• Andrew Levinson, Jezid Miranda, and Jose Antonio Rojas-Suarez.
• Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island.
• Semin Respir Crit Care Med. 2017 Apr 1; 38 (2): 191-200.

AbstractThe use of predictive models has been proposed as a potential tool to reduce maternal morbidity and mortality, by aiding in the timely identification of potential high-risk patients. Prognostic models in critical care have been used to characterize the severity of illness of specific diseases. Physiological changes in pregnancy may result in general critical illness prediction models overestimating mortality in obstetric patients. Models that specifically reflect the unique characteristics of obstetric patients may have better prognostic value. Recently developed tools have focused on identifying at-risk patients before they require intensive care unit (ICU) admission to target early interventions and prevent acute clinical decompensation. The aim of the newest scoring systems, specifically designed for groups of obstetric patients receiving non-ICU care, is to reduce maternal morbidity and mortality by identifying early high-risk patients and initiating prompt effective medical responses.

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