Evidence map›Paper›PMID 34154560›Full record

SynthesisBMC geriatrics2021

Effectiveness of comprehensive geriatric assessment intervention on quality of life, caregiver burden and length of hospital stay: a systematic review and meta-analysis of randomised controlled trials.

Zhongyi Chen, Zhaosheng Ding, Caixia Chen, Yangfan Sun, Yuyu Jiang, Fenglan Liu, Shanshan Wang

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 5 pooled it
5.2field-weighted citation impact, top 4% of its field
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

42 citing papers in PubMed, 5 syntheses or guidelines pooled it, 67 citations in OpenAlex.

  1. Pooled it
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  16. Treatment decision-making for patients with cancer aged 75 and older: perspectives from focus group interviews with patients, family caregivers, and healthcare providers.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  17. Observational
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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

7 authors at 3 institutions in 1 country.

Zhongyi ChenResearch Office of Chronic Disease Management and Rehabilitation, Wuxi School of Medicine, Jiangnan University, No. 1800 Lihu Avenue, Wuxi, Jiangsu Province, China.
Zhaosheng DingRongjun Hospital of Jiangsu Province, Wuxi, China.
Caixia ChenWuxi Tongren Rehabilitation Hospital, Wuxi, China.
Yangfan SunWuxi Tongren Rehabilitation Hospital, Wuxi, China.
Yuyu JiangResearch Office of Chronic Disease Management and Rehabilitation, Wuxi School of Medicine, Jiangnan University, No. 1800 Lihu Avenue, Wuxi, Jiangsu Province, China. doctoryuyu@jiangnan.edu.cn.
Fenglan LiuMedical School, Liaocheng University, Liaocheng, China.
Shanshan WangResearch Office of Chronic Disease Management and Rehabilitation, Wuxi School of Medicine, Jiangnan University, No. 1800 Lihu Avenue, Wuxi, Jiangsu Province, China.
Jiangnan University · CNTongren Hospital · CNLiaocheng University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComprehensive geriatric assessment (CGA) interventions can improve functional ability and reduce mortality in older adults, but the effectiveness of CGA intervention on the quality of life, caregiver burden, and length of hospital stay remains unclear. The study aimed to determine the effectiveness of CGA intervention on the quality of life, length of hospital stay, and caregiver burden in older adults by conducting meta-analyses of randomised controlled trials (RCTs).

methodsA literature search in PubMed, Embase, and Cochrane Library was conducted for papers published before February 29, 2020, based on inclusion criteria. Standardised mean difference (SMD) or mean difference (MD) with 95% confidence intervals (CIs) was calculated using the random-effects model. Subgroup analyses, sensitivity analyses, and publication bias analyses were also conducted.

resultsA total of 28 RCTs were included. Overall, the intervention components common in different CGA intervention models were interdisciplinary assessments and team meetings. Meta-analyses showed that CGA interventions improved the quality of life of older people (SMD = 0.12; 95% CI = 0.03 to 0.21; P = 0.009) compared to usual care, and subgroup analyses showed that CGA interventions improved the quality of life only in participants' age > 80 years and at follow-up ≤3 months. The change value of quality of life in the CGA intervention group was better than that in the usual care group on six dimensions of the 36-Item Short-Form Health Survey questionnaire (SF-36). Also, compared to usual care, the CGA intervention reduced the caregiver burden (SMD = - 0.56; 95% CI = - 0.97 to - 0.15, P = 0.007), but had no significant effect on the length of hospital stay.

conclusionsCGA intervention was effective in improving the quality of life and reducing caregiver burden, but did not affect the length of hospital stay. It is recommended that future studies apply the SF-36 to evaluate the impact of CGA interventions on the quality of life and provide supportive strategies for caregivers as an essential part of the CGA intervention, to find additional benefits of CGA interventions.

Indexed as

Geriatric AssessmentQuality of LifeAgedAged, 80 and overCaregiver BurdenCaregiversHumansLength of StayRandomized Controlled Trials as TopicCaregiver burdenComprehensive geriatric assessment interventionLength of hospital stayMeta-analysisQuality of life

Identifiers

PMID34154560
PMCPMC8218512
OpenAlexW3173949063

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.