Onychomycosis in clinical practice: factors contributing to recurrence
Bibliographic record
Abstract
The treatment of onychomycosis has improved in recent years and many patients can now expect a complete and lasting cure. However, for up to 25% of patients, persistent disease remains a problem, thus presenting a particular challenge to the clinician. For these patients, it is obviously important to ensure that a correct diagnosis of onychomycosis has been made, as misdiagnosis will inevitably jeopardize the perception of therapeutic effectiveness. Although onychomycosis accounts for about 50% of all nail diseases seen by physicians, nonfungal causes of similar symptoms include repeated trauma, psoriasis, lichen planus, local tumours vascular disorders and inflammatory diseases. Predisposing factors that contribute to a poor response to topical and/or oral therapy include the presence of a very thick nail, extensive involvement of the entire nail unit, lateral nail disease and yellow spikes. However, poor penetration of systemic agents to the centre of infection, or the inability of topical agents to diffuse between the surface of the nail plate and the active disease below, probably contributes to this. Other factors contributing to recurrence may be related to the patient's family history, occupation, lifestyle or underlying physiology. In addition, patients with concomitant disease (e.g. peripheral vascular disease, diabetes) or patients who are immunosuppressed (e.g. those with human immunodeficiency virus/acquired immunodeficiency syndrome) are more susceptible to onychomycosis. In the elderly, the prevalence of onychomycosis may be as high as 60%, and increases with age; in this population, physical trauma plays a major role in precipitating recurrence, especially in patients with faulty biomechanics due to underlying arthritis and bone abnormalities. It is also possible that recurrence in some cases is due to early termination of treatment or use of an inappropriate dose, and these possibilities should be eliminated before further investigations are undertaken. There is good evidence to suggest that a combination of oral and topical therapies, when given at the same time, yield excellent clinical outcomes, although there remains a need for more effective topical agents with greater nail penetration and more effective oral antifungal agents.
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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 | 0.002 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".