ABSTRACT
BACKGROUNDThe aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis. METHODSParticipants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time. FINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1{middle dot}18, 95% confidence interval [95% CI] 1{middle dot}03-1{middle dot}36) and poorer sleep quality (1{middle dot}13, 1{middle dot}03-1{middle dot}24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0{middle dot}83, 95% CI 0{middle dot}75-0{middle dot}91 and 0{middle dot}77, 0{middle dot}63-0{middle dot}94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1{middle dot}61, 95% CI 1{middle dot}27-2{middle dot}05 and 1{middle dot}43, 1{middle dot}26-1{middle dot}63, respectively) throughout the 16-month study period. CONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.
ABSTRACT
BackgroundThe 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. MethodsAll 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. ResultsThe 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. ConclusionOur prognostic model can accurately predict the outcome of SARS-CoV-2 infection using information that is available at the time of diagnosis.
ABSTRACT
The spread of SARS-CoV-2 is dependent on several factors, both biological and behavioral. The effectiveness of various non-pharmaceutical interventions can largely be attributed to changes in human behavior, but quantifying this effect remains challenging. Reconstructing the transmission tree of the third wave of SARS-CoV-2 infections in Iceland using contact tracing and viral sequence data from 2522 cases enables us to compare the infectiousness of distinct groups of persons directly. We find that people diagnosed outside of quarantine are 89% more infectious than those diagnosed while in quarantine, and infectiousness decreases as a function of the time spent in quarantine. Furthermore, we find that people of working age, 16-66 years old, are 47% more infectious than those outside that age range. Lastly, the transmission tree enables us to model the effect that given population prevalence of vaccination would have had on the third wave had they been administered before that time using several different strategies. We find that vaccinating in order of ascending age or uniformly at random would have prevented more infections per vaccination than vaccinating in order of descending age.
ABSTRACT
BackgroundPrevious studies on the epidemiology and clinical characteristics of COVID-19 have generally been limited to hospitalized patients. The aim of this study was to describe the complete clinical spectrum of COVID-19, based on a nationwide cohort with extensive diagnostic testing and a rigorous contact tracing approach. MethodsA population-based cohort study examining symptom progression using prospectively recorded data on all individuals with a positive test (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who were enrolled in a telehealth monitoring service provided to all identified cases in Iceland. Symptoms were systematically monitored from diagnosis to recovery. ResultsFrom January 31 to April 30, 2020, a total of 45,105 individuals (12% of the Icelandic population) were tested for SARS-CoV-2, of whom 1797 were positive, yielding a population incidence of 5 per 1000 individuals. The most common presenting symptoms were myalgia (55%), headache (51%), and non-productive cough (49%). At the time of diagnosis, 5.3% of cases reported no symptoms and 3.1% remained asymptomatic during follow-up. In addition, 216 patients (13.8%) and 349 patients (22.3%) did not meet the case definition of the Centers for Disease Control and Prevention and the World Health Organization, respectively. The majority (67.5%) of patients had mild symptoms throughout the course of the disease. ConclusionIn the setting of broad access to diagnostic testing, the majority of SARSCoV-2-positive patients were found to have mild symptoms. Fever and dyspnea were less common than previously reported. A substantial proportion of patients did not meet recommended case definitions at the time of diagnosis. Key pointsO_ST_ABSQuestionC_ST_ABSWhat is the frequency and progression of various symptoms experienced by patients with COVID-19? FindingsIn this population-based cohort study that included all SARS-CoV-2-positive patients in Iceland, most patients (67.5%) had mild symptoms throughout their disease course. At the time of diagnosis, 5.3% were asymptomatic, of whom roughly half developed symptoms during follow-up. Common presenting symptoms included myalgia (55%), headache (51%), and non-productive cough (49%). At diagnosis, 13.8% and 22.3% did not meet the Centers for Disease Control and Prevention and World Health Organization case definitions for suspected COVID-19, respectively. MeaningIn the setting of broad access to diagnostic testing, the majority of SARSCoV-2-positive patients were found to have mild symptoms and almost one-fifth did not meet published clinical criteria for RT-PCR testing.
ABSTRACT
OBJECTIVE: Information on the medical problems and diseases encountered by practicing Internists in the hospital environment is lacking. The aim of this study is to assess the prevalence of various diagnostic categories that present to internists in the hospital setting in Europe. DESIGN: A pan-European study used the Young Internists Research Network of the European Federation of Internal Medicine. RESULTS: Data on 1501 patients from 31 physicians in 18 European countries were included in the study. The patients carried an average of 2.75 (+/-2.22) chronic medical diagnoses, ranging from 0 to 18. The most common presenting complaint was shortness of breath, followed by chest pain and abdominal pain. A cardiac condition was most common, followed by infectious disease. The complexity of patients averaged 2.5 (+/-1.14). CONCLUSIONS: The results of this study will be useful for the development of a modern internal medicine curriculum, both at the graduate and postgraduate level, which reflects the competencies required for the delivery of comprehensive patient care in internal medicine wards.
