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Record W4391562702 · doi:10.1097/ta.0000000000004232

Proposed revision of the American Association for Surgery of Trauma Renal Organ Injury Scale: Secondary analysis of the Multi-institutional Genitourinary Trauma Study

2024· article· en· W4391562702 on OpenAlexaff
Rano Matta, Sorena Keihani, Kevin Hebert, Joshua J. Horns, Raminder Nirula, Marta L. McCrum, Benjamin J. McCormick, Joel A. Gross, Ryan P. Joyce, Douglas Rogers, Sherry S. Wang, Judith C. Hagedorn, J. Patrick Selph, Rachel Sensenig, Rachel A. Moses, Christopher Dodgion, Shubham Gupta, Kaushik Mukherjee, Sarah Majercik, Joshua A. Broghammer, Ian Schwartz, Sean P. Elliott, Benjamin N. Breyer, Nima Baradaran, Scott Zakaluzny, Bradley A. Erickson, Brandi D. Miller, Reza Askari, Matthew M. Carrick, Frank Burks, Scott H. Norwood, Jeremy B. Myers

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2024
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineInjury Severity ScoreTrauma centerLogistic regressionGrading (engineering)Psychological interventionGenitourinary systemSurgeryGrading scaleBlunt traumaRetrospective cohort studyEmergency medicineInternal medicinePoison controlInjury prevention

Abstract

fetched live from OpenAlex

BACKGROUND: This study updates the American Association for the Surgery of Trauma (AAST) Organ Injury Scale (OIS) for renal trauma using evidence-based criteria for bleeding control intervention. METHODS: This was a secondary analysis of a multicenter retrospective study including patients with high-grade renal trauma from seven level 1 trauma centers from 2013 to 2018. All eligible patients were assigned new renal trauma grades based on revised criteria. The primary outcome used to measure injury severity was intervention for renal bleeding. Secondary outcomes included intervention for urinary extravasation, units of packed red blood cells transfused within 24 hours, and mortality. To test the revised grading system, we performed mixed-effect logistic regression adjusted for multiple baseline demographic and trauma covariates. We determined the area under the curve (AUC) to assess accuracy of predicting bleeding interventions from the revised grading system and compared this to 2018 AAST OIS. RESULTS: Based on the 2018 OIS grading system, we included 549 patients with AAST grades III to V injuries and computed tomography scans (III, 52% [n = 284]; IV, 45% [n = 249]; and V, 3% [n = 16]). Among these patients, 89% experienced blunt injury (n = 491), and 12% (n = 64) underwent intervention for bleeding. After applying the revised grading criteria, 60% (n = 329) of patients were downgraded, and 4% (n = 23) were upgraded; 2.8% (n = 7) downgraded from grade V to IV, and 69.5% (n = 173) downgraded from grade IV to III. The revised renal trauma grading system demonstrated improved predictive ability for bleeding interventions (2018 AUC, 0.805; revised AUC, 0.883; p = 0.001) and number of units of packed red blood cells transfused. When we removed urinary injury from the revised system, there was no difference in its predictive ability for renal hemorrhage intervention. CONCLUSION: A revised renal trauma grading system better delineates the need for hemostatic interventions than the current AAST OIS renal trauma grading system. LEVEL OF EVIDENCE: Diagnostic Test/Criteria; Level III.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.339
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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