Confirmatory Testing Prior to Initiating Onychomycosis Therapy Is Cost-Effective
Bibliographic record
Abstract
BACKGROUND: Onychomycosis can be investigated by sampling. Information gleaned includes nail bed involvement, nail plate penetration, fungal viability, and species identification. Testing samples can confirm a diagnosis. While diagnostic testing is considered useful in directing therapy, a substantial number of clinicians do not confirm diagnosis prior to treatment. OBJECTIVES: The aim of this study is to quantify the benefit of confirmatory testing prior to treating toenail onychomycosis. METHODS: The cost of mycological cure (negative potassium hydroxide and negative culture) and the cost-effectiveness of confirmatory testing were determined using the average cost of potassium hydroxide (KOH), culture, periodic acid-Schiff (PAS), efinaconazole, ciclopirox, terbinafine, and itraconazole. Costs were obtained through literature searches, public domain websites, and telephone surveys to local pharmacies and laboratories. To represent the potential risks of prescribing onychomycosis treatment, the costs associated with liver monitoring, potential life-threatening adverse events, and drug-drug interactions were obtained through public domain websites, published studies, and product inserts. RESULTS: PAS was determined to be the most sensitive confirmatory test and KOH the least expensive. The overall cost of an incorrect diagnosis (no confirmatory test used) ranged between $350 and $1175 CAD per patient for treatment of 3 infected toenails. Comparatively, performing confirmatory testing prior to treatment decreases the overall cost to $320 to $930, depending on the therapy, physician, and test. CONCLUSIONS: It is preferred to diagnose onychomycosis prior to treatment. Furthermore, there are cost savings when confirmatory testing is performed before initiating treatment with both topical and oral antifungals in Canada.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".