The global map for traumatic spinal cord injury epidemiology: update 2011, global incidence rate
Bibliographic record
Abstract
STUDY DESIGN: Literature review. OBJECTIVES: Update the global maps for traumatic spinal cord injury (TSCI) and incorporate methods for extrapolating incidence data. SETTING: An initiative of the International Spinal Cord Society (ISCoS) Prevention Committee. METHODS: A search of Medline/Embase was performed (1959-Jun/30/2011). Enhancement of data-quality 'zones' including individual data-ranking as well as integrating regression techniques to provide a platform for continued regional and global estimates. RESULTS: A global-incident rate (2007) is estimated at 23 TSCI cases per million (179,312 cases per annum). Regional data are available from North America (40 per million), Western Europe (16 per million) and Australia (15 per million). Extrapolated regional data are available for Asia-Central (25 per million), Asia-South (21 per million), Caribbean (19 per million), Latin America, Andean (19 per million), Latin America, Central (24 per million), Latin America-Southern (25 per million), Sub-Saharan Africa-Central (29 per million), Sub-Saharan Africa-East (21 per million). DISCUSSION: It is estimated that globally in 2007, there would have been between 133 and 226 thousand incident cases of TSCI from accidents and violence. The proportion of TSCI from land transport is decreasing/stable in developed but increasing in developing countries due to trends in transport mode (transition to motorised transport), poor infrastructure and regulatory challenges. TSCIs from low falls in the elderly are increasing in developed countries with ageing populations. In some developing countries low falls, resulting in TSCI occur while carrying heavy loads on the head in young people. In developing countries high-falls feature, commonly from trees, balconies, flat roofs and construction sites. TSCI is also due to crush-injuries, diving and violence. CONCLUSION: The online global maps now inform an extrapolative statistical model, which estimates incidence for areas with insufficient TSCI data. The accuracy of this methodology will be improved through the use of prospective, standardised-data registries.
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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 | 0.012 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.035 | 0.035 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".