Implant failures and age at the time of surgery: A retrospective study on implant treatments in 4585 edentulous jaws
Bibliographic record
Abstract
BACKGROUND: There is limited knowledge on the relationship between implant failures and patient age at implant surgery. PURPOSE: To further analyze and report long-term data on previously presented significant associations between implant failures and age at surgery in patients receiving treatment in the edentulous jaw. MATERIALS AND METHODS: A total of 4049 patients were provided with 24 781 implants during 4585 operations in edentulous jaws between 1986 and 2015 in one referral clinic. Patients were thereafter invited to be followed up until the termination of the study. All implant failures were recorded, and nonlinear spline statistical methods and calculations of survival curves for different age groups were used to analyze implant failures related to age at surgery. RESULTS: Ten-year age groups presented consistently higher overall survival rates with increasing age. The overall 10-year survival rates for treated jaws without failures ranged between 83.4% and 91.0% for different age groups. The risk of implant failures in 50-year-old patients was higher than in older patients within 15 years of follow-up (66/78 years; P < 0.05). The difference between young (<45 years), middle-aged (45-64 years), and old (>64 years) patients became more pronounced in patients included later in the study (2003-2015). CONCLUSIONS: Young edentulous patients presented an overall significantly higher risk of implant failure than did old patients. The risk decreased consistently from patients in the youngest age group (30-39 years) to those in the oldest age group (>79 years), with a more pronounced pattern for the patients included in the late period. This finding suggests a change in patient characteristics during the time of inclusion, but no causal explanations for the present observations have been established.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".