Outcome of traumatic thoracolumbar spine fractures in elderly: A systematic review
Bibliographic record
Abstract
Introduction: Adequate guidelines for treatment of people over 65 years, suffering traumatic thoracolumbar spine fractures without neurologic deficit, are currently lacking. Research question: The aim of this study was to systematically review the available literature regarding the outcome of conservative and surgical treatment of thoracolumbar spinal trauma in elderly patients. Material and methods: A systematic review according the PRISMA guidelines was performed. Pubmed, Web of Science, EMBASE and the Cochrane Central register were searched until June 2021. Risk of bias of the included studies was evaluated. Clinical and radiological results, as well as complications of conservative or surgical treatment were reviewed. Results: Six articles were included (one prospective randomized trial, two prospective and three retrospective cohort studies). In these studies conflicting results were observed with regard to pain, radiological results and complications following both conservative and surgical treatment strategies for thoracolumbar spine fractures in elderly. Discussion and conclusion: Treatment of thoracolumbar fractures in elderly should focus on early mobilization to reduce complications and hospital stay. This may improve functional outcome and prevent worsening of frailty in this vulnerable group of patients. To elucidate the optimal treatment for elderly patient with thoracolumbar fractures, future research should focus on patient specific treatment rather than the mere difference between outcome of surgical and conservative treatment.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".