Effects of alternative instrumentation strategies in adolescent idiopathic scoliosis: A biomechanical analysis
Bibliographic record
Abstract
The recent advent of modern instrumentation systems has improved the correction of scoliosis, but complicated the surgical decision-making process, especially with the introduction of diverse spinal fixation devices, new preoperative corrective maneuvers, and the reevaluation of many rules concerning the selection of fusion levels and other guidelines for surgical correction. Our objective was to assess the biomechanical effects of different instrumentation strategies for the same scoliotic cases. Several instrumentation strategies suggested by a group of 32 experienced senior surgeons for five cases were individually simulated using a validated computer model implemented in a spine surgery simulator. The resulting geometric indices varied among the five cases (e.g., range of main thoracic Cobb angles: 5-17 degrees , 16-29 degrees , 25-44 degrees , 15-34 degrees , 16-32 degrees ; kyphosis: 22-33 degrees , 20-54 degrees , 33-55 degrees , 24-49 degrees , 29-46 degrees ; and lordosis: 10-52 degrees , 24-38 degrees , 26-54 degrees , 8-28 degrees , 34-53 degrees ). The average correction was better with pedicle screws (71%) than with hooks (51%) and hybrid constructs (67%). For the first time, to our knowledge, the effect of different instrumentation strategies was compared on the same patients, which is possible only with a surgery simulator. A large variability of instrumentation strategies existed among experienced surgeons and produced rather different results. This study questions the criteria for optimal configuration and standards to design the best surgical construct.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".