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Record W2919377965 · doi:10.1097/ta.0000000000001584

Outcomes after concomitant traumatic brain injury and hemorrhagic shock

2017· article· en· W2919377965 on OpenAlexfundno aff
Samuel M. Galvagno, Erin E. Fox, Savitri Appana, Sarah Baraniuk, Patrick L. Bosarge, Eileen M. Bulger, Rachel A. Callcut, Bryan A. Cotton, Michael D. Goodman, Kenji Inaba, Terence O’Keeffe, Martin A. Schreiber, Charles E. Wade, Thomas M. Scalea, John B. Holcomb, Deborah M. Stein

Bibliographic record

VenueThe Journal of Trauma: Injury, Infection, and Critical Care · 2017
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Heart, Lung, and Blood InstituteNational Institute of Environmental Health SciencesCanadian Institutes of Health Research
KeywordsTraumatic brain injuryInterquartile rangeMedicineConcomitantConfidence intervalInternal medicineOdds ratioAbbreviated Injury ScaleGlasgow Outcome ScaleInjury Severity ScoreGlasgow Coma ScalePoison controlSurgeryInjury preventionEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Often the clinician is faced with a diagnostic and therapeutic dilemma in patients with concomitant traumatic brain injury (TBI) and hemorrhagic shock (HS), as rapid deterioration from either can be fatal. Knowledge about outcomes after concomitant TBI and HS may help prioritize the emergent management of these patients. We hypothesized that patients with concomitant TBI and HS (TBI + HS) had worse outcomes and required more intensive care compared with patients with only one of these injuries. METHODS: This is a post hoc analysis of the Pragmatic, Randomized Optimal Platelets and Plasma Ratios (PROPPR) trial. TBI was defined by a head Abbreviated Injury Scale score greater than 2. HS was defined as a base excess of -4 or less and/or shock index of 0.9 or greater. The primary outcome for this analysis was mortality at 30 days. Logistic regression, using generalized estimating equations, was used to model categorical outcomes. RESULTS: Six hundred seventy patients were included. Patients with TBI + HS had significantly higher lactate (median, 6.3; interquartile range, 4.7-9.2) compared with the TBI group (median, 3.3; interquartile range, 2.3-4). TBI + HS patients had higher activated prothrombin times and lower platelet counts. Unadjusted mortality was higher in the TBI + HS (51.6%) and TBI (50%) groups compared with the HS (17.5%) and neither group (7.7%). Adjusted odds of death in the TBI and TBI + HS groups were 8.2 (95% confidence interval, 3.4-19.5) and 10.6 (95% confidence interval, 4.8-23.2) times higher, respectively. Ventilator, intensive care unit-free and hospital-free days were lower in the TBI and TBI + HS groups compared with the other groups. Patients with TBI + HS or TBI had significantly greater odds of developing a respiratory complication compared with the neither group. CONCLUSION: The addition of TBI to HS is associated with worse coagulopathy before resuscitation and increased mortality. When controlling for multiple known confounders, the diagnosis of TBI alone or TBI+HS was associated with significantly greater odds of developing respiratory complications. LEVEL OF EVIDENCE: Prognostic study, level II.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.331
Teacher spread0.305 · 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

Citations57
Published2017
Admission routes1
Has abstractyes

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