Onychomycosis: Quality of Studies
Bibliographic record
Abstract
OBJECTIVE: The quality of original clinical trial publications pertaining to the use of oral antifungal agents to treat onychomycosis was evaluated using predetermined criteria. METHODS: The list of studies included in this analysis was determined by conducting a search in Medline. For each clinical trial, two independent reviewers each determined a composite score by evaluating a list of criteria that were felt to represent a good study, for example, randomization and blinding, prior sample size calculated, and treatment regimen clearly explained. A citation count was performed to determine whether higher-quality papers were cited more often than lower-quality papers. RESULTS: Forty-five studies were included in this quality analysis of study design. Of these, 27 were considered to be "high quality" (score greater than or equal to 11 out of 20). A significant correlation coefficient of 0.997 was found between the two reviewers (P < 0.00001). Higher-quality papers were cited significantly more often than lower-quality papers (P = 0.03). CONCLUSION: The scale that we use to evaluate the quality of onychomycosis studies has high interrater reliability. According to this scale, many published studies (18 out of 45) pertaining to treatments for onychomycosis do not meet the criteria required to be considered "high quality."
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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 | 0.302 | 0.573 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.022 | 0.024 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".