Evidence map›Paper›PMID 41641052›Full record

ArticleFrontiers in public health2025

The problem of frailty caused by acute infection and future health management strategies to improve frailty.

Guihua Li, Yue Zhao, Wenhui Gu, Qianqian Wang, Xinyi Lu, Xinlei Miao

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. 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

6 authors.

Guihua Li *Health Management Center, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Yue Zhao *Health Management Center, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Wenhui GuHealth Management Center, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Qianqian WangHealth Management Center, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.
Xinyi LuPeking University Third Hospital, Beijing, China.
Xinlei MiaoHealth Management Center, The Second Hospital of Dalian Medical University, Dalian, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We aimed to analyze changes in frailty associated with long-COVID, while providing effective health management measures to improve frailty. Methods: We conducted a 4-month follow-up cohort study involving 2,471 participants to analyze changes in body frailty after the prevalence of COVID-19 in China. We performed interrupted time series analysis to estimate the impact of acute infection on the changes in frailty. The time-dependent COX model was considered to assess the association between frailty status and infection, and sensitivity analysis was performed to verify the stability of the results. In addition, we established a traditional Cox model to analyze the relationship between healthy behaviors and infections, aiming to improve health management and reduce frailty. Results: There were significantly elevated trend changes in the frailty index compared to the prepandemic period in the total population (+0.029[0.016, 0.041], Conclusion: In this study, it was found that the population generally became more frail after the pandemic, and frailty increases the risk of acute reinfection. Therefore, it is necessary to carry out health management strategies to improve frailty.

Indexed as

COVID-19FrailtyAgedChinaFemaleFollow-Up StudiesFrail ElderlyHumansInterrupted Time Series AnalysisMalePandemicsPost-Acute COVID-19 SyndromeProportional Hazards ModelsSARS-CoV-2COVID-19 pandemicfrailtyhealth improvementhealth managementinterrupted time series

Identifiers

PMID41641052
PMCPMC12864481

What OpenQuestion holds

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LicenceCC BY
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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.