Assessment of the Effect of Photodynamic Therapy on Treatment of Moderate-to-Severe Periodontitis; a Randomized Clinical Trial Study
Bibliographic record
Abstract
BACKGROUND & AIM: Photodynamic therapy is a localized non-invasive treatment modality for the periodontal disease. Some evidences have shown that this technique is effective in improving the treatment outcome. This study compared the effects of photodynamic therapy with and without scaling and root planing and scaling and root planing alone on the clinical parameters of the chronic periodontitis. MATERIALS & METHODS: In this single-blind, randomized clinical trial, 30 chronic periodontitis patients (10 for each modality) were selected and three different methods; photodynamic therapy alone (Group1) by FotoSan 630 system, scaling and root planning (SRP) alone (Group2), scaling and root planing combined with photodynamic therapy (Group3) were done for them randomly. Clinical parameters of probing pocket depth (PPD), bleeding on probing (BOP), and clinical attachment level (CAL) were measured at the baseline and 3, 6 and 12 weeks later. One-sided analysis of variance test was used to analyze PPD and CAL among the treatment groups in each time interval while the paired comparisons were carried out by employment of Dunnett’s test. The treatment groups were statically analyzed by the chi-square test regarding BOP. RESULTS: Before the treatment; no significant differences observed among treatment modalities regarding clinical parameters; while the differences were significant at three weeks (p<0.0001 for PPD and CAL; p<0.001 for BOP); six weeks (p<0.0001 for PPD and CAL, p<0.002 for BOP); and 12 weeks after the treatment (all: p<0.0001). The least PPD and CAL values and the most frequency of non-bleeding on probing status were measured for PDT+SRP modality at three, six, and twelve weeks after the treatment. CONCLUSION: Photodynamic therapy supported the clinical parameters of periodontitis similar to SRP; however, PDT combined with SRP demonstrated a better result than that of SRP alone. Therefore, PDT combined with SRP can be used to improve outcomes of clinical parameters of periodontitis as compared to SRP alone in the short-term.
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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".