Evidence map›Paper›PMID 38393457›Full record

ArticleEuropean geriatric medicine2024

The diagnostic performance of Cr/CysC for sarcopenia and its predictive value on clinical outcomes in hospitalized older patients: a prospective cohort study.

Xiangping Tu, Taiping Lin, Li Huang, Tianjiao Tang, Dongmei Xie, Langli Gao, Tingting Jiang, Jirong Yue

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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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Xiangping Tu *Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Taiping Lin *Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Li Huang *Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Tianjiao TangDepartment of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Dongmei XieDepartment of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Langli GaoDepartment of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Tingting JiangDepartment of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China.
Jirong YueDepartment of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu City, Sichuan Province, China. yuejirong11@hotmail.com.ORCID 0000-0002-3730-779X
Sichuan University · CN

Funding

1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University ZYJC21005Chinese National Science & Technology Pillar Program 2020YFC2009004Health Research of Cadres in Sichuan province SCR2022-101National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University Z20191012Sichuan Science and Technology Program 2022YFG0205Sichuan Science and Technology Program 2022YFS0295
6 · The paper itself

Abstract

purposeThe utilization of the creatinine-to-cystatin C ratio (Cr/CysC) represents an innovative method for predicting sarcopenia. Our objectives encompassed the evaluation of sarcopenia diagnostic accuracy for Cr/CysC, SARC-F, SARC-CalF, the combination of Cr/CysC and SARC-CalF, and the Ishii score, as well as an exploration of the predictive value of Cr/CysC concerning clinical outcomes within hospitalized older individuals.

methodsWe employed receiver operating characteristic (ROC) curves and calculated areas under the curves (AUCs) to assess the diagnostic accuracy. Furthermore, we applied univariate and multivariate Cox proportional-hazard models to calculate the hazard ratio (HR) and 95% confidence interval (CI) of risk factors affecting prognosis.

resultsOur study included 312 participants, comprising 167 men and 145 women, with an average age of 71 years. Among males, the AUCs for Cr/CysC, SARC-F, SARC-CalF, the combination of Cr/CysC and SARC-CalF, and the Ishii score were 0.717 [95% CI 0.642-0.784], 0.669 (95% CI 0.592-0.739), 0.845 (95% CI 0.781-0.896), 0.882 (95% CI 0.823-0.926), and 0.938 (95% CI 0.890-0.969), respectively. In females, the AUCs for Cr/CysC, SARC-F, SARC-CalF, the combination of Cr/CysC and SARC-CalF, and the Ishii score were 0.706 (95% CI 0.625-0.779), 0.631 (95% CI 0.547-0.710), 0.763 (95% CI 0.686-0.830), 0.789 (95% CI 0.714-0.853), and 0.898 (95% CI 0.837-0.942), respectively. After adjusting for age, sex, physical exercise, smoking, drinking, hypertension, coronary heart disease (CHD), chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), and cancer, sarcopenia identified by Cr/CysC (adjusted HR = 2.176, 95% CI 1.062-4.460, P = 0.034) was independently associated with poor overall survival in hospitalized older patients.

conclusionsCr/CysC has satisfactory diagnostic accuracy for sarcopenia diagnosis and predictive value for poor outcomes in hospitalized older patients. The combination of Cr/CysC and SARC-CalF may provide a more accurate screening for sarcopenia and the Ishii score may be the most accurate clinical method for detecting sarcopenia.

Indexed as

SarcopeniaAgedCystatin CFemaleHumansLegMaleProspective StudiesROC CurveCystatin CAdverse outcomesCreatinineCystatin CDiagnosisSarcopenia

Identifiers

PMID38393457
OpenAlexW4392109740

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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.