Maternal age and risk of cesarean section in women with induced labor at term—A Nordic register‐based study

Bergholt, Thomas; Skjeldestad, Finn Egil; Pyykönen, Aura; Rasmussen, Steen; Tapper, Anna‐Maija; Bjarnadóttir, Ragnheiður I.; Smárason, Alexander K.; Másdóttir, Birna Björg; Klungsøyr, Kari; Albrechtsen, Susanne; Källén, Karin; Gissler, Mika; Løkkegaard, Ellen

doi:10.1111/aogs.13743

Cited by 37 publications

(28 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The models highlight the importance of variables such as maternal age, maternal height, pre-pregnancy BMI, gestational age, weight gain during pregnancy, degree of meconium-stained amniotic uid, indicator for occurrence of premature rupture of membranes and fetal sex in determining the cesarean delivery when women failed the trial of labor. These results are consistent with the existing literature on the risk of cesarean delivery [16,[21][22][23]. Past studies also found gestational age of induced labor and induction methods were related to the incidence of cesarean [24,25].…”

Section: Discussionsupporting

confidence: 92%

Development And Validation Of Models To Predict Cesarean Delivery Among Low-Risk Nulliparous Women At Term: A Retrospective Study In China

Sun¹,

Han²,

Wu³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Cesarean delivery after failure of trial of labor is associated with adverse maternal and perinatal outcomes. A prediction algorithm to identify women with high risk of an emergency cesarean could help reduce morbidity and mortality associated with labor. The objective of the present study was to derive and validate a simple model to predict cesarean delivery for low-risk nulliparous women in Chinese population.Methods: This retrospective study analyzed the low-risk nulliparous women with singleton cephalic full-term fetus delivered in two medical centers. After the clinical data of the women who delivered at the tertiary referral center (n=6 551) was collected and was used univariate and multivariable logistic regression analysis, the prediction model was fitted. We performed external validation using data from nulliparous who delivered from another hospital(secondary referral center, n=7 657). A new nomogram was established based on the development cohort to predict the cesarean. The ROC curve, calibration plot and decision curve analysis were used to assess the predictive performance. Results: The cesarean delivery rates in the development cohort and the external validation cohort were 8.79% (576/6 551) and 7.82% (599/7 657). Multivariable logistic regression analysis showed that maternal age, height, BMI, weight gained during pregnancy, gestational age, induction method, meconium-stained amniotic fluid and neonatal sex were independent factors affecting cesarean outcome. Because sex of the fetuses were unknown until they born(China's Fertility Policy), we established two prediction models according to fetal sex was involved or not. The AUC was 0.782 and 0.774, respectively. The Hosmer-Lemeshow goodness-of-fit test showed that these two models fitted well. Decision curve analysis demonstrated that the models were clinically useful. And internal validation using Bootstrap method showed that these prediction models perform well. On the external validation set, the AUC were 0.775 and 0.775, respectively. The calibration plots for the probability of cesarean showed a good correlation. The online web server was constructed based on the nomogram for convenient clinical use.Conclusions: Both two models established by these factors have good prediction efficiency and high accuracy, which can provide the reference for clinicians to guide pregnant women to choose an appropriate delivery mode.

show abstract

Section: Discussionsupporting

confidence: 92%

Development And Validation Of Models To Predict Cesarean Delivery Among Low-Risk Nulliparous Women At Term: A Retrospective Study In China

Sun¹,

Han²,

Wu³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The model highlight the importance of variables such as maternal age, maternal height, pre-pregnancy BMI, gestational age, weight gain during pregnancy, induction method, degree of meconium-stained amniotic uid, indicator for occurrence of premature rupture of membranes and male fetus in determining the cesarean delivery when women failed the trial of labor. These results are consistent with the existing literature on the risk of cesarean delivery [18,[24][25][26]. Past studies also found gestational age of induced labor and induction methods were related to the incidence of cesarean [27,28].…”

Section: Discussionsupporting

confidence: 92%

Development and validation of models to predict cesarean delivery among low-risk nulliparous women at term: a retrospective study in China

Sun

Han

Wu³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background A prediction algorithm to identify women with high risk of an emergency cesarean could help reduce morbidity and mortality associated with labor. The objective of the present study was to derive and validate a simple model to predict intrapartum cesarean delivery for low-risk nulliparous women in Chinese population.Methods We conducted a retrospective cohort study of low-risk nulliparous women with singleton, term, cephalic pregnancies. A predictive model for cesarean delivery was derived using univariate and multivariable logistic regression from the hospital of the First Affiliated Hospital of Soochow University. External validation of the prediction model was then performed using the data from Sihong county People’s Hospital. A new nomogram was established based on the development cohort to predict the cesarean. The ROC curve, calibration plot and decision curve analysis were used to assess the predictive performance.Results The intrapartum cesarean delivery rates in the development cohort and the external validation cohort were 8.79% (576/6,551) and 7.82% (599/7,657). Multivariable logistic regression analysis showed that maternal age, height, BMI, weight gained during pregnancy, gestational age, induction method, meconium-stained amniotic fluid and neonatal sex were independent factors affecting cesarean outcome. We had established two prediction models according to fetal sex was involved or not. The AUC was 0.782 and 0.774, respectively. The two prediction models were well-calibrated with Hosmer-Lemeshow test P=0.263 and P=0.817, respectively. Decision curve analysis demonstrated that two models had clinical application value, and they provided greatest net benefit between threshold probabilities of 4% to 60%. And internal validation using Bootstrap method demonstrated similar discriminatory ability. We external validated the model involving fetal sex, for which the AUC was 0.775, while the slope and intercept of the calibration plot were 0.979 and 0.004, respectively. On the external validation set, another model had an AUC of 0.775 and a calibration slope of 1.007. The online web server was constructed based on the nomogram for convenient clinical use.Conclusions Both two models established by these factors have good prediction efficiency and high accuracy, which can provide the reference for clinicians to guide pregnant women to choose an appropriate delivery mode.

show abstract

“…With advances of blood transfusion, anesthesiology, diversification of surgical methods, improvement of surgical suture materials, cesarean section has become an effective treatment of maternal women [ [1,2]]. However, the risks of postoperative thrombosis, intraoperative bleeding, uterine rupture, and placenta previa of repregnancy after cesarean delivery are significantly higher than those of women delivered via vaginal delivery [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

The risk factors and care measures of surgical site infection after cesarean section in China: a retrospective analysis

Cui

2021

BMC Surg

View full text Add to dashboard Cite

Background Surgical site infections after cesarean section are very common clinically, it is necessary to evaluate the risk factors of surgical site infections after cesarean section, to provide evidences for the treatment and nursing care of cesarean section. Methods This study was a retrospective cohort study design. Patients undergone cesarean section in a tertiary hospital of China from May 2017 to May 2020 were identified, we collected the clinical data of the included patients, and we analyzed the infection rate, etiological characteristics and related risk factors of surgical site infection after caesarean section. Results A total of 206 patients with cesarean section were included, and the incidence of surgical site infection in patients with cesarean section was 23.30%. A total of 62 cases of pathogens were identified, Enterococcus faecalis (33.87%) and Escherichia coli (29.03%) were the most common pathogens. Both Enterococcus faecalis and Escherichia coli were highly sensitive to Cefoperazone, Meropenem, and Levofloxacin. Logistic regression analyses indicated that Age ≥ 30y (OR 4.18, 95%CI: 1.23–7.09), BMI ≥ 24 (OR 2.39, 95%CI: 1.02–4.55), duration of cesarean section ≥ 1.5 h (OR 3.90, 95%CI: 1.28–5.42), estimated blood loss ≥ 400 ml (OR 2.35, 95%CI: 1.10–4.37) and the duration of urinary catheter ≥ 24 h (OR 3.18, 95% CI: 1.21–5.71) were the independent risk factors of surgical site infection after cesarean section (all p < 0.05). Conclusions Age, BMI, duration of surgery, blood loss and urinary catheter use were associated with higher risk of the surgical site infection after cesarean section. Clinical preventions and interventions are warranted for those population to reduce the occurrence of surgical site infection.

show abstract

Maternal age and risk of cesarean section in women with induced labor at term—A Nordic register‐based study

Cited by 37 publications

References 28 publications

Development And Validation Of Models To Predict Cesarean Delivery Among Low-Risk Nulliparous Women At Term: A Retrospective Study In China

Development And Validation Of Models To Predict Cesarean Delivery Among Low-Risk Nulliparous Women At Term: A Retrospective Study In China

Development and validation of models to predict cesarean delivery among low-risk nulliparous women at term: a retrospective study in China

The risk factors and care measures of surgical site infection after cesarean section in China: a retrospective analysis

Contact Info

Product

Resources

About