Evidence map›Paper›PMID 40652176›Full record

ArticleBMC neurology2025

Construction and verification of a risk prediction model for patients with kinesophobia after cerebral hemorrhage surgery.

Yan Huang, Ya-Ting Huang, Jie Yuan, Zhi-Yu WuYang, Xue Zhang, Chuan-Qing Yu

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Article in BMC neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yan HuangDepartment of Neurosurgery, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China.
Ya-Ting HuangDepartment of Interventional Catheterization Laboratory, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China.
Jie YuanDepartment of Neurological Intensive Care Unit, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China.
Zhi-Yu WuYangDepartment of Neurological Intensive Care Unit, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China.
Xue ZhangDepartment of Neurological Intensive Care Unit, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China.
Chuan-Qing YuDepartment of Neurology, The First Affiliated Hospital of Anhui University of Science and Technology(First People's Hospital of Huainan), Huainan, Anhui, 232007, China. yuchuanqing2022@sina.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo establish a risk prediction model of kinesophobia in patients after cerebral hemorrhage surgery and verify its effect.

methodsA total of 218 patients after cerebral hemorrhage surgery were selected, and the differences in clinical data between kinesophobia patients and non-kinesophobia patients were analyzed. Using 20 indexes as independent variables, the characteristic variables were screened by LASSO regression, and then multivariate Logistic regression analysis was carried out. Based on the results, the nomogram prediction model was constructed, and the model was verified from the aspects of clinical applicability, discrimination, and calibration.

resultsSignificant differences were found in age, electronic health literacy score, depression score, NIHSS score, VAS pain score, intraoperative blood loss, and anxiety score between patients with phobia and non-phobia (P < 0.05). 12 characteristic variables were selected by LASSO regression. Multivariate Logistic regression analysis showed that age, NIHSS score, VAS pain score and depression score were independent risk factors for the occurrence of kinesophobia after cerebral hemorrhage surgery (OR > 1 and P < 0.05), and electronic health literacy score was an independent protective factor (OR < 1 and P < 0.05). Based on age, NIHSS score, VAS pain score, e-health literacy score, and depression score, a nomogram prediction model was constructed. The DCA curve shows that the model has the highest clinical net benefit when the threshold probability is between 0.14 and 0.99, indicating good clinical applicability. The area under the ROC curve (AUC) is 0.836(95% CI: 0.782-0.890), which indicates good discrimination. Spiegelhalter's z test and the calibration curve show that the calibration degree is good, and the C statistic after Bootstrap self-sampling internal verification is 0.820 (95% CI: 0.772-0.877), indicating that the prediction is robust.

conclusionThe nomogram prediction model of the risk of kinesophobia after cerebral hemorrhage based on multivariate regression analysis has a good prediction effect, which can provide reference for the clinical prevention of kinesophobia after cerebral hemorrhage.

Indexed as

Cerebral HemorrhagePhobic DisordersPostoperative ComplicationsAdultAgedFemaleHumansKinesiophobiaMaleMiddle AgedNomogramsRisk AssessmentRisk FactorsCerebral hemorrhageKinesophobiaNomogramPrediction modelRisk factors

Identifiers

PMID40652176
PMCPMC12255136

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