Predictors of Maternal Mortality and Prognostic Models in Obstetric Patients.

Semin Respir Crit Care Med

Intensive Care in Obstetric Research Group (GRICIO), Department of Obstetrics and Gynecology, University of Cartagena, Cartagena, Colombia.

Published: April 2017

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.

Download full-text PDF

Source
http://dx.doi.org/10.1055/s-0037-1602244DOI Listing

Publication Analysis

Top Keywords

obstetric patients
16
prognostic models
8
reduce maternal
8
maternal morbidity
8
morbidity mortality
8
high-risk patients
8
patients
7
models
5
predictors maternal
4
mortality
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!