Dataset Information

Cross-validated prediction model for severe adverse neonatal outcomes in a term, non-anomalous, singleton cohort.

ABSTRACT:

Objective

The aim of this study was to develop a predictive model using maternal, intrapartum and ultrasound variables for a composite of severe adverse neonatal outcomes (SANO) in term infants.

Design

Prospectively collected observational study. Mixed effects generalised linear models were used for modelling. Internal validation was performed using the K-fold cross-validation technique.

Setting

This was a study of women that birthed at the Mater Mother's Hospital in Brisbane, Australia between January 2010 and April 2017.

Patients

We included all term, non-anomalous singleton pregnancies that had an ultrasound performed between 36 and 38?weeks gestation and had recordings for the umbilical artery pulsatility index, middle cerebral artery pulsatility index and the estimated fetal weight (EFW).

Main outcome measures

The components of the SANO were: severe acidosis arterial, admission to the neonatal intensive care unit, Apgar score of ?3?at 5?min or perinatal death.

Results

There were 5439 women identified during the study period that met the inclusion criteria, with 11.7% of this cohort having SANO. The final generalised linear mixed model consisted of the following variables: maternal ethnicity, socioeconomic score, nulliparity, induction of labour, method of birth and z-scores for EFW and cerebroplacental ratio. The final model had an area under the receiver operating characteristic curve of 0.71.

Conclusions

The results of this study demonstrate it is possible to predict infants that are at risk of SANO at term with moderate accuracy using a combination of maternal, intrapartum and ultrasound variables. Cross-validation analysis suggests a high calibration of the model.

SUBMITTER: Flatley C

PROVIDER: S-EPMC6422248 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cross-validated prediction model for severe adverse neonatal outcomes in a term, non-anomalous, singleton cohort.

Flatley Christopher C Gibbons Kristen K Hurst Cameron C Flenady Vicki V Kumar Sailesh S

BMJ paediatrics open 20190315 1

<h4>Objective</h4>The aim of this study was to develop a predictive model using maternal, intrapartum and ultrasound variables for a composite of severe adverse neonatal outcomes (SANO) in term infants.<h4>Design</h4>Prospectively collected observational study. Mixed effects generalised linear models were used for modelling. Internal validation was performed using the K-fold cross-validation technique.<h4>Setting</h4>This was a study of women that birthed at the Mater Mother's Hospital in Brisba ...[more]

PMID: 30957032

Similar Datasets

Project description:ImportanceDespite the increased perinatal risks associated with pregnancies conceived with infertility treatment, there are no recommendations for timing of delivery among this at-risk population.ObjectiveTo identify the gestational age at which the ongoing risks of stillbirth are optimally balanced with the risks of neonatal comorbidities and infant deaths in term singleton pregnancies conceived with infertility treatment.Design, setting, and participantsThis cohort study used birth and death data from January 1, 2014, to December 31, 2018, in the US obtained from the National Center for Health Statistics. Singleton pregnancies conceived with infertility treatment delivered at term (37-42 weeks' gestation) were eligible for inclusion. The exclusion criteria were deliveries at less than 37 weeks' or at least 43 weeks' gestation and pregnancies with unknown history of infertility treatment, congenital anomalies, pregestational diabetes, pregestational hypertension, gestational hypertension, and preeclampsia. Data were analyzed from July 22, 2022, to June 24, 2023.ExposureGestational age at delivery between 37 and 42 weeks.Main outcomes and measuresThe primary outcome was optimal timing of delivery. To ascertain this timing, the risk of delivery (rate of neonatal morbidity and infant death) at a given gestational week was compared with the risk of delivery in the subsequent week of gestation for an additional week (rate of stillbirth during the given week per 10 000 ongoing pregnancies plus rate of neonatal morbidity and infant death in the subsequent week of gestation per 10 000 deliveries). The rates of stillbirth, neonatal morbidity, and infant death (within 1 year of life) were compared at each week. Neonatal morbidity included an Apgar score of 3 or lower at 5 minutes, requirement of ventilation for 6 hours or more, neonatal intensive care unit admission, and seizures.ResultsOf the 178 448 singleton term pregnancies conceived with infertility treatment (maternal mean [SD] age, 34.2 [5.2] years; mean [SD] gestational age, 39.2 [1.2] weeks; 130 786 [73.5%] were non-Hispanic White patients). The risk of delivery in the subsequent week of gestation was lower than the risk of delivery at both 37 weeks (628 [95% CI, 601-656] vs 1005 [95% CI, 961-1050] per 10 000 live births) and 38 weeks (483 [95% CI, 467-500 vs 625 [95% CI, 598-652] per 10 000 live births). The risks of delivery in subsequent week of gestation significantly exceeded the risk of delivery at 39 weeks (599 [95% CI, 576-622] vs 479 [95% CI, 463-495] per 10 000 live births) and were not significant at 40 weeks (639 [95% CI, 605-675] vs 594 [95% CI, 572-617] per 10 000 live births) and 41 weeks (701 [95% CI, 628-781] vs 633 [95% CI, 599-669] per 10 000 live births).Conclusions and relevanceResults of this study suggest that, in pregnancies conceived with infertility treatment, delivery at 39 weeks provided the lowest perinatal risk when comparing risk of delivery at this week of gestation vs the subsequent week of gestation.

Dataset Information

Cross-validated prediction model for severe adverse neonatal outcomes in a term, non-anomalous, singleton cohort.

Objective

Design

Setting

Patients

Main outcome measures

Results

Conclusions

Publications

Cross-validated prediction model for severe adverse neonatal outcomes in a term, non-anomalous, singleton cohort.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets