Literature DB >> 29444899

Comparison of Glasgow Admission Prediction Score and Amb Score in predicting need for inpatient care.

Allan Cameron1, Dominic Jones2, Eilidh Logan3, Colin A O'Keeffe2, Suzanne M Mason2, David J Lowe3,4.   

Abstract

AIM: We compared the abilities of two established clinical scores to predict emergency department (ED) disposition: the Glasgow Admission Prediction Score (GAPS) and the Ambulatory Score (Ambs).
METHODS: The scores were compared in a prospective, multicentre cohort study. We recruited consecutive patients attending ED triage at two UK sites: Northern General Hospital in Sheffield and Glasgow Royal Infirmary, between February and May 2016. Each had a GAPS and Ambs calculated at the time of triage, with the triage nurses and treating clinicians blinded to the scores. Patients were followed up to hospital discharge. The ability of the scores to discriminate discharge from ED and from hospital at 12 and 48 hours after arrival was compared using the area under the curve (AUC) of their receiving-operator characteristics (ROC).
RESULTS: 1424 triage attendances were suitable for analysis during the study period, of which 567 (39.8%) were admitted. The AUC for predicting admission was significantly higher for GAPS at 0.807 (95% CI 0.785 to 0.830), compared with 0.743 (95% CI 0.717 to 0.769) for Ambs, P<0.00001. Similar results were seen when comparing ability to predict hospital stay of >12 hour and >48 hour. GAPS was also more accurate as a binary test, correctly predicting 1057 outcomes compared with 1004 for Ambs (74.2vs70.5%, P=0.012).
CONCLUSION: The GAPS is a significantly better predictor of need for hospital admission than Ambs in an unselected ED population. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  admission avoidance; effectiveness; emergency care systems, emergency departments; research, operational; triage

Mesh:

Year:  2018        PMID: 29444899     DOI: 10.1136/emermed-2017-207246

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


  5 in total

1.  Possible futures of acute medical care in the NHS: a multispecialty approach.

Authors:  John Dean; Mike Jones; Philip Dyer; Chris Moulton; Vicky Price; Daniel Lasserson
Journal:  Future Healthc J       Date:  2022-07

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.  Predicting hospital admission at emergency department triage using machine learning.

Authors:  Woo Suk Hong; Adrian Daniel Haimovich; R Andrew Taylor
Journal:  PLoS One       Date:  2018-07-20       Impact factor: 3.240

4.  Multicentre, prospective observational study of the correlation between the Glasgow Admission Prediction Score and adverse outcomes.

Authors:  Dominic Jones; Allan Cameron; David J Lowe; Suzanne M Mason; Colin A O'Keeffe; Eilidh Logan
Journal:  BMJ Open       Date:  2019-08-10       Impact factor: 2.692

5.  Real-time prediction of patient disposition and the impact of reporter confidence on mid-level triage accuracies: an observational study in Israel.

Authors:  Daniel Trotzky; Noaa Shopen; Jonathan Mosery; Neta Negri Galam; Yizhaq Mimran; Daniel Edward Fordham; Shiran Avisar; Aya Cohen; Malka Katz Shalhav; Gal Pachys
Journal:  BMJ Open       Date:  2021-12-09       Impact factor: 2.692

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.