Epidemiology of Traumatic Spinal Cord Injury in Ireland, 2010–2015
Bibliographic record
Abstract
BACKGROUND: The International Spinal Cord Society and World Health Organisation recommend the collection of epidemiological data on traumatic spinal cord injury (TSCI). A 1-year prospective study is ongoing in Ireland. While the results of this study are awaited, it was concluded from a feasibility exercise that a complete retrospective dataset, 2010-2015, could be obtained and would be useful for service planning. METHODS: All patients with TSCI discharged from the national SCI acute and rehabilitation centres were included. Data was collected on gender, age, aetiology, level of injury, American Spinal Injuries Association impairment scale, length of rehabilitation admission and discharge destination. Population denominators were national census figures 2006 and 2011, rolled forward. RESULTS: The incidence of TSCI remained constant throughout the study period, 11.5-13.3 per million per year. The mean age of injury onset was 48.9 (SD 19.8) years. Males accounted for 71.5%. The most common injury level/AIS was incomplete tetraplegia, accounting for 43.2% of all TSCI. Leading aetiology was falls, accounting for 53.3% of injuries. Patients with incomplete tetraplegia were older than those with all other injuries (p < 0.001). CONCLUSIONS: The epidemiological trends identified are similar to those prevalent elsewhere in the developed world. More incomplete tetraplegia among an older patient population necessitates a review of how acute care and rehabilitation services are delivered.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".