Outcome of peri‐implant maintenance care in patients with an implant‐supported lower denture—A 3.5‐year retrospective analysis
Bibliographic record
Abstract
BACKGROUND: Implant-supported overdentures represent a successful treatment for edentulous patients. As early diagnosis, detection and supportive care are considered key factors for the prevention of peri-implant diseases, consistent maintenance of these implants is becoming increasingly relevant. PURPOSE: This retrospective analysis evaluated a cohort of edentulous patients with a mandibular implant-supported overdenture over a period of 3.5 years during which the peri-implant tissues were assessed. MATERIALS AND METHODS: A total of 108 patients that had consistently adhered to the annual maintenance appointments was selected. The clinical peri-implant pocket probing depth (PiPPD) and peri-implant bleeding on probing score (PiBOP) were investigated. Data from the 3.5-year follow-up were compared to data from the baseline assessment. RESULTS: A 100% implant survival was reported after 3.5 years. The mean PiBOP showed a significant decrease over time (P = .028). The mean PiPPD was found significantly deeper for male patients both at baseline (P = .004) and 3.5-year follow-up (P < .001). Besides, the PiPPD for locator anchorages was found significantly deeper compared to ball anchorages at the 3.5-year follow-up (P = .026). CONCLUSION: In those patients that adhered to the annual maintenance visits during the 3.5 years after implant surgery a stable peri-implant condition was observed. As future consideration, the comparison of the clinical outcomes of patients participating in the maintenance program with those that did not would make this observation even more meaningful.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".