Clinical Diagnosis and Laboratory Testing of Abnormal Appearing Toenails: A Retrospective Assessment of Confirmatory Testing for Onychomycosis in the United States, 2022–2023
Bibliographic record
Abstract
Onychomycosis is an under-recognized healthcare burden. Despite the risk of misdiagnosis, confirmatory laboratory testing is under-utilized. Histopathologic examination with polymerase chain reaction (PCR) is currently the most effective diagnostic method; it offers direct detection and identification of a fungal invasion. In this retrospective cohort study, we assessed confirmatory testing results, with matching clinical diagnoses, in 96,293 nail specimens submitted during a 9-month period from 2022 to 2023. Toenail specimens were examined using fungal culture, histopathology and/or PCR. Clinical diagnoses were identified using the International Classification of Diseases 10th Revision codes. For clinically diagnosed onychomycosis patients, the overall positivity rate was 59.4%; a similar positivity rate (59.5%) was found in patients with clinically diagnosed non-fungal nail dystrophy. Performing a histopathologic examination with PCR was more likely to provide pathogen identification results than using fungal culture. Male patients had a higher rate of onychomycosis overall; however, female patients had more non-dermatophyte mold onychomycosis caused by Aspergillus. Clinically diagnosed onychomycosis patients with a co-diagnosis of tinea pedis were more likely to test positive for onychomycosis by PCR (odds ratio [OR]: 4.2; 95% confidence interval [CI]: 2.7–6.4), histopathology (OR: 2.5; 95% CI: 2.0–3.1) and fungal culture (OR: 3.2; 95% CI: 1.5–6.6). Our results support the use of confirmatory laboratory testing when there is a clinical diagnosis of onychomycosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".