Does Red Cell Distribution Width Predict Outcome in Traumatic Brain Injury: Comparison to Corticosteroid Randomization After Significant Head Injury
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) is a leading cause of death and disability. The role of red cell distribution width (RDW) as a prognostic biomarker for outcome in TBI patients is unknown. Based on the corticosteroid randomization after significant head injury (CRASH) trial database, a prognosis calculator (CRASH) has been developed for outcome prediction in TBI. The objectives of this study are to investigate the association between RDW on day 1 of TBI and outcome, and to compare outcome prediction from RDW to that from CRASH. METHODS: We performed a retrospective review of patients with TBI and a Glasgow coma scale (GCS) score of 14 or less. Day 1 RDW and CRASH data were extracted. CRASH was calculated for each patient. Outcome was defined as mortality at 14 days and GOS at 6 months, with poor outcome defined as GOS of 1 - 3. Patients were stratified according to RDW values into six groups, and according to CRASH values into six groups. RESULTS: A total of 416 patients with TBI were included, with 339 survivors (S) and 77 non-survivors (NS). Compared to survivors, non-survivors were of similar age in years (58 ± 23 vs. 58 ± 23, P = 1.0), had lower GCS scores (5 ± 3 vs. 12 ± 3, P = 0.0001), similar RDW (14.0 ± 1.2 vs. 13.9 ± 1.5, P = 0.6), and higher CRASH values (68 ± 26 vs. 24 ± 22, P = 0.0001). Estimating the receiver-operating characteristic (ROC) area under the curve (AUC) showed that CRASH was a significantly better predictor of mortality compared to RDW (AUC = 0.91 ± 0.01 for CRASH compared to 0.66 ± 0.03 for RDW; P < 0.0001). In addition, CRASH was a better predictor of neurologic outcome compared to RDW (AUC = 0.85 ± 0.02 for CRASH compared to 0.76 ± 0.03 for RDW; P = 0.005). CONCLUSIONS: CRASH calculator was a strong predictor of mortality in patients with TBI. RDW on day 1 did not differ between survivors and non-survivors, and was a poor predictor of mortality. Both RDW on day 1 and CRASH calculator are good predictors of 6-month outcome in TBI patients, although CRASH calculator remains a better predictor.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".