Care and Aftercare Related to Implant‐Retained Dental Crowns in the Maxillary Aesthetic Region: A 5‐Year Prospective Randomized Clinical Trial
Bibliographic record
Abstract
AIM: To prospectively assess surgical and prosthetic care and aftercare related to the placement of implant-retained dental crowns after local bone augmentation in patients missing one tooth in the maxillary aesthetic region. METHODS: Ninety-three patients were randomly allocated to one of three local augmentation groups: (1) chin bone; (2) chin bone covered by a Bio-Gide® membrane (Geistlich, Wolhusen, Switzerland); and (3) Bio-Oss® covered by a Bio-Gide® membrane. After local augmentation, implant placement (ITI) and fabrication of an implant-retained dental crown (cemented metal-ceramic dental crown) was performed. Prosthetic and surgical care and aftercare was scored from the first visit until 5 years after the augmentation of the implant region. RESULTS: The need for care and aftercare was comparable between the local augmentation groups. Three implants were lost (5-year implant survival rate: 96.7%). Surgical aftercare was needed in 9% of patients and consisted of care related to peri-implant tissue problems. Prosthetic aftercare was needed more often: all patients needed periodic routine inspections; 63% needed supplemental oral hygiene support; and 16% needed additional prosthetic care, mainly consisting of fabricating new crowns (12%). CONCLUSION: Placing an implant in the maxillary esthetic region after local bone augmentation is a safe and reliable treatment option not needing much specific aftercare other than periodic preventive routine inspections, routine oral hygiene care, and fabrication of a new crown in one out of every eight to nine patients in 5 years. The method used for augmentation was irrespective of the patients' need for aftercare.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".