Demographic, clinical and image findings on admission
63 patients that were treated between 7th, February, 2020 and 27th, March, 2020 were screened. Among them, 21 patients were excluded (see Methods and Fig. 1), resulting in a total of 42 patients being included in the final analysis. The median CT assessments per patient was 4 (range: 2–5 times), while the median follow-up period was 4 weeks (range: 3–6 weeks). The major demographic characteristics, clinical outcomes and laboratory findings of the cohort on admission are summarized in Table 1. Consistent with previous studies (4, 5), the majority of patients presented with fever (38/42, 90.5%), cough (39/42, 92.9%), and dyspnea (29/42, 69.0%) on admission, with an average CAP-Sym18 score of 18.7 ± 8.4. Moreover, the most frequent abnormalities were elevations in white blood cell, lymphocyte, and platelet counts as well as D-dimer (32/42, 76.2%) and C-reactive protein (CRP)(38/42, 90.5%) levels in the majority of patients on admission. Lastly, high-sensitivity cardiac troponin I was elevated in a subset of patients (8/42, 19.1%).
Table 1
Demographic, clinical and laboratory findings of patients on admission
|
Characteristics
|
|
All patients (n = 42)
|
Sex
|
Male
|
|
14 /42(33.3%)
|
|
Female
|
|
28/42 (66.7%)
|
Age (years)
|
|
|
64.7 ± 10.5
|
Body Mass Index (BMI)(kg/m2)
|
|
|
38.4 ± 5.7
|
Basic diseases
|
Heart disease
|
|
4/42(9.5%)
|
|
Chronic obstructive pulmonary disease
|
|
4/42(9.5%)
|
|
Hypertension
|
|
18/42(42.9%)
|
|
Diabetes
|
|
8/42(19.1%)
|
|
Cerebrovascular disease
|
|
3/42(7.1%)
|
|
Other diseases#
|
|
4/42(9.5%)
|
Clinical symptoms
|
Fever(> 37.3 °C)
|
|
38/42 (90.5%)
|
|
Cough
|
|
39/42 (92.9%)
|
|
Dyspnea
|
|
29/42 (69.0%)
|
|
CAP-Sym 18 score (on admission) *
|
|
18.7 ± 8.4 points
|
Symptom Onset to Admission
|
|
Mean
|
12.6 ± 5.5 days
|
|
|
Range
|
2–15 days
|
Laboratory Findings (on Admission)
|
White blood cell count (x109 per L)
|
< 4
|
7/42 (16.7%)
|
|
|
4–10
|
31/42 (73.8%)
|
|
|
> 10
|
4/42 (9.5%)
|
|
Lymphocyte count (x109 per L)
|
< 1.10
|
19/42(45.24.4%)
|
|
|
1.10–3.20
|
22/42(52.38%)
|
|
|
> 3.20
|
1/42(2.38)
|
|
Platelet count (× 109 per L)
|
< 100
|
5 /42(11.9%)
|
|
|
100–300
|
27/42 (64.3%)
|
|
|
> 300
|
10/42 (23.8%)
|
|
High-sensitivity cardiac troponin I (pg/mL)
|
> 99% up-limit
|
8/42 (19.1%)
|
|
D-dimer (µg/mL)
|
Elevated (> 0.5)
|
32/42 (76.2%)
|
|
C-reactive protein (CRP)(mg/L)
|
Elevated (> 1)
|
38/42 (90.5%)
|
#: Other diseases include thyroid diseases, urinary diseases and digestive system disorders
*:CAP-Sym score: CAP-symptom questionnaire, acquired as method mentioned
|
Table 2.
Chest CT image patterns on admission and discharge
|
Characteristic
|
Admission
All patients (n = 42)
|
Discharge All patients(n = 42)
|
Lobes involved
|
|
|
|
|
5
|
26/42 (61.9%)
|
23/42 (54.8%)
|
|
4
|
10/42 (23.8%)
|
9/42 (21.4%)
|
|
3
|
2/42 (4.8%)
|
4/42 (9.5%)
|
|
2
|
3/42 (7.1%)
|
4/42 (9.5%)
|
|
1
|
1/42 (2.4%)
|
1/42 (2.4%)
|
|
0
|
0/42 (0%)
|
1/42(2.4%)
|
Distribution of pulmonary lesions
|
|
|
|
|
Peripheral
|
13/42 (31.0%)
|
12/42 (28.3%)
|
|
Random
|
8/42 (19.0%)
|
9/42 (21.4%)
|
|
Diffuse
|
21/42 (50.0%)
|
21/42 (50.0%)
|
Scattering
|
|
|
|
|
Focal
|
1/42 (2.4%)
|
1/42 (2.4%)
|
|
Multifocal
|
41/42 (97.6%)
|
41/42 (97.6%)
|
Special signs
|
|
|
|
Pulmonary changes
|
|
|
|
|
Vacuolar sign
|
3/42 (7.1%)
|
1/42 (2.4%)
|
|
Cavitation
|
0/42 (0%)
|
0/42 (0%)
|
|
Microvascular dilation sign
|
20/42 (47.6%)
|
4/42 (9.53%)
|
|
Subpleural line
|
6/42 (14.3%)
|
7/42 (1.7%)
|
|
Subpleural transparent line
|
19/42 (45.2%)
|
11/42 (26.2%)
|
|
Crazy paving
|
34/42 (81.0%)
|
18/42 (42.9%)
|
|
Interstitial fibrosis
|
0 (0%)
|
0 (0%)
|
Bronchial changes
|
|
|
|
|
Air Bronchogram
|
11/42 (26.2%)
|
5/42 (11.9%)
|
|
Bronchial wall thickening
|
4/42 (9.5%)
|
2/42 (4.8%)
|
|
Traction bronchiectasis
|
3/42 (7.1%)
|
2/42 (4.8%)
|
|
Bronchus distortion
|
5/42 (11.9%)
|
2/42 (4.8%)
|
Pleural changes
|
|
|
|
|
Thickening of pleura
|
35/42 (83.3%)
|
21/42 (50.0%)
|
|
Pleural retraction sign
|
31/42 (73.8%)
|
19/42 (45.2%)
|
|
Pleural effusion(minor)
|
10/42 (23.8%)
|
3/42 (7.1%)
|
Lymphadenopathy
|
|
0/42 (0%)
|
0/42 (0%)
|
Pericardial effusion(minor)
|
|
5/42 (11.9%)
|
1/42 (2.4%)
|
On admission, a number of lung abnormalities were detected in chest CT images among all patients. As outlined in Table 2, patients typically presented with a multi-lobar involvement (more than one lobe), with the majority of patients showing lesions in 4 (23.8%) or 5 (61.9%) lobes. Consistent with previous studies (4, 5), lung abnormalities were peripherally distributed (31.0%), with a diffuse (50.0%) and/or multifocal pattern (97.6%) frequently observed on admission. In addition to the prominent finding of ground-glass opacities (GGO), a crazy-paving pattern of lung abnormalities was common (81.0%). Atypical CT manifestations included pleural changes, microvascular dilation and subpleural transparent line (45.2%) were less commonly observed.
To assess temporal changes in patient symptoms over the study period, CAP-sym 18 scores were evaluated from week 3 to week 8. As shown in Fig. 3, CAP-sym scores were highly variable in weeks 3 and 4, but showed a progressive decline from week 3 (median score 8, range = 0–20) to week 8 (median score 1, range = 0–4), consistent with patient recovery from COVID-19 and hospital discharge throughout the study period.
CT image patterns change course after 3 weeks since symptom onset
To determine temporal changes in CT findings at least 3 weeks from symptom onset to patient discharge, CT scans were analyzed by two experienced radiologists using two different scoring systems that were based on the area (i.e., ABS analysis) and intensity (i.e., IWS analysis) of lung abnormalities. Temporal changes in the two scores as well as the IWS grades (1–4) are shown in Fig. 4. Specifically, as shown in Fig. 4B, while individual IWS scoring grades, namely Grade 1 (GGO), Grade 2 (GGO with crazy paving), Grade 3 (GGO with consolidation), and Grade 4 (total consolidation), appeared consistent between weeks 3 and 4, there was a clear reduction in Grades 2 through 4 over time, consistent with resolution of more severe lung abnormalities. In comparing the ABS- and IWS-scoring approaches (Fig. 4A), IWS-scores showed a consistent decrease in a temporal fashion in all patients, indicative progressive resolution of lung abnormalities that aligned with symptom improvement. By contrast, rather than showing a reduction in lesion areas, ABS scores unexpectedly remained relatively stable, developing a more binary distribution in which scores remained elevated in a number of patients. Specifically, we found that in many patients the intensity of pulmonary lesions would decline throughout the study period without any change in lesion area. To determine the efficacy of ABS versus IWS systems within a given patient to track temporal changes in lung abnormalities, we compared the relative (week-to-week) changes in ABS and IWS systems. As shown in Fig. 4C, the IWS system showed a more dramatic and progressive changes in lung abnormalities from week 3 after symptom onward compared to the ABS system, suggesting the IWS system is more sensitive to detect improvements in lung abnormalities. Thus, changes in lung abnormality scoring with the IWS system closely tracks with improvements in symptom scores, with the ABS system showing an apparent disconnect.
Given the apparent greater sensitivity of the IWS system to assess temporal changes in lung abnormalities, an area under the curve (AUC) analysis was undertaken to further determine the average temporal changes in lesion burden during recovery by dividing the IWS-time curve by time. As shown in Fig. 5, the distribution of averaged AUC scores was 26.9 ± 16.1 (points per week), suggesting variability in the extent of lung lesions persisted into the late phase of recovery. Specifically, some patients still exhibited strong pulmonary pathology at weeks 7 and 8, the long-term impact of which require further study. Next, we sought to determine whether temporal changes in mean lesion burden (AUC score) were linked to clinical characteristics on admission. As shown in Table 3, Spearman correlations revealed a significant relationship between white blood cell count (WBC)(p = 0.0435), lymphocyte percentage (Lym%)(p = 0.0073), C-reactive protein (CRP)(p = 0.0004), and D-dimer levels (p = 0.0039) on admission with the average AUC level of a patient. To assess whether these four factors were predictive of mean lesion burden in our patient cohort, a Logistical regression analysis was undertaken (Fig. 6), with individuals initially grouped as a high-level AUC and a low-level AUC group based on whether the average AUC is ranked in the higher 50% or the lower 50%. Our results revealed that only CRP and D-dimer levels, with hazard ratio (HR) values of 5.32 and 1.05 respectively, were predictive of the degree of lung abnormalities in late-phase recovery. In spite of elevated inflammatory indices, no evidence of persistent interstitial fibrosis on CT images was observed during the late-phase in our patient cohort.
Table 3
Correlations between average AUC score with clinical factors on admission
|
R-value
|
P-value
|
Age
|
-0.1168
|
0.4613
|
Gender
|
-0.09004
|
0.5707
|
BMI
|
0.1496
|
0.4139
|
WBC
|
0.313
|
0.0435*
|
Lym%
|
-0.4080
|
0.0073*
|
Platelet count
|
0.1492
|
0.3456
|
CRP
|
0.5423
|
0.0004*
|
D-dimer
|
0.4412
|
0.0039*
|
Numbers of combined disorders
|
-0.06430
|
0.6896
|
BMI: body mass index; WBC: white blood cell count; Lym%: lymphocyte percentage; CRP: C-reactive protein. *:p < 0.05
|