Long-Term Outcomes Following Lumbar Nucleus Replacement
Bibliographic record
Abstract
BACKGROUND: Nucleus replacement devices are designed to replace the native pain-generating lumbar nucleus while preserving the annulus fibrosus, endplates, and natural motion. The DASCOR Disc Arthroplasty Device seemed to perform well clinically but was discontinued in 2009. While there are no commercially available NRDs today, the potential advantages of using such devices have prompted a renewed interest in further developing the technology and assessing long-term outcomes for the DASCOR device. METHODS: A retrospective review of hospital records from a single institution was performed to identify all patients that underwent implantation of a DASCOR device between 2006 and 2009. Clinical outcome and imaging data were gathered to assess device performance of the DASCOR device over an extended period of time. Clinical data were assessed using a visual analog scale for back pain (VAS), Oswestry Disability Index (ODI) scores, and analgesic medication use score (ANS). Magnetic resonance images were systematically evaluated at the index and adjacent disc levels: disc height, Modic changes, Pfirrmann grade, and any implant-associated findings. RESULTS: = 0.07) compared to baseline values, while 46% developed radiological adjacent segment degeneration on MRI and 54% did not. In total, 6 patients underwent revision surgery at the index level and 3 underwent surgery at adjacent lumbar levels. CONCLUSIONS: While any conclusions should be interpreted with caution, there was a subgroup of patients that had excellent clinical and radiological outcomes. Additional studies on this device or other similar devices would add to our knowledge regarding ideal treatment of discogenic low back pain in younger patients. CLINICAL RELEVANCE: Treatment of discogenic low back pain. LEVEL OF EVIDENCE: 4.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".