Anterior Thoracoscopic Instrumentation in Adolescent Idiopathic Scoliosis
Bibliographic record
Abstract
STUDY DESIGN: A Systematic Review of published series of patients with adolescent idiopathic scoliosis treated with anterior thoracoscopic instrumentation. OBJECTIVE: To conduct a systematic review of the results of thoracoscopic surgery and to compare them with those of open anterior and posterior spine instrumentation to enable surgeons judge the applicability of the method. SUMMARY OF BACKGROUND DATA: Instrumentation through video-assisted thoracoscopic surgery is an attractive alternative for the treatment of thoracic adolescent idiopathic scoliosis. The advantages claimed by its proponent over conventional instrumentations are better cosmesis and reduced morbidity due its minimal invasive nature. However, superiority of thoracoscopic instrumentation over conventional methods has not been proven so far. METHODS: Via Medline, Pubmed, and other literature searches, 8 articles met the inclusion criteria for our systematic review. The evaluations were made according to the parameters employed for evaluating spinal deformities. Instrumentation through video-assisted thoracoscopic surgery results were compared to those of open anterior or posterior surgeries. RESULTS: Mean number of instrumented levels was 7. The extent of disc excision was not indicated in any of the studies. The mean operative time was found to be approximately 5.2 hours. Average blood loss was 391.7 mL (100-1300 mL). The average Cobb curve correction was 64.6%. The mean preoperative kyphosis angle was 21.3 degrees ; the postoperative kyphosis angle was 25.2 degrees . These angular corrections were found to be comparable to posterior procedures using hooks, but less than with pedicle screws. Two studies reported on patient satisfaction favoring thoracoscopic instrumentation. Instrumentation-related complications were the most predominant. CONCLUSION: Anterior thoracoscopic instrumentation is comparable in terms of curve correction to anterior or posterior procedures. Theoretical advantages of better cosmesis and less aggressiveness seem to be offset by the increased operative and intensive care unit time, and complication rate. More prospective studies need to be conducted to determine the benefit and general applicability of this procedure.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".