Spine Surgical Subspecialty and Its Effect on Patient Outcomes
Bibliographic record
Abstract
STUDY DESIGN: Systematic review and meta-analysis. OBJECTIVE: To perform a systematic review and meta-analysis to identify if intraoperative or postoperative differences in outcomes exist between orthopedic and neurological spine surgeons. SUMMARY OF BACKGROUND DATA: Spine surgeons may become board certified through orthopedic surgery or neurosurgical residency training, and recent literature has compared surgical outcomes between surgeons based on residency training background with conflicting results. MATERIALS AND METHODS: Using Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, a search of PubMed and Scopus databases was conducted and included articles comparing outcomes between orthopedic spine surgeons and neurosurgeons. The Newcastle-Ottawa scale was used to determine the quality of studies. Forest plots were generated using mean differences (MD) for continuous variables and odds ratios (OR) for binomial variables, and 95% CI was reported. RESULTS: Of 615 search term results, 16 studies were identified for inclusion. Evaluation of the studies found no differences in readmission rates [OR, ref: orthopedics: 0.99 (95% CI: 0.901, 1.09); I2 = 80%], overall complication rates [OR, ref: orthopedics: 1.03 (95% CI: 0.97, 1.10); I2 = 70%], reoperation rates [OR, ref: orthopedics: 0.91 (95% CI: 0.82, 1.00); I2 = 86%], or overall length of hospital stay between orthopedic spine surgeons and neurosurgeons [MD: -0.19 days (95% CI: -0.38, 0.00); I2 = 98%]. However, neurosurgeons ordered a significantly lower rate of postoperative blood transfusions [OR, ref: orthopedics: 0.49 (95% CI: 0.41, 0.57); I2 = 75%] while orthopedic spine surgeons had shorter operative times [MD: 14.28 minutes, (95% CI: 8.07, 20.49), I2 = 97%]. CONCLUSIONS: Although there is significant data heterogeneity, our meta-analysis found that neurosurgeons and orthopedic spine surgeons have similar readmission, complication, and reoperation rates regardless of the type of spine surgery performed.
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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 | 0.020 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.047 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".