Peri‐Implantitis Associated with Type of Cement: A Retrospective Analysis of Different Types of Cement and Their Clinical Correlation to the Peri‐Implant Tissue
Bibliographic record
Abstract
BACKGROUND: The cementation of fixed implant-supported dental restorations involves the risk of leaving excess cement in the mouth which can promote biofilm formation in the peri-implant sulcus. As a result, an inflammation may develop. PURPOSE: The aim of the present study was to investigate the clinical effect of two different luting cements on the peri-implant tissue. MATERIALS AND METHODS: Within the scope of a retrospective clinical follow-up study, the prosthetic structures of 22 patients with 45 implants were revised. In all cases, a methacrylate cement (Premier Implant Cement [PIC], Premier® Dental Products Company, Plymouth Meeting, PA, USA) had been used for cementation. In 16 additional patients with 28 implants, the suprastructures were retained with a zinc oxide-eugenol cement (Temp Bond [TB], Kerr Sybron Dental Specialities, Glendora, CA, USA). These patients were evaluated in the course of routine treatment. RESULTS: In both populations, the retention time of the suprastructures was similar (TB 3.77 years, PIC 4.07 years). In the PIC cases, 62% of all implants had excess cement. In the TB cases, excess cement was not detectable on any of the implants. Bleeding on probing was significantly more frequent on implants cemented with PIC (100% with and 94% without excess cement) than on implants cemented with TB (46%). Pocket suppuration was observed on 89% of the PIC-cemented implants with excess cement (PIC without excess cement 24%), whereas implants with TB were not affected by it at all. The peri-implant bone loss was significantly greater in the PIC patients (with excess cement 1.37 mm, without excess cement 0.41 mm) than it was in the TB patients (0.07 mm). CONCLUSION: The frequency of undetected excess cement depends essentially on the type of cement used. Cements that tend to leave more undetected excess have a higher prevalence for peri-implant inflammation and cause a more severe peri-implant bone loss.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".