Onychomycosis in Qassim Region of Saudi Arabia: A Clinicoaetiologic Correlation
Bibliographic record
Abstract
BACKGROUND: Onychomycosis is mainly caused by dermatophytes, but yeasts and nondermatophyte molds have also been implicated, giving rise to diverse clinical presentations. The aetiological agents of the disease may show geographic variation. AIM: The aim of the present study was to isolate the causative pathogens and to correlate the various clinical patterns of onychomycosis with causative pathogens. MATERIALS AND METHODS: The study population comprised 170 patients with clinical suspicion of onychomycosis. Nail samples were collected for direct microscopic examination and culture. Clinical patterns were noted and correlated with causative pathogens. RESULTS: Out of total 170 cases included in the study, 140 (82.4%) were positive by microscopy and 77 (45.3%) showed positive mycological findings by both microscopy and culture. The male: female ratio was 1:2.5 and the mean age was 35.29 ± 16.47 years. Fingernails were involved in 51.9%, toenails in 28.6% and both fingernails and toenails in 19.5% of the 77 patients. The clinical types noted were distal lateral subungual onychomycosis (71.4%), proximal subungual onychomycosis (10.4%), total dystrophic onychomycosis (10.4%), superficial white onychomycosis (3.9%) and mixed pattern onychomycosis (3.9%). Yeasts were the most common pathogens isolated, being found in 36 patients (46.8%) followed by nondermatophyte molds which were isolated from 28 patients (36.4%) followed by dermatophytes which were isolated from 13 patients (16.9%). CONCLUSION: Distal lateral subungual onychomycosis was the most common clinical presentation. Candida albicans, Aspergillus species and Tricophyton rubrum were the major pathogens. A single pathogen can give rise to more than one clinical type.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".