Bone Remodeling Around Implants with External Hexagon and Morse‐Taper Connections: A Randomized, Controlled, Split‐Mouth, Clinical Trial
Bibliographic record
Abstract
OBJECTIVES: To evaluate clinical, radiographic, microbiologic, and biomechanical parameters related to bone remodeling around implants with external hexagon (EH) and Morse-taper (MT) connections. MATERIALS AND METHODS: Twelve totally edentulous patients received four custom-made implants in the interforaminal region of the mandible. Two of those implants had the same macroscopic design, but different prosthetic connections. All patients received an immediate implant-supported prosthesis. Clinical parameters (periimplant probing pocket depth (PPD), modified gingival index (mGI), and mucosal thickness (MTh)) were evaluated at 12 months follow-up. The distance between the top of the implant and the first bone-to-implant contact (IT-FBIC) was evaluated on standardized digital peri-apical radiographs acquired at 1, 3, 6, and 12 months follow-up. Samples of the subgingival microbiota were collected 1, 3, and 6 months after implant loading and used for the quantification of Tanerella forsythia, Porphyromonas gingivalis, Aggragatibacter actinomycetemcomitans, Prevotella intermedia, and Fusobacterium nucleatum. Further, 36 computerized-tomography based finite element (FE) models were accomplished, simulating each patient under three loading conditions. RESULTS: The evaluated clinical parameters were equal for EH and MT implants. Mean IT-FBIC was significantly different between the tested connections (1.17 ± 0.44 mm for EH, and 0.17 ± 0.54 mm for MT, considering all evaluated time periods). No significant microbiological differences could be observed between tested connections. FE analysis showed a significantly higher peak of equivalent (EQV) strain (p = 0.005) for EH (mean 3,438.65 µε) compared to MT (mean 840.98 µε) connection. CONCLUSIONS: Radiographic periimplant bone loss depends on the implant connection type. MT connections showed less periimplant bone loss, compared to EH connections.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".