2021
DOI: 10.3390/jcm10173855
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Specific Risk Factors for Fatal Outcome in Critically Ill COVID-19 Patients: Results from a European Multicenter Study

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 identif… Show more

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Cited by 13 publications
(10 citation statements)
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“…This study analyzed patient data from the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort [ 30 ]. The LEOSS project represents a non-interventional, multicenter network that aims at addressing the lack of in-depth knowledge on the epidemiology and clinical course of COVID-19.…”
Section: Methodsmentioning
confidence: 99%
“…This study analyzed patient data from the Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) cohort [ 30 ]. The LEOSS project represents a non-interventional, multicenter network that aims at addressing the lack of in-depth knowledge on the epidemiology and clinical course of COVID-19.…”
Section: Methodsmentioning
confidence: 99%
“…On the other hand, finding of SARS-CoV-2 RNA is only possible if a contact to the virus had happened. Various preexisting diseases increase the probability for fatal courses, e.g., heart diseases [ 56 , 57 , 58 , 59 ]. Often it is difficult to discriminate if SARS-CoV-2 infection contributed to the death of a patient, e.g., if a still SARS-CoV-2 positive patient with a previous infection dies due to a heart attack.…”
Section: Discussionmentioning
confidence: 99%
“…Finally, a variable selection, which is usually not presented as part of the traditional selection methods but has found its use in various studies, was also implemented [ 56 , 57 ]. In this approach, the least absolute shrinkage and selection operator (LASSO) is used to select the relevant variables.…”
Section: Methodsmentioning
confidence: 99%