Evaluation of COVID-19 risk in patients on systemic retinoid therapy

Background and Design: Systemic retinoids are commonly used medications in dermatology and indicated in various skin disorders such as acne vulgaris and psoriasis. Data about the risk of Coronavirus disease-2019 (COVID-19) in patients using systemic retinoids are limited. Thus, this study aimed to investigate the risk of COVID-19 in patients undergoing systemic retinoid therapy. Materials and Methods: A total of 186 patients who have undergone systemic isotretinoin and acitretin therapy were recruited. Patients who presented to the dermatology clinic for various skin diseases, such as eczema, vitiligo, tinea, etc., who were not on systemic retinoid therapy, and who received topical medications comprised the control group. The development of COVID-19 in the retinoid therapy group and the control group was retrospectively reviewed using hospital database. Results: The mean age of the patients in the retinoid therapy group was 25.72 +/- 0.67 and that in the control group was 25.4 +/- 0.62. Moreover,165 patients received isotretinoin, and 21 patients received acitretin treatment. The isotretinoin dosage ranged from 0.5 to 0.8 mg/kg wheras the acitretin dosage ranged between 10 and 25 mg/day. Two patients (1.07%) in the retinoid therapy group and 8 (4.3%) patients in the control group were diagnosed with COVID-19. None of the patients receiving acitretin was diagnosed with COVID-19. COVID-19 diagnosis was established in the 2nd and 3rd months of isotretinoin treatment, and lung involvement was not observed. No significant difference regarding the number of COVID-19 cases and disease severity was found between the two groups (p=0.105; p=0.258, respectively). Conclusion: Isotretinoin and acitretin use was not associated with increased COVID-19 risk or disease severity. Systemic retinoids appear to be a safe treatment modality in the COVID-19 era

Diyabet Hastalığının Erken Aşamada Tahmin Edilmesi İçin Makine Öğrenme Algoritmalarının Performanslarının Karşılaştırılması

Şeker hastalığı, kan şekerinde anormalliklere neden olan zararlı hastalıklardan biridir. Bu hastalığın erken teşhisi insan vücudunda oluşabilecek organ bozulmalarını engeller. Yapay zekâ tabanlı çalışmalar medikal alanda etkin bir şekilde gerçekleştirilmektedir. Makine öğrenmesine dayalı bilgisayar destekli uzman sistemler bu hastalığın erken teşhisi için oldukça faydalıdır. Bu çalışmadaki şeker hastalığı problemi, klasik bir denetimli ikili sınıflandırma problemidir. Bu verisetinde 16 öznitelik bulunmakta olup, 200'ü negatif örnek ve 320'si pozitif örnek olmak üzere toplam 520 örnek içermektedir. Önişlemden geçirilen veriseti üzerinde Rastgele Orman, Gradyan Arttırma, K-En Yakın Komşu, Derin Sinir Ağları ve son olarak da Oylama topluluk sınıflandırıcısı kullanılarak inşa edilen modellerin performansları dışarıda tutma ve 5-kat çapraz doğrulama senaryoları çerçevesinde analiz edilmiştir. Her iki senaryoda da, Oylama topluluğu sınıflandırıcısı, deneylerde en iyi performansı sundu. Buna göre, Oylama topluluğu sınıflandırıcısı, tutma tekniğiyle yapılan deneylerde %100'lük bir sınıflandırma doğruluğu ve 5 kat çapraz doğrulamalı deneylerde ortalama %97,31'lik bir sınıflandırma doğruluğu sundu. Sonuç olarak, Oylama topluluğu sınıflandırıcısı kullanılarak diyabeti gerçek zamanlı olarak erken teşhis eden bir uzman sistem tasarlanabilir

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC

Mean platelet volume is associated with disease severity in patients with obstructive sleep apnea syndrome

OBJECTIVE: Obstructive sleep apnea syndrome is associated with cardiovascular diseases and thromboembolic events. The mean platelet volume (MPV) is a predictor of cardiovascular thromboembolic events. The aim of the present study is to investigate the association between the MPV and disease severity in patients with obstructive sleep apnea syndrome. METHODS: We prospectively included 194 obstructive sleep apnea syndrome patients without cardiovascular disease (mean age 56.5±12.5 years) who were undergoing sleep tests. An overnight full laboratory polisomnography examination was conducted on each patient. The patients were divided into 3 groups according to the apnea-hypopnea index (AHI): (1) AHIlow group: 5≤AH

Antiviral Properties of Caffeic Acid Phenethyl Ester and Its Potential Application

Caffeic acid phenethyl ester (CAPE) is found in variety of plants and well known active ingredient of the honeybee propolis. CAPE showed anti-inflammatory, anticarcinogenic, antimitogenic, antiviral and immunomodulatory properties in several studies. The beneficial effects of CAPE on different health issues attracted scientists to make more studies on CAPE. Specifically, the anti-viral effects of CAPE and its molecular mechanisms may reveal the important properties of virus-induced diseases. CAPE and its targets may have important roles to design new therapeutics and understand the molecular mechanisms of virus related diseases. In this mini-review, we summarize the antiviral effects of CAPE under the light of medical and chemical literature. [J Intercult Ethnopharmacol 2015; 4(4.000): 344-347

Antiviral Properties Of Caffeic Acid Phenethyl Ester And Its Potential Application

Caffeic acid phenethyl ester (CAPE) is found in a variety of plants and well-known the active ingredient of the honeybee propolis. CAPE showed anti-inflammatory, anticarcinogenic, antimitogenic, antiviral, and immunomodulatory properties in several studies. The beneficial effects of CAPE on different health issues attracted scientists to make more studies on CAPE. Specifically, the anti-viral effects of CAPE and its molecular mechanisms may reveal the important properties of virus-induced diseases. CAPE and its targets may have important roles to design new therapeutics and understand the molecular mechanisms of virus-related diseases. In this mini-review, we summarize the antiviral effects of CAPE under the light of medical and chemical literature.PubMe