Literature DB >> 30171976

Can early warning scores identify deteriorating patients in pre-hospital settings? A systematic review.

Rita Patel1, Manjula D Nugawela2, Hannah B Edwards2, Alison Richards2, Hein Le Roux3, Anne Pullyblank4, Penny Whiting2.   

Abstract

OBJECTIVE: To evaluate the effectiveness and predictive accuracy of early warning scores (EWS) to predict deteriorating patients in pre-hospital settings.
METHODS: Systematic review. Seven databases searched to August 2017. Study quality was assessed using QUADAS-2. A narrative synthesis is presented. ELIGIBILITY: Studies that evaluated EWS predictive accuracy or that compared outcomes in populations that did or did not use EWS, in any pre-hospital setting were eligible for inclusion. EWS were included if they aggregated three or more physiological parameters.
RESULTS: Seventeen studies (157,878 participants) of predictive accuracy were included (16 in ambulance service and 1 in nursing home). AUCs ranged from 0.50 (CI not reported) to 0.89 (95%CI 0.82, 0.96). AUCs were generally higher (>0.80) for prediction of mortality within short time frames or for combination outcomes that included mortality and ICU admission. Few patients with low scores died at any time point. Patients with high scores were at risk of deterioration. Results were less clear for intermediate thresholds (≥4 or 5). Five studies were judged at low or unclear risk of bias, all others were judged at high risk of bias.
CONCLUSIONS: Very low and high EWS are able to discriminate between patients who are not likely and those who are likely to deteriorate in the pre-hospital setting. No study compared outcomes pre- and post-implementation of EWS so there is no evidence on whether patient outcomes differ between pre-hospital settings that do and do not use EWS. Further studies are required to address this question and to evaluate EWS in pre-hospital settings.
Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Critical care; Deteriorating patients; Early warning score; Pre hospital setting; Track and trigger system

Mesh:

Year:  2018        PMID: 30171976     DOI: 10.1016/j.resuscitation.2018.08.028

Source DB:  PubMed          Journal:  Resuscitation        ISSN: 0300-9572            Impact factor:   5.262


  28 in total

1.  Predictive value of the New Zealand Early Warning Score for early mortality in low-acuity patients discharged at scene by paramedics: an observational study.

Authors:  Verity Frances Todd; Melanie Moylan; Graham Howie; Andy Swain; Aroha Brett; Tony Smith; Bridget Dicker
Journal:  BMJ Open       Date:  2022-07-14       Impact factor: 3.006

2.  Accuracy of prehospital clinicians' perceived prognostication of long-term survival in critically ill patients: a nationwide retrospective cohort study on helicopter emergency service patients.

Authors:  Anssi Heino; Johannes Björkman; Miretta Tommila; Timo Iirola; Helena Jäntti; Jouni Nurmi
Journal:  BMJ Open       Date:  2022-05-17       Impact factor: 3.006

3.  Distributions of the National Early Warning Score (NEWS) across a healthcare system following a large-scale roll-out.

Authors:  Lauren J Scott; Niamh M Redmond; Joanna Garrett; Penny Whiting; Kate Northstone; Anne Pullyblank
Journal:  Emerg Med J       Date:  2019-03-06       Impact factor: 2.740

4.  A Multicenter Observational Prospective Cohort Study of Association of the Prehospital National Early Warning Score 2 and Hospital Triage with Early Mortality.

Authors:  Francisco Martín-Rodríguez; Raúl López-Izquierdo; Carlos Del Pozo Vegas; Juan F Delgado-Benito; Carmen Del Pozo Pérez; Virginia Carbajosa Rodríguez; Agustín Mayo Iscar; José Luis Martín-Conty; Carlos Escudero Cuadrillero; Miguel A Castro-Villamor
Journal:  Emerg Med Int       Date:  2019-07-01       Impact factor: 1.112

5.  Random forest machine learning method outperforms prehospital National Early Warning Score for predicting one-day mortality: A retrospective study.

Authors:  Jussi Pirneskoski; Joonas Tamminen; Antti Kallonen; Jouni Nurmi; Markku Kuisma; Klaus T Olkkola; Sanna Hoppu
Journal:  Resusc Plus       Date:  2020-12-05

6.  Using National Early Warning Score (NEWS) 2 to help manage medical emergencies in the dental practice.

Authors:  Phil Jevon; Shaam Shamsi
Journal:  Br Dent J       Date:  2020-09       Impact factor: 2.727

7.  Efficacy of prehospital National Early Warning Score to predict outpatient disposition at an emergency department of a Japanese tertiary hospital: a retrospective study.

Authors:  Takuro Endo; Toru Yoshida; Tomohiro Shinozaki; Takako Motohashi; Hsiang-Chin Hsu; Shunsuke Fukuda; Jumpei Tsukuda; Takaki Naito; Kenichiro Morisawa; Nobuhiko Shimozawa; Yasuhiko Taira; Shigeki Fujitani
Journal:  BMJ Open       Date:  2020-06-15       Impact factor: 2.692

8.  Telemonitoring for Patients With COVID-19: Recommendations for Design and Implementation.

Authors:  Anna V Silven; Annelieke H J Petrus; María Villalobos-Quesada; Ebru Dirikgil; Carlijn R Oerlemans; Cyril P Landstra; Hileen Boosman; Hendrikus J A van Os; Marco H Blanker; Roderick W Treskes; Tobias N Bonten; Niels H Chavannes; Douwe E Atsma; Y K Onno Teng
Journal:  J Med Internet Res       Date:  2020-09-02       Impact factor: 5.428

9.  Using the National Early Warning Score (NEWS) outside acute hospital settings: a qualitative study of staff experiences in the West of England.

Authors:  Emer Brangan; Jonathan Banks; Heather Brant; Anne Pullyblank; Hein Le Roux; Sabi Redwood
Journal:  BMJ Open       Date:  2018-10-27       Impact factor: 2.692

10.  Machine learning model predicts short-term mortality among prehospital patients: A prospective development study from Finland.

Authors:  Joonas Tamminen; Antti Kallonen; Sanna Hoppu; Jari Kalliomäki
Journal:  Resusc Plus       Date:  2021-02-05
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