Evidence mapPaperPMID 41814218Full record

ArticleBMC medical imaging2026

Nomogram based on quantitative lung CT features to identify cardiovascular disease in chronic obstructive pulmonary disease and predict prognosis.

Xiaoqing Lin, Qianxi Jin, Taohu Zhou, Xiuxiu Zhou, Yu Guan, Xin'ang Jiang, Yi Xia, Jiong Ni, Fangyi Xu, Hongjie Hu and 3 more

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Article in BMC medical imaging, 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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5 · Who and what money

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13 authors.

Xiaoqing Lin *Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Qianxi Jin *Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Taohu Zhou *Department of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Xiuxiu ZhouDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Yu GuanDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Xin'ang JiangDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Yi XiaDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Jiong NiDepartment of Radiology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China.
Fangyi XuDepartment of Radiology, Sir Run Run Shaw Hospital, No. 3 Qingchun East Road, Zhejiang, 310018, China.
Hongjie HuDepartment of Radiology, Sir Run Run Shaw Hospital, No. 3 Qingchun East Road, Zhejiang, 310018, China.
Shiyuan LiuDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China.
Rozemarijn VliegenthartDepartment of Radiology, University Medical Center Groningen, No. 9712 CP, Groningen, 9613, The Netherlands.
Li FanDepartment of Radiology, Second Affiliated Hospital of Naval Medical University, No. 415 Fengyang Road, Shanghai, 200003, China. fanli0930@163.com.

Funding

Excellent Health Sector Program of Shanghai Municipal Health Commission 20254Z0003National Key R&D Program of China 2022YFC2010002, 2022YFC2010000 and 2022YFC2010005National Natural Science Foundation of China 82430065; 82171926the Medical Imaging Database Construction Program of National Health Commission YXFSC2022JJSJ002
6 · The paper itself

Abstract

objectivesTo explore the performance of a CT-derived lung nomogram for identifying cardiovascular disease (CVD) among individuals with chronic obstructive pulmonary disease (COPD) and assessing the relationship with COPD prognosis.

methodsThis retrospective analysis enrolled hospitalized COPD patients between September 2015 and April 2023, with clinical data and visually assessed coronary artery calcium scores (CACS) collected for all participants. A quantitative model was constructed by extracting features from lung CT images and employing the least absolute shrinkage and selection operator algorithm for feature selection. The quantitative features and clinical factors were merged to formulate a nomogram. Area under the ROC curve (AUC) and decision curve analysis were used to study the ability of the nomogram to identify prevalent CVD. In Kaplan-Meier analysis, the predictive value of the nomogram for COPD re-hospitalization and all-cause mortality as endpoints was studied.

resultsOf 643 COPD patients (mean age, 68 years ± 10[SD]; 110 female), 159 had a history of CVD. The derived nomogram had better ability to identify CVD (AUC: 0.87; 95%CI 0.78, 0.94) than the clinical factors alone (AUC: 0.75; 95%CI 0.63, 0.86) and visual CACS (AUC: 0.68; 95%CI 0.56, 0.79) in internal validation, and achieved good performance in external validation with highest AUC (0.77; 95%CI 0.71, 0.84). The nomogram demonstrated a strong association with events (P < 0.001).

conclusionA nomogram based on quantitative CT features and clinical factors could effectively identify CVD in COPD patients, with bette discriminatory capacity than visual CACS or clinical factors alone. The nomogram also showed association with COPD re-hospitalization and all-cause mortality.

trial registrationIn accordance with the Declaration of Helsinki, this retrospective study was approved (Ethical Approval: Second Affiliated Hospital of Naval Medical University Ethics Committee, 2022SL068, December 6, 2022; Trial Registration: Chinese Clinical Trial Registry, ChiCTR2300069929, March 29, 2023), with a waiver for individual patient consent requirements.

Indexed as

Cardiovascular DiseasesLungNomogramsPulmonary Disease, Chronic ObstructiveTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRetrospective Studies

Identifiers

PMID41814218
PMCPMC13094078

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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 Socratic graph.