Evidence map›Paper›PMID 37545080›Full record

ArticleSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2023

[Relationship Between Frailty and Poor Prognosis in Older Trauma Patients in the Emergency Department: A Prospective Cohort Study].

Jing Yang, Jing Gao, Xinyu Chen, Dingxi Bai, Chenxi Wu

Abstract readEnglish Abstract
In one paragraph

Article in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2023. 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
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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

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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.

Jing YangSchool of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Jing GaoSchool of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Xinyu ChenSchool of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Dingxi BaiSchool of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
Chenxi WuSchool of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the relationship between frailty and adverse outcomes in older trauma patients in the emergency department. Methods: A prospective cohort study was conducted. Older trauma patients admitted to the emergency department of three tertiary-care hospitals in Chengdu between January 2021 and August 2021 were enrolled. The patients were divided into a frailty group and a non-frailty group according to their assessment results for Trauma-Specific Frailty Index (TSFI). The end points, including falls, readmission, and deaths, were documented during the 6-month follow-up. Cox risk regression model was used to analyze the relationship between frailty and adverse outcomes in older trauma patients in the emergency department. Results: A total of 375 older trauma patients in the emergency department were enrolled, including 131 in the frailty group and 244 in the non-frailty group. After 6 months of follow-up, the incidences of falls, readmission and deaths in older trauma patients in the emergency department were 18.93%, 14.40%, and 7.73%, respectively. The incidences of falls (28.24% vs. 13.93%, Conclusion: Frailty is a risk factor for falls and readmissions in older trauma patients in the emergency department and the association between frailty and the risk of deaths in older trauma patients in the emergency department needs to be validated by further studies.

Indexed as

FrailtyAgedEmergency Service, HospitalGeriatric AssessmentHospitalizationHumansPrognosisProspective StudiesEmergency departmentFrailtyOlder adultsPrognosisProspective cohort studyTrauma

Identifiers

PMID37545080
PMCPMC10442631

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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.