Evidence map›Paper›PMID 40817389›Full record

ArticleJournal of cachexia, sarcopenia and muscle2025

The Predictive Power of the Cystatin C-Creatinine Score in Assessing Frailty.

Li Deng, Xin Zheng, Yue Chen, Chenan Liu, Jinyu Shi, Zhaoting Bu, Xiaoyue Liu, Hong Zhao, Shuqun Li, Bing Yin and 2 more

Abstract read
In one paragraph

Article in Journal of cachexia, sarcopenia and muscle, 2025. 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
–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

3 citing papers in PubMed.

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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.

Li DengDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xin ZhengDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Yue ChenDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Chenan LiuDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Jinyu ShiDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Zhaoting BuDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Xiaoyue LiuDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Hong ZhaoDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Shuqun LiDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Bing YinDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Siyu XingDepartment of Biology, Faculty of Science, The University of Hong Kong, Hong Kong, China.
Hanping ShiDepartment of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-4514-8693

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
Laboratory for Clinical Medicine, Capital Medical University 2023-SYJCLC01National Key Research and Development Program 2022YFC2009600National Key Research and Development Program 2022YFC2009601National Multidisciplinary Cooperative Diagnosis and Treatment Capacity Project for Major Diseases: Comprehensive Treatment and Management of Critically Ill Elderly Inpatients 2019.YLFWNIA NIH HHS U01AG009740
6 · The paper itself

Abstract

backgroundAs the global population ages, identifying reliable biomarkers to predict frailty and mortality is critical for early intervention. This study aims to construct a valuable biomarker and evaluate its predictive performance in assessing frailty and all-cause mortality.

methodsData from 3613 participants in the Health and Retirement Study (HRS) were used to construct the nomogram and main analysis, whereas data from the National Health and Nutrition Examination Survey were used to validate the robustness of the model. LASSO regression identified key biomarkers, and a nomogram was used to construct the score. The frailty index (FI) and all-cause mortality were used as the outcomes, and the score's predictive ability was evaluated using ROC curves, C-index and decision curve analysis. Subgroup analyses were conducted to assess the score's consistency across age, sex and clinical conditions.

resultsSixteen haematological markers were selected through LASSO regression. The nomogram demonstrated that a scoring model based on cystatin C and creatinine can achieve optimal predictive performance. The Cystatin C-Creatinine Score demonstrated strong predictive power for frailty (AUC = 0.687) and all-cause mortality (AUC = 0.733). Logistic regression analysis showed a significant association between higher Cystatin C-Creatinine Scores and increased frailty risk, with participants in the high-risk group having an OR of 1.48 (95% CI: 1.35-1.62, p < 0.001) compared to the low-risk group. Cox proportional hazards models also indicated that higher scores were associated with increased mortality risk (HR = 3.34, 95% CI: 1.75-6.38, p < 0.001 for the high-risk group). In the validation set, the AUC values of the Cystatin C-Creatinine Score for predicting frailty and all-cause mortality reached 0.701 and 0.713, respectively.

conclusionOur findings support the use of the Cystatin C-Creatinine Score as a practical and effective tool for identifying individuals at higher risk of frailty and mortality.

Indexed as

CreatinineCystatin CFrailtyAgedAged, 80 and overBiomarkersFemaleHumansMaleMiddle AgedNomogramsPredictive Value of TestsPrognosisROC CurveBiomarkersCreatinineCystatin Cageingcreatininecystatin Cfrailtymortality

Identifiers

PMID40817389
PMCPMC12356705

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.