A retrospective study on the treatment outcome of wide-bodied implants.
Bibliographic record
Abstract
PURPOSE: This retrospective study documented the 5-year cumulative survival rate (CSR) of 5-mm-diameter wide-bodied implants in posterior jaws as related to identified risk factors and relative host bone site dimensions. MATERIALS AND METHODS: Sixty-four wide-bodied implants placed consecutively in the posterior jaws of 43 patients were matched using several identified risk factors with 64 regular-diameter implants (3.75-mm or 4-mm diameter) placed in the posterior jaws of 25 of the same patients and 14 others. Life table analyses were undertaken to examine the difference in CSR between the groups. Multivariate Cox regression was conducted to assess the relationship between potential risk factors and overall CSR. RESULTS: Ten of the wide-bodied implants failed (CSR 80.9%), while two of the regular-diameter implants failed (CSR 96.8%). The difference between the groups was statistically significant. Multivariate analysis demonstrated a significant predictive relationship between overall CSR and the ratio of implant volume to remaining bone volume. This suggests that relative determinants of critical bone volume to implant dimensions may need to be considered when planning implant surgery. CONCLUSION: Wide-bodied implants placed in the posterior jaw can suffer a significantly elevated risk of implant failure compared to regular-diameter implants. This susceptibility may relate to either implant design or the relative relationship of implant to host bone dimensions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".