10 research outputs found

    Clinical and Dermoscopic Approaches to Diagnosis of Frontal Fibrosing Alopecia: Results From a Multicenter Study of the International Dermoscopy Society

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    Introduction: Frontal fibrosing alopecia (FFA) is a form of primary lymphocytic scarring alopecia ABSTRACT characterized by a progressive recession of the fronto-temporal hairline. Although the clinical presentation of FFA is very typical, biopsy for histopathological examination is still recommended to confirm the diagnosis. Currently, a growing number of skin and mucosal inflammatory diseases are diagnosed with modern noninvasive techniques such as dermoscopy without the necessity of a biopsy. Objectives: The International Dermoscopy Society (IDS) aimed to test the ability of its members to diagnose classic FFA through clinical and dermoscopic parameters and to compare acquired data to the largest cohort studies published since 1994. Methods: This is an observational, cross-sectional study describing patient demographics, clinical presentation and diagnostic tools used in a sample of FFA patients collected by IDS members. A literature search was then performed using Pubmed to review studies reporting more than 100 cases. Results: IDS members submitted 188 cases demonstrating a predominant female population (98.4%). In 71.8% of the cases, the clinical presentation and the trichoscopic findings allowed for the diagnosis. Out of 24 revised studies, 13 showed that clinical and trichoscopic features were decisive for the diagnosis in almost all cases. Conclusions: Demographic and clinical data of our cohort were mostly comparable to previous reported data on FFA. The relevant role of the clinical and trichoscopic features in diagnosing FFA was confirmed by our study and the reviewed literature. Trichoscopy could be considered a worldwide-acknowledged non-invasive technique for the diagnosis of FFA

    Dermatoscopy of nodular/plaque-type primary cutaneous T- and B-cell lymphomas: A retrospective comparative study with pseudolymphomas and tumoral/inflammatory mimickers by the International Dermoscopy Society

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    Background: Limited data on dermatoscopy of nodular/plaque-type T-/B-cell primary cutaneous lymphomas (PCLs) is available. Objective: To describe dermatoscopic features of nodular/plaque-type PCLs, comparing them with those of clinical mimickers (pseudolymphomas, tumors, and inflammatory lesions) and investigating possible differences according to histologic subtypes. Methods: Participants were invited to join this retrospective, multicenter case-control study by submitting histologically/immunohistochemically confirmed instances of nodular/plaque-type PCLs and controls. Standardized assessments of the dermatoscopic images and comparative analyses were performed. Results: A total of 261 lesions were included (121 PCLs and 140 controls). Orange structureless areas were the strongest PCL dermatoscopic predictor on multivariate analysis compared with tumors and noninfiltrative inflammatory dermatoses. On the other hand, a positive association was found between PCLs and either unfocused linear vessels with branches or focal white structureless areas compared with infiltrative inflammatory dermatoses, whereas white lines were predictive of PCLs over pseudolymphomas. Differences in the vascular pattern were also seen between B- and T-cell PCLs and among B-cell PCL subtypes. Limitations: Retrospective design and the lack of a dermatoscopic-pathologic correlation analysis. Conclusion: Nodular/plaque-type PCLs display dermatoscopic clues, which may partially vary according to histologic subtype and whose diagnostic relevance depends on the considered clinical differential diagnoses

    Delay in diagnosis of influenza A (H1N1)pdm09 virus infection in critically ill patients and impact on clinical outcome

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    Background: Patients infected with influenza A (H1N1)pdm09 virus requiring admission to the ICU remain an important source of mortality during the influenza season. The objective of the study was to assess the impact of a delay in diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection on clinical outcome in critically ill patients admitted to the ICU. Methods: A prospective multicenter observational cohort study was based on data from the GETGAG/SEMICYUC registry (2009–2015) collected by 148 Spanish ICUs. All patients admitted to the ICU in which diagnosis of influenza A (H1N1)pdm09 virus infection had been established within the first week of hospitalization were included. Patients were classified into two groups according to the time at which the diagnosis was made: early (within the first 2 days of hospital admission) and late (between the 3rd and 7th day of hospital admission). Factors associated with a delay in diagnosis were assessed by logistic regression analysis. Results: In 2059 ICU patients diagnosed with influenza A (H1N1)pdm09 virus infection within the first 7 days of hospitalization, the diagnosis was established early in 1314 (63.8 %) patients and late in the remaining 745 (36.2 %). Independent variables related to a late diagnosis were: age (odds ratio (OR) = 1.02, 95 % confidence interval (CI) 1.01–1.03, P < 0.001); first seasonal period (2009–2012) (OR = 2.08, 95 % CI 1.64–2.63, P < 0.001); days of hospital stay before ICU admission (OR = 1.26, 95 % CI 1.17–1.35, P < 0.001); mechanical ventilation (OR = 1.58, 95 % CI 1.17–2.13, P = 0.002); and continuous venovenous hemofiltration (OR = 1.54, 95 % CI 1.08–2.18, P = 0.016). The intra-ICU mortality was significantly higher among patients with late diagnosis as compared with early diagnosis (26.9 % vs 17.1 %, P < 0.001). Diagnostic delay was one independent risk factor for mortality (OR = 1.36, 95 % CI 1.03–1.81, P < 0.001). Conclusions: Late diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection is associated with a delay in ICU admission, greater possibilities of respiratory and renal failure, and higher mortality rate. Delay in diagnosis of flu is an independent variable related to death

    Hailey–Hailey Disease: An Update Review with a Focus on Treatment Data

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