Evidence map›Paper›PMID 41982210›Full record

ArticleFrontiers in aging neuroscience2026

Development and validation of a nomogram for predicting the risk of shoulder-hand syndrome after ischemic stroke: a retrospective study.

Yuan Luo, Yujie Xie, Xin Zeng, Pan Huang, Yong Tang, Akira Miyamoto, Fan Li, Guomin Ding, Guoyin Pang, Bin Liang and 4 more

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In one paragraph

Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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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

14 authors.

Yuan Luo *Rehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Yujie Xie *Rehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Xin ZengRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Pan HuangThe School of Nursing of The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
Yong TangSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Akira MiyamotoFaculty of Rehabilitation, Nishikyushu University, Saitama, Japan.
Fan LiCollege of Artificial Intelligence (CUIT Shuangliu Industrial College), Chengdu University of Information Technology, Chengdu, China.
Guomin DingRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Guoyin PangRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Bin LiangRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Peng LiaoRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Huanhuan CaoRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Xin TangRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Chi ZhangRehabilitation Medicine Department, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to assess the relevant risk factors and construct a nomogram model to assist in the early identification of shoulder-hand syndrome (SHS) after ischemic stroke. Method: One thousand five hundred and thirty-nine ischemic stroke patients admitted to the First People's Hospital of Neijiang from September 2021 to August 2025 were selected as the research subjects. After exclusion, 1,211 patients were selected. These patients were divided into the training group ( Result: Multivariate Logistic regression analysis revealed that age, hypertension, alcohol drinking, muscle strength of the affected upper limb, NIHSS, albumin, and total cholesterol were independent risk factors for shoulder-hand syndrome after ischemic stroke. The nomogram model demonstrated reliable predictive efficacy, with an area under the curve (AUC value) of 0.891 (95% CI, 0.853-0.929). Both DCA and CIC confirmed that the nomogram model has strong clinical practical value. Conclusion: This study developed a novel predictive model for shoulder-hand syndrome after ischemic stroke, providing a valuable tool for the early identification of high-risk patients in clinical settings.

Indexed as

ischemic strokelogisticnomogramprediction modelshoulder-hand syndrome

Identifiers

PMID41982210
PMCPMC13071036

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.