Porous titanium‐nickel for intervertebral fusion in a sheep model: Part 1. Histomorphometric and radiological analysis<sup>1</sup>
Bibliographic record
Abstract
Porous titanium-nickel (PTN) implants represent an alternative to traditional intervertebral fusion cages. Indeed, PTN materials possess interconnecting pores with cell capillarity properties that may promote bone ingrowth and intervertebral fusion without the need for bone grafting. In this study, a PTN intervertebral fusion device was compared to a conventional TiAlV cage packed with autologous bone in a sheep model. The two devices were implanted at two noncontiguous intervertebral lumbar sites for 3, 6, and 12 months. PTN osseointegration showed a time-dependent trend increasing from 21.4% to 37.6% (3-12 months), whereas TiAlV cages remained at the same level of bone ingrowth (22.7%-25.4%; 3-12 months). Furthermore, PTN bone apposition (10.9%-24.2%; 3-12 months) was significantly higher than that of TiAlV implants (1.1%-5.1%; 3-12 months; p < 0.001, ANOVA). Radiological fusion scores increased with postsurgery time regardless of material type, but were consistently superior for PTN (12.5-18.5; 3-12 months) than for TiAlV cages (2.0-15.0; 3-12 months; p < 0.001, ANOVA). Implant materials were not significantly different according to the radiological interbody index based on preoperative disc height: Interbody index began at 132.6% (PTN) and 123.5% (TiAlV) immediately after surgery, then declined to 80.8% (PTN) and 91.0% (TiAlV) after 12 months. Nevertheless, ungrafted PTN constituted an excellent substrate for osteogenic cell integration and represents a new osteoconductive biomaterial with improved fusion characteristics in comparison to conventional TiAlV cages.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".