Wear and Corrosion in Retrieved Thoracolumbar Posterior Internal Fixation
Bibliographic record
Abstract
STUDY DESIGN: Posterior thoracolumbar spine implants retrieved as part of routine clinical practice over a 2-year period were analyzed to identify wear and corrosion. OBJECTIVE: Engineering analyses of retrieved posterior instrumentation for indications of performance and failure and correlation of this information with clinical factors. SUMMARY OF BACKGROUND DATA: Recent studies have reported spinal instrumentation particulate wear debris and have noted the importance of design considerations at implant connector interfaces. METHODS: A total of 57 implants were analyzed from patients (39 female, 18 male) whose average age at implantation was 43.9 years (range, 13.7-77.4 years). Time of implantation ranged from 2 months to 13.5 years. The top 3 implantation diagnoses were radiculopathy (33%), scoliosis (30%), and back pain (25%). Metallurgical analyses were performed to characterize the wear and/or corrosion, and fractures of the implants. RESULTS: Wear was present in 75%, corrosion in 39%, and fractures in 7% of the retrieved implants. Wear and/or corrosion was more prevalent, with respect to the total number of implants retrieved, in implants that had been in service at least 1 year. There was no evidence of corrosion in any of the Ti implants, whereas corrosion was present (with wear) in 58% of the stainless steel (SS) implants. Wear and corrosion were more frequently observed in long rods than in short rods. Implantation times were longer for SS implants than for Ti implants. CONCLUSIONS: Retrieved rods exhibited corrosion, wear, and fracture, with wear and corrosion mainly located at the interfaces with hooks, screws, or cross-connectors. The mechanisms causing this material loss in situ, as well as what local or systemic responses it may stimulate are of clinical significance and should be studied further.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".