Clinical Features and Outcome of Stroke with COVID-19. COVID-19 Stroke Study Group (CSSG), India.

BACKGROUND AND PURPOSE: Occurrence of stroke has been reported among patients with COVID-19. The present study compares clinical features and outcomes of stroke patients with and without COVID-19. METHODS: The COVID-19 Stroke Study Group (CSSG) is a multicentric study in 18 sites across India to observe and compare the clinical characteristics of patients with stroke admitted during the current pandemic period and a similar epoch in 2019. The present study reports patients of stroke with and without COVID-19 (CoVS and non-CoVS, respectively) seen between February 2020 and July 2020. Demographic, clinical, treatment, and outcome details of patients were collected. RESULTS: The mean age and gender were comparable between the two groups. CoVS patients had higher stroke severity and extent of cerebral involvement on imaging. In-hospital complications and death were higher among CoVS patients (53.06% vs. 17.51%; P < 0.001) and (42.31% vs. 7.6%; P < 0.001), respectively. At 3 months, higher mortality was observed among CoVS patients (67.65% vs. 13.43%; P < 0.001) and good outcome (modified Rankin score [mRS]: 0-2) was seen more often in non-CoVS patients (68.86% vs. 33.33%; P < 0.001). The presence of COVID-19 and baseline stroke severity were independent predictors of mortality. CONCLUSIONS: CoVS is associated with higher severity, poor outcome, and increased mortality. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and baseline stroke severity are independent predictors of mortality.

Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays.

SARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature and algorithms with the paucity of initial training data; we describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets. The performance and explainability of CovBaseAI was primarily validated on two independent datasets. Firstly, 1401 randomly selected CxR from an Indian quarantine center to assess effectiveness in excluding radiological COVID-Pneumonia requiring higher care. Second, curated dataset; 434 RT-PCR positive cases and 471 non-COVID/Normal historical scans, to assess performance in advanced medical settings. CovBaseAI had an accuracy of 87% with a negative predictive value of 98% in the quarantine-center data. However, sensitivity was 0.66-0.90 taking RT-PCR/radiologist opinion as ground truth. This work provides new insights on the usage of EDS with DL methods and the ability of algorithms to confidently predict COVID-Pneumonia while reinforcing the established learning; that benchmarking based on RT-PCR may not serve as reliable ground truth in radiological diagnosis. Such tools can pave the path for multi-modal high throughput detection of COVID-Pneumonia in screening and referral.

Survey of prevalence of anxiety and depressive symptoms among 1124 healthcare workers during the coronavirus disease 2019 pandemic across India.

BACKGROUND: A prospective study was conducted during the second phase of the coronavirus disease 2019 (COVID-19) pandemic in India to assess the prevalence of anxiety and depressive symptoms among healthcare workers (HCWs) and factors that influence the outcome. METHODS: A self-administered questionnaire was completed by 1124 HCWs during the COVID-19 pandemic (March 30, 2020, to April 2, 2020). Demographic data, questions on COVID-19 and scores of the Hospital Anxiety and Depression Scale were analysed using the chi-square test (Bonferroni correction) and binary logistic regression. RESULTS: The study consists of 1124 HCWs, including 749 doctors, 207 nurses, 135 paramedics, 23 administrators and ten supporting staff members. The prevalence of anxiety and depressive symptoms were reported as 37.2% and 31.4%, respectively. The risk factors for anxiety were female gender (30.6% vs 45.5%), age group (20-35 years) (50.4% vs 61.2%), unmarried (21.2% vs 30.6%) and job profile (nurse) (14.7% vs 26.4%). The protective factor was having service of more than 20 years (23.4% vs 14.8%). The risk factors for depression were age group (20-35 years) (51.3% vs 61.3%) and employed at a primary care hospital (16.2% vs 23.4%). The protective factors were job profile (doctor) (69.9% vs 59.6%) and having service of more than 20 years (22.3% vs 15.5%). CONCLUSION: Approximately one-third of the HCWs reported anxiety and depressive symptoms. The risk factors for anxiety symptoms were female gender, younger age and job profile (nurse) and for depressive symptoms were younger age and working at a primary care hospital. Future research studies should identify strategies for providing a safer and supportive work environment for HCWs to face epidemics/pandemics.

Open-label randomized control trial of hydroxychloroquine in patients with moderate to severe coronavirus disease 2019 infection.

BACKGROUND: At onset of coronavirus disease 2019 (COVID-19) pandemic, hydroxychloroquine (HCQ) was repurposed for treatment of patients based on reports that it had in vitro activity. The aim of this study was to find out if HCQ reduces number of days of hospitalization when given to patients with moderate to severe COVID-19 infections who require hospitalized care. METHODS: This was an open-label randomized control trial of HCQ administered 400 mg twice on day 1, then 400 mg once daily from day 2 to day 5 in patients with moderate to severe COVID-19 infection. Assessment was not blinded. Standard of care was given to both arms.Primary outcome was number of days of hospitalization till discharge or death. RESULT: One hundred ten patients (55 in each arm) were included. Mean age was 58 years. Baseline characteristics were well matched. There was no difference in the primary outcome (13.67 vs 13.89; p = 0.98). Number of deaths were more in HCQ arm (RR: 1.81; 95% CI: 1.13-2.93; p = 0.03). There was no difference in number of days on oxygen or normalization of oxygen saturation, number who needed ventilator, days to ventilator requirement and days on ventilator. Twenty-nine patients in control arm received remdesivir. When adjusted analysis was done after removal of these patients, there was no difference in primary or secondary outcomes. Number of deaths in adjusted analysis were not significant (RR: 1.28; 95% CI: 0.87-1.88; p = 0.37). CONCLUSION: HCQ does not change the number of days of hospitalization when compared with control.

Myositis in a patient with coronavirus disease 2019: A rare presentation.

The world is presently struggling with coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). A patient with COVID-19 typically presents with fever, non-productive cough, dyspnea, and myalgia. A 49-year-old female presented with complaints of subacute onset and progressive symmetrical proximal muscle weakness of both upper limbs and lower limbs with no sensory, cranial nerve deficit. She had elevated creatine phosphokinase levels of 906 U/L, an aspartate aminotransferase level of 126 IU/L, a lactate dehydrogenase level of 354 U/L, and an erythrocyte sedimentation rate of 68 mm/1 hr, and magnetic resonance imaging of the pelvis and thigh revealed muscle edema suggestive of myositis. Her reverse transcriptase-polymerase chain reaction result for SARS-CoV-2 was positive. Her evaluation for other causes of myositis was negative. She was managed with intravenous immunoglobulins and supportive care. She showed rapid improvement in symptoms and motor weakness. To our knowledge, this is the first reported case of COVID-19 related disabling myositis in India.

Clinical profile and outcome of non-COVID strokes during pandemic and the pre pandemic period: COVID-Stroke Study Group (CSSG) India.

BACKGROUND: As the health systems around the world struggled to meet the challenges of COVID-19 pandemic, care of many non-COVID emergencies was affected. AIMS: The present study examined differences in the diagnosis, evaluation and management of stroke patients during a defined period in the ongoing pandemic in 2020 when compared to a similar epoch in year 2019. METHODS: The COVID stroke study group (CSSG) India, included 18 stroke centres spread across the country. Data was collected prospectively between February and July 2020 and retrospectively for the same period in 2019. Details of demographics, stroke evaluation, treatment, in-hospital and three months outcomes were collected and compared between these two time points. RESULTS: A total of 2549 patients were seen in both study periods; 1237 patients (48.53%) in 2019 and 1312 (51.47%) in 2020. Although the overall number of stroke patients and rates of thrombolysis were comparable, a significant decline was observed in the month of April 2020, during the initial period of the pandemic and lockdown. Endovascular treatment reduced significantly and longer door to needle and CT to needle times were observed in 2020. Although mortality was higher in 2020, proportion of patients with good outcome were similar in both the study periods. CONCLUSIONS: Although stroke admissions and rates of thrombolysis were comparable, some work flow metrics were delayed, endovascular stroke treatment rates declined and mortality was higher during the pandemic study period. Reorganization of stroke treatment pathways during the pandemic has likely improved the stroke care delivery across the globe.