Bone loss around oral and orthopedic implants: An immunologically based condition
Bibliographic record
Abstract
BACKGROUND: Marginal bone resorption has by some been identified as a "disease" whereas in reality it generally represents a condition. PURPOSE: The present article is a comparison between oral and orthopedic implants, as previously preferred comparisons between oral implants and teeth seem meaningless. MATERIALS AND METHODS: The article is a narrative review on reasons for marginal bone loss. RESULTS AND CONCLUSIONS: The pathology of an oral implant is as little related to a tooth as is pathology of a hip arthroplasty to a normally functioning, pristine hip joint. Oral as well as orthopedic implants are recognized as foreign bodies by the immune system and bone is formed, either in contact or distance osteogenesis, to shield off the foreign materials from remaining tissues. A mild immune reaction coupled to a chronic state of inflammation around the implant serve to protect implants from bacterial attacks. Having said this, an overreaction of the immune system may lead to clinical problems. Marginal bone loss around oral and orthopedic implants is generally not dependent on disease, but represents an immunologically driven rejection mechanism that, if continuous, will threaten implant survival. The immune system may be activated by various combined patient and clinical factors or, if rarely, by microbes. However, the great majority of cases with marginal bone loss represents a temporary immune overreaction only and will not lead to implant failure due to various defense mechanisms.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".