Spectrum of Dermatological Manifestations among Travelers Presenting at aTravel Medicine Center in Western Nepal
Bibliographic record
Abstract
Introduction: Skin disorders are among the most common reasons for travelers to seek medical care during and after travel. There is limited data on the spectrum of dermatoses reported among travelers during travel especially in South Asian continent. Objective: To review the spectrum of skin disorder manifested among the traveler population attending a travel medicine hospital in western Nepal. Materials and Methods: We performed a prospective study of the travelers visiting The Canadian International Water and Energy Consultants (CIWEC) Hospital, and Travel Medicine Center in Pokhara with history of skin disorders. This study was done from September 2014 until December 2015. Results: A total of 130 (14.7%) patients presenting with dermatological manifestations were enrolled in the study. The most common diagnoses were bacterial skin infections 0.4%, arthropod bites 3.6% followed by animal bites and skin laceration due to trauma,each were 12.1%. Among patients with bacterial skin and soft tissue infections, pus culture and sensitivity were recorded in 13 patients. In almost fifty percent of our sample Staphylococcus aureus growth was seen, of which 38.5% were Methicillin Resistant Staphylococcus aureus. Conclusion: Bacterial skin and soft tissue infections, arthropod bites and animal bites were common reasons for travelers to seek medical consultations during travel in Nepal. This information will be useful for the medicine professionals while taking care of travelers and also while providing pre-travel consultation to the prospective travelers.
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 | 0.000 | 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".