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Neuroradiological Features of Mild and Severe SARS-CoV-2 Infection.

ABSTRACT: RATIONALE AND OBJECTIVES:An increasing number of neurological complications and corresponding radiological findings have been reported in patients with COVID-19 infection. The purpose of this study is to systematically review the current literature on COVID-19-associated neuroradiological findings and examine the prevalence of different findings in patients with both severe and mild COVID-19 infection. MATERIALS AND METHODS:A comprehensive literature search of the PubMed and Embase databases was performed. Any studies reporting CT or MRI neuroimaging findings in patients with confirmed COVID-19 infection were included. Patient demographics, main radiological findings, neurological symptoms, and severity of COVID-19 infection were tabulated and quantified according to infection severity. RESULTS:Sixty-one studies published between 2019 and 2020 comprising 711 patients were analyzed according to severity of respiratory symptoms. The main neuroradiological findings for patients with mild classification were cranial nerve abnormalities, ischemic infarction, and white matter abnormalities, while the main findings in patients with severe classification were white matter abnormalities, ischemic infarction, and hemorrhagic events. CONCLUSION:Neuroradiological manifestations in COVID-19 infection are highly heterogeneous and differ based on the severity of COVID-19 infection. Cranial nerve abnormalities appear exclusive to mild infection, with a high degree of olfactory tract involvement, while hemorrhagic events are more common in severe infection. Notably, ischemic infarction was equally prevalent in both mild and severe COVID-19 infection. Healthcare providers treating COVID-19 patients should be aware of these potential complications and consider neurological assessment and neuroimaging studies when indicated.

SUBMITTER: Pan S

PROVIDER: S-EPMC7456302 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Neuroradiological Features of Mild and Severe SARS-CoV-2 Infection.

Pan Simon S Chen Willam C WC Baal Joe D JD Sugrue Leo P LP

Academic radiology 20200829 11

<h4>Rationale and objectives</h4>An increasing number of neurological complications and corresponding radiological findings have been reported in patients with COVID-19 infection. The purpose of this study is to systematically review the current literature on COVID-19-associated neuroradiological findings and examine the prevalence of different findings in patients with both severe and mild COVID-19 infection.<h4>Materials and methods</h4>A comprehensive literature search of the PubMed and Embas ...[more]

PMID: 32912668

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Project description:IntroductionThe coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The viral genetic variants associated with outcome severity are still being discovered.MethodsWe downloaded 155 958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased the predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes.ResultsLogistic regression models that included viral genomic variants outperformed other models (area under the curve = 0.91 as compared with 0.68 for age and gender alone; P < 0.001). We found 84 variants with odds ratios greater than 2 for outcome severity (17 and 67 for higher and lower severity, respectively). The median frequency of associated variants was 0.15% (interquartile range 0.09-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.ConclusionNumerous SARS-CoV-2 variants have 2-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.Lay summary: This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

Project description:Background and Objectives: The severe forms of SARS-CoV-2 pneumonia are associated with acute hypoxic respiratory failure and high mortality rates, raising significant challenges for the medical community. The objective of this paper is to present the importance of early quantitative evaluation of radiological changes in SARS-CoV-2 pneumonia, including an alternative way to evaluate lung involvement using normal density clusters. Based on these elements we have developed a more accurate new predictive score which includes quantitative radiological parameters. The current evolution models used in the evaluation of severe cases of COVID-19 only include qualitative or semi-quantitative evaluations of pulmonary lesions which lead to a less accurate prognosis and assessment of pulmonary involvement. Materials and Methods: We performed a retrospective observational cohort study that included 100 adult patients admitted with confirmed severe COVID-19. The patients were divided into two groups: group A (76 survivors) and group B (24 non-survivors). All patients were evaluated by CT scan upon admission in to the hospital. Results: We found a low percentage of normal lung densities, PaO2/FiO2 ratio, lymphocytes, platelets, hemoglobin and serum albumin associated with higher mortality; a high percentage of interstitial lesions, oxygen flow, FiO2, Neutrophils/lymphocytes ratio, lactate dehydrogenase, creatine kinase MB, myoglobin, and serum creatinine were also associated with higher mortality. The most accurate regression model included the predictors of age, lymphocytes, PaO2/FiO2 ratio, percent of lung involvement, lactate dehydrogenase, serum albumin, D-dimers, oxygen flow, and myoglobin. Based on these parameters we developed a new score (COV-Score). Conclusions: Quantitative assessment of lung lesions improves the prediction algorithms compared to the semi-quantitative parameters. The cluster evaluation algorithm increases the non-survivor and overall prediction accuracy.COV-Score represents a viable alternative to current prediction scores, demonstrating improved sensitivity and specificity in predicting mortality at the time of admission.

Dataset Information

Neuroradiological Features of Mild and Severe SARS-CoV-2 Infection.

Publications

Neuroradiological Features of Mild and Severe SARS-CoV-2 Infection.

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