The application of IMPACT prognostic models to elderly adults with traumatic brain injury: A population-based observational cohort study
Bibliographic record
Abstract
OBJECTIVE: To examine the performance of the International Mission for Prognosis and Clinical Trial Design in Traumatic Brain Injury (IMPACT) prognostic models in older patients. METHODS: Using data from the National Study on Costs and Outcomes of Trauma (NSCOT), this study identified adult patients presenting to US hospitals in 2001 and 2002 with non-penetrating moderate or severe traumatic brain injury (GCS ≤ 12). IMPACT model calibration and discrimination in the older stratum (65-84 years) was compared to that in the younger stratum (18-64 years). RESULTS: IMPACT model discrimination did not differ significantly between the older (n = 202; weighted n = 268) and younger strata (n = 613; weighted n = 1632) and was generally adequate (c-statistic for the core-death model = 0.81 [0.77-0.84] vs 0.75 [0.66-0.84], respectively; p = 0.26). IMPACT model calibration was poor for both older and younger strata (Hosmer-Lemeshow p-value for the core-death model = 0.01 vs < 0.0001, respectively). Pre-specified qualitative graphical evaluation suggested substantial under-prediction of mortality in the oldest decades of life, but not among younger patients. CONCLUSIONS: The examined IMPACT prognostic models demonstrated adequate discrimination and poor calibration in both older and younger patients, yet particular caution may be required when applying these models to the elderly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".