SURGERY FOR ADULT SPINAL SCOLIOSIS: DO THE BENEFITS OUTWEIGH THE RISKS?
Bibliographic record
Abstract
ABSTRACT Around 6% of the elderly population over 65 years of age are affected by adult spinal deformity (ASD). The increasing prevalence of ASD with aging has prompted discussion regarding the use of various techniques for its treatment, such as surgery and conservative treatment. The objective of this study is to investigate whether surgical treatment demonstrates significant benefits as compared to conservative treatment. A literature review was conducted, focusing on the most relevant papers on the topic published in the last five years. Surgical treatment, which costs an average of US$ 99,114 per procedure, enables almost instant improvement of the pain and disability of ASD. The rate of perioperative complications in ASD is approximately 7.5%, and the average improvement in back pain is 6.2 times higher in the surgical approach than in conservative treatment. In addition, the use of modern operative techniques, such as minimally invasive surgery (MIS), reduces the complications and greatly improves patients’ quality of life, compared to open surgery. Therefore, the expected benefits of surgical treatment meets the patient’s expectations by eliminating the pain caused by ASD. Although surgical treatment has a higher cost and a greater risk of complications, the use of minimally invasive techniques give the ASD patient a better quality of life. Level of evidence III; Non-Systematic Review.
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".