The Role of Chlorhexidine on Endotoxin Penetration to the Implant‐Abutment Interface (<scp>IAI</scp>)
Bibliographic record
Abstract
PURPOSE: The aim of this study is to assess the risk of endotoxin penetration to the implant-abutment interface (IAI) of implants with Morse-taper connection and the effect of chlorhexidine in the prevention of such penetration. MATERIALS AND METHODS: Thirty implants with Morse-taper connection were divided into three groups (n = 10/group) based on type of inoculation of the internal aspect of the implant. Implants in Group 1 were inoculated with 1 μl Escherichia coli for 24 hours; supernatant was removed and 0.5 μl of sterile saline was added. Implants in Group 2 were inoculated with 1 μl E. coli for 24 hours; supernatant was removed and 0.5 μl 0.2% chlorhexidine solution was added. Implants in Group 3 were inoculated with 0.5 μl of sterile saline and served as controls. Following inoculation procedures, implants were connected to standard abutments, immersed in sterile culture media, and loaded with 200,000 cycles of 160 N in a wear simulator. Samples were collected from the supernatant solution of each implant for endotoxin identification at the beginning of the loading cycle (T0) and following 9 hours (T9), 18 hours (T18), 27 hours (T27), 36 hours (T36), 45 hours (T45), and 54 hours (T54). RESULTS: For Group 1 and Group 2, there were statistically significant differences between the endotoxin concentration at T0 and the endotoxin concentration at the subsequent sampling points (p < .05 Kruskal-Wallis with Bonferoni corrections for intragroup comparisons). There were no statistically significant differences between Group 1 and Group 2 at all sampling points. CONCLUSIONS: This study indicates that bacterial endotoxin can penetrate the IAI of implants with Morse-taper connection, and 0.2% chlorhexidine solution had no significant effect on that penetration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".