Bovine‐originated xenografts versus synthetic bone grafting materials in lateral maxillary sinus floor augmentation: A systematic review and meta‐analysis
Bibliographic record
Abstract
AIMS: This study aimed to systematically compare the patients undergoing lateral MSFA therapies utilizing bovine-originated xenografts versus varied synthetic bone grafting materials. METHODS: Pubmed, Scopus, Embase, and Cochrane Library were searched up to April 2023, compensated by a manual search in selected journals. Studies reporting histological outcomes (residual bone graft, newly formed bone, non-mineralized tissue) and clinical outcomes (implant survival, ISQ value) were included. Several analyses were performed, including meta-analysis, sensitivity study, and Egger's regression tests. RESULTS: Sixteen clinical/randomized control trials were included in this systematic review, among which 12 were enrolled in a meta-analysis. The percentage of newly formed bone within the grafted sinuses by hybrid HA/TCP was significantly higher than those by xenografts (WMD 2.85, 95%CI [0.72; 4.99]), but those grafted by pure HA (WMD -1.72, 95%CI [-3.15; -0.29]) or TCP (WMD -7.10, 95%CI [-13.02; -1.17]) were significantly lower than xenograft counterparts. The residual bone graft and non-mineralized tissue yielded by synthetic HA, TCP, and HA/TCP showed no significant differences with the xenograft group. CONCLUSION: The chemistry of grafted bone substitutes in lateral MSFA influenced the quantity of newly formed bone. Those grafted with hybrid HA/TCP yielded the highest amount of new bone compared to bovine-originated HA. However, this influence was not significant on residual bone graft and non-mineralized tissue.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| 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".