COVITALE 2020 from eastern Indian population: imageologists perspective, a learning curve

BackgroundHigh-resolution computed tomography (HRCT) chest becomes a valuable diagnostic tool for identifying patients infected with Coronavirus Disease 2019 (COVID-19) in the early stage, where patients may be asymptomatic or with non-specific pulmonary symptoms. An early diagnosis of COVID-19 is of utmost importance, so that patients can be isolated and treated in time, eventually preventing spread of the disease, improving the prognosis and reducing the mortality. In this paper, we have highlighted our radiological experience of dealing with the pandemic crisis of 2020 through the study of HRCT thorax, lung ultrasonography, chest X-rays and artificial intelligence (AI).ResultsResults of CT thorax analysis have been given in detail. We had also compared CT severity score (CTSS) with clinical and laboratory parameters. Correlation of CTSS with SpO2 values and comorbidities was also studied. We also analysed manual CTSS with the CTSS scored calculated by the AI software.ConclusionsCTSS and use of COVID-19 Reporting and Data System (CORADS) result in accuracy and uniform percolation of information among the clinicians. Bed-side X-rays and ultrasonography have played a role where the patients could not be shifted for CT scan. The possibility of predicting impending or progression of hypoxia was not possible when SpO2 mapping was correlated with the CTSS. AI was alternatively tried with available software (CT pneumonia analysis) which was not so appropriate considering the imaging patterns in the bulk of atypical category.

Characteristics of a COVID-19 Cohort With Large Vessel Occlusion: A Multicenter International Study.

BACKGROUND: The mechanisms and outcomes in coronavirus disease (COVID-19)-associated stroke are unique from those of non-COVID-19 stroke. OBJECTIVE: To describe the efficacy and outcomes of acute revascularization of large vessel occlusion (LVO) in the setting of COVID-19 in an international cohort. METHODS: We conducted an international multicenter retrospective study of consecutively admitted patients with COVID-19 with concomitant acute LVO across 50 comprehensive stroke centers. Our control group constituted historical controls of patients presenting with LVO and receiving a mechanical thrombectomy between January 2018 and December 2020. RESULTS: The total cohort was 575 patients with acute LVO; 194 patients had COVID-19 while 381 patients did not. Patients in the COVID-19 group were younger (62.5 vs 71.2; P < .001) and lacked vascular risk factors (49, 25.3% vs 54, 14.2%; P = .001). Modified thrombolysis in cerebral infarction 3 revascularization was less common in the COVID-19 group (74, 39.2% vs 252, 67.2%; P < .001). Poor functional outcome at discharge (defined as modified Ranklin Scale 3-6) was more common in the COVID-19 group (150, 79.8% vs 132, 66.7%; P = .004). COVID-19 was independently associated with a lower likelihood of achieving modified thrombolysis in cerebral infarction 3 (odds ratio [OR]: 0.4, 95% CI: 0.2-0.7; P < .001) and unfavorable outcomes (OR: 2.5, 95% CI: 1.4-4.5; P = .002). CONCLUSION: COVID-19 was an independent predictor of incomplete revascularization and poor outcomes in patients with stroke due to LVO. Patients with COVID-19 with LVO were younger, had fewer cerebrovascular risk factors, and suffered from higher morbidity/mortality rates.

International controlled study of revascularization and outcomes following COVID-positive mechanical thrombectomy.

BACKGROUND AND PURPOSE: Previous studies suggest that mechanisms and outcomes in patients with COVID-19-associated stroke differ from those in patients with non-COVID-19-associated strokes, but there is limited comparative evidence focusing on these populations. The aim of this study, therefore, was to determine if a significant association exists between COVID-19 status with revascularization and functional outcomes following thrombectomy for large vessel occlusion (LVO), after adjustment for potential confounding factors. METHODS: A cross-sectional, international multicenter retrospective study was conducted in consecutively admitted COVID-19 patients with concomitant acute LVO, compared to a control group without COVID-19. Data collected included age, gender, comorbidities, clinical characteristics, details of the involved vessels, procedural technique, and various outcomes. A multivariable-adjusted analysis was conducted. RESULTS: In this cohort of 697 patients with acute LVO, 302 had COVID-19 while 395 patients did not. There was a significant difference (p < 0.001) in the mean age (in years) and gender of patients, with younger patients and more males in the COVID-19 group. In terms of favorable revascularization (modified Thrombolysis in Cerebral Infarction [mTICI] grade 3), COVID-19 was associated with lower odds of complete revascularization (odds ratio 0.33, 95% confidence interval [CI] 0.23-0.48; p < 0.001), which persisted on multivariable modeling with adjustment for other predictors (adjusted odds ratio 0.30, 95% CI 0.12-0.77; p = 0.012). Moreover, endovascular complications, in-hospital mortality, and length of hospital stay were significantly higher among COVID-19 patients (p < 0.001). CONCLUSION: COVID-19 was an independent predictor of incomplete revascularization and poor functional outcome in patients with stroke due to LVO. Furthermore, COVID-19 patients with LVO were more often younger and had higher morbidity/mortality rates.

Discriminating the Pneumonia-Positive Images from COVID-19-Positive Images Using an Integrated Convolutional Neural Network

One of the most pressing issues in the current COVID-19 pandemic is the early detection and diagnosis of COVID-19, as well as the precise separation of non-COVID-19 cases at the lowest possible cost and during the disease's early stages. Deep learning-based models have the potential to provide an accurate and efficient approach for the identification and diagnosis of COVID-19, with considerable increases in sensitivity, specificity, and accuracy when used in the processing of modalities. COVID-19 illness is difficult to detect and recognize since it is comparable to pneumonia. The main objective of this study is to distinguish between COVID-19-positive images and pneumonia-positive images. We have proposed an integrated convolutional neural network focused on discriminating against COVID-19-infected patients and pneumonia patients. Preprocessing is done on the image datasets. The novelty of this research work is to differentiate the COVID-19 images from the pneumonia images. It will help the medical experts in the decision-making. In order to train the model, the image is given directly as input to integrated convolutional neural network architecture;after training the model, the system is integrated with three different kinds of datasets: COVID-19 image dataset, RSNA pneumonia dataset, and a new dataset created from COVID-19 image dataset. The attainment of the system is evaluated by calculating the measures of sensitivity, specificity, precision, and accuracy, and this system produces the accuracy values of 94.04%, 97.2%, and 97.5% for the above datasets, respectively. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The rising burden of invasive fungal infections in COVID-19, can structured CT thorax change the game

Background The occurrence of invasive fungal infections in COVID-19 patients is on surge in countries like India. Several reports related to rhino-nasal-sinus mucormycosis in COVID patients have been published in recent times;however, very less has been reported about invasive pulmonary fungal infections caused mainly by mucor, aspergillus or invasive candida species. We aimed to present 6 sputum culture proved cases of invasive pulmonary fungal infection (four mucormycosis and two invasive candidiasis) in COVID patients, the clues for the diagnosis of fungal invasion as well as difficulties in diagnosing it due to superimposed COVID imaging features. Case presentation The HRCT imaging features of the all 6 patients showed signs of fungal invasion in the form of cavities formation in the pre-existing reverse halo lesions or development of new irregular margined soft tissue attenuating growth within the pre-existing or in newly formed cavities. Five out of six patients were diabetics. Cavities in cases 1, 2, 3 and 4 of mucormycosis were aggressive and relatively larger and showed relatively faster progression into cavities in comparison with cases 5 and 6 of invasive candidiasis. Conclusion In poorly managed diabetics or with other immunosuppressed conditions, invasive fungal infection (mucormycosis, invasive aspergillosis and invasive candidiasis) should be considered in the differential diagnosis of cavitary lung lesions.

Rethinking Consent for Stroke Trials in Time-Sensitive Situations: Insights From the COVID-19 Pandemic.

Informed consent is a key concept to ensure patient autonomy in clinical trials and routine care. The coronavirus disease 2019 (COVID-19) pandemic has complicated informed consent processes, due to physical distancing precautions and increased physician workload. As such, obtaining timely and adequate patient consent has become a bottleneck for many clinical trials. However, this challenging situation might also present an opportunity to rethink and reappraise our approach to consent in clinical trials. This viewpoint discusses the challenges related to informed consent during the COVID-19 pandemic, whether it could be acceptable to alter current consent processes under these circumstances, and outlines a possible framework with predefined criteria and a system of checks and balances that could allow for alterations of existing consent processes to maximize patient benefit under exceptional circumstances such as the COVID-19 pandemic without undermining patient autonomy.

Pandemic Guidance for Stroke Centers Aiding COVID-19 Treatment Teams.

The coronavirus disease 2019 (COVID-19) pandemic has in some regions overwhelmed the capacity and staffing needs of healthcare systems, necessitating the provision of resources and staff from different disciplines to aid COVID treatment teams. Stroke centers have multidisciplinary clinical and procedural expertise to support COVID treatment teams. Staff safety and patient safety are essential, as are open lines of communication between stroke center leaders and hospital leadership in a pandemic where policies and procedures can change or evolve rapidly. Support needs to be allocated in a way that allows for the continued operation of a fully capable stroke center, with the ability to adjust if stroke center volume or staff attrition requires.

Prehospital Triage of Acute Stroke Patients During the COVID-19 Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has broad implications on stroke patient triage. Emergency medical services providers have to ensure timely transfer of patients while minimizing the risk of infectious exposure for themselves, their co-workers, and other patients. This statement paper provides a conceptual framework for acute stroke patient triage and transfer during the COVID-19 pandemic and similar healthcare emergencies in the future.