Evidence map›Paper›PMID 32546488›Full record

Observational studyBMJ open2020

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

Takuro Endo, Toru Yoshida, Tomohiro Shinozaki, Takako Motohashi, Hsiang-Chin Hsu, Shunsuke Fukuda, Jumpei Tsukuda, Takaki Naito, Kenichiro Morisawa, Nobuhiko Shimozawa and 2 more

Erratum issuedAbstract readObservational Study
In one paragraph

Observational study in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
  4. Article
  5. Observational
  6. Review
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Takuro EndoDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.ORCID 0000-0003-0020-6642
Toru YoshidaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Tomohiro ShinozakiDepartment of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, Katsushika-ku, Tokyo, Japan.ORCID 0000-0003-3395-9691
Takako MotohashiDepartment of Preventive Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Hsiang-Chin HsuEmergency Medicine, National Cheng Kung University Hospital, Tainan, Taiwan.ORCID 0000-0002-4350-6701
Shunsuke FukudaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.ORCID 0000-0003-2023-013X
Jumpei TsukudaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Takaki NaitoDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Kenichiro MorisawaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Nobuhiko ShimozawaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Yasuhiko TairaDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Shigeki FujitaniDepartment of Emergency and Critical Care Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan shigekifujitani@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe National Early Warning Score (NEWS) was originally developed to assess hospitalised patients in the UK. We examined whether the NEWS could be applied to patients transported by ambulance in Japan.

designThis retrospective study assessed patients and calculated the NEWS from paramedic records. Emergency department (ED) disposition data were categorised into the following groups: discharged from the ED, admitted to the ward, admitted to the intensive care unit (ICU) or died in the ED. The predictive performance of NEWS for patient disposition was assessed using receiver operating characteristic curve analysis. Patient dispositions were compared among NEWS-based categories after adjusting for age, sex and presence of traumatic injury.

settingA tertiary hospital in Japan.

participantsOverall, 2847 patients transported by ambulance between April 2017 and March 2018 were included.

resultsThe mean (±SD) NEWS differed significantly among patients discharged from the ED (n=1330, 3.7±2.9), admitted to the ward (n=1263, 60.3±3.8), admitted to the ICU (n=232, 9.4±4.0) and died in the ED (n=22, 110.7±2.9) (p<0.001). The prehospital NEWS C-statistics (95% CI) for admission to the ward, admission to the ICU or death in the ED; admission to the ICU or death in the ED; and death in the ED were 0.73 (0.72-0.75), 0.81 (0.78-0.83) and 0.90 (0.87-0.93), respectively. After adjusting for age, sex and trauma, the OR (95% CI) of admission to the ICU or death in the ED for the high-risk (NEWS ≥7) and medium-risk (NEWS 5-6) categories was 13.8 (8.9-21.6) and 4.2 (2.5-7.1), respectively.

conclusionThe findings from this Japanese tertiary hospital setting showed that prehospital NEWS could be used to identify patients at a risk of adverse outcomes. NEWS stratification was strongly correlated with patient disposition.

Indexed as

Early Warning ScoreAdolescentAdultAgedAged, 80 and overEmergency Medical ServicesEmergency Service, HospitalFemaleHumansJapanMaleMiddle AgedRetrospective StudiesTertiary Care Centersambulanceearly warning scoresprehospital

Identifiers

PMID32546488
PMCPMC7299041

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.