A novel growing rod technique to treat early-onset scoliosis (EOS): a step-by-step 2D surgical video
Bibliographic record
Abstract
Early-onset scoliosis (EOS) correction techniques have evolved slowly over the past 40 years and still remain a challenge for the spine surgeon. Avoiding spinal fusion in these patients is key to decreasing morbidity and mortality in this population. Current treatments for EOS include both conservative and surgical options. The authors present the modified Luqué technique that has been performed at their institution for the past decade. This modified technique relies on Luqué's principle, but with newer "gliding" implants through a less disruptive approach. The goal of this technique is to delay fusion as long as possible, with the intent to prevent deformity progression while preserving maximal growth. Normally, these patients will have definitive fusion surgery once they have reached skeletal maturity or as close as possible. Out of 23 patients until present (close to 4-year follow-up), the authors have not performed any revision due to implant failure. Three patients have undergone final fusion as the curve progressed (one patient, 4 years out, had final fusion at age 12 years; two other patients had final fusion at 3 years). These implants, which have the CE mark in Europe, are available in Canada via a special access process with Health Canada. The implants have not yet been submitted to the FDA, as they are waiting on clinical data out of Europe and Canada. In the following video the authors describe the modified Luqué technique step-by-step. The video can be found here: https://youtu.be/k0AuFa9lYXY.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".