Prediction of mode of delivery in term pregnancies: development of scoring system

Kotha, Swathi; Kushtagi, Pralhad; Radhakrishnan, Krishnapriya

doi:10.18203/2320-1770.ijrcog20150697

Cited by 2 publications

(5 citation statements)

References 22 publications

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“…This is in agreement with a previous study which found that heavier fetal weight was associated with the increased risk of c-section. 14,30 Another previous study also supports our finding, suggesting that a total of 60.7% of pregnancies with a fetal weight more than 3500 were delivered by c-section, compared to 39.3% for a fetus weighing < 3500 g. 28 Although our study used the clinical birthweight rather than the estimated fetal weight, previous studies have found that there was no significant difference between estimated fetal weight and actual birth weight in normal weight population. 31 Significant difference of fetal weight usually found in small for gestational age fetus, with differences up to 200 g. 32 Thus, a clinically-determined estimated fetal weight of ⩾ 3500 g, can still be a predictive factor for an increased risk of c-section.…”

Section: Discussionsupporting

confidence: 87%

“…This is because the pelvic of multiparous women with previous vaginal delivery was considered to be more flexible and easier to undergo vaginal delivery in the following pregnancies. 15,23,28 Furthermore, obstetrical complications are also wellestablished major risk factors of c-section procedure. In this study, we included preeclampsia/eclampsia, gestational diabetes mellitus, IUGR, placenta previa, and placental abruption, since those are the most common pregnancy problems in Indonesia.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…A previous study found that the incidence of c-section in non-cephalic presentation was 93.3% (p < 0.001) compared to head presentation, the incidence of which is 37.3%. 28 Nevertheless, studies have suggested that non-cephalic presentation was best diagnosed at 36 weeks of gestational age. 33 Therefore, pregnant women who uses our scoring tool with diagnosed fetal presentation before 36 weeks of gestation, is recommended to repeat the examination in the subsequent weeks of pregnancy.…”

Section: Discussionmentioning

confidence: 99%

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Maternal and fetal characteristics to predict c-section delivery: A scoring system for pregnant women

Irwinda

Hiksas

Lokeswara

et al. 2021

Womens Health (Lond Engl)

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Introduction: Cesarean section is one of the most common obstetrical interventions that has been performed at an increasing rate globally, due to both medical and non-medical reasons. This study aims to develop a prediction tool for pregnant women potentially needing c-section, such that necessary preparations from the mothers, families, and health providers can be made. Methods: A total of 603 pregnant women were recruited in the first phase of c-section prediction tool development. The association between the maternal and fetal factors on the risk of c-section were analyzed, followed by a stepwise multivariate regression analysis. In the next phase, 61 pregnant women were enrolled for external validation. Discrimination was assessed using area under the curve. The calibration plot was then made and assessed using the Hosmer–Lemeshow test. Results: There were 251 (41.6%) cases of vaginal delivery and 352 (58.4%) of c-section assessed. Multivariate analysis showed that gestational age < 37 wg (OR: 1.66, 95% CI: 1.10–2.51), pre-pregnancy body mass index (underweight) (OR: 0.40, 95% CI: 0.22–0.76), no history of vaginal delivery (OR: 2.66, 95% CI: 1.76–4.02), history of uterine surgery (OR: 8.34, 95% CI: 4.54–15.30), obstetrical complications (OR: 5.61, 95% CI: 3.53–8.90), birthweight ⩾ 3500 g (OR: 4.28, 95% CI: 2.16–8.47), and non-cephalic presentation (OR: 2.74, 95% CI: 1.53–4.89) were independently associated with c-section delivery. Those parameters were included in a 7-item scoring tool, with consecutive predictive scores of 1,–1,2,3,3,2,2,1. The area under the curve result was 0.813 (95% CI: 0.779–0.847), indicating a good predictive ability. The external validation showed AUC: 0.806, 95% CI: 0.694–0.917, Hosmer–Lemeshow test p = 0.666 and calibration plot coefficient of r = 0.939. Conclusion: A total of 7 maternal-fetal factors were found to be strongly associated with c-section delivery, including gestational age < 37, maternal underweight body mass index, previous uterine surgery, obstetrical complications, birthweight ⩾ 3500, history of vaginal delivery, and non-cephalic presentation. Using these factors, a prediction tool was developed and validated with good quality.

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Section: Discussionsupporting

confidence: 87%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Maternal and fetal characteristics to predict c-section delivery: A scoring system for pregnant women

Irwinda

Hiksas

Lokeswara

et al. 2021

Womens Health (Lond Engl)

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“…The cut-off score predicted 21 vaginal deliveries with the sensitivity of 80%, the speci city of 65%, the positive predictive value of 70%, and negative predictive value of 76%, respectively, but a score above 21 did not always mean cesarean Sect. (16).…”

Section: Discussionmentioning

confidence: 99%

Predicting and Relation between Bio-psychosocial Factors and Type of Childbirth using Decision Tree Method

Hajimirzaie

Tehranian

Mousavi

et al. 2020

Preprint

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Background Growing the worldwide and Iranian cesarean section rate and rising morbidity and mortality thereafter for the mother and infant has been an important health issue. Predictive models can identify individuals with a higher probability of cesarean section and make better decisions. In this study, we investigated the bio-psychosocial factors associated with type of delivery. We designed a predictive model using the decision tree C4.5 algorithm. Methods In this longitudinal study 170 pregnant women were sampled in the third trimester of pregnancy. At the baseline phase blood samples were taken from mothers to measure estrogen hormone. Birth information was recorded at the follow-up time at 30–42 days postpartum. Modeling was performed using MATLAB software and C4.5 decision tree algorithm using input variables and the target variable. Results Previous type of childbirth, maternal body mass index at childbirth, maternal age, and serum estrogen were the most significant factors in predicting the childbirth type, respectively and decision tree model with 89.6%accuracy in the training stage and 83.3% in the test stage predicted the result. Conclusion The decision tree model designed with high accuracy and sensitivity can predict the type of childbirth. By recognizing the contributing factors and model rules, health practitioners and policymakers can take preventive action.

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Prediction of mode of delivery in term pregnancies: development of scoring system

Cited by 2 publications

References 22 publications

Maternal and fetal characteristics to predict c-section delivery: A scoring system for pregnant women

Maternal and fetal characteristics to predict c-section delivery: A scoring system for pregnant women

Predicting and Relation between Bio-psychosocial Factors and Type of Childbirth using Decision Tree Method

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