Validating the Performance of the Modified Early Obstetric Warning System Multivariable Model to Predict Maternal Intensive Care Unit Admission.

Objectives: To evaluate the performance of the Modified Early Obstetric Warning System (MEOWS) to predict maternal ICU admission in an obstetric population.
Design: Case-control study.
Setting: Two maternity units in Vancouver, Canada, one with ICU facilities, between January 1, 2000, and December 31, 2011.
Patients: Pregnant or recently delivered (≤6 weeks) women admitted to the hospital for >24 hours. Three control patients were randomly selected per case and matched for year of admission.
Measurements and Main Results: Retrospective, observational, case-control validation study investigating the physiologic predictors of admission in the 24-hour period preceding either ICU admission >24 hours (cases) or following admission (control patients). Model performance was assessed based on sensitivity, specificity, and predictive values. Forty-six women were admitted to the ICU for >24 hours (0.51/1000 deliveries); the study included 138 randomly selected control patients. There were no maternal deaths in the cohort. MEOWS had high sensitivity (0.96) but low specificity (0.54) for ICU admission >24 hours, whereas ≥1 one red trigger maintained sensitivity (0.96) and improved specificity (0.73).
Conclusion: Altering MEOWS trigger parameters may improve the accuracy of MEOWS in predicting ICU admission. Formal modelling of a MEOWS scoring system is required to support evidence-based care.
(Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)