A model for predicting unscheduled caesarean section in nulliparae

České info

Analýza prediktorů neplánovaného císařského řezu u nullipar

Cíl práce: Analýza prediktorů neplánovaného císařského řezu u nullipar.

Typ studie: Prospektivní kohortová studie.

Název a sídlo pracoviště: Ústav pro péči o matku a dítě, Praha.

Metodika: Soubor tvořily nulipary rodící mezi 37. a 42. týdnem s jednočetnou a nízkorizikovou graviditou, s plodem v poloze podélné hlavičkou a bez primární indikace pro císařský řez. Byly analyzovány vybrané prenatální a intranatální faktory ve vztahu k akutnímu císařskému řezu v indikaci zástavy progrese porodu a/nebo hypoxie plodu. Pomocí logistické regresní analýzy a metody klasifikačního stromu bylo testováno pět predikčních modelů.

Výsledky: V souboru 3728 nulipar byl císařský řez proveden u 908 (24,4 %) žen. Všechny modely logistické regrese byly srovnatelné (ROC 0,837–0,0881) a jako nejvýznamnější rizikové faktory byly identifikovány zadní postavení (OPP) plodu, věk matky a použití epidurální analgezie. Spontánní nástup porodu, podání oxytocinu a vyšší tělesná výška rodičky snižují pravděpodobnost akutního císařského řezu. Schopnost modelů předpovědět vaginální porod byla 95,7–96,3 % a 58,5–61,8 % pro predikci císařského řezu. Metoda klasifikačního stromu (ROC 0,860–0,861) identifikovala podobné rizikové faktory, jako je zadní postavení plodu, užití peridurální analgezie a absence spontánního nástupu porodu. Predikční schopnosti byly podobné s hodnotami 94,5–96,4 % pro vaginální porod a 64,6–59,0% pro císařský řez.

Závěr: Zadní postavení plodu je nejvýznamnějším prediktorem neúspěšného vaginálního porodu.

Klíčová slova:

zadní postavení – peridurální analgezie – prediktivní modely – vaginální porod – císařský řez

Authors: P. Krepelka ^1,2; I. Urbánková ¹; L. Krofta ^1,2; J. Hanacek ^1,2; J. Feyereisl ^1,2
Authors‘ workplace: Institute for the Care of Mother and Child, Prague, head J. Feyereisl, MD, Ph. D., assoc. prof. ¹; Department of Obstetrics and Gynaecology, Third Faculty of Medicine, Charles University, Prague, head L. Rob, MD, Ph. D., prof., Data availability statement: DOI: 10. 6084/m9. figshare. 6983246. ²
Published in: Ceska Gynekol 2020; 85(6): 375-384
Category:

Overview

Objective: The objective of the study is to analyze the predictors of unplanned cesarean section in nulliparae.

Design: Prospective cohort study.

Setting: Institute for the Care of Mother and Child in Prague.

Methods: This study consisted of nulliparae giving birth between the 37th and 42nd weeks of singleton low-risk pregnancy, with the fetus in vertex position and without primary indication for CS. Selected prenatal and intranatal factors were analyzed in relation to acute CS due to a failure to progress in labor and/or fetal distress. Using logistic regression analysis (LR1-3) and the classification tree method (chi-square automatic interaction detector 1–2), five prediction models were tested.

Results: Of 3,728 nulliparae, 908 (24.4%) had an acute CS. All logistic regression models were comparable (receiver operating characteristic (ROC) 0.837–0.0881) and identified the occiput posterior position (OPP) of the fetus, maternal age, and epidural analgesia as the most influential risk factors. Spontaneous onset of labor, oxytocin administration, and maternal body height decreased are likely indicated for acute CS. The ability to predict a vaginal delivery was 95.7–96.3% and CS was 58.5–61.8%. The classification tree method (ROC 0.860–0.861) identified similar risk factors such as the OPP, peridural analgesia, and spontaneous onset of labor. The prediction abilities were similar at 94.5–96.4% for vaginal delivery and 64.6–59.0% for CS.

Conclusion: OPP of the fetus was the strongest risk factor for the unsuccessful trial of vaginal labor.

Keywords:

occiput posterior position – peridural analgesia – prediction model – vaginal delivery

INTRODUCTION

Cesarean section (CS) is the most frequent mode of operative delivery. Its proportion is continuously increasing because of specific selection pressure. In 2016, it accounted to 26.3% of all deliveries [37]. The proportion of acute CS due to a failure to progress with/or to fetal hypoxia has been increasing [28]. Particularly, acute CS during the second stage of labor is subject to higher risks of maternal and neonatal morbidity [13]. Clinical predictors of an unsuccessful vaginal delivery are excess weight before and during pregnancy [4, 5], gestational diabetes mellitus (GDM) [6], and increased maternal age [7, 20, 21, 25, 40]. The maternal body height and fetal birth weight affect the course of vaginal delivery; however, they are inadequate predictors of acute CS [15]. Another specific issue represents that the occiput posterior position (OPP) also increases the risk of operative delivery [12]. Increasing the ratio of scheduled CS might decrease specific maternal morbidity. Pre- or early perinatal identification of the predictors of acute CS (unsuccessful vaginal delivery) could make choosing between elective CS and attempted vaginal delivery easier and thus limit acute CS-related complications [27]. In our clinical settings, we often have to perform the unscheduled CS in the late first or second stage, both of which are related with difficult fetal head extraction and more extensive damage of the lower uterine segment. Therefore, we performed this study to create a prediction model for unscheduled CS due to a failure to progress in labor and/or signs of fetal hypoxia in low risk nulliparae.

MATERIALS AND METHODS

This prospective cohort study was conducted in 2011–2015 at the Institute for the Care of Mother and Child. All Caucasian nulliparae with an uncomplicated singleton pregnancy who started giving birth or whose labor was induced at ≥37th week of pregnancy were prospectively monitored. Women with a primary indication for CS or with other than vertex position were not included. The study design was approved by the Institutional Ethical committee, and all participants signed the informed consent.

Induction and delivery management

For delivery induction, dinoprostone was administered vaginally as recommended by the Czech Gynecological and Obstetrical Society [2]. Deliveries were managed by midwives under obstetrician’s supervision according to rules of active labor management [29]. To alleviate excessive birth pain, either nalbuphine (10 mg every 3 h, i.v.) or peridural analgesia (PDA; 0.5% bupivacaine+sufentanil, every 2 h) were administered. PDA was given at the cervix dilatation >3 cm (so-called delayed-walking PDA). After 30 min of lying, the paras were advised to actively move around the room. In the second stage of labor, after the fetal head descent to the +3 level, the women were encouraged to actively push at contractions. During crowning, manual perineal support and control of fetal head progression were provided. Mediolateral episiotomy was performed where necessary, yet no clear rules were defined. Acute CS was performed in the case of failure to progress and/or fetal hypoxia. Failure to progress was defined as an arrest in the cervical opening over the 4-h course, with oxytocin augmentation given for at least 2 h. Fetal hypoxia diagnosis was based on the presence of severe recurrent variable or late decelerations or 40-min silent record on external cardiotocography [31].

Ultrasound examination during labor

Vaginal examination was performed in the active stage of labor every 2 h. After amniotic fluid discharge and with the fetal head at the pelvic level +1, transabdominal ultrasonography was performed to determine the fetal position (anterior vs. posterior). The OPP referred to either the left or right position, where the occiput was dorsally positioned regarding the mother (>3 and <9 clock face).

Demographic and obstetric data

From the hospital database, basic demographic data (age, height, weight, and body mass index (BMI) before pregnancy and at delivery and their difference), information on the course of pregnancy and labor (labor induction, GDM, analgesia, etc.), and the postnatal fetal weight were recorded.

Statistical evaluation

The goal was to identify demographic and obstetric factors affecting the completion of labor by CS. Two different statistical methods were employed: logistic regression (LS) and chi-square automatic interaction detector (CHAID). Statistical analyses were performed in SPSS Statistics 19 software (SPSS Inc., Chicago, Illinois, USA). The distribution of numerical variables was tested using the Shapiro-Wilk test. The normally distributed variables were tested by Student’s t-test and other variables by Mann-Whitney’s test. Categorical variables were analyzed using the Pearson’s chi-square test. The results were evaluated at 5% significance level (p ≤ 0.05). The Cochran-Mantel-Haenszel test was used for calculating the expected risk of the CS odds ratio.

Likelihood ratio

Variables with a significant difference were evaluated using likelihood ratio (LR) with the forward elimination (likelihood ratio) method. The receiver operating characteristic (ROC) curve and independent variables increasing the CS odds ratio were identified. Gradually, three models (LR1–3) were tested. For LR2–3 models, the numerical variables (maternal age, fetal weight, etc.) were divided into two categories using the optimal binning method.

CHAID

To confirm the variables identified using LR, the classification tree analysis was performed. It included all variables without any transformation or categorization. The analysis identified the most relevant variables increasing the likelihood of an acute CS.

RESULTS

The study included 3,728 women, of whom 908 (24.4%) gave birth by CS (Tables 1, 2). Apart from fetal birth weight, other numerical variables did not show normal distributions.

**Table 1 Numerical demographical and obstetrical characteristics**

**Table 2 Categorical obstetrical characteristics and univariate analysis of their effect on acute CS**

The parameters of all models were comparable. The LR2 model achieved somewhat better values and was simpler. The LR3 model appeared to be more suitable; however, it only includes variables known before beginning labor. The LR1 model (Table 3, Figure 1) comprises the original numerical and categorical variables (age, height, weight, and BMI before pregnancy/delivery, BMI difference, fetal birth weight, GDM, spontaneous onset of labor, oxytocin, PDA, and OPP). The forward LR process eliminated GDM, all BMI parameters, and weight before pregnancy. The absolute prediction accuracy was 87.7%, with 96.3% (specificity) for vaginal delivery, and 59.8% (sensitivity) for CS. The most powerful predictor was the OPP. The LR2 model (Table 4, Figure 1) comprises categorized numerical variables and all categorical variables (age, height, weight, and BMI before pregnancy/delivery, BMI difference, fetal birth weight, GDM, spontaneous onset of labor, oxytocin, PDA, and OPP). Based on the forward LR method, GDM, weight before pregnancy and before delivery, BMI before pregnancy, and BMI difference parameters were eliminated. The absolute prediction accuracy was 87.8%, with 95.7% (specificity) for vaginal delivery, and 61.8% (sensitivity) for CS. The most powerful predictor was the OPP. The LR3 model (Table 4, Figure 1), from which the spontaneous onset of the labor and oxytocin parameters were eliminated, can be an alternative to LR2. Based on the forward LR method, GDM, weight before pregnancy/delivery, BMI before pregnancy, and BMI difference were eliminated. This model is more suitable for deciding on the method of delivery management prior to its start. The absolute accuracy of the model prediction was 87.2%, with 95.9% (specificity) for vaginal delivery and 58.5% (sensitivity) for CS.

**Figure 1 ROC curves of models LR 1, LR 2, LR 3, CHAID 1, CHAID 2**

Classification Tree Method

CHAID1 included all available variables (Figures 2). Based on their relevance, these variables were identified as follows: OPP, PDA, spontaneous onset of the labor, and oxytocin. The most powerful predictor was OPP. The absolute accuracy of the model prediction was 87.5%, with 94.9% for vaginal delivery and 64.6% for CS. In the CHAID2 model (Figures 3), as in the LR3 model, the variables spontaneous onset of the labor and oxytocin were eliminated. The model identified OPP, PDA, BMI before delivery, and height and weight before delivery, based on their relevance. The total success of the model prediction was 87.3%, with 96.4% for vaginal delivery and 59.0% for CS

**Figure 2 Classification tree of model CHAID 1**

**Figure 3 Classification tree of model CHAID 2**

DISCUSSION

Using two different statistical methods, we identified identical factors that increase the risk of acute CS due to progress failure and/or intranatal fetal hypoxia in nulliparae. They were related to the somatotype (BMI before pregnancy, before delivery and difference thereof, and body height), course of pregnancy (excessive increase in weight during pregnancy, GDM, and fetal weight), and clinical circumstances during the delivery itself (induced labor, OPP, PDA, and oxytocin). The OPP of the fetus at the beginning of labor was the most relevant risk factor. In addition, the CS risk was higher in smaller women with a higher body weight before pregnancy. The use of PDA and oxytocin was ascertained as a protective measure during delivery.

Age

Women on acute CS were on average 1 year older than those who delivered vaginally. The higher age has been already identified as a negative predictive factor for vaginal delivery in 15 studies. Contrarily, a causal relationship with other age-related risk factors has not yet been clarified completely [8]. Given the minimal difference between groups, it cannot be used as an independent clinical predictor of CS.

Somatotype and Fetal Birth Weight

Specific woman’s somatotype (increase in weight, higher body weight, and BMI before pregnancy/delivery) was associated with a higher risk of acute CS. Previously, it has been ascertained that an increase in BMI by one unit during the pregnancy increases the CS likelihood by 7% [10]. Maternal obesity also increases the risk of other pregnancy and delivery complications (pre-eclampsia, fetal macrosomia, premature delivery, GDM, post-term pregnancy, protracted first labor-stage, etc.) [9, 32, 38]. Higher fetal birth weight is another known independent risk factor for any CS [30]. The characteristic curve of the CS risk and fetal birth weight is U-shaped, with the lowest risk in medium-weighted fetuses (3,000–3,500 g) [35]. The absolute difference in somatotypes was small; thus, they cannot be used independently.

OPP

OPP was found in 587 (15.9%) women, of whom 102 (17.4%) completed vaginal delivery. The likelihood of acute CS was increased by OR 38–45. At the beginning of the delivery, 20–30% of fetuses are in OPP; however, 85% of them will rotate to some anterior position, and only 6.6% fetuses are delivered in the OPP [17, 19]. The OPP is the most frequent failure of fetal presentation contributing to 18% of acute CS [26]. Up to 82% of deliveries with OPP are completed by operative delivery [12]. The persistence of OPP could be increased by PDA and oxytocin augmentation [34]. These pregnancies are more frequently induced, protracted, and complicated by chorioamnionitis, post-delivery hemorrhage, severe perineal ruptures, wound infection, and puerperal endometritis [12]. Moreover, newborns more frequently suffer from postpartum post-traumatic stress disorder and low Apgar score and are more likely admitted to the intensive care unit [14].

PDA

PDA was associated with a 3.8–4.4 times higher likelihood of acute CS. Comparison to other studies is difficult considering various medications are used with different dosages and timing [24, 36]. An earlier Cochrane meta-analysis did not prove the effect of PDA on the higher risk of acute CS [4]. Similarly, later studies showed an increased likelihood only of vaginal extraction operation (OR 3.63, 95% CI: 2.51–5.24) but not of acute CS [5]. Contrariwise, PDA administration in an early first stage of labor in nulliparae increases the likelihood of acute CS [24]. One study showed a powerful relationship between PDA and CS was required because of the failure to progress or fetal distress. Although it was lacking randomization, PDA was likely more frequently administered if dystocia was present [6]. Our observations are consistent with those studies that identified up to 2.5 times higher risk of acute CS. We administered PDA in the active stage of the labor. Therefore, the higher percentage of acute CS in women with PDA is probably related to other clinical circumstances resulting in acute CS.

Labor induction

Similar to other studies, we recorded a higher likelihood of CS following labor induction [40]. Most probably, this is associated with the reasons for the labor induction [23].

Oxytocin

Oxytocin augmentation was used in 67% of the nulliparae, and it was related to a lower occurrence of acute CS. The literature on oxytocin augmentation and CS risk is inconsistent. Some described the slightly decreased risk of CS, yet others linked its application with more PDA application, intrapartum fewer, and earlier acute CS [22, 39]. CS risk is also increased if oxytocin is administered in the presence of other risk factors (e.g., higher maternal BMI) [1].

GDM

GDM was more frequent in women with CS but was not identified as a risk factor. Other studies reported that women with GDM are exposed to a higher risk of acute CS after adjustment for pre-pregnancy BMI, weight-gain, and fetal birth weight [7, 20].

Prediction models

The clinical relevance of the individually employed risk factors is very low; moreover they are often concurrent. Therefore, we opted for two types of analyses (LR and CHAID) for identifying the key risk factors. Both methods recognized similar risk factors for acute CS, with comparable sensitivity and specificity. The use of CHAID appears to be more clinically relevant as it attains fewer variables and incorporates missing data. Early identification of nulliparae with a high risk of acute CS would simplify the decision-making process for obstetricians concerning the delivery method. Unfortunately, the ability to predict acute CS using LR and the “neural network” software in nulliparae ranges from 26 to 53% for the acute CS and from 88 to 95% for the vaginal delivery [3]. A genesis study developed a five-parameter model (para’s age, BMI, body height, and abdomen measurement) that is clinically implementable [11]. The application identifies women with higher risk and recommends primary CS. Its prediction ability for vaginal delivery is 95% and 49% for CS (38). The CS prediction is generally more difficult, possibly because of the significance level below 0.5, but at the expense of specificity. The ultimate consequence would be an increase in unnecessary CS. Another improvement could be done by including more input variables. Authors included 78 variables and obtained a high ROC for acute CS prediction, amounting to 0.86 in LR for nulliparae and 0.93 for multiparae, and in CHAID 0.82 for nulliparae and 0.93 for multiparae [33]. Our models included only basic variables but attained relatively high predictive values for CS; therefore, we assume that they can be used during the decision-making process. If oxytocin application and labor induction were included, the most significant risk factor was unchanged (OPP; OR: 45.5, 95%CI: 34.5–60.2). Interestingly, oxytocin application (OR 0.49, 95% CI: 0.39–0.61) and spontaneous onset of labor (OR 0.36, 95%CI: 0.29–0.45) were shown as protective factors. Both are similar to another prospective study reporting an OR 2.9 for OPP (95% CI: 1.3–6.7; p = 0.01) and OR 2.4 for delivery induction (95% CI: 1.0–5.6; p = 0.05) [16]. Our model would definitely benefit from including more ultrasonographic data obtained at intrapartum (such as fetal head position, cervix dilatation, and fetal-head-perineum distance) [18]. This study has some limitations. The presented results must be perceived within the context of the group demographic composition. Included women were only Caucasians, and they were 2 years older than the national average age of nulliparae (28.2 years) [37]; however, the group very well represents the population delivering in our institute. Other limitations are the subjective evaluation of the fetal head progression, unclear indications for PDA application and dosage of oxytocin used during the delivery. Possibly, there would have been less OPP if ultrasonography had been performed at the lower levels of the pelvis. The strengths are the robust prospectively monitored group who gave birth in a large hospital (>5,000 deliveries/year), the “active” delivery management, and uniform rules for CS [29]. The study also included only a low-risk population to eliminate bias caused by premature deliveries or growth-restricted fetuses. For predicting CS, we developed three models based on LR and two classification tree models. The LR models are always based on selected variables. CHAID works with all of them yet selecting only the critical ones and can be used for clinical decision-making. The absolute prediction accuracy for all models was about 87%, with an inferior predictive ability for the execution of acute CS (about 60%). The most significant predictor was always the OPP. Peripartal ultrasound detection of the fetal position offers important information for delivery management and decision-making on the execution of acute CS.

CONCLUSION

Analysis of specific factors known before or during the first parturition could determine the risk of the acute CS during childbirth. Identification of high-risk women and conceivably earlier indications of CS may reduce risk related to the second stage CS. This study helped us to create a basis for predictive model including few but basic characteristics. However, this preventive approach should firstly be tested in a prospective randomized study. Future studies should include the intrapartum ultrasound data to improve its prediction ability. At this stage of knowledge, we at least should implement the easier classification tree (CHAID) into the clinical practice. Women with OPP are 45-fold more likely to have an unplanned CS; therefore, they should be offered PDA and oxytocin in case of slow progression of cervical opening, and they should be monitored if they have a higher risk of unplanned CS.

Petr Krepelka, MD, PhD

Institute for the Care of Mother and Child

Podolske Nabrazi 157

147 00 Prague 4

e-mail: petr.krepelka@upmd.eu

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