Related Experiment Video
Updated: Jun 25, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Identifying Mortality Predictors in Hospitalized COVID-19 Patients: Insights from a Single-Center Retrospective Study
Ondrej Zahornacky1, Alena Rovnakova1, Maria Surimova2
1Department of Infectology and Travel Medicine, Faculty of Medicine, Louis Pasteur University Hospital, Pavol Jozef Šafarik University, 041 90 Košice, Slovakia.
Introduction:
The pandemic instigated by the SARS-CoV-2 virus has led to over 7 million deaths globally, primarily attributable to viral pneumonia. Identifying fundamental markers associated with an elevated risk of mortality can aid in the early identification of patients prone to disease progression to a severe state, enabling prompt intervention.
Methods:
This was a single-center, retrospective study.
Results:
In this study, we examined 299 patients admitted to the Department of Infectology and Travel Medicine in Košice, Slovakia, with PCR-confirmed COVID-19 pneumonia. Patients were monitored from 1 January 2021 to 31 March 2021, with the endpoint being discharge from the hospital or death. All patient-related data were retrospectively collected from medical records. This study identified several risk factors significantly associated with an increased risk of mortality, including the requirement of HFNO (p < 0.001), age over 60 years (p < 0.001), Ne/Ly values of >6 (p < 0.001), as well as certain lymphocyte subtypes-CD4+ < 0.2 × 109/L (p = 0.035), CD8+ < 0.2 × 109/L (p < 0.001), and CD19+ < 0.1 × 109/L (p < 0.001)-alongside selected biochemical inflammatory markers-IL-6 > 50 ng/L (p < 0.001) and lactate > 3 mmol/L (p < 0.001).
Conclusions:
We confirmed that the mentioned risk factors were significantly associated with the death of patients from viral pneumonia in the hospital.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Related Concept Videos
Kaplan-Meier Approach
Cancer Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Assumptions of Survival Analysis
Censoring Survival Data