Influence of repeated screw tightening on bacterial leakage along the implant–abutment interface
Bibliographic record
Abstract
OBJECTIVES: Bacterial penetration along the implant-abutment interface as a consequence of abutment screw loosening has been reported in a number of recent studies. The aim of this in vitro study was to investigate the influence of repeated tightening of the abutment screw on leakage of Streptococcus mutans along the interface between implants and pre-machined abutments. MATERIALS AND METHODS: Twenty pre-machined abutments with a plastic sleeve were used. The abutment screws were tightened to 32 N cm in group 1 (n=10 - control) and to 32 N cm, loosened and re-tightened with the same torque twice in group 2 (n=10). The assemblies were completely immersed in 5 ml of Tryptic Soy Broth medium inoculated with S. mutans and incubated for 14 days. After this period, contamination of the implant internal threaded chamber was evaluated using the DNA Checkerboard method. RESULTS: Microorganisms were found on the internal surfaces of both groups evaluated. However, bacterial counts in group 2 were significantly higher than that in the control group (P<0.05). CONCLUSION: These results suggest that bacterial leakage between implants and abutments occurs even under unloaded conditions and at a higher intensity when the abutment screw is tightened and loosened repeatedly.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".