Implantatbehandling i atrofiske overkjever rekonstruert med hoftebenstransplantat
Bibliographic record
Abstract
English summary Dental implants in bone grafted maxilla. Assessment of pain experience and satisfaction with treatment – a pilot study 642 – 7. Background: Little is known about long-term results of implant treatment in the grafted maxilla concerning pain experience and satisfaction with treatment. Material and method: Bone grafting to the severely resorbed maxilla with a Le Fort I down fracture osteotomy and a 2-stage method (SAILER) was performed in 11 patients at Sørlandet Hospital, Arendal, Norway. A total of 79 dental implants were inserted, before rehabilitation with a fixed implant-supported prosthesis. Pain was recorded according to the short version of the McGill Pain Questionnaire (NSF-MPQ). A clinical and radiographic examination and evaluation of patient satisfaction was performed, before surgery and retrospectively in 9 of the 11 patients. Results and interpretation: No implants were lost and minor complications were recorded. Pain experience was low after a mean period of 33.6 months, compared to postoperative pain (NSF-MPQ: 0.3 versus 7.9). Evaluation of retrospective pain results seems reliable. Perceived masticatory function, phonetic ability and oral health related quality of life improved scientifically after treatment (p<0.05). The long-term results of implant treatment in the grafted maxilla, using a two-stage method, showed good results, according to patient satisfaction with treatment and pain experience.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.034 | 0.006 |
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".