Influence of Skeletal and Local Bone Density on Dental Implant Stability in Patients with Osteoporosis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Osteoporosis is a major skeletal disease affecting millions of people worldwide. Recent studies claim that patients with osteoporosis do not have a higher risk of early implant failure compared to non-osteoporotic patients. The aim of this study was to assess the effect of skeletal osteoporosis and local bone density on initial dental implant stability. MATERIALS AND METHODS: Seventy-three patients were recruited and were assigned (based on a Dual-energy X-ray Absorptiometry scan) to either the osteoporosis (Opr), osteopenia (Opn), or control (C) group. Forty nine of the 73 patients received dental implants and had implant stability measured by means of resonance frequency analysis (RFA) at implant placement and at prosthetic abutment placement. On the computerized tomography scans, the cortical thickness and the bone density (Hounsfield Units) at the sites of implant placement were measured. RESULTS: At implant placement, primary stability was on average lower in group Opr (63.3 ± 10.3 ISQ) than in group Opn (65.3 ± 7.5 implant stability qutient (ISQ)), and group C (66.7 ± 8.7 ISQ). At abutment placement, a similar trend was observed: group Opr (66.4 ± 9.5 ISQ) scored lower than group Opn (70.7 ± 7.8 ISQ), while the highest average was for group C (72.2 ± 7.2 ISQ). The difference between groups Opr and C was significant. Implant length and diameter did not have a significant effect on implant stability as measured with RFA. A significant correlation was found between local bone density and implant stability for all regions of interest. CONCLUSIONS: Implant stability seems to be influenced by both local and skeletal bone densities. The lower stability scores in patient with skeletal osteoporosis reinforce the recommendations that safe protocols and longer healing times could be recommended when treating those patients with dental implants.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".