Surgical Management of the Elderly With Traumatic Cervical Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Aging of the population has modified the epidemiology of traumatic spinal cord injury (SCI) as evidenced by the establishment of a bimodal distribution of injuries with increased frequency of fall-related injuries among the elderly. OBJECTIVE: To assess the economic impact of older age (65 years of age and older), using a cost-utility analysis, in the context of acute surgical management and rehabilitation of traumatic cervical SCI, given the paucity of economic studies involving elderly individuals with SCI. METHODS: The cost-utility analysis was performed from the perspective of a public health care insurer. A time horizon of 6 months from SCI onset was used. Costs were estimated in 2014 US dollars. Utilities were generated from the Surgical Timing in Acute Spinal Cord Injury study. RESULTS: The baseline analysis indicated that surgical and rehabilitative management of acute cervical SCI in the elderly (n = 17) is costlier, but similarly effective, than that in younger adults (n = 47). When considering acute spinal surgical management and rehabilitation of younger adults with SCI as the baseline, the incremental cost-effectiveness ratio analysis revealed an additional cost of $5 655 557 per quality-adjusted life-year gained when managing elderly patients with traumatic cervical SCI. The probabilistic analysis confirmed that spinal surgery in the elderly is costlier, but similarly effective, in younger adults after SCI, even though there is no definitive dominance. CONCLUSION: This economic analysis indicates that surgical management and rehabilitation of acute traumatic cervical SCI in the elderly are costlier but similarly effective compared with younger adults with similar impairment. ABBREVIATIONS: AIS, ASIA (American Spinal Injury Association) Impairment Scale.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".