Influence of immediate loading on healing of implants installed with different insertion torques--an experimental study in dogs
Bibliographic record
Abstract
OBJECTIVE To evaluate the influence of different insertion torques on healing of implants loaded immediately or left unloaded. MATERIAL AND METHODS In six Labrador dogs, all mandibular premolars and molars were extracted. After 4 months of healing, flaps were elevated, and two implant sites were prepared at each side of the mandible. The distal sites were prepared conventionally while the mesial sites were underprepared by 0.3 mm. As a consequence, different final insertion torques of about 30 Ncm at the distal and >70 Ncm at the mesial sites were recorded. Healing abutments were applied to the left and transmucosal abutments to the right side. Flaps were sutured, crown preparation of the upper right second and third premolars was performed, and impressions were taken. Within 24 h, crowns were cemented both to implants and teeth in the right side of the mouth. After 4 months, the animals were sacrificed and ground sections obtained for histological evaluation. RESULTS A higher buccal bony crestal resorption and a more apical position of the coronal level of osseointegration were found at the loaded compared with the unloaded sites. MBIC% and percentages of peri-implant mineralized tissue (MB%) were higher at the loaded compared with the unloaded sites. Moreover, a higher MBIC% was found at the lower compared with the higher final insertion torque. CONCLUSIONS Immediate loading does not seem to have a negative effect on osseointegration. High torque values for the immediate loading procedures were not necessary. Probably, low torque values, were sufficient to obtain primary stability and hence may provide better osseointegration than high torque value.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".