ABSTRACT
OBJECTIVE: Analyzing the symptom characteristics of Coronavirus Disease 2019(COVID-19) to improve control and prevention. METHODS: Using the Baidu Index Platform (http://index.baidu.com) and the website of Chinese Center for Disease Control and Prevention as data resources to obtain the search volume (SV) of keywords for symptoms associated with COVID-19 from January 1 to February 20 in each year from 2017 to 2020 and the epidemic data in Hubei province and the other top 9 impacted provinces in China. Data of 2020 were compared with those of the previous three years. Data of Hubei province were compared with those of the other 9 provinces. The differences and characteristics of the SV of COVID-19-related symptoms, and the correlations between the SV of COVID-19 and the number of newly confirmed/suspected cases were analyzed. The lag effects were discussed. RESULTS: Comparing the SV from January 1, 2020 to February 20, 2020 with those for the same period of the previous three years, Hubei's SV for cough, fever, diarrhea, chest tightness, dyspnea, and other symptoms were significantly increased. The total SV of lower respiratory symptoms was significantly higher than that of upper respiratory symptoms (Pï¼0.001). The SV of COVID-19 in Hubei province was significantly correlated with the number of newly confirmed/suspected cases (r confirmed = 0.723, r suspected = 0.863, both p < 0.001). The results of the distributed lag model suggested that the patients who searched relevant symptoms on the Internet may begin to see doctors in 2-3 days later and be confirmed in 3-4 days later. CONCLUSION: The total SV of lower respiratory symptoms was higher than that of upper respiratory symptoms, and the SV of diarrhea also increased significantly. It warned us to pay attention to not only the symptoms of the lower respiratory tract but also the gastrointestinal symptoms, especially diarrhea in patients with COVID-19. Internet search behavior had a positive correlation with the number of newly confirmed/suspected cases, suggesting that big data has an important role in the early warning of infectious diseases.
ABSTRACT
In the last few decades, there has been a progressive increase in the prevalence of allergic rhinitis (AR) in China, where it now affects approximately 250 million people. AR prevention and treatment include allergen avoidance, pharmacotherapy, allergen immunotherapy (AIT), and patient education, among which AIT is the only curative intervention. AIT targets the disease etiology and may potentially modify the immune system as well as induce allergen-specific immune tolerance in patients with AR. In 2017, a team of experts from the Chinese Society of Allergy (CSA) and the Chinese Allergic Rhinitis Collaborative Research Group (C2AR2G) produced the first English version of Chinese AIT guidelines for AR. Since then, there has been considerable progress in basic research of and clinical practice for AIT, especially regarding the role of follicular regulatory T (TFR) cells in the pathogenesis of AR and the use of allergen-specific immunoglobulin E (sIgE) in nasal secretions for the diagnosis of AR. Additionally, potential biomarkers, including TFR cells, sIgG4, and sIgE, have been used to monitor the incidence and progression of AR. Moreover, there has been a novel understanding of AIT during the coronavirus disease 2019 pandemic. Hence, there was an urgent need to update the AIT guideline for AR by a team of experts from CSA and C2AR2G. This document aims to serve as professional reference material on AIT for AR treatment in China, thus improving the development of AIT across the world.
ABSTRACT
Corticosteroids are efficacious in treating chronic rhinosinusitis (CRS), but concerns on the potential side effects remain, especially for long-term usage of systemic corticosteroids. Accumulated evidence shows that transnasal nebulization may be a reasonable solution in balancing both efficacy and safety. However, no consensus or guideline has been formulated on the use of steroid transnasal nebulization in treating CRS. The consensus is achieved through literature review and exchange of Chinese experts in Group of Otorhinolaryngology and Ophthalmology, Chinese Society of Allergy (CSA). This document covers the development, equipment, pharmacological mechanism, and evidence-based efficacy and safety, as well as the special concern of the application of steroid transnasal nebulization during the coronavirus disease (COVID-19) pandemic. The expert consensus clarifies the application of steroid transnasal nebulization in treating CRS and common comorbidities during the perioperative and postoperative periods.
ABSTRACT
BACKGROUND: Chest CT is important for the diagnosis of Corona Virus Disease 2019, which is caused by SARS-CoV-2 via the receptor angiotensin-converting enzyme 2. This study aimed to present special chest CT changes in the detection and management of COVID-19. METHODS: From February 20 to March 6, 2020, clinical data and chest CT of patients with COVID-19 being treated by the Hubei Medical Team were retrospectively analyzed with a time-interval of 2 weeks. In addition, the expressions of ACE2 in different parts of the respiratory system were detected by immunohistochemical staining to explain the special chest CT features of COVID-19 by ACE2 expression. RESULTS: Of 58 patients, the main respiratory manifestations were fever and cough. Spherical or patchy GGO was the initial CT manifestation of COVID-19 pneumonia. CT findings manifested as rapid evolution from focal unilateral to diffuse bilateral ground-glass opacities (GGO) that progressed to or co-existed with consolidations in chest CT scans. Lung consolidation increased as the disease progressed, accounting for 63.2%, 76.3%, and 87.5% in group 1 (disease course with 0 - 2 weeks), group 2 (2 - 4 weeks), and group 3 (> 4 weeks). Fibrous lesions (72.3%), high density vascular shadow (69.2%), reticular pattern (63.1%), and subpleural parallel sign (61.5%) were common signs of chest CT of COVID-19. IHC results showed that ACE2-expression in the pulmonary alveoli was significantly higher than that in the bronchial mucosa and pleura (p < 0.001). CONCLUSIONS: The special change of CT features in the lung of COVID-19 pneumonia patients have a connection with ACE2 expression patterns in the respiratory system.
Subject(s)
COVID-19 , Peptidyl-Dipeptidase A , Humans , Lung/diagnostic imaging , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray ComputedABSTRACT
BACKGROUND: Respiratory epithelium expressing angiotensin-converting enzyme 2 (ACE2) is the entry for novel coronavirus (SARS-CoV-2), pathogen of the COVID-19 pneumonia outbreak, although a few recent studies have found different ACE2 expression in lung tissue of smokers. The effect of smoking on ACE2 expression and COVID-19 is still not clear. So, we did this research to determine the effect of smoking on ACE2 expression pattern and its relationship with the risk and severity of COVID-19. METHODS: The clinical data of COVID-19 patients with smoking and non-smoking were analyzed, and ACE2 expression of respiratory and digestive mucosa epithelia from smoker and non-smoker patients or healthy subjects were detected by immunohistochemical (IHC) staining. RESULTS: Of all 295 laboratory-confirmed COVID-19 patients, only 24 (8.1%) were current smokers with moderate smoking or above, which accounted for 54.2% of severe cases with higher mortality than non-smokers (8.3% vs. 0.4%, p = 0.018). Data analysis showed the proportion of smokers in COVID-19 patients was lower than that in general population of China (Z = 11.65, P < 0.001). IHC staining showed ACE2 expression in respiratory and digestive epithelia of smokers were generally downregulated. CONCLUSIONS: The proportion of smokers in COVID-19 patients was lower, which may be explained by ACE2 downregulation in respiratory mucosa epithelia. However, smoking COVID-19 patients accounted for a higher proportion in severe cases and higher mortality than for non-smoking COVID-19 patients, which needs to be noted.
Subject(s)
COVID-19 , Peptidyl-Dipeptidase A , Angiotensin-Converting Enzyme 2 , China/epidemiology , Humans , Peptidyl-Dipeptidase A/genetics , SARS-CoV-2 , Smoking/adverse effectsABSTRACT
BACKGROUND: To explore the epidemiological characteristics of allergic rhinitis (AR) and allergic conjunctivitis (AC) based on the Internet big data. METHODS: The Baidu index (BDI) of keywords "allergic rhinitis" and "allergic conjunctivitis" in Mandarin, the daily pollen concentration (PC) released by the Beijing Meteorological Bureau and the volumes of outpatient visits (OV) of the Beijing Tongren Hospital (Beijing) and the Third Affiliated Hospital of Sun Yat-sen University (Guangzhou) from 2017 to 2020 were obtained. The temporal and spatial changes of AR and AC were discussed. The correlations between BDI and PC/OV were analyzed by Spearman correlation analysis. RESULTS: The trends of BDI of "AR"/"AC" in Beijing showed obvious seasonal variations, but not in Guangzhou. The BDI of "AR" and "AC" was consistent with the OV in both cities (r1AR-BJ=0.580, P<0.001; r1AR-GZ=0.360, P=0.031; r1AC-BJ=0.885, P<0.001; r1AC-GZ=0.694, P<0.001). The BDI of "AR" and "AC" was highly consistent with the change of the PC in Beijing (r AR-Pollen=0.826, P<0.001; r AC-Pollen=0.564, P<0.001). The OV of AR in Beijing and Guangzhou decreased significantly in the first half of 2020, but there was no significant change in AC. In the first half of 2020, the OV of AC in Beijing was significantly higher than that of AR, while that of AC in Guangzhou was slightly higher than that of AR. CONCLUSION: The BDI could reflect the real-world situation to some extent and has the potential to predict the epidemiological characteristics of AR and AC. The BDI and OV of AR decreased significantly, but those of AC were still at a high level, during the COVID-19 pandemic, in the environment where most people in Beijing and Guangzhou wore masks without eye protection.