Patient-reported outcomes in patients with severe maxillary bone atrophy restored with zygomatic implant-supported complete dental prostheses: a systematic review
Bibliographic record
Abstract
Introduction and Objective: Zygomatic implants (ZI) offer a good and predictable alternative to reconstructive procedures of atrophic maxillae. The main objetive of this systematic review was to assess the effect of rehabilitation with zygomatic implants on patient's quality of life (QLP) using Patient Reported Outcomes Measures (PROMs).Materials and Methods: This review followed PRISMA guidelines. An automated electronic search was conducted in four databases supplemented by a manual search for relevant articles published until the end of January 2021. The Cochrane Collaboration Risk of Bias tool and the Newcastle-Ottawa Quality Assessment Scale were used to assess the quality of evidence in the studies reviewed.Results: General findings of this systematic review showed substantial increases in Oral health-related quality of life (OHRQoL) among patients restored with ZI and high scores in terms of general satisfaction, especially in chewing ability and esthetics. An overall survival rate of ZI was 98.3% after a mean follow-up time of 46.5 months was observed. Occurrence of 13.1% biological complications and 1.8% technical complications were reported.Conclusions: Patients rehabilitated with zygomatic implant-supported complete dental prostheses showed substantial improvements in OHRQoL and general satisfaction with the treatment received.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".