Complication and Failure Rates with Implant‐Supported Fixed Dental Prostheses and Single Crowns: A 10‐Year Retrospective Study
Bibliographic record
Abstract
PURPOSE: Clinical studies related to the long-term outcomes with implant-supported reconstructions are still sparse. The aim of this 10-year retrospective study was to assess the rate of mechanical/technical complications and failures with implant supported fixed dental prostheses (FDPs) and single crowns (SCs) in a large cohort of partially edentulous patients. MATERIALS AND METHODS: The comprehensive multidisciplinary examination consisted of a medical/dental history, clinical examination, and a radiographic analysis. Prosthodontic examination evaluated the implant-supported reconstructions for mechanical/technical complications and failures, occlusal analysis, presence/absence of attrition, and location, extension, and retention type. RESULTS: Out of three hundred ninety seven fixed reconstructions in three hundred three patients, two hundred sixty eight were SCs and one hundred twenty seven were FDPs. Of these three hundred ninety seven implant-supported reconstructions, 18 had failed, yielding a failure rate of 4.5% and a survival rate of 95.5% after a mean observation period of 10.75 years (range: 8.4-13.5 years). The most frequent complication was ceramic chipping (20.31%) followed by occlusal screw loosening (2.57%) and loss of retention (2.06%). No occlusal screw fracture, one abutment loosening, and two abutment fractures were noted. This resulted in a total mechanical/technical complication rate of 24.7%. The prosthetic success rate over a mean follow-up time of 10.75 years was 70.8%. Generalized attrition and FDPs were associated with statistically significantly higher rates of ceramic fractures when compared with SCs. Cantilever extensions, screw retention, anterior versus posterior, and gender did not influence the chipping rate. CONCLUSIONS: After a mean exposure time of 10.75 years, high survival rates for reconstructions supported by Sand-blasted Large-grit Acid-etched implants can be expected. Ceramic chipping was the most frequent complication and was increased in dentitions with attrition and in FDPs compared with SCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".