Clinical and radiographic peri‐implant variables around short dental implants in type 2 diabetic, prediabetic, and non‐diabetic patients
Bibliographic record
Abstract
BACKGROUND: Clinical and radiographic status around short dental implants in patients with different glycemic levels remains unexplored. PURPOSE: To determine the clinical and radiographic bone level (RBL) around short dental implants in type-2 diabetes mellitus (T2DM), prediabetic, and non-diabetic patients. MATERIALS AND METHODS: Participants were grouped into three groups based on HbA1c levels: T2DM (Group-1); prediabetic patients (Group-2); and non-diabetic subjects (Group-3). Clinical recordings included the assessment of peri-implant plaque index (PI), bleeding on probing (BOP), probing depth (PD). Radiographic analysis included evaluation of standardized periapical digital radiographs using specialized software and image analyzer. RESULTS: Clinical peri-implant parameters including PI and BOP were statistically significantly higher in group-1 (P < .01) and group 2 (P < .05) as compared to group-3. Mean PD was statistically significantly higher in group-1 patients compared to group-3 (P < .01). Radiographic bone loss was significantly higher in both group-1 (P < .01) and group-2 (P < .05) patients as compared to patients in group 3. RBL showed statistically significant difference among T2DM patients even after adjusting for HbA1c, total cholesterol, and body mass index (P < .05) and statistically significant difference in prediabetic patients after adjusting for only HbA1c (P < .05). CONCLUSION: Clinical and radiographic peri-implant parameters are compromised around short dental implants in type-2 diabetes mellitus patients. Further longitudinal studies are needed to compare clinical performance of short dental implants with standard dental implants placed in patients with different glycemic level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".