Clinical Experience of CNC‐Milled Titanium Frameworks Supported by Implants in the Edentulous Jaw: A 3‐Year Interim Report
Bibliographic record
Abstract
BACKGROUND: The use of computer numeric controlled (CNC)-milled titanium frameworks is a new technique for framework fabrication, and few clinical reports have been made on this treatment modality. PURPOSE: The goal of this study was to report the clinical performance of implant-supported prostheses with CNC-milled titanium frameworks in the edentulous jaw and to compare the results with prostheses provided with conventional cast frameworks during the first 3 years of function. MATERIALS AND METHODS: A consecutive group of 126 edentulous patients were provided by random distribution with 67 prostheses with CNC-milled titanium frameworks in 23 upper and 44 lower jaws and 62 conventional prostheses with gold-alloy castings in 31 upper and 31 lower jaws. Radiographic 1-year data and clinical 3-year data were collected for both the titanium and control group. RESULTS: One prosthesis was lost in each group owing to loss of implants, and the overall 3-year prosthesis cumulative survival rate was 98.2% for both groups. Patients with smoking habits experienced significantly more implant failures than nonsmokers (p =.006). Few problems were observed. No metal fractures were seen in the test group, whereas two frameworks and one abutment screw fractured in the control group. Resin veneer fractures were the most common complication, with a slightly higher incidence observed in the control group. CONCLUSIONS: Computer numeric controlled-milled titanium frameworks can be used as an alternative to conventional castings in the edentulous jaw, presenting clinical performance similar to that of conventional cast frameworks during the first 3 years of function. key words: computer numeric controlled, implant supported, prostheses, titanium
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".