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Background and Objectives: To investigate whether coronavirus disease 2019 (COVID-19) survivors who had different disease severities have different levels of pulmonary sequelae at 3 months post-discharge.Methods: COVID-19 patients discharged from four hospitals 3 months previously, recovered asymptomatic patients from an isolation hotel, and uninfected healthy controls (HCs) from the community were prospectively recruited. Participants were recruited at Wuhan Union Hospital and underwent examinations, including quality-of-life evaluation (St. George Respiratory Questionnaire [SGRQ]), laboratory examination, chest computed tomography (CT) imaging, and pulmonary function tests.Results: A total of 216 participants were recruited, including 95 patients who had recovered from severe/critical COVID-19 (SPs), 51 who had recovered from mild/moderate disease (MPs), 28 who had recovered from asymptomatic disease (APs), and 42 HCs. In total, 154 out of 174 (88.5%) recovered COVID-19 patients tested positive for serum SARS-COV-2 IgG, but only 19 (10.9%) were still positive for IgM. The SGRQ scores were highest in the SPs, while APs had slightly higher SGRQ scores than those of HCs; 85.1% of SPs and 68.0% of MPs still had residual CT abnormalities, mainly ground-glass opacity (GGO) followed by strip-like fibrosis at 3 months after discharge, but the pneumonic lesions were largely absorbed in the recovered SPs or MPs relative to findings in the acute phase. Pulmonary function showed that the frequency of lung diffusion capacity for carbon monoxide abnormalities were comparable in SPs and MPs (47.1 vs. 41.7%), while abnormal total lung capacity (TLC) and residual volume (RV) were more frequent in SPs than in MPs (TLC, 18.8 vs. 8.3%; RV, 11.8 vs. 0%).Conclusions: Pulmonary abnormalities remained after recovery from COVID-19 and were more frequent and conspicuous in SPs at 3 months after discharge.

Objective To compare the 5-year outcomes of acute versus subacute thoracic endovascular aortic repair (TEVAR) in patients with uncomplicated acute type B aortic dissection (ATBAD). Methods Between March 2008 and September 2018, 238 consecutive patients with uncomplicated ATBAD underwent TEVAR in the acute or subacute phase and were analyzed retrospectively. The primary end points were all-cause death and aortic-related death. The secondary end point was a composite of the outcomes of death from any cause, rupture, new dissection, retrograde type A aortic dissection, endoleak, and late reintervention. Inverse probability treatment weighting was used to balance baseline characteristics. Weight-adjusted Kaplan-Meier estimate with landmark analysis and weighted Cox model were performed to assess time-to-event outcomes. Results In the inverse probability treatment weighting-adjusted population, the 30-day mortality was 1.5% in the acute TEVAR group and 0% in the subacute TEVAR group (P = .24). The incidence of 30-day adverse events occurred in 16.8% and 6.9% patients in the acute TEVAR and subacute TEVAR groups, respectively (P = .13). At 5 years, there was no statistically significant difference in all-cause death (hazard ratio [HR], 1.50; 95% confidence interval [CI], 0.59-3.81; P = .39) and aortic-related death (HR, 1.11; 95% CI, 0.34-3.60; P = .86) between the two groups. The composite outcomes occurred in 30 patients (23.0%) in the acute TEVAR group and 18 patients (22.3%) in the subacute TEVAR group, respectively (HR, 0.67; 95% CI, 0.36-1.25; P = .20). However, a landmark analysis of the composite outcomes indicated that there was a significant interaction between treatment effect and time (Pinteraction = .01), with a significantly higher incidence of the composite outcomes in the acute TEVAR group compared with the subacute TEVAR group within 1 year (HR, 0.25; 95% CI, 0.08-0.79; P = .02), and a comparable rate between 1 and 5 years (HR, 1.25; 95% CI, 0.56-2.76; P = .59). Conclusions At the 5-year follow-up, no significant differences exist in the all-cause death and aortic-related death between acute and subacute TEVAR. However, acute TEVAR is associated with an increased rate of severe complications within 1 year, which suggests that performing TEVAR in the subacute phase of ATBAD may be the preferable option.

BackgroundChest computed tomography (CT) has been widely used to assess pulmonary involvement in COVID-19. We aimed to investigate the correlation between chest CT and clinical features in COVID-19 suspected patients with or without fever.MethodsWe retrospectively enrolled 211 COVID-19 suspected patients who underwent both chest CT and reverse transcription polymerase chain reaction in Wuhan, China. The performance of CT in patients with relevant onset of symptoms, with fever (n = 141) and without fever (n = 70), was assessed respectively.ResultsThe sensitivity of CT for COVID-19 was 97.3%, with area under the curve (AUC) of 0.71 (95% confidence interval [CI], 0.66–0.76). There were 141 suspected patients with fever and 70 without fever. In the fever group, 4 variables were screened to establish the basic model: age, monocyte, red blood cell, and hypertension. The AUC of the basic model was 0.72 (95% CI, 0.63–0.81), while the AUC of the CT-aided model was 0.77 (95% CI, 0.68–0.85), a significant difference (P < .05). In the nonfever group, only dry cough was screened out to establish the basic model. The AUC was 0.76 (95% CI, 0.64–0.88), which was not significantly different than the CT-aided model (P = .08).ConclusionsChest CT has a high sensitivity in patients with COVID-19, and it can improve diagnostic accuracy for COVID-19 suspected patients with fever during the initial screen, whereas its value for nonfever patients remains questionable.

This study aims to investigate radiological and clinical characteristics of suspected COVID-19 patients with negative RT-PCR testing. 22 suspected COVID-19 patients with 2-5 negative RT-PCR testing were enrolled. The most common symptoms at onset included fever (18[81.8%] patients), fatigue (16[72.7%]) and cough (12[54.5%]). 20(90.9%) patients were with normal or decreased Leukocyte count, 17 (77.3%) with decreased Lymphocyte count, 16 (72.7%) and 18 (81.8%) with increased level of C-reactive protein and D-dimers, respectively. Ground-glass opacity (GGO) (22[100]), reticular/interlobular septal thickening (11 [50%]) and consolidation (14 [63.6%)) with predominantly bilateral and peripheral distribution were typical findings at initial CT scan. The CT score of right lower lobe was significantly higher than right upper lobe (P=0.042). The total CT scores of group 2, 3, 4 (2nd week, 3rd week, 4th week and after) were significantly higher than group 1 (1st week) (P＜0.01,for all). After rapid progression at first week, the most extensive pulmonary involvement emerged at second week after symptom onset, then the involvement gradually decreased. Given the clinical symptoms, laboratory results and typical radiological manifestations, even suspected COVID-19 patients with multiple negative RT-PCR testing deserve great concern for active management.

Background: In this study, our focus was on pulmonary sequelae of coronavirus disease 2019 (COVID-19). We aimed to develop and validate CT-based radiomic models for predicting the presence of residual lung lesions in COVID-19 survivors at three months after discharge. Methods: We retrospectively enrolled 162 COVID-19 confirmed patients in our hospital (84 patients with residual lung lesions and 78 patients without residual lung lesions, at three months after discharge). The patients were all randomly allocated to a training set (n = 114) or a test set (n = 48). Radiomic features were extracted from chest CT images in different regions (entire lung or lesion) and at different time points (at hospital admission or at discharge) to build different models, sequentially, or in combination, as follows: (1) Lesion_A model (based on the lesion region at admission CT); (2) Lesion_D model (based on the lesion region at discharge CT); (3) Δlesion model (based on the lesion region at admission CT and discharge CT); (4) Lung_A model (based on the lung region at admission CT); (5) Lung_D model (based on the lung region at discharge CT); (6) Δlung model (based on the lung region at admission CT and discharge CT). The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to evaluate the predictive performances of the radiomic models. Results: Among the six models, the Lesion_D and the Δlesion models achieved better predictive efficacy, with AUCs of 0.907 and 0.927, sensitivity of 0.898 and 0.763, and specificity of 0.855 and 0.964 in the training set, and AUCs of 0.875 and 0.837, sensitivity of 0.920 and 0.680, and specificity of 0.826 and 0.913 in the test set, respectively. Conclusions: The CT-based radiomic models showed good predictive effects on the presence of residual lung lesions in COVID-19 survivors at three months after discharge, which may help doctors to plan follow-up work and to reduce the psychological burden of COVID-19 survivors.

Objective: To provide the quantitative volumetric data of the total lung and lobes in inspiration and expiration from healthy adults, and to explore the value of paired inspiratory–expiratory chest CT scan in pulmonary ventilatory function and further explore the influence of each lobe on ventilation. Methods: A total of 65 adults (29 males and 36 females) with normal clinical pulmonary function test (PFT) and paired inspiratory–expiratory chest CT scan were retrospectively enrolled. The inspiratory and expiratory volumetric indexes of the total lung (TL) and 5 lobes (left upper lobe [LUL], left lower lobe [LLL], right upper lobe [RUL], right middle lobe [RML], and right lower lobe [RLL]) were obtained by Philips IntelliSpace Portal image postprocessing workstation, including inspiratory lung volume (LVin), expiratory lung volume (LVex), volume change (∆LV), and well-aerated lung volume (WAL, lung tissue with CT threshold between −950 and −750 HU in inspiratory scan). Spearman correlation analysis was used to explore the correlation between CT quantitative indexes of the total lung and ventilatory function indexes (including total lung capacity [TLC], residual volume [RV], and force vital capacity [FVC]). Multiple stepwise regression analysis was used to explore the influence of each lobe on ventilation. Results: At end-inspiratory phase, the LVin-TL was 4664.6 (4282.7, 5916.2) mL, the WALTL was 4173 (3639.6, 5250.9) mL; both showed excellent correlation with TLC (LVin-TL: r = 0.890, p < 0.001; WALTL: r = 0.879, p < 0.001). From multiple linear regression analysis with lobar CT indexes as variables, the LVin and WAL of these two lobes, LLL and RUL, showed a significant relationship with TLC. At end-expiratory phase, the LVex-TL was 2325.2 (1969.7, 2722.5) mL with good correlation with RV (r = 0.811, p < 0.001), of which the LVex of RUL and RML had a significant relationship with RV. For the volumetric change within breathing, the ∆LVTL was 2485.6 (2169.8, 3078.1) mL with good correlation with FVC (r = 0.719, p < 0.001), moreover, WALTL showed a better correlation with FVC (r = 0.817, p < 0.001) than that of ∆LVTL. Likewise, there was also a strong association between ∆LV, WAL of these two lobes (LLL and RUL), and FVC. Conclusions: The quantitative indexes derived from paired inspiratory–expiratory chest CT could reflect the clinical pulmonary ventilatory function, LLL, and RUL give greater impact on ventilation. Thus, the pulmonary functional evaluation needs to be more precise and not limited to the total lung level.