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Original article
Cross-validated prediction model for severe adverse neonatal outcomes in a term, non-anomalous, singleton cohort
  1. Christopher Flatley1,
  2. Kristen Gibbons2,
  3. Cameron Hurst3,
  4. Vicki Flenady1,4,
  5. Sailesh Kumar1
  1. 1 Mater Research, Mater Research Institute/University of Queensland, Brisbane, Queensland, Australia
  2. 2 Mater Medical Research Institute, South Brisbane, Queensland, Australia
  3. 3 QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
  4. 4 Centre for Research Excellence in Stillbirth, Mater Research Institute/University of Queensland, Brisbane, Queensland, Australia
  1. Correspondence to Dr Sailesh Kumar; sailesh.kumar{at}mater.uq.edu.au

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.

  • fetal medicine
  • imaging
  • statistics
  • epidemiology

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Footnotes

  • Contributors CF and SK conceived the study. CF, KG and CH designed the statistical analysis plan. CF prepared the data and carried out the analysis. CF and SK interpreted the results. VF assisted in the concept and interpretation. All authors drafted and finalised the paper.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Ethics approval This study meets national guidelines set out by the National Health and Medical Research Council of Australia. Ethics approval was granted by The Mater Misericordiae Ltd Human Research Ethics Committee (reference number HREC/14/MHS/37).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement The data used throughout this study are available from Mater Research but restrictions apply to the availability. Data were used under an agreement of confidentiality and privacy and therefore not available publicly. Data are available from the authors with privacy agreements and with permission from Mater Research. Statistical code is available from authors on request.

  • Patient consent for publication Not required.

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