Global burden of skin and subcutaneous diseases and its association with socioeconomic status in children and adolescents: an analysis of the Global Burden of Diseases Study 2019.

Skin and subcutaneous diseases are one of the most common problems affecting the health of children and adolescents. The purpose of this study was to investigate the burden of skin and subcutaneous diseases among children and adolescents and its association with socioeconomic status. Data was obtained from the Global Burden of Disease Study 2019. The number of cases, incidence rate, number of deaths, and death rate in 204 countries and territories from 1990 to 2019 were extracted and stratified by age, sex, and socioeconomic status. In 2019, the global incidence and death rates of skin and subcutaneous diseases in children and adolescents were 57966.98 (95% Uncertainty Interval [UI] 53776.15 to 62521.24) per 100,000 and 0.21 (95% UI 0.13 to 0.26) per 100,000, respectively. From 1990 to 2019, the global incidence rate increased by 5.80% (95% UI 4.82-6.72%) and the death rate decreased by 43.68% (95% UI 23.04-65.27%). The incidence and death rates were negatively correlated with socioeconomic status. Incidence rates were not different between females and males, but death rates were higher among females than males. The highest incidence and death rates were found in the 1-4-year age group and < 1-year age group, respectively. The global burden of skin and subcutaneous diseases in children and adolescents was characterized by regional imbalances. The global burden of skin and subcutaneous diseases in children and adolescents from poorer regions requires more attention. This study provides strong evidence for global policymaking for childhood and adolescent diseases.

Prevalence of skin diseases among elderly prisoners in Taiwan: an examination of skin health in prison.

BACKGROUND: Although prisoner health is a topic of significant importance, it has received limited attention in epidemiological studies, likely due to challenges in obtaining data. Therefore, this study aimed to investigate the prevalence of skin diseases among elderly prisoners in Taiwan. METHODS: We examined the presence of skin diseases in 2215 elderly prisoners based on the International Classification of Diseases, 9th revision Clinical Modification (ICD-9-CM). Additionally, the most common types of skin diseases among elderly prisoners in Taiwan were identified. RESULTS: The prevalence of skin diseases among prisoners was estimated to be 55.03%. Elderly men prisoners exhibited a higher prevalence of skin diseases than the women prisoners. The most common skin diseases observed were as follows: contact dermatitis and other forms of eczema; pruritus and related conditions; cellulitis and abscesses; and urticaria. CONCLUSION: Skin diseases were identified in more than half of the elderly prisoners. The overall quality of life of elderly prisoners can be improved by addressing their skin health, which would contribute to the fulfilment of their basic human rights. CLINICAL TRIALS NUMBER: NA.

Recommendations on cutaneous and hematological manifestations of Sjögren's disease by the Brazilian Society of Rheumatology.

Sjogren's disease (SjD) is an autoimmune disease that is characterized not only by the sicca symptoms it causes but also by its systemic nature, which is capable of several and not yet fully understood extraglandular manifestations. To gain a clearer understanding of these manifestations as well as a better practical approach, a panel of experts from the Brazilian Society of Rheumatology conducted a systematic review and meta-analysis on the identification of epidemiologic and clinical features of the extraglandular manifestations present in ESSDAI (EULAR Sjogren´s syndrome disease activity index), followed by a voting panel with recommendations for clinical practice. This publication is complementary to others already published and covers cutaneous and hematological manifestations, with prevalence data generated by a meta-analysis of 13 clinical or laboratory manifestations and 6 clinical management recommendations.

Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata.

BACKGROUND: Sexually transmitted infections (STIs) pose a significant global public health challenge. Early diagnosis and treatment reduce STI transmission, but rely on recognising symptoms and care-seeking behaviour of the individual. Digital health software that distinguishes STI skin conditions could improve health-seeking behaviour. We developed and evaluated a deep learning model to differentiate STIs from non-STIs based on clinical images and symptoms. METHODS: We used 4913 clinical images of genital lesions and metadata from the Melbourne Sexual Health Centre collected during 2010-2023. We developed two binary classification models to distinguish STIs from non-STIs: (1) a convolutional neural network (CNN) using images only and (2) an integrated model combining both CNN and fully connected neural network (FCN) using images and metadata. We evaluated the model performance by the area under the ROC curve (AUC) and assessed metadata contributions to the Image-only model. RESULTS: Our study included 1583 STI and 3330 non-STI images. Common STI diagnoses were syphilis (34.6%), genital warts (24.5%) and herpes (19.4%), while most non-STIs (80.3%) were conditions such as dermatitis, lichen sclerosis and balanitis. In both STI and non-STI groups, the most frequently observed groups were 25-34 years (48.6% and 38.2%, respectively) and heterosexual males (60.3% and 45.9%, respectively). The Image-only model showed a reasonable performance with an AUC of 0.859 (SD 0.013). The Image + Metadata model achieved a significantly higher AUC of 0.893 (SD 0.018) compared to the Image-only model (p < 0.01). Out of 21 metadata, the integration of demographic and dermatological metadata led to the most significant improvement in model performance, increasing AUC by 6.7% compared to the baseline Image-only model. CONCLUSIONS: The Image + Metadata model outperformed the Image-only model in distinguishing STIs from other skin conditions. Using it as a screening tool in a clinical setting may require further development and evaluation with larger datasets.

Construction of a Risk Prediction Model for the Occurrence of Acute Skin Failure in Critically Ill Patients: A Prospective Study.

BACKGROUND: The risk factors for acute skin failure (ASF), a serious complication of the skin, are not fully understood. PURPOSE: This study was designed to explore the risk factors for ASF in critically ill patients and construct a clinical prediction model. METHODS: Intensive care unit patients were prospectively observed and assigned into two groups: with and without ASF. A logistic regression model was constructed, and its predictive power and clinical utility were evaluated. RESULTS: Of the 204 eligible patients enrolled as participants, 58 (28.43%) developed ASF. Sepsis, vasoactive drugs, and age were shown to be risk factors for ASF, whereas peripheral perfusion index ratio and albumin level were shown to be protective factors. The area under the receiver operating characteristic curve was 0.83. The maximum Youden index of the model was 0.39 (specificity: 0.87, sensitivity: 0.77). The Hosmer-Lemeshow test (p = .20) and calibration curve showed good fitness and predictive utility with respect to the model. CONCLUSIONS: The developed model effectively predicts ASF risk, allowing for the early identification of high-risk patients. Identifying risk factors such as sepsis, vasoactive drugs, and age and considering protective factors such as peripheral perfusion index and albumin levels may help optimize care plans. Clinical staff should pay special attention to these factors and their impact on skin health in critically ill patients.

Fundamental dermatology education of medical doctors at a regional hospital in Johannesburg, South Africa.

Introduction: dermatology is a prevalent field of global health and dermatological conditions are amongst the most frequent complaints affecting communities, yet dermatology has become an overlooked aspect of the medical school curricula and many medical schools have failed to provide doctors with training to manage these conditions confidently and adequately. This study aimed to determine the baseline dermatological knowledge of medical doctors and determine the influence of fundamental dermatology education on hospital medical staff at a regional hospital in Johannesburg, South Africa. Methods: the knowledge and confidence of 33 medical doctors were tested using a pre-test and post-test quasi-experimental design. Participants completed an online questionnaire followed by an image-based test consisting of 20 questions to determine their level of confidence in diagnosing and managing common dermatological conditions. The participants then attended a sixty-minute educational session based on common dermatological conditions. Following this, their level of confidence and knowledge on the subject was re-assessed using the same online test. Pre and post-intervention confidence and test scores were compared. Results: the pre-intervention test mean score was 67.11%. The post-intervention mean score was 92.50%. The difference between means (post-intervention - pre-intervention) ± SEM was 25.39 ± 4.81. The intervention significantly improved overall test scores (p-value < 0.0001). Many participants felt that their undergraduate training was insufficient in preparing them for the management of common dermatological conditions. Conclusion: the baseline knowledge and confidence of medical doctors in managing common dermatological conditions was poor and such educational interventions have significant value in improving the ability of medical doctors in managing common dermatological conditions. More time should be dedicated to dermatology training at an undergraduate level.

The Role of Quercetin as a Plant-Derived Bioactive Agent in Preventive Medicine and Treatment in Skin Disorders.

Quercetin, a bioactive plant flavonoid, is an antioxidant, and as such it exhibits numerous beneficial properties including anti-inflammatory, antiallergic, antibacterial and antiviral activity. It occurs naturally in fruit and vegetables such as apples, blueberries, cranberries, lettuce, and is present in plant waste such as onion peel or grape pomace which constitute good sources of quercetin for technological or pharmaceutical purposes. The presented study focuses on the role of quercetin in prevention and treatment of dermatological diseases analyzing its effect at a molecular level, its signal transduction and metabolism. Presented aspects of quercetin potential for skin treatment include protection against aging and UV radiation, stimulation of wound healing, reduction in melanogenesis, and prevention of skin oxidation. The article discusses quercetin sources (plant waste products included), methods of its medical administration, and perspectives for its further use in dermatology and diet therapy.

Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4.

Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors' notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.

Quality of life of dermatology outpatients and its associated factors in Halibet National Referral Hospital in Asmara, Eritrea.

Skin diseases are prevalent globally and can have detrimental effects on the individual's health-related quality of life (HRQoL). The treatment of dermatological patients typically focuses on clinical signs and symptoms and a subjective view of the impact of the disease on the patient's life. Assessing quality of life can help provide patients with better service, by acknowledging their real needs and interfering with treatment decisions. The aim of the study was therefore to assess quality of life of dermatology outpatients and its associated factors. An analytical cross-sectional study was conducted in the dermatology clinic of Halibet National Referral Hospital in Asmara, Eritrea. HRQoL data were collected between May 6 and August 18, 2022 using a validated standard tool (Skindex-29). Descriptive statistics, logistic regression and paired t-test were employed using Statistical Package for Social Sciences (Version-26.0). A total of 375 dermatology clinic out-patients with a median age of 29 (Interquartile range: 25) were included in the study. The most commonly seen skin diseases were eczema, seborrhoeic dermatitis and tinea pedis. Emotion, symptom, and functioning domains of HRQoL were severely impaired in 75.7%, 50.4% and 57.6% of all dermatology outpatients, respectively. More than half of the respondents (57.9%) had a severely impaired overall HRQoL. In the overall HRQoL, being a rural resident [Adjusted Odds Ratio (AOR) 1.98, 95% CI 1.18, 3.33] and presence of chronic illness (AOR 2.16, 95% CI 1.22, 3.82) were significantly associated with severely impaired overall quality of life. A significantly higher mean score (p < 0.001) was observed in emotion [Mean (M) = 55.60, Standard Deviation (SD) = 21.0] as compared to functioning (M = 46.89, SD = 21.2). On the other hand, significantly higher mean score (p < 0.001) was observed on symptom (M = 54.08, SD = 20.5) as compared to functioning (M = 46.89, SD = 21.2). Skin diseases severely affected the emotion, functioning, and symptom domains of health-related quality of life. This highlights the importance of providing physical and psychosocial support to patients with dermatologic problems.

Efficacy of an Artificial Intelligence App (Aysa) in Dermatological Diagnosis: Cross-Sectional Analysis.

BACKGROUND: Dermatology is an ideal specialty for artificial intelligence (AI)-driven image recognition to improve diagnostic accuracy and patient care. Lack of dermatologists in many parts of the world and the high frequency of cutaneous disorders and malignancies highlight the increasing need for AI-aided diagnosis. Although AI-based applications for the identification of dermatological conditions are widely available, research assessing their reliability and accuracy is lacking. OBJECTIVE: The aim of this study was to analyze the efficacy of the Aysa AI app as a preliminary diagnostic tool for various dermatological conditions in a semiurban town in India. METHODS: This observational cross-sectional study included patients over the age of 2 years who visited the dermatology clinic. Images of lesions from individuals with various skin disorders were uploaded to the app after obtaining informed consent. The app was used to make a patient profile, identify lesion morphology, plot the location on a human model, and answer questions regarding duration and symptoms. The app presented eight differential diagnoses, which were compared with the clinical diagnosis. The model's performance was evaluated using sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1-score. Comparison of categorical variables was performed with the χ2 test and statistical significance was considered at P<.05. RESULTS: A total of 700 patients were part of the study. A wide variety of skin conditions were grouped into 12 categories. The AI model had a mean top-1 sensitivity of 71% (95% CI 61.5%-74.3%), top-3 sensitivity of 86.1% (95% CI 83.4%-88.6%), and all-8 sensitivity of 95.1% (95% CI 93.3%-96.6%). The top-1 sensitivities for diagnosis of skin infestations, disorders of keratinization, other inflammatory conditions, and bacterial infections were 85.7%, 85.7%, 82.7%, and 81.8%, respectively. In the case of photodermatoses and malignant tumors, the top-1 sensitivities were 33.3% and 10%, respectively. Each category had a strong correlation between the clinical diagnosis and the probable diagnoses (P<.001). CONCLUSIONS: The Aysa app showed promising results in identifying most dermatoses.

Visual Learning Equity Initiative Enhances Preclinical Dermatologic Image Representation: A Cross-Sectional Study.

Despite growing diversity in the United States population, studies show that medical education lacks representation of conditions in darker skin tones. Given that medical conditions present differently in different skin tones, limited exposure to images of darker tones in medical training may contribute to incorrect or delayed diagnoses, perpetuating health inequities. This study examines the preclinical curriculum at the Georgetown University School of Medicine (GUSOM) to report on its image representation with respect to skin tone and to assess the impact of a student-driven initiative in achieving visual learning equity (VLE). Of 1050 preclinical images, 58.2% depicted conditions in light/white skin tones, 31.3% in medium/brown, and 10.5% in dark/black. The microbiology and pathology courses had the highest percentages of dark/black and medium/brown images. Infectious disease images made up 36.3% of all images with 54.6% light/white, 31.5% medium/brown, and 13.9% dark/black. Overall, the first images representing conditions were 63.5% light/white, 30.0% medium/brown, and 6.6% dark/black. When dark/black images were presented first, 64.3% were of infectious diseases, compared to 35.1% for medium/brown and only 28.4% for white/light first images that were infectious diseases. A significant increase in images of conditions in darker skin tones was observed in the IRD course 2022 compared to the IRD course 2020 (P<.001). Our study highlights an underrepresentation of darker skin tones compared to lighter skin tones in the GUSOM preclinical curriculum. A student-led initiative significantly increased the representation of darker skin tones in dermatologic images, demonstrating the potential impact of such efforts in achieving VLE in medical education.J Drugs Dermatol. 2024;23(7):519-524.  doi:10.36849/JDD.7992.

Study of Genetic Mutations and Their Association With the Development of Atopic Dermatitis and Other Skin Diseases.

The purpose of this study was to identify the heterogeneity of atopic dermatitis and to identify key genetic factors. This can lead to new approaches and personalized treatment strategies. I conducted a literature review of three scientific publication platforms (i.e., PubMed, Cochrane Library, Scopus) for records published between July 2011 and July 2023 using key words related to the genetics of atopic dermatitis. The high heritability and genetic pleiotropia of atopic dermatitis emphasize the importance of its genetic predisposition and interaction with concomitant diseases. The study also shows the role of various genes associated with immunity and inflammatory reactions, as well as the high heritability of atopic dermatitis, particularly among twins. Genetic mutations, specifically polymorphisms of genes encoding immune factors and inflammatory responses, determine an individual's predisposition to atopic dermatitis. Research findings also point to genetic aspects associated with other skin conditions such as psoriasis and vitiligo, confirming the existence of common genetic mechanisms between these diseases. Specifically, polymorphisms of the filaggrin gene have been found to be key genetic determinants of atopic dermatitis. I analyzed the genetic basis of atopic dermatitis, emphasizing the importance of genetic determinants and their interaction with the immune system and extracellular matrix. This study contributes to the understanding of the mechanisms of atopic dermatitis and opens new perspectives for individualized treatments.

Pyroptosis and its role in autoimmune skin disease.

Autoimmune skin disease is a kind of heterogeneous disease with complicated pathogenesis. Many factors such as genetic, infectious, environmental and even psychological factors may interact together to trigger a synergistic effect for the development of abnormal innate and adaptive immune responses. Although the exact mechanisms remain unclear, recent evidence suggests that pyroptosis plays a pivotal role in the development of autoimmune skin disease. The feature of pyroptosis is the first formation of pores in cellular membranes, then cell rupture and the release of intracellular substances and pro-inflammatory cytokines, such as interleukin-1 beta (IL-1ß) and IL-18. This hyperactive inflammatory programmed cell death damages the homeostasis of the immune system and advances autoimmunity. This review briefly summarises the molecular regulatory mechanisms of pyrin domain-containing protein 3 (NLRP3) inflammasome and gasdermin family, as well as the molecular mechanisms of pyroptosis, highlights the latest progress of pyroptosis in autoimmune skin disease, including systemic lupus erythematosus, psoriasis, atopic dermatitis and systemic scleroderma and attempts to identify its potential advantages as a therapeutic target or prognostic biomarker for these diseases.