Evidence map›Paper›PMID 38596204›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2024

Multidimensional Frailty Instruments Can Predict Acute Exacerbations Within One Year in Patients with Stable Chronic Obstructive Pulmonary Disease: A Retrospective Longitudinal Study.

Lujie Wei, Pingyang Li, Xiaofeng Liu, Yuxia Wang, Zhengping Tang, Hang Zhao, Lu Yu, Kaixiu Li, Jianping Li, Min Du and 8 more

Open access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

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

18 authors at 3 institutions in 1 country.

Lujie Wei *Geriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.ORCID 0009-0006-8053-5567
Pingyang Li *Medical College, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Xiaofeng LiuGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Yuxia WangGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Zhengping TangGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Hang ZhaoGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Lu YuDepartment of Respiratory and Critical Care Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Kaixiu LiGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Jianping LiGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Min DuDepartment of Respiratory and Critical Care Medicine, Nanbu County People's Hospital, Nanbu, Sichuan, People's Republic of China.
Xinzhu ChenMedical College, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Xin ZhengMedical College, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Yixiong ZhengCollege of Medicine and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Yao LuoMedical College, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.
Jing ChenCollege of Medicine and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, People's Republic of China.
Xiamin JiangClinical College, North Sichuan Medical College, Nanchong, Sichuan, People's Republic of China.
Xiaobing ChenDepartment of Respiratory and Critical Care Medicine, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, People's Republic of China.
Huaicong LongGeriatric Intensive Care Unit, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, People's Republic of China.ORCID 0000-0002-1718-426X
University of Electronic Science and Technology of China · CNChengdu University of Traditional Chinese Medicine · CNNorth Sichuan Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is closely associated with frailty, and prevention of acute exacerbations is important for disease management. Moreover, COPD patients with frailty experience a higher risk of acute exacerbations. However, the frailty instruments that can better predict acute exacerbations remain unclear. Purpose: (1) To explore the factors influencing frailty and acute exacerbations in stable COPD patients, and (2) quantify the ability of multidimensional frailty instruments to predict acute exacerbations within 1 year. Patients and methods: In this retrospective longitudinal study, stable COPD patients were recruited from the outpatient department of Sichuan Provincial People's Hospital from July 2022 to June 2023. COPD patients reviewed their frailty one year ago and their acute exacerbations within one year using face-to-face interviews with a self-developed frailty questionnaire. Frailty status was assessed using the Frailty Index (FI), frailty questionnaire (FRAIL), and Clinical Frailty Scale (CFS). One-way logistic regression was used to explore the factors influencing frailty and acute exacerbations. Multivariate logistic regression was used to establish a prediction model for acute exacerbations, and the accuracy of the three frailty instruments was compared by measuring the area under the receiver operating characteristic curve (AUC). Results: A total of 120 individuals were included. Frailty incidence estimates using FI, FRAIL, and CFS were 23.3%, 11.7%, and 15.8%, respectively. The three frailty instruments showed consistency in COPD assessments ( Conclusion: Multidimensional frailty assessments could improve the identification of COPD patients at high risk of acute exacerbations and facilitate targeted interventions to reduce acute exacerbations in these patients.

Indexed as

FrailtyPulmonary Disease, Chronic ObstructiveHumansLongitudinal StudiesRetrospective StudiesRisk Factorsacute exacerbationschronic obstructive pulmonary diseasefrailty

Identifiers

PMID38596204
PMCPMC11001541
OpenAlexW4393947812

What OpenQuestion holds

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LicenceCC BY-NC
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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.