SARS-CoV-2 has posed an unprecedented challenge to the world. Pandemics have been caused previously by viruses of this family like Middle East Respiratory Corona Virus (MERS CoV), Severe Acute Respiratory Syndrome Corona Virus (SARS CoV). Although these viruses are primarily respiratory viruses, but they have been isolated from non-respiratory samples as well. Presently, the detection rate of SARS‐CoV‐2 RNA from different clinical specimens using Real Time Reverse Transcriptase Polymerized Chain Reaction (qRT‐PCR) after onset of symptoms is not yet well established. Therefore, the aim of this systematic review was to establish the profile of detecting SARS‐CoV‐2, MERS CoV, SARS CoV from different types of clinical specimens other than the respiratory using a standard diagnostic test (qRT‐PCR). A total of 3429 non-respiratory specimens were recorded: SARS CoV (total sample—802), MERS CoV (total sample—155), SARS CoV-2 (total sample—2347). Out of all the samples studied high positive rate was seen for saliva with 96.7% (14/14; 95% CI 87.6–100.0%) for SARS CoV and 57.5% (58/250; 95% CI − 1.2 to 116.2%) for SARS CoV-2, while low detection rate in urine samples for SARS CoV-2 with 2.2% (8/318; 95% CI 0.6–3.7%) and 9.6% (12/61; 95% CI − 0.9 to 20.1%) for SARS CoV but there was relatively higher positivity in urine samples for MERS CoV with detection rate of 32.4% (2/38; 95% CI − 37.3 to 102.1%). In Stool sample positivity was 54.9% (396/779; 95% CI 41.0–68.8%), 45.2% (180/430; 95% CI 28.1–62.3%) and 34.7% (4/38; 95% CI − 29.5 to 98.9%) for SARS CoV-2, MERS CoV, and SARS CoV, respectively. In blood sample the positivity was 33.3% (7/21; 95% CI 13.2–53.5%), 23.7% (42/277; 95% CI 10.5–36.9%) and 2.5% (2/81; 95% CI 0.00–5.8%) for MERS CoV, SARS CoV-2 and SARS CoV respectively. SARS‐CoV‐2 along with previous two pandemic causing viruses from this family, were highly detected stool and saliva. A low positive rate was recorded in blood samples. Viruses were also detected in fluids along with unusual samples like semen and vaginal secretions thus highlighting unique pathogenic potential of SARS‐CoV‐2.
The novel coronavirus (COVID-2019) pandemic has caused a catastrophic effect on health and global economy. Early screening and diagnosis of COVID-19 pneumonia are the critical steps to stop the further spread of the virus. The most common standard for confirming the virus relies on RT-PCR tests. This method generates false-negative results if there is limited viral load. Recent radiological findings suggest that the distinct distribution of ground-glass opacities (GGOs), which are found on certain parts of lungs, can determine the status of the infection among patients. As a complement to RT-PCR, Computed tomography (CT) can be used for diagnosing COVID-19. In this study, the authors have described a Mask R-CNN (region-based convolution neural network) approach for the detection of the ground glass opacities (GGOs) in chest CT images of COVID-19 infected persons. The proposed approach provides an accuracy of 98.25% during instance segmentation. Therefore, the authors believe this proposed method will aid health professionals to fasten the screening and validation of the initial assessment towards COVID-19 patients.
Lymphatic filariasis is a vector borne infection classified under the WHO category of Neglected Tropical Disease (NTD). It is a major public health concern globally. This study describes this vector-borne infection in a young pregnant lady, a known case of chronic myeloid leukemia (CML) on chemotherapy. Such an association is hitherto unreported.
Down syndrome is a well-recognised genetic condition associated with several comorbidities. Although CHD is common in Down syndrome, transposition of the great arteries is exceptionally rare. We describe a neonate with Down syndrome who presented with transient abnormal myelopoiesis and transposition of the great arteries. Down syndrome may accelerate pulmonary hypertension in transposition of the great arteries and is associated with poor outcomes.
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