Evidence map›Paper›PMID 42607050›Full record

ArticlePloS one2026

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.

Arthur James, David Hajage, Noémie Simon-Tillaux, Sophie Tezenas du Montcel, Pierre Rufat, Bruno Riou, Mathieu Raux

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Arthur JamesSorbonne University, GRC 29, and Department of Anesthesiology and Critical Care Medicine, Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France.ORCID https://orcid.org/0000-0002-1172-6398
David HajageSorbonne University, Pierre Louis Institute of Epidemiology and Public Health (IPLESP), INSERM UMR-S, Department of Public Health, Pharmacoepidemiology Center (Cephepi), and Clinical Research Unit, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
Noémie Simon-TillauxDepartment of Biostatistics and Epidemiology, Gustave Roussy Institute, Oncostat INSERM U1018, Paris-Saclay University, Villejuif, France.
Sophie Tezenas du MontcelSorbonne University, Paris Brain Institute, INSERM-CNRS UMR, Department of Medical Information, Pitié-Salpêtrière Hospital, AP-HP, Inria Paris, France.
Pierre RufatDepartment of Medical Information, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
Bruno RiouSorbonne University, INSERM UMR-S, IHU ICAN, and Emergency Department, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.
Mathieu RauxSorbonne University, INSERM UMR-S, and Department of Anesthesiology and Critical Care Medicine, Pitié-Salpêtrière Hospital, AP-HP, Paris, France.ORCID https://orcid.org/0000-0003-2493-9146

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundReliable 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.

methodsWe 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.

resultsA 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 (ρ = 0.88), while concordance for shock and coma was weak (κ ≈ 0.25). The XGBoost model using individual PMSI codes achieved the best performance (optimism-adjusted R2 = 0.72). SAPS II was the main contributor, with additional contributions from shock, coma, and anatomical injury codes.

conclusionTRISS 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.

Indexed as

Injury Severity ScoreTrauma CentersTrauma Severity IndicesWounds and InjuriesAdultDatabases, FactualFemaleFranceHospital MortalityHumansMaleMiddle AgedRetrospective Studies

Identifiers

PMID42607050
PMCPMC13480638

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