COMPARISON OF EFFICACY OF STEROIDS ALONE AND COMBINATION OF STEROIDS WITH HYALURONIDASE ON MOUTH OPENING IN ORAL SUBMUCOUS FIBROSIS PATIENTS
Bibliographic record
Abstract
BACKGROUND: Eventually Oral submucous fibrosis causes pronounced stiffness and failure to open the mouth. Objectives are to determine compare the efficacy of intralesional steroids alone and combination of steroids with hyaluronidase on mouth opening in oral submucous fibrosis. METHODS: It was a prospective comparative cohort study. Total of 74 patients both male and female having history of pan chewing and limited mouth opening and burning sensations were included in the study. Informed consent was taken and divided into two groups. Patients of group 1 were managed with mixture of betamethasone 1 ml and hyaluronidase 1500 IU and patients of group 2 were treated with only steroid injection of betamethasone 1 ml given intralesional, both injections were given intralesional, by multiple puncture technique and once a week and continued for twelve weeks (3 months). And data compiled and analyzed in SPSS-20. RESULTS: The mean age of group 1 was 40.027±6.97 years, and mean age of Group 2 was 37.351±5.48 years. In both groups, the greatest number of cases aged from 31-59 years. Compared to females in both groups, the majority of patients were males. In 32 (86.4)% patients of group 1 showed efficacy compared with 18[43.2] patients in group 2 [p-0.000]. Conclusion: In this study Intralesional steroids with hyaluronidase injections are more efficient for opening the mouth in patients with oral sub-mucus fibrosis.
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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) | 0.000 | 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 | 0.000 |
| 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".