COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Analysis of De Novo Mutations in Sporadic Cardiomyopathies Emphasizes Their Clinical Relevance and Points to Novel Candidate Genes

The vast majority of cardiomyopathies have an autosomal dominant inheritance; hence, genetic testing is typically offered to patients with a positive family history. A de novo mutation is a new germline mutation not inherited from either parent. The purpose of our study was to search for de novo mutations in patients with cardiomyopathy and no evidence of the disease in the family. Using next-generation sequencing, we analyzed cardiomyopathy genes in 12 probands. In 8 (66.7%), we found de novo variants in known cardiomyopathy genes (TTN, DSP, SCN5A, TNNC1, TPM1, CRYAB, MYH7). In the remaining probands, the analysis was extended to whole exome sequencing in a trio (proband and parents). We found de novo variants in genes that, so far, were not associated with any disease (TRIB3, SLC2A6), a possible disease-causing biallelic genotype (APOBEC gene family), and a de novo mosaic variant without strong evidence of pathogenicity (UNC45A). The high prevalence of de novo mutations emphasizes that genetic screening is also indicated in cases of sporadic cardiomyopathy. Moreover, we have identified novel cardiomyopathy candidate genes that are likely to affect immunological function and/or reaction to stress that could be especially relevant in patients with disease onset associated with infection/infestation

Mechanisms of Myocardial Infarction in Patients With Nonobstructive Coronary Artery Disease: Results From the Optical Coherence Tomography Study

Objectives: This study sought to assess the presence and morphological features of coronary plaques on optical coherence tomography (OCT) as the causes of myocardial infarction with nonobstructive coronary arteries (MINOCA). Background: Although coronary atherosclerosis has been postulated as a potential mechanism of MINOCA, the interaction between disrupted coronary plaques and myocardial injury remains unknown. Methods: In a prospective study, consecutive patients with MI but without significant coronary stenosis (≥50%) at angiography underwent OCT and cardiac magnetic resonance (CMR) with late gadolinium-enhancement (LGE). The infarct-related artery (IRA) was identified by localization of ischemic-type LGE. Results: Thirty-eight MINOCA patients (mean age 62 ± 13 years, 55% female, 39% with ST-segment elevation) were enrolled. Maximal diameter stenosis was 35% by angiography, and 5 patients (13%) had normal angiogram results. Plaque disruption and coronary thrombus were observed in 9 patients (24%) and 7 patients (18%), respectively. Sixteen of 31 patients (52%) undergoing CMR showed LGE. Ischemic-type LGE was present in 7 patients (23%) and was more common in patients with than without plaque disruption (50% vs. 13%, respectively; p = 0.053) and coronary thrombus (67% vs. 12%, respectively; p = 0.014). In the per-lesion analysis, the IRA showed significantly more plaque disruption (40% vs. 6%; p = 0.02), thrombus (50% vs. 4%; p = 0.014), and thin-cap fibroatheroma (70% vs. 30%; p = 0.03) than the non-IRA. Conclusions: Plaque disruption and thrombus are not uncommon in MI without obstructive coronary stenoses at angiography and may be associated with the presence and location of ischemic-type myocardial injury on CMR. OCT may be valuable in identifying atherosclerotic etiology in individuals with MINOCA. (Optical Coherence Tomography in Patients With Acute Myocardial Infarction and Nonobstructive Coronary Artery Disease [SOFT-MI]; NCT02783963

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19

Background: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. Methods: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). Results: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. Conclusions: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use