Publications by authors named "Katharina S Appel"

Purpose: 'Post-COVID Syndrome' (PCS), which encompasses the multifaceted sequelae of COVID-19, can be severity-graded by a previously defined score encompassing 12 different long-term symptom complexes. The PCS score was shown to have two main predictors, namely acute COVID-19 severity and individual resilience. The purpose of the present study was to verify these predictors and to assess their detailed relationship to the symptom complexes constituting the PCS score.

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Purpose: The benefit of antibiotic treatment (ABT) for patients with moderate COVID-19 is unclear and overtreatment poses the risk of adverse effects such as Clostridioides difficile infection and antibiotic resistance. This multi-center study compares health status improvement between patients with and without ABT at hospital admission.

Methods: Between March 2020 and May 2023, hospitalized adults with confirmed SARS-CoV-2 infection were recruited from the German National Pandemic Cohort Network (NAPKON), which includes patients from various hospitals across Germany.

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If health impairments due to coronavirus disease 2019 (COVID-19) persist for 12 weeks or longer, patients are diagnosed with Post-COVID Syndrome (PCS), or Long-COVID. Although the COVID-19 pandemic has largely subsided in 2024, PCS is still a major health burden worldwide, and identifying potential genetic modifiers of PCS remains of great clinical and scientific interest. We therefore performed a case-control type genome-wide association study (GWAS) of three recently developed PCS (severity) scores in 2,247 participants of COVIDOM, a prospective, multi-centre, population-based cohort study of SARS-CoV-2-infected individuals in Germany.

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Viremia defined as detectable SARS-CoV-2 RNA in the blood is a potential marker of disease severity and prognosis in COVID-19 patients. Here, we determined the frequency of viremia in serum of two independent COVID-19 patient cohorts within the German National Pandemic Cohort Network (German: tionales andemie horten etzwerk, NAPKON) with diagnostic RT-PCR against SARS-CoV-2. A cross-sectional cohort with 1122 COVID-19 patients (German: , SUEP) and 299 patients recruited in a high-resolution platform with patients at high risk to develop severe courses (German: , HAP) were tested for viremia.

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Background: Existing risk evaluation tools underperform in predicting intensive care unit (ICU) admission for patients with coronavirus disease 2019 (COVID-19). This study aimed to develop and evaluate an accurate and calculator-free clinical tool for predicting ICU admission at emergency room (ER) presentation.

Methods: Data from patients with COVID-19 in a nationwide German cohort (March 2020-January 2023) were analyzed.

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Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM).

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Article Synopsis
  • The study investigates the prevalence and predictors of post-COVID-19 condition (PCC) symptoms in patients infected with SARS-CoV-2 variants delta and omicron.
  • A total of 758 patients were analyzed, revealing that fatigue was the most common PCC symptom, with no significant difference in prevalence between delta and omicron infections at the three-month follow-up.
  • Most patients reported stable health-related quality of life, with over two-thirds experiencing no decline, indicating that PCC is a common issue for both variants in the German population.
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Purpose: The objective examination of the Post-COVID syndrome (PCS) remains difficult due to heterogeneous definitions and clinical phenotypes. The aim of the study was to verify the functionality and correlates of a recently developed PCS score.

Methods: The PCS score was applied to the prospective, multi-center cross-sectoral cohort (in- and outpatients with SARS-CoV-2 infection) of the "National Pandemic Cohort Network (NAPKON, Germany)".

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Background: Depression and fatigue are commonly observed sequelae following viral diseases such as COVID-19. Identifying symptom constellations that differentially classify post-COVID depression and fatigue may be helpful to individualize treatment strategies. Here, we investigated whether self-reported post-COVID depression and post-COVID fatigue are associated with the same or different symptom constellations.

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Background: Numerous prognostic scores have been published to support risk stratification for patients with coronavirus disease 2019 (COVID-19).

Methods: We performed a systematic review to identify the scores for confirmed or clinically assumed COVID-19 cases. An in-depth assessment and risk of bias (ROB) analysis (Prediction model Risk Of Bias ASsessment Tool [PROBAST]) was conducted for scores fulfilling predefined criteria ([I] area under the curve [AUC)] ≥ 0.

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Objectives: The use of remdesivir (RDV) as the first drug approved for coronavirus disease 2019 (COVID-19) remains controversial. Based on the Lean European Open Survey on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infected patients (LEOSS), we aim to contribute timing-focused complementary real-world insights to its evaluation.

Methods: SARS-CoV-2 infected patients between January 2020 and December 2021 treated with RDV were matched 1:1 to controls considering sociodemographics, comorbidities and clinical status.

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The prevalence of post-COVID syndrome (PCS) has not yet been conclusively clarified. The existing definitions primarily reflect temporal aspects, but disregard functional deficits as well as the objectification of symptoms. This leads to diagnostic as well as therapeutic ambiguities.

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The German government initiated the Network University Medicine (NUM) in early 2020 to improve national research activities on the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. To this end, 36 German Academic Medical Centers started to collaborate on 13 projects, with the largest being the National Pandemic Cohort Network (NAPKON). The NAPKON's goal is creating the most comprehensive Coronavirus Disease 2019 (COVID-19) cohort in Germany.

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