Immediately loaded full arch implant rehabilitation and oral health‐related quality of life: A retrospective cohort study from primary dental care
Bibliographic record
Abstract
AIMS: This study evaluates patient-centered outcomes in patients undergoing full-arch rehabilitation, with immediate loading of implants. Using the Oral Health Impact Profile questionnaire pre-and post-treatment, it assesses the hypothesis that immediate full arch loading significantly improves quality of life. METHODOLOGY: A dataset was defined as: 20 consecutive patients from a research database who had undergone IFAL surgery (maxilla, mandible, or both) and definitive restoration by a single clinician, and completed the OHIP-14 questionnaire prior to treatment and after restoration. RESULTS: score 4.6. Differences were statistically significant (p = 0.00008). Greatest improvements were seen in psychological discomfort and disability, and pain. Worsening quality of life was shown by questions relating to speech in six patients and taste in three patients. CONCLUSION: This study demonstrates that overall IFAL significantly improves tooth-related quality of life. It suggests reasons for patients to seek treatment while providing evidence to manage expectations, such as possible implications on speech, thus supporting informed consent of future patients in a primary care setting.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".