JMIR dermatology最新文献

Unlabelled: The VISIA camera is a device that captures images of the skin, offering a detailed look at skin health by detecting changes that are often missed during physical exams and by the naked eye. It can help identify changes in UV damage, pigmentation, texture, fine lines, and redness. In dermatology, it has become a useful tool to build targeted treatment plans and follow patient progress over time. We present a case of a male patient diagnosed with diffuse scalp actinic keratoses who was treated with topical 5-fluorouracil (5-FU). VISIA images were taken before treatment, at one week, and again three months following therapy. The images were reviewed for changes in UV spots, texture, and other generalized spots. Results revealed a decrease in UV spots, a temporary improvement in texture followed by a later rise, and no significant change in generalized spots. This case highlights the value of VISIA imaging as an objective method for assessing treatment response and evaluating the effectiveness of 5-FU in the management of actinic keratoses.

Background: The integration of artificial intelligence (AI) into dermatology holds promise for education and diagnostic purposes, particularly through image generation, which has not been well studied.

Objective: This study aimed to assess whether AI image generation software can generate accurate images of classic dermatological conditions and whether they are recognizable as computer-generated.

Methods: Images of 10 dermatological conditions were generated using DALLE-2 and DALLE-3 programs. These images were randomized among clinical photographs and distributed to dermatology residents and attending physicians. Participants were instructed to (1) identify AI-generated images and (2) provide their diagnosis.

Results: AI-generated images were detected as computer-generated in 70.8% (85/120) of cases. Correct diagnoses were made based on all AI images 40.83% (49/120) of the time. This was significantly lower than the 72.0% (46/60) recognition rate for clinical photographs (P<.001). DALLE-2 images were diagnosed correctly less frequently (25.0%, 15/60) than DALLE-3 images (56.6%, 34/60; P<.001).

Conclusions: AI-generated images of common dermatological conditions are becoming more accurate. This holds great implications for education but should be used with caution as further research is needed with more advanced, specific, and inclusive training data. Limitations include the use of AI image generators created by a single parent company as well as the use of a limited set of diagnoses.

Unlabelled: This retrospective observational study was conducted to evaluate trends in synchronous teledermatology use across different levels of clinical complexity among Medicare beneficiaries, analyzing data from the Medicare Part B Physician/Supplier Procedure Summary Master Files; we founding that the growing use of teledermatology for complex visits highlights its potential as a long-term approach for improving dermatologic care.

Background: TikTok serves as a major source of information. Most content on common skin conditions comes from patients rather than clinicians. Hidradenitis suppurativa disproportionately affects Black women and faces frequent misdiagnosis and delayed care. Understanding content sources and messaging on TikTok remains important.

Objective: This study aimed to describe who produces HS TikTok content featuring Black skin and to quantify the treatments, products, and themes presented.

Methods: TikTok was searched using the phrase "hidradenitis suppurativa in black skin." Fifty videos were reviewed by a single evaluator. Data collected included creator type, board certification status, themes, products mentioned, and commercial involvement such as paid sponsorships or sales commissions.

Results: Among 50 videos, patients produced 24 (48%). Board-certified dermatologists produced 10 (20%) videos, and board-certified plastic surgeons produced seven (14%). Other creators, including nurse practitioners, beauty service providers, and individuals with unclear credentials, accounted for nine videos (18%). Seven videos included products linked to sales commissions, and two involved paid sponsorships. Treatment-related content dominated, appearing in 35 videos (70%). PanOxyl and Hibiclens were the most frequently mentioned products, appearing in five (10%) and six (12%) videos. Fifteen videos (30%) focused on explaining hidradenitis suppurativa, with nine created by healthcare professionals and six by patients. Remaining content emphasized lived experience and dietary approaches.

Conclusions: Patients dominate experiential and lifestyle-focused hidradenitis suppurativa content on TikTok, while physicians primarily provide treatment education. Limited dermatologist representation contributes to gaps between medical guidance and patient-driven narratives. Greater participation by dermatologists on TikTok offers an opportunity to address misinformation, discuss product safety, and provide evidence-based guidance alongside patient experiences.

Clinicaltrial:

Unlabelled: DermGPT demonstrated strong potential for improving answer clarity and conciseness in dermatology-related queries, while ChatGPT provided more robust source citations, enhancing trust in evidence-based responses.

Background: TikTok, with more than 2 billion users worldwide, has become an influential venue for health information, including dermatologic advice. However, concerns remain about the accuracy and impact of sunscreen-related content.

Objective: This study aimed to assess the quality, accuracy, and themes of popular TikTok videos about sunscreen; evaluate associations with creator credentials and promotional content; and identify implications for public health.

Methods: We conducted a cross-sectional content analysis of the 100 most-liked English-language TikTok videos generated by the search term "sunscreen." Metadata, creator characteristics, Global Quality Score (GQS), accuracy, attitudes, promotional disclosures, and reference use were extracted using a structured codebook. Thematic and statistical analyses (ie, Pearson correlations, χ2, 2-tailed t tests, and ANOVA) were conducted, with significance defined as P<.05.

Results: Of the top 100 videos, 74 (74%) expressed a positive attitude toward sunscreen, 35 (35%) were accurate, 57 (57%) were opinion based, and 6 (6%) were inaccurate. None of the videos cited references. GQS ratings were low: 40 (40%) videos were rated poor (score=1), 31 (31%) below average (score=2), and only 2 (2%) excellent (score=5). Promotional content appeared in 27 (27%) videos. Accuracy was negatively correlated with likes (r=-0.229; P=.02) and views (r=-0.242; P=.02), while GQS correlated positively with accuracy (r=0.270; P=.007) but not with engagement. Likes and views were strongly correlated (r=0.726; P<.001).

Conclusions: Despite broadly positive sentiment toward sunscreen, misinformation and promotional bias are common in highly engaged TikTok videos, and user engagement is often unrelated to accuracy or educational quality. Dermatologists and public health experts must proactively engage on social platforms to counter misinformation and promote reliable skin health information.

Background: Laser hair removal is a noninvasive cosmetic procedure that targets melanin in hair follicles through selective photothermolysis.

Objective: This study aims to evaluate the long-term efficacy and safety of the 755-nm alexandrite laser for axillary hair removal by comparing single- and dual-flash lamp systems.

Methods: In total, 40 women aged 20 to 35 years with Fitzpatrick skin types II and III participated in a study on laser hair removal for their axillae. Participants underwent 3 treatment sessions, each spaced 4 weeks apart, from January to April 2024. They were divided into 2 groups, both receiving treatments with an alexandrite laser (755 nm, 14 mm spot size). The first group was treated with a dose of 8 J/cm² using a single-flash lamp device operating at 5 Hz, with a pulse duration of 10 ms. The second group received doses between 9 and 11 J/cm² from a dual-flash lamp device operating at 2.5 Hz, with pulse durations ranging from 10 to 15 ms. Photographs and hair counts were taken at baseline and 1 month after the final session. A 2-tailed t test was used to assess statistical significance, and regression analysis evaluated treatment effects. Pain scores and side effects were assessed using a visual analog scale in a satisfaction questionnaire.

Results: The dual-flash lamp laser achieved an overall hair reduction of 94%, while the single-flash lamp laser resulted in a 91% reduction in the axilla. The difference was not statistically significant (P=.14). No serious adverse effects were reported with either device, indicating effective safety features.

Conclusions: The outcomes show that both systems provide similar results in terms of efficacy and safety, with no reported side effects, and results were maintained even after 6 and 12 months of follow-up.

Unlabelled: This single-center retrospective case series included 28 patients with alopecia (7 with lichen planopilaris, 7 with discoid lupus erythematosus, and 14 with alopecia areata). Trichoscopic markers were systematically compared across groups. Exclamation-mark hairs and yellow dots were characteristic of alopecia areata, whereas follicular ostia loss and white scarring were confined to lichen planopilaris/discoid lupus erythematosus, providing a simple and practical distinction between nonscarring and scarring alopecias in routine practice.

Unlabelled: Chronic spontaneous urticaria (CSU) is an autoimmune prompted skin disorder, whose hallmarks include the unpredictable onset of hives and itch. Symptom duration typically exceed 6 weeks, and flares can occur for up to 5 years or longer if untreated, impacting potentially any area of the body. The absence of obvious triggers and the variation in onset frequency often delays formal diagnosis which on average is approximately 2 years from first presentation. Initial standard of care is the use of low through to higher strength antihistamines in the first instance, with eventual escalation to prescription anti-inflammatory agents and potentially biologics once patients are under managed care. The societal impacts of delays in diagnosis are marked, with data suggesting CSU impacts up to 1% of the population, primarily of working age and with twice the prevalence in women. Herein, we advocate for the deployment of smartphone imaging and generative artificial intelligence technology to improve detection and early management of CSU through integrated self-care approaches. Such approaches embodying the tenets of P4 personalized medicine could have sustained impact on the disease through awareness campaigns, reducing the burden on the dermatology community and facilitating earlier access to curative therapeutic interventions.