Skip to main content
Top

2019 | OriginalPaper | Chapter

Time-to-Birth Prediction Models and the Influence of Expert Opinions

Authors : Gilles Vandewiele, Isabelle Dehaene, Olivier Janssens, Femke Ongenae, Femke De Backere, Filip De Turck, Kristien Roelens, Sofie Van Hoecke, Thomas Demeester

Published in: Artificial Intelligence in Medicine

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Preterm birth is the leading cause of death among children under five years old. The pathophysiology and etiology of preterm labor are not yet fully understood. This causes a large number of unnecessary hospitalizations due to high–sensitivity clinical policies, which has a significant psychological and economic impact. In this study, we present a predictive model, based on a new dataset containing information of 1,243 admissions, that predicts whether a patient will give birth within a given time after admission. Such a model could provide support in the clinical decision-making process. Predictions for birth within 48 h or 7 days after admission yield an Area Under the Curve of the Receiver Operating Characteristic (AUC) of 0.72 for both tasks. Furthermore, we show that by incorporating predictions made by experts at admission, which introduces a potential bias, the prediction effectiveness increases to an AUC score of 0.83 and 0.81 for these respective tasks.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Alleman, B.W., et al.: A proposed method to predict preterm birth using clinical data, standard maternal serum screening, and cholesterol. AJOG 208(6), 472-e1 (2013)CrossRef Alleman, B.W., et al.: A proposed method to predict preterm birth using clinical data, standard maternal serum screening, and cholesterol. AJOG 208(6), 472-e1 (2013)CrossRef
2.
go back to reference Allouche, M., et al.: Development & validation of nomograms for predicting ptb. AJOG 204(3), 242 (2011)CrossRef Allouche, M., et al.: Development & validation of nomograms for predicting ptb. AJOG 204(3), 242 (2011)CrossRef
3.
go back to reference Behrman, R.E., Butler, A.S., et al.: Societal costs of preterm birth (2007) Behrman, R.E., Butler, A.S., et al.: Societal costs of preterm birth (2007)
4.
go back to reference Beta, J., et al.: Prediction of spontaneous preterm delivery from maternal factors, obstetric history and placental perfusion and function at 11–13 weeks. Prenat. Diagn. 31(1), 75–83 (2011)CrossRef Beta, J., et al.: Prediction of spontaneous preterm delivery from maternal factors, obstetric history and placental perfusion and function at 11–13 weeks. Prenat. Diagn. 31(1), 75–83 (2011)CrossRef
5.
go back to reference Celik, E., et al.: Cervical length and obstetric history predict sptb: development & validation of a model to provide individualized risk assessment. UOG 31(5), 549–554 (2008) Celik, E., et al.: Cervical length and obstetric history predict sptb: development & validation of a model to provide individualized risk assessment. UOG 31(5), 549–554 (2008)
6.
go back to reference De Silva, D.A., et al.: Timing of delivery in a high-risk obstetric population: a clinical prediction model. BMC Pregnancy Childbirth 17(1), 202 (2017)CrossRef De Silva, D.A., et al.: Timing of delivery in a high-risk obstetric population: a clinical prediction model. BMC Pregnancy Childbirth 17(1), 202 (2017)CrossRef
7.
go back to reference García-Blanco, A., et al.: Can stress biomarkers predict preterm birth in women with threatened preterm labor? Psychoneuroendocrinology 83, 19–24 (2017)CrossRef García-Blanco, A., et al.: Can stress biomarkers predict preterm birth in women with threatened preterm labor? Psychoneuroendocrinology 83, 19–24 (2017)CrossRef
8.
go back to reference Liu, L., et al.: Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the sustainable development goals. Lancet 388(10063), 3027–3035 (2016)CrossRef Liu, L., et al.: Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the sustainable development goals. Lancet 388(10063), 3027–3035 (2016)CrossRef
9.
go back to reference Mailath-Pokorny, M., et al.: Individualized assessment of preterm birth risk using two modified prediction models. Eur. J. Obstet. Gynecol. Reprod. Biol. 186, 42–48 (2015)CrossRef Mailath-Pokorny, M., et al.: Individualized assessment of preterm birth risk using two modified prediction models. Eur. J. Obstet. Gynecol. Reprod. Biol. 186, 42–48 (2015)CrossRef
10.
go back to reference Meertens, L.J., et al.: Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation. Acta Obstet. Gynecol. Scand. 97(8), 907–920 (2018)CrossRef Meertens, L.J., et al.: Prediction models for the risk of spontaneous preterm birth based on maternal characteristics: a systematic review and independent external validation. Acta Obstet. Gynecol. Scand. 97(8), 907–920 (2018)CrossRef
11.
go back to reference Melamed, N., et al.: Association between antenatal corticosteroid administration-to-birth interval and outcomes of preterm neonates. Obstet. Gynecol. 125(6), 1377–1384 (2015)CrossRef Melamed, N., et al.: Association between antenatal corticosteroid administration-to-birth interval and outcomes of preterm neonates. Obstet. Gynecol. 125(6), 1377–1384 (2015)CrossRef
12.
go back to reference Menon, R., et al.: Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth. Acta Obstet. Gynecol. Scand. 93(4), 382–391 (2014)CrossRef Menon, R., et al.: Multivariate adaptive regression splines analysis to predict biomarkers of spontaneous preterm birth. Acta Obstet. Gynecol. Scand. 93(4), 382–391 (2014)CrossRef
13.
go back to reference Roelens, K., et al.: Prevention of preterm birth in women at risk: Selected topics. Technical report, Belgian Health Care Knowledge Centre (KCE) (2014) Roelens, K., et al.: Prevention of preterm birth in women at risk: Selected topics. Technical report, Belgian Health Care Knowledge Centre (KCE) (2014)
14.
go back to reference Sananes, N., et al.: Prediction of spontaneous preterm delivery in the first trimester of pregnancy. Eur. J. Obstet. Gynecol. Reprod. Biol. 171(1), 18–22 (2013)CrossRef Sananes, N., et al.: Prediction of spontaneous preterm delivery in the first trimester of pregnancy. Eur. J. Obstet. Gynecol. Reprod. Biol. 171(1), 18–22 (2013)CrossRef
15.
go back to reference Schaaf, J.M., et al.: Development of a prognostic model for predicting spontaneous singleton preterm birth. Eur. J. Obstet. Gynecol. Reprod. Biol. 164(2), 150–155 (2012)CrossRef Schaaf, J.M., et al.: Development of a prognostic model for predicting spontaneous singleton preterm birth. Eur. J. Obstet. Gynecol. Reprod. Biol. 164(2), 150–155 (2012)CrossRef
16.
go back to reference Tan, H., et al.: Early prediction of preterm birth for singleton, twin, and triplet pregnancies. Eur. J. Obstet. Gynecol. Reprod. Biol. 131(2), 132–137 (2007)CrossRef Tan, H., et al.: Early prediction of preterm birth for singleton, twin, and triplet pregnancies. Eur. J. Obstet. Gynecol. Reprod. Biol. 131(2), 132–137 (2007)CrossRef
17.
go back to reference Tekesin, I., et al.: Evaluation and validation of a new risk score (cleopatra score) to predict the probability of premature delivery for patients with threatened preterm labor. UOG 26(7), 699–706 (2005) Tekesin, I., et al.: Evaluation and validation of a new risk score (cleopatra score) to predict the probability of premature delivery for patients with threatened preterm labor. UOG 26(7), 699–706 (2005)
18.
go back to reference To, M., et al.: Prediction of patient-specific risk of early preterm delivery using maternal history and sonographic measurement of cervical length. UOG 27(4), 362–367 (2006) To, M., et al.: Prediction of patient-specific risk of early preterm delivery using maternal history and sonographic measurement of cervical length. UOG 27(4), 362–367 (2006)
19.
go back to reference Tsiartas, P., et al.: Prediction of spontaneous preterm delivery in women with threatened preterm labour: a prospective cohort study of multiple proteins in maternal serum. BJOG 119(7), 866–873 (2012)CrossRef Tsiartas, P., et al.: Prediction of spontaneous preterm delivery in women with threatened preterm labour: a prospective cohort study of multiple proteins in maternal serum. BJOG 119(7), 866–873 (2012)CrossRef
20.
go back to reference Van Baaren, G.J., et al.: Risk factors for preterm delivery: do they add to fetal fibronectin testing and cervical length measurement in the prediction of preterm delivery in symptomatic women? Eur. J. Obstet. Gynecol. Reprod. Biol. 192, 79–85 (2015)CrossRef Van Baaren, G.J., et al.: Risk factors for preterm delivery: do they add to fetal fibronectin testing and cervical length measurement in the prediction of preterm delivery in symptomatic women? Eur. J. Obstet. Gynecol. Reprod. Biol. 192, 79–85 (2015)CrossRef
21.
go back to reference Vandewiele, G., et al.: A decision support system to follow up and diagnose primary headache patients using semantically enriched data. BMC Med. Inform. Decis. Mak. 18(1), 98 (2018)CrossRef Vandewiele, G., et al.: A decision support system to follow up and diagnose primary headache patients using semantically enriched data. BMC Med. Inform. Decis. Mak. 18(1), 98 (2018)CrossRef
22.
go back to reference Vovsha, I., et al.: Predicting preterm birth is not elusive: machine learning paves the way to individual wellness. In: 2014 AAAI Symposia (2014) Vovsha, I., et al.: Predicting preterm birth is not elusive: machine learning paves the way to individual wellness. In: 2014 AAAI Symposia (2014)
23.
go back to reference Watson, H., et al.: Quipp app: a safe alternative to a treat-all strategy for threatened preterm labor. UOG 50(3), 342–346 (2017) Watson, H., et al.: Quipp app: a safe alternative to a treat-all strategy for threatened preterm labor. UOG 50(3), 342–346 (2017)
Metadata
Title
Time-to-Birth Prediction Models and the Influence of Expert Opinions
Authors
Gilles Vandewiele
Isabelle Dehaene
Olivier Janssens
Femke Ongenae
Femke De Backere
Filip De Turck
Kristien Roelens
Sofie Van Hoecke
Thomas Demeester
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-21642-9_36

Premium Partner