Comparative Study of Pyogenic Granuloma Management with Conservative Sclerotherapy to Invasive Surgical Excision: A Randomized Clinical Trial
Bibliographic record
Abstract
Introduction: Pyogenic granuloma is a common benign reactive mucocutaneous lesion. Various treatment options like excision, sclerotherapy, cryotherapy, laser is widely practiced. Objective: This study was conducted to determine and compare the effect of 3% sodium tetradecyl sulfate to surgical excision in the management of oral pyogenic granuloma. Methods: The prospective randomized controlled trial was conducted among two equal randomly allocated groups (48 each) of histologically confirmed cases. Group A was treated by surgical excision while group B was treated by 3% STDS. Both groups were evaluated weekly for a month for pain and healing and 1st, 3rd & 6th for recurrence. Results: Pain score is statistically significant on 1st and 2nd week follow up. No clinical and statistical difference observed in pain on 3rd and 4th week. Clinically significant recurrence was observed in group ‘A’ (4.1%) than group ‘B’ on 3 months but was statistically insignificant. 1 recurrence was observed in group ‘B’ on 6 months whereas, 3 were reported from group ‘A’ in the same duration. Healing on 1st and 2nd weeks were comparable and statistically significant in both groups however the results failed to show any significant difference on 3rd and 4th week. The demographics showed mean age 30.97±12.4 years with 60.42% of incidence in female and the commonest site being mandibular anterior teeth (25%). Conclusion: Although, surgical excision is commonly practiced, it is associated with higher recurrence, increased pain score & prolonged healing period. On contrary, sclerotherapy with 3% STDS proved to be safer, minimally invasive and more accepted by patients with minimum postoperative morbidity.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".