scholarly journals Prediction of vaginal birth after cesarean delivery in Southeast China: a retrospective cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Hua-Le Zhang ◽  
Liang-Hui Zheng ◽  
Li-Chun Cheng ◽  
Zhao-Dong Liu ◽  
Lu Yu ◽  
...  
Keyword(s):  
Cesarean Section ◽  
Pregnant Women ◽  
Success Rate ◽  
Gestational Age ◽  
Prediction Models ◽  
Curve Analysis ◽  
Vaginal Birth ◽  
Lasso Regression ◽  
Vaginal Birth After Cesarean ◽  
Decision Curve Analysis

Abstract Background We aimed to develop and validate a nomogram for effective prediction of vaginal birth after cesarean (VBAC) and guide future clinical application. Methods We retrospectively analyzed data from hospitalized pregnant women who underwent trial of labor after cesarean (TOLAC), at the Fujian Provincial Maternity and Children’s Hospital, between October 2015 and October 2017. Briefly, we included singleton pregnant women, at a gestational age above 37 weeks who underwent a primary cesarean section, in the study. We then extracted their sociodemographic data and clinical characteristics, and randomly divided the samples into training and validation sets. We employed the least absolute shrinkage and selection operator (LASSO) regression to select variables and construct VBAC success rate in the training set. Thereafter, we validated the nomogram using the concordance index (C-index), decision curve analysis (DCA), and calibration curves. Finally, we adopted the Grobman’s model to perform comparisons with published VBAC prediction models. Results Among the 708 pregnant women included according to inclusion criteria, 586 (82.77%) patients were successfully for VBAC. Multivariate logistic regression models revealed that maternal height (OR, 1.11; 95% CI, 1.04 to 1.19), maternal BMI at delivery (OR, 0.89; 95% CI, 0.79 to 1.00), fundal height (OR, 0.71; 95% CI, 0.58 to 0.88), cervix Bishop score (OR, 3.27; 95% CI, 2.49 to 4.45), maternal age at delivery (OR, 0.90; 95% CI, 0.82 to 0.98), gestational age (OR, 0.33; 95% CI, 0.17 to 0.62) and history of vaginal delivery (OR, 2.92; 95% CI, 1.42 to 6.48) were independently associated with successful VBAC. The constructed predictive model showed better discrimination than that from the Grobman’s model in the validation series (c-index 0.906 VS 0.694, respectively). On the other hand, decision curve analysis revealed that the new model had better clinical net benefits than the Grobman’s model. Conclusions VBAC will aid in reducing the rate of cesarean sections in China. In clinical practice, the TOLAC prediction model will help improve VBAC’s success rate, owing to its contribution to reducing secondary cesarean section.

scholarly journals Prediction of vaginal birth after cesarean delivery in southeast China: A retrospective cohort study

2020 ◽  
Author(s):  
Hua-Le Zhang ◽  
Liang-Hui Zheng ◽  
Li-Chun Cheng ◽  
Zhao-Dong Liu ◽  
Lu Yu ◽  
...  
Keyword(s):  
Cesarean Section ◽  
Pregnant Women ◽  
Success Rate ◽  
Gestational Age ◽  
Prediction Models ◽  
Curve Analysis ◽  
Vaginal Birth ◽  
Lasso Regression ◽  
Vaginal Birth After Cesarean ◽  
Decision Curve Analysis

Abstract Background We aimed to develop and validate a nomogram for effective prediction of vaginal birth after cesarean (VBAC) and guide future clinical application. Methods We retrospectively analyzed data from hospitalized pregnant women who underwent trial of labor after cesarean (TOLAC), at the Fujian Provincial Maternity and Children's Hospital, between October 2015 and October 2017. Briefly, we included singleton pregnant women, at a gestational age above 37 weeks who underwent a primary cesarean section, in the study. We then extracted their sociodemographic data and clinical characteristics, and randomly divided the samples into training and validation sets. We employed the least absolute shrinkage and selection operator (LASSO) regression to select variables and construct VBAC success rate in the training set. Thereafter, we validated the nomogram using the concordance index (C-index), decision curve analysis (DCA), and calibration curves. Finally, we adopted the Grobman’s model to perform comparisons with published VBAC prediction models. Results Among the 708 pregnant women included according to inclusion criteria, 586 (82.77%) patients were successfully for VBAC. Multivariate logistic regression models revealed that maternal height (OR, 1.11; 95% CI, 1.04 to 1.19), maternal BMI at delivery (OR, 0.89; 95% CI, 0.79 to 1.00), fundal height (OR, 0.71; 95% CI, 0.58 to 0.88), cervix Bishop score (OR, 3.27; 95% CI, 2.49 to 4.45), maternal age at delivery (OR, 0.90; 95% CI, 0.82 to 0.98), gestational age (OR, 0.33; 95% CI, 0.17 to 0.62) and history of vaginal delivery (OR, 2.92; 95% CI, 1.42 to 6.48) were independently associated with successful VBAC. The constructed predictive model showed better discrimination than that from the Grobman’s model in the validation series (c-index 0.906 VS 0.694, respectively). On the other hand, decision curve analysis revealed that the new model had better clinical net benefits than the Grobman’s model. Conclusions VBAC will aid in reducing the rate of cesarean sections in China. In clinical practice, the TOLAC prediction model will help improve VBAC’s success rate, owing to its contribution to reducing secondary cesarean section.

scholarly journals Prediction of vaginal birth after cesarean delivery in southeast China: A retrospective cohort study

2020 ◽  
Author(s):  
Hua-Le Zhang ◽  
Liang-Hui Zheng ◽  
Li-Chun Cheng ◽  
Zhao-Dong Liu ◽  
Lu Yu ◽  
...  
Keyword(s):  
Cesarean Section ◽  
Pregnant Women ◽  
Success Rate ◽  
Gestational Age ◽  
Curve Analysis ◽  
Inclusion Criteria ◽  
Vaginal Birth After Cesarean ◽  
Training Set ◽  
Decision Curve Analysis ◽  
Validation Set

Abstract Objective To develop and validate a nomogram to better predict the vaginal birth after cesarean (VBAC) on the premise of clinical guide application. Methods We retrospectively identified hospitalised pregnant women who trial of labor after cesarean (TOLAC) between October 2015 and October 2017 using data from the Fujian Provincial Maternity and Children's Hospital. The inclusion criteria were as follows: Singleton pregnant women whose gestational age was above 37 weeks and underwent a primary cesarean section. Sociodemographic data and Clinical Characteristics were extracted. The samples were randomly divided into a training set and a validation set. Least absolute shrinkage and selection operator (LASSO) regression were used to select variables and construct of VBAC success rate in training set. The validation of the nomogram was performed using the concordance index (C-index), decision curve analysis (DCA), and calibration curves in the validation set. For comparison with published VBAC prediction models, the Grobman’s model was used. Results Among the 708 pregnant women included according to inclusion criteria, 586 (82.77%) patients were successfully for VBAC. In multivariate logistic regression models, Maternal height (OR, 1.11; 95% CI, 1.04 to 1.19), maternal BMI at delivery (OR, 0.89; 95% CI, 0.79 to 1.00), fundal height (OR, 0.71; 95% CI, 0.58 to 0.88), cervix Bishop score (OR, 3.27; 95% CI, 2.49 to 4.45), maternal age at delivery (OR, 0.90; 95% CI, 0.82 to 0.98), gestational age (OR, 0.33; 95% CI, 0.17 to 0.62) and history of vaginal delivery (OR, 2.92; 95% CI, 1.42 to 6.48) were independently associated with successful VBAC. The predictive model was constructed showed better discrimination in the validation series than Grobman’s model (c-index 0.906 VS 0.694, respectively). Decision curve analysis revealed that the new model resulted in a better clinical net benefit than the Grobman’s model. Conclusions The promotion of VBAC is helpful to reduce the cesarean section rate in China. On the basis of following the clinical practice guidelines, the TOLAC prediction model helps to improve the success rate of VBAC and has a potential contribution to the reduction of secondary cesarean section.

scholarly journals Frequency of Successful Vaginal Birth after Previous One Cesarean Section in Low Risk Pregnant Women

2016 ◽  
Vol 22 (1) ◽  
pp. 60
Author(s):  
Saadia Rasheed ◽  
Sehar Shahbaz ◽  
Shazia Hammad
Keyword(s):  
Cesarean Section ◽  
Pregnant Women ◽  
Success Rate ◽  
Placental Abruption ◽  
Cost Effective ◽  
Vaginal Birth ◽  
Low Risk ◽  
Vaginal Birth After Cesarean ◽  
Live Fetus ◽  
Prior Cesarean Section

AbstractAims and Objectives:determine the frequency of successful vaginal birth after cesarean section VBAC in low risk pregnant women.Study Design: It was a descriptive study.Duration:From 2010 to 2014.Material and Method:A total of 130 cases who were at term (37)+ weeks of gestation, between 20 40 years of age with a single prior cesarean section, presenting in their next pregnancy (G2) with a single, live fetus in cephalic presentation and those who given the consent of trial of VBAC were included in the study while high risk cases e.g. hypertensive disorders, gestational diabetes mellitus, placental abruption etc were excluded from this review. All these cases were collected from Maternity and Children's hospital Hail, Kingdom of Saudia Arabia.Results:In our study, 63.85% of the cases were between 20 30 years of age while 36.15% (n = 47) were between 31 40 years, mean sd was calculated as 27.24 3.52 years, mean gestational age was 38.43 2.43 weeks while successful vaginal birth after cesarean section was recorded in 78.46% (n = 102) while 21.54% (n = 28) had failed trial of VBAC.Conclusion:Higher success rate of vaginal birth after one cesarean section in low risk pregnant women is recorded while no significant adverse outcome in these cases is found. However, in our setup it is safe and cost-effective as well.Key Words:Cesarean delivery, low risk, VBAC, success rate, safe, cost effective.

Vaginal birth after cesarean (VBAC): fear it or dare it? An evaluation of potential risk factors

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anastasia Lazarou ◽  
Magdalena Oestergaard ◽  
Johanna Netzl ◽  
Jan-Peter Siedentopf ◽  
Wolfgang Henrich
Keyword(s):  
Body Mass Index ◽  
Birth Weight ◽  
Cesarean Section ◽  
Pregnant Women ◽  
Body Mass ◽  
Vaginal Birth ◽  
Vacuum Extraction ◽  
Vaginal Birth After Cesarean ◽  
Vaginal Deliveries ◽  
Spontaneous Delivery

Abstract Objectives The consultation of women aspiring a vaginal birth after caesarean may be improved by integrating the individual evaluation of factors that predict their chance of success. Retrospective analysis of correlating factors for all trials of labor after caesarean that were conducted at the Department of Obstetrics of Charité-Universitätsmedizin Berlin, Campus Virchow Clinic from 2014 to October 2017. Methods Of 2,151 pregnant women with previous caesarean, 408 (19%) attempted a vaginal birth after cesarean. A total of 348 women could be included in the evaluation of factors, 60 pregnant women were excluded because they had obstetric factors (for example preterm birth, intrauterine fetal death) that required a different management. Results Spontaneous delivery occurred in 180 (51.7%) women and 64 (18.4%) had a vacuum extraction. 104 (29.9%) of the women had a repeated caesarean delivery. The three groups showed significant differences in body mass index, the number of prior vaginal deliveries and the child’s birth weight at cesarean section. The indication for the previous cesarean section also represents a significant influencing factor. Other factors such as maternal age, gestational age, sex, birth weight and the head circumference of the child at trial of labor after caesarean showed no significant influence. Conclusions The clear majority (70.1%) of trials of labor after caesarean resulted in vaginal delivery. High body mass index, no previous spontaneous delivery, and fetal distress as a cesarean indication correlated negatively with a successful vaginal birth after cesarean. These factors should be used for the consultation of pregnant women.

Factors predicting Success of Vaginal Birth after Cesarean Section

2016 ◽  
Vol 8 (3) ◽  
pp. 198-201
Author(s):  
Uma Singh ◽  
Manju L Verma ◽  
S Nisha ◽  
Pushpa L Sankhwar ◽  
Sabuhi Qureshi
Keyword(s):  
Cesarean Section ◽  
Success Rate ◽  
Cesarean Delivery ◽  
Fetal Distress ◽  
Vaginal Birth ◽  
Vaginal Birth After Cesarean ◽  
Trial Of Labor ◽  
Emergency Cesarean ◽  
Predicting Success ◽  
History Of

ABSTRACT Aim The aim of this article is to study the various factors that can predict the success of vaginal birth after cesarean (VBAC) section. Materials and methods A retrospective cohort study of deliveries was conducted from 1 January 2014 to 31 December 2014 by the Department of Obstetrics and Gynecology in our hospital. Patients with previous low transverse cesarean section who had undergone a trial of labor were identified. Maternal inpatient and prenatal records were reviewed in all eligible subjects. During labor, uterine activity and fetal heart rate were monitored. When indicated, oxytocin or prostaglandin E2 was used for induction of labor according to Bishop score. Emergency cesarean delivery was considered in cases with the appearance of scar tenderness, fetal distress, nonprogress of labor, and deep transverse arrest. Results A total of 200 women were eligible for VBAC, but after written informed consent, 131 (65.5%) subjects were given trial of labor at term after one prior cesarean delivery among 3,604 deliveries while 69 (34.5%) subjects opted for elective repeat cesarean section. The overall VBAC success rate was 63.3% (76 of 120) in our study. History of spontaneous labor (p = 0.042) and history of previous vaginal delivery (p = 0.038) were found to be significantly associated with increased chance of success of VBAC, and lesser interdelivery interval was not found to be associated with decreased success rate (p = 0.096). Neither indication of previous cesarean nor birth weight of newborn (>3 kg) was found to be related to the success of VBAC. Conclusion Vaginal birth after cesarean section is a safe practice as long as it is offered with a proper selection of candidates with factors having a high success rate. Physicians need to be aware of factors having a good outcome before counseling mothers so that failure rates decrease and successful VBAC is increased. How to cite this article Verma ML, Nisha S, Singh U, Sankhwar PL, Qureshi S. Factors predicting Success of Vaginal Birth after Cesarean Section. J South Asian Feder Obst Gynae 2016;8(3):198-201.

scholarly journals Scoring system development and validation for prediction choledocholithiasis before open cholecystectomy

2015 ◽  
Vol 143 (11-12) ◽  
pp. 681-687 ◽  
Author(s):  
Tomislav Pejovic ◽  
Miroslav Stojadinovic
Keyword(s):  
Bile Duct ◽  
Clinical Utility ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Open Cholecystectomy ◽  
Univariate Analysis ◽  
Curve Analysis ◽  
Decision Curve Analysis ◽  
Scoring Model ◽  
Validation Set

Introduction. Accurate precholecystectomy detection of concurrent asymptomatic common bile duct stones (CBDS) is key in the clinical decision-making process. The standard preoperative methods used to diagnose these patients are often not accurate enough. Objective. The aim of the study was to develop a scoring model that would predict CBDS before open cholecystectomy. Methods. We retrospectively collected preoperative (demographic, biochemical, ultrasonographic) and intraoperative (intraoperative cholangiography) data for 313 patients at the department of General Surgery at Gornji Milanovac from 2004 to 2007. The patients were divided into a derivation (213) and a validation set (100). Univariate and multivariate regression analysis was used to determine independent predictors of CBDS. These predictors were used to develop scoring model. Various measures for the assessment of risk prediction models were determined, such as predictive ability, accuracy, the area under the receiver operating characteristic curve (AUC), calibration and clinical utility using decision curve analysis. Results. In a univariate analysis, seven risk factors displayed significant correlation with CBDS. Total bilirubin, alkaline phosphatase and bile duct dilation were identified as independent predictors of choledocholithiasis. The resultant total possible score in the derivation set ranged from 7.6 to 27.9. Scoring model shows good discriminatory ability in the derivation and validation set (AUC 94.3 and 89.9%, respectively), excellent accuracy (95.5%), satisfactory calibration in the derivation set, similar Brier scores and clinical utility in decision curve analysis. Conclusion. Developed scoring model might successfully estimate the presence of choledocholithiasis in patients planned for elective open cholecystectomy.

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