Effectiveness of zygomatic implants using the externalized technique in the rehabilitation of atrophic maxillae. A systematic review with meta-analysis
Bibliographic record
Abstract
BACKGROUND: The objective of this work is to identify the effectiveness and summarize the scientific evidence of zygomatic implants using the externalized technique, as well as to evaluate the possible complications associated with this technique. MATERIAL AND METHODS: The study was registered in PROSPERO (CRD42022330060) and the searches were carried out in 6 databases (PubMed, Cochrane, LILACS, Scopus, Embase and Google Scholar), by two researchers individually. The aggregated data were subjected to statistical analysis using the MedCalc program for the variables: success rate and frequency of complications, using a 95% confidence interval. The risk of bias of the included studies was determined using the Newcastle-Ottawa Scale (NOS) tool. RESULTS: 912 articles were found in the initial search and 15 of them were included in this systematic review. A total of 1555 zygomatic implants and 1865 conventional implants were part of the study, with an overall success rate of 96.7% for zygomatic implants and 97.9% for conventional implants. There was no statistically significant difference between the survival of zygomatic implants using the externalized technique when compared with conventional implants (p=0.015). There was no significant heterogeneity between studies (p=0.89, I²=0%). Regarding complications, the most prevalent were sinusitis, which showed a proportion of 3.028% (CI95% = 1.053, 5.980%) and infections, which showed a proportion of 1.56% (CI95% = 0.358, 3.590%). Only three articles included presented a low risk of bias. CONCLUSIONS: Based on the present systematic review and with limited evidence, the use of zygomatic implants using the externalized technique proved to have a high implant success rate and few associated complications for the treatment of atrophic maxillae.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".