Early detection and diagnosis are critical factors to control the COVID-19 spreading. A number of deep learning-based methodologies have been recently proposed for COVID-19 screening in CT scans as a tool to automate and help with the diagnosis. These approaches, however, suffer from at least one of the following problems: (i) they treat each CT scan slice independently and (ii) the methods are trained and tested with sets of images from the same dataset. Treating the slices independently means that the same patient may appear in the training and test sets at the same time which may produce misleading results. It also raises the question of whether the scans from the same patient should be evaluated as a group or not. Moreover, using a single dataset raises concerns about the generalization of the methods. Different datasets tend to present images of varying quality which may come from different types of CT machines reflecting the conditions of the countries and cities from where they come from. In order to address these two problems, in this work, we propose an Efficient Deep Learning Technique for the screening of COVID-19 with a voting-based approach. In this approach, the images from a given patient are classified as group in a voting system. The approach is tested in the two biggest datasets of COVID-19 CT analysis with a patient-based split. A cross dataset study is also presented to assess the robustness of the models in a more realistic scenario in which data comes from different distributions. The cross-dataset analysis has shown that the generalization power of deep learning models is far from acceptable for the task since accuracy drops from 87.68% to 56.16% on the best evaluation scenario. These results highlighted that the methods that aim at COVID-19 detection in CT-images have to improve significantly to be considered as a clinical option and larger and more diverse datasets are needed to evaluate the methods in a realistic scenario.

These findings suggest that 4 weeks of PR before lung cancer resection improves preoperative functional capacity and decreases the postoperative respiratory morbidity.

OBJECTIVE: To validate a Portuguese-language version of the COPD assessment test (CAT) for use in Brazil and to assess the reproducibility of this version. METHODS: This was multicenter study involving patients with stable COPD at two teaching hospitals in the city of Fortaleza, Brazil. Two independent observers (twice in one day) administered the Portuguese-language version of the CAT to 50 patients with COPD. One of those observers again administered the scale to the same patients one week later. At baseline, the patients were submitted to pulmonary function testing and the six-minute walk test (6MWT), as well as completing the previously validated Portuguese-language versions of the Saint George's Respiratory Questionnaire (SGRQ), modified Medical Research Council (MMRC) dyspnea scale, and hospital anxiety and depression scale (HADS). RESULTS: Inter-rater and intra-rater reliability was excellent (intraclass correlation coefficient [ICC] = 0.96; 95% CI: 0.93-0.97; p < 0.001; and ICC = 0.98; 95% CI: 0.96-0.98; p < 0.001, respectively). Bland Altman plots showed good test-retest reliability. The CAT total score correlated significantly with spirometry results, 6MWT distance, SGRQ scores, MMRC dyspnea scale scores, and HADS-depression scores. CONCLUSIONS: The Portuguese-language version of the CAT is a valid, reproducible, and reliable instrument for evaluating patients with COPD in Brazil.

Despite rescue pLVAD insertion, hemodynamic collapse during VT ablation is associated with a persistently high 30-day mortality. Further studies are warranted to predict hemodynamic collapse and to refine the role of pLVAD in this setting.

BackgroundSystemic inflammation plays an important role in the initiation, promotion, and progression of lung carcinogenesis. In patients with non-small cell lung cancer (NSCLC), fibrinogen levels correlate with neoplasia. Here we compared the effects of pulmonary rehabilitation (PR) with chest physical therapy (CPT) on fibrinogen and albumin levels in patients with LC and previous inflammatory lung disease awaiting lung resection.MethodsWe conducted a randomized clinical trial with 24 patients who were randomly assigned to Pulmonary Rehabilitation (PR) and Chest Physical Therapy (CPT) groups. Each group underwent training 5 days weekly for 4 weeks. All patients were assessed before and after four weeks of training through clinical assessment, measurement of fibrinogen and albumin levels, spirometry, 6-minute Walk Test (6MWT), quality of life survey, and anxiety and depression scale. PR involved strength and endurance training, and CPT involved lung expansion techniques. Both groups attended educational classes.ResultsA mixed between-within subjects analysis of variance (ANOVA) revealed a significant interaction between time (before and after intervention) and group (PR vs. CPT) on fibrinogen levels (F(1, 22) = 0.57, p < 0.0001) and a significant main effect of time (F(1, 22) = 0.68, p = 0.004). Changes in albumin levels were not statistically significant relative to the interaction effect between time and group (F(1, 22) = 0.96, p = 0.37) nor the main effects of time (F(1, 22) = 1.00, p = 1.00) and group (F(1, 22 ) = 0.59, p = 0.45). A mixed between-within subjects ANOVA revealed significant interaction effects between time and group for the peak work rate of the unsupported upper limb exercise (F(1, 22) = 0.77, p = 0.02), endurance time (F(1, 22) = 0.60, p = 0.001), levels of anxiety (F(1, 22) = 0.60, p = 0.002) and depression (F(1, 22) = 0.74, p = 0.02), and the SF-36 physical component summary (F(1, 22) = 0.83, p = 0.07).ConclusionPR reduced serum fibrinogen levels, improved functional parameters, and quality of life of patients with LC and inflammatory lung disease awaiting lung resection.Trial registrationCurrent Controlled Trials RBR-3nm5bv.

Administration of autologous ALDH(br) cells appears to be safe and warrants further study in patients with CLI.

The application of these new cut-points would reclassify about one-third of the patients with COPD and, thus, would impact on individual disease management. Further validation in prospective studies of these new values are needed.

Background-The increasing worldwide prevalence of coronary artery disease (CAD) continues to challenge the medical community. Management options include medical and revascularization therapy. Despite advances in these methods, CAD is a leading cause of recurrent ischemia and heart failure, posing significant morbidity and mortality risks along with increasing health costs in a large patient population worldwide.