Bone antiresorptive or antiangiogenic medication and dental implant treatment in osteoporotic patients : A systematic review
Bibliographic record
Abstract
Aim: The overall aim is to (i) analyze the prognosis of dental implant treatment concerning marginal bone loss (MBL) in patients undergoing or have undergone treatment with bone antiresorptive or antiangiogenic medication for osteoporosis (ii) and additional purpose to assess the available scientific literature in the first aim concerning the risk of getting medication-related osteonecrosis of the jaw (MRONJ) associated with dental implant installation. Material and methods: A systematic literature search was conducted in October 2021 in the following three databases; MEDLINE/PubMed, Cochrane Library and Web of Science. PRISMA 2009 Flow Diagram were used for the selection process, whereas the included studies were evaluated for quality assessment using Newcastle Ottawa Scale (NOS). Results: The search resulted in four included studies considering the eligibility criteria. The studies evaluated MBL in osteoporotic patients undergoing or have undergone oral bisphosphonate (BP) treatment before and/or during implant placement. MRONJ was also assessed in all four articles. Conclusions: The results of this present study do not indicate that patients undergoing or have undergone antiresorptive or antiangiogenic medication for osteoporosis are at an increased risk of MBL in dental implants during follow-up periods. The present data assessing the risk for developing MRONJ remains low for osteoporotic patients. Therefore, dental implant surgery is considered possible with success in osteoporotic patients receiving earlier mentioned medications. However additional studies are required to evaluate the effects on this patient group concerning osseointegration of dental implant regarding MBL.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".