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Predictors of readmission for postpartum preeclampsia

  • Rodney A. McLaren
  • , Melissa Magenta
  • , Laura Gilroy
  • , Maria Gabriela Duarte
  • , Sujatha Narayanamoorthy
  • , Jeremy Weedon
  • , Howard Minkoff
  • Maimonides Medical Center
  • School of Public Health

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Objective: To develop a predictive model for re-admission for postpartum preeclampsia (PPEC). Methods: A case-control study; cases were patients re-admitted for PPEC; controls were not re-admitted. Mixed linear modelling was used to develop a predictive model on the training set, then validated on the validation set. Results: Two-hundred-sixty-nine patients were readmitted, and matched to 538 controls. A risk calculator was developed and yielded a sensitivity and specificity for readmission of 80.9% and 53.5%, respectively. Conclusion: A predictive model using age, race, discharge blood pressures, and preeclampsia was able to predict re-admission for PPEC with a high level of sensitivity.

Original languageEnglish
Pages (from-to)254-260
Number of pages7
JournalHypertension in Pregnancy
Volume40
Issue number3
DOIs
StatePublished - 2021

Keywords

  • Hypertensive disease in pregnancy
  • postpartum preeclampsia
  • prediction model
  • risk factors

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