Cryotherapy with liquid nitrogen versus topical salicylic acid application for cutaneous warts in primary care: randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Cryotherapy is widely used for the treatment of cutaneous warts in primary care. However, evidence favours salicylic acid application. We compared the effectiveness of these treatments as well as a wait-and-see approach. METHODS: Consecutive patients with new cutaneous warts were recruited in 30 primary care practices in the Netherlands between May 1, 2006, and Jan. 26, 2007. We randomly allocated eligible patients to one of three groups: cryotherapy with liquid nitrogen every two weeks, self-application of salicylic acid daily or a wait-and-see approach. The primary outcome was the proportion of participants whose warts were all cured at 13 weeks. Analysis was on an intention-to-treat basis. Secondary outcomes included treatment adherence, side effects and treatment satisfaction. Research nurses assessed outcomes during home visits at 4, 13 and 26 weeks. RESULTS: Of the 250 participants (age 4 to 79 years), 240 were included in the analysis at 13 weeks (loss to follow-up 4%). Cure rates were 39% (95% confidence interval [CI] 29%-51%) in the cryotherapy group, 24% (95% CI 16%-35%) in the salicylic acid group and 16% (95% CI 9.5%-25%) in the wait-and-see group. Differences in effectiveness were most pronounced among participants with common warts (n = 116): cure rates were 49% (95% CI 34%-64%) in the cryotherapy group, 15% (95% CI 7%-30%) in the salicylic acid group and 8% (95% CI 3%-21%) in the wait-and-see group. Cure rates among the participants with plantar warts (n = 124) did not differ significantly between treatment groups. INTERPRETATION: For common warts, cryotherapy was the most effective therapy in primary care. For plantar warts, we found no clinically relevant difference in effectiveness between cryotherapy, topical application of salicylic acid or a wait-and-see approach after 13 weeks. (ClinicalTrial.gov registration no. ISRCTN42730629).
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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 | 0.004 | 0.007 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".