What is the impact of bisphosphonate therapy upon dental implant survival? A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: A systematic review and meta-analysis are carried out to assess the scientific evidence that bisphosphonate therapy can decrease the success rate of dental implants. MATERIAL AND METHODS: The PubMed (Medline) database was used to search for articles published up until February 22, 2014. The meta-analysis was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). The Newcastle-Ottawa scale (NOS) was used to assess study quality. RESULTS: The combinations of search terms resulted in a list of 256 titles. Fourteen finally met the inclusion criteria and were thus selected for inclusion in the systematic review. Eight studies (six retrospective and two prospective) were included in the meta-analysis, with a total of 1288 patients (386 cases and 902 controls) and 4562 dental implants (1090 dental implants in cases and 3472 in controls). The summary odds ratio (OR = 1.43, P = 0.156) indicates that there is not enough evidence that bisphosphonates have a negative impact upon implant survival. According to the number need to harm (NNH), over 500 dental implants are required in patients receiving bisphosphonate treatment to produce a single implant failure. CONCLUSION: Our results show that dental implant placement in patients receiving bisphosphonates does not reduce the dental implant success rate. On the other hand, such patients are not without complications, and risk evaluation therefore must be established on an individualized basis, as one of the most serious though infrequent complications of bisphosphonate therapy is bisphosphonate-related osteonecrosis of the jaws. Given the few studies included in our meta-analysis, further prospective studies involving larger sample sizes and longer durations of follow-up are required to confirm the results obtained.
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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 | 0.028 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.025 | 0.063 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".