Pedicle subtraction osteotomies (PSO) in the lumbar spine for sagittal deformities
Bibliographic record
Abstract
INTRODUCTION: The narrow correlation between sagittal alignment parameters and clinical outcomes has been widely established, demonstrating that improper sagittal alignment is a clinical condition that is associated with increased pain and limitations in patients' functional ability. INDICATION: Lumbar pedicle subtraction osteotomy (PSO) is indicated in the treatment of large sagittal (more than 25° of rigid loss of lordosis) deformities of the lumbar spine or its combination with coronal deformity, especially when they are rigid. Indication should be based on careful assessment of the severity of symptoms, functional impairment, functional expectations of the patient, general clinical condition and surgical and anesthesiological team experience. Risk should be carefully assessed and discussed to obtain appropriate informed consent. SURGICAL PROCEDURE: Surgical planning includes selection of the safest levels for the upper and lower instrumented vertebra, site of the osteotomy, modality of fixation, and, most importantly angular value of the correction goal (target lumbar lordosis). Failure to adequately obtain the necessary amount of sagittal correction is the most frequent cause of failure and reoperation. CONCLUSION: PSO is a valuable surgical procedure in correction of severe hypolordosis (=relative kyphosis) in the lumbar spine. It is a demanding procedure for the surgeon, the anesthesiologist and the intensive care team. Although its complication rate is high, it has a substantial positive impact in the quality of life of patients, including the elderly.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".