Effect of Crown to Implant Ratio and Anatomical Crown Length on Clinical Conditions in a Single Implant: A Retrospective Cohort Study
Bibliographic record
Abstract
PURPOSE: The aim of this retrospective cohort study was to evaluate the long-term influence of the crown-to-implant (C/I) ratio and anatomical crown length on clinical conditions around Astra single dental implants placed in the premolar and molar regions. MATERIALS AND METHODS: Seventy-six subjects were selected from patients who had been treated with single Astra implants for replacement of missing premolars and molars. The peri-implant marginal bone level change was assessed 1 year after functional loading and 6 years after functional loading. To predict the peri-implant marginal bone level change using clinical and radiographic data, a multiple linear regression model was applied. The Wilcoxon rank sum test was used to analyze difference median in technical complications. RESULTS: The C/I ratio and anatomical crown length were not associated with peri-implant marginal bone loss or changes in the bone level at 6 years (p = .48, p = .31). However, the modified plaque index, modified sulcus bleeding index, and smoking status influenced the peri-implant marginal bone loss (p < .05, r(2) = 0.54). In addition, the patient with technical complication group did show significantly increased anatomical crown length (p < .05) CONCLUSIONS: The higher C/I ratio and anatomical crown length did not increase the risk of peri-implant marginal bone loss during 6 years of functional loading. In addition, higher anatomical crown lengths are associated with higher technical complications.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".