Observational Study with a New Portable Cryosurgery Device, HYDROZID®, in Superficial Epidermal Lesions: An Indian Experience
Bibliographic record
Abstract
Background: , a new portable cryosurgery medical device using norflurane as a cryogen, was recently introduced in the Indian market. This paper reports the findings of the phase IV study conducted in India. Aims: This is a prospective phase IV study to evaluate its safety and efficacy in the treatment of superficial epidermal and dermal lesions. Methods: The study was conducted across 4 centres in India. The cryosurgery cycles were decided based on the skin lesion considered for the treatment. Safety and efficacy parameters were assessed at day 1, day 7, day 14, day 30 (±2) (end of treatment), and day 60 (±2) after the initial cryosurgery treatment. The local skin reactions scale, pain VAS scale, and Vancouver scale for assessment of pigmentation and scarring were used for the assessment of cutaneous reactions. Assessment of efficacy was done by evaluating the total disappearance of skin lesions at the end of the study visit. Results: Ninety-seven patients completed the study. The reported post-procedural pain was mild to moderate and subsided over the period of 24 hours. There was no pain observed in 84.76% of patients at the end of 24 hours. Complete disappearance of the lesion was seen in 47.4% of patients at the end of the study, while the reduction in the diameter of skin lesions by more than 50% was observed in 79.38% of patients. Conclusion: portable cryo device.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".