Evidence map›Paper›PMID 42175455›Full record

ArticleMedicine2026

Development and validation of a predictive model for postoperative deep vein thrombosis in elderly patients undergoing hip fracture surgery: A retrospective study.

Zheng Xu, Jie Liu, Weiting Wu, Xing Liu, Xuli Yang

Abstract readValidation Study
In one paragraph

Article in Medicine, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zheng XuSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Jie LiuScientific Research Administration Office, Jiangxi Provincial Center for Disease Control and Prevention, Nanchang, Jiangxi, China.ORCID 0000-0002-1856-8564
Weiting WuSchool of Public Health, Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Xing LiuDepartment of Medical Equipment, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Xuli YangDepartment of Medical Equipment, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.ORCID 0000-0002-4825-7425

Funding

science and technology program project of Jiangxi provincial Health commission No.202310212ã€No.202311111 and No.202610289
6 · The paper itself

Abstract

This study aimed to systematically examine the incidence of deep vein thrombosis (DVT) after hip surgery and identify its key determinants. The findings are intended to inform the refinement of postoperative risk assessment tools, the optimization of prevention strategies, and the development of personalized nursing protocols. This retrospective cohort study consecutively enrolled elderly patients aged ≥ 60 years who underwent hip fracture surgery at the First Affiliated Hospital of Nanchang University between January and September 2024 and had complete medical records. The primary outcome was postoperative DVT confirmed by imaging. Predictive factors were identified through univariate and multivariate logistic regression analyses, and a nomogram prediction model was constructed. A total of 710 patients were included, with a postoperative DVT incidence of 12.11% (86/710). Significant differences were observed between the DVT group and the non-DVT group in terms of 24-hour post-admission assessment and venous thromboembolism scores (P < .05).Multivariate logistic regression revealed that a specialized risk score within 24 hours of admission (OR = 4.326, 95% CI: 2.00-9.35, P < .001), elevated preoperative C-reactive protein levels (OR = 1.018, 95% CI: 1.01-1.03, P < .05), perioperative blood transfusion (OR = 0.212, 95% CI: 0.10-0.43, P < .001), Postoperative graded elevation in D-dimer levels (OR = 2.691, 95% CI: 1.08-6.37, P < .05), and preexisting DVT risk scores (OR = 1.711, 95% CI: 1.35-2.17, P < .001) were identified as independent predictors of postoperative DVT in elderly patients undergoing hip replacement surgery. The constructed nomogram model demonstrated excellent predictive performance (concordance index: 0.873). In elderly patients receiving hip replacement surgery, 5 independent predictors of postoperative DVT were identified. These factors were integrated into a bar-chart-based risk assessment tool, which quantifies individualized thrombotic risk through a visual scoring system. This model provides clinicians with a practical method for early risk stratification, supporting targeted prevention strategies and postoperative monitoring in routine care.

Indexed as

Hip FracturesPostoperative ComplicationsVenous ThrombosisAgedAged, 80 and overC-Reactive ProteinFemaleHumansIncidenceLogistic ModelsMaleMiddle AgedNomogramsRetrospective StudiesRisk AssessmentRisk FactorsC-Reactive Proteindeep vein thrombosiship arthroplastynomogram model

Identifiers

PMID42175455
PMCPMC13201063

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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.