The Impact of Onychomycosis on Quality of Life: A Systematic Review of the Available Literature
Bibliographic record
Abstract
<b><i>Purpose:</i></b> Onychomycosis is a nail disorder that is increasing in prevalence worldwide. The psychological and social limitations caused by onychomycosis can potentially undermine the work and social lives of those experiencing these negative effects. This review aimed to evaluate the randomized controlled trials (RCTs) available in the current literature on the impact onychomycosis has on quality of life (QoL). <b><i>Methods:</i></b> A systematic review was performed using the databases PubMed, PsycINFO, Scopus, ClinicalTrials.gov, and Cochrane Library on July 18, 2017. Only RCTs with clinical effects described in English were included for review. <b><i>Results:</i></b> Ten RCTs reported QoL outcomes for patients suffering from onychomycosis. Treatment satisfaction was statistically significant from baseline to end of treatment in 100.0% (4/4) measures which reported on satisfaction with treatment; mental health was also significant in 100.0% (3/3), symptoms index rating in 100.0% (2/2), symptom frequency in 75.0% (3/4), overall problems in 75.0% (3/4), functional activities in 75.0% (6/8), appearance problems in 66.7% (2/3), symptom distress in 57.1% (4/7), and stigma in 40.0% (2/5). The OnyCOE-t<sup>TM</sup> and the NailQoL were the most used common outcome measures to describe QoL. <b><i>Conclusion:</i></b> The study sanctions that onychomycosis physically and psychologically distresses patients’ lives. Further research should include validated outcome measures to more effectively treat onychomycosis.
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".