Immediate versus Conventional Loading of Post‐Extraction Implants in the Edentulous Jaws
Bibliographic record
Abstract
PURPOSE: This retrospective study deals with the issue of how to realize the transition from a failing dentition to an implant-supported prosthesis. The main aim was to assess the reliability of immediate implant and immediate loading (IL) protocols in the edentulous jaws. A further aim was to investigate the role of patient-related, implant-related, and surgery-related secondary variables in the occurrence of implant failure. MATERIALS AND METHODS: Patients with at least a 4-year post-loading follow-up undergoing the transition from a failing dentition to an implant-supported prosthesis were retrospectively investigated. Primary variables of implant failure were immediate placement and IL. Secondary variables were categorized as demographic, anatomic, site, and prosthetically related. Cumulative survival rates (CSRs) were compared using the Kaplan-Meier survival estimate method. Predictors of failure were included in a multivariate Cox regression model to evaluate the simultaneous effects of multiple covariates and control for correlated observation. Crestal bone loss was also measured at the delayed and the immediately loaded implants. RESULTS: Five hundred nineteen implants rehabilitating 91 jaws in 80 patients were followed. The Kaplan-Meier survival estimate method showed that immediate implant and IL decreased the CSR significantly in the maxilla but not in the mandible. Some secondary variables were found to affect the CSR: maxillary location, age over 70 years, prostheses supported by only immediate implants or a majority of them, temporary cementation, implant diameter, and length. Crestal bone loss was not significantly related to the outcomes. CONCLUSIONS: The present data may provide clinical recommendations to the practitioner treating the transitional patient. In the mandible, the use of immediate implants and IL does not increase the failure rate. In the maxilla however, combining immediate placement and IL may significantly increase the failure rate.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".