Immediate loading of implants with mandibular overdentures: one-year clinical results of a prospective study.
Bibliographic record
Abstract
PURPOSE: The aim of this report is to present the implant and clinical outcomes of an immediate-loading protocol of TiUnite implants with mandibular overdentures in edentulous patients. MATERIALS AND METHODS: Two groups of edentulous patients were selected. Thirty-five consecutively treated patients received 70 immediately loaded TiUnite implants and 69 Brånemark implants as backup (1 patient received 1 Brånemark implant). The control group was a historical cohort that comprised 42 patients who received 111 Brånemark implants. All overdentures were supported by a resilient bar mechanism. Implant and clinical outcomes, including maintenance events for the first year, were recorded. RESULTS: Implant success rates were in excess of 95% with both protocols. Immediately loaded implants had less bone loss than did implants loaded with the conventional protocol (Mann-Whitney U test; P = .001). Patients in the immediate-loading group required more prosthodontic maintenance, consisting of overdenture remakes and laboratory relining of prostheses (Chi-square test; P < .05). Of note, 74% of patients in the immediate-loading group needed a reline to improve the denture seal around the bar housing (Chi-square test; P < .05). CONCLUSION: The favorable implant and bone level outcomes with immediate loading attest to its biologic success. The prosthetic maintenance encountered in the immediate-loading group does not negate the clinical potential of the treatment but rather suggests that the protocol may benefit from modifications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".