{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T09:50:17Z","timestamp":1776851417546,"version":"3.51.2"},"reference-count":37,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:00:00Z","timestamp":1776816000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Science and Technology Program Project of Enshi Tujia and Miao Autonomous Prefecture, Hubei Province","award":["E20240028"],"award-info":[{"award-number":["E20240028"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Patients undergoing surgery for traumatic spinal fractures are at high risk for postoperative venous thromboembolism (VTE), with deep vein thrombosis (DVT) incidence approaching 20% despite standard prophylaxis. This highlights the need for enhanced and specialized risk stratification. We aimed to develop and internally validate a preoperative prediction model for postoperative lower extremity DVT in this population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This retrospective cohort study analyzed data from 1,676 patients who underwent surgery for traumatic spinal fractures at a single center between January 2020 and March 2025. Postoperative DVT was diagnosed\n                      <jats:italic>via<\/jats:italic>\n                      ultrasonography. Predictors were identified from 29 candidate variables through univariate analysis, followed by stepwise multivariable logistic regression. Model performance was evaluated using discrimination (area under the receiver operating characteristic curve, AUC), calibration (calibration plot, Hosmer-Lemeshow test), and clinical utility (decision curve analysis, DCA). A nomogram was constructed for visualization.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The postoperative DVT incidence was 14.3% (239\/1,676). Six independent preoperative predictors were identified: prolonged bed rest &gt; 72 hours (adjusted odds ratio (aOR) = 5.208, 95% CI [3.319\u20138.171]), pre-existing lower extremity vascular disease (aOR = 2.938, 95% CI [1.641\u20135.258]), elevated D-dimer (aOR = 1.582 per mg\/L, 95% CI [1.448\u20131.729]), elevated fibrinogen (aOR = 1.434 per g\/L, 95% CI [1.138\u20131.807]), severe neurological impairment (American Spinal Injury Association (ASIA) Impairment Scale grade A\/B), and advanced age (aOR = 1.019 per year, 95% CI [1.003\u20131.035]). The model exhibited robust discrimination (AUC: 0.891 in the training set, 0.885 in the testing set), excellent calibration (Hosmer-Lemeshow\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0&gt;\u00a00.7), high sensitivity (90.5\u201391.2%), and moderate specificity (74.3\u201374.5%). DCA confirmed its clinical utility across a wide range of threshold probabilities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study developed and validated a novel preoperative nomogram for predicting postoperative DVT in patients undergoing surgery for traumatic spinal fractures. Incorporating six readily accessible variables, this tool enables individualized risk stratification and may inform targeted prophylactic strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.7717\/peerj.21184","type":"journal-article","created":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T08:53:41Z","timestamp":1776848021000},"page":"e21184","source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of a nomogram for predicting postoperative lower extremity deep vein thrombosis in patients with traumatic spinal fractures: a retrospective study"],"prefix":"10.7717","volume":"14","author":[{"given":"Guangxu","family":"Fu","sequence":"first","affiliation":[{"name":"Department of Orthopedic Surgery, The People\u2019s Hospital of Lichuan City, Enshi Tujia and Miao Autonomous Prefecture, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery, The People\u2019s Hospital of Lichuan City, Enshi Tujia and Miao Autonomous Prefecture, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dengwu","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, The People\u2019s Hospital of Lichuan City, Enshi Tujia and Miao Autonomous Prefecture, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, The People\u2019s Hospital of Lichuan City, Enshi Tujia and Miao Autonomous Prefecture, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyan","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery, The People\u2019s Hospital of Lichuan City, Enshi Tujia and Miao Autonomous Prefecture, 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