Evidence map›Paper›PMID 39190227›Full record

ArticleEuropean geriatric medicine2024

Frailty detection with routine blood tests using data from the english longitudinal study of ageing (ELSA).

Lingxiao He, Jinzhu Yang, Shujing Lin, Kanglin Shi, Ya Fang

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Article in European geriatric medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

5 citing papers in PubMed.

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4 · The record

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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.

Lingxiao HeCenter for Ageing and Health Research, School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China.
Jinzhu YangCenter for Ageing and Health Research, School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China.
Shujing LinCenter for Ageing and Health Research, School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China.
Kanglin ShiCenter for Ageing and Health Research, School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China.
Ya FangCenter for Ageing and Health Research, School of Public Health, Xiamen University, Xiang'an South Road, Xiamen, 361102, China. fangya@xmu.edu.cn.ORCID 0000-0002-9895-3234

Funding

Fundamental Research Funds for the Central Universities 20720220061
6 · The paper itself

Abstract

purposeFrailty is a rising global health issue in ageing society. Easily accessible and sensitive tools are needed for frailty monitoring while routine blood factors can be potential candidates.

methodsData from 1907 participants (aged 60 years or above) were collected from the 4th to 9th wave of the English longitudinal study of ageing. 14 blood factors obtained from blood tests were included in the analysis. A 52-item frailty index (FI) was calculated for frailty evaluation. Logistic regression and Cox proportional hazards analysis were used to explore the relationships between baseline blood factors and the incidence of frailty over time respectively. All analyses were controlled for age and sex.

resultsThe mean age of participants was 67.3 years and 47.2% of them were male. Our study identified that 8 blood factors (mean corpuscular haemoglobin, HDL, triglyceride, ferritin, hsCRP, dehydroepiandrosterone, haemoglobin, and WBC) involved in inflammatory, nutritional and metabolic processes were associated with frailty. The combined model with these 8 blood factors had an AUC of 0.758 at cross-sectional level. In the Cox proportional hazards analysis, higher triglyceride (HR: 1.30, 95%CI: 1.07 ~ 1.59), WBC (HR: 1.16, 95%CI: 1.05 ~ 1.28), and lower HDL (HR: 0.58, 95%CI: 0.38 ~ 0.90) at baseline were linked to greater risk of developing frailty within 10 years. Compared to adults without abnormal blood factors at baseline, the hazard ratios of participants with two or more abnormal blood factors were almost twofold higher in developing frailty over time.

conclusionsRoutine blood factors, particularly triglyceride, HDL and WBC, could be used for frailty screening in clinical practice and estimate the development of frailty over time.

Indexed as

FrailtyGeriatric AssessmentAgedAged, 80 and overAgingCross-Sectional StudiesEnglandFemaleFrail ElderlyHematologic TestsHumansLogistic ModelsLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsTriglyceridesAgeingBlood factorsFrailty detectionRoutine

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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.