Literature DB >> 28501815

Can the prehospital National Early Warning Score identify patients most at risk from subsequent deterioration?

Joanna Shaw1, Rachael T Fothergill1,2, Sophie Clark1, Fionna Moore1.   

Abstract

INTRODUCTION: The National Early Warning Score (NEWS) aids the early recognition of those at risk of becoming critically ill. NEWS has been recommended for use by ambulance services, but very little work has been undertaken to date to determine its suitability. This paper examines whether a prehospital NEWS derived from ambulance service clinical observations is associated with the hospital ED disposition.
METHODS: Prehospital NEWS was retrospectively calculated from the ambulance service clinical records of 287 patients who were treated by the ambulance service and transported to hospital. In this cohort study, derived NEWS scores were compared with ED disposition data and patients were categorised into the following groups depending on their outcome: discharged from ED, admitted to a ward, admitted to intensive therapy unit (ITU) or died.
RESULTS: Prehospital NEWS-based ambulance service clinical observations were significantly associated with discharge disposition groups (p<0.001), with scores escalating in line with increasing severity of outcome. Patients who died or were admitted to ITU had higher scores than those admitted to a ward or discharged from ED (mean NEWS 7.2 and 7.5 vs 2.6 and 1.7, respectively), and in turn those who were admitted to a ward had higher pre-hospital NEWS than those who were discharged (2.6 vs 1.7).
CONCLUSION: Our findings suggest that the NEWS could successfully be used by ambulance services to identify patients most at risk from subsequent deterioration. The implementation of this early warning system has the potential to support ambulance clinician decision making, providing an additional tool to identify and appropriately escalate care for acutely unwell patients. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  ambulances; early warning score; emergency medical services; national early warning score

Mesh:

Year:  2017        PMID: 28501815     DOI: 10.1136/emermed-2016-206115

Source DB:  PubMed          Journal:  Emerg Med J        ISSN: 1472-0205            Impact factor:   2.740


  19 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

Review 2.  How do we identify acute medical admissions that are suitable for same day emergency care?

Authors:  Catherine Atkin; Bridget Riley; Elizabeth Sapey
Journal:  Clin Med (Lond)       Date:  2022-01-19       Impact factor: 5.410

3.  The prehospital quick SOFA score is associated with in-hospital mortality in noninfected patients: A retrospective, cross-sectional study.

Authors:  Osamu Kitahara; Kei Nishiyama; Bunsei Yamamoto; Shigeaki Inoue; Sadaki Inokuchi
Journal:  PLoS One       Date:  2018-08-16       Impact factor: 3.240

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.  National Early Warning Score for predicting intensive care unit admission among elderly patients with influenza infections in the emergency department: an effective disposition tool during the influenza season.

Authors:  Te-Hao Wang; Jing-Cheng Jheng; Yen-Ting Tseng; Li-Fu Chen; Jui-Yuan Chung
Journal:  BMJ Open       Date:  2021-06-11       Impact factor: 2.692

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.  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

9.  Predicting mortality in patients with suspected sepsis at the Emergency Department; A retrospective cohort study comparing qSOFA, SIRS and National Early Warning Score.

Authors:  Anniek Brink; Jelmer Alsma; Rob Johannes Carel Gerardus Verdonschot; Pleunie Petronella Marie Rood; Robert Zietse; Hester Floor Lingsma; Stephanie Catherine Elisabeth Schuit
Journal:  PLoS One       Date:  2019-01-25       Impact factor: 3.240

10.  Predicting need for intensive care unit admission in adult emphysematous pyelonephritis patients at emergency departments: comparison of five scoring systems.

Authors:  Xiao-Han Yap; Chip-Jin Ng; Kuang-Hung Hsu; Cheng-Yu Chien; Zhong Ning Leonard Goh; Chih-Huang Li; Yi-Ming Weng; Ming-Shun Hsieh; Hsien-Yi Chen; Joanna Chen-Yeen Seak; Chen-Ken Seak; Chen-June Seak
Journal:  Sci Rep       Date:  2019-11-12       Impact factor: 4.379

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