Effect of scaling and root planing with and without minocycline hydrochloride microspheres on serum biomarkers and acute phase reactants
Bibliographic record
Abstract
Background This study tests the effects of scaling and root planing (SRP) vs SRP with minocycline hydrochloride microspheres (MMs) (SRP with MM) on serum biomarkers interleukin (IL)-1β, IL-6, tumor necrosis factor-α, and matrix metalloproteinase-8 and acute phase reactants hemoglobin A 1c (HbA 1c ), high-sensitivity C-reactive proteins and haptoglobin (Hp) in patients with stage II-IV grade B periodontitis. Methods Seventy participants were randomized to receive SRP (n = 35) or SRP+MM (n = 35). Serum was collected at baseline (before SRP), 1-month reevaluation visit, and 3- and 6-month periodontal maintenance visits. MMs were delivered to pockets 5 mm or larger immediately after SRP and immediately after the 3-month periodontal maintenance visit. Serum for acute phase reactants only was collected at the 9- and 12-month posttreatment follow-up. All outcomes were summarized using estimated marginal means back-transformed to the original response scale with 95% CIs. Results At 6 months, no statistical significance was yielded in either group for IL-6 ( P = .91), tumor necrosis factor-α ( P = .34), or matrix metalloproteinase-8 ( P = .34). IL-1β ( P = .06) was slightly higher in the SRP-alone group, suggesting a clinical impact with the addition of MM. Acute phase reactants were not statistically significant for high-sensitivity C-reactive proteins ( P = .59), HbA 1c ( P = .46), or haptoglobin ( P = .22) for either group. These outcomes continued at the 9- and 12-month posttreatment follow-up. Conclusions SRP alone and SRP+MM minimally reduced levels of cytokine biomarkers and acute phase reactants in self-reported systemically healthy patients with advanced stages of periodontitis. Thresholds for resolution of local clinical inflammation may not have been achieved in this study to result in a reduction of systemic inflammation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".