The effects of periodontal treatment on diabetic patients: The <scp>DIAPERIO</scp> randomized controlled trial
Bibliographic record
Abstract
Abstract Aim To assess whether periodontal treatment can lead to clinical, glycaemic control and quality of life improvements in metabolically unbalanced diabetic patients (type 1 or type 2) diagnosed with periodontitis. Methods In this open‐labelled randomized controlled trial, diabetic subjects (n = 91) were given “immediate” or “delayed” periodontal treatment (full‐mouth non‐surgical scaling and root planing, systemic antibiotics, and oral health instructions). The main outcome was the effect on glycated haemoglobin (HbA1C) and fructosamine levels. The General Oral Health Assessment Index and the SF‐36 index were used to assess quality of life (QoL). Results Periodontal health significantly improved after periodontal treatment (p < 0.001). Periodontal treatment seemed to be safe but had no significant effects on glycaemic control based on HbA1C (adjusted mean difference with a 95% confidence interval (aMD) of 0.04 [−0.16;0.24]) and fructosamine levels (aMD 5.0 [−10.2;20.2]). There was no obvious evidence of improvement in general QoL after periodontal treatment. However, there was significant improvement in oral health‐related QoL (aMD 7.0 [2.4;11.6], p = 0.003). Conclusion Although periodontal treatment showed no clinical effect on glycaemic control in this trial, important data were provided to support periodontal care among diabetic patients. Periodontal treatment is safe and improves oral health‐related QoL in patients living with diabetes. ISRCTN15334496.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".