Utility of the Siriraj Psoriatic Arthritis Screening Tool, the Thai Psoriasis Epidemiology Screening Tool, and the Early Arthritis for Psoriatic Patients Questionnaire to Screen for Psoriatic Arthritis in an Outpatient Dermatology Clinic Setting, and Identification of Factors Significantly Associated with Psoriatic Arthritis

Objective: To assess the clinical utility of the Psoriasis Epidemiology Screening Tool (PEST), the Early Arthritis for Psoriatic Patients (EARP) questionnaire, and the Siriraj Psoriatic Arthritis Screening Tool (SiPAT) as screening tools for psoriatic arthritis (PsA), and to identify factors significantly associated with PsA. Methods: This cross-sectional study included adult psoriasis patients who attended the outpatient clinic at Siriraj Hospital and had not been diagnosed with PsA during 1 March 2017 to 28 February 2018. Participants completed the EARP, PEST, and SiPAT, after which musculoskeletal history was taken, and examination and radiography were performed. Diagnosis of PsA was based on Classification Criteria for Psoriatic Arthritis. Receiver operator characteristic (ROC) curves, sensitivity, and specificity were used to determine assessment tool performance. Logistic regression analysis was used to identify factors associated with PsA. Results: Eighty-seven patients with a mean age of 45.90±14.75 years were enrolled. Twenty-six (29.88%) patients were diagnosed as PsA. According to ROC values, EARP had the best discriminative power (0.83) for distinguishing between psoriatic patients with and without PsA (SiPAT: 0.78, PEST: 0.77). SiPAT had the highest sensitivity (92.3%), followed by EARP (84.6%) and PEST (50.0%); whereas, PEST had the highest specificity (82.0%), followed by EARP (62.3%) and SiPAT (54.1%) for detecting PsA. Multivariate analysis revealed body surface area involvement >10% to be the only independent predictor of PsA (OR: 2.99, 95% CI: 1.09-8.21). Conclusion: SiPAT is an effective and simple to use tool for screening PsA in psoriasis patients. Body surface area involvement >10% is a significant predictor of PsA

Factors Influencing Willingness to Pay for Teledermatology among Patients with Psoriasis

Objective: To determine the proportion of patients with psoriasis prepared to pay for TD. Attitudes and factors influencing their willingness to pay (WTP) were evaluated. Materials and Methods: This cross-sectional study was conducted from July 2020 to October 2021. Adult patients with psoriasis completed a 2-page self-administered questionnaire. Results: Of 200 patients, 133 (66.5%) were unfamiliar with TD. However, 144 (72%) were prepared to pay for TD if it were introduced. The majority of patients answered that 300 Bath was the maximum price that they were willing to pay for TD service. Compared with traditional in-person visits, the significant positive influencing factors on WTP were TD’s quicker delivery of treatment, lower costs, and non-inferiority to usual care. Multivariate analysis showed that the independent factors for WTP were higher educational levels, elimination of out-of-pocket, in-hospital visit expenses, owning a business, TD options suited to psoriasis, and no adverse effects on the patient-doctor relationship. Conclusion: Knowing patients’ attitudes toward TD and the factors influencing their WTP is essential for developing efficient services. Data from this study can be used to develop successful TD services for patients with psoriasis

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

Diabetic eye disease is one of the fastest growing causes of preventable blindness. With the advent of anti-VEGF (vascular endothelial growth factor) therapies, it has become increasingly important to detect center-involved diabetic macular edema (ci-DME). However, center-involved diabetic macular edema is diagnosed using optical coherence tomography (OCT), which is not generally available at screening sites because of cost and workflow constraints. Instead, screening programs rely on the detection of hard exudates in color fundus photographs as a proxy for DME, often resulting in high false positive or false negative calls. To improve the accuracy of DME screening, we trained a deep learning model to use color fundus photographs to predict ci-DME. Our model had an ROC-AUC of 0.89 (95% CI: 0.87-0.91), which corresponds to a sensitivity of 85% at a specificity of 80%. In comparison, three retinal specialists had similar sensitivities (82-85%), but only half the specificity (45-50%, p<0.001 for each comparison with model). The positive predictive value (PPV) of the model was 61% (95% CI: 56-66%), approximately double the 36-38% by the retinal specialists. In addition to predicting ci-DME, our model was able to detect the presence of intraretinal fluid with an AUC of 0.81 (95% CI: 0.81-0.86) and subretinal fluid with an AUC of 0.88 (95% CI: 0.85-0.91). The ability of deep learning algorithms to make clinically relevant predictions that generally require sophisticated 3D-imaging equipment from simple 2D images has broad relevance to many other applications in medical imaging

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning

Center-involved diabetic macular edema (ci-DME) is a major cause of vision loss. Although the gold standard for diagnosis involves 3D imaging, 2D imaging by fundus photography is usually used in screening settings, resulting in high false-positive and false-negative calls. To address this, we train a deep learning model to predict ci-DME from fundus photographs, with an ROC–AUC of 0.89 (95% CI: 0.87–0.91), corresponding to 85% sensitivity at 80% specificity. In comparison, retinal specialists have similar sensitivities (82–85%), but only half the specificity (45–50%, p < 0.001). Our model can also detect the presence of intraretinal fluid (AUC: 0.81; 95% CI: 0.81–0.86) and subretinal fluid (AUC 0.88; 95% CI: 0.85–0.91). Using deep learning to make predictions via simple 2D images without sophisticated 3D-imaging equipment and with better than specialist performance, has broad relevance to many other applications in medical imaging

Catching the therapeutic window of opportunity in early initial-onset Vogt�Koyanagi�Harada uveitis can cure the disease

Purpose: Vogt�Koyanagi�Harada (VKH) disease is a primary autoimmune granulomatous choroiditis that begins in the choroidal stroma. The aim of this review was to gather a body of evidence for the concept of a window of therapeutic opportunity, defined as a time interval following initial-onset disease during which adequate treatment will substantially modify the disease outcome and possibly even lead to cure, similar to what has been described for rheumatoid arthritis. Methods: We reviewed the literature and consulted leading experts in VKH disease to determine the consensus for the notion of a therapeutic window of opportunity in VKH disease. Results: We found a substantial body of evidence in the literature that a therapeutic window of opportunity exists for initial-onset acute uveitis associated with VKH disease. The disease outcome can be substantially improved if dual systemic steroidal and non-steroidal immunosuppressants are given within 2�3 weeks of the onset of initial VKH disease, avoiding evolution to chronic disease and development of �sunset glow fundus.� Several studies additionally report series in which the disease could be cured, using such an approach. Conclusions: There is substantial evidence for a therapeutic window of opportunity in initial-onset acute VKH disease. Timely and adequate treatment led to substantial improvement of disease outcome and prevented chronic evolution and �sunset glow fundus,� and very early treatment led to the cure after discontinuation of therapy in several series, likely due to the fact that the choroid is the sole origin of inflammation in VKH disease. © 2018 The Author(s

Erratum to: Changes in patterns of uveitis at a tertiary referral center in Northern Italy: analysis of 990 consecutive cases

Erratum to: Changes in patterns of uveitis at a tertiary referral center in Northern Italy: analysis of 990 consecutive case

Polymorphic Eruption of Pregnancy Presented with Targetoid Lesions: A Report of Two Cases

Background: Skin lesions in pregnant women could be caused by physiologic or pathologic changes. Polymorphic eruption of pregnancy (PEP), which manifests as various types of skin lesions, is the most common pregnancy dermatosis. Thus, PEP could mimic other skin diseases related to unfavorable maternal and fetal outcomes. Main Observations: Two PEP patients with targetoid lesions are presented here. One of them was a primigravida, whereas the other was a secundigravida. Both patients had singleton pregnancies and skin rash which started during the third trimester. The lesions began on the abdomen and then spread to the trunk and extremities. The face, palms, soles, and mucosa were not affected. Pruritus was observed but no other systemic symptoms were reported. Both patients delivered healthy, term infants without complications. Conclusion: Targetoid lesions in PEP are an uncommon presentation, and the differential diagnosis of PEP along with other dermatoses should be considered. However, the prognosis for this type of PEP is not different from that for classic PEP