Early peri‐implant bone loss as a predictor for peri‐implantitis: A 10‐year prospective cohort study
Bibliographic record
Abstract
PURPOSE: To evaluate the effect of early bone loss (EBL), on long-term bone stability and future peri-implantitis development. MATERIALS AND METHODS: Patients referred for implant placement between 2005 and 2009 were consecutively treated and followed for 10 years. After 10 years, patients were invited for a scientific diagnostic visit to evaluate implant survival and bone loss. Bone level changes were compared with baseline. Non-parametric testing was performed in cross-tabs (Pearson Chi-square and Fishers's exact test). Kaplan-Meier-estimated survival curves were plotted for different thresholds for EBL at different timepoints. Generalized linear mixed models with binomial distribution and logit link for peri-implantitis were fitted. An adjusted logistic mixed model was made to evaluate peri-implantitis, in relation with smoking status, history of periodontitis, and EBL > 0.5 mm. RESULTS: Four hundred and seven patients (mean age of 64.86 years [range 28-92, SD 10.11]), with 1482 implants, responded to the 10-year recall invitation. After an average follow-up time of 10.66 years (range 10-14, SD 0.87), implant survival was 94.74%. Mean crestal bone loss after 10 years was 0.81 mm (SD 1.58, range 0.00-17.00). One hundred and seventy five implants in 76 patients had peri-implantitis (11.8% on implant level, 18.7% on patient level). EBL of 0.5, 1, and 2 mm were significant predictors for peri-implantitis and implant loss after 10 years. Implants with EBL ≥0.5 mm during the first year of function showed a 5.43 times higher odds for future peri-implantitis development. Probability in developing peri-implantitis was 52.06% when smoking, Periodontal history and EBL of >0.5 mm was combined. CONCLUSION: The present study suggests that EBL is a predictor for long-term peri-implant pathology, with a significant higher risk for peri-implantitis when early bone loss exceeds the thresholds of 0.5 and 1 mm, especially when additional risk factors such as smoking or susceptibility for periodontal disease prior to implant treatment are present. Clinical trial registration number B670201524796.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".