Marginal bone loss in ball versus locator attachments in implant-retained overdentures: systematic review and meta-analysis.
Bibliographic record
Abstract
OBJECTIVES: This systematic review compares the impact of ball and locator attachments on marginal bone loss in implant-retained overdentures in completely edentulous patients. METHOD AND MATERIALS: Following PRISMA guidelines, health science librarians completed literature searches from inception to 17 March 2023 in seven databases. There were 15,686 items exported to EndNote from Embase.com, CINAHL (EBSCO), Cochrane Library, Ovid MEDLINE-ALL, PubMed, Scopus, and Web of Science. Hand-searching added four more articles. After deduplication, 6,756 items were screened for eligibility. Twenty-nine studies were assessed by full text, of which ten studies, involving 424 subjects, were included in the review. Risk of bias assessment was conducted using the Cochrane risk-of-bias tool and the Newcastle-Ottawa scale. A meta-analysis was performed to synthesize and analyze the collective data from the selected studies. RESULTS: The included studies used diverse methodologies, implant systems, and loading protocols. Most studies reported no significant difference in marginal bone loss between ball and locator attachments. The meta-analysis revealed high heterogeneity. CONCLUSION: The results of this systematic review suggest that ball and locator attachments exhibit similar performance in terms of marginal bone loss in implant-retained overdentures. However, the limited number, risk of bias, and heterogeneity of studies highlight the need for standardized research designs and larger sample sizes in future investigations to draw more definitive conclusions.
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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 | 0.022 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".