vs. 40.95%) and lumbar soreness (92.97% vs. 53.04%).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eGravidity, parity, cervical dilation, PROM, DPE utilization, and cesarean delivery rates showed no statistical differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Complete data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of maternal clinical data between satisfied and unsatisfied groups in the training set\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eSatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDissatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c7\" namest=\"c6\" rowspan=\"2\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,299\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;256\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e29.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e29.69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeight(cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e160.71\u0026thinsp;\u0026plusmn;\u0026thinsp;5.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e160.06\u0026thinsp;\u0026plusmn;\u0026thinsp;4.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight(kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e67.32\u0026thinsp;\u0026plusmn;\u0026thinsp;8.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65.93\u0026thinsp;\u0026plusmn;\u0026thinsp;8.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGravidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.282\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e735 (56.58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e142 (55.47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e358 (27.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81 (31.64%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e206 (15.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e33 (12.89%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.500\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e939 (72.29%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e194 (75.78%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e309 (23.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54 (21.09%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e51 (3.93%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (3.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGestational age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e38.51\u0026thinsp;\u0026plusmn;\u0026thinsp;2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.713\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCervical dilation(cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.424\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e322 (24.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e57 (22.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026ndash;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e791 (60.89%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e167 (65.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e186 (14.32%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32 (12.50%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePROM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e866 (66.67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e181 (70.70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e433 (33.33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75 (29.30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDPE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.737\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e471 (36.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90 (35.16%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e828 (63.74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e166 (64.84%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInitial dose (ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e8.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.661\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime interval (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e50.47\u0026thinsp;\u0026plusmn;\u0026thinsp;5.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e49.98\u0026thinsp;\u0026plusmn;\u0026thinsp;5.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.167\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCEA duration (min)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e550.62\u0026thinsp;\u0026plusmn;\u0026thinsp;316.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e560.43\u0026thinsp;\u0026plusmn;\u0026thinsp;313.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e0.648\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCesarean delivery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.831\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,255 (96.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e248 (96.88%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (3.39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e8 (3.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,091 (83.99%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e196 (76.56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e208 (16.01%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e60 (23.44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNasuse and vomiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,102 (84.83%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e198 (77.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e197 (15.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e58 (22.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUrinary retention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e774 (59.58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e129 (50.39%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e525 (40.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e127 (49.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePuncture pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e767 (59.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e88 (34.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e532 (40.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e168 (65.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLumbar soreness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e610 (46.96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e18 (7.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e689 (53.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e238 (92.97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLower limb\u003c/p\u003e\u003cp\u003emotor impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e233 (17.94%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e8 (3.13%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,066 (82.06%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u003cp\u003e248 (96.88%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{X}\\)\u003c/span\u003e\u003c/span\u003e\u0026plusmn;S; n (%)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003eWelch Two Sample t-test; Pearson's Chi-squared test\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eFactors influencing maternal satisfaction with epidural analgesia​\u003c/h2\u003e\u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\u003ch2\u003eVariable Selection via LASSO Regression\u003c/h2\u003e\u003cp\u003eLASSO regression was employed to identify determinants of maternal satisfaction with epidural analgesia (MSEA). All variables presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were included in the analysis using the training cohort (n\u0026thinsp;=\u0026thinsp;1,555). This approach refined the predictors to five optimal variables: fever, nausea and vomiting, puncture pain, lumbar soreness and lower limb motor impairment. The model utilized 10-fold cross-validation with the one-standard-error rule to select the regularization parameter λ. This criterion identifies the most parsimonious model within one standard error of the minimum cross-validation error (largest λ value: λ\u0026thinsp;=\u0026thinsp;0.025), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea. Variable coefficient trajectories across λ values are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, with final LASSO coefficients shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe five predictors identified by LASSO regression underwent collinearity diagnostics. A correlation heatmap (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed) visualized pairwise Pearson correlation coefficients among variables, these results confirm the suitability of included predictors for multivariable modeling, though cautious interpretation is warranted to mitigate potential multicollinearity bias.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eUnivariate Analysis of Predictors for MSEA\u003c/h2\u003e\u003cp\u003eThe five variables selected by LASSO regression were subsequently analyzed using univariate logistic regression. All predictors demonstrated statistically significant associations with dissatisfaction after epidural analgesia (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05): fever (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004), nausea and vomiting (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), puncture pain (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lumbar soreness (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lower limb motor impairment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eThese results confirm each variable as a significant risk factor for maternal dissatisfaction, with detailed odds ratios and confidence intervals presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate Logistic Regression Analysis of Maternal Satisfaction with Epidural Analgesia\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplications\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDissatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.15, 2.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNasuse and vomiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.17, 2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuncture pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.08, 3.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLumbar soreness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.37, 19.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower limb\u003c/p\u003e\u003cp\u003emotor impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.53, 15.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003eOR = Odds Ratio, CI\u0026thinsp;=\u0026thinsp;Confidence Interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eMultivariable Analysis of Independent Risk Factors\u003c/h2\u003e\u003cp\u003eVariables identified as significant in LASSO regression were included as predictors in a multivariable logistic regression model, with maternal satisfaction as the outcome. After adjusting for potential confounders, five independent risk factors for dissatisfaction were confirmed (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05):\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFever: Increased dissatisfaction odds by 83% (OR\u0026thinsp;=\u0026thinsp;1.83, 95% CI: 1.26\u0026ndash;2.62; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eNausea/vomiting: 79% higher odds of dissatisfaction (OR\u0026thinsp;=\u0026thinsp;1.79, 95% CI: 1.23\u0026ndash;2.58; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePuncture pain: 78% elevated dissatisfaction risk (OR\u0026thinsp;=\u0026thinsp;1.78, 95% CI: 1.31\u0026ndash;2.43; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLumbar soreness: 10.89-fold higher odds vs. unaffected parturients (OR\u0026thinsp;=\u0026thinsp;10.89, 95% CI: 6.74\u0026ndash;18.69; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eMotor impairment: 9.70-fold increased odds vs. unimpaired women (OR\u0026thinsp;=\u0026thinsp;9.70, 95% CI: 4.95\u0026ndash;21.96; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eComplete multivariate regression results are provided in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariable Logistic Regression Analysis of Determinants of Dissatisfaction with Epidural Analgesia in Parturients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComplications\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDissatisfied\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFever\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.26, 2.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNasuse and vomiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.23, 2.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuncture pain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.31, 2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLumbar soreness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.74, 18.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLower limb\u003c/p\u003e\u003cp\u003emotor impairment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e233\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1,066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e248\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.95, 21.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e1\u003c/sup\u003eOR = Odds Ratio, CI\u0026thinsp;=\u0026thinsp;Confidence Interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eDevelopment and Validation of the MSEA Nomogram Prediction Model\u003c/h2\u003e\u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\u003ch2\u003eDevelopment of the Nomogram\u003c/h2\u003e\u003cp\u003eBased on multivariable logistic regression results, five independent predictors were incorporated into the nomogram for predicting maternal dissatisfaction with epidural analgesia (MSEA; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The model was constructed using R software, assigning weighted points to each variable proportional to its regression coefficient.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNomogram Interpretation:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFor each predictor, draw a vertical line to the Points axis to determine its individual score.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eSum all variable scores to obtain the Total Points value.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eProject a vertical line downward from Total Points to the Risk of Dissatisfaction axis.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe resulting value represents the predicted probability of maternal dissatisfaction with epidural analgesia.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eValidation and Evaluation of the Nomogram Model\u003c/h2\u003e\u003cdiv id=\"Sec24\" class=\"Section4\"\u003e\u003ch2\u003eModel Discrimination Assessment\u003c/h2\u003e\u003cp\u003eThe nomogram's discriminatory power was evaluated using ROC curves and corresponding AUC values. Predictive performance was interpreted as: poor discrimination (AUC\u0026thinsp;\u0026lt;\u0026thinsp;0.600), moderate discrimination (AUC 0.600\u0026ndash;0.750), good discrimination (AUC\u0026thinsp;\u0026gt;\u0026thinsp;0.750). In the training set, the model achieved an AUC of 0.789 (95% CI: 0.764\u0026ndash;0.814) with 57.74% sensitivity and 91.02% specificity. The validation set yielded an AUC of 0.764 (95% CI: 0.720\u0026ndash;0.809), demonstrating 59.72% sensitivity and 88.42% specificity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). These results indicate robust discrimination capacity for MSEA prediction. Concordance indices further validated ranking consistency:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTraining set C-index: 0.789\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eValidation set C-index: 0.764\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThe model effectively prioritized dissatisfied parturients with stable ranking performance.\u003c/p\u003e\u003cp\u003eThe final logistic regression model was translated into an accessible nomogram. To enhance clinical utility, a complementary web-based tool was developed for real-time risk calculation at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zhp1999.shinyapps.io/dynnomapp\u003c/span\u003e\u003cspan address=\"https://zhp1999.shinyapps.io/dynnomapp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. This interactive platform dynamically generates dissatisfaction probabilities based on predictor inputs, as demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eModel Calibration Assessment\u003c/h2\u003e\u003cp\u003eCalibration was evaluated using calibration curves and the Hosmer-Lemeshow goodness-of-fit test. Calibration curves visualize agreement between predicted probabilities (x-axis) and observed outcomes (y-axis), where:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eBlue dashed line (Ideal): Perfect prediction reference\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRed solid line (Apparent): Model's actual performance\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eGreen solid line (Bias-corrected): Bootstrap-corrected curve (1,000 resamples) reflecting true population performance\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eCloser alignment between solid and dashed lines indicates superior calibration. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and b, both training and validation sets demonstrated excellent curve concordance with the ideal line.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe Hosmer-Lemeshow test confirmed good fit (χ\u0026sup2; = 4.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.205), indicating no significant deviation between predicted and observed dissatisfaction probabilities (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These results align with the calibration curve findings.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eClinical Utility via Decision Curve Analysis\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec and d presents decision curves for the nomogram in training and validation sets. The horizontal axis denotes the threshold probability, while the vertical axis represents net benefit \u0026ndash; quantifying clinical value after accounting for false positives.\u003c/p\u003e\u003cp\u003eThe high-risk threshold indicates the probability level where clinicians would consider intervention despite potential trade-offs. The model demonstrated clinical utility across threshold probabilities of:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eTraining set: 3\u0026ndash;40%\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eValidation set: 3\u0026ndash;30%\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eWithin these ranges, the nomogram provided superior net benefit compared to \"treat-all\" or \"treat-none\" strategies, confirming its value for guiding individualized clinical decisions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eEpidural analgesia represents a pivotal advancement in modern obstetric care, significantly enhancing the childbirth experience. However, maternal satisfaction remains influenced by multifaceted factors including analgesic efficacy, complication profiles, and individual variability. While epidural analgesia continues to serve as the primary method for labor pain management due to its established effectiveness and safety profile \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, procedure-related complications directly impact satisfaction levels \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, subsequently affecting overall birth experiences and postpartum recovery trajectories. Current research predominantly focuses on technical aspects (e.g., infusion modes, drug selection, concentration optimization) or labor parameters (e.g., second-stage duration) \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, with limited systematic investigation into perinatal complications. Consequently, our integrated analysis of associations between perinatal complications and epidural satisfaction provides a framework for optimizing personalized analgesic management. This approach enables targeted reduction of complication incidence, thereby enhancing maternal satisfaction while improving childbirth experiences.\u003c/p\u003e\u003cp\u003e Our analysis incorporated comprehensive perinatal clinical data, utilizing LASSO regression for initial variable screening followed by univariate and multivariate logistic regression. Results confirmed fever, nausea/vomiting, puncture pain, lumbar soreness, and lower limb motor impairment as significant risk factors for maternal dissatisfaction with epidural analgesia. Crucially, multivariate analysis established these perinatal complications as independent predictors of dissatisfaction.\u003c/p\u003e\u003cp\u003eClinical observations indicate that procedural pain during epidural placement triggers stress responses and heightens patient anxiety \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Our findings quantitatively demonstrate that puncture pain increases dissatisfaction risk by 78% (OR\u0026thinsp;=\u0026thinsp;1.78). Lv et al.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e reported intranasal low-dose dexmedetomidine significantly improved Ramsay sedation scores and reduced puncture-related pain. Sun et al.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e confirmed analogous outcomes, noting procedural pain directly compromises labor analgesia experiences. These collective findings underscore that mitigating puncture pain through targeted interventions\u0026mdash;such as adjuvant sedation protocols\u0026mdash;holds demonstrated clinical significance for optimizing analgesia efficacy and enhancing maternal satisfaction.\u003c/p\u003e\u003cp\u003eIntrapartum fever occurs in up to 15.8% of parturients receiving labor analgesia\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Two predominant hypotheses explain its etiology: One implicates thermoregulatory dysregulation from analgesic agents, initially evidenced by Fusi et al. (1989) who documented significantly elevated mean temperatures in epidural recipients\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Another proposes maternal-fetal inflammatory processes, exemplified by Curtin et al.'s finding that histologic chorioamnionitis and epidural analgesia were independently associated with intrapartum fever \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Compared to afebrile counterparts, febrile parturients face increased risks of instrumental delivery and cesarean section\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Maternal fever directly impacts obstetric decision-making, while consequent interventions indirectly endanger neonates. Epidural analgesia constitutes the strongest independent risk factor for intrapartum fever (over 10-fold increase)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Although neonatal consequences remain debated\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, maternal concerns about potential fetal risks inevitably heighten perinatal anxiety. This mechanistic and psychological burden substantiates fever as a critical determinant of epidural satisfaction \u0026ndash; a finding aligning with our multivariate results (OR\u0026thinsp;=\u0026thinsp;1.83).\u003c/p\u003e\u003cp\u003eEvidence indicates that postoperative nausea and vomiting (PONV) following elective cesarean delivery correlates with maternal dissatisfaction regarding pre-anesthesia assessment practices\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Proactive perioperative evaluation by anesthesiologists and prophylactic antiemetics demonstrably improve satisfaction\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Echoing this, Ida et al.'s study on spinal anesthesia for cesarean sections confirmed that intraoperative antiemetic use positively influenced satisfaction (AOR\u0026thinsp;=\u0026thinsp;0.71; 95% CI: 0.53\u0026ndash;0.94)\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. While our study identified nausea and vomitting as an independent risk factor for reduced epidural satisfaction (OR\u0026thinsp;=\u0026thinsp;1.79), the inclusion of both vaginal and cesarean deliveries limited our ability to analyze prophylactic antiemetic administration\u0026mdash;a variable warranting future investigation.\u003c/p\u003e\u003cp\u003eDivergent findings exist regarding back pain etiology: Prospective studies implicate multiple spinal needle attempts, PONV, and postoperative back pain as predictors of spinal anesthesia dissatisfaction, with refusal of repeat procedures linked primarily to back pain and prior negative experiences\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Conversely, epidural analgesia shows no increased risk of early or 6-month postpartum back pain compared to unmedicated deliveries, despite a 30% prevalence across both groups\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. This paradox suggests lumbar soreness likely stems from multifactorial origins\u0026mdash;including labor fatigue, physical exertion, immediate postpartum postural stress, and later musculoskeletal strain from infant care\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Notably, while lumbar soreness affected only 7% of dissatisfied parturients in our training cohort, these women demonstrated a striking 10.89-fold increased dissatisfaction risk compared to unaffected counterparts (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This profound impact necessitates multifaceted interventions: implementing targeted strategies for postpartum back pain management alongside structured education programs demystifying epidural procedures\u0026mdash;both critical for rectifying misconceptions about obstetric complications and alleviating procedure-related anxieties. Furthermore, technical optimization through minimizing puncture attempts by experienced anesthesiologists reduces tissue trauma, potentially mitigating lumbar soreness incidence and collectively enhancing maternal satisfaction with epidural analgesia.\u003c/p\u003e\u003cp\u003eA systematic review and meta-analysis indicates that programmed intermittent epidural bolus (PIEB) combined with patient-controlled epidural analgesia (PCEA) enhances maternal satisfaction, potentially attributable to reduced local anesthetic consumption, decreased incidence of lower limb motor impairment, and higher spontaneous vaginal delivery rates\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. While conventional wisdom suggests PCEA alone improves satisfaction by augmenting maternal control over pain management\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, evidence demonstrates that standalone PCEA fails to increase satisfaction or perceived control compared to continuous epidural infusion (CIEA) or intermittent bolus techniques (IBEA)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This paradox underscores that optimizing drug delivery regimens to minimize motor impairment critically influences satisfaction\u0026mdash;a finding corroborated by our multivariate analysis identifying motor impairment as a high-risk dissatisfaction factor (OR\u0026thinsp;=\u0026thinsp;9.70). The apparent discrepancy between our motor impairment incidence (84.8%) and prior meta-analytical reports (14.36%)\u003csup\u003e18\u003c/sup\u003e primarily stems from definitional variations: our operational criteria encompassed ambulatory dysfunction (numbness, paresthesia) reflecting real-world perinatal experiences. Pharmacological strategies\u0026mdash;such as using 0.125% ropivacaine-sufentanil over bupivacaine equivalents\u0026mdash;may reduce motor block incidence, though lower concentrations (e.g., 0.1% ropivacaine) risk inadequate analgesia without eliminating impairment\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Mitigating motor impairment remains imperative for facilitating postpartum functional rehabilitation; preserved mobility fosters positive psychological states and accelerates recovery, directly enhancing childbirth experiences and indirectly reinforcing epidural satisfaction through demonstrable functional benefits.\u003c/p\u003e\u003cp\u003eThe predictive model for maternal satisfaction with epidural analgesia (MSEA) leveraged LASSO regression with 10-fold cross-validation (λ\u0026thinsp;=\u0026thinsp;0.025) to identify five core predictors from perinatal complications: fever, nausea and vomiting, puncture pain, lumbar soreness, and motor impairment. This approach effectively mitigated overfitting (cross-validation error within one standard error) while preserving clinically synergistic variables. Collinearity diagnostics revealed a moderate positive correlation between puncture pain and lumbar soreness (r\u0026thinsp;=\u0026thinsp;0.37), potentially attributable to combined tissue irritation and positional compression during epidural procedures. Critically, LASSO regularization compressed redundant information rather than eliminating collinear variables\u0026mdash;retaining clinical authenticity by acknowledging their pathological interdependence (e.g., puncture trauma potentiating neuropathic compression). Other variables exhibited near-zero correlations, confirming controlled multicollinearity risk.\u003c/p\u003e\u003cp\u003eUnivariate analysis identified extreme initial effects for lumbar soreness (OR\u0026thinsp;=\u0026thinsp;11.71) and motor impairment (OR\u0026thinsp;=\u0026thinsp;6.78), but multivariable adjustment attenuated these to OR\u0026thinsp;=\u0026thinsp;10.89 and OR\u0026thinsp;=\u0026thinsp;9.70, respectively, indicating that 7.0%-43.1% of univariate effects stemmed from confounding synergies. Notably, puncture pain's OR reduction (2.75\u0026rarr;1.78) suggests partial mediation through lumbar pathways, warranting future mediation analysis. The modest ORs for fever (1.83) and nausea and vomiting (1.79) reflect their nonspecific pathophysiology (inflammatory cascades and opioid effects).\u003c/p\u003e\u003cp\u003eThe resultant nomogram demonstrated robust generalizability: discrimination consistency between training (AUC\u0026thinsp;=\u0026thinsp;0.789) and validation sets (AUC\u0026thinsp;=\u0026thinsp;0.764) was high, with minimal C-index divergence (3.2%). Calibration accuracy was confirmed by Hosmer-Lemeshow testing (χ\u0026sup2;=4.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.205) and curve alignment. Decision curve analysis affirmed net clinical benefit across 3%-40% threshold probabilities versus default strategies.\u003c/p\u003e\u003cp\u003eThe web-based dynamic nomogram (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zhp1999.shinyapps.io/dynnomapp/\u003c/span\u003e\u003cspan address=\"https://zhp1999.shinyapps.io/dynnomapp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) enables instant risk visualization, surpassing traditional scoring systems in clinical utility.\u003c/p\u003e\u003cp\u003eThis study pioneers the first perinatal complication-based nomogram for predicting maternal satisfaction with epidural analgesia (MSEA), offering dual innovations: clinical interpretability through regression coefficient-weighted risk quantification (e.g., lumbar soreness contributing 38.6% predictive weight), and operational accessibility via an online scoring tool providing real-time decision support.\u003c/p\u003e\u003cp\u003eLimitations warrant consideration: First, single-center data introduces selection and admission biases; second, retrospective design with internal validation necessitates external verification to assess generalizability; third, 24-hour follow-up misses delayed complications (e.g., post-dural puncture headache peaking at 72 hours)\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e; fourth, satisfaction\u0026rsquo;s multidimensional nature\u0026mdash;encompassing sociodemographic, psychosocial, and care-quality factors\u0026mdash;remains partially unexplored. Nevertheless, this model identifies validated independent risk factors with robust discrimination (AUC 0.764\u0026ndash;0.789) and calibration accuracy (χ\u0026sup2;=4.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.205), establishing a clinically actionable reference.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eFever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment were identified as independent risk factors for maternal dissatisfaction with epidural analgesia. The perinatal complication-based nomogram demonstrated strong discriminative capability and calibration accuracy, providing a validated tool for clinical implementation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYihan Zheng and Haiping Zhang contributed equally to this work (co-first authors). Yihan Zheng designed the study protocol, collected and analyzed the clinical data, and drafted the initial manuscript. Haiping Zhang assisted in data analysis, performed statistical modeling for the predictive nomogram, and revised the manuscript critically for important intellectual content. Xizhu Wu participated in clinical data collection, conducted preliminary data sorting, and ensured the accuracy of raw data. Wenqiang You provided insights into the association between obstetric clinical practices and perinatal complications during the initial study conceptualization phase. Chuantao Lin (co-corresponding author) supervised the entire process of data quality control, particularly for perinatal complication indicators (e.g., fever, lumbar soreness, lower limb motor impairment), participated in the validation of the nomogram model, and revised the manuscript to refine the interpretation of anesthetic-related outcome data. Li Zhang (corresponding author) conceived and supervised the overall study design, provided expert guidance on statistical analysis and clinical significance interpretation of results, and finalized the manuscript for submission. All authors have read and approved the final version of the manuscript, and confirm that no relevant contributions have been omitted. The co-corresponding authors (Chuantao Lin and Li Zhang) are responsible for the overall direction of the study, handling editorial correspondence, ensuring the integrity of the work, and responding to post-publication queries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding authors upon reasonable request. The data are not publicly available due to privacy and ethical restrictions related to the inclusion of patient clinical information, as specified by the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to all the parturients who participated in this study and contributed their clinical data, without which this research would not have been possible. We are deeply thankful to the medical staff of Fujian Maternity and Child Health Hospital, especially those from the Departments of Anesthesiology, Obstetrics, and related units, for their invaluable assistance in data collection, patient care, and logistical support throughout the study process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to the funds of Joint Funds for the innovation of science and Technology, Fujian province (Grant number:2023Y9390).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted in accordance with the Declaration of Helsinki. The study protocol was approved by the Institutional Review Board of Fujian Maternity and Child Health Hospital (Approval No. 2021KLRD09022). Given the retrospective, observational, and anonymous nature of data collection, the requirement for informed consent was waived by the ethics committee. All procedures involving human participants were performed in compliance with relevant ethical guidelines and regulations to ensure the protection of patient privacy and data confidentiality.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChassard, D. et al. Anesthesia practices for management of labor pain and cesarean delivery in France (EPIDOL): A cross-sectional survey. \u003cem\u003eAnaesth. 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K. \u0026amp; Shepherd, D. B. Post-dural puncture headache: pathogenesis, prevention and treatment. \u003cem\u003eBr. J. Anaesth.\u003c/em\u003e \u003cb\u003e91\u003c/b\u003e, 718\u0026ndash;729. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bja/aeg231\u003c/span\u003e\u003cspan address=\"10.1093/bja/aeg231\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Epidural Analgesia, Perinatal Complications, Maternal Satisfaction, Risk Factors, Nomogram","lastPublishedDoi":"10.21203/rs.3.rs-7354374/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7354374/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMaternal satisfaction with epidural analgesia (MSEA) is influenced by multiple factors. This study aimed to develop and validate a predictive model for MSEA based on perinatal complications associated with epidural analgesia, providing a tool for personalized analgesia protocols and enhanced childbirth experiences. We retrospectively analyzed clinical data from 2,221 parturients admitted to Fujian Maternity and Child Health Hospital (July 2023\u0026ndash;March 2024). The cohort was randomly divided into training (1,555 cases) and internal validation (666 cases) sets at a 7:3 ratio. In the training set: Statistically significant variables were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Collinearity diagnostics assessed variable relationships. Univariate and multivariate logistic regression identified independent predictors of MSEA and constructed a nomogram. Validation: Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curves, Hosmer-Lemeshow test, and decision curve analysis (DCA) for clinical net benefit. The prevalence of maternal dissatisfaction with epidural analgesia was 15.80% (351/2,221). Independent risk factors included fever (OR\u0026thinsp;=\u0026thinsp;1.83, 95% CI: 1.26\u0026ndash;2.62, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), nausea and vomiting (OR\u0026thinsp;=\u0026thinsp;1.79, 95% CI: 1.23\u0026ndash;2.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), puncture pain (OR\u0026thinsp;=\u0026thinsp;1.78, 95% CI: 1.31\u0026ndash;2.43, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lumbar soreness (OR\u0026thinsp;=\u0026thinsp;10.89, 95% CI: 6.74\u0026ndash;18.64, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and lower limb motor impairment (OR\u0026thinsp;=\u0026thinsp;9.70, 95% CI: 4.95\u0026ndash;21.96, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The nomogram showed strong discrimination, with AUCs of 0.789 (95% CI: 0.764\u0026ndash;0.814; training) and 0.764 (95% CI: 0.720\u0026ndash;0.809; validation). Calibration curves and Hosmer-Lemeshow test (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.205) indicated excellent agreement between predicted and observed outcomes. DCA confirmed clinical utility. Fever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment independently predict maternal dissatisfaction with epidural analgesia (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The validated nomogram based on perinatal complications effectively predicts MSEA, demonstrating robust discrimination and calibration.\u003c/p\u003e","manuscriptTitle":"Development of a Predictive Model for Maternal Satisfaction with Epidural Analgesia Based on Perinatal Complications","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 10:01:05","doi":"10.21203/rs.3.rs-7354374/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-23T14:55:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-22T21:11:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"177347860720028791787191493614770537634","date":"2026-03-20T14:52:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-09T11:23:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41408599726542275174053061131441942786","date":"2026-01-05T01:00:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-07T05:02:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-15T19:50:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-13T09:00:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T08:47:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-18T15:42:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c476fe52-6af0-4295-8101-3ef6efeed166","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":59257313,"name":"Health sciences/Diseases"},{"id":59257314,"name":"Health sciences/Health care"},{"id":59257315,"name":"Health sciences/Medical research"},{"id":59257316,"name":"Health sciences/Neurology"},{"id":59257317,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-27T16:08:59+00:00","versionOfRecord":{"articleIdentity":"rs-7354374","link":"https://doi.org/10.1038/s41598-026-50262-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-24 15:59:17","publishedOnDateReadable":"April 24th, 2026"},"versionCreatedAt":"2025-12-11 10:01:05","video":"","vorDoi":"10.1038/s41598-026-50262-2","vorDoiUrl":"https://doi.org/10.1038/s41598-026-50262-2","workflowStages":[]},"version":"v1","identity":"rs-7354374","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7354374","identity":"rs-7354374","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}