Browsing by Author "Soares, F"
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- Morphological Changes of the Internal Carotid Artery: Prevalence and Characteristics. A Clinical and Ultrasonographic Study in a Series of 19 804 Patients Over 25 Years OldPublication . Martins, H; Mayer, A; Batista, P; Soares, F; Almeida, V; Pedro, AJ; Oliveira, VBackground and purpose: Morphological changes of the internal carotid arteries (McICA) are frequently found during cervical ultrasound studies. However, the etiology of McICA remains controversial. During this study, the prevalence and demographic characteristics of McICA, such as kinking, coiling or looping identified by Doppler ultrasound, were analysed and its relationship with vascular risk factors and stroke was assessed. Methods: A retrospective study was performed by analysing 19 804 patients who were subjected to cervical ultrasonographic study between January 2000 and June 2012. The data were statistically analysed with SPSS® 20 and a multivariate logistic regression was performed. Statistical significance was accepted for P < 0.05 and 95% confidence intervals (CIs) were used. Results: Morphological changes of the internal carotid arteries were present in 2678 patients (13.5%) and were unilateral in 61.6% of these cases. Carotid kinking was found in 80% of the patients, coiling in 16% and looping in 1%. In multivariate analysis, the presence of McICA was related to older groups (1.04; 95% CI, 1.04-1.05; P < 0.01), female gender (1.78; 95% CI, 1.64-1.94; P < 0.01), patients with hyperlipidemia (1.28; 95% CI, 1.17-1.40; P < 0.01), carotid thickness (1.22; 95% CI, 1.13-1.33; P < 0.01) and cardiac or cardioembolic disease (1.11; 95% CI, 1.01-1.21; P = 0.02). The results of this study indicate that kinking in the carotid artery was associated with ipsilateral cerebral ischemic events (1.43; 95% CI, 1.040-1.958; P < 0.05). Conclusion: Morphological changes of the internal carotid arteries were associated with aging, female gender and patients with hyperlipidemia, hypertension, diabetes and heart disease. Kinking was associated with ipsilateral cerebral ischemia.
- Reliability of Classification by Ophthalmologists with Telescreening Fundus Images for Diabetic Retinopathy and Image QualityPublication . Rêgo, S; Dutra-Medeiros, M; Bacelar-Silva, GM; Borges, T; Soares, F; Monteiro-Soares, M
- Screening for Diabetic Retinopathy Using an Automated Diagnostic System Based on Deep Learning: Diagnostic Accuracy AssessmentPublication . Rêgo, S; Dutra-Medeiros, M; Soares, F; Monteiro-Soares, MPurpose: To evaluate the diagnostic accuracy of a diagnostic system software for the automated screening of diabetic retinopathy (DR) on digital colour fundus photographs, the 2019 Convolutional Neural Network (CNN) model with Inception-V3. Methods: In this cross-sectional study, 295 fundus images were analysed by the CNN model and compared to a panel of ophthalmologists. Images were obtained from a dataset acquired within a screening programme. Diagnostic accuracy measures and respective 95% CI were calculated. Results: The sensitivity and specificity of the CNN model in diagnosing referable DR was 81% (95% CI 66-90%) and 97% (95% CI 95-99%), respectively. Positive predictive value was 86% (95% CI 72-94%) and negative predictive value 96% (95% CI 93-98%). The positive likelihood ratio was 33 (95% CI 15-75) and the negative was 0.20 (95% CI 0.11-0.35). Its clinical impact is demonstrated by the change observed in the pre-test probability of referable DR (assuming a prevalence of 16%) to a post-test probability for a positive test result of 86% and for a negative test result of 4%. Conclusion: A CNN model negative test result safely excludes DR, and its use may significantly reduce the burden of ophthalmologists at reading centres.