Objective To characterise the symptoms of coronavirus disease 2019 (covid-19). Design Population based cohort study. Setting Iceland. Participants All individuals who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse transcription polymerase chain reaction (RT-PCR) between 17 March and 30 April 2020. Cases were identified by three testing strategies: targeted testing guided by clinical suspicion, open invitation population screening based on self referral, and random population screening. All identified cases were enrolled in a telehealth monitoring service, and symptoms were systematically monitored from diagnosis to recovery. Main outcome measures Occurrence of one or more of 19 predefined symptoms during follow-up. Results Among 1564 people positive for SARS-CoV-2, the most common presenting symptoms were myalgia (55%), headache (51%), and non-productive cough (49%). At the time of diagnosis, 83 (5.3%) individuals reported no symptoms, of whom 49 (59%) remained asymptomatic during follow-up. At diagnosis, 216 (14%) and 349 (22%) people did not meet the case definition of the Centers for Disease Control and Prevention and the World Health Organization, respectively. Most (67%) of the SARS-CoV-2-positive patients had mild symptoms throughout the course of their disease. Conclusion In the setting of broad access to RT-PCR testing, most SARS-CoV-2-positive people were found to have mild symptoms. Fever and dyspnoea were less common than previously reported. A substantial proportion of SARS-CoV-2-positive people did not meet recommended case definitions at the time of diagnosis.

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Our findings support the conclusion that ESD may be a safe alternative to conventional surgery for removal of large symptomatic gastric lipomas.

Multiple myeloma (MM) patients have increased risk of severe coronavirus disease 2019 (COVID-19) when infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Monoclonal gammopathy of undetermined significance (MGUS), the precursor of MM has been associated with immune dysfunction which may lead to severe COVID-19. No systematic data have been published on COVID-19 in individuals with MGUS. We conducted a large population-based cohort study evaluating the risk of SARS-CoV-2 infection and severe COVID-19 among individuals with MGUS. We included 75,422 Icelanders born before 1976, who had been screened for MGUS in the Iceland Screens Treats or Prevents Multiple Myeloma study (iStopMM). Data on SARS-CoV-2 testing and COVID-19 severity were acquired from the Icelandic COVID-19 Study Group. Using a test-negative study design, we included 32,047 iStopMM participants who had been tested for SARS-CoV-2, of whom 1754 had MGUS. Among these participants, 1100 participants, tested positive, 65 of whom had MGUS. Severe COVID-19 developed in 230 participants, including 16 with MGUS. MGUS was not associated with SARS-CoV-2 infection (Odds ratio (OR): 1.05; 95% confidence interval (CI): 0.81–1.36; p = 0.72) or severe COVID-19 (OR: 0.99; 95%CI: 0.52–1.91; p = 0.99). These findings indicate that MGUS does not affect the susceptibility to SARS-CoV-2 or the severity of COVID-19.

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Background: The severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 at the time of diagnosis and determine risk factors for severe disease. Methods: All SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview with those diagnosed before May 1, 2020 and validated in those diagnosed between May 1 and December 31, 2020. Outcomes were defined on an ordinal scale; no need for escalation of care during follow-up, need for outpatient visit, hospitalization, and admission to intensive care unit (ICU) or death. Risk factors were summarized as odds ratios (OR) adjusted for confounders identified by a directed acyclic graph. Results: The prognostic model was derived from and validated in 1,625 and 3,131 individuals, respectively. In total, 375 (7.9%) only required outpatient visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. Discrimination and calibration were excellent for outpatient visit or worse (C-statistic 0.75, calibration intercept 0.04 and slope 0.93) and hospitalization or worse (C-statistic 0.81, calibration intercept 0.16 and slope 1.03). Age was the strongest risk factor for adverse outcomes with OR of 75- compared to 45- year-olds, ranging from 5.29-17.3. Higher BMI consistently increased the risk and chronic obstructive pulmonary disease and chronic kidney disease correlated with worse outcomes. Conclusion: Our prognostic model can accurately predict the outcome of SARS-CoV-2 infection using information that is available at the time of diagnosis.