{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T13:16:21Z","timestamp":1758287781471,"version":"3.44.0"},"reference-count":29,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T00:00:00Z","timestamp":1758153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Surg."],"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To develop a perioperative lower-extremity deep vein thrombosis (DVT) risk prediction model for spinal fracture surgery patients using logistic regression, supporting clinical prevention strategies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Clinical data from 249 patients undergoing spinal fracture surgery (July 2019\u2013October 2024) were retrospectively analyzed. Participants were divided into a model group (<jats:italic>n<\/jats:italic>\u2009=\u2009166) and a validation group (<jats:italic>n<\/jats:italic>\u2009=\u200983) in a 2:1 ratio. Univariate and multivariate logistic regression identified independent risk factors for perioperative DVT, and a predictive model was established. Model fit was evaluated using the Hosmer-Lemeshow test, and predictive performance was assessed via receiver operating characteristic (ROC) curve analysis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Independent risk factors included perioperative blood transfusion, elevated C-reactive protein, D-dimer &amp;gt;500\u2005\u03bcg\/L, hypertension, age \u226560 years, and prolonged bed rest. The model [<jats:italic>P<\/jats:italic>\u2009=\u20091\/(1\u2009+\u2009e^\u2212Z)] demonstrated a good fit (Hosmer-Lemeshow <jats:italic>\u03c7<\/jats:italic><jats:sup>2<\/jats:sup>\u2009=\u200912.139, <jats:italic>P<\/jats:italic>\u2009=\u20090.807). ROC analysis showed AUC values of 0.75 (95% CI: 0.80\u20130.92) for the model group and 0.81 (95% CI: 0.64\u20130.98) for the validation group, indicating robust predictive performance.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The identified risk factors are critical predictors of perioperative DVT in spinal fracture patients. The proposed model exhibits strong clinical utility for early risk stratification and intervention guidance.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fsurg.2025.1597101","type":"journal-article","created":{"date-parts":[[2025,9,18]],"date-time":"2025-09-18T08:59:07Z","timestamp":1758185947000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A clinical risk prediction model for perioperative lower extremity DVT in patients undergoing spinal fracture 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