Atypical pneumonia caused by Chlamydia psittaci during the COVID-19 pandemic.

OBJECTIVES: Here, we retrospectively described the diagnosis and treatment of 32 cases diagnosed with Chlamydia psittaci pneumonia during the COVID-19 pandemic. METHODS: Clinical information was collected from all the patients. Reverse transcription-PCR and ELISAs were conducted for the detection of COVID-19 using nasal swabs and bronchoalveolar lavage fluid (BALF) samples. Metagenomic next-generation sequencing (mNGS) was performed for the identification of causative pathogens using BALF, peripheral blood and sputum samples. End-point PCR was performed to confirm the mNGS results. RESULTS: All 32 patients showed atypical pneumonia and had infection-like symptoms that were similar to COVID-19. Results of reverse transcription-PCR and ELISAs ruled out COVID-19 infection. mNGS identified C. psittaci as the suspected pathogen in these patients within 48 hours, which was validated by PCR, except for three blood samples. The sequence reads that covered fragments of C. psittaci genome were detected more often in BALF than in sputum or blood samples. All patients received doxycycline-based treatment regimens and showed favorable outcomes. CONCLUSION: This retrospective study, with the highest number of C. psittaci pneumonia enrolled cases in China so far, suggests that human psittacosis may be underdiagnosed and misdiagnosed clinically, especially in the midst of the COVID-19 pandemic.

Multicenter analysis and a rapid screening model to predict early novel coronavirus pneumonia using a random forest algorithm.

ABSTRACT: Early determination of coronavirus disease 2019 (COVID-19) pneumonia from numerous suspected cases is critical for the early isolation and treatment of patients.The purpose of the study was to develop and validate a rapid screening model to predict early COVID-19 pneumonia from suspected cases using a random forest algorithm in China.A total of 914 initially suspected COVID-19 pneumonia in multiple centers were prospectively included. The computer-assisted embedding method was used to screen the variables. The random forest algorithm was adopted to build a rapid screening model based on the training set. The screening model was evaluated by the confusion matrix and receiver operating characteristic (ROC) analysis in the validation.The rapid screening model was set up based on 4 epidemiological features, 3 clinical manifestations, decreased white blood cell count and lymphocytes, and imaging changes on chest X-ray or computed tomography. The area under the ROC curve was 0.956, and the model had a sensitivity of 83.82% and a specificity of 89.57%. The confusion matrix revealed that the prospective screening model had an accuracy of 87.0% for predicting early COVID-19 pneumonia.Here, we developed and validated a rapid screening model that could predict early COVID-19 pneumonia with high sensitivity and specificity. The use of this model to screen for COVID-19 pneumonia have epidemiological and clinical significance.

Development and application of quality checklist for the prevention and control of COVID-19 in fever clinic and isolation ward of the general hospital.

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.

A rapid screening model for early predicting novel coronavirus pneumonia in Zhejiang Province of China: a multicenter study.

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. A total of 880 participants who were initially suspected of NCP from January 17 to February 19 were included. Potential predictors were selected via stepwise logistic regression analysis. The model was established based on epidemiological features, clinical manifestations, white blood cell count, and pulmonary imaging changes, with the area under receiver operating characteristic (AUROC) curve of 0.920. At a cut-off value of 1.0, the model could determine NCP with a sensitivity of 85% and a specificity of 82.3%. We further developed a simplified model by combining the geographical regions and rounding the coefficients, with the AUROC of 0.909, as well as a model without epidemiological factors with the AUROC of 0.859. The study demonstrated that the screening model was a helpful and cost-effective tool for early predicting NCP and had great clinical significance given the high activity of NCP.

[Standardized sputum collection increases sputum sample collection rate for novel coronavirus nucleic acid detection].

OBJECTIVE: To evaluate the effect of standardized health education on the sputum specimen collection rate for nucleic acid detection of coronavirus disease 2019 (COVID-19). METHODS: Two hundred and twenty-seven patients in fever clinics and isolation wards of Sir Run Run Shaw Hospital of Zhejiang University and 307 migrant workers returning to 5 enterprises in Shanghai from February 3 to March 14, 2020 were enrolled in the study. Through clarifying the procedures of collecting sputum specimens, making graphic/video health education materials, standardizing the contents and methods of health education, we conducted education to the subjects. The subject expectorated spontaneously or with medical assistance. For patients, the number of sampling attempts and sputum acquisition times were documented before and after the implementation of the standardized expectoration method; for the returning migrant employees in the enterprises, only the number of collected samples after the implementation of the standardized expectoration method were recorded. RESULTS: A total of 378 sputum samples were collected from 227 patients. The sputum sampling rates before and after the implementation of health education were 40.9%and 58.4%, respectively (P<0.01). A total of 304 sputum samples were obtained from 307 enterprise returnees, with a sample collection rate of 99.0%. CONCLUSIONS: The education for standardized sputum sample collection method can effectively increase the sputum collection rate.