The Effect of Crown-to-Implant Ratio on the Clinical Outcomes of Dental Implants: A Systematic Review
Bibliographic record
Abstract
PURPOSE: To analyze the effect of crown-to-implant (C/I) ratio over survival rate, marginal bone loss, and prosthetic complications of dental implants. MATERIALS AND METHODS: Electronic (PubMed, Ovid MEDLINE, and Cochrane Central) and manual searches for clinical trials with a minimum follow-up of 1 year were performed. Clinical and anatomical C/I ratios were obtained. Regression models were created to assess for potential correlation between C/I ratio (anatomical and clinical) and survival rate, marginal bone loss, or prosthetic complications. A subgroup analysis of 6-mm implants and a comparison of C/I ratios of > 1.5 versus ≤ 1.5 were also performed. The Newcastle-Ottawa Scale and Cochrane Risk of Bias Tool For Randomized Controlled Trials were used to evaluate the risk of bias. RESULTS: An overall moderate risk of bias was assessed among the selected articles. Linear regression analysis did not reveal a significant correlation between anatomical C/I ratios and survival rate (P = .905), marginal bone loss (P = 0.33), or prosthetic complications (P = .67). Similarly, no significant correlation to survival rate and marginal bone loss (P = 0.42, P = 0.84) was observed in the articles providing the clinical C/I ratios. CONCLUSION: Increased C/I ratio does not seem to be directly related with increased marginal bone loss and does not represent a biomechanical risk factor for the stability of the prosthesis and for the survival of dental implants.
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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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".