{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T18:26:36Z","timestamp":1786991196312,"version":"build-2736575974"},"reference-count":25,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T00:00:00Z","timestamp":1786924800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Reliable mortality prediction is central to trauma research, quality assessment, and resource allocation. While the French national hospital discharge database (PMSI) provides comprehensive nationwide data, it does not capture clinical parameters required for established severity scores such as TRISS, which is used for predicting in-hospital survival after trauma and necessary for implementing national-level evaluations of health system performance. This study tested whether TRISS could nonetheless be accurately derived from PMSI data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective study of adult patients admitted for severe trauma to an academic trauma center between 2012 and 2023. Clinical data from medical records were linked with corresponding PMSI records. Surrogate predictors of TRISS were derived from PMSI codes. An extreme gradient boosting (XGBoost) model was used, model performance was assessed using bootstrap validation and interpretability was explored through SHapley Additive exPlanations analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 2,523 trauma patients were successfully matched between PMSI and medical records. Median age was 35 years, 79% were male, and in-hospital mortality was 15%. Correlation between Simplified Acute Physiology Score II (SAPS II) in PMSI and medical records was strong (\u03c1\u2009=\u20090.88), while concordance for shock and coma was weak (\u03ba\u2009\u2248\u20090.25). The XGBoost model using individual PMSI codes achieved the best performance (optimism-adjusted R\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20090.72). SAPS II was the main contributor, with additional contributions from shock, coma, and anatomical injury codes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>TRISS can be reliably approximated from PMSI data using an XGBoost model. This approach enables patient-specific assessment of trauma severity and mortality risk from PMSI, opening perspectives for nationwide surveillance and quality evaluation of trauma care in France.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0354700","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T17:30:16Z","timestamp":1786987816000},"page":"e0354700","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting the Trauma and Injury Severity Score (TRISS) in patients admitted to trauma centers after trauma: A modeling study based on data from the French National Programme for Medicalization of Information"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1172-6398","authenticated-orcid":true,"given":"Arthur","family":"James","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Hajage","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"No\u00e9mie","family":"Simon-Tillaux","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sophie","family":"Tezenas du Montcel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre","family":"Rufat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruno","family":"Riou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2493-9146","authenticated-orcid":true,"given":"Mathieu","family":"Raux","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,8,17]]},"reference":[{"issue":"5","key":"pone.0354700.ref001","first-page":"461","article-title":"Epidemiology of trauma in France: mortality and risk factors based on a national medico-administrative database","volume":"38","author":"T B\u00e8ge","year":"2019","journal-title":"Anaesth Crit Care Pain Med"},{"key":"pone.0354700.ref002","doi-asserted-by":"crossref","first-page":"2133","DOI":"10.1016\/S0140-6736(24)00757-8","article-title":"Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990\u20132021: a systematic analysis for the Global Burden of Disease Study 2021","volume":"403","author":"AJ Ferrari","year":"2024","journal-title":"Lancet"},{"issue":"1","key":"pone.0354700.ref003","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1097\/SLA.0000000000003879","article-title":"Important Issues to Severe Trauma Survivors: A Qualitative Study","volume":"275","author":"A James","year":"2022","journal-title":"Ann Surg"},{"issue":"1","key":"pone.0354700.ref004","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.respe.2017.10.002","article-title":"La codification PMSI identifie mal les traumatismes graves","volume":"66","author":"A Perozziello","year":"2018","journal-title":"Revue d\u2019\u00c9pid\u00e9miologie et de Sant\u00e9 Publique"},{"issue":"4","key":"pone.0354700.ref005","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1097\/00005373-198704000-00005","article-title":"Evaluating trauma care: the TRISS method. 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