Immediate Provisionalization of NanoTite Implants in Support of Single‐Tooth and Unilateral Restorations: One‐Year Interim Report of a Prospective, Multicenter Study
Bibliographic record
Abstract
BACKGROUND: Clinical studies reporting immediate loading of endosseous implants for edentulous cases and for fixed partial restorations have been well documented with satisfactory survival rates. Implants with a recently developed, nanometer-scale surface topography (NanoTite, BIOMET 3i, Palm Beach Gardens, FL, USA), created by discrete crystalline depositions (DCD) of calcium phosphate nano-crystals onto a dual acid-etched (DAE) surface, show enhanced early fixation in preclinical studies when compared with DAE-surfaced implants. These outcomes suggest DCD-surfaced implants may be advantageous for immediate loading approaches. OBJECTIVE: The aim of this prospective, multicenter, observational study is to report clinical outcomes for DCD-surfaced implants placed in immediate functional support of single- and multi-unit restorations according to an immediate loading protocol. MATERIALS AND METHODS: One hundred eighty-five patients enrolled at 15 international study centers received a total of 335 implants supporting 216 immediate provisionalizations consisting of 128 single-tooth restorations and 88 fixed restorations. Of the 335 implants, 77% are located in posterior and 23% in anterior regions with 55.5% of the total in mandibles and 44.5% in maxillae. Patients were evaluated for implant mobility, gingival health, symptomatology, and radiographic outcomes. RESULTS: At the time of this 1-year interim report, a total of 17 failures have been observed in 11 patients, yielding a cumulative survival rate of 94.9%. CONCLUSION: Relative to other prospective, multicenter studies of immediately loaded implants with various surface enhancements, NanoTite implants perform comparatively well when immediately provisionalized with single-tooth and fixed restorations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".