The REDCap consortium: Building an international community of software platform partners.

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators

Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia the official statement of the American Thoracic Society and the Infectious Disease Society of America (特集 救急診療ガイドライン) -- (海外のガイドライン)

Background The coronavirus disease 2019 (Covid-19) outbreak is evolving rapidly worldwide. Objective To evaluate the risk of serious adverse outcomes in patients with coronavirus disease 2019 (Covid-19) by stratifying the comorbidity status. Methods We analysed the data from 1590 laboratory-confirmed hospitalised patients 575 hospitals in 31 province/autonomous regions/provincial municipalities across mainland China between December 11th, 2019 and January 31st, 2020. We analyse the composite endpoints, which consisted of admission to intensive care unit, or invasive ventilation, or death. The risk of reaching to the composite endpoints was compared according to the presence and number of comorbidities. Results The mean age was 48.9 years. 686 patients (42.7%) were females. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached to the composite endpoints. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD [hazards ratio (HR) 2.681, 95% confidence interval (95%CI) 1.424–5.048], diabetes (HR 1.59, 95%CI 1.03–2.45), hypertension (HR 1.58, 95%CI 1.07–2.32) and malignancy (HR 3.50, 95%CI 1.60–7.64) were risk factors of reaching to the composite endpoints. The HR was 1.79 (95%CI 1.16–2.77) among patients with at least one comorbidity and 2.59 (95%CI 1.61–4.17) among patients with two or more comorbidities. Conclusion Among laboratory-confirmed cases of Covid-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.

https://erj.ersjournals.com/content/erj/55/5/2000547.full.pdf

Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis.

Background There is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (Covid-19) Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19 Methods We conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case-control panels Results We detected cross-replicating associations with rs11385942 at locus 3p2131 and with rs657152 at locus 9q342, which were significant at the genomewide level (P Conclusions We identified a 3p2131 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system (Funded by Stein Erik Hagen and others)

/pdf/genomewide-association-study-of-severe-covid-19-with-5go9vzc689.pdf

Genomewide Association Study of Severe Covid-19 with Respiratory Failure.

https://journal.chestnet.org/article/S0012-3692(16)48816-1/pdf

A Critical Review of the Quality of Cough Clinical Practice Guidelines

Background Spirometry confers limited value for identifying small-airway disorders (SADs) in early-stage COPD, which can be detected with impulse oscillometry (IOS) and endobronchial optical coherence tomography (EB-OCT). Whether IOS is useful for reflecting small-airway morphological abnormalities in COPD remains unclear. Objectives To compare the diagnostic value of spirometry and IOS for identifying SADs in heavy-smokers and COPD based on the objective assessment with EB-OCT. Methods We recruited 59 COPD patients (stage I, n=17; stage II, n=18; stage III-IV, n=24), 26 heavy-smokers and 21 never-smokers. Assessments of clinical characteristics, spirometry, IOS and EB-OCT were performed. Receiver operation characteristic curve was employed to demonstrate the diagnostic value of IOS and spirometric parameters. Results More advanced staging of COPD was associated with greater abnormality of IOS and spirometric parameters. Resonant frequency (Fres) and peripheral airway resistance (R5-R20) conferred greater diagnostic values than forced expiratory volume in one second (FEV1%) and maximal (mid-)expiratory flow (MMEF%) predicted in discriminating SADs in never-smokers from heavy-smokers (area under curve [AUC]: 0.771 and 0.753 vs 0.570 and 0.558, respectively), and heavy-smokers from patients with stage I COPD (AUC: 0.726 and 0.633 vs 0.548 and 0.567, respectively). The combination of IOS (Fres and R5-R20) and spirometric parameters (FEV1% and MMEF% predicted) contributed to a further increase in the diagnostic value for identifying SADs in early-stage COPD. Small airway wall area percentage (Aw% 7-9), an EB-OCT parameter, correlated significantly with Fres and R5-R20 in COPD and heavy-smokers, whereas EB-OCT parameters correlated with FEV1% and MMEF% in advanced, rather than early-stage, COPD. Conclusions IOS parameters correlated with the degree of morphologic abnormalities of small airways assessed with EB-OCT in COPD and heavy-smokers. Fres and R5-R20 might be sensitive parameters that reliably reflect SADs in heavy-smokers and early-stage COPD.

/pdf/significances-of-spirometry-and-impulse-oscillometry-for-352talbl0n.pdf

Significances of spirometry and impulse oscillometry for detecting small airway disorders assessed with endobronchial optical coherence tomography in COPD

Background Unsupervised learning technique allows researchers to identify different phenotypes of diseases with complex manifestations. Objectives To identify bronchiectasis phenotypes and characterise their clinical manifestations and prognosis. Methods We conducted hierarchical cluster analysis to identify clusters that best distinguished clinical characteristics of bronchiectasis. Demographics, lung function, sputum bacteriology, aetiology, radiology, disease severity, quality-of-life, cough scale and capsaicin sensitivity, exercise tolerance, health care use and frequency of exacerbations were compared. Results Data from 148 adults with stable bronchiectasis were analysed. Four clusters were identified. Cluster 1 (n = 69) consisted of the youngest patients with predominantly mild and idiopathic bronchiectasis with minor health care resource use. Patients in cluster 2 (n = 22), in which post-infectious bronchiectasis predominated, had the longest duration of symptoms, greater disease severity, poorer lung function, airway Pseudomonas aeruginosa colonisation and frequent health care resource use. Cluster 3 (n = 16) consisted of elderly patients with shorter duration of symptoms and mostly idiopathic bronchiectasis, and predominantly severe bronchiectasis. Cluster 4 (n = 41) constituted the most elderly patients with moderate disease severity. Clusters 2 and 3 tended to have a greater risk of bronchiectasis exacerbations (P = 0.06) than clusters 1 and 4. Conclusion Identification of distinct phenotypes will lead to greater insight into the characteristics and prognosis of bronchiectasis.

Mei Jiang

Papers

A Critical Review of the Quality of Cough Clinical Practice Guidelines

Significances of spirometry and impulse oscillometry for detecting small airway disorders assessed with endobronchial optical coherence tomography in COPD

Unsupervised learning technique identifies bronchiectasis phenotypes with distinct clinical characteristics.

Clinical applications of detecting IgG, IgM or IgA antibody for the diagnosis of COVID-19: A meta-analysis and systematic review.

Modified IDSA/ATS Minor Criteria for Severe Community-Acquired Pneumonia Best Predicted Mortality