{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T04:57:51Z","timestamp":1783573071381,"version":"3.55.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T00:00:00Z","timestamp":1770163200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T00:00:00Z","timestamp":1772755200000},"content-version":"vor","delay-in-days":30,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["Grant No.82272204"],"award-info":[{"award-number":["Grant No.82272204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-026-03363-x","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T08:53:26Z","timestamp":1770195206000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy"],"prefix":"10.1186","volume":"26","author":[{"given":"Jinmei","family":"Wu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xianwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenglong","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baoxin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyuan","family":"Ruan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihua","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueyang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingye","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"issue":"1","key":"3363_CR1","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1038\/s41590-023-01660-5","volume":"25","author":"EJ Giamarellos-Bourboulis","year":"2024","unstructured":"Giamarellos-Bourboulis EJ, Aschenbrenner AC, Bauer M, et al. The pathophysiology of sepsis and precision-medicine-based immunotherapy. Nat Immunol. 2024;25(1):19\u201328.","journal-title":"Nat Immunol"},{"key":"3363_CR2","doi-asserted-by":"publisher","first-page":"1552","DOI":"10.1007\/s00134-020-06151-x","volume":"46","author":"C Fleischmann-Struzek","year":"2020","unstructured":"Fleischmann-Struzek C, Mellhammar L, Rose N, et al. Incidence and mortality of hospital-and ICU-treated sepsis: results from an updated and expanded systematic review and meta-analysis. Intensive Care Med. 2020;46:1552\u201362.","journal-title":"Intensive Care Med"},{"issue":"10219","key":"3363_CR3","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/S0140-6736(19)32989-7","volume":"395","author":"KE Rudd","year":"2020","unstructured":"Rudd KE, Johnson SC, Agesa KM, et al. Global, regional, and National sepsis incidence and mortality, 1990\u20132017: analysis for the global burden of disease study. Lancet. 2020;395(10219):200\u201311.","journal-title":"Lancet"},{"key":"3363_CR4","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1023\/B:THRO.0000014592.27892.11","volume":"16","author":"M Levi","year":"2003","unstructured":"Levi M, de Jonge E, van der Poll T. Sepsis and disseminated intravascular coagulation. J Thromb Thrombolysis. 2003;16:43\u20137.","journal-title":"J Thromb Thrombolysis"},{"issue":"5","key":"3363_CR5","doi-asserted-by":"publisher","first-page":"1238","DOI":"10.1097\/ALN.0000000000003122","volume":"132","author":"T Iba","year":"2020","unstructured":"Iba T, Levy JH. Sepsis-induced coagulopathy and disseminated intravascular coagulation. Anesthesiology. 2020;132(5):1238\u201345.","journal-title":"Anesthesiology"},{"issue":"1","key":"3363_CR6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s13613-022-01093-7","volume":"13","author":"T Schmoch","year":"2023","unstructured":"Schmoch T, M\u00f6hnle P, Weigand MA, et al. The prevalence of sepsis-induced coagulopathy in patients with sepsis\u2013a secondary analysis of two German multicenter randomized controlled trials. Ann Intensiv Care. 2023;13(1):3.","journal-title":"Ann Intensiv Care"},{"key":"3363_CR7","unstructured":"Williams B, Zou L, Pittet J-F, Chao W. Sepsis-Induced coagulopathy: a comprehensive narrative review of pathophysiology, clinical presentation, diagnosis, and management strategies. Anesth Analgesia. 2022;10:1213."},{"issue":"09","key":"3363_CR8","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1160\/TH07-02-0117","volume":"98","author":"S Bergmann","year":"2007","unstructured":"Bergmann S, Hammerschmidt S. Fibrinolysis and host response in bacterial infections. Thromb Haemost. 2007;98(09):512\u201320.","journal-title":"Thromb Haemost"},{"issue":"11","key":"3363_CR9","doi-asserted-by":"publisher","first-page":"1989","DOI":"10.1111\/jth.14578","volume":"17","author":"T Iba","year":"2019","unstructured":"Iba T, Levy JH, Warkentin TE, et al. Diagnosis and management of sepsis-induced coagulopathy and disseminated intravascular coagulation. J Thromb Haemost. 2019;17(11):1989\u201394.","journal-title":"J Thromb Haemost"},{"issue":"02","key":"3363_CR10","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1055\/s-0038-1676610","volume":"119","author":"K Yamakawa","year":"2019","unstructured":"Yamakawa K, Yoshimura J, Ito T, Hayakawa M, Hamasaki T, Fujimi S. External validation of the two newly proposed criteria for assessing coagulopathy in sepsis. Thromb Haemost. 2019;119(02):203\u201312.","journal-title":"Thromb Haemost"},{"issue":"2","key":"3363_CR11","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1007\/s12185-021-03152-4","volume":"114","author":"C Tanaka","year":"2021","unstructured":"Tanaka C, Tagami T, Kudo S, et al. Validation of sepsis-induced coagulopathy score in critically ill patients with septic shock: post hoc analysis of a nationwide multicenter observational study in Japan. Int J Hematol. 2021;114(2):164\u201371.","journal-title":"Int J Hematol"},{"issue":"17","key":"3363_CR12","doi-asserted-by":"publisher","first-page":"1775","DOI":"10.1001\/jama.2016.14799","volume":"316","author":"D Keh","year":"2016","unstructured":"Keh D, Trips E, Marx G, et al. Effect of hydrocortisone on development of shock among patients with severe sepsis: the HYPRESS randomized clinical trial. JAMA. 2016;316(17):1775\u201385.","journal-title":"JAMA"},{"issue":"9","key":"3363_CR13","doi-asserted-by":"publisher","first-page":"e017046","DOI":"10.1136\/bmjopen-2017-017046","volume":"7","author":"T Iba","year":"2017","unstructured":"Iba T, Di Nisio M, Levy JH, Kitamura N, Thachil J. New criteria for sepsis-induced coagulopathy (SIC) following the revised sepsis definition: a retrospective analysis of a nationwide survey. BMJ Open. 2017;7(9):e017046.","journal-title":"BMJ Open"},{"issue":"1","key":"3363_CR14","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.jtha.2022.10.022","volume":"21","author":"T Iba","year":"2023","unstructured":"Iba T, Levi M, Thachil J, Helms J, Scarlatescu E, Levy JH. Communication from the scientific and standardization committee of the international society on thrombosis and haemostasis on sepsis-induced coagulopathy in the management of sepsis. J Thromb Haemost. 2023;21(1):145\u201353.","journal-title":"J Thromb Haemost"},{"issue":"6","key":"3363_CR15","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1097\/MBC.0000000000000755","volume":"29","author":"R Ding","year":"2018","unstructured":"Ding R, Wang Z, Lin Y, Liu B, Zhang Z, Ma X. Comparison of a new criteria for sepsis-induced coagulopathy and international society on thrombosis and haemostasis disseminated intravascular coagulation score in critically ill patients with sepsis 3.0: a retrospective study. Blood Coagul Fibrinolysis. 2018;29(6):551\u20138.","journal-title":"Blood Coagul Fibrinolysis"},{"key":"3363_CR16","doi-asserted-by":"publisher","first-page":"661710","DOI":"10.3389\/fmed.2021.661710","volume":"8","author":"Z Lu","year":"2021","unstructured":"Lu Z, Zhang J, Hong J, et al. Development of a nomogram to predict 28-day mortality of patients with sepsis-induced coagulopathy: an analysis of the MIMIC-III database. Front Med. 2021;8:661710.","journal-title":"Front Med"},{"issue":"1","key":"3363_CR17","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1186\/s40001-023-01593-7","volume":"29","author":"S Zhou","year":"2024","unstructured":"Zhou S, Lu Z, Liu Y, et al. Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation. Eur J Med Res. 2024;29(1):14.","journal-title":"Eur J Med Res"},{"key":"3363_CR18","doi-asserted-by":"publisher","first-page":"847206","DOI":"10.3389\/fcvm.2022.847206","volume":"9","author":"Y Xu","year":"2022","unstructured":"Xu Y, Han D, Huang T, et al. Predicting ICU mortality in rheumatic heart disease: comparison of XGBoost and logistic regression. Front Cardiovasc Med. 2022;9:847206.","journal-title":"Front Cardiovasc Med"},{"issue":"1","key":"3363_CR19","doi-asserted-by":"publisher","first-page":"6263","DOI":"10.1038\/s41598-023-33525-0","volume":"13","author":"MJ Raihan","year":"2023","unstructured":"Raihan MJ, Khan MA-M, Kee S-H, Nahid A-A. Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP. Sci Rep. 2023;13(1):6263.","journal-title":"Sci Rep"},{"issue":"2","key":"3363_CR20","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1164\/rccm.2201087","volume":"168","author":"D Annane","year":"2003","unstructured":"Annane D, Aegerter P, Jars-Guincestre MC, Guidet B. Current epidemiology of septic shock: the CUB-Rea network. Am J Respir Crit Care Med. 2003;168(2):165\u201372.","journal-title":"Am J Respir Crit Care Med"},{"key":"3363_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13613-020-00704-5","volume":"10","author":"J Helms","year":"2020","unstructured":"Helms J, Severac F, Merdji H, et al. Performances of disseminated intravascular coagulation scoring systems in septic shock patients. Ann Intensiv Care. 2020;10:1\u20137.","journal-title":"Ann Intensiv Care"},{"key":"3363_CR22","unstructured":"Zhu W, Huang D, Wang Q, et al. A clinical research on relationship between sepsis-induced coagulopathy and prognosis in patients with sepsis. Chin J Emerg Med. 2023:781\u20136."},{"key":"3363_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12865-020-00369-6","volume":"21","author":"L Zhang","year":"2020","unstructured":"Zhang L, Yu C-h, Guo K-p, Huang C-z. Mo L-y. Prognostic role of red blood cell distribution width in patients with sepsis: a systematic review and meta-analysis. BMC Immunol. 2020;21:1\u20138.","journal-title":"BMC Immunol"},{"key":"3363_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.clinbiochem.2020.01.001","volume":"77","author":"Z-D Hu","year":"2020","unstructured":"Hu Z-D, Lippi G, Montagnana M. Diagnostic and prognostic value of red blood cell distribution width in sepsis: a narrative review. Clin Biochem. 2020;77:1\u20136.","journal-title":"Clin Biochem"},{"issue":"2","key":"3363_CR25","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1159\/000522261","volume":"31","author":"D Dankl","year":"2022","unstructured":"Dankl D, Rezar R, Mamandipoor B, et al. Red cell distribution width is independently associated with mortality in sepsis. Med Principles Pract. 2022;31(2):187\u201394.","journal-title":"Med Principles Pract"},{"issue":"6","key":"3363_CR26","doi-asserted-by":"publisher","first-page":"S","DOI":"10.1016\/S0016-5085(20)33490-9","volume":"158","author":"S Arora","year":"2020","unstructured":"Arora S, Nath P, Patro S. Tu1591 red cell distribution width (RDW) to platelet ratio (RPR): a novel marker in early prediction of severity of acute pancreatitis. Gastroenterology. 2020;158(6):S\u20131128.","journal-title":"Gastroenterology"},{"key":"3363_CR27","doi-asserted-by":"publisher","first-page":"1140755","DOI":"10.3389\/fimmu.2023.1140755","volume":"14","author":"H Zhou","year":"2023","unstructured":"Zhou H, Liu L, Zhao Q, et al. Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization. Front Immunol. 2023;14:1140755.","journal-title":"Front Immunol"},{"issue":"1","key":"3363_CR28","doi-asserted-by":"publisher","first-page":"52","DOI":"10.23736\/S0375-9393.20.14420-1","volume":"87","author":"YW Fan","year":"2021","unstructured":"Fan YW, Liu D, Chen JM, Li WJ, Gao CJ. Fluctuation in red cell distribution width predicts disseminated intravascular coagulation morbidity and mortality in sepsis: a retrospective single-center study. Minerva Anestesiol. 2021;87(1):52\u201364.","journal-title":"Minerva Anestesiol"},{"issue":"17","key":"3363_CR29","doi-asserted-by":"publisher","first-page":"2120","DOI":"10.3390\/cells12172120","volume":"12","author":"A Unar","year":"2023","unstructured":"Unar A, Bertolino L, Patauner F, Gallo R, Durante-Mangoni E. Pathophysiology of disseminated intravascular coagulation in sepsis: a clinically focused overview. Cells. 2023;12(17):2120.","journal-title":"Cells"},{"issue":"1","key":"3363_CR30","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1051\/ject\/19972916","volume":"29","author":"G Grist","year":"1997","unstructured":"Grist G, Thomas D. Blood anion gaps and venoarterial carbon dioxide gradients as risk factors in Long-Term extra corporeal support. J Extracorpor Technol. 1997;29(1):6\u201310.","journal-title":"J Extracorpor Technol"},{"issue":"11","key":"3363_CR31","doi-asserted-by":"publisher","first-page":"e1063","DOI":"10.1097\/CCM.0000000000005337","volume":"49","author":"L Evans","year":"2021","unstructured":"Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Crit Care Med. 2021;49(11):e1063\u2013143.","journal-title":"Crit Care Med"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-026-03363-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-026-03363-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-026-03363-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T11:17:09Z","timestamp":1772795829000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12911-026-03363-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,4]]},"references-count":31,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["3363"],"URL":"https:\/\/doi.org\/10.1186\/s12911-026-03363-x","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,4]]},"assertion":[{"value":"10 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All procedures performed in the present study were in accordance with the principles outlined in the 1964 Helsinki Declaration and its later amendments.The establishment of MIMIC-IV was approved by the institutional review boards of the Beth Israel Deaconess Medical Center (Boston, MA) and Massachusetts Institute of Technology (Cambridge, MA), thus, this study was granted a waiver of informed consent. The data of external validation cohort were de-identified, and informed consent was not required. This study was reviewed and approved by the Ethics Committee in Clinical Research of the First Affiliated Hospital of Wenzhou Medicine University (KY2023-R061).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"67"}}