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.