Economic Impact of Aging on the Initial Spine Care of Patients With Acute Spine Trauma: From Bedside to Teller
Bibliographic record
Abstract
BACKGROUND: Aging of the population has prompted an escalation of service utilization and costs in many jurisdictions including North America. However, relatively little is known on the economic impact of old age on the management of acute spine trauma (AST). OBJECTIVE: To examine the potential effects of age on the service utilization and costs of the management of patients with acute spine trauma. METHODS: This retrospective cohort study included consecutive patients with AST admitted to an acute spine care unit of a Canadian quaternary university hospital between February, 2002 and September, 2007. The study population was grouped into elderly (≥65 yr) and younger individuals. All costing data were converted and updated to US dollars in June/2017. RESULTS: There were 55 women and 91 men with AST (age range: 16-92 yr, mean age of 49.9 yr) of whom 37 were elderly. The mean total hospital costs for initial admission after AST in the elderly (USD $19 338 ± $4892) were significantly greater than among younger individuals (USD $13 775 ± $1344). However, elderly people had significantly lower per diem total, fixed, direct, and indirect costs for AST than younger individuals. Both groups were comparable regarding the proportion of services utilized in the acute care hospital. CONCLUSION: Given the escalating demand for surgical and nonsurgical spine treatment in the age of aging population, the timely results of this study underline key aspects of the economic impact of the spine care of the elderly. Further investigations are needed to fulfill significant knowledge gaps on the economics of caring for elderly with AST.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".