Comparison of the wound healing and complications of zipper type closure adhesive tape and stapler for surgical wound suture: A randomized control, single-centre, open-label trial.

Xkin closure is a newly developed medical suture device for lacerations and surgical wounds that can reduce scarring, pain and the risk of infection compared with conventional sutures or staplers. A randomized controlled study was performed to compare the wound healing effects and complications of Xkin closure with stapler closure. Fifty patients who underwent robot-assisted radical prostatectomy for prostate cancer were randomly assigned. Only the wound above the navel, which was extended to take out the prostate was targeted. The wound was examined at 2, 6 and 12 weeks after surgery, and the modified Vancouver Scar Scale (mVSS), scar height and side effects were assessed with a 3D skin analyser. Forty-six patients (23 Xkin, 23 Stapler) were analysed. The mVSS scores, vascularity and pliability were significantly lower in the Xkin group compared with the stapler group at the 12-week follow-up. No significant differences in the maximum peak and depth of the scars were detected between the two groups using 3D photographs at 12 weeks. Xkin is an effective wound closure method for improving scar outcomes. This method is expected to be widely used for surgical wounds and lacerations caused by trauma in daily life.

Automatic evaluation of Nail Psoriasis Severity Index using deep learning algorithm.

Nail psoriasis is a chronic condition characterized by nail dystrophy affecting the nail matrix and bed. The severity of nail psoriasis is commonly assessed using the Nail Psoriasis Severity Index (NAPSI), which evaluates the characteristics and extent of nail involvement. Although the NAPSI is numeric, reproducible, and simple, the assessment process is time-consuming and often challenging to use in real-world clinical settings. To overcome the time-consuming nature of NAPSI assessment, we aimed to develop a deep learning algorithm that can rapidly and reliably evaluate NAPSI, thereby providing numerous clinical and research advantages. We developed a dataset consisting of 7054 single fingernail images cropped from images of the dorsum of the hands of 634 patients with psoriasis. We annotated the eight features of the NAPSI in a single nail using bounding boxes and trained the YOLOv7-based deep learning algorithm using this annotation. The performance of the deep learning algorithm (DLA) was evaluated by comparing the NAPSI estimated using the DLA with the ground truth of the test dataset. The NAPSI evaluated using the DLA differed by 2 points from the ground truth in 98.6% of the images. The accuracy and mean absolute error of the model were 67.6% and 0.449, respectively. The intraclass correlation coefficient was 0.876, indicating good agreement. Our results showed that the DLA can rapidly and accurately evaluate the NAPSI. The rapid and accurate NAPSI assessment by the DLA is not only applicable in clinical settings, but also provides research advantages by enabling rapid NAPSI evaluations of previously collected nail images.

Genome-wide Association Study of Susceptibility Loci for Self-Reported Atopic Dermatitis and Allergic Rhinitis in the Korean Population.

BACKGROUND: Allergic diseases include atopic dermatitis (AD) and allergic rhinitis (AR), which are chronic, relapsing inflammatory disorders of the skin or mucosa that usually accompany immunoglobulin E-mediated immune responses. They are complex, multifactorial diseases with an etiology involving interactions between genetic and environmental factors. OBJECTIVE: We performed a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with allergic diseases in the Korean population. METHODS: A total of 8,840 samples were obtained from the Korean Association Resource Consortium dataset of the Korean Genome and Epidemiology Study Ansan-Anseong cohort. The allergic disease phenotype was determined based on self-reported physician diagnoses. After quality control, 8,823 subjects with 877,242 variants remained for the final analysis. The GWAS was performed using logistic regression analysis in an additive model adjusted for age and sex. RESULTS: A total of 636 patients with allergic disease and 8,176 controls were analyzed. Three SNPs were associated with allergic disease at a level of genome-wide suggestive significance (p<1.0×10-5) in the Korean population: rs7275360, located in neural cell adhesion molecule 2; rs698195; and rs3750552, located in family with sequence similarity 189, member A2. These polymorphisms were on chromosomes 21q21.1, 7q31.1, and 9q21.12, respectively. CONCLUSION: We identified 3 novel SNPs significantly associated with allergic diseases in the Korean population. Further research is required to confirm the association between these novel SNPs and allergic disease in the Korean population and in other ethnicities.

Artificial intelligence-based prescription of personalized scalp cosmetics improved the scalp condition: efficacy results from 100 participants.

Background: Scalp-related symptoms such as dandruff and itching are common with diverse underlying etiologies. We previously proposed a novel classification and scoring system for scalp conditions, called the scalp photographic index (SPI); it grades five scalp features using trichoscopic images with good reliability. However, it requires trained evaluators.Aim: To develop artificial intelligence (AI) algorithms for assessment of scalp conditions and to assess the feasibility of AI-based recommendations on personalized scalp cosmetics.Methods: Using EfficientNet, convolutional neural network (CNN) models (SPI-AI) ofeach scalp feature were established. 101,027 magnified scalp images graded according to the SPI scoring were used for training, validation, and testing the model Adults with scalp discomfort were prescribed shampoos and scalp serums personalized according to their SPI-AI-defined scalp types. Using the SPI, the scalp conditions were evaluated at baseline and at weeks 4, 8, and 12 of treatment.Results: The accuracies of the SPI-AI for dryness, oiliness, erythema, folliculitis, and dandruff were 91.3%, 90.5%, 89.6%, 87.3%, and 95.2%, respectively. Overall, 100 individuals completed the 4-week study; 43 of these participated in an extension study until week 12. The total SPI score decreased from 32.70 ± 7.40 at baseline to 15.97 ± 4.68 at week 4 (p < 0.001). The efficacy was maintained throughout 12 weeks.Conclusions: SPI-AI accurately assessed the scalp condition. AI-based prescription of tailored scalp cosmetics could significantly improve scalp health.

Automated mass screening and association rules analysis for comorbidities of psoriasis: A population-based case-control study.

Patients with psoriasis frequently have comorbidities, which are linked to higher mortality rates. An in-depth investigation of comorbidities and their effects on health can help improve the management of patients with psoriasis. We conducted a comprehensive and unbiased investigation of comorbidities in patients with psoriasis and explored the pattern of association between comorbidities. A nationwide population-based study included 384 914 patients with psoriasis and 384 914 matched controls between 2011 and 2021. We used automated mass screening of all diagnostic codes to identify psoriasis-associated comorbidities and applied association rule analysis to explore the patterns of comorbidity associations in patients with psoriasis. Patients with psoriasis had an increased risk of autoimmunity-related diseases such as inflammatory arthritis, Crohn's disease, type 1 diabetes, and acute myocardial infarction. The comorbidities of patients with psoriasis with a history of cardiovascular events demonstrated strong interrelationships with other cardiovascular risk factors including type 2 diabetes mellitus, essential hypertension, and dyslipidemia. We also found comorbidities, such as malignant skin tumors and kidney and liver diseases, which could have adverse effects of anti-psoriasis therapy. In contrast, patients with psoriasis showed a decreased association with upper respiratory tract infection. Our results imply that comorbidities in patients with psoriasis are associated with the systemic inflammation of psoriasis and the detrimental effects of its treatment. Furthermore, we found patterns of associations between the cardiovascular risk factors and psoriasis. Mass screening and association analyses using large-scale databases can be used to investigate impartially the comorbidities of psoriasis and other diseases.