ObjectiveTo investigate the diagnostic value of mini peak flow meters in cough variant asthma (CVA). Methods131 patients with the main symptom of chronic cough whose chest X-ray showed normal were included in this study. The peak expiratory flow (PEF) rate of each patient was measured by mini peak flow meters during the bronchial dilation test, and the results were analyzed. ResultsThe rate of positive reaction in the test was 33.6% (44/131), of whom 40.9% (18/44) were delayed over 1 year. 16.8% (22/131) of all the patients' PEF increased 10% to 15% in after the test. ConclusionMini peak flow meters can be used in the diagnosis of CVA.

Objective To establish an artificial intelligence (AI)-assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases. Methods A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI-assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results An AI-assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions The AI-assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis.

To develop a quality control checklist for the prevention and control of coronavirus disease 2019 （COVID-19） in fever clinic and isolation ward of the general hospital and to assess its application. Based on the relevant prevention and control plans and technical guidelines for COVID-19，Delphi method was used to identity items for evaluation，and a quality control checklist for the prevention and control of COVID-19 in the fever clinic and isolation ward was developed in Sir Run Run Shaw Hospital. The checklists included 8 dimensions and 32 items for fever clinic，7 dimensions and 27 items for the isolation ward. The appointed inspectors conducted daily quality control for each shift with this checklist. The expert authority coefficient was 0.88，the mean of the importance of each index in the quality control table was not less than 4.8，and the coefficient of variation was not more than 0.07. During the entire February 2020，8 problems were found and rectified on-the-spot with the application of the checklist. Quality inspection rate was 100% in both isolation wards and fever clinic. The compliance rate and accuracy rate of hand hygiene were 100%; the correct rate of wearing and removing protective equipment increased from 96% to 100%. During the same period，a total of 1915 patients were admitted to the fever clinic，including 191 suspected patients （all were isolated in the hospital，3 were confirmed）. There were no medical staff infected with COVID-19，no cross infection of patients and their families in the hospital. A quality control checklist for the prevention and control of COVID-19 has been developed and applied in the isolation wards and fever clinic，which plays an important role in preventing nosocomial infection.
COVID-19 ; Checklist ; Fever ; Hospitals, General ; Humans ; SARS-CoV-2