Bibliographic record
Abstract
Background This study examined the effects of concomitant TBI on injury epidemiology, management and outcomes of individuals with traumatic SCI. Methods A propensity-score matched cohort study compared a SCI+TBI group (n=1018) with a SCI-only group (n=3687), which were matched on a 1:1 ratio by age, sex, severity and level of SCI, and Charlson Comorbidity Index. TBI was defined as a Glasgow coma score of <15 at admission. Both groups were compared regarding injury epidemiology (mechanism, ethnicity, GCS, other injuries), management (mechanical ventilation, traction, Methylprednisone, surgery, time to decompression), and post-SCI outcomes (length of stay [LOS], International Standards for Neurological Classification of SCI [ISNCSCI] motor subscore, Functional Independence Measure, discharge destination, spasticity and pain at discharge). Results Overall, being white (OR=5.332, p=0.0265) was associated with having TBI, while having other body injuries (OR=0.095, p=0.0065) was associated with the SCI-only group. Odds of dying in a hospital were 2.442 times larger for the TBI+SCI group. The TBI+SCI group had longer acute-care LOS. Both groups had similar rehabilitation LOS. Odds of being discharged to nursing homes/long-term care facilities were 1.949 times higher for TBI+SCI individuals. Concomitant TBI did not influence change in ISNCSCI motor subscore from initial admission to final discharge. Odds of individuals with pain was 1.52 times higher for the TBI+SCI group. Occurrence of spasticity was similar between the groups. Conclusion This study highlights discrepancies between the TBI+SCI and SCI-only groups regarding injury epidemiology, survival, discharge disposition, and pain. Both groups experienced similar access to treatment services, motor recovery, and spasticity. Disclosure These data were presented in the 2022 Annual Meeting of the American Neurological Association, which has a different attendance audience.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.867 | 0.804 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".