ABSTRACT
BACKGROUND: Inflammation plays a major role in coronavirus disease (COVID-19). Factors that convey information about the status of inflammation could predict disease severity and help identify patients prone to clinical deterioration. Here, we aimed to evaluate the predictive value of inflammatory markers on the extent of lung involvement and survival of patients with COVID-19. MATERIALS AND METHODS: Eighty patients with confirmed COVID-19 were enrolled. Demographic, clinical, and laboratory data were collected at admission. All patients underwent chest computed tomography (CT); the extent of lung involvement was assessed by a scoring system. Patients were followed up until death or discharge occurred. Logistic regression analysis was performed to evaluate the association of investigated variables with COVID-19-related death. The association between different variables and CT score was assessed using linear regression model. Receiver operator characteristic curve analysis was applied to identify the predictive value of inflammatory markers and CT score on survival. RESULTS: The mean age of patients was 54.2 ± 15.2 years; 65% were male. Increased neutrophil-to-lymphocyte ratio (ß =0.69, odds ratio [OR] =1.50), platelet-to-lymphocyte ratio (ß =0.019, OR = 1.01), and decreased lymphocyte to C-reactive protein ratio (LCR) (ß = -0.35, OR = 0.62) were significantly associated with a higher CT score and increased odds of death (P < 0.05). Lactate dehydrogenase level was also positively related with extensive lung involvement and death (ß =1.15, OR = 1.52, P < 0.05). The LCR threshold for identifying survivors from nonsurvivors was 0.53 (area under curve [AUC] =0.82, 78% sensitivity and 74% specificity). Lung involvement ≥50% on chest CT was an excellent predictor of death (AUC = 0.83, 81% sensitivity and 79% specificity). CONCLUSION: Daily-performed laboratory tests that represent inflammation have great value for predicting the amount of disease burden and risk of mortality. Moreover, their cost-effectiveness and feasibility turn them into ideal prognostic markers.
ABSTRACT
BACKGROUND: Coronavirus infection is a novel respiratory disease affecting people across the world. Although the majority of patients present with fever, dyspnea, cough, or myalgia, various signs and symptoms have been reported for this disease. Recently, neurological symptoms have been noticed in patients with COVID-19 with unknown etiology. However, the occurrence of strokes in young and middle aged patients with COVID-19 is not fully explained. METHODS: In this series, six patients younger than 55 years of age with diagnosis of stroke and a confirmed diagnosis of COVID-19 were evaluated for symptoms, lab data, imaging findings, and outcomes from March 2020 to the end of April 2020 from all stroke cases in a tertiary academic hospital. Patients older than 55 and all others who had evidence of cardiac abnormalities (arrhythmia/valvular) were excluded. RESULTS: Fever, myalgia, cough, and dyspnea were the most common clinical symptoms noted in 66.66% (4/6), 66.66% (4/6), 50% (3/6), and 50% (3/6) of the patients, respectively. The mean ± standard deviation (SD) of National Institutes of Health Stroke Scale (NIHSS) for the patient was 10.16 ± 7.13 (ranged 5-24). The most involved area was middle cerebral artery (MCA) (five in MCA versus one in basal ganglia) and the majority of our patients had a low lung involvement score (mean ± SD: 13.16 ± 6.49 out of 24). Finally, one patient was deceased and rest discharged. CONCLUSION: Stroke may be unrelated to age and the extent of lung involvement. However, different factors may play roles in co-occurrence of stroke and COVID-19 and its outcome. Future studies with long-term follow-up and more cases are needed to assess prognostic factors.