Instrumentation Removal following Minimally Invasive Posterior Percutaneous Pedicle Screw-Rod Stabilization (PercStab) of Thoracolumbar Fractures Is Not Always Required
Bibliographic record
Abstract
BACKGROUND: Percutaneous stabilization for spinal trauma confers less blood loss, reduces postoperative pain, and is less invasive than open stabilization and fusion. The current standard of care includes instrumentation removal. OBJECTIVE: 1. Reporting patient outcomes following minimally invasive posterior percutaneous pedicle screw-rod stabilization (PercStab). 2. Evaluating the results of instrumentation retention. METHODS: A prospective observational study of 32 consecutive patients receiving PercStab without direct decompression or fusion. Baseline data demographics were collected. Operative outcomes of interest were operative room (OR) time, blood loss, and length of hospital stay. Follow-up variables of interest included patient satisfaction, Numeric Rating Scales for Back and Leg (NRS-B/L) pain, Oswestry Disability Index (ODI), and return to work. Clinical outcome data (ODI and NRS-B/L) were collected at 3, 12, 24 months and continued at a 24-month interval up to a maximum of 8 years postoperatively. RESULTS: = 26) retained their instrumentation and reported minimal disability, mild pain, and satisfaction with their surgery and returned to work (mean = 6 months). Six patients required instrumentation removal due to prominence of the instrumentation or screw loosening, causing discomfort/pain. Instrumentation removal patients reported moderate back and leg pain until removal occurred; after removal, they reported minimal disability and mild pain. Neither instrumentation removal nor retention resulted in complications or further surgical intervention. CONCLUSIONS: PercStab without instrumentation removal provided high patient satisfaction, mild pain, and minimal disability and relieved the patient from the burden of finances and resources allocation of a second surgery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".