Short Implants (5 to 8 mm) Versus Longer Implants (>8 mm) with Sinus Lifting in Atrophic Posterior Maxilla: A Meta‐Analysis of RCTs
Bibliographic record
Abstract
OBJECTIVE: The specific purposes of this study were (1) to undertake a thorough systematic review and meta-analysis based only on randomized clinical trials (RCTs) to compare the rates of survival and complications of short implants to those of long implants; (2) to compare the surgical time and cost of short implants to those of long implants. METHODS: RCTs were identified from the major electronic databases (MEDLINE, Embase and Cochrane Library) using the keywords "dental implant," "short implant" and "atrophic maxilla," and a quantitative meta-analysis was conducted. The survival rate of implants and complications were the primary outcome measures, and other parameters assessed included costs and surgical time. RESULTS: Seven RCTs that met the inclusion criteria included 554 implants (265 implants in the short implant group). There was no significant difference in survival rate between two groups (RR: 1.00; 95% CI: [0.97, 1.03]; p = .96; seven trials, 554 participants). Compared with long implant group, the short implant group had a lower complications and the effect measure was significant (RR: 0.58; 95% CI: [0.37, 0.90]; p = .02; seven trials, 554 participants). CONCLUSION: This systematic review showed that no difference between the survival rates of short implants (5-8 mm) and long implants (>8 mm); complications in short implants are lower than that in long implants. However, further studies are required to substantiate our findings.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.052 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".