Evidence map›Paper›PMID 40640716›Full record

ArticleBMC geriatrics2025

A nomogram to predict sarcopenia in older adults: a multi-center study in rural China.

Xin Hu, Jielong Wu, Yihao Gu, Lina Zhang, Mengjie Zhang, Weinuo Mi, Xingjia Li, Yu Sun, Huiling Zou, Yan Wang and 3 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC geriatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Xin Hu *Center of Integrated Chinese and Western Medicine, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, No. 55 Zhenhai Road, Siming District, Xiamen, 361003, China.
Jielong Wu *Center of Integrated Chinese and Western Medicine, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, No. 55 Zhenhai Road, Siming District, Xiamen, 361003, China.
Yihao GuEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China.
Lina ZhangEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China.
Mengjie ZhangEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China.
Weinuo MiEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China.
Xingjia LiKey Laboratory of TCM Syndrome and Treatment of Yingbing (Thyroid Disease) of State Administration of Traditional Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing, China.
Yu SunDepartment of Endocrinology, The Affiliated Suqian Hospital of Xuzhou Medical University, Suqian, China.
Huiling ZouDepartment of Endocrinology, The Affiliated Suqian Hospital of Xuzhou Medical University, Suqian, China.
Yan WangDepartment of Geriatrics, The Affiliated Suqian Hospital of Xuzhou Medical University, Suqian, China.
Chao LiuEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China.
Shuyu YangCenter of Integrated Chinese and Western Medicine, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, No. 55 Zhenhai Road, Siming District, Xiamen, 361003, China. xmyangshuyu@xmu.edu.cn.
Shuhang XuEndocrine and Diabetes Center, The Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, No. 100 Cross Street, Hongshan Road, Qixia District, Nanjing, 210028, China. shuhangxu@163.com.

Funding

Geriatric Health Scientific Research Project of Jiangsu Province LK2021059Natural Science Foundation of China 82205050Open project of the National Traditional Chinese Medicine Clinical Research Base JD2022SZXZD05Suqian Key Research and Development Program S202110
6 · The paper itself

Abstract

backgroundSarcopenia is closely associated with activity limitations, falls and fractures, all serving as major causes of physiological deterioration and even mortality in older adults. The purpose of this study was to develop and validate a novel nomogram for predicting the risk of sarcopenia in Chinese older adults from rural areas.

methodsOverall, 611 older adults were enrolled from the Thyroid Diseases in Older Population (TOPS) study and randomly assigned to the training and validation datasets in a ratio of 8:2. Based on the risk factors for sarcopenia identified by stepwise multivariate logistic regression, a nomogram to predict sarcopenia in older adults was created. Its discrimination ability, calibration accuracy and clinical utility were assessed via the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), respectively. Additionally, a web-based nomogram was developed.

resultsA nomogram to predict sarcopenia in older adults was created by incorporating the following variables: age (years), sex, body mass index (BMI, kg/m2), free triiodothyronine (FT3), total cholesterol (TC), triglyceride (TG), and TG/HDL-C. The area under the curve (AUC) of the nomogram was 0.813 (95% CI 0.775–0.846) in the training dataset and 0.819 (95% CI 0.739–0.883) in the validation dataset. Both calibration curves and DCA verified high calibration accuracy and clinical utility of the nomogram.

conclusionsA nomogram is created based on routine laboratory values of blood testing, showing an outstanding ability to predict sarcopenia in older adults from rural areas in China accurately, specifically and cost-effectively.

Indexed as

NomogramsRural PopulationSarcopeniaAgedAged, 80 and overChinaFemaleHumansMalePredictive Value of TestsRisk FactorsBlood testingNomogramOlder adultsRisk predictionSarcopenia

Identifiers

PMID40640716
PMCPMC12243246

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.