Impact of the COVID-19 Pandemic on Dermatology Practice Worldwide: Results of a Survey Promoted by the International Dermoscopy Society
Bibliographic record
Abstract
Background The International Dermoscopy Society (IDS) conducted an online survey to investigate the impact of the COVID-19 outbreak on the daily practice of dermatologists working with patients with skin cancer, to collect data regarding the frequency of skin manifestations noticed by the members, and to obtain information about the use of teledermatology during the pandemic. Objective The aims of this study are to identify changes within dermatology departments during lockdowns, to evaluate the use of teledermatology during the COVID-19 pandemic, and to find the most frequent cutaneous manifestations associated with COVID-19. Methods All IDS members (approximately 160,000 members) were asked to fill in a questionnaire sent by email. The questionnaire was available in English and was anonymous, with a compiling time of less than 5 minutes. The survey was open for 30 days (from April 24, 2020, to May 24, 2020) and it could only be filled out once. Results Overall, 678 dermatologists responded to the questionnaire; of these, 334 members stated that there had been a reduction of more than 75% in daily work activity during the pandemic, 265 dermatologists worked fewer days per week, and 118 experienced telemedicine for the first time. Acrodermatitis was the most frequently observed skin manifestation (n=80), followed by urticarial rash (n=69), morbilliform rash (n=53), and purpuric manifestation (n=40). Regarding the role of teledermatology, 565 dermatologists reported an increased number of teleconsultations, and the number of melanomas diagnosed during the pandemic was practically 0 for 385 (56.8%) respondents. Conclusions This survey highlights that the outbreak had a negative impact on most dermatology services, with a significant reduction in consultation time spent for patients with chronic conditions, and an increased risk of missed melanoma and nonmelanoma skin cancer diagnosis. Moreover, our study confirms earlier findings of a wide range of skin manifestations associated with COVID-19. Conflicts of Interest None declared.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| 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".