General Session 2: Chronic Care
Bibliographic record
Abstract
Objective: Individuals with chronic spinal cord injury (SCI) may be at greater risk of emergency room (ER) visits-related hospitalizations, yet essentially no studies have been reported with chronic SCI.Our purpose is to identify the incidence of ER visits and hospitalizations in a cohort of 1,654 participants who average 16 years post injury.Design/Method: Cross-sectional, selfreport.Inclusion criteria were (1) traumatic SCI, (2) minimum of 1 year post injury, (3) minimum of 18 years of age, and (4) some residual impairment.Results: Thirty-seven percent reported at least one ER visit in the previous 12 months (average of 2.3 among those with 1+ visit).ER-related hospitalizations were observed among 50% of those with 1+ visit.ER visits were significantly related to race-ethnicity and injury severity, with the greatest risk among Black non-Hispanics and those with the most severe SCI (C1-C4).Injury severity was also related to ER hospitalizations, although race-ethnicity was not.Both age and age at injury onset were significantly related to ER hospitalizations, with those in the oldest age groups at greatest risk.Conclusion: ER visits are a significant problem after SCI, particularly among Blacks.Risk of ER-related hospitalizations, an indicator of severity of the consequence of the conditions leading to the visit, is highest among vulnerable participants due to injury severity and age.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.740 | 0.388 |
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".