Evidence map›Paper›PMID 31908435›Full record

ArticleClinical interventions in aging2019

Identification of Frailty and Its Risk Factors in Elderly Hospitalized Patients from Different Wards: A Cross-Sectional Study in China.

Yao-Dan Liang, Yao-Nan Zhang, Yan-Ming Li, Yu-Hui Chen, Jing-Yong Xu, Ming Liu, Jing Li, Zhao Ma, Lin-Lin Qiao, Zi Wang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Clinical interventions in aging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 6% 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

49 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

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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

12 authors at 2 institutions in 1 country.

Yao-Dan LiangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.
Yao-Nan ZhangDepartment of Orthopedics.
Yan-Ming LiDepartment of Pulmonary and Critical Care Medicine.
Yu-Hui ChenDepartment of Neurology.
Jing-Yong XuDepartment of General Surgery.ORCID 0000-0003-4942-2557
Ming LiuDepartment of Urology.
Jing LiDepartment of Geriatrics.ORCID 0000-0003-4136-6204
Zhao MaDepartment of Rehabilitation.
Lin-Lin QiaoDepartment of Traditional Chinese Medicine.
Zi WangDepartment of Cardiac Surgery, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.ORCID 0000-0002-7361-1406
Jie-Fu YangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.
Hua WangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.ORCID 0000-0002-1643-4108
Beijing Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo survey the difference of frailty prevalence in elderly inpatients amongdifferent wards; to compare the diagnostic performance of five frailty measurements (Clinical Frailty Scale [CFS], FRAIL, Fried, Edmonton, Frailty Index [FI]) in identifying frailty; and to explore the risk factors of frailty in elderly inpatients. PARTICIPANTS AND

methodsThis was a cross-sectional study including 1000 inpatients (mean age 75.2±6.7 years, 51.5% male; 542, 229, and 229 patients from cardiology, non-surgical, and surgical wards, respectively) in a tertiary hospital from September 2018 to February 2019. We applied the combined index to integrate the five frailty measurements mentioned above as the gold standard of frailty diagnosis. Multivariate logistic regression models were used to determine the independent risk factors of frailty.

resultsFrailty prevalence was 32.3% (Fried), 36.2% (CFS), 19.2% (FRAIL), 25.2% (Edmonton), 35.1% (FI) in all patients. The frailty was more common in non-surgical wards, regardless of the frailty assessment tools used (non-surgical wards: 27.5% to 51.5%; cardiology ward: 14.9% to 29.3%; surgical wards: 18.8% to 41.9%). CFS≥5 showed a sensitivity of 94.1% and a specificity of 85.2% for all patients. FI≥0.25 showed a sensitivity of 94.8% and a specificity of 87.0% for all patients. Age [odds ratio (OR) = 1.089, P<0.001], education level (OR = 0.782, P=0.001), heart rate (OR = 1.025, P<0.001), albumin (OR = 0.911, P=0.002), log D-dimer (OR = 2.940, P<0.001), ≥5 comorbidities (OR = 2.164, P=0.002), and ≥5 medications (OR = 2.819, P<0.001) were independently associated with frailty in all participants.

conclusionFrailty is common among elderly inpatients, especially in non-surgical wards. CFS is a preferred screening tool and FI may be an optimal assessment tool. Old age, low educational level, fast heart rate, low albumin, high D-dimer, ≥5 comorbidities, and polypharmacy are independent risk factors of frailty in elderly hospitalized patients.

Indexed as

InpatientsAgedChinaComorbidityCross-Sectional StudiesEmergency Service, HospitalFemaleFrail ElderlyFrailtyGeriatric AssessmentHumansMalePrevalenceRisk FactorsSurveys and QuestionnairesChinaelderly hospitalized patientsfrailtyrisk factorwards

Identifiers

PMID31908435
PMCPMC6927496
OpenAlexW2996624608

What OpenQuestion holds

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LicenceCC BY-NC
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.