Trial of Vaginal Birth After Cesarean (VBAC): External validation of the Polish prediction indices of the VBAC

Trial of Vaginal Birth After Cesarean (VBAC): External validation of the Polish prediction indices of the VBAC | 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 Research Article Trial of Vaginal Birth After Cesarean (VBAC): External validation of the Polish prediction indices of the VBAC Szymon Paruszewski, Aleksandra Urban, Agnieszka Dobrowolska-Redo, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8330044/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background Vaginal birth after cesarean section (VBAC) is a safe option for both mothers and children. Currently available prediction tools have not been validated in the Polish population. Dobrowolska-Redo proposed a model for predicting VBAC success, and the aim of this study was to evaluate its clinical utility. Methods This retrospective analysis of data collected from 462 pregnant women with a history of one previous cesarean section, all qualified for a VBAC attempt. Deliveries occurred between January 1, 2021, and December 31, 2023, at the II Department of Obstetrics and Gynecology, Medical University of Warsaw. Inclusion criteria were: previous low transverse cesarean section, singleton pregnancy, no indication for elective cesarean delivery, and live birth. Ethical approval was granted by the local committee (reference no. AKBE/300/2024). The data were anonymized before analysis. Results Among the cohort of 462 women, 271 (58.7%) had successful VBAC, whereas 191 (41.3%) underwent intrapartum cesarean section. The prediction model for preterm births (pTi) showed no clinical utility. The median Ti score differed significantly between the VBAC group and the cesarean group. Removing two parameters (manual labor and place of residence) improved model performance. Higher BMI increased the likelihood of cesarean delivery, both before pregnancy (23.43 vs. 24.54 kg/m²; p = 0.006) and at delivery (27.99 vs. 29.36 kg/m²; p = 0.007). Prior vaginal birth was a strong predictor of successful VBAC (31.5% vs. 11.2%; p = 0.000), as was a history of fetal macrosomia (15.5% vs. 8.7%; p = 0.047). Gestational diabetes was more common in women who ultimately required cesarean delivery (34.2% vs. 23.7%; p = 0.023). Epidural anesthesia use correlated with a lower cesarean rate (26.6%; p = 0.000). Conclusions In this single-center cohort, the Polish index model for full-term VBAC (Ti) prediction showed moderate accuracy. A refined version demonstrated improved performance compared with the original. Several predictors of successful VBAC were confirmed, including prior vaginal delivery and history of macrosomia, while high BMI and gestational diabetes increased the risk of intrapartum cesarean section. Trial registration Retrospectively registered. Vaginal birth after cesarean section prediction index model calculator risk factors Figures Figure 1 Figure 2 Figure 3 Background In 1985, a consensus was established by the WHO stating that the percentage of births via cesarean section should be maintained at 10–15%1 . According to recent WHO studies, the rates of cesarean section have been steadily increasing, reaching 21% of all births worldwide in 2021, on the basis of the latest available data 2 . It is anticipated that by 2030, cesarean deliveries will account for 29% of all births worldwide 1,2 . According to a report by the National Health Service, a noticeable decrease in the number of births in Poland occurred between 2019 and 2022, with a simultaneous increase in the proportion of births by cesarean section, from 45% in 2019 to 48% in 2022. Moreover, in 2023, this percentage was 32.4% in the USA and 48% in Poland 3,4 . The consequence of this trend is an increase in the cost of childbirth, as well as an increase in the risk of short-term and long-term maternal and neonatal complications 5 . A direct consequence of the increasing rate of cesarean section is an increase in the proportion of pregnant women with a history of cesarean delivery. Women who have previously undergone a cesarean section, due to urgent or reversible indications, may be eligible for either a vaginal birth after cesarean (VBAC) or an elective repeat cesarean section. Both VBAC and repeat cesarean sections carry an elevated risk of perinatal complications 6 , with the risk of severe complications increasing with each subsequent cesarean section 7 . While successful VBAC is the least risky option, with a success rate of 60–80% 8 , unplanned cesarean section during a VBAC trial significantly increases the complication rate compared with elective repeat cesarean section. Since 1990, various prediction models and risk assessment calculators have been developed to evaluate the likelihood of a successful VBAC and to assist both physicians and patients in deciding whether to attempt it 9 . General factors associated with a greater probability of a successful VBAC, such as a history of vaginal delivery or low BMI, have been identified 10 . However, these factors alone do not provide precise estimates, nor do they allow for the development of specific prediction models that would enable patients to make fully informed decisions about their mode of delivery. The only VBAC success prediction model that has found clinical application is the Maternal - Fetal Medicine Units (MFMU) Network model. It predicts VBAC success on the basis of six variables known as early as the first prenatal visit 11 . Although this model has been validated in multiple studies across different populations, the findings have unfortunately been inconsistent, leading to divergent conclusions, which led to its subsequent editions 12,13 . Currently, the literature lacks validated tools for predicting VBAC success in the Polish population. In 2019, in her doctoral dissertation 14 , an intrapartum cesarean section hazard ratio index model was developed for pregnant women who were qualified for VBAC, called the Polish Prediction Indices of VBAC (pTi/Ti), on the basis of variables from a cohort of 412 pregnant women who had previously undergone a single cesarean section. The study was conducted in the delivery room at the Second Department of Obstetrics and Gynecology Warsaw Medical University, covering the period from January 1, 2013, to December 31, 2015. The author used multivariate logistic regression analysis, which resulted in formulas estimating the probability of requiring an intrapartum cesarean section. The Index models provided separate risk assessments for two groups: Women who delivered preterm (pTi index – pre-Term index). Women delivering at term (Ti index – Term index). Some of the variables included in the Index models are definitively known at the time of delivery, which may improve the accuracy of the VBAC success estimation. The study revealed that the risk of requiring an intrapartum cesarean section was more than twice as high among women who delivered preterm (OR = 2.06; P < .005). The index model’s predictive performance was evaluated via an ROC curve, which yielded an AUC of 0.94 (95% CI: 0.90–0.99) for preterm deliveries (pTi) and 0.71 (95% CI: 0.64–0.77) for term deliveries (Ti). Methods Study design and data acquisition This study was a retrospective analysis of collected data from a cohort of pregnant women with a history of one previous cesarean section who were eligible for a vaginal birth after a cesarean delivery (VBAC). These women gave birth at the II Department of Obstetrics and Gynecology of the Medical University of Warsaw (Księżna Anna Mazowiecka Clinical Hospital in Warsaw), a tertiary referral center, between January 1, 2021, and December 31, 2023. The demographic and obstetric data of the patients were obtained from the clinic's archives. During the creation and development of the database, all patient identification data were anonymized to ensure confidentiality. Demographic and obstetric data were incorporated into the validated index models to predict the probability of intrapartum cesarean section risk after one previous cesarean section (in both study groups). The performance of the index models in the current study cohort was then compared with their performance in the original study cohort. Selection criteria The inclusion criteria for the study were a history of one previous cesarean section in the lower uterine segment, singleton pregnancy, no indications for elective cesarean section (qualified for a VBAC trial), and live birth. The exclusion criterion for the study was lack of consent for the VBAC trial. Out of 7983 deliveries during the study period, after applying the selection criteria, 462 pregnant women (5.8%) were included in the study. Given the significantly different risks associated with delivery, the study participants were divided into two groups: preterm delivery and term delivery. Study outcomes The primary objective of this study was to verify the factors influencing VBAC success as established by Dobrowolska-Redo and to externally validate her index models, assessing their utility in predicting the risk of intrapartum cesarean section after a previous abdominal delivery in the Polish population. A secondary objective is to evaluate additional variables within the study cohort, analyze their correlation with the risk of intrapartum cesarean section, and refine the index models to improve their predictive accuracy. Predictors The patient data included: age, type of work, marital status, population size of place of residence, smoking before and during pregnancy, weight before pregnancy and weight just before delivery, BMI before pregnancy and BMI just before delivery, height, previous pregnancies, previous miscarriages, previous natural deliveries, indications for previous cesarean section, occurrence of fetal macrosomia in previous pregnancies, week of pregnancy in which delivery occurred, indications and method of labor induction if it occurred, method of delivery, indications for cesarean section or operative delivery if it occurred, length of each stage of labor, use of epidural anesthesia during delivery, anesthesia used during cesarean section if it occurred; whether the pregnancy was complicated by: risk of preterm birth, cholestasis, urinary tract infection, anemia, pre-pregnancy hypertension, pregnancy-induced hypertension, pre-pregnancy diabetes, gestational diabetes; occurrence of postpartum anemia. The data collected on newborns included: estimated weight on ultrasound scan up to 7 days before delivery, sex, birth weight, birth length, and Apgar score at 1 and 5 minutes after delivery. Statistical analysis Statistical analysis was conducted via the Statistica 13 software package. A p value < 0.05 was considered statistically significant. A comparison of the study groups was then performed. Differences between women who had successful VBAC and those whose pregnancies ended with cesarean section were analyzed. Qualitative data were compared via the chi-square (χ²) test, and quantitative data were analyzed via the Mann‒Whitney test. Then, the Polish prediction indices of the VBAC were evaluated. The pTi/Ti models were assessed in the new cohort via receiver operating characteristic (ROC) curves. The index model AUCs were compared with the AUCs obtained in the original study. The optimal ROC cutoff point was determined via the Youden method. At this cutoff point, the sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) were calculated and compared with those from the original studies. Ethical approval This retrospective study was approved by the local institutional ethical committee (reference no. AKBE/300/2024; obtained on 18.11.2024). Written informed consent was not required because unidentifiable patient information used only. Results Preliminary results Among the 462 pregnant women included in the study, 271 (58.7%) had a successful vaginal birth, whereas 191 (41.3%) required an intrapartum cesarean section. In the preterm delivery group, the prediction index (pTi) did not demonstrate effectiveness, yielding completely divergent results. As a result, further analyses in this subgroup were discontinued, and the study focused exclusively on the Index for term deliveries (Ti) group . The following results were obtained for only the study group (393 pregnant women). Factors associated with the success or failure of VBAC Statistically significant differences were observed between the group that had a successful VBAC and the group that required an intrapartum cesarean section. High BMI values, both before pregnancy (23.43 kg/m 2 vs. 24.54 kg/m 2 ; p = 0.006) and before delivery (27.99 kg/m 2 vs. 29.36 kg/m 2 ; p = 0.007), were associated with an increased risk of intrapartum cesarean section. In contrast, the number of previous pregnancies played a protective role, as women with a greater number of pregnancies had a significantly lower risk of requiring a cesarean section (1.5 vs. 1; p = 0.000). A strong predictor of successful VBAC was a history of vaginal delivery (31.5% vs. 11.2%; p = 0.000); women who had previously given birth vaginally had a much lower risk of requiring a cesarean section during labor, as only 19.8% of these women required a cesarean section. A history of fetal macrosomia in previous pregnancies was also a predictor of successful VBAC (15.5% vs. 8.7%; p = 0.047), as only 28% of women with a history of fetal macrosomia in previous pregnancies required a cesarean section. These predictors significantly reduced the likelihood of intrapartum cesarean section. Conversely, gestational diabetes was linked to a significantly greater risk of intrapartum cesarean section, affecting 34.2% of the women in the cesarean group compared with 23.7% in the successful VBAC group (p = 0.023). Interestingly, the use of epidural anesthesia was associated with a lower risk of intrapartum cesarean section, as only 26.6% of women who received epidural anesthesia required a cesarean section (p = 0.000). The results are summarized in Table 1. Table 1. Characteristics of the study cohort of pregnant women with term deliveries. VBAC (232) C-s (161) Parameter Median (Q1-Q3) or n (%) Median (Q1-Q3) or n (%) p value Age (years) 33.0 (30.0-36.0) 33.0 (30.0-36.0) .752 Gestational weight gain (kg) 12.7 (9.7-15.7) 12.0 (8.5-15.5) .316 Prepregnancy body weight (kg) 65.0 (56.3-73.8) 66.0 (56.0-76.0) .278 Body weight before delivery (kg) 78.0 (69.0-87.0) 78.0 (68.5-87.5) .576 Prepregnancy BMI (kg/m 2 ) 23.43 (20.60-26.30) 24.54 (21.30-27.80) .006 BMI before delivery (kg/m 2 ) 27.99 (25.20-30.80) 29.36 (26.40-32.30) .007 Number of previous pregnancies 1.5 (1.0-2.0) 1.0 (0.5-1.5) .000 Delivery week 39.0 (38.0-40.0) 39.0 (38.0-40.0) .858 Estimated fetal weight (g) 3405.0 (3187.0-3623.0) 3508.0 (3249.5-3766.5) .082 Birth weight (g) 3420.0 (3175.0-3665.0) 3450.0 (3170.0-3730.0) 0.750 Vaginal delivery in the past 73 (31.5%) 18 (11.2%) .000 Fetal macrosomia in previous pregnancies 36 (15.5%) 14 (8.7%) .047 Risk of preterm delivery 12 (5.2%) 6 (3.2%) .500 Cholestasis in pregnancy 4 (1.7%) 2 (1.2%) .702 Urinary tract infection in pregnancy 11 (4.7%) 7 (4.3%) .854 Anemia in pregnancy 41 (17.7%) 29 (18.0%) .931 Prepregnancy hypertension 11 (4.7%) 11 (6.8%) .375 Pregnancy-induced hypertension 8 (3.4%) 9 (5.6%) .305 Prepregnancy diabetes 10 (4.3%) 9 (5.6%) .561 Gestational diabetes 55 (23.7%) 55 (34.2%) .023 Epidural anesthesia used 157 (67.7%) 57 (35.4%) .000 VBAC – vaginal birth after cesarean C-s – cesarean section BMI – body mass index Bolded p values are statistically significant. The effectiveness of the Polish Ti index Applying the Polish prediction index of VBACs (Ti) to the studied cohort of full-term deliveries resulted in an AUC value of 0.671 (95% CI: 0.671–0.724). This finding is comparable to the results obtained in the original cohort studied by Dobolska-Redo, where the AUC was 0.71 (95% CI: 0.64–0.77). These findings confirm the predictive ability of the constructed index model (Figure 1). A statistically significant difference was observed in the median Polish prediction index of VBAC (Ti) values between women who had a successful VBAC and those who required a repeat intrapartum cesarean section. The median Ti model for successful vaginal deliveries was 0.308, whereas for women requiring a repeat cesarean section, it was 0.403 (Mann‒Whitney test, p < 0.001; Table 2). These findings are consistent with those reported by Dobolska-Redo, further validating the index model's effectiveness. Table 2. Median values of Ti according to method of delivery. Mann‒Whitney Test (p=0,000000) Method of delivery N Mean Median Minimum Maximum Lower quartile Upper quartile Standard Deviation VBAC 232 0.3224 0.3076 0.0484 0.7481 0.2107 0.4250 0.1449 C-s 161 0.4186 0.4027 0.0718 0.9143 0.3038 0.4940 0.1649 VBAC – vaginal birth after cesarean C-s – cesarean section For the proposed cutoff point of 0.34 on the ROC curve, the Ti model demonstrated the following predictive parameters: Sensitivity: 69.6%; specificity: 63.4%; positive predictive value (PPV): 54.2%; negative predictive value (NPV): 73.4%; overall accuracy: 63.4% The Youden index, which was used to optimize sensitivity and specificity, reached its highest value at 0.29 (Figure 2, Table 3). These results confirm the potential utility of the Polish prediction index of the VBAC (Ti) in predicting intrapartum cesarean section risk among women attempting VBAC. Table 3. Predictors of performing an intrapartum cesarean section for term deliveries according to the value of the Ti model assessed by sensitivity, specificity, PPV and NPV, original results (left) vs. validation results (right). TI Sensivity (%) Specificity (%) PPV (%) NPV (%) Original results Validation results Original results Validation results Original results Validation results Original results Validation results 0 100.0 100.0 0.0 0.0 32.8 41.0 - - 0.1 99.9 98.8 1.0 3.0 32.8 41.4 66.7 77.8 0.2 92.1 92.5 26.6 21.6 38.0 45.0 87.3 80.6 0.3 70.3 75.2 58.5 49.1 45.2 50.6 80.1 74.0 0.4 38.6 51.6 82.6 70.3 52.0 54.6 73.4 67.6 0.5 19.8 23.6 90.8 89.2 51.3 60.3 69.9 62.7 0.6 10.9 14.9 96.1 95.3 57.9 68.6 68.9 61.7 0.7 3.0 6.8 98.1 98.7 42.9 78.6 67.4 60.4 0.8 2.0 2.5 99.5 100.0 66.7 100.0 67.5 59.6 0.9 0.0 0.6 100.0 100.0 - 100.0 67.2 59.2 1 0.0 0.00 100.0 100.0 - - 67.2 59.2 PPV – positive predictive value NPV – negative predictive value Discussion Principal Findings This study was a single-center retrospective analysis aimed at assessing the clinical utility of intrapartum cesarean section hazard ratio index models, called the Polish Prediction Indices of VBAC (pTi/Ti), for predicting intrapartum cesarean section after one previous cesarean delivery in the Polish population. Additionally, we sought to identify factors influencing the risk of intrapartum cesarean section. Our findings highlight key factors influencing the success of VBAC and reinforce the importance of individualized risk assessment in pregnant women with a history of cesarean section. The protective effect of previous vaginal deliveries and the beneficial impact of epidural anesthesia suggest that appropriate labor management strategies could improve VBAC success rates. Moreover, the association between high BMI and increased cesarean risk underscores the need for preconceptional and prenatal weight management interventions. The key finding of this study is that the Polish prediction index of the VBAC (Ti) for full-term deliveries demonstrates moderate predictive effectiveness; however, its performance was lower than that initially reported in the original study (AUC 0.671, 95% CI: 0.671–0.724, p < 0.001 vs. AUC 0.71, 95% CI: 0.64–0.77). Results in the context of what is known The Polish prediction index of the VBAC (Ti) may theoretically be used at the time of a patient’s admission to the hospital for delivery. However, it does not provide support for decision-making regarding the mode of delivery earlier in pregnancy. Therefore, rather than serving as a standalone predictive tool, it may function as one component of a more comprehensive prediction index model for determining the final mode of delivery in women with one previous cesarean section who are eligible for VBAC 9 , as it contains predictors not included in other prediction models, as shown in Table 4. Table 4. Comparison of the Polish prediction indices of the VBAC (Ti) with other models published between 2015 and 2025. Study Predictors AUC (95% CI) Development/validation Dobrowolska-Redo 2019 Physical work, place of residence (>100 000 citizens), pregnancy weight gain, body weight at delivery, prepregnancy BMI, previous vaginal birth history, gestational age at delivery, threatened preterm delivery, prepregnancy diabetes mellitus, epidural anesthesia in labor, fetal weight 0.71 (0.64-0.77)/0.671 (0.671-0.724) Bhide et al. 2016 Ethnicity, BMI at delivery, induction of labor, prior cesarean delivery for failure to progress 0.72 (0.69–0.76)/- Ashwal et al. 2016 Maternal age, prior successful VBAC, vaginal delivery prior to the previous cesarean delivery, time interval from the previous cesarean delivery, recurring indication for prior cesarean delivery, labor induction, gestational age at delivery , fetal weight 0.689 (0.648–0.730)/no validation Xing et al. 2019 The previous primary indication of cesarean delivery, previous vaginal birth history , maternal age, pregnancy weight gain , labor induction, score of pelvic/ birth weight , Bishop's score 0.849 (0.78–0.89)/- Lin et al. 2019 Bishop's score, spontaneous labor during the current birth 0.953/- Li et al. 2019 Gestational age, history of vaginal delivery, fetal weight, prepregnancy BMI , spontaneous onset of labor, cervix Bishop's score, rupture of membranes 0.77 (0.73–0.81)/0.70 (0.60–0.79) Manzanares et al. 2020 Spontaneous onset of labor, fetal weight, BMI at delivery, previous cesarean delivery as an elective or for fetal distress reasons, interdelivery interval 0.69/- Bi et al. 2020 Maternal age, prepregnancy BMI, BMI at delivery , prior vaginal delivery , prior VBAC, recurrent indication for cesarean 0.743 (0.694–0.785)/- Lakra et al. 2020 Maternal age, gestational age , Bishop's score, BMI at delivery, indication for primary cesarean section, fetal weight 0.77 (0.68–0.85)/no validation Zhang et al. 2020 Maternal height, BMI at delivery, fundal height, cervix Bishop's score, maternal age at delivery, gestational age, history of vaginal delivery 0.889/0.906 Carlsson and Kallen et al. 2020 Maternal age, BMI at delivery , maternal height, previous vaginal birth , previous VBAC, the time elapsed since previous cesarean delivery, indication of previous cesarean delivery 0.66/0.67 Liao et al. 2020 Maternal age, previous vaginal delivery , interdelivery interval, presence of prior trial of labor after cesarean, dystocia as prior cesarean delivery indication, intertuberous diameter, BMI at delivery, gestational age at delivery, fetal weight , hypertensive disorders 0.777 (0.738–0.815)/no validation Misgan et al. 2020 Prior VBAC, prepregnancy BMI , fetal membrane status, the fetal station at admission 0.87 (0.81–0.93)/no validation Grobman et al. 2021 Maternal age, pregnancy weight , height, indication for previous cesarean delivery, obstetrical history (vaginal delivery) , chronic hypertension 0.76 (0.74–0.78)/0.75 (0.73–0.76) Mi et al. 2021 Gravidity of parity, prepregnancy BMI , cervix Bishop's score, a history of past vaginal delivery , interdelivery interval, fetal weight 0.815 (0.762–0.854)/0.730 (0.652–0.808) VBAC – vaginal birth after cesarean BMI – body mass index Common predictors with the Polish prediction indices of the VBAC (Ti) are bolded. As shown in Table 4, several prediction models have been developed to estimate the likelihood of successful VBAC, incorporating a variety of maternal, fetal, and labor-related factors. Commonly included predictors across studies are maternal age, body mass index (BMI), gestational age, fetal weight, Bishop’s score, and a history of prior vaginal delivery or successful VBAC. Notably, Bishop’s score and spontaneous onset of labor have emerged as strong indicators of VBAC success in multiple models. The predictive performance of these models varies, with reported area under the curve (AUC) values ranging from moderate (e.g., 0.66–0.71 in studies by Carlsson and Dobolska-Redo) to high (e.g., 0.849 in Xing et al., 0.87 in Misgan et al., and 0.953 in Lin et al.). However, only a few studies, including those by Zhang et al., Grobman et al., and Mi et al., provide external validation, which is essential for assessing the generalizability of these models. Interestingly, even models with relatively few predictors, such as Lin et al.’s model, which uses only Bishop’s score and spontaneous labor, demonstrated promising results. In contrast, more complex models with numerous variables do not necessarily offer better predictive power, especially in the absence of external validation. It is possible that combining models tailored to different stages of pregnancy—for example, early pregnancy characteristics versus intrapartum factors—could enhance predictive accuracy and provide more personalized guidance throughout the course of care. Overall, to assess the effectiveness of combining prediction models, it would be advisable to conduct further research evaluating the performance of integrated models in improving VBAC outcome prediction. Clinical implications Given the single-center nature of this study, it would be beneficial to validate the Index model in an external cohort from a different medical center that was not involved in the development or initial validation of the Index model. This would allow for a more comprehensive evaluation of the Index model's effectiveness across different clinical settings and institutional standards of care. The index model for preterm deliveries proved to be ineffective. One key factor influencing this outcome is the significantly different therapeutic approaches applied to preterm deliveries compared with full-term deliveries. In cases of live singleton preterm pregnancy, labor is not induced as a standard practice 15 . Instead, the onset of labor or the need for cesarean section often results from pregnancy complications that pose a threat to either the mother and/or fetus. When preterm delivery is imminent, medical interventions focus primarily on delaying labor for as long as safely possible to improve neonatal outcomes. The goal is to prevent preterm delivery rather than actively facilitating vaginal birth, as would be the case in full-term deliveries, and the obstetrician's decision to finish a pregnancy with labor is highly subjective owing to the lack of strict cutoff points for many of the indications for finishing a pregnancy with labor. These factors contribute to the higher rate of intrapartum cesarean section in this group and significantly complicate the prediction of delivery mode. Research implications Certain components of the Index model were identified as factors that negatively impact its predictive effectiveness, specifically, manual job and residence in an area with a population exceeding 100 000 people. Among women with these characteristics, the Index model’s accuracy decreased. The problematic nature of the manual job variable may stem from the lack of classification regarding the degree of physical strain involved, as well as the absence of data on the number of years spent in physically demanding jobs. This lack of detailed information resulted in a highly heterogeneous subgroup, making it difficult to assess its true impact on the risk of intrapartum cesarean section. Similarly, challenges in classifying places of residence may have contributed to the Index model’s decreased effectiveness. Ongoing urbanization in Poland and migration from Eastern Europe, which intensified during the study period, complicated accurate classification of a woman's residence. The place of residence was often recorded on the basis of the immediate predelivery period, which may not reflect a woman’s long-term living environment. These factors likely contributed to the misclassification of participants in the >100 000 population category. By excluding these two parameters (manual job and place of residence) from the index model, an improved version of the index model was obtained, demonstrating better predictive performance than the originally validated version (AUC 0.714, 95% CI: 0.663–0.766, p < 0.001). The refined index model achieved the following results: sensitivity: 70.8%; specificity: 63.4%; positive predictive value (PPV): 57.2%; negative predictive value (NPV): 75.8%; and overall accuracy: 66.4%. These results suggest that refining the index model by eliminating less reliable variables enhances its practical utility for predicting intrapartum cesarean section risk (Figure 3). Strengths and Limitations The ineffectiveness of the index model for preterm deliveries may also stem from the relatively small sample size of preterm deliveries used for validation. The limited dataset may have affected the index model’s predictive ability, further emphasizing the need for future research on larger cohorts to refine predictive tools for this specific group. The limitation of this study was the relatively low percentage of all pregnant women (5.8%) who were eligible for a trial of vaginal delivery after cesarean delivery. This is primarily due to the wide range of indications for cesarean section under current clinical guidelines 16 . Additionally, the legal framework in Poland, which regulates the civil and criminal liability of physicians, may also contribute to this limitation. The legal environment favors decisions toward performing intrapartum cesarean sections, particularly in cases where deviations from physiological labor occur. For example, temporary abnormalities in cardiotocography (CTG) recordings often lead to a decision for cesarean section, even though an expectant management approach—continuing vaginal delivery under close monitoring—could, in many cases, ultimately prove safe for both mothers and children. This legal pressure may influence clinical decision-making, reducing the proportion of women eligible for VBAC trials. Conclusions The Polish prediction index of the VBAC for full-term deliveries (Ti) demonstrated moderate predictive effectiveness in the Polish population. Although its performance was lower than that initially reported in the original study, we present an adjusted index model that demonstrates better predictive performance than the originally validated version. In contrast, the Polish prediction index of the VBAC for preterm deliveries (pTi) is not effective and requires further study. We confirmed several clinical predictors of VBAC success and identified factors associated with an increased risk of intrapartum cesarean section in women attempting VBAC. The index model may serve as a useful decision-support tool for both obstetricians and pregnant women when choosing the mode of delivery. We recommend replicating the study via data from other clinical centers and suggest the development of a more comprehensive prediction model that integrates additional factors influencing VBAC outcomes. Abbreviations Ti: Term index; pTi: pre-Term index; VBAC: Vaginal Birth After Cesarean; C-s: cesarean section; BMI: Body Mass Index; AUC: Area Under The Curve; ROC Curve: Receiver Operating Characteristic Curve; SD: Standard Deviation; OR: Odds Ratio; CI: Confidence interval, PPV: positive predictive value, NPV: negative predictive value Declarations Ethics approval and consent to participate The Local Ethics Committee of the Medical University of Warsaw approved the study (reference no. AKBE/300/2024; obtained on 18.11.2024). Written informed consent was not required because unidentifiable patient information used only. Consent for publication Not applicable. Availability of data and materials The data were anonymized and did not contain any patient information in order to maintain confidentiality. The datasets used and analyzed in this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research received no external funding. Authors’ contributions SP, ADR, JZS, and ERW developed the study concept. SP collected the data. SP and ERW designed the analyses, and SP, AU, JKB, and ERW performed the analyses. SP and AU wrote the first draft of the manuscript. All authors read and approved the final version of the manuscript for important intellectual content. Acknowledgements We would like to thank Mr. Piotr Lewandowski, who is the main person responsible for the statistical processing of the collected data. References WHO. WHO statement on cesarean section rates. WHO/RHR/15.02. 15 Feb 2015. https://www.who.int/publications/i/item/WHO-RHR-15.02 Betran AP, Ye J, Moller AB, Souza JP, Zhang J. Trends and projections of cesarean section rates: global and regional estimates. BMJ Glob Heal. 2021; 6(6):e005671. doi: 10.1136/bmjgh-2021-005671. Hamilton BE, Martin JA, Osterman MJK. 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Grobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O'Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Can a prediction model for vaginal birth after cesarean also predict the probability of morbidity related to a trial of labor? Am J Obstet Gynecol. 2009 Jan;200(1):56.e1-6. doi: 10.1016/j.ajog.2008.06.039. Epub 25 Sep 2008. Deng B, Li Y, Chen JY, Guo J, Tan J, Yang Y, Liu N. Prediction models of vaginal birth after cesarean delivery: A systematic review. Int J Nurs Stud. 2022 Nov;135:104359. doi: 10.1016/j.ijnurstu.2022.104359. Epub 7 Sep 2022. Landon MB, Leindecker S, Spong CY, Hauth JC, Bloom S, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, Peaceman AM, O'Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM, Gabbe SG. The MFMU Cesarean Registry: factors affecting the success of trial of labor after previous cesarean delivery. Am J Obstet Gynecol. 2005 Sep;193(3 Pt 2):1016-23. doi: 10.1016/j.ajog.2005.05.066. Grobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O'Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Development of a nomogram for prediction of vaginal birth after cesarean delivery. Obstet Gynecol. 2007 Apr;109(4):806-12. doi: 10.1097/01.AOG.0000259312.36053.02. Grobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Simhan HN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O'Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Does information available at admission for delivery improve prediction of vaginal birth after cesarean? Am J Perinatol. 2009 Nov;26(10):693-701. doi: 10.1055/s-0029-1239494. Epub 7 Oct 2009. Grobman WA, Sandoval G, Rice MM, Bailit JL, Chauhan SP, Costantine MM, Gyamfi-Bannerman C, Metz TD, Parry S, Rouse DJ, Saade GR, Simhan HN, Thorp JM Jr, Tita ATN, Longo M, Landon MB. Prediction of vaginal birth after cesarean delivery in term gestations: a calculator without race and ethnicity. Am J Obstet Gynecol. 2021 Dec;225(6):664.e1-664.e7. doi: 10.1016/j.ajog.2021.05.021. Epub 24 May 2021. Dobrowolska-Redo A. Assessment of risk factors for intrapartum cesarean section in women after cesarean section. Dissertation for the degree of doctor of medicine in the field of medicine. 2019. doi: 10.48745/ppm.0d4m-8z53. https://ppm.edu.pl/info/phd/WUMb14585d3c3c1478f8105fe113234e3ad/ Bomba-Opoń D, Drews K, Huras H, Laudanski P, Paszkowski T, Wielgos M, Fuchs T, Pomorski M, Zimmer M. Polish Society of Gynecologists and Obstetricians recommendations for labor induction. 2021 update. Ginekologia i Perinatologia Praktyczna 2021;6(2):86-99. https://journals.viamedica.pl/ginekologia_perinatologia_prakt/article/view/85182 Wielgos M, Bomba-Opoń D, Breborowicz GH, Czajkowski K, Debski R, Leszczynska-Gorzelak B, Oszukowski P, Radowicki S, Zimmer M. Recommendations of the Polish Society of Gynecologists and Obstetricians regarding cesarean sections. Ginekol Pol. 2018;89(11):644-657. doi: 10.5603/GP.a2018.0110. https://journals.viamedica.pl/ginekologia_polska/article/view/GP.a2018.0110/46969 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Apr, 2026 Reviewers agreed at journal 08 Apr, 2026 Reviews received at journal 08 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviews received at journal 09 Feb, 2026 Reviewers agreed at journal 23 Jan, 2026 Reviewers agreed at journal 23 Jan, 2026 Reviewers agreed at journal 10 Jan, 2026 Reviewers invited by journal 11 Dec, 2025 Editor invited by journal 11 Dec, 2025 Editor assigned by journal 10 Dec, 2025 Submission checks completed at journal 10 Dec, 2025 First submitted to journal 10 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":128554,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve with AUC for the risk index for intrapartum cesarean section in term deliveries (Ti).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8330044/v1/680412aebfd8201d7c66f753.png"},{"id":98440903,"identity":"c567f89c-ebef-4ec4-9b77-424675a50c2a","added_by":"auto","created_at":"2025-12-17 17:04:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153514,"visible":true,"origin":"","legend":"\u003cp\u003eGraph of the sensitivity and specificity of the Ti model.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8330044/v1/b851575d19a02e30a27b2d32.png"},{"id":98378391,"identity":"3af15a87-a9f8-416c-b5e8-adc60199ab49","added_by":"auto","created_at":"2025-12-17 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17:04:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19436,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8330044/v1/ad6142630e1e144ef4279c5d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trial of Vaginal Birth After Cesarean (VBAC): External validation of the Polish prediction indices of the VBAC","fulltext":[{"header":"Background","content":"\u003cp\u003eIn 1985, a consensus was established by the WHO stating that the percentage of births via cesarean section should be maintained at \u003csup\u003e10\u0026ndash;15%1\u003c/sup\u003e. According to recent WHO studies, the rates of cesarean section have been steadily increasing, reaching 21% of all births worldwide in 2021, on the basis of the latest available data\u003csup\u003e2\u003c/sup\u003e. It is anticipated that by 2030, cesarean deliveries will account for 29% of all births worldwide\u003csup\u003e1,2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAccording to a report by the National Health Service, a noticeable decrease in the number of births in Poland occurred between 2019 and 2022, with a simultaneous increase in the proportion of births by cesarean section, from 45% in 2019 to 48% in 2022. Moreover, in 2023, this percentage was 32.4% in the USA and 48% in Poland\u003csup\u003e3,4\u003c/sup\u003e. The consequence of this trend is an increase in the cost of childbirth, as well as an increase in the risk of short-term and long-term maternal and neonatal complications\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA direct consequence of the increasing rate of cesarean section is an increase in the proportion of pregnant women with a history of cesarean delivery. Women who have previously undergone a cesarean section, due to urgent or reversible indications, may be eligible for either a vaginal birth after cesarean (VBAC) or an elective repeat cesarean section.\u003c/p\u003e \u003cp\u003eBoth VBAC and repeat cesarean sections carry an elevated risk of perinatal complications\u003csup\u003e6\u003c/sup\u003e, with the risk of severe complications increasing with each subsequent cesarean section\u003csup\u003e7\u003c/sup\u003e. While successful VBAC is the least risky option, with a success rate of 60\u0026ndash;80%\u003csup\u003e8\u003c/sup\u003e, unplanned cesarean section during a VBAC trial significantly increases the complication rate compared with elective repeat cesarean section.\u003c/p\u003e \u003cp\u003eSince 1990, various prediction models and risk assessment calculators have been developed to evaluate the likelihood of a successful VBAC and to assist both physicians and patients in deciding whether to attempt it\u003csup\u003e9\u003c/sup\u003e. General factors associated with a greater probability of a successful VBAC, such as a history of vaginal delivery or low BMI, have been identified\u003csup\u003e10\u003c/sup\u003e. However, these factors alone do not provide precise estimates, nor do they allow for the development of specific prediction models that would enable patients to make fully informed decisions about their mode of delivery.\u003c/p\u003e \u003cp\u003eThe only VBAC success prediction model that has found clinical application is the Maternal\u003cb\u003e-\u003c/b\u003eFetal Medicine Units (MFMU) Network model. It predicts VBAC success on the basis of six variables known as early as the first prenatal visit\u003csup\u003e11\u003c/sup\u003e. Although this model has been validated in multiple studies across different populations, the findings have unfortunately been inconsistent, leading to divergent conclusions, which led to its subsequent editions\u003csup\u003e12,13\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrently, the literature lacks validated tools for predicting VBAC success in the Polish population.\u003c/p\u003e \u003cp\u003eIn 2019, in her doctoral dissertation\u003csup\u003e14\u003c/sup\u003e, an intrapartum cesarean section hazard ratio index model was developed for pregnant women who were qualified for VBAC, called the Polish Prediction Indices of VBAC (pTi/Ti), on the basis of variables from a cohort of 412 pregnant women who had previously undergone a single cesarean section. The study was conducted in the delivery room at the Second Department of Obstetrics and Gynecology Warsaw Medical University, covering the period from January 1, 2013, to December 31, 2015.\u003c/p\u003e \u003cp\u003eThe author used multivariate logistic regression analysis, which resulted in formulas estimating the probability of requiring an intrapartum cesarean section. The Index models provided separate risk assessments for two groups:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWomen who delivered preterm (pTi index \u0026ndash; pre-Term index).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWomen delivering at term (Ti index \u0026ndash; Term index).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eSome of the variables included in the Index models are definitively known at the time of delivery, which may improve the accuracy of the VBAC success estimation.\u003c/p\u003e \u003cp\u003eThe study revealed that the risk of requiring an intrapartum cesarean section was more than twice as high among women who delivered preterm (OR\u0026thinsp;=\u0026thinsp;2.06; P\u0026thinsp;\u0026lt;\u0026thinsp;.005). The index model\u0026rsquo;s predictive performance was evaluated via an ROC curve, which yielded an AUC of 0.94 (95% CI: 0.90\u0026ndash;0.99) for preterm deliveries (pTi) and 0.71 (95% CI: 0.64\u0026ndash;0.77) for term deliveries (Ti).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and data acquisition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was a retrospective analysis of collected data from a cohort of pregnant women with a history of one previous cesarean section who were eligible for a vaginal birth after a cesarean delivery (VBAC). These women gave birth at the II Department of Obstetrics and Gynecology of the Medical University of Warsaw (Księżna Anna Mazowiecka Clinical Hospital in Warsaw), a tertiary referral center, between January 1, 2021, and December 31, 2023.\u003c/p\u003e\n\u003cp\u003eThe demographic and obstetric data of the patients were obtained from the clinic's archives. During the creation and development of the database, all patient identification data were anonymized to ensure confidentiality. Demographic and obstetric data were incorporated into the validated index models to predict the probability of intrapartum cesarean section risk after one previous cesarean section (in both study groups). The performance of the index models in the current study cohort was then compared with their performance in the original study cohort.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelection criteria\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria for the study were a history of one previous cesarean section in the lower uterine segment, singleton pregnancy, no indications for elective cesarean section (qualified for a VBAC trial), and live birth. The exclusion criterion for the study was lack of consent for the VBAC trial.\u003c/p\u003e\n\u003cp\u003eOut of 7983 deliveries during the study period, after applying the selection criteria, 462 pregnant women (5.8%) were included in the study. Given the significantly different risks associated with delivery, the study participants were divided into two groups: preterm delivery and term delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary objective of this study was to verify the factors influencing VBAC success as established by \u003cstrong\u003eDobrowolska-Redo\u003c/strong\u003e and to externally validate her index models, assessing their utility in predicting the risk of intrapartum cesarean section after a previous abdominal delivery in the Polish population.\u003c/p\u003e\n\u003cp\u003eA secondary objective is to evaluate additional variables within the study cohort, analyze their correlation with the risk of intrapartum cesarean section, and refine the index models to improve their predictive accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe patient data included: age, type of work, marital status, population size of place of residence, smoking before and during pregnancy, weight before pregnancy and weight just before delivery, BMI before pregnancy and BMI just before delivery, height, previous pregnancies, previous miscarriages, previous natural deliveries, indications for previous cesarean section, occurrence of fetal macrosomia in previous pregnancies, week of pregnancy in which delivery occurred, indications and method of labor induction if it occurred, method of delivery, indications for cesarean section or operative delivery if it occurred, length of each stage of labor, use of epidural anesthesia during delivery, anesthesia used during cesarean section if it occurred; whether the pregnancy was complicated by: risk of preterm birth, cholestasis, urinary tract infection, anemia, pre-pregnancy hypertension, pregnancy-induced hypertension, pre-pregnancy diabetes, gestational diabetes; occurrence of postpartum anemia.\u003c/p\u003e\n\u003cp\u003eThe data collected on newborns included: estimated weight on ultrasound scan up to 7 days before delivery, sex, birth weight, birth length, and Apgar score at 1 and 5 minutes after delivery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was conducted via the Statistica 13 software package. A p value \u0026lt; 0.05 was considered statistically significant. A comparison of the study groups was then performed.\u003c/p\u003e\n\u003cp\u003eDifferences between women who had successful VBAC and those whose pregnancies ended with cesarean section were analyzed. Qualitative data were compared via the chi-square (χ²) test, and quantitative data were analyzed via the Mann‒Whitney test. Then, the Polish prediction indices of the VBAC were evaluated. The pTi/Ti models were assessed in the new cohort via receiver operating characteristic (ROC) curves. The index model AUCs were compared with the AUCs obtained in the original study. The optimal ROC cutoff point was determined via the Youden method.\u003c/p\u003e\n\u003cp\u003eAt this cutoff point, the sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) were calculated and compared with those from the original studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the local institutional ethical committee (reference no. AKBE/300/2024; obtained on 18.11.2024). Written informed consent was not required because unidentifiable patient information used only.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePreliminary results\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 462 pregnant women included in the study, 271 (58.7%) had a successful vaginal birth, whereas 191 (41.3%) required an intrapartum cesarean section.\u003c/p\u003e\n\u003cp\u003eIn the preterm delivery group, the prediction index (pTi) did not demonstrate effectiveness, yielding completely divergent results. As a result, further analyses in this subgroup were discontinued, and the study focused exclusively on the Index for term deliveries (Ti) group\u003cstrong\u003e.\u003c/strong\u003e The following results were obtained for only the study group (393 pregnant women).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFactors associated with the success or failure of VBAC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistically significant differences were observed between the group that had a successful VBAC and the group that required an intrapartum cesarean section. High BMI values, both before pregnancy (23.43 kg/m\u003csup\u003e2\u003c/sup\u003e vs. 24.54 kg/m\u003csup\u003e2\u003c/sup\u003e; p = 0.006) and before delivery (27.99 kg/m\u003csup\u003e2\u003c/sup\u003e vs. 29.36 kg/m\u003csup\u003e2\u003c/sup\u003e; p = 0.007), were associated with an increased risk of intrapartum cesarean section. In contrast, the number of previous pregnancies played a protective role, as women with a greater number of pregnancies had a significantly lower risk of requiring a cesarean section (1.5 vs. 1; p = 0.000).\u003c/p\u003e\n\u003cp\u003eA strong predictor of successful VBAC was a history of vaginal delivery (31.5% vs. 11.2%; p = 0.000); women who had previously given birth vaginally had a much lower risk of requiring a cesarean section during labor, as only 19.8% of these women required a cesarean section. A history of fetal macrosomia in previous pregnancies was also a predictor of successful VBAC (15.5% vs. 8.7%; p = 0.047), as only 28% of women with a history of fetal macrosomia in previous pregnancies required a cesarean section. These predictors significantly reduced the likelihood of intrapartum cesarean section.\u003c/p\u003e\n\u003cp\u003eConversely, gestational diabetes was linked to a significantly greater risk of intrapartum cesarean section, affecting 34.2% of the women in the cesarean group compared with 23.7% in the successful VBAC group (p = 0.023). Interestingly, the use of epidural anesthesia was associated with a lower risk of intrapartum cesarean section, as only 26.6% of women who received epidural anesthesia required a cesarean section (p = 0.000).\u003c/p\u003e\n\u003cp\u003eThe results are summarized in Table 1.\u003c/p\u003e\n\u003cp\u003eTable 1. Characteristics of the study cohort of pregnant women with term deliveries.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"107%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eVBAC\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e(232)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eC-s\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e(161)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eParameter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eMedian (Q1-Q3)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eor n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003eMedian (Q1-Q3)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eor n (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003cp\u003e(30.0-36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e33.0\u003c/p\u003e\n \u003cp\u003e(30.0-36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eGestational weight gain (kg)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e12.7\u003c/p\u003e\n \u003cp\u003e(9.7-15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e12.0\u003c/p\u003e\n \u003cp\u003e(8.5-15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003ePrepregnancy body weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003cp\u003e(56.3-73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003cp\u003e(56.0-76.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.278\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eBody weight before delivery (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e78.0\u003c/p\u003e\n \u003cp\u003e(69.0-87.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e78.0\u003c/p\u003e\n \u003cp\u003e(68.5-87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003ePrepregnancy BMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e23.43\u003c/p\u003e\n \u003cp\u003e(20.60-26.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e24.54\u003c/p\u003e\n \u003cp\u003e(21.30-27.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eBMI before delivery (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e27.99\u003c/p\u003e\n \u003cp\u003e(25.20-30.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e29.36\u003c/p\u003e\n \u003cp\u003e(26.40-32.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eNumber of previous pregnancies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003cp\u003e(1.0-2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e(0.5-1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eDelivery week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003cp\u003e(38.0-40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003cp\u003e(38.0-40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.858\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eEstimated fetal weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e3405.0\u003c/p\u003e\n \u003cp\u003e(3187.0-3623.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e3508.0\u003c/p\u003e\n \u003cp\u003e(3249.5-3766.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eBirth weight (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e3420.0\u003c/p\u003e\n \u003cp\u003e(3175.0-3665.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e3450.0\u003c/p\u003e\n \u003cp\u003e(3170.0-3730.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eVaginal delivery in the past\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003cp\u003e(31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e(11.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eFetal macrosomia in previous pregnancies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003cp\u003e(15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003cp\u003e(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.047\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eRisk of preterm delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e(5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e(3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.500\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eCholestasis in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e(1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e(1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.702\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eUrinary tract infection in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e(4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e(4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eAnemia in pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003cp\u003e(17.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003cp\u003e(18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.931\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003ePrepregnancy hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e(4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003cp\u003e(6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.375\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003ePregnancy-induced hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e(3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003ePrepregnancy diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003cp\u003e(4.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e.561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eGestational diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003cp\u003e(23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003cp\u003e(34.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003eEpidural anesthesia used\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003cp\u003e(67.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003cp\u003e(35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eVBAC \u0026ndash; vaginal birth after cesarean\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eC-s \u0026ndash; cesarean section\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBMI \u0026ndash; body mass index\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBolded p values are statistically significant.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe effectiveness of the Polish Ti index\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApplying the Polish prediction index of VBACs (Ti) to the studied cohort of full-term deliveries resulted in an AUC value of 0.671 (95% CI: 0.671\u0026ndash;0.724). This finding is comparable to the results obtained in the original cohort studied by Dobolska-Redo, where the AUC was 0.71 (95% CI: 0.64\u0026ndash;0.77). These findings confirm the predictive ability of the constructed index model (Figure 1).\u003c/p\u003e\n\u003cp\u003eA statistically significant difference was observed in the median Polish prediction index of VBAC (Ti) values between women who had a successful VBAC and those who required a repeat intrapartum cesarean section. The median Ti model for successful vaginal deliveries was 0.308, whereas for women requiring a repeat cesarean section, it was 0.403 (Mann‒Whitney test, p \u0026lt; 0.001; Table 2). These findings are consistent with those reported by Dobolska-Redo, further validating the index model\u0026apos;s effectiveness.\u003c/p\u003e\n\u003cp\u003eTable 2. Median values of Ti according to method of delivery.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"92%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 501px;\"\u003e\n \u003cp\u003eMann‒Whitney Test (p=0,000000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eMethod of delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eLower quartile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eUpper quartile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eVBAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.3224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.3076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.0484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.7481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.2107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.4250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.1449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eC-s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0.4186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.4027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.0718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e0.9143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.3038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.4940\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e0.1649\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eVBAC \u0026ndash; vaginal birth after cesarean\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eC-s \u0026ndash; cesarean section\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor the proposed cutoff point of 0.34 on the ROC curve, the Ti model demonstrated the following predictive parameters:\u003c/p\u003e\n\u003cp\u003eSensitivity: 69.6%; specificity: 63.4%; positive predictive value (PPV): 54.2%; negative predictive value (NPV): 73.4%; overall accuracy: 63.4%\u003c/p\u003e\n\u003cp\u003eThe Youden index, which was used to optimize sensitivity and specificity, reached its highest value at 0.29 (Figure 2, Table 3). These results confirm the potential utility of the Polish prediction index of the VBAC (Ti) in predicting intrapartum cesarean section risk among women attempting VBAC.\u003c/p\u003e\n\u003cp\u003eTable 3. Predictors of performing an intrapartum cesarean section for term deliveries according to the value of the Ti model assessed by sensitivity, specificity, PPV and NPV, original results (left) vs. validation results (right).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"677\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 38px;\"\u003e\n \u003cp\u003eTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eSensivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eSpecificity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 154px;\"\u003e\n \u003cp\u003ePPV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eNPV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eOriginal results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eValidation results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eOriginal results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eValidation results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eOriginal results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003eValidation results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003eOriginal results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eValidation results\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e41.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e32.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e41.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e77.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e92.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e92.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e21.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e45.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e87.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e80.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e75.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e58.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e45.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e50.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e80.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e74.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e51.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e82.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e70.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e52.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e54.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e73.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e19.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e23.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e90.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e89.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e51.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e62.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e96.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e95.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e57.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e68.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e68.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e61.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e42.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e78.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e67.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e99.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e66.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e67.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e59.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e67.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e59.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e67.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e59.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;PPV \u0026ndash; positive predictive value\u003c/p\u003e\n\u003cp\u003eNPV \u0026ndash; negative predictive value\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003ePrincipal Findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was a single-center retrospective analysis aimed at assessing the clinical utility of intrapartum cesarean section hazard ratio index models, called the Polish Prediction Indices of VBAC (pTi/Ti), for predicting intrapartum cesarean section after one previous cesarean delivery in the Polish population. Additionally, we sought to identify factors influencing the risk of intrapartum cesarean section.\u003c/p\u003e\n\u003cp\u003eOur findings highlight key factors influencing the success of VBAC and reinforce the importance of individualized risk assessment in pregnant women with a history of cesarean section. The protective effect of previous vaginal deliveries and the beneficial impact of epidural anesthesia suggest that appropriate labor management strategies could improve VBAC success rates. Moreover, the association between high BMI and increased cesarean risk underscores the need for preconceptional and prenatal weight management interventions.\u003c/p\u003e\n\u003cp\u003eThe key finding of this study is that the Polish prediction index of the VBAC (Ti) for full-term deliveries demonstrates moderate predictive effectiveness; however, its performance was lower than that initially reported in the original study (AUC 0.671, 95% CI: 0.671\u0026ndash;0.724, p \u0026lt; 0.001 vs. AUC 0.71, 95% CI: 0.64\u0026ndash;0.77).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults in the context of what is known\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Polish prediction index of the VBAC (Ti) may theoretically be used at the time of a patient\u0026rsquo;s admission to the hospital for delivery. However, it does not provide support for decision-making regarding the mode of delivery earlier in pregnancy. Therefore, rather than serving as a standalone predictive tool, it may function as one component of a more comprehensive prediction index model for determining the final mode of delivery in women with one previous cesarean section who are eligible for VBAC\u003csup\u003e9\u003c/sup\u003e, as it contains predictors not included in other prediction models, as shown in Table 4.\u003c/p\u003e\n\u003cp\u003eTable 4. Comparison of the Polish prediction indices of the VBAC (Ti) with other models published between 2015 and 2025.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAUC (95% CI) Development/validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDobrowolska-Redo\u003c/p\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical work, place of residence (\u0026gt;100\u0026nbsp;000 citizens), pregnancy weight gain, body weight at delivery, prepregnancy BMI, previous vaginal birth history, gestational age at delivery, threatened preterm delivery, prepregnancy diabetes mellitus, epidural anesthesia in labor, fetal weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.71 (0.64-0.77)/0.671 (0.671-0.724)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBhide et al.\u003c/p\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEthnicity, BMI at delivery, induction of labor, prior cesarean delivery for failure to progress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.72 (0.69\u0026ndash;0.76)/-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAshwal et al.\u003c/p\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age, prior successful VBAC, vaginal delivery prior to the previous cesarean\u003c/p\u003e\n \u003cp\u003edelivery, time interval from the previous cesarean delivery, recurring indication for prior cesarean delivery, labor induction, \u003cstrong\u003egestational age at delivery\u003c/strong\u003e, \u003cstrong\u003efetal weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.689 (0.648\u0026ndash;0.730)/no validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eXing et al.\u003c/p\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eThe previous primary indication of cesarean\u003c/p\u003e\n \u003cp\u003edelivery, \u003cstrong\u003eprevious vaginal birth history\u003c/strong\u003e, maternal age, \u003cstrong\u003epregnancy weight gain\u003c/strong\u003e, labor induction, score of pelvic/\u003cstrong\u003ebirth weight\u003c/strong\u003e, Bishop\u0026apos;s score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.849 (0.78\u0026ndash;0.89)/-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLin et al.\u003c/p\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBishop\u0026apos;s score, spontaneous labor during the current birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.953/-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLi et al.\u003c/p\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGestational age, history of vaginal delivery, fetal weight, prepregnancy BMI\u003c/strong\u003e, spontaneous onset of labor, cervix Bishop\u0026apos;s score, rupture of membranes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.77 (0.73\u0026ndash;0.81)/0.70\u003c/p\u003e\n \u003cp\u003e(0.60\u0026ndash;0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eManzanares et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpontaneous onset of labor, \u003cstrong\u003efetal weight,\u0026nbsp;\u003c/strong\u003eBMI at delivery, previous cesarean delivery as an elective or for fetal distress reasons, interdelivery interval\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.69/-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBi et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age,\u003cstrong\u003e\u0026nbsp;prepregnancy BMI,\u0026nbsp;\u003c/strong\u003eBMI at delivery\u003cstrong\u003e, prior vaginal delivery\u003c/strong\u003e, prior VBAC, recurrent indication for cesarean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.743 (0.694\u0026ndash;0.785)/-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLakra et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age, \u003cstrong\u003egestational age\u003c/strong\u003e, Bishop\u0026apos;s score, BMI at delivery, indication for primary cesarean section, \u003cstrong\u003efetal weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.77 (0.68\u0026ndash;0.85)/no validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eZhang et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal height, BMI at delivery, fundal height,\u003c/p\u003e\n \u003cp\u003ecervix Bishop\u0026apos;s score, maternal age at delivery,\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003egestational age, history of vaginal delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.889/0.906\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCarlsson and Kallen et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age, BMI at delivery\u003cstrong\u003e,\u003c/strong\u003e maternal height, \u003cstrong\u003eprevious vaginal birth\u003c/strong\u003e, previous VBAC, the time elapsed since previous cesarean delivery, indication of previous cesarean delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.66/0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLiao et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age, \u003cstrong\u003eprevious vaginal delivery\u003c/strong\u003e,\u003c/p\u003e\n \u003cp\u003einterdelivery interval, presence of prior trial of\u003c/p\u003e\n \u003cp\u003elabor after cesarean, dystocia as prior cesarean\u003c/p\u003e\n \u003cp\u003edelivery indication, intertuberous diameter, BMI at delivery, \u003cstrong\u003egestational age at delivery, fetal weight\u003c/strong\u003e, hypertensive disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.777 (0.738\u0026ndash;0.815)/no validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMisgan et al.\u003c/p\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrior VBAC, \u003cstrong\u003eprepregnancy BMI\u003c/strong\u003e, fetal membrane status, the fetal station at admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.87 (0.81\u0026ndash;0.93)/no validation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGrobman et al.\u003c/p\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age, \u003cstrong\u003epregnancy weight\u003c/strong\u003e, height, indication for previous cesarean delivery, \u003cstrong\u003eobstetrical history (vaginal delivery)\u003c/strong\u003e, chronic hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.76 (0.74\u0026ndash;0.78)/0.75\u003c/p\u003e\n \u003cp\u003e(0.73\u0026ndash;0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMi et al.\u003c/p\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGravidity of parity, \u003cstrong\u003eprepregnancy BMI\u003c/strong\u003e, cervix\u003c/p\u003e\n \u003cp\u003eBishop\u0026apos;s score, \u003cstrong\u003ea history of past vaginal delivery\u003c/strong\u003e, interdelivery interval, \u003cstrong\u003efetal weight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003cp\u003e(0.762\u0026ndash;0.854)/0.730\u003c/p\u003e\n \u003cp\u003e(0.652\u0026ndash;0.808)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eVBAC \u0026ndash; vaginal birth after cesarean\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBMI \u0026ndash; body mass index\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCommon predictors with the Polish prediction indices of the VBAC (Ti) are bolded.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table 4, several prediction models have been developed to estimate the likelihood of successful VBAC, incorporating a variety of maternal, fetal, and labor-related factors. Commonly included predictors across studies are maternal age, body mass index (BMI), gestational age, fetal weight, Bishop\u0026rsquo;s score, and a history of prior vaginal delivery or successful VBAC. Notably, Bishop\u0026rsquo;s score and spontaneous onset of labor have emerged as strong indicators of VBAC success in multiple models. The predictive performance of these models varies, with reported area under the curve (AUC) values ranging from moderate (e.g., 0.66\u0026ndash;0.71 in studies by Carlsson and Dobolska-Redo) to high (e.g., 0.849 in Xing et al., 0.87 in Misgan et al., and 0.953 in Lin et al.). However, only a few studies, including those by Zhang et al., Grobman et al., and Mi et al., provide external validation, which is essential for assessing the generalizability of these models. Interestingly, even models with relatively few predictors, such as Lin et al.\u0026rsquo;s model, which uses only Bishop\u0026rsquo;s score and spontaneous labor, demonstrated promising results. In contrast, more complex models with numerous variables do not necessarily offer better predictive power, especially in the absence of external validation. It is possible that combining models tailored to different stages of pregnancy\u0026mdash;for example, early pregnancy characteristics versus intrapartum factors\u0026mdash;could enhance predictive accuracy and provide more personalized guidance throughout the course of care. Overall, to assess the effectiveness of combining prediction models, it would be advisable to conduct further research evaluating the performance of integrated models in improving VBAC outcome prediction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the single-center nature of this study, it would be beneficial to validate the Index model in an external cohort from a different medical center that was not involved in the development or initial validation of the Index model. This would allow for a more comprehensive evaluation of the Index model\u0026apos;s effectiveness across different clinical settings and institutional standards of care.\u003c/p\u003e\n\u003cp\u003eThe index model for preterm deliveries proved to be ineffective. One key factor influencing this outcome is the significantly different therapeutic approaches applied to preterm deliveries compared with full-term deliveries. In cases of live singleton preterm pregnancy, labor is not induced as a standard practice\u003csup\u003e15\u003c/sup\u003e. Instead, the onset of labor or the need for cesarean section often results from pregnancy complications that pose a threat to either the mother and/or fetus.\u003c/p\u003e\n\u003cp\u003eWhen preterm delivery is imminent, medical interventions focus primarily on delaying labor for as long as safely possible to improve neonatal outcomes. The goal is to prevent preterm delivery rather than actively facilitating vaginal birth, as would be the case in full-term deliveries, and the obstetrician\u0026apos;s decision to finish a pregnancy with labor is highly subjective owing to the lack of strict cutoff points for many of the indications for finishing a pregnancy with labor. These factors contribute to the higher rate of intrapartum cesarean section in this group and significantly complicate the prediction of delivery mode.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch implications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCertain components of the Index model were identified as factors that negatively impact its predictive effectiveness, specifically, manual job and residence in an area with a population exceeding 100 000 people. Among women with these characteristics, the Index model\u0026rsquo;s accuracy decreased.\u003c/p\u003e\n\u003cp\u003eThe problematic nature of the manual job variable may stem from the lack of classification regarding the degree of physical strain involved, as well as the absence of data on the number of years spent in physically demanding jobs. This lack of detailed information resulted in a highly heterogeneous subgroup, making it difficult to assess its true impact on the risk of intrapartum cesarean section.\u003c/p\u003e\n\u003cp\u003eSimilarly, challenges in classifying places of residence may have contributed to the Index model\u0026rsquo;s decreased effectiveness. Ongoing urbanization in Poland and migration from Eastern Europe, which intensified during the study period, complicated accurate classification of a woman\u0026apos;s residence. The place of residence was often recorded on the basis of the immediate predelivery period, which may not reflect a woman\u0026rsquo;s long-term living environment. These factors likely contributed to the misclassification of participants in the \u0026gt;100 000 population category.\u003c/p\u003e\n\u003cp\u003eBy excluding these two parameters (manual job and place of residence) from the index model, an improved version of the index model was obtained, demonstrating better predictive performance than the originally validated version (AUC 0.714, 95% CI: 0.663\u0026ndash;0.766, p \u0026lt; 0.001). The refined index model achieved the following results: sensitivity: 70.8%; specificity: 63.4%; positive predictive value (PPV): 57.2%; negative predictive value (NPV): 75.8%; and overall accuracy: 66.4%.\u003c/p\u003e\n\u003cp\u003eThese results suggest that refining the index model by eliminating less reliable variables enhances its practical utility for predicting intrapartum cesarean section risk (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ineffectiveness of the index model for preterm deliveries may also stem from the relatively small sample size of preterm deliveries used for validation. The limited dataset may have affected the index model\u0026rsquo;s predictive ability, further emphasizing the need for future research on larger cohorts to refine predictive tools for this specific group.\u003c/p\u003e\n\u003cp\u003eThe limitation of this study was the relatively low percentage of all pregnant women (5.8%) who were eligible for a trial of vaginal delivery after cesarean delivery. This is primarily due to the wide range of indications for cesarean section under current clinical guidelines\u003csup\u003e16\u003c/sup\u003e. Additionally, the legal framework in Poland, which regulates the civil and criminal liability of physicians, may also contribute to this limitation. The legal environment favors decisions toward performing intrapartum cesarean sections, particularly in cases where deviations from physiological labor occur. For example, temporary abnormalities in cardiotocography (CTG) recordings often lead to a decision for cesarean section, even though an expectant management approach\u0026mdash;continuing vaginal delivery under close monitoring\u0026mdash;could, in many cases, ultimately prove safe for both mothers and children. This legal pressure may influence clinical decision-making, reducing the proportion of women eligible for VBAC trials.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe Polish prediction index of the VBAC for full-term deliveries (Ti) demonstrated moderate predictive effectiveness in the Polish population. Although its performance was lower than that initially reported in the original study, we present an adjusted index model that demonstrates better predictive performance than the originally validated version. In contrast, the Polish prediction index of the VBAC for preterm deliveries (pTi) is not effective and requires further study. We confirmed several clinical predictors of VBAC success and identified factors associated with an increased risk of intrapartum cesarean section in women attempting VBAC. The index model may serve as a useful decision-support tool for both obstetricians and pregnant women when choosing the mode of delivery. We recommend replicating the study via data from other clinical centers and suggest the development of a more comprehensive prediction model that integrates additional factors influencing VBAC outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTi: Term index; pTi: pre-Term index; VBAC: Vaginal Birth After Cesarean; C-s: cesarean section; BMI: Body Mass Index; AUC: Area Under The Curve; ROC Curve: Receiver Operating Characteristic Curve; SD: Standard Deviation; OR: Odds Ratio; CI: Confidence interval, PPV: positive predictive value, NPV: negative predictive value\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Local Ethics Committee of the Medical University of Warsaw approved the study (reference no. AKBE/300/2024; obtained on 18.11.2024).\u0026nbsp;Written informed consent was not required because unidentifiable patient information used only.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were anonymized and did not contain any patient information in order to maintain confidentiality. The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSP, ADR, JZS, and ERW developed the study concept. SP collected the data.\u003c/p\u003e\n\u003cp\u003eSP and ERW designed the analyses, and SP, AU, JKB, and ERW performed the analyses.\u003c/p\u003e\n\u003cp\u003eSP and AU wrote the first draft of the manuscript. All authors read and approved\u003c/p\u003e\n\u003cp\u003ethe final version of the manuscript for important intellectual content.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Mr. Piotr Lewandowski, who is the main person responsible for the statistical processing of the collected data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWHO. WHO statement on cesarean section rates. WHO/RHR/15.02. 15 Feb 2015. https://www.who.int/publications/i/item/WHO-RHR-15.02\u003c/li\u003e\n \u003cli\u003eBetran AP, Ye J, Moller AB, Souza JP, Zhang J. Trends and projections of cesarean section rates: global and regional estimates. BMJ Glob Heal. 2021; 6(6):e005671. doi: 10.1136/bmjgh-2021-005671.\u003c/li\u003e\n \u003cli\u003eHamilton BE, Martin JA, Osterman MJK. Births: provisional data for 2023. Vital Statistics Rapid Release; no 35. April 2024. doi: 10.15620/cdc/151797.\u003c/li\u003e\n \u003cli\u003ePolish National Health Fund (NFZ). Birth and perinatal care. 11 Mar 2025. https://ezdrowie.gov.pl/portal/home/badania-i-dane/zdrowe-dane/monitorowanie/porody-opieka-okoloporodowa\u003c/li\u003e\n \u003cli\u003eAntoine C, Young BK. Cesarean section one hundred years 1920-2020: the Good, the Bad and the Ugly. J Perinat Med. 2020 Sep 4;49(1):5-16. doi: 10.1515/jpm-2020-0305.\u003c/li\u003e\n \u003cli\u003eCrowther CA, Dodd JM, Hiller JE, Haslam RR, Robinson JS. Planned vaginal birth or elective repeat cesarean: patient preference restricted cohort with nested randomized trial. PLoS Med. 2012;9(3):e1001192. doi: 10.1371/journal.pmed.1001192. Epub 13 Mar 2012.\u003c/li\u003e\n \u003cli\u003eNisenblat V, Barak S, Griness OB, Degani S, Ohel G, Gonen R. Maternal complications associated with multiple cesarean deliveries. Obstet Gynecol. 2006 Jul;108(1):21-6. doi: 10.1097/01.AOG.0000222380.11069.11.\u003c/li\u003e\n \u003cli\u003eGrobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O\u0026apos;Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Can a prediction model for vaginal birth after cesarean also predict the probability of morbidity related to a trial of labor? Am J Obstet Gynecol. 2009 Jan;200(1):56.e1-6. doi: 10.1016/j.ajog.2008.06.039. Epub 25 Sep 2008.\u003c/li\u003e\n \u003cli\u003eDeng B, Li Y, Chen JY, Guo J, Tan J, Yang Y, Liu N. Prediction models of vaginal birth after cesarean delivery: A systematic review. Int J Nurs Stud. 2022 Nov;135:104359. doi: 10.1016/j.ijnurstu.2022.104359. Epub 7 Sep 2022.\u003c/li\u003e\n \u003cli\u003eLandon MB, Leindecker S, Spong CY, Hauth JC, Bloom S, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, Peaceman AM, O\u0026apos;Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM, Gabbe SG. The MFMU Cesarean Registry: factors affecting the success of trial of labor after previous cesarean delivery. Am J Obstet Gynecol. 2005 Sep;193(3 Pt 2):1016-23. doi: 10.1016/j.ajog.2005.05.066.\u003c/li\u003e\n \u003cli\u003eGrobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Caritis SN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O\u0026apos;Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Development of a nomogram for prediction of vaginal birth after cesarean delivery. Obstet Gynecol. 2007 Apr;109(4):806-12. doi: 10.1097/01.AOG.0000259312.36053.02.\u003c/li\u003e\n \u003cli\u003eGrobman WA, Lai Y, Landon MB, Spong CY, Leveno KJ, Rouse DJ, Varner MW, Moawad AH, Simhan HN, Harper M, Wapner RJ, Sorokin Y, Miodovnik M, Carpenter M, O\u0026apos;Sullivan MJ, Sibai BM, Langer O, Thorp JM, Ramin SM, Mercer BM. Does information available at admission for delivery improve prediction of vaginal birth after cesarean? Am J Perinatol. 2009 Nov;26(10):693-701. doi: 10.1055/s-0029-1239494. Epub 7 Oct 2009.\u003c/li\u003e\n \u003cli\u003eGrobman WA, Sandoval G, Rice MM, Bailit JL, Chauhan SP, Costantine MM, Gyamfi-Bannerman C, Metz TD, Parry S, Rouse DJ, Saade GR, Simhan HN, Thorp JM Jr, Tita ATN, Longo M, Landon MB. Prediction of vaginal birth after cesarean delivery in term gestations: a calculator without race and ethnicity. Am J Obstet Gynecol. 2021 Dec;225(6):664.e1-664.e7. doi: 10.1016/j.ajog.2021.05.021. Epub 24 May 2021.\u003c/li\u003e\n \u003cli\u003eDobrowolska-Redo A. Assessment of risk factors for intrapartum cesarean section in women after cesarean section. Dissertation for the degree of doctor of medicine in the field of medicine. 2019. doi: 10.48745/ppm.0d4m-8z53. https://ppm.edu.pl/info/phd/WUMb14585d3c3c1478f8105fe113234e3ad/\u003c/li\u003e\n \u003cli\u003eBomba-Opoń D, Drews K, Huras H, Laudanski P, Paszkowski T, Wielgos M, Fuchs T, Pomorski M, Zimmer M. Polish Society of Gynecologists and Obstetricians recommendations for labor induction. 2021 update. Ginekologia i Perinatologia Praktyczna 2021;6(2):86-99. https://journals.viamedica.pl/ginekologia_perinatologia_prakt/article/view/85182\u003c/li\u003e\n \u003cli\u003eWielgos M, Bomba-Opoń D, Breborowicz GH, Czajkowski K, Debski R, Leszczynska-Gorzelak B, Oszukowski P, Radowicki S, Zimmer M. Recommendations of the Polish Society of Gynecologists and Obstetricians regarding cesarean sections. Ginekol Pol. 2018;89(11):644-657. doi: 10.5603/GP.a2018.0110. https://journals.viamedica.pl/ginekologia_polska/article/view/GP.a2018.0110/46969\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vaginal birth after cesarean section, prediction index model, calculator, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-8330044/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8330044/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVaginal birth after cesarean section (VBAC) is a safe option for both mothers and children. Currently available prediction tools have not been validated in the Polish population. Dobrowolska-Redo proposed a model for predicting VBAC success, and the aim of this study was to evaluate its clinical utility.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective analysis of data collected from 462 pregnant women with a history of one previous cesarean section, all qualified for a VBAC attempt. Deliveries occurred between January 1, 2021, and December 31, 2023, at the II Department of Obstetrics and Gynecology, Medical University of Warsaw. Inclusion criteria were: previous low transverse cesarean section, singleton pregnancy, no indication for elective cesarean delivery, and live birth. Ethical approval was granted by the local committee (reference no. AKBE/300/2024). The data were anonymized before analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the cohort of 462 women, 271 (58.7%) had successful VBAC, whereas 191 (41.3%) underwent intrapartum cesarean section. The prediction model for preterm births (pTi) showed no clinical utility. The median Ti score differed significantly between the VBAC group and the cesarean group. Removing two parameters (manual labor and place of residence) improved model performance. Higher BMI increased the likelihood of cesarean delivery, both before pregnancy (23.43 vs. 24.54 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) and at delivery (27.99 vs. 29.36 kg/m\u0026sup2;; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007). Prior vaginal birth was a strong predictor of successful VBAC (31.5% vs. 11.2%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000), as was a history of fetal macrosomia (15.5% vs. 8.7%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047). Gestational diabetes was more common in women who ultimately required cesarean delivery (34.2% vs. 23.7%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). Epidural anesthesia use correlated with a lower cesarean rate (26.6%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this single-center cohort, the Polish index model for full-term VBAC (Ti) prediction showed moderate accuracy. A refined version demonstrated improved performance compared with the original. Several predictors of successful VBAC were confirmed, including prior vaginal delivery and history of macrosomia, while high BMI and gestational diabetes increased the risk of intrapartum cesarean section.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eRetrospectively registered.\u003c/p\u003e","manuscriptTitle":"Trial of Vaginal Birth After Cesarean (VBAC): External validation of the Polish prediction indices of the VBAC","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 07:22:33","doi":"10.21203/rs.3.rs-8330044/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-09T10:23:27+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"135893825220895924520196846610835541170","date":"2026-04-08T17:24:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-08T05:38:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"236673344651243148600196988404849923447","date":"2026-04-07T10:18:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-09T17:42:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6997518689886638547818120646795575065","date":"2026-01-23T16:44:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185383565144807149653631220080478360360","date":"2026-01-23T16:25:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"141975141348308357927088312578673425560","date":"2026-01-10T10:10:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-11T14:40:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-11T07:14:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-11T03:31:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-11T03:31:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-12-10T17:48:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b98f13ed-cff0-4d13-9285-b8bafa6ba79f","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T12:55:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 07:22:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8330044","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8330044","identity":"rs-8330044","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}