Patient satisfaction and survival of maxillary overdentures supported by four or six splinted implants: a systematic review with meta-analysis
Bibliographic record
Abstract
Abstract Background Implant-supported overdentures offer enhanced mechanical properties, which lead to better patient satisfaction and survival rates than conventional dentures. However, it is unclear whether these satisfaction levels and survival rates depend on the number of implants supporting the overdenture. Therefore, this systematic review aimed to compare maxillary overdentures supported by four or six splinted implants in terms of patient satisfaction, implant survival, overdenture survival, and prosthodontic complications. Methods Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (PubMed), and EMBASE databases were systematically searched and complemented by hand searching from 2000 to 2019, employing a combination of specific keywords. Studies comparing the use of four versus six implants for supporting overdentures with at least one-year of follow-up after prosthesis installation and including ten fully edentulous patients were included. The risk of bias (RoB) was analyzed with Cochrane's RoB 2 and Newcastle–Ottawa tools. Implants and prosthesis survival rates were analyzed by random-effects meta-analysis and expressed as risk ratios or risk differences, respectively, and by the non-parametric unpaired Fisher's test. Results A total of 15 from 1865 articles were included, and reported follow-up times after implant placement ranged from 1 to 10 years. Irrespective of the number of implants used, high scores were reported by all studies investigating patient satisfaction. Meta-analysis and non-parametric Fisher's test showed no statistical differences regarding the survival rate of implants ( P = 0.34, P = 0.3) or overdentures ( P = 0.74, P = 0.9) when using 4 versus 6 splinted implants to support overdentures, and no significant differences regarding prosthodontic complications were found between groups. Randomized studies presented high RoB and non-randomized studies presented acceptable quality. Conclusions Within the limits of this systematic review, we can conclude that the bar-supported overdenture on four implants is not inferior to the overdenture supported by six implants for rehabilitating the edentulous maxilla, in terms of patient satisfaction, survival rates of implants and overdentures, and prosthodontic complications.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".