{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T19:58:12Z","timestamp":1792180692102,"version":"4.4.0"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T00:00:00Z","timestamp":1706572800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T00:00:00Z","timestamp":1706572800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Beijing Municipal Natural Science Foundation","award":["7202168"],"award-info":[{"award-number":["7202168"]}]},{"name":"Beijing Municipal Natural Science Foundation","award":["7202168"],"award-info":[{"award-number":["7202168"]}]},{"name":"Artificial Intelligence and Information Technology Application Fund of Fuwai Hospital, Chinese Academy of Medical Sciences","award":["2022-AI01"],"award-info":[{"award-number":["2022-AI01"]}]},{"name":"Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences","award":["2021-I2M-C&T-B-032"],"award-info":[{"award-number":["2021-I2M-C&T-B-032"]}]},{"name":"Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences","award":["2020-I2M-C&T-B-055"],"award-info":[{"award-number":["2020-I2M-C&T-B-055"]}]},{"name":"Double First-Class Discipline Construction Fund of Peking Union Medical College and Chinese Academy of Medical Sciences","award":["2019E-XK04-02"],"award-info":[{"award-number":["2019E-XK04-02"]}]},{"name":"Double First-Class Discipline Construction Fund of Peking Union Medical College and Chinese Academy of Medical Sciences","award":["2019E-XK04-02"],"award-info":[{"award-number":["2019E-XK04-02"]}]},{"name":"the Capital's Funds for Health Improvement and Research","award":["2020-2-4033"],"award-info":[{"award-number":["2020-2-4033"]}]},{"name":"National High Level Hospital Clinical Research Funding","award":["2022-GSP-GG-35"],"award-info":[{"award-number":["2022-GSP-GG-35"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Thrombosis J"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Identifying venous thromboembolism (VTE) is challenging for patients with cardiovascular diseases due to similar clinical presentation. Most hospital-acquired VTE events are preventable, whereas the implementation of VTE prophylaxis in clinical practice is far from sufficient. There is a lack of hospital-acquired VTE prediction models tailored specifically designed for patients with cardiovascular diseases. We aimed to develop a nomogram predicting hospital-acquired VTE specifically for patients with cardiovascular diseases.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Material and methods<\/jats:title>\n                <jats:p>Consecutive patients with cardiovascular diseases admitted to internal medicine of Fuwai hospital between September 2020 and August 2021 were included. Univariable and multivariable logistic regression were applied to identify risk factors of hospital-acquired VTE. A nomogram was constructed according to multivariable logistic regression, and internally validated by bootstrapping.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>A total of 27,235 patients were included. During a median hospitalization of four days, 154 (0.57%) patients developed hospital-acquired VTE. Multivariable logistic regression identified that female sex, age, infection, pulmonary hypertension, obstructive sleep apnea, acute coronary syndrome, cardiomyopathy, heart failure, immobility, central venous catheter, intra-aortic balloon pump and anticoagulation were independently associated with hospital-acquired VTE. The nomogram was constructed with high accuracy in both the training set and validation (concordance index 0.865 in the training set, and 0.864 in validation), which was further confirmed in calibration. Compared to Padua model, the Fuwai model demonstrated significantly better discrimination ability (area under curve 0.865 vs. 0.786, net reclassification index 0.052, 95% confidence interval 0.012\u20130.091, <jats:italic>P<\/jats:italic>\u2009=\u20090.009; integrated discrimination index 0.020, 95% confidence interval 0.001\u20130.039, <jats:italic>P<\/jats:italic>\u2009=\u20090.051).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>The incidence of hospital-acquired VTE in patients with cardiovascular diseases is relatively low. The nomogram exhibits high accuracy in predicting hospital-acquired VTE in patients with cardiovascular diseases.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12959-024-00584-w","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T09:02:59Z","timestamp":1706605379000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Nomogram for hospital-acquired venous thromboembolism among patients with cardiovascular diseases"],"prefix":"10.1186","volume":"22","author":[{"given":"Qin","family":"Luo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihui","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhihong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weixian","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,30]]},"reference":[{"issue":"1","key":"584_CR1","doi-asserted-by":"publisher","first-page":"406","DOI":"10.1186\/s13054-023-04683-4","volume":"27","author":"C Guan","year":"2023","unstructured":"Guan C, Ma F, Chang S, Zhang J. 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