Dataset Information

Predicting the Risk of Adverse Events in Pregnant Women With Congenital Heart Disease.

ABSTRACT: Background Women with congenital heart disease are considered at high risk for adverse events. Therefore, we aim to establish 2 prediction models for mothers and their offspring, which can predict the risk of adverse events occurred in pregnant women with congenital heart disease. Methods and Results A total of 318 pregnant women with congenital heart disease were included; 213 women were divided into the development cohort, and 105 women were divided into the validation cohort. Least absolute shrinkage and selection operator was used for predictor selection. After validation, multivariate logistic regression analysis was used to develop the model. Machine learning algorithms (support vector machine, random forest, AdaBoost, decision tree, k-nearest neighbor, naïve Bayes, and multilayer perceptron) were used to further verify the predictive ability of the model. Forty-one (12.9%) women experienced adverse maternal events, and 93 (29.2%) neonates experienced adverse neonatal events. Seven high-risk factors were discovered in the maternal model, including New York Heart Association class, Eisenmenger syndrome, pulmonary hypertension, left ventricular ejection fraction, sinus tachycardia, arterial blood oxygen saturation, and pregnancy duration. The machine learning-based algorithms showed that the maternal model had an accuracy of 0.76 to 0.86 (area under the receiver operating characteristic curve=0.74-0.87) in the development cohort, and 0.72 to 0.86 (area under the receiver operating characteristic curve=0.68-0.80) in the validation cohort. Three high-risk factors were discovered in the neonatal model, including Eisenmenger syndrome, preeclampsia, and arterial blood oxygen saturation. The machine learning-based algorithms showed that the neonatal model had an accuracy of 0.75 to 0.80 (area under the receiver operating characteristic curve=0.71-0.77) in the development cohort, and 0.72 to 0.79 (area under the receiver operating characteristic curve=0.69-0.76) in the validation cohort. Conclusions Two prenatal risk assessment models for both adverse maternal and neonatal events were established, which might assist clinicians in tailoring precise management and therapy in pregnant women with congenital heart disease.

SUBMITTER: Chu R

PROVIDER: S-EPMC7660735 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting the Risk of Adverse Events in Pregnant Women With Congenital Heart Disease.

Chu Ran R Chen Wei W Song Guangmin G Yao Shu S Xie Lin L Song Li L Zhang Yue Y Chen Lijun L Zhang Xiangli X Ma Yuyan Y Luo Xia X Liu Yuan Y Sun Ping P Zhang Shuquan S Fang Yan Y Dong Taotao T Zhang Qing Q Peng Jin J Zhang Lu L Wei Yuan Y Zhang Wenxia W Su Xuantao X Qiao Xu X Song Kun K Yang Xingsheng X Kong Beihua B

Journal of the American Heart Association 20200714 14

Background Women with congenital heart disease are considered at high risk for adverse events. Therefore, we aim to establish 2 prediction models for mothers and their offspring, which can predict the risk of adverse events occurred in pregnant women with congenital heart disease. Methods and Results A total of 318 pregnant women with congenital heart disease were included; 213 women were divided into the development cohort, and 105 women were divided into the validation cohort. Least absolute s ...[more]

PMID: 32662348

Similar Datasets

Project description:ObjectiveTo estimate nationwide trends in the prevalence of maternal congenital heart disease (CHD) and determine whether women with CHD are more likely than women without maternal CHD to have medical and obstetric complications.MethodsThe 2000-2010 Nationwide Inpatient Sample was queried for International Classification of Diseases, 9th Revision, Clinical Modification codes to identify delivery hospitalizations of women with and without CHD. Trends in the prevalence of CHD were determined and then rates of complications were reported for CHD per 10,000 delivery hospitalizations. For Nationwide Inpatient Sample 2008-2010, logistic regression was used to examine associations between CHD and complications.ResultsFrom 2000 to 2010, there was a significant linear increase in the prevalence of CHD from 6.4 to 9.0 per 10,000 delivery hospitalizations (P<.001). Multivariable logistic regression demonstrated that all selected medical complications, including mortality (17.8 compared with 0.7/10,000 deliveries, adjusted odds ratio [OR] 22.10, 95% confidence interval [CI] 13.96-34.97), mechanical ventilation (91.9 compared with 6.9/10,000, adjusted OR 9.94, 95% CI 7.99-12.37), and a composite cardiovascular outcome (614 compared with 34.3/10,000, adjusted OR 10.54, 95% CI 9.55-11.64) were more likely to occur among delivery hospitalizations with maternal CHD than without. Obstetric complications were also common among women with CHD. Delivery hospitalizations with maternal CHD that also included codes for pulmonary circulatory disorders had higher rates of medical complications compared with hospitalizations with maternal CHD without pulmonary circulatory disorders.ConclusionThe number of delivery hospitalizations with maternal CHD in the United States is increasing, and although we were not able to determine whether correction of the cardiac lesion affected outcomes, these hospitalizations have a high burden of medical and obstetric complications.Level of evidenceII.

Project description:ImportanceWomen with disabilities have a higher risk of preterm birth, gestational diabetes, preeclampsia, and cesarean delivery; however, their risk of other obstetric interventions, adverse maternal outcomes, and clinical indications for increased cesarean delivery is unclear.ObjectiveTo evaluate risk of a range of obstetric interventions and adverse maternal outcomes, including severe maternal morbidities (SMM) and mortality, among women with and without disabilities.Design, setting, and participantsThe Consortium on Safe Labor was a retrospective cohort that included comprehensive medical chart review for deliveries between January 2002 and January 2008. Data were collected from 12 clinical sites, which included 19 hospitals across the United States. This secondary analysis was conducted in February to July 2021.ExposuresUsing International Classification of Diseases, Ninth Revision, codes and a validated algorithm to define disability, participants were classified as having physical, intellectual, sensory, or any disability, and compared with women with no documented disability.Main outcomes and measuresThe relative risk (RR) of 23 obstetric interventions and adverse maternal outcomes, including SMM and mortality, was evaluated.ResultsOf the 223 385 women in the study, 9206 (4.1%) were Asian or Pacific Islander, 50 235 (22.5%) were Black, 39 039 (17.5%) were Hispanic, and 110 443 (49.4%) were White, with a mean (SD) age of 27.6 (6.2) years. There were 2074 (0.9%) women with disability and 221 311 (99.1%) without. Among women with disabilities, 1733 (83.5%) were physical, 91 (4.4%) were intellectual, and 250 (12.1%) were sensory. Compared with women with no disability, women with disabilities had higher risk of gestational diabetes, placenta previa, premature rupture of membranes, preterm premature rupture of membranes, and postpartum fever as well as maternal death (adjusted relative risk [aRR], 11.19; 95% CI, 2.40-52.19) and individual SMMs: severe preeclampsia/eclampsia (aRR, 2.15; 95% CI, 1.80-2.56), hemorrhage (aRR, 1.27; 95% CI, 1.09-1.49), and fever (aRR, 1.32; 95% CI, 1.03-1.67), with the highest risk observed for thromboembolism (aRR, 6.08; 95% CI, 4.03-9.16), cardiovascular events (aRR, 4.02; 95% CI, 2.87-5.63), and infection (aRR, 2.69; 95% CI, 1.97-3.67). Women with any disability also had higher risk of interventions, including oxytocin augmentation, operative vaginal delivery, and cesarean delivery (aRR, 1.33; 95% CI, 1.25-1.42), with the cesarean indication less likely to be medically indicated (aRR, 0.79; 95% CI, 0.70-0.89). Risk of adverse outcomes and interventions remained consistent across disability categories.Conclusions and relevanceIn this study, women with physical, intellectual, and sensory disability during pregnancy were at higher risk of adverse outcomes, including a broad range of SMM and maternal mortality.

Dataset Information

Predicting the Risk of Adverse Events in Pregnant Women With Congenital Heart Disease.

Publications

Predicting the Risk of Adverse Events in Pregnant Women With Congenital Heart Disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets