Cargando…
The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis
BACKGROUND: It is unclear which Early Warning System (EWS) score best predicts in-hospital deterioration of patients when applied in the Emergency Department (ED) or prehospital setting. METHODS: This systematic review (SR) and meta-analysis assessed the predictive abilities of five commonly used EW...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929648/ https://www.ncbi.nlm.nih.gov/pubmed/35298560 http://dx.doi.org/10.1371/journal.pone.0265559 |
_version_ | 1784670905811599360 |
---|---|
author | Guan, Gigi Lee, Crystal Man Ying Begg, Stephen Crombie, Angela Mnatzaganian, George |
author_facet | Guan, Gigi Lee, Crystal Man Ying Begg, Stephen Crombie, Angela Mnatzaganian, George |
author_sort | Guan, Gigi |
collection | PubMed |
description | BACKGROUND: It is unclear which Early Warning System (EWS) score best predicts in-hospital deterioration of patients when applied in the Emergency Department (ED) or prehospital setting. METHODS: This systematic review (SR) and meta-analysis assessed the predictive abilities of five commonly used EWS scores (National Early Warning Score (NEWS) and its updated version NEWS2, Modified Early Warning Score (MEWS), Rapid Acute Physiological Score (RAPS), and Cardiac Arrest Risk Triage (CART)). Outcomes of interest included admission to intensive care unit (ICU), and 3-to-30-day mortality following hospital admission. Using DerSimonian and Laird random-effects models, pooled estimates were calculated according to the EWS score cut-off points, outcomes, and study setting. Risk of bias was evaluated using the Newcastle-Ottawa scale. Meta-regressions investigated between-study heterogeneity. Funnel plots tested for publication bias. The SR is registered in PROSPERO (CRD42020191254). RESULTS: Overall, 11,565 articles were identified, of which 20 were included. In the ED setting, MEWS, and NEWS at cut-off points of 3, 4, or 6 had similar pooled diagnostic odds ratios (DOR) to predict 30-day mortality, ranging from 4.05 (95% Confidence Interval (CI) 2.35–6.99) to 6.48 (95% CI 1.83–22.89), p = 0.757. MEWS at a cut-off point ≥3 had a similar DOR when predicting ICU admission (5.54 (95% CI 2.02–15.21)). MEWS ≥5 and NEWS ≥7 had DORs of 3.05 (95% CI 2.00–4.65) and 4.74 (95% CI 4.08–5.50), respectively, when predicting 30-day mortality in patients presenting with sepsis in the ED. In the prehospital setting, the EWS scores significantly predicted 3-day mortality but failed to predict 30-day mortality. CONCLUSION: EWS scores’ predictability of clinical deterioration is improved when the score is applied to patients treated in the hospital setting. However, the high thresholds used and the failure of the scores to predict 30-day mortality make them less suited for use in the prehospital setting. |
format | Online Article Text |
id | pubmed-8929648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89296482022-03-18 The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis Guan, Gigi Lee, Crystal Man Ying Begg, Stephen Crombie, Angela Mnatzaganian, George PLoS One Research Article BACKGROUND: It is unclear which Early Warning System (EWS) score best predicts in-hospital deterioration of patients when applied in the Emergency Department (ED) or prehospital setting. METHODS: This systematic review (SR) and meta-analysis assessed the predictive abilities of five commonly used EWS scores (National Early Warning Score (NEWS) and its updated version NEWS2, Modified Early Warning Score (MEWS), Rapid Acute Physiological Score (RAPS), and Cardiac Arrest Risk Triage (CART)). Outcomes of interest included admission to intensive care unit (ICU), and 3-to-30-day mortality following hospital admission. Using DerSimonian and Laird random-effects models, pooled estimates were calculated according to the EWS score cut-off points, outcomes, and study setting. Risk of bias was evaluated using the Newcastle-Ottawa scale. Meta-regressions investigated between-study heterogeneity. Funnel plots tested for publication bias. The SR is registered in PROSPERO (CRD42020191254). RESULTS: Overall, 11,565 articles were identified, of which 20 were included. In the ED setting, MEWS, and NEWS at cut-off points of 3, 4, or 6 had similar pooled diagnostic odds ratios (DOR) to predict 30-day mortality, ranging from 4.05 (95% Confidence Interval (CI) 2.35–6.99) to 6.48 (95% CI 1.83–22.89), p = 0.757. MEWS at a cut-off point ≥3 had a similar DOR when predicting ICU admission (5.54 (95% CI 2.02–15.21)). MEWS ≥5 and NEWS ≥7 had DORs of 3.05 (95% CI 2.00–4.65) and 4.74 (95% CI 4.08–5.50), respectively, when predicting 30-day mortality in patients presenting with sepsis in the ED. In the prehospital setting, the EWS scores significantly predicted 3-day mortality but failed to predict 30-day mortality. CONCLUSION: EWS scores’ predictability of clinical deterioration is improved when the score is applied to patients treated in the hospital setting. However, the high thresholds used and the failure of the scores to predict 30-day mortality make them less suited for use in the prehospital setting. Public Library of Science 2022-03-17 /pmc/articles/PMC8929648/ /pubmed/35298560 http://dx.doi.org/10.1371/journal.pone.0265559 Text en © 2022 Guan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Guan, Gigi Lee, Crystal Man Ying Begg, Stephen Crombie, Angela Mnatzaganian, George The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title | The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title_full | The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title_fullStr | The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title_full_unstemmed | The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title_short | The use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: A systematic review and meta-analysis |
title_sort | use of early warning system scores in prehospital and emergency department settings to predict clinical deterioration: a systematic review and meta-analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929648/ https://www.ncbi.nlm.nih.gov/pubmed/35298560 http://dx.doi.org/10.1371/journal.pone.0265559 |
work_keys_str_mv | AT guangigi theuseofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT leecrystalmanying theuseofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT beggstephen theuseofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT crombieangela theuseofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT mnatzaganiangeorge theuseofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT guangigi useofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT leecrystalmanying useofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT beggstephen useofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT crombieangela useofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis AT mnatzaganiangeorge useofearlywarningsystemscoresinprehospitalandemergencydepartmentsettingstopredictclinicaldeteriorationasystematicreviewandmetaanalysis |