JMIR dermatology最新文献

Background: Artificial intelligence (AI) has many applications in numerous medical fields, including dermatology. Although the majority of AI studies in dermatology focus on skin cancer, there is growing interest in the applicability of AI models in inflammatory diseases, such as psoriasis. Psoriatic disease is a chronic, inflammatory, immune-mediated systemic condition with multiple comorbidities and a significant impact on patients' quality of life. Advanced treatments, including biologics and small molecules, have transformed the management of psoriatic disease. Nevertheless, there are still considerable unmet needs. Globally, delays in the diagnosis of the disease and its severity are common due to poor access to health care systems. Moreover, despite the abundance of treatments, we are unable to predict which is the right medication for the right patient, especially in resource-limited settings. AI could be an additional tool to address those needs. In this way, we can improve rates of diagnosis, accurately assess severity, and predict outcomes of treatment.

Objective: This study aims to provide an up-to-date literature review on the use of AI in psoriatic disease, including diagnostics and clinical management as well as addressing the limitations in applicability.

Methods: We searched the databases MEDLINE, PubMed, and Embase using the keywords "AI AND psoriasis OR psoriatic arthritis OR psoriatic disease," "machine learning AND psoriasis OR psoriatic arthritis OR psoriatic disease," and "prognostic model AND psoriasis OR psoriatic arthritis OR psoriatic disease" until June 1, 2023. Reference lists of relevant papers were also cross-examined for other papers not detected in the initial search.

Results: Our literature search yielded 38 relevant papers. AI has been identified as a key component in digital health technologies. Within this field, there is the potential to apply specific techniques such as machine learning and deep learning to address several aspects of managing psoriatic disease. This includes diagnosis, particularly useful for remote teledermatology via photographs taken by patients as well as monitoring and estimating severity. Similarly, AI can be used to synthesize the vast data sets already in place through patient registries which can help identify appropriate biologic treatments for future cohorts and those individuals most likely to develop complications.

Conclusions: There are multiple advantageous uses for AI and digital health technologies in psoriatic disease. With wider implementation of AI, we need to be mindful of potential limitations, such as validation and standardization or generalizability of results in specific populations, such as patients with darker skin phototypes.

Unlabelled: Analyses of women dermatology literature authorship from 2018 to 2022 reveal a slight increase in total female authors, female first authors, and female senior authors with no substantial immediate impact of COVID-19 on current trends, encouraging future examination of long-term effects and ongoing promotion of systemic initiatives to support gender equity.

Background: Androgenetic alopecia (AGA) is the most prevalent cause of hair loss around the world.

Objective: The purpose of this study was to evaluate the efficacy of laser stimulation with a 675-nm wavelength for the treatment of AGA in male and female Indian patients.

Methods: A total of 20 Indian healthy patients aged 23-57 years who presented a grade of alopecia stage I to stage V underwent one single pass with a 675-nm laser to the scalp area twice a week for a total of 8 sessions, followed by once a week for 4 sessions and once in 2 weeks for 2 sessions. There are 14 laser treatments in total. Macro- and dermatoscopic images have been acquired at T0 (baseline) and T1 (4 months). The vertex, frontal, and parietal areas of the scalp were evaluated. Many parameters were analyzed including hair count and hair density of terminal; mean thickness; vellus follicles; total follicular units; units with 1 hair, 2 hairs, 3 hairs, 4 hairs, and >4 hairs; unit density; and average hair/unit.

Results: The macroimages and dermatoscopic evaluations showed good improvement over the entire treated area, with a clear increase in the number of hairs and hair thickness. General parameters such as hair count and hair density showed a percentage increase of around 17%. The hair mean thickness parameters showed a significant (P<.001) percentage increase of 13.91%. Similar results were obtained for terminal and vellus hair: terminal hair count and hair density significantly (P=.04 and P=.01, respectively) increased by 17.45%, vellus hair count increased by 16.67% (P=.06), and the density of vellus hair increased by 16.61% (P=.06).

Conclusions: The study findings demonstrate that the 675-nm laser system improved AGA in Indian patients, facilitating the anagen phase and improving hair density and other positive hair parameters.

In 2023, JMIR Dermatology embraced papers treating all topics related to diseases of the skin, hair, and nails. This editorial aims to bring attention and recognize reviewers, staff, and authors for their contributions to the journal. JMIR Dermatology updated the Research Letter format and introduced the In Memorium article type to feature and celebrate highly accomplished and internationally recognized leaders in dermatology. We also summarize the 3 JMIR Dermatology publications from 2023 with the highest Altmetric scores and share what we look forward to in the coming year.

Background: Although several digital health interventions (DHIs) have shown promise in the care of skin diseases their uptake in Germany has been limited. To fully understand the reasons for the low uptake, an in-depth analysis of patients' and health care providers' barriers and facilitators in dermatology is needed.

Objective: The objective of this study was to explore and compare attitudes, acceptability, barriers, and facilitators of patients, dermatologists, and nurses toward DHIs in dermatology.

Methods: We conducted 6 web-based focus groups each with patients (n=34), dermatologists (n=30), and nurses (n=30) using a semistructured interview guide with short descriptions of DHIs described in the literature. A content analysis was performed using deductive constructs, following the unified theory of acceptance and use of technology framework, and inductive categories.

Results: Patients identified many positive performance expectancies, such as reduced travel times and improvement in follow-up appointments. Dermatologists also stated positive effects (eg, promotion of standardized care), but also negative implications of health care digitalization (eg, increased workload). All stakeholders reported that a DHI should bring additional value to all stakeholders. A lack of digital competence among patients was identified as the major barrier to adoption by all 3 groups. Nurses and dermatologists want apps that are easy to use and easy to implement into their daily routines. Trust in selected institutions, colleagues, and physicians was identified as a facilitator. Patients reported their dependence on the dermatologists' acceptance. All groups expressed concerns about data privacy risks and dermatologists stated insecurities toward data privacy laws.

Conclusions: To ensure successful digitalization in dermatology, apps should be user-friendly, adapted to users' skill levels, and beneficial for all stakeholders. The incorporation of dermatologists' perspectives is especially important as their acceptance may impact use among patients and nurses. DHIs should ensure and be transparent about data privacy. The found barriers and facilitators can be used for implementation strategies.

Epithelioid hemangioendothelioma (EHE) is a rare vascular tumor with metastatic potential. EHE can have single- or multiorgan involvement, with presentations ranging from asymptomatic disease to pain and systemic symptoms. The extremely heterogeneous clinical presentation and disease progression complicates EHE diagnosis and management. We present the case of a 24-year-old woman with two periauricular erythematous papules, leading to the discovery of metastatic EHE through routine biopsy, despite a noncontributory medical history. Histology revealed the dermal proliferation of epithelioid cells and vacuoles containing red blood cells. Immunohistochemistry markers consistent with EHE solidified the diagnosis. Although extremely rare, prompt diagnosis of EHE is essential for informed decision-making and favorable outcomes. Key clinical and histopathological findings are highlighted to aid dermatologists in diagnosing and managing this uncommon condition.

The prevalence of and factors associated with musculoskeletal (MSK) symptoms in patients with hidradenitis suppurativa (HS) have yet to be elucidated. Given the association between HS and inflammatory comorbidities, understanding the burden of MSK symptoms in patients with HS is crucial for patient-centered care. Our objective was to describe the prevalence of and factors associated with MSK symptoms in patients with HS. A cross-sectional study of 78 consecutive patients recruited between November 2021 and February 2023 with a dermatology-confirmed diagnosis of HS, irrespective of MSK symptoms, was performed. The average age of participants (n=78) was 37 (SD 12.2) years, and the average age at symptom onset was 23 (SD 12.1) years; 54% (n=42) of participants identified as women, and 46% (n=36) as men. The most common comorbidities included depression (n=17, 22%) and preexisting arthritis (n=12, 16%). Approximately 24% (n=18) of participants reported prolonged morning stiffness. In a multivariate regression, depression was significantly associated with morning stiffness (odds ratio [OR] 6.1, 95% CI 1.4-26.1; P=.02), while female sex was significantly associated with arthralgia (OR 19.1, 95% CI 1.6-235.2; P=.02). Every patient with depression reported arthralgia. We highlight the high prevalence of MSK symptoms among patients with HS and note the interplay between depression and MSK symptoms, with each one potentially contributing to the other.

Background: Cellulitis is a bacterial skin infection that tends to recur. Previous studies have identified several risk factors that may contribute to its pathogenesis. Obesity is an increasingly prevalent worldwide disease that has been associated with skin and soft tissue infections.

Objective: The aim of our systematic review and meta-analysis was to investigate the association of cellulitis with obesity.

Methods: The Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Web of Science databases were searched for the relevant studies from the inception of each respective database to March 13, 2021. Case-control, cross-sectional, or cohort studies that examined the odds or risk of increased BMI in patients with cellulitis were included. This study was carried out in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The Newcastle-Ottawa scale (NOS) was used to evaluate the risk of bias in included studies.

Results: In total, 9 case-control studies were included in our quantitative meta-analysis with a total of 68,148 study participants. A significant association was found between cellulitis and obesity (pooled odds ratio [OR] 2.67, 95% CI 1.91-3.71). No significant association was observed between cellulitis and being overweight (pooled OR 1.69, 95% CI 0.99-2.88). Patients with cellulitis were also found to have 1.63-fold increased odds of being male (pooled OR 1.63, 95% CI 1.12-2.38).

Conclusions: Our findings suggest that cellulitis is significantly associated with obesity. Maintaining a healthy BMI may be indicated for patients presenting with cellulitis.