Dermatology Practice Research Articles

Wait times for scheduling appointments with hospital affiliated dermatologists in New York City

Patients’ experience accessing dermatologic care is understudied. The purpose of this cross-sectional study was to examine current wait times for new patients to receive dermatological care in NYC. Websites at 58 accredited private and public hospitals in the five boroughs of NYC were reviewed to identify dermatology practices. Office telephone numbers listed on each website were called to collect information pertaining to whether the physician was accepting new patients, type of insurance accepted (public, private, both, or none), and the number of days until a new patient could be seen for an appointment. Data pertaining to the time kept on hold and availability of web-based booking were also collected. Mean waiting time for an appointment was 50 days [standard deviation, SD 66] – nearly 2 months, but the distribution was considerably skewed. The median waiting time was 19.5 days [Interquartile range, IQR 4–60]. The time kept on hold to make the appointment was negligible at about 1 min (63 s, SD = 77) but could take up to ~ 7 min. Two-thirds of dermatologists accepted private, Medicare, and Medicaid insurance (n = 228, 66%); a small number accepted only private insurance (n = 12, 4%) or no insurance at all (n = 16, 5%). The median waiting time for an appointment for the 228 providers that accepted Medicaid was 30.5 days (IQR = 5.0-73.25) while for providers who did not accept Medicaid (n = 116) the median wait time for an appointment was 13.0 days (IQR = 3.0–38.0). Just over half (56%) of the dermatologists allowed for appointments to be booked on their website (n = 193). This research highlights the necessity of incorporating new strategies into routine dermatology appointments in order to increase treatment availability and decrease healthcare inequality.

Natural language processing in dermatology: A systematic literature review and state of the art.

Natural Language Processing (NLP) is a field of both computational linguistics and artificial intelligence (AI) dedicated to analysis and interpretation of human language. This systematic review aims at exploring all the possible applications of NLP techniques in the dermatological setting. Extensive search on 'natural language processing' and 'dermatology' was performed on MEDLINE and Scopus electronic databases. Only journal articles with full text electronically available and English translation were considered. The PICO (Population, Intervention or exposure, Comparison, Outcome) algorithm was applied to our study protocol. Natural Language Processing (NLP) techniques have been utilized across various dermatological domains, including atopic dermatitis, acne/rosacea, skin infections, non-melanoma skin cancers (NMSCs), melanoma and skincare. There is versatility of NLP in data extraction from diverse sources such as electronic health records (EHRs), social media platforms and online forums. We found extensive utilization of NLP techniques across diverse dermatological domains, showcasing its potential in extracting valuable insights from various sources and informing diagnosis, treatment optimization, patient preferences and unmet needs in dermatological research and clinical practice. While NLP shows promise in enhancing dermatological research and clinical practice, challenges such as data quality, ambiguity, lack of standardization and privacy concerns necessitate careful consideration. Collaborative efforts between dermatologists, data scientists and ethicists are essential for addressing these challenges and maximizing the potential of NLP in dermatology.

Chatting Ethically: Practical Recommendations for Ethical Use of Large Language Models in Dermatology Practice, Research, and Education.

As large language model (LLM) utilization increases, developing ethical standards for their applications to supplement dermatologists is critically important. Here, we summarize primary applications of LLMs in dermatology, their ethical implications, and recommendations for appropriate use.

Review and Therapeutic Approach to Malalignment of the Great Toenails: A Common Condition That Is Uncommonly Diagnosed.

Malalignment of the great toenails is a common nail disorder that is uncommonly recognized in general practice. Review available literature on lateral malalignment of the great toenails to increase awareness of this underdiagnosed condition and provide management recommendations. A PubMed search was conducted using the terms "congenital malalignment toenail" and "malalignment great toenail". All articles were reviewed, and all relevant articles were included in this analysis. Thirty-four distinct articles encompassing 117 patients with similar clinical findings: lateral deviation of the great toenails with yellow brown dyschromia, thickening, and scalloping. Description of malalignment and terminology can vary, which may have led to exclusion of some relevant articles. Lateral malalignment is a common nail condition that is underappreciated and often misdiagnosed in general dermatologic and medical practice. This review aims to increase awareness to facilitate better care of these patients.

Frequency of Skin Biopsies for Psoriasis by Race and Ethnicity

This cross-sectional study evaluates the frequency of skin biopsies, as an indicator of diagnostic uncertainty, by race and ethnicity among patients with psoriasis seen in an academic dermatology practice.

Detection of terbinafine-resistant Trichophyton indotineae isolates within the Trichophyton mentagrophytes species complex isolated from patients in Hue City, Vietnam: A comprehensive analysis.

The Trichophyton mentagrophytes complex comprises a group of dermatophyte fungi responsible for various dermatological infections. The increasing drug resistance of this species complex, especially terbinafine resistance of Trichophyton indotineae, is a major concern in dermatologist practice. This study provides a comprehensive analysis of T. mentagrophytes complex strains isolated from patients in Hue City, Vietnam, focusing on their phenotypic and genetic characteristics, antifungal susceptibility profiles, and molecular epidemiology. Keratinophilic fungi from dermatophytosis culture samples were identified morphologically and phenotypically, with species and genotypes confirmed by internal transcribed spacer sequencing and phylogenetic analysis. Antifungal susceptibility testing was carried out to evaluate their susceptibility to itraconazole, voriconazole, and terbinafine. The 24% (n=27/114) of superficial mycoses were phenotypically attributed to T. mentagrophytes complex isolates. Trichophyton interdigitale, mainly genotype II*, was predominant (44.4%), followed by T. mentagrophytes genotype III* (22.2%), T. indotineae (14.8%), T. tonsurans (11.2%), and T. mentagrophytes (7.4%). While all isolates were susceptible to itraconazole and voriconazole, half of T. indotineae isolates exhibited resistance to terbinafine, linked to the Phe397Leu mutation in the SQLE protein. This study highlighted the presence of terbinafine-resistant T. indotineae isolates in Vietnam, emphasizing the need to investigate dermatophyte drug resistance and implement effective measures in clinical practice.

Identification of piRNA Expression Profiles in Vitiligo

Objective: Vitiligo is a systemic dermatological disorder characterized by skin depigmentation due to melanocyte damage and dysfunction. The treatment of vitiligo remains a challenging aspect in dermatological practice. PIWI-interacting RNAs (piRNAs), approximately 24–32 nucleotides in length, are crucial in the epigenetic regulation of developmental processes. However, research on piRNA expression profiling in vitiligo is limited. This study aimed to identify and characterize piRNAs in skin tissues from vitiligo patients and healthy controls. Methods: We compared and analyzed piRNA expression profiles of human vitiligo skin by RNA sequencing. Results and Discussion: Our findings revealed a pronounced preference for uridine (U) at the 5′ end of piRNAs, predominantly originating from repeat and other genomic regions. Notably, we detected 73 differentially expressed piRNAs between the patient and control groups, with 40 piRNAs upregulated and 33 downregulated in vitiligo patients. Bioinformatics analysis indicated that the genes responsible for piRNA production were more prevalent in metabolic processes and implicated in regulating the PI3K-Akt and AMPK signaling pathways. Conclusions: The elucidation of piRNA expression profiles enhances our understanding of their functional roles in the pathogenesis of vitiligo.

Advantages and Disadvantages of Using AI in Dermatology

ABSTRACTIntroductionArtificial intelligence (AI) in dermatology is both promising and challenging. This is important for clinicians to recognize most up‐to‐date knowledge and advancements.ResultsAdvantages include timely detection and diagnosis, enhanced accuracy, efficient triage, workflow automation, personalized treatment, outcome prediction, education support, telemedicine aid, research facilitation, cost‐efficiency, scalability, and drug development. However, limitations include generalizability issues, image quality variations, data requirements, interpretability concerns, patient acceptance, liability, multidisciplinary coordination challenges, data bias risks, lack of explainability, potential loss of clinical skills, security and privacy risks, resource intensiveness, integration challenges, validation and regulation gaps, and limited clinical assessment. Bridging these gaps requires robust ethical frameworks, interdisciplinary collaboration, education, regulation focusing on patient safety and privacy, standardized data sets, transparency, and human oversight.ConclusionDespite the challenges, AI holds significant potential to revolutionize dermatology practice, improving patient outcomes, healthcare accessibility, and research advancements. Further research and interdisciplinary collaboration are crucial to maximize AI's benefits and address its limitations effectively.

Ethics of dynamic and differential pricing for cosmetic procedures

Patient demand for procedures has increased in the evolving landscape of cosmetic dermatology. This has been fueled, in part, by social media and the growing normalization of cosmetic enhancements, developments that have led some patients to have potentially unrealistic expectations and place undue pressure on dermatologists to meet these often unrealistic demands. This pressure is exacerbated further by patients who are seen as difficult, demanding, and time-consuming and who may require extensive counseling. Physicians may adopt dynamic or differential pricing strategies to offset the additional time and effort that these patients require. We discuss the ethical concerns surrounding these pricing strategies in the cosmetic sphere, highlight the importance of transparency in pricing, and offer suggestions to promote clarity and fairness in cosmetic dermatology practices.

Categorizing Dermatological Malignancies Via Computational Methods

In this study, a machine learning model is developed to classify different types of cancer using convolutional neural networks (CNNs) for image processing. The core objective is to achieve a performance level comparable to that of dermatologists. The model is trained on a substantial dataset of medical images, enabling it to learn and recognize various characteristics indicative of different cancer types. By leveraging the power of CNNs, the model can process these images effectively, identifying subtle patterns and features that are often challenging to detect with the naked eye. The training process involves feeding the CNN with labelled images, enabling it to differentiate between benign and malignant cases with high accuracy. Through rigorous testing, the model demonstrates competence on par with experienced dermatologists, both in terms of sensitivity and specificity. This equivalence in performance is particularly significant as it underscores the model's potential to aid in clinical settings, providing reliable second opinions and enhancing diagnostic workflows. A user interface is also developed to allow input images to be analysed by the trained CNN model. This interface not only displays the model’s predictions but also provides essential metrics such as confidence scores and probability distributions. These metrics offer valuable insights into the model's decision-making process, aiding clinicians in understanding and trusting the AI's assessments. Overall, the findings suggest that convolutional neural networks hold substantial promise for improving cancer diagnosis. The model's high performance in classification tasks demonstrates its viability as a tool for supporting dermatologists in clinical practice. By reducing diagnostic errors and accelerating the identification process, this technology has the potential to significantly impact patient outcomes and advance the field of medical imaging and diagnostics. Keywords: Convolutional Neural Networks (CNNs); Cancer Classification; Medical Image Processing; Dermatology AI; Diagnostic Accuracy

Unmasking Acne: Azithromycin Edges Out Doxycycline in Randomized Trial at Tertiary Care Centre

Background: Acne vulgaris, a prevalent global condition, often necessitates antibiotic therapy. Doxycycline has been a mainstay treatment; however, recent research suggests azithromycin might be superior. Conflicting data and a lack of local studies regarding their comparative efficacy warrant further investigation. Objectives: This study aimed to compare the efficacy of oral azithromycin with oral doxycycline in treating acne vulgaris at a tertiary care hospital in Islamabad. Methods: A randomized controlled trial was conducted. Patients aged 14-30 years (n=190) were enrolled and randomly assigned to either azithromycin or doxycycline treatment groups. Baseline and post-treatment (12 weeks) Global Acne Grading System (GAGS) scores were assessed. Percent reductions in GAGS score were categorized into four groups (<25%, 25-50%, 51-75%, and >75%) for intergroup comparison. Written informed consent was obtained from all participants. Results: The mean patient age was 21.30±4.93 years, with a female predominance (male:female ratio 1:1.2). Most patients had Fitz-Patrick Skin Type-V (64.7%) compared to Type-IV (35.3%). Baseline GAGS scores were comparable between groups (p=0.612). Notably, post-treatment GAGS scores were significantly lower in the azithromycin group (p<0.001), demonstrated by a greater mean change (19.33±3.03 vs. 17.70±2.99; p<0.001) and percent reduction (81.87±8.74 vs. 75.97±11.12%; p<0.001) compared to doxycycline. Additionally, 75.3% of patients achieved an excellent reduction in GAGS score, with a significantly higher proportion observed in the azithromycin group (87.4% vs. 63.2%; p<0.001). Similar significant differences were observed across subgroups based on age, gender, and skin type. Conclusion: This study suggests that azithromycin demonstrates superior efficacy to doxycycline for acne vulgaris management, regardless of patient demographics or skin type. Its established better safety profile further supports its potential as a preferred therapeutic option in future dermatological practice. Keywords: Acne Vulgaris, Azithromycin, Doxycycline, Percent Reduction in GAGS Score

Optimizing CNN Kernel Sizes for Enhanced Melanoma Lesion Classification in Dermoscopy Images

Skin cancer, particularly melanoma, presents a significant global health challenge due to its increasing incidence and mortality rates. Current diagnostic methods relying on visual inspection and histopathological examination are subjective and time-consuming, often leading to delayed diagnoses. Recent advancements in machine and deep learning, particularly convolutional neural networks (CNNs), offer a promising avenue for transforming melanoma detection by automating precise classification of dermoscopy images. This study leverages a comprehensive dataset sourced from Kaggle, comprising 10,605 images categorized into benign and malignant classes. Methodologically, a custom CNN architecture is trained and evaluated using varying kernel sizes (3x3, 5x5, 7x7) to optimize melanoma lesion classification. Results demonstrate that smaller kernel sizes, notably 3x3, consistently yield superior accuracy of 93.00% and F1-scores of 96.00%, indicating their efficacy in distinguishing between benign and malignant lesions. The CNN model exhibits robust generalization capabilities with minimal overfitting, supported by high validation accuracy throughout training epochs. Comparative analysis with related studies highlights competitive performance, suggesting potential enhancements through advanced feature selection and optimization techniques. Despite these advancements, challenges such as dataset diversity and model optimization persist, particularly concerning underrepresented darker skin tones. The study underscores the transformative potential of CNNs in enhancing diagnostic accuracy and efficiency in dermatological practice, paving the way for improved patient outcomes through early detection and intervention strategies. Future research directions include refining segmentation techniques and expanding dataset evaluations to ensure the model's applicability across diverse clinical settings. Ultimately, this research contributes to advancing melanoma diagnosis by integrating cutting-edge deep learning methodologies with clinical practice, thereby addressing current limitations and driving forward innovations in dermatological image analysis.

Psoriasis in pediatric dermatological clinical practice: diagnosis and management

The relevance of this topic is confirmed by the widespread psoriasis prevalence. Psoriasis in children has severe forms growth and diagnostic difficulties. It is crucially important to examine histologically the skin especially in pediatric dermatological clinical practice. According to our observations Pityriasis Rubra Pilaris has become one of the most frequent dermatoses with which differential diagnosis of psoriasis has to be carried out. A clinical dermatosis observation in a 13-year-old girl is described. The disease was similar to the manifestations of Pityriasis Rubra Pilaris. The results of the affected skin biopsy study did not exclude this diagnosis. The clinical and morphological manifestations of the dermatosis could be effected by steroid therapy. Subsequent dynamic observation and histological examination allowed us to diagnose psoriasis. Current data is collected and presented. The choice of external therapy in pediatric practice is a controversial topic. Clinical results of the Activated Zinc Pyrithion external forms use in the psoriasis treatment are presented.

Two years of innovative dermatological care: the first public health consultation service for the transgender and gender diverse community in Argentina

BackgroundThe LGBTQI + community encounters distinct healthcare challenges due to discrimination and inadequate understanding of their needs. Dermatologists play a crucial role in addressing this by fostering inclusiveness, recognizing individual concerns, and adopting tailored approaches, thereby promoting a more equitable healthcare system. ObjectiveTo address the need for an inclusive healthcare space, the authors established the first dermatological practice exclusively for transgender and non-binary patients. This article presents a comprehensive two-year experience in a public hospital. MethodsThe authors conducted a retrospective and descriptive study, analyzing the medical records of 114 patients evaluated at a specialized dermatological practice between June 2021 and May 2023. Key variables assessed included self-identified gender, age, residence, access to private healthcare, human immunodeficiency virus status, hormonal treatment, surgical interventions, consultation motives, employment stability, and family support during gender expression transition. ResultsThe present study included 114 patients, 49.1% trans men, 39.5% trans women, and 8.8% non-binary individuals. Trans men, on average younger than trans women (p < 0.001), predominantly sought care for body modification-related concerns, particularly acne and androgenetic alopecia. In contrast, trans women exhibited a more diverse range of consultation motives typically unrelated to hormonal or surgical procedures. Study limitationsThis study is retrospective and limited in geographic scope. Additionally, the patient population lacked diversity in terms of Black ethnicity. ConclusionsThe pioneering dermatological practice for transgender and non-binary patients exemplifies healthcare equity and cultural competence. Effective LGBTQI + healthcare requires addressing unique dermatological concerns while fostering inclusiveness and continuous learning within the medical community.

Evaluating the Efficacy and Safety of Alpha-Hydroxy Acids in Dermatological Practice: A Comprehensive Clinical and Legal Review.

The global market for alpha-hydroxy acids (AHAs) is undergoing significant expansion, propelled by increasing demand for skincare products that address aging and environmental damage. This review focuses on the dermatological applications of AHAs, particularly in cosmetic formulations like chemical peels. We have identified that AHAs, such as glycolic and lactic acids, enhance skin rejuvenation by promoting apoptosis in skin cells, boosting collagen and elastin synthesis, and improving skin texture and luminosity. Our comprehensive analysis reveals a nuanced understanding of AHAs' effectiveness across various skin types and conditions, demonstrating their broad utility in treating conditions like acne, hyperpigmentation, and photoaging. However, the optimal concentrations for therapeutic efficacy with minimal side effects are yet to be precisely defined, necessitating further research. Regulatory compliance is underscored as essential for the safe application of AHAs in cosmetics, with international guidelines recommending specific concentrations and pH levels to minimize potential skin irritation. In Conclusion, the review highlights the effectiveness of AHAs in cosmetic dermatology, emphasizing the necessity for continued research and rigorous regulatory adherence to maximize their safe and beneficial application worldwide.

Management of small wounds: result of an Italian survey.

Infection at the surgical site is a frequent complication of office skin procedures, such as electrodesiccation, laser therapy, superficial peelings, curettage, cryotherapy, and incisional or shave biopsies. The use of antibiotic therapy in their prevention is highly controversial due to the raising phenomenon of antibiotic resistance. Italy ranks fifth among high-income countries for resistance to antibiotics, with a rate seven times higher than Scandinavia. In order to raise awareness on this alarming issue, a survey was planned to disclose the misuse of topical antibiotics in the dermatologic practice. A specifically designed questionnaire aimed at analyzing the topical management of skin lesions following common office skin procedures was distributed nationwide to physicians engaged in the management of small surgical wounds and then collected for statistical data processing and evaluation. A total of 1500 forms were distributed nationwide, 1340 (89.3%) of which were completed by dermatologists. Analysis of the collected data showed that more than 70% of the respondents always use topical antibiotics in the attempt of preventing possible post-procedure superinfections. This survey confirms not only an antibiotic misuse by a large part of the respondents, but above all the widespread erroneous belief that such therapeutic approach can be useful in averting the risk of infections postoperatively. These findings may obviously explain the spread of antibiotic resistance in Italy and confirm that there is an absolute need to raise awareness among dermatologists about the damage caused by the misuse of antibiotics in the management of small wounds.

Cons of dermatology practices opting out of Medicare and Medicaid insurances

Cons of dermatology practices opting out of Medicare and Medicaid insurances

Representation of Racially Minoritized Patients on Dermatology Private Practice Websites.

Images on the homepages of private practice dermatology websites often do not reflect the racial diversity of the metropolitan area in which each practice is located. A Google Maps scraper (Apify) was used to identify websites for private practices in 27 United States metropolitan areas selected from the 2020 U.S. Census list of 100 largest areas where non-white individuals makeup more than 50% of the population. Homepages from the top ten websites listed by the search engine were analyzed for images, use of non-English language, and mention of "Skin of Color" or "Ethnic Skin." One hundred seventeen websites were included. Two mentioned "Skin of Color" or "Ethnic Skin"; seven mentioned a non-English language. A significantly lower percentage of non-white-presenting patients (p < 0.001) and providers (p < 0.001) were pictured on the selected dermatology websites than reported in the Census. These findings suggest that the images on the homepages of private practice dermatology websites were not reflective of the racial diversity of the metropolitan area in which each practice is located. Private practice dermatologists should be mindful of how their services are represented online, as it may dissuade potential minoritized patients from seeking dermatologic care.

Integrating Artificial Intelligence in dermatology: progress, challenges and perspectives

Dermatology is currently seeing a substantial transformation due to the integration of Artificial Intelligence, particularly through the use of machine learning and convolutional neural networks. AI’s potential in dermatology is based on its ability to increase visual diagnosis, which is a core aspect of dermatological practice. This integration promises improvements in diagnostic precision, process efficiency, and personalized patient care. Although there has been some progress, there are still obstacles that need to be overcome. The ethical considerations surrounding the confidentiality of medical data, and the transparency of AI algorithms, are of utmost importance. Additionally, the availability of high-quality, annotated dermatological datasets is a limiting factor, alongside with the need for substantial technical investments and training for healthcare professionals. This article provides an extensive analysis of AI's impact on dermatology, presenting its applications in various domains and discussing the associated challenges. By highlighting AI’s potential and addressing its challenges, the article aims to contribute to a deeper understanding of how AI can enhance dermatological practices to achieve better patient outcomes.

Cadaveric Study: Sign of Leser-Trélat Associated with Breast Cancer

INTRODUCTION: Seborrheic keratoses (SK) is considered the most common benign skin lesions found in individuals that are middle aged and older. In dermatology practice, these lesions pose no threat to the individual but can be concerning for cosmetic and underlying malignancy reasons when they cover most of the skin surface. Of specific concern is the sign of Leser-Trélat, which has been documented as a cutaneous harbinger of underlying malignancy associated with proliferation of the size and/or number seborrheic keratoses. The rare sign is usually caused by malignancies such as gastrointestinal adenocarcinoma, but also lung, kidney, liver, or pancreatic cancer. This case report will describe the histology of the skin lesions in Lesar Trélat and analyze the current literature regarding its association with breast cancer, which is quite rare. RESOURCES: For this case study, a cadaver from the body donor program in Philadelphia College of Osteopathic Medicine (PCOM), South Georgia was used. Skin samples were sent to Colquitt Regional Center for processing, where sections were embedded in paraffin and were stained with H&amp;E stain. A pathologist reported histopathological findings of the skin lesions and the breast tissue samples. DESCRIPTION: Multiple SK lesions covering the face, abdomen, back, as well as both upper and lower extremities were observed in one of the cadavers in the gross anatomy laboratory. Due to the significant number of pigmented, verrucous lesions, the sign of Leser-Trélat was clinically postulated, later confirmed during routine laboratory dissection of the breast tissue. Histology sections confirmed not only multiple SK lesions in the skin, but also revealed an associated breast cancer in the form of an infiltrative ductal carcinoma. SIGNIFICANCE: The sign of Leser-Trélat is rare by itself and its association with breast cancer is even more uncommon. Once a clinician recognizes the multiple SK eruptions, the patient should be meticulously investigated for not only for an underlying GI malignancy, but also for other cancers like breast cancer. Additionally, a case report confirmed malignant melanoma that mimicked sign of Leser-Trélat, warranting the importance of further analyzing the pathology diagnosis when there is a proliferation of multiple seborrheic keratoses.Therefore, biopsy and histology diagnosis is crucial for ruling out both cutaneous as well as underlying malignancies and should be encouraged when patients present in clinic rather than assuming the typical benign characteristics of seborrheic keratosis.