@article{PilgramEberweinWilleetal.2021,
  author    = {Pilgram, Lisa and Eberwein, Lukas and Wille, Kai and Koehler, Felix C. and Stecher, Melanie and Rieg, Siegbert and Kielstein, Jan T. and Jakob, Carolin E. M. and R{\"u}thrich, Maria and Burst, Volker and Prasser, Fabian and Borgmann, Stefan and M{\"u}ller, Roman-Ulrich and Lanznaster, Julia and Isberner, Nora and Tometten, Lukas and Dolff, Sebastian},
  title     = {Clinical course and predictive risk factors for fatal outcome of SARS-CoV-2 infection in patients with chronic kidney disease},
  series = {Infection},
  volume    = {49},
  journal   = {Infection},
  number    = {4},
  organization    = {LEOSS Study group},
  issn      = {0300-8126},
  doi       = {10.1007/s15010-021-01597-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-308957},
  pages     = {725-737},
  year      = {2021},
  abstract  = {Purpose The ongoing pandemic caused by the novel severe acute respiratory coronavirus 2 (SARS-CoV-2) has stressed health systems worldwide. Patients with chronic kidney disease (CKD) seem to be more prone to a severe course of coronavirus disease (COVID-19) due to comorbidities and an altered immune system. The study's aim was to identify factors predicting mortality among SARS-CoV-2-infected patients with CKD. Methods We analyzed 2817 SARS-CoV-2-infected patients enrolled in the Lean European Open Survey on SARS-CoV-2-infected patients and identified 426 patients with pre-existing CKD. Group comparisons were performed via Chi-squared test. Using univariate and multivariable logistic regression, predictive factors for mortality were identified. Results Comparative analyses to patients without CKD revealed a higher mortality (140/426, 32.9\% versus 354/2391, 14.8\%). Higher age could be confirmed as a demographic predictor for mortality in CKD patients (> 85 years compared to 15-65 years, adjusted odds ratio (aOR) 6.49, 95\% CI 1.27-33.20, p = 0.025). We further identified markedly elevated lactate dehydrogenase (> 2 × upper limit of normal, aOR 23.21, 95\% CI 3.66-147.11, p < 0.001), thrombocytopenia (< 120,000/µl, aOR 11.66, 95\% CI 2.49-54.70, p = 0.002), anemia (Hb < 10 g/dl, aOR 3.21, 95\% CI 1.17-8.82, p = 0.024), and C-reactive protein (≥ 30 mg/l, aOR 3.44, 95\% CI 1.13-10.45, p = 0.029) as predictors, while renal replacement therapy was not related to mortality (aOR 1.15, 95\% CI 0.68-1.93, p = 0.611). Conclusion The identified predictors include routinely measured and universally available parameters. Their assessment might facilitate risk stratification in this highly vulnerable cohort as early as at initial medical evaluation for SARS-CoV-2.},
  language  = {en}
}
@article{SolimandoBittrichShahinietal.2023,
  author    = {Solimando, Antonio G. and Bittrich, Max and Shahini, Endrit and Albanese, Federica and Fritz, Georg and Krebs, Markus},
  title     = {Determinants of COVID-19 disease severity - lessons from primary and secondary immune disorders including cancer},
  series = {International Journal of Molecular Sciences},
  volume    = {24},
  journal   = {International Journal of Molecular Sciences},
  number    = {10},
  issn      = {1422-0067},
  doi       = {10.3390/ijms24108746},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-319412},
  year      = {2023},
  abstract  = {At the beginning of the COVID-19 pandemic, patients with primary and secondary immune disorders — including patients suffering from cancer — were generally regarded as a high-risk population in terms of COVID-19 disease severity and mortality. By now, scientific evidence indicates that there is substantial heterogeneity regarding the vulnerability towards COVID-19 in patients with immune disorders. In this review, we aimed to summarize the current knowledge about the effect of coexistent immune disorders on COVID-19 disease severity and vaccination response. In this context, we also regarded cancer as a secondary immune disorder. While patients with hematological malignancies displayed lower seroconversion rates after vaccination in some studies, a majority of cancer patients' risk factors for severe COVID-19 disease were either inherent (such as metastatic or progressive disease) or comparable to the general population (age, male gender and comorbidities such as kidney or liver disease). A deeper understanding is needed to better define patient subgroups at a higher risk for severe COVID-19 disease courses. At the same time, immune disorders as functional disease models offer further insights into the role of specific immune cells and cytokines when orchestrating the immune response towards SARS-CoV-2 infection. Longitudinal serological studies are urgently needed to determine the extent and the duration of SARS-CoV-2 immunity in the general population, as well as immune-compromised and oncological patients.},
  language  = {en}
}
@article{BertramBartschSodmannetal.2022,
  author    = {Bertram, Ralph and Bartsch, Vanessa and Sodmann, Johanna and Hennig, Luca and M{\"u}jde, Engin and Stock, Jonathan and Ruedig, Vivienne and Sodmann, Philipp and Todt, Daniel and Steinmann, Eike and Hitzl, Wolfgang and Steinmann, Joerg},
  title     = {Risk stratification of SARS-CoV-2 breakthrough infections based on an outbreak at a student festive event},
  series = {Vaccines},
  volume    = {10},
  journal   = {Vaccines},
  number    = {3},
  issn      = {2076-393X},
  doi       = {10.3390/vaccines10030432},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-267270},
  year      = {2022},
  abstract  = {In early 2022, the Coronavirus disease 2019 (COVID-19) remains a global challenge. COVID-19 is caused by an increasing number of variants of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we report an outbreak of SARS-CoV-2 breakthrough infections related to a student festive event with 100 mostly vaccinated guests, which took place in Northern Bavaria, Germany, in October 2021. The data were obtained by retrospective guest interviews. In total, 95 students participated in the study, with 94 being fully vaccinated and 24 reporting infection by the delta variant. Correlation analyses among 15 examined variables revealed that time spent at the event, conversation with the supposed index person, and a homologous viral vector vaccination regime were significant risk factors for infection. Non-significant observations related to higher rates of infection included time since last vaccination, shared use of drinking vessels, and number of individual person-to-person contacts at the event. Our data suggest that a high rate of breakthrough infections with the delta variant occurs if no preventive measures are practiced. To limit infection risk, high-quality testing of participants should be considered a mandatory measure at gatherings, irrespective of the participants' vaccination status.},
  language  = {en}
}
@article{MeintrupBorgmannSeidletal.2021,
  author    = {Meintrup, David and Borgmann, Stefan and Seidl, Karlheinz and Stecher, Melanie and Jakob, Carolin E. M. and Pilgram, Lisa and Spinner, Christoph D. and Rieg, Siegbert and Isberner, Nora and Hower, Martin and Vehreschild, Maria and G{\"o}pel, Siri and Hanses, Frank and Nowak-Machen, Martina},
  title     = {Specific risk factors for fatal outcome in critically ill COVID-19 patients: results from a European multicenter study},
  series = {Journal of Clinical Medicine},
  volume    = {10},
  journal   = {Journal of Clinical Medicine},
  number    = {17},
  issn      = {2077-0383},
  doi       = {10.3390/jcm10173855},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-245191},
  year      = {2021},
  abstract  = {(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06-1.10), cardiovascular disease (OR 1.64, CI 1.06-2.55), pulmonary disease (OR 1.87, CI 1.16-3.03), baseline Statin treatment (0.54, CI 0.33-0.87), oxygen saturation (unit = 1\%, OR 0.94, CI 0.92-0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01-1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94-0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62-0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05-1.18), kidney failure (OR 1.68, CI 1.05-2.70), congestive heart failure (OR 2.62, CI 1.11-6.21), severe liver failure (OR 4.93, CI 1.94-12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14-2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.},
  language  = {en}
}