Evidence map›Paper›PMID 41867139›Full record

Observational studyInquiry : a journal of medical care organization, provision and financing

Predicting Adverse Outcomes in Older Adults with 72-Hour Emergency Department Returns: A Retrospective Cohort Study Developing the Rec-FLASH Score.

Chung-Ting Chen, Yu-Hsiang Meng, Hsin-Hua Yu, Chorng-Kuang How, Yu-Chi Tung

Abstract readObservational Study
In one paragraph

Observational study in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Chung-Ting ChenEmergency Department, Taipei Veterans General Hospital, Taiwan.ORCID 0000-0003-4747-2710
Yu-Hsiang MengEmergency Department, Taipei Veterans General Hospital, Taiwan.
Hsin-Hua YuEmergency Department, Taipei Veterans General Hospital, Taiwan.
Chorng-Kuang HowEmergency Department, Taipei Veterans General Hospital, Taiwan.
Yu-Chi TungInstitute of Health Policy and Management, College of Public Health, National Taiwan University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Older patients are heavy users of emergency department (ED) resources and are at high risk for short-term ED visits, often leading to adverse outcomes. We aim to elucidate the characteristics of older patients who undergo 72-h ED returns, and develop a prediction model for unfavorable outcomes to facilitate clinical practices. This retrospective observational study enrolled older patients who shortly returned to the ED of a tertiary hospital within 72 h between 2019 and 2020. The study population was divided into development and validation datasets. The primary outcome was high-risk ED returns, defined as intensive care unit admission or in-hospital mortality after ED returns. Multivariable logistic regression was performed to identify predictors of high-risk returns, and a prediction model was built accordingly. A total of 1118 encounters were enrolled in our development dataset, with a mean age of 79.4 ± 9.5 years. Through multivariable analysis, independent predictors of high-risk ED returns were identified. A simple prediction model (ReC-FLASH) was developed, demonstrating a C-statistic of 0.862 (95% CI: 0.822-0.903,

Indexed as

Emergency Service, HospitalPatient ReadmissionAgedAged, 80 and overEmergency Room VisitsFemaleHospital MortalityHumansIntensive Care UnitsLogistic ModelsMaleRetrospective StudiesRisk AssessmentRisk FactorsTriageemergency department returnemergency department revisitolder patientprediction modelrisk stratificationscoring system

Identifiers

PMID41867139
PMCPMC13010041

What OpenQuestion holds

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Registered trials

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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.