The relationship between internet use preference and loneliness among college students during COVID-19: The chain mediating effect of online social support and self-esteem.

The outbreak of COVID-19, especially the demands of social interaction and spatial distancing behavior, has led to a surge in Internet use, which has also led to an increase in loneliness. Therefore, we investigated the role of online social support and self-esteem in the relationship between Internet use preference and loneliness. In this study, 1053 college students were surveyed with a questionnaire based on the framework of Ecological System Theory, and a chain mediation model was established to clarify the mechanism between Internet use preference and loneliness. The results show that Internet use preference not only positively predicts loneliness, but also indirectly influences loneliness through the mediators of online social support and self-esteem, thereby impacting loneliness through the "online social support → self-esteem" chain. The results also indicate the need to pay attention to college students' mental health status during COVID-19. The advent of COVID-19 has impacted people's lifestyles and has changed the impact of the Internet on individual mental health. This study provides a new way to further understand college students' Internet use preferences, online social support, self-esteem, and loneliness status during COVID-19. It provides targeted interventions for college students' loneliness during COVID-19.

Cardiac involvement in patients 1 year after recovery from moderate and severe COVID-19 infections.

Background: Some patients suffered persistent cardiac symptoms after hospital discharge following COVID-19 infection, including chest tightness, chest pain, and palpitation. However, the cardiac involvement in these patients remains unknown. The purpose of this study was to investigate the effect of COVID-19 infection on the cardiovascular system after 1 year of recovery in patients hospitalized with persistent cardiac symptoms. Materials and methods: In this prospective observational study, a total of 32 patients who had COVID-19 (11 diagnosed as severe COVID-19 and 21 as moderate) with persistent cardiac symptoms after hospital discharge were enrolled. Contrast-enhanced cardiovascular magnetic resonance (CMR) imaging was performed on all patients. Comparisons were made with age- and sex-matched healthy controls (n = 13), and age-, sex- and risk factor-matched controls (n = 21). Further analysis was made between the severe and moderate COVID-19 cohorts. Results: The mean time interval between acute COVID-19 infection and CMR was 462 ± 18 days. Patients recovered from COVID-19 had reduced left ventricular ejection fraction (LVEF) (p = 0.003) and increased extracellular volumes (ECVs) (p = 0.023) compared with healthy controls. Focal late gadolinium enhancement (LGE) was found in 22 (68.8%) patients, mainly distributed linearly in the septal mid-wall or patchily in RV insertion point. The LGE extent in patients with severe COVID-19 was higher than that in patients with moderate COVID-19 (p = 0.009). Conclusion: This 1-year follow-up study revealed that patients with persistent cardiac symptoms, after recovering from COVID-19, had decreased cardiac function and increased ECV compared with healthy controls. Patients with COVID-19 predominately had a LGE pattern of septal mid-wall or RV insertion point. Patients with severe COVID-19 had greater LGE extent than patients with moderate COVID-19.

Compatibility of Fuzi and Ginseng Significantly Increase the Exposure of Aconitines.

The herb-pair ginseng-Fuzi (the root of Aconitum carmichaelii) is the material basis of Shenfu prescriptions and is popular in traditional Chinese medicine for the treatment of heart failure, and even shock with severe-stage of COVID-19. A narrow therapeutic window of Fuzi may cause significant regional loss of property and life in clinics. Therefore, systemic elucidation of active components is crucial to improve the safety dose window of Shenfu oral prescriptions. A high performance liquid chromatography-mass spectrometry method was developed for quantification of 10 aconitines in SD rat plasma within 9 min. The limit of detection and the limit of quantification were below 0.032 ng/ml and 0.095 ng/ml, respectively. Furthermore, a systemic comparison with their pharmacokinetic characteristics after oral administration of a safe dosage of 2 g/kg of Fuzi and ginseng-Fuzi decoction for 24 h was conducted. Eight representative diester, monoester, and non-ester aconitines and two new active components (i.e., songorine and indaconitine) were all adopted to elucidating the differences of the pharmacokinetic parameters in vivo. The compatibility of Fuzi and ginseng could significantly increase the in vivo exposure of active components. The terminal elimination half-life and the area under the concentration-time curve of mesaconitine, benzoylaconitine, benzoylmesaconitine, benzoylhypaconitine, and songorine were all increased significantly. The hypaconitine, benzoylmesaconitine, and songorine were regarded as the main active components in vivo, which gave an effective clue for the development of new Shenfu oral prescriptions.

Factors Defining the Development of Severe Illness in Patients with COVID-19: A Retrospective Study.

OBJECTIVE: Early triage of patients with coronavirus disease 2019 (COVID-19) is pivotal in managing the disease. However, studies on the clinical risk score system of the risk factors for the development of severe disease are limited. Hence, we conducted a clinical risk score system for severe illness, which might optimize appropriate treatment strategies. METHODS: We conducted a retrospective, single-center study at the JinYinTan Hospital from January 24, 2020 to March 31, 2020. We evaluated the demographic, clinical, and laboratory data and performed a 10-fold cross-validation to split the data into a training set and validation set. We then screened the prognostic factors for severe illness using the least absolute shrinkage and selection operator (LASSO) and logistic regression, and finally conducted a risk score to estimate the probability of severe illness in the training set. Data from the validation set were used to validate the score. RESULTS: A total of 295 patients were included. From 49 potential risk factors, 3 variables were measured as the risk score: neutrophil to lymphocyte ratio ( OR, 1.27; 95% CI, 1.15-1.39), albumin ( OR, 0.76; 95% CI, 0.70-0.83), and chest computed tomography abnormalities ( OR, 2.01; 95% CI, 1.41-2.86) and the AUC of the validation cohort was 0.822 (95% CI, 0.7667-0.8776). CONCLUSION: This report may help define the potential of developing severe illness in patients with COVID-19 at an early stage, which might be related to the neutrophil to lymphocyte ratio, albumin, and chest computed tomography abnormalities.

Separation, identification and quantification of associated impurities in cobratide using sheathless CE-MS and CE-UV.

Cobratide is a peptide drug extracted from the venom of Chinese cobra, and has been widely used in the clinical treatment of chronic, intractable and persistent pain. In a recent study, it was reported that it has the potential to treat COVID-19. In order to control the quality of commercial cobratide drugs, a protocol was established for the separation, identification and quantification of cobratide and its associated impurities, in which sheathless capillary electrophoresis-mass spectrometry (CE-MS) was used for identification and a rapid capillary electrophoresis-ultraviolet-visible detector (CE-UV) method was developed for accurate quantification. Separation conditions that affect the resolution and MS intensities of cobratide and its associated impurities were investigated, including pH value, concentration of background electrolyte (BGE), ratio of organic additive and sample solution. The optimized CE conditions (BGE: 50 mM NH4Ac, pH 4.0; sample solution: deionized water) were used for both sheathless CE-MS and CE-UV methods. Three associated impurities were separated and identified for the first time by sheathless CE-MS. Then, a rapid CE-UV method was validated and used for accurate quantification of cobratide and its associated impurities. The CE-UV method showed good linearity between concentration and corrected peak area of cobratide in the concentration range of 5.36-536.30 µg mL-1. The limit of quantification of the CE-UV method was 4.16 µg mL-1. The relative standard deviations of migration time were less than 1% for both intra-day and inter-day experiments, and those of corrected peak area were less than 5%. Finally, different cobratide drugs were analyzed to evaluate the batch-to-batch consistency. This established protocol combining sheathless CE-MS and CE-UV methods would provide useful information for both quality control and process analysis of peptide drugs.

Does Government Intervention Ensure Food Safety? Evidence from China.

Food safety is related to public health, social welfare, and human survival, all of which are important and pressing areas of concern all over the world. The government plays an increasingly important role in the supervision of food safety. The role of the government, however, is also controversial. Using provincial panel data of China from 2005 to 2015, the present study intends to shed light on the associations between government intervention and food safety performance under two scenarios of local government-competition and noncompetition. This will be accomplished through an exploratory spatial data analysis and a spatial econometric model. The results reveal negative associations between food safety performance and government intervention without considering local government competition. As was also observed, government intervention not only inhibits the improvement of food safety in the region, but also has a negative spatial spillover effect on food safety in neighboring provinces. This is the result after considering government competition, thus, showing the competitive strategic interaction of the "race to the bottom". Further analysis reveals that, if geographically similar regions are selected as reference objects, the food safety performance of each province will have a stronger tendency to compete for the better. If regions with similar economic development levels are selected as reference objects, food safety performance will have a stronger tendency to compete for the worse. This work provides new evidence for the relationships between government intervention and food safety, and, also, proposes some insightful implications for policymakers for governing food safety.

Longitudinal Dynamics of the Neutralizing Antibody Response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global pandemic with no licensed vaccine or specific antiviral agents for therapy. Little is known about the longitudinal dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific neutralizing antibodies (NAbs) in patients with COVID-19. METHODS: Blood samples (n = 173) were collected from 30 patients with COVID-19 over a 3-month period after symptom onset and analyzed for SARS-CoV-2-specific NAbs using the lentiviral pseudotype assay, coincident with the levels of IgG and proinflammatory cytokines. RESULTS: SARS-CoV-2-specific NAb titers were low for the first 7-10 days after symptom onset and increased after 2-3 weeks. The median peak time for NAbs was 33 days (interquartile range [IQR], 24-59 days) after symptom onset. NAb titers in 93.3% (28/30) of the patients declined gradually over the 3-month study period, with a median decrease of 34.8% (IQR, 19.6-42.4%). NAb titers increased over time in parallel with the rise in immunoglobulin G (IgG) antibody levels, correlating well at week 3 (r = 0.41, P < .05). The NAb titers also demonstrated a significant positive correlation with levels of plasma proinflammatory cytokines, including stem cell factor (SCF), TNF-related apoptosis-inducing ligand (TRAIL), and macrophage colony-stimulating factor (M-CSF). CONCLUSIONS: These data provide useful information regarding dynamic changes in NAbs in patients with COVID-19 during the acute and convalescent phases.

Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging.

PURPOSE: In the prediction of COVID-19 disease progression, a clear illustration and early determination of an area that will be affected by pneumonia remain great challenges. In this study, we aimed to predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness by using chest CT. METHODS: COVID-19 patients who underwent three chest CT scans in the progressive phase were retrospectively enrolled. An extended CT ventilation imaging (CTVI) method was proposed in this work that was adapted to use two chest CT scans acquired on different days, and then lung ventilation maps were generated. The prediction maps were obtained according to the fractional ventilation values, which were related to pulmonary regional function and tissue property changes. The third CT scan was used to validate whether the prediction maps could be used to distinguish healthy regions and potential lesions. RESULTS: A total of 30 patients (mean age ± SD, 43 ± 10 years, 19 females, and 2-12 days between the second and third CT scans) were included in this study. The predicted lesion locations and sizes were almost the same as the true ones visualized in third CT scan. Quantitatively, the predicted lesion volumes and true lesion volumes showed both a good Pearson correlation (R2 = 0.80; P < 0.001) and good consistency in the Bland-Altman plot (mean bias = 0.04 cm3). Regarding the enlargements of the existing lesions, prediction results also exhibited a good Pearson correlation (R2 = 0.76; P < 0.001) with true lesion enlargements. CONCLUSION: The present findings demonstrated that the extended CTVI method could accurately predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness, which is helpful for physicians to predetermine the severity of COVID-19 pneumonia and make effective treatment plans in advance.

Serial Quantitative Chest CT Assessment of COVID-19: A Deep Learning Approach.

PURPOSE: To quantitatively evaluate lung burden changes in patients with coronavirus disease 2019 (COVID-19) by using serial CT scan by an automated deep learning method. MATERIALS AND METHODS: Patients with COVID-19, who underwent chest CT between January 1 and February 3, 2020, were retrospectively evaluated. The patients were divided into mild, moderate, severe, and critical types, according to their baseline clinical, laboratory, and CT findings. CT lung opacification percentages of the whole lung and five lobes were automatically quantified by a commercial deep learning software and compared with those at follow-up CT scans. Longitudinal changes of the CT quantitative parameter were also compared among the four clinical types. RESULTS: A total of 126 patients with COVID-19 (mean age, 52 years ± 15 [standard deviation]; 53.2% males) were evaluated, including six mild, 94 moderate, 20 severe, and six critical cases. CT-derived opacification percentage was significantly different among clinical groups at baseline, gradually progressing from mild to critical type (all P < .01). Overall, the whole-lung opacification percentage significantly increased from baseline CT to first follow-up CT (median [interquartile range]: 3.6% [0.5%, 12.1%] vs 8.7% [2.7%, 21.2%]; P < .01). No significant progression of the opacification percentages was noted from the first follow-up to second follow-up CT (8.7% [2.7%, 21.2%] vs 6.0% [1.9%, 24.3%]; P = .655). CONCLUSION: The quantification of lung opacification in COVID-19 measured at chest CT by using a commercially available deep learning-based tool was significantly different among groups with different clinical severity. This approach could potentially eliminate the subjectivity in the initial assessment and follow-up of pulmonary findings in COVID-19.Supplemental material is available for this article.© RSNA, 2020.

Mobile chest X-ray manifestations of 54 deceased patients with coronavirus disease 2019: Retrospective study.

To describe the mobile chest X-ray manifestations of deceased patients with coronavirus disease 2019 (COVID-19).In this retrospective study, we analyzed in patients with COVID-19 from Tongji Hospital (Wuhan, China), who had been died between February 18 and March 25, 2020. Two radiologists analyzed the radiologic characteristics of mobile chest X-ray, and analyzed the serial X-ray changes.Fifty-four deceased patients with COVID-19 were included in the study. We found that 50 (93%) patients with lesions occurred in the bilateral lung, 4 (7%) patients occurred in the right lung, 54 (100%) patients were multifocal involvement. The number of lung fields involved was 42 (78%) patients in 6 fields, 3 (6%) patients in 5 lung fields, 4 (7%) patients in 4 lung fields, and 5 (9%) patients in 3 lung fields. Fifty-three (98%) patients had patchy opacities, 3 (6%) patients had round or oval solid nodules, 9 (17%) patients had fibrous stripes, 13 (24%) patients had pleural effusion, 8 (15%) patients had pleural thickening, 6 (11%) patients had pneumothorax, 3 (6%) patients had subcutaneous emphysema. Among the 24 patients who had serial mobile chest X-rays, 16 (67%) patients had the progression of the lesions, 8 (33%) patients had no significant change of the lesions, and there was no case of reduction of the lesions.The mobile chest X-ray manifestations of deceased patients with COVID-19 were mostly bilateral lung, multifocal involvement, and extensive lung field, and pleural effusion, pleural thickening, and pneumothorax probably could be observed. The serial mobile chest X-ray showed that the chest lesions were progressive with a high probability.

Fibrotic Changes Depicted by Thin-Section CT in Patients With COVID-19 at the Early Recovery Stage: Preliminary Experience.

Objectives: To analyze follow-up CTs of patients recovering from COVID-19 in Wuhan, focusing on fibrotic change and its relevant risk factors. Methods: From January 13 to February 27, 2020, 166 hospitalized patients meeting our criteria were included. The scores of fibrotic patterns on follow-up CT were evaluated. Patients were designated as group 1 (with CT evidence of fibrotic pattern) and group 2 (without CT evidence of fibrotic pattern). Multivariate logistic regression was performed to explore risk factors for fibrotic change in patients with COVID-19. Results: The follow-up CTs were obtained on 56 days (median, IQR 51-63 days) after symptom onset. Of the 166 patients (mean age, 57 ± 15 years; 69/166 male), 46% (76/166) had CT evidence of fibrotic change and 77% (127/166) were severe or critical cases. Among patients with fibrotic change on CT, 84% (64/76) got a minimal or mild score of fibrosis. The high total score on peak CT, peak eosinophils, erythrocyte sedimentation rate (ESR) and advancing age were related to lung fibrotic change in patients with COVID-19. Conclusion: Forty six percentages of patients (mainly severe or critical cases) with COVID-19 showed fibrotic change on follow-up CT at early recovery phase, while the extent of fibrosis was not large. The advancing age, high total score on peak CT, peak eosinophils and ESR were associated with fibrotic change depicted by CT in patients recovering from COVID-19. An extended follow up by CT imaging and pulmonary function testing is necessary to fully assess the sequela of COVID-19.

Recent discoveries in HIV-1 reverse transcriptase inhibitors.

HIV-1 reverse transcriptase inhibitors (RTIs) are indispensable components of highly active antiretroviral therapy (HAART), which has achieved great success in controlling AIDS epidemic in reducing drastically the morbidity and mortality of HIV-infected patients. RTIs are divided into two categories, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs). In this review, the recent discoveries in NRTIs and NNRTIs, including approved anti-HIV drugs and noteworthy drug candidates in different development stages, are summarized, and their future direction is prospected.

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

Background: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics. Methods: We trained a U-Net-based model on unenhanced chest CT scans obtained from 2447 patients admitted to Tongji Hospital (Wuhan, China) between Feb 1, 2020, and March 3, 2020 (1647 patients with RT-PCR-confirmed COVID-19 and 800 patients without COVID-19) to segment lung opacities and alert cases with COVID-19 imaging manifestations. The ability of artificial intelligence (AI) to triage patients suspected to have COVID-19 was assessed in a large external validation set, which included 2120 retrospectively collected consecutive cases from three fever clinics inside and outside the epidemic centre of Wuhan (Tianyou Hospital [Wuhan, China; area of high COVID-19 prevalence], Xianning Central Hospital [Xianning, China; area of medium COVID-19 prevalence], and The Second Xiangya Hospital [Changsha, China; area of low COVID-19 prevalence]) between Jan 22, 2020, and Feb 14, 2020. To validate the sensitivity of the algorithm in a larger sample of patients with COVID-19, we also included 761 chest CT scans from 722 patients with RT-PCR-confirmed COVID-19 treated in a makeshift hospital (Guanggu Fangcang Hospital, Wuhan, China) between Feb 21, 2020, and March 6, 2020. Additionally, the accuracy of AI was compared with a radiologist panel for the identification of lesion burden increase on pairs of CT scans obtained from 100 patients with COVID-19. Findings: In the external validation set, using radiological reports as the reference standard, AI-aided triage achieved an area under the curve of 0·953 (95% CI 0·949-0·959), with a sensitivity of 0·923 (95% CI 0·914-0·932), specificity of 0·851 (0·842-0·860), a positive predictive value of 0·790 (0·777-0·803), and a negative predictive value of 0·948 (0·941-0·954). AI took a median of 0·55 min (IQR: 0·43-0·63) to flag a positive case, whereas radiologists took a median of 16·21 min (11·67-25·71) to draft a report and 23·06 min (15·67-39·20) to release a report. With regard to the identification of increases in lesion burden, AI achieved a sensitivity of 0·962 (95% CI 0·947-1·000) and a specificity of 0·875 (95 %CI 0·833-0·923). The agreement between AI and the radiologist panel was high (Cohen's kappa coefficient 0·839, 95% CI 0·718-0·940). Interpretation: A deep learning algorithm for triaging patients with suspected COVID-19 at fever clinics was developed and externally validated. Given its high accuracy across populations with varied COVID-19 prevalence, integration of this system into the standard clinical workflow could expedite identification of chest CT scans with imaging indications of COVID-19. Funding: Special Project for Emergency of the Science and Technology Department of Hubei Province, China.

Cardiac Involvement in Patients Recovered From COVID-2019 Identified Using Magnetic Resonance Imaging.

Objectives: This study evaluated cardiac involvement in patients recovered from coronavirus disease-2019 (COVID-19) using cardiac magnetic resonance (CMR). Background: Myocardial injury caused by COVID-19 was previously reported in hospitalized patients. It is unknown if there is sustained cardiac involvement after patients' recovery from COVID-19. Methods: Twenty-six patients recovered from COVID-19 who reported cardiac symptoms and underwent CMR examinations were retrospectively included. CMR protocols consisted of conventional sequences (cine, T2-weighted imaging, and late gadolinium enhancement [LGE]) and quantitative mapping sequences (T1, T2, and extracellular volume [ECV] mapping). Edema ratio and LGE were assessed in post-COVID-19 patients. Cardiac function, native T1/T2, and ECV were quantitatively evaluated and compared with controls. Results: Fifteen patients (58%) had abnormal CMR findings on conventional CMR sequences: myocardial edema was found in 14 (54%) patients and LGE was found in 8 (31%) patients. Decreased right ventricle functional parameters including ejection fraction, cardiac index, and stroke volume/body surface area were found in patients with positive conventional CMR findings. Using quantitative mapping, global native T1, T2, and ECV were all found to be significantly elevated in patients with positive conventional CMR findings, compared with patients without positive findings and controls (median [interquartile range]: native T1 1,271 ms [1,243 to 1,298 ms] vs. 1,237 ms [1,216 to 1,262 ms] vs. 1,224 ms [1,217 to 1,245 ms]; mean ± SD: T2 42.7 ± 3.1 ms vs. 38.1 ms ± 2.4 vs. 39.1 ms ± 3.1; median [interquartile range]: 28.2% [24.8% to 36.2%] vs. 24.8% [23.1% to 25.4%] vs. 23.7% [22.2% to 25.2%]; p = 0.002; p < 0.001, and p = 0.002, respectively). Conclusions: Cardiac involvement was found in a proportion of patients recovered from COVID-19. CMR manifestation included myocardial edema, fibrosis, and impaired right ventricle function. Attention should be paid to the possible myocardial involvement in patients recovered from COVID-19 with cardiac symptoms.

A Peptide-Based Magnetic Chemiluminescence Enzyme Immunoassay for Serological Diagnosis of Coronavirus Disease 2019.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel ß-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection. METHODS: In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2. RESULTS: To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively. CONCLUSIONS: Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.

Early CT features and temporal lung changes in COVID-19 pneumonia in Wuhan, China.

PURPOSE: To analyse the high-resolution computed tomography (HRCT) early imaging features and the changing trend of coronavirus disease 2019 (COVID-19) pneumonia. MATERIALS AND METHODS: Forty-six patients with COVID-19 pneumonia who had an isolated lesion on the first positive CT were enrolled in this study. The following parameters were recorded for each lesion: sites, sizes, location (peripheral or central), attenuation (ground-glass opacity or consolidation), and other abnormalities (supply pulmonary artery dilation, air bronchogram, interstitial thickening, etc.). The follow-up CT images were compared with the previous CT scans, and the development of the lesions was evaluated. RESULTS: The lesions tended to be peripheral and subpleural. All the lesions exhibited ground-glass opacity with or without consolidation. A higher proportion of supply pulmonary artery dilation (89.13 % [41/46]) and air bronchogram (69.57 % [32/46]) were found. Other findings included thickening of the intralobular interstitium and a halo sign of ground glass around a solid nodule. Cavitation, calcification or lymphadelopathy were not observed. The reticular patterns were noted from the 14 days after symptoms onset in 7 of 20 patients (45 %). At 22-31 days, the lesions were completely absorbed only in 2 of 7 patients (28.57 %). CONCLUSION: The typical early CT features of COVID-19 pneumonia are ground-glass opacity, and located peripheral or subpleural location, and with supply pulmonary artery dilation. Reticulation was evident after the 2nd week and persisted in half of patients evaluated in 4 weeks after the onset. Long-term follow-up is required to determine whether the reticulation represents irreversible fibrosis.

Early Clinical and CT Manifestations of Coronavirus Disease 2019 (COVID-19) Pneumonia.

OBJECTIVE. The purpose of this study was to investigate early clinical and CT manifestations of coronavirus disease (COVID-19) pneumonia. MATERIALS AND METHODS. Patients with COVID-19 pneumonia confirmed by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid test (reverse transcription-polymerase chain reaction) were enrolled in this retrospective study. The clinical manifestations, laboratory results, and CT findings were evaluated. RESULTS. One hundred eight patients (38 men, 70 women; age range, 21-90 years) were included in the study. The clinical manifestations were fever in 94 of 108 (87%) patients, dry cough in 65 (60%), and fatigue in 42 (39%). The laboratory results were normal WBC count in 97 (90%) patients and normal or reduced lymphocyte count in 65 (60%). High-sensitivity C-reactive protein level was elevated in 107 (99%) patients. The distribution of involved lobes was one lobe in 38 (35%) patients, two or three lobes in 24 (22%), and four or five lobes in 46 (43%). The major involvement was peripheral (97 patients [90%]), and the common lesion shape was patchy (93 patients [86%]). Sixty-five (60%) patients had ground-glass opacity (GGO), and 44 (41%) had GGO with consolidation. The size of lesions varied from smaller than 1 cm (10 patients [9%]) to larger than 3 cm (56 patients [52%]). Vascular thickening (86 patients [80%]), crazy paving pattern (43 patients [40%]), air bronchogram sign (52 patients [48%]), and halo sign (69 [64%]) were also observed in this study. CONCLUSION. The early clinical and laboratory findings of COVID-19 pneumonia are low to midgrade fever, dry cough, and fatigue with normal WBC count, reduced lymphocyte count, and elevated high-sensitivity C-reactive protein level. The early CT findings are patchy GGO with or without consolidation involving multiple lobes, mainly in the peripheral zone, accompanied by halo sign, vascular thickening, crazy paving pattern, or air bronchogram sign.