| Literature DB >> 28561250 |
Andrew Levinson1, Jezid Miranda2, Jose Antonio Rojas-Suarez3.
Abstract
The 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.Entities:
Mesh:
Year: 2017 PMID: 28561250 DOI: 10.1055/s-0037-1602244
Source DB: PubMed Journal: Semin Respir Crit Care Med ISSN: 1069-3424 Impact factor: 3.119