ABSTRACT
PurposeTo identify differences in CT imaging and clinical features between COVID-19 and influenza pneumonia in the early stage, and to identify the most valuable features in the differential diagnosis. Materials and MethodA consecutive cohort of 73 COVID-19 and 48 influenza pneumonia patients were retrospectively recruited from five independent institutions. The courses of both diseases were confirmed to be in the early stages (2.66 {+/-} 2.62 days for COVID-19 and 2.19 {+/-} 2.10 days for influenza pneumonia after onset). The chi-square test, students t-test, and Kruskal-Wallis H-test were performed to compare CT imaging and clinical features between the two groups. Spearman or Kendall correlation tests between feature metrics and diagnosis outcomes were also assessed. The diagnostic performance of each feature in differentiating COVID-19 from influenza pneumonia was evaluated with univariate analysis. The corresponding area under the curve (AUC), accuracy, specificity, sensitivity and threshold were reported. ResultsThe ground-glass opacification (GGO) was the most common imaging feature in COVID-19, including pure-GGO (75.3%) and mixed-GGO (78.1%), mainly in peripheral distribution. For clinical features, most COVID-19 patients presented normal white blood cell (WBC) count (89.04%) and neutrophil count (84.93%). Twenty imaging features and 6 clinical features were identified to be significantly different between the two diseases. The diagnosis outcomes correlated significantly with the WBC count (r=-0.526, P<0.001) and neutrophil count (r=-0.500, P<0.001). Four CT imaging features had absolute correlations coefficients higher than 0.300 (P<0.001), including crazy-paving pattern, mixed-GGO in peripheral area, pleural effusions, and consolidation. ConclusionsAmong a total of 1537 lesions and 62 imaging and clinical features, 26 features were demonstrated to be significantly different between COVID-19 and influenza pneumonia. The crazy-paving pattern was recognized as the most powerful imaging feature for the differential diagnosis in the early stage, while WBC count yielded the highest diagnostic efficacy in clinical manifestations.
ABSTRACT
Objective To investigate the risk factors for leukoaraiosis (LA). Methods The clinical and imaging data in patients with stroke were collected retrospectively. LA was divided into periventricular LA and subcortical LA according to the findings of MRI, and they were scored and classified. Results A total of 113 patients with stroke were included. There were 39 women and 74 men (mean age 61.33 ± 1.32 years). The age (65.52 ± 12. 56 vs.47. 96 ±9. 23 years, t =5. 634, P =0. 000), hypertension (68. 60% vs. 29. 63% ,x2 = 12. 932,P =0. 000), diabetes (30. 23% vs. 3.70%, x2 = 7. 953, P = 0. 005), systolic blood pressure (SBP) (147. 42 ± 2. 78 mm Hg vs. 134. 00 ± 22. 45 mm Hg,t = 2. 862, P = 0. 004), glucose (6. 54 ± 3. 48 mmol/L vs. 5. 35 ± 1.37 mmol/L, t = 2. 808, P = 0. 005), and total cholesterol (TC) level (5. 17±0.89 mmol/L vs. 4.59±0.61 mmol/L, t=3. 152, P=0. 002) in patients with periventricular LA (n = 86) were significantly higher than those without periventricular LA (n =27). The age (66. 44 ± 11.33 vs. 47. 96 ±9. 23 years, t =4. 768, P =0. 000), hypertension (74. 29% vs. 34. 88%, x2 = 17. 134, P = 0. 000), SBP (85.46 ± 9. 80 mm Hg vs. 69. 81 ±8. 74 mm Hg, t =2. 999, P=0. 003), diastolic blood pressure (DBP) (85.46 ±9. 80 mm Hg vs.69. 81 ±8.74 mm Hg, t =2. 999, P =0. 003), and TC level (5.22±0.99 mmol/L vs. 4.91 ±0. 75 mmol/L, t =3. 330, P =0. 001) in patients with subcortical LA (n =70) were significantly higher than those without subcortical LA (n =43). Spearman correlation analysis showed that the periventricular LA classification was significantly correlated with the age (rs = 0. 606, P =0. 000), drinking (rs = -0. 257, P = 0. 006), hypertension (rs = 0. 428, P = 0. 000), diabetes (rs =0. 236, P =0. 012), SBP (rs =0. 382, P =0. 000), and DBP (rs =0. 258, P =0. 006). The subcortical LA classification was significantly correlated with the age (rs = 0.488, P = 0. 000),hypertension (rs = 0. 416, P = 0. 000), SBP (rs = 0. 386, P = 0. 000), DBP (rs = 0. 326, P =0. 006), and TC level (rs =0. 231, P =0. 014). Multivariate logistic regression analysis showed that the age (odds ratio[OR] = 1.071, 95% confidence interval [CI] 1.009-1. 137; P=O. 024), hypertension (OR =4. 106, 95% CI 1. 657-10. 174; P =0. 002), and SBP (OR =1. 049,95% CI 1. 162-7. 013; P = 0. 022) were independently correlated with LA. Conclusions The age, hypertension, and SBP are the independent risk factors for LA, in which the age is an uncontrollable factor, and the aggressive prevention and treatment of hypertension may reduce the occurrence of LA.
