Lumbar Spinal Arthroplasty
Bibliographic record
Abstract
STUDY DESIGN: This is a retrospective analysis of data that were collected prospectively from 2 concurrent FDA IDE lumbar arthroplasty clinical trials performed at a single center. OBJECTIVES: The purpose of this study was to determine if factors differentiating those patients with the best and worst clinical outcomes from total disc arthroplasty (TDR) could be identified. SUMMARY OF BACKGROUND DATA: Overall the results of TDR have been favorable, including recent results from 2 FDA IDE trials conducted in the United States. However, as with any surgical procedure, there were some patients with extremely good outcomes, and some with poor outcomes. If factors differentiating these groups could be identified, this may help refine patient selection criteria and improve future results. METHODS: The databases of Charite and ProDisc patients at a single site were reviewed to identify patients who reached the 24-month follow-up period. A total of 203 patients, 63 who were implanted with the Charite prosthesis, and 140 who were implanted with the ProDisc prosthesis, were identified. The percentage change in the preoperative to postoperative VAS and Oswestry scores were used to identify the 10 best and 10 worst outcomes for each of the device types. Logistic regression analysis was conducted to determine which of a battery of demographic and clinical assessments were related to the best/worst group classification. RESULTS: Results of the regression analysis found that the only factor significantly related to clinical outcome was the length of time off work before surgery. None of the demographic variables, preoperative VAS or Oswestry scores or radiographic assessment of device placement, were significantly related to clinical outcome. Patients who were off work for shorter durations, or not at all, were more likely to be in the best-outcome group compared with patients who were off work for an extended period of time before surgery. CONCLUSION: This study suggests that among patients undergoing TDR, the length of time off work before surgery was related to outcome. No additional factors related to the best/worst classification were identified in the current study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".