Patient’s perception of timing concepts in implant dentistry: A systematic review
Bibliographic record
Abstract
Protocols for implant dentistry, most frequently include periods until healing of the extraction sockets and osseointegration of the implant. Deductional thinking imply that patients would prefer if treatment time in implant dentistry were reduced. AIM: What is the patient perception of immediate or early implant placement or loading in comparison with traditional, delayed placement, and/or loading assessed by patient-reported outcome measures, as evidenced in randomized controlled clinical trials or prospective controlled studies? MATERIAL AND METHODS: A systematic review was performed following the PRISMA guidelines with a literature search up to June 30. All hits were imported into Rayyan online software and analyzed by two authors for eligibility. Cochrane RoB2.0 and Newcastle-Ottawa Scale were used to evaluate risk of bias in the individual studies. RESULTS: Of the initially 1439 articles, 76 underwent full-text analysis and finally 40 articles, representing 35 cohort studies, were included. The quality evaluation demonstrated some concerns among most of the studies. CONCLUSION: a) There is no strong evidence to support that the time for implant placement or loading of implant-supported single or short-span reconstructions or overdentures influence patients´ discomfort, satisfaction with function or esthetics or overall satisfaction with the implant treatment. b) There is some evidence that studies including edentulous patients rehabilitated with implant-supported full-arch FDPs demonstrate more satisfied patients with immediate than for the early or delayed loaded implant reconstructions after short time, but the difference is not clear one year after treatment.
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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 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".