Transfusion of red blood cells in patients with traumatic brain injuries admitted to Canadian trauma health centres: a multicentre cohort study
Bibliographic record
Abstract
BACKGROUND: Optimisation of healthcare practices in patients sustaining a traumatic brain injury is of major concern given the high incidence of death and long-term disabilities. Considering the brain's susceptibility to ischaemia, strategies to optimise oxygenation to brain are needed. While red blood cell (RBC) transfusion is one such strategy, specific RBC strategies are debated. We aimed to evaluate RBC transfusion frequency, determinants of transfusions and associated clinical outcomes. METHODS: We conducted a retrospective multicentre cohort study using data from the National Trauma Registry of Canada. Patients admitted with moderate or severe traumatic brain injury to participating hospitals between April 2005 and March 2013 were eligible. Patient information on blood products, comorbidities, interventions and complications from the Discharge Abstract Database were linked to the National Trauma Registry data. Relative weights analyses evaluated the contribution of each determinant. We conducted multivariate robust Poisson regression to evaluate the association between potential determinants, mortality, complications, hospital-to-home discharge and RBC transfusion. We also used proportional hazard models to evaluate length of stay for time to discharge from ICU and hospital. RESULTS: Among the 7062 patients with traumatic brain injury, 1991 patients received at least one RBC transfusion during their hospital stay. Female sex, anaemia, coagulopathy, sepsis, bleeding, hypovolemic shock, other comorbid illnesses, serious extracerebral trauma injuries were all significantly associated with RBC transfusion. Serious extracerebral injuries altogether explained 61% of the observed variation in RBC transfusion. Mortality (risk ratio (RR) 1.23 (95% CI 1.13 to 1.33)), trauma complications (RR 1.38 (95% CI 1.32 to 1.44)) and discharge elsewhere than home (RR 1.88 (95% CI 1.75 to 2.04)) were increased in patients who received RBC transfusion. Discharge from ICU and hospital were also delayed in transfused patients. CONCLUSIONS: RBC transfusion is common in patients with traumatic brain injury and associated with unfavourable outcomes. Trauma severity is an important determinant of RBC transfusion. Prospective studies are needed to further evaluate optimal transfusion strategies in traumatic brain injury.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".