Long term follow‐up of titanium implants installed in block‐grafted areas: A systematic review
Bibliographic record
Abstract
BACKGROUND: An enduring clinical question concerns the outcome (ie, success) of implants placed in areas grafted with block-grafts. OBJECTIVE: To undertake a systematic review of the literature on the long term results (≥5 years) of implants placed in maxillofacial areas grafted with any type of osseous block-grafts in two-stage surgeries. Further, the review addresses how available success criteria were used within the studies. MATERIALS AND METHODS: The MEDLINE (PubMed) and EMBASE bibliographic databases were searched up to March 2017 for studies evaluating the long term results of implants placed in grafted areas. The search strategy was restricted to English language publications using combined terms which referred to the treatment method (implants placed in areas grafted with bone blocks), and follow-up characteristics (≥5 years and assessment of at least one parameter related to implant success criteria). To qualify for inclusion, studies should present outcome measurements indicating the success (or at least the survival) of the implants. RESULTS: The search strategy yielded 17 studies, which were included in this systematic review. These studies presented survival rates ranging from 88.7% (after 15 years follow-up) to 98.7% (after 5 years follow-up). Five studies presented data based on predefined success criteria with success rates ranging from 86.8% to 100%. In these studies, the term "success" was often not properly defined. CONCLUSION: The long term survival (≥5 years) of implants placed into block-grafted areas in two-stage surgeries was not lower than 75%, while success rates ranged from 86.8% to 100%. Although it was possible to identify published success criteria for implant follow-up, there is no broad consensus on how to report implant success in a consistent manner.
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".