BackgroundPost-viral symptoms have long been known in the medical community but have received more public attention during the COVID-19 pandemic. Many post-viral symptoms were reported as particularly frequent after SARS-CoV-2 infection. However, there is still a lack of evidence regarding the specificity, frequency and persistence of these symptoms in comparison to other viral infectious diseases such as influenza.MethodsWe investigated a large population-based cohort based on German routine healthcare data. We matched 573,791 individuals with a PCR-test confirmed SARS-CoV-2 infection from the year 2020 to contemporary controls without SARS-CoV-2 infection and controls from the last influenza outbreak in 2018 and followed them up to 18 months.ResultsWe found that post-viral symptoms as defined for COVID-19 by the WHO as well as tissue damage were more frequent among the COVID-19 cohort than the influenza or contemporary control cohort. The persistence of post-viral symptoms was similar between COVID-19 and influenza.ConclusionPost-viral symptoms following SARS-CoV-2 infection constitute a substantial disease burden as they are frequent and often persist for many months. As COVID-19 is becoming endemic, the disease must not be trivialized. Research should focus on the development of effective treatments for post-viral symptoms.

Objectives To investigate whether the risk of developing an incident autoimmune disease is increased in patients with prior COVID-19 disease compared to those without COVID-19, a large cohort study was conducted. Method A cohort was selected from German routine health care data. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through December 31, 2020. Patients were matched 1:3 to control patients without COVID-19. Both groups were followed up until June 30, 2021. We used the four quarters preceding the index date until the end of follow-up to analyze the onset of autoimmune diseases during the post-acute period. Incidence rates (IR) per 1000 person-years were calculated for each outcome and patient group. Poisson models were deployed to estimate the incidence rate ratios (IRRs) of developing an autoimmune disease conditional on a preceding diagnosis of COVID-19. Results In total, 641,704 patients with COVID-19 were included. Comparing the incidence rates in the COVID-19 (IR=15.05, 95% CI: 14.69–15.42) and matched control groups (IR=10.55, 95% CI: 10.25–10.86), we found a 42.63% higher likelihood of acquiring autoimmunity for patients who had suffered from COVID-19. This estimate was similar for common autoimmune diseases, such as Hashimoto thyroiditis, rheumatoid arthritis, or Sjögren syndrome. The highest IRR was observed for autoimmune diseases of the vasculitis group. Patients with a more severe course of COVID-19 were at a greater risk for incident autoimmune disease. Conclusions SARS-CoV-2 infection is associated with an increased risk of developing new-onset autoimmune diseases after the acute phase of infection. Key Points • In the 3 to 15 months after acute infection, patients who had suffered from COVID-19 had a 43% (95% CI: 37–48%) higher likelihood of developing a first-onset autoimmune disease, meaning an absolute increase in incidence of 4.50 per 1000 person-years over the control group. • COVID-19 showed the strongest association with vascular autoimmune diseases.

We aimed to develop a risk score to calculate a person’s individual risk for a severe COVID-19 course (POINTED score) to support prioritization of especially vulnerable patients for a (booster) vaccination. This cohort study was based on German claims data and included 623,363 individuals with a COVID-19 diagnosis in 2020. The outcome was COVID-19 related treatment in an intensive care unit, mechanical ventilation, or death after a COVID-19 infection. Data were split into a training and a test sample. Poisson regression models with robust standard errors including 35 predefined risk factors were calculated. Coefficients were rescaled with a min–max normalization to derive numeric score values between 0 and 20 for each risk factor. The scores’ discriminatory ability was evaluated by calculating the area under the curve (AUC). Besides age, down syndrome and hematologic cancer with therapy, immunosuppressive therapy, and other neurological conditions were the risk factors with the highest risk for a severe COVID-19 course. The AUC of the POINTED score was 0.889, indicating very good predictive validity. The POINTED score is a valid tool to calculate a person’s risk for a severe COVID-19 course.

To the Editor, Atopic dermatitis (AD) is a frequent, chronic inflammatory disease constituting significant burden to patients, their families and healthcare systems.1 The pathophysiology is multifactorial involving genetic predisposition, epidermal dysfunction, and cutaneous inflammation.2 Systemic infections trigger AD flares and are related to the manifestation of new-onset AD.1 Following the acute phase of a SARS-CoV-2 infection, some people develop long-lasting symptoms, known as post- or long-COVID.3 Different incident diseases are associated with prior COVID-19 disease, including cardiovascular and respiratory diseases, mental health problems, fatigue, and autoimmune diseases.4, 5 Due to the role of viral infections in the pathophysiology of AD, we hypothesized that the risk of new-onset AD is increased in individuals with previous SARS-CoV-2 infection. To test this, we undertook a large matched cohort study based on German routine healthcare data covering inpatient and outpatient care, diagnoses, prescriptions and demographic data. Patients with polymerase chain reaction (PCR)-confirmed COVID-19 infection in the year 2020 were matched 1:3 by age, sex, previous occurrence of an autoimmune disease and comorbidity propensity score to control subjects without COVID-19-infection and followed up to 15 months through June 2021. Patients with prevalent AD in the four quarters (one inpatient diagnosis or two outpatient diagnoses in two different quarters with ICD-10: L20 or L30 for adults) before the initial SARS-CoV-2 infection or their assigned index date were excluded. Following the NICE guidelines on long-COVID,3 we defined the post-COVID-19-phase starting 3 months after the assigned index date. Primary outcome was new-onset AD. Patients were considered as having new-onset AD, if they received at least two physician documented diagnoses of AD (ICD-10: L20 or L30 for adults), no more than two quarters apart or an inpatient diagnosis in the post-COVID period. Additionally, we requested at least one prescription of topical or systemic treatment approved for AD (Table S1). We calculated incidence rates (IR) per 1000 person-years for the entire study population and predefined subgroups using Poisson models to estimate the IR-ratios (IRR) for the development of AD as a function of a prior diagnosis of COVID-19.5 Because of the non-interventional nature of routine healthcare data, no consent to participate was collected. This waiver for informed consent was confirmed by ethics committee of the Faculty of Medicine Carl Gustav Carus at the TU Dresden (BO-EK [COVID]-482,102,021). In total, 641,704 COVID-19-patients, and 1,907,992 matched control cases without COVID-19 were included (Figure S1). 23,740 patients in the COVID-19-group and 111,818 cases in the control cohort were excluded because of prior AD. The IR of AD 3 to 15 months after the assigned index date was 7.35 (95%-CI 7.11–7.59) per 1000 person-years in the COVID-19 group and 5.53 (95% CI: 5.32–5.74) in the control group. The largest risk difference was observed among those under 18 years of age. Thus, patients with prior COVID-19 infection had a 33% increased risk of developing AD compared to controls (IRR 1.33; 95%-CI 1.26–1.40). The risk for new-onset AD was significantly increased in both sex groups, medication groups and all age groups. However, the confidence intervals of the relative risks overlapped between these groups. (Table 1, Figure 1). In summary, our study shows consistent and significantly increased new-onset of AD in patients with previous SARS-CoV-2 infection. Limitations of the presented study include its observational nature so that causal conclusions can only be drawn with caution. A major strength is the large sample size and the robustness of the findings in several analyzed subgroups. This new evidence strengthens previous studies that suggested a relevant pathophysiological role of viral infections in AD.6 Future research is necessary to further investigate the role of the COVID-19 pandemic on the global burden of AD. Conception: all authors Methodology: JS, FT, FE, DW, MB, FL, SM, MS, CS. Data analysis: FT, FE. Writing of draft paper: JS, BK, SA. Revision and approval of final paper: all authors. The authors thank the participating statutory health insurer for the opportunity to use their data for research. Open Access funding was made possible by Projekt DEAL. This work was supported by a research grant from the German Ministry of Health (Grant Number ZMI1-2521NIK705). Unrelated to this study, JS reports grants for investigator-initiated research from the German GBA, the BMG, BMBF, EU, Federal State of Saxony, Novartis, Sanofi, ALK, and Pfizer. He also participated in advisory board meetings for Sanofi, Lilly, and ALK. MB reports payment for data analysis which is presented in this paper from DAK-Gesundheit. Unrelated to this study, MB reports grants from German GBA, Pfizer and Sanofi Pasteur and consulting fees from Janssen-Cilag. He participated in an advisory board for GSK. SA has received speaking and/or consulting fees and is involved in clinical trials for Novartis, Sanofi, Beiersdorf, UCB, Amgen, LEO Pharma, Tekeda, Lilly, Boehringer Ingelheim, and AbbVie. The other authors declare that they have no competing interest. The raw data used in this study cannot be made available in the manuscript, the supplemental files, or in a public repository due to German data protection laws (Bundesdatenschutzgesetz). The aggregated data is stored on a secure drive at ZEGV. Table S1: Medication atopic dermatitis. Figure S1: Flowchart for the selection of the COVID-19 and control groups. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Background Long-term health sequelae of the Coronavirus Disease 2019 (COVID-19) are a major public health concern. However, evidence on post-acute COVID-19 syndrome (post-COVID-19) is still limited, particularly for children and adolescents. Utilizing comprehensive healthcare data on approximately 46% of the German population, we investigated post-COVID-19-associated morbidity in children/adolescents and adults. Methods and findings We used routine data from German statutory health insurance organizations covering the period between January 1, 2019 and December 31, 2020. The base population included all individuals insured for at least 1 day in 2020. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through June 30, 2020. A control cohort was assigned using 1:5 exact matching on age and sex, and propensity score matching on preexisting medical conditions. The date of COVID-19 diagnosis was used as index date for both cohorts, which were followed for incident morbidity outcomes documented in the second quarter after index date or later.Overall, 96 prespecified outcomes were aggregated into 13 diagnosis/symptom complexes and 3 domains (physical health, mental health, and physical/mental overlap domain). We used Poisson regression to estimate incidence rate ratios (IRRs) with 95% confidence intervals (95% CIs). The study population included 11,950 children/adolescents (48.1% female, 67.2% aged between 0 and 11 years) and 145,184 adults (60.2% female, 51.1% aged between 18 and 49 years). The mean follow-up time was 236 days (standard deviation (SD) = 44 days, range = 121 to 339 days) in children/adolescents and 254 days (SD = 36 days, range = 93 to 340 days) in adults. COVID-19 and control cohort were well balanced regarding covariates. The specific outcomes with the highest IRR and an incidence rate (IR) of at least 1/100 person-years in the COVID-19 cohort in children and adolescents were malaise/fatigue/exhaustion (IRR: 2.28, 95% CI: 1.71 to 3.06, p < 0.01, IR COVID-19: 12.58, IR Control: 5.51), cough (IRR: 1.74, 95% CI: 1.48 to 2.04, p < 0.01, IR COVID-19: 36.56, IR Control: 21.06), and throat/chest pain (IRR: 1.72, 95% CI: 1.39 to 2.12, p < 0.01, IR COVID-19: 20.01, IR Control: 11.66). In adults, these included disturbances of smell and taste (IRR: 6.69, 95% CI: 5.88 to 7.60, p < 0.01, IR COVID-19: 12.42, IR Control: 1.86), fever (IRR: 3.33, 95% CI: 3.01 to 3.68, p < 0.01, IR COVID-19: 11.53, IR Control: 3.46), and dyspnea (IRR: 2.88, 95% CI: 2.74 to 3.02, p < 0.01, IR COVID-19: 43.91, IR Control: 15.27). For all health outcomes combined, IRs per 1,000 person-years in the COVID-19 cohort were significantly higher than those in the control cohort in both children/adolescents (IRR: 1.30, 95% CI: 1.25 to 1.35, p < 0.01, IR COVID-19: 436.91, IR Control: 335.98) and adults (IRR: 1.33, 95% CI: 1.31 to 1.34, p < 0.01, IR COVID-19: 615.82, IR Control: 464.15). The relative magnitude of increased documented morbidity was similar for the physical, mental, and physical/mental overlap domain. In the COVID-19 cohort, IRs were significantly higher in all 13 diagnosis/symptom complexes in adults and in 10 diagnosis/symptom complexes in children/adolescents. IRR estimates were similar for age groups 0 to 11 and 12 to 17. IRs in children/adolescents were consistently lower than those in adults. Limitations of our study include potentially unmeasured confounding and detection bias. Conclusions In this retrospective matched cohort study, we observed significant new onset morbidity in children, adolescents, and adults across 13 prespecified diagnosis/symptom complexes, following COVID-19 infection. These findings expand the existing available evidence on post-COVID-19 conditions in younger age groups and confirm previous findings in adults. Trial registration ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT05074953.