Relationship between the <scp>CT</scp> Value and Cortical Bone Thickness at Implant Recipient Sites and Primary Implant Stability with Comparison of Different Implant Types
Bibliographic record
Abstract
BACKGROUND: Studies have shown that bone quality at the implant recipient site can influence primary stability. PURPOSE: The aims of this study were to explore the quantitative estimation of the primary stability of implants preoperatively using CT values and to examine the effect of different implant designs with recommended socket preparation on primary stability. MATERIALS AND METHODS: Forty-four fresh porcine femoral heads were prepared. The bone surrounding implant sockets was preoperatively evaluated by helical CT. Forty-four implants (φ 4.3 × 10 mm), 22 straight and 22 tapered, were placed according to the manufacturer's instructions. The insertion torque value (ITV), implant stability quotient (ISQ), and removal torque value (RTV) were recorded as indicators of primary implant stability. RESULTS: Significant correlations and linear relationships were found between the CT value and ITV, ISQ, and RTV for both straight and tapered implants (Spearman's correlation coefficient, p < .001; linear regression analysis, p < .01). Tapered implants had a significantly higher ITV than straight implants (analysis of covariance, p < .01). CONCLUSIONS: Obtained results suggest that the primary stability of implants could be quantitatively estimated using the CT value preoperatively, indicating the CT value of bone surrounding an implant can contribute considerably to implant planning and design choice in clinical situations.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".