3. RESULTS
Demographic characteristics of all patients was listed in Table 1. The mean age of patients was 41.7, the median age 63 years (range 32–69) for critical patients which 65 % were male and 34 % were female (one-way ANOVA, p < 0.0001). Almost 198 patients (58%) were aged ≤ 38 years. Generally, 183 (53%) patients had one or two types of chronic diseases, such as cancer, immune system defects, coronary heart disease (CHD), hypertension (HBP) and diabetes (DM). Hypertension 154 (45.29 %), Cardiovascular Disease 90 (26.47%) and Diabetes 178 (52.35%) were the most common Coexisting Conditions. According to the results of this study, 28 patients (9%) of patients had familial infection or familial clusters. There was significant difference among patients by their epidemiology history. The patients indeed presented significantly different on the most common symptoms like Fever, Dyspnea, Muscular pain, Fatigue, Shortness of Breath, Chill, Dry Cough and Diarrhea (Table 1) (one-way ANOVA, p = 0.001). Furthermore, the mean length of hospital stay in these patients were 14.12 days that in the critically ill patients took average 2.08 days longer than total average levels. From the 340 cases with the suspicion of COVID-19 infection, 230 patients (164 males, 76 females with a positive RT-PCR test for covid-19). The most common clinical manifestations were fever, coughing, Muscular pain and dyspnea. In this study change CRP levels were found in patients and increased D-dimer levels were found in patients and decreased lymphocyte count was observed in 98 patients according to Table 2 Summary of Changes in Biomarkers Seen in Severe COVID-19 Infection. Change clinical in biochemistry parameters patients are summarized in Table 2. The results of this study show that the white blood cell (WBC) and neutrophil cell numbers were significantly higher and platelets and HB severely lower and a quite distinguishable difference on the blood biochemical test at different patients. Among patients in people with underlying diseases and high-risk groups showed significantly higher levels of serum ALT, AST, LDH, than other healthy. According to Table 2 ALT, CRP, LDH, and Urea had very good precision in predicting cases with positive RT-PCR for COVID19. The result of this study RT-PCR for COVID-19 patients was positive in 252 (74%) cases and negative in 88(25%). Based on the CDC clinical scoring for covid-19 infection (10), 150 (44.11%) were classified as mild, 118 (34.70%) as severe, and 72 patients (21.17%) as critical.
The results of this study ( Table 3) in CT features, scoring, screening patients show the most common patterns of disease included GGO, observed in 152 patients (44.7%), followed by followed by crazy-paving pattern 68 (20 %) and parenchymal consolidations in 78 (22.9%) (Fig. 2). Features and characteristics related to CT were found as follows: fibrosis (n = 57; 16.76%), sub pleural lines (n= 43; 12.46%), pleural effusion (n = 28; 8.23%), precordial effusion (n = 8; 2.35%), and mediastinal lymphadenopathy (n = 27; 7.94 %), COPD thinking of ILD, ILS (n = 30; 8.82 %). Findings of this study also shown lobar involvement, lesion distribution, and localization in pulmonary parenchyma. Pathological involvement in the left lower lobe (LLL) in 157 patients (46.17%) was most common and right lower lobe (RLL) in 143 patients (42.05 %). The mean of involvement lung lobes and CT scores were show in (Fig. 3) (Table.4).
According to the average global CT score was 12.3±11.1. All patient did show parenchymal involvement at CT reports and there are not any patient therefor scored as 0. In comparisons between lung lobes, the mean CT score was significantly higher in RLL than in ML and RUL (p<0.0001) and the mean CT score was significantly higher in LLL than in LUL (p<0.0001) (Fig. 3), also the distribution of parenchymal abnormalities in pathological findings were posterior in 118 patients (34.70%) and anterior in 68 patients (20 %). In the 50 patients (16.8%), there was involvement of both anterior and posterior areas. Regarding the results of this study and investigation of CT features, demonstrated the GGO pattern was most prevalent in early-phase disease and late-phase disease, while crazy-paving and consolidation patterns were most common in late-phase, also fibrosis were significantly common in late-phase. The pleural effusion and lymphadenopathy in patients were rarely observed in late-phase. CT score in late-phase was significantly higher than in early-phase patients (p<0.0001). CT score between age range groups statistically significant difference was found (p=0.0018), in this way CT score was significantly higher in age range >75 than in other age groups (p=0.001).
Furthermore, the results of this study indicated statistically significant correlations between CT score with SAA (p<0.0001, r= 0.4314), LDH (p<0.0001, r= 0.3214), Cardiac troponin (p<0.0001, r= 0.6714), Renal biomarkers Urea & creatinine (p<0.0001, r= 0.3314), CRP (p<0.0001, r= 0.6314), D-dimer (p<0.0001, r=0.6427), lymphocyte count (p=0.0001, r =0.1630) levels. Univariate and multivariate analyses of 340 patients in this study show that 48 patients (11.17 %) died during a mean follow-up of 14.1±4.8 days (range 1–26 days), all of which indicated at least one or more of the previously mentioned underlying diseases. The mortality rate was significantly higher in patients ≥75 years old (n=39; 11.47%) and among critical patients (12/12; 100%). The univariate analysis CT score in this patients indicated a higher risk of death in patients with a CT score ≥18 (HR, 8.23; 95% CI, 2.17–25.63; p<0.0001), and significantly correlated with increase of age (HR,1.02;95% CI,1.01–1.21; p=0.001), HDL (HR, 1.01; 95% CI, 1.03–1.07; p<0.001), Cardiac troponin (HR, 1.003; 95% CI, 1.10–1.00; p<0.001), Urea (HR, 1.06; 95% CI, 1.03–1.07; p<0.001), creatinine (HR, 1.01; 95% CI, 1.00 –1.01; p<0.001) CRP (HR, 1.06; 95% CI, 1.03–1.07; p<0.001) and D-dimer levels (HR,1.011; 95% CI,1–1.08.001; p=0.0001). Table 5 show the correlations between Clinical Findings, laboratory tests and CT reports.
In this study we investigated the correlation of clinical and laboratory findings with CT-based quantitative score of pulmonary involvement in COVID-19 pneumonia, that we realized CT scan findings may be predictive of patients ‘outcome and had a correct correlate with laboratory findings and disease severity.