BIOCHEMICAL MARKERS OF BLOOD IN ACUTE PERIODS OF COVID-19 AND INFLUENZA A

Recent studies show that the clinical picture of COVID-19 and influenza A, accompanied by pneumonia, looks similar at the initial stage. Therefore, it is important to determine the type of viral disease before starting treatment. The aim of the pilot clinical observational cross-sectional study was to identify a marker distinguishing acute COVID-19 from acute influenza A among routine blood serum biochemical indicators. The study material was blood samples from patients who met the inclusion criteria and were treated in two hospitals in the Krasnodar region (Russia) between 2020 and 2022. The selected patients aged 35-65 years had confirmed COVID-19 or influenza A conditions, accompanied by grade 3 pneumonia, and did not have any chronic diseases that could complicate the course of viral diseases. The results of the following biochemical parameters were evaluated: ferritin, hemoglobin, serum iron, C-reactive protein and the number of red blood cells. Blood samples from patients without viral diseases were added as a positive control. As a result of the study, we obtained constructed ROC curves for each indicator of blood serum and a discriminant analysis for all indicators combined showed that viral diseases successfully differ, mainly in terms of ferritin and C-reactive protein values.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-26
DOI
https://doi.org/10.5281/zenodo.17199962
Primary Topic
Coronary Interventions and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

BIOCHEMICAL MARKERS OF BLOOD IN ACUTE PERIODS OF COVID-19 AND INFLUENZA A

Zenodo (CERN European Organization for Nuclear Research)
Coronary Interventions and Diagnostics
article

BIOCHEMICAL MARKERS OF BLOOD IN ACUTE PERIODS OF COVID-19 AND INFLUENZA A

article en

Abstract

Recent studies show that the clinical picture of COVID-19 and influenza A, accompanied by pneumonia, looks similar at the initial stage. Therefore, it is important to determine the type of viral disease before starting treatment. The aim of the pilot clinical observational cross-sectional study was to identify a marker distinguishing acute COVID-19 from acute influenza A among routine blood serum biochemical indicators. The study material was blood samples from patients who met the inclusion criteria and were treated in two hospitals in the Krasnodar region (Russia) between 2020 and 2022. The selected patients aged 35-65 years had confirmed COVID-19 or influenza A conditions, accompanied by grade 3 pneumonia, and did not have any chronic diseases that could complicate the course of viral diseases. The results of the following biochemical parameters were evaluated: ferritin, hemoglobin, serum iron, C-reactive protein and the number of red blood cells. Blood samples from patients without viral diseases were added as a positive control. As a result of the study, we obtained constructed ROC curves for each indicator of blood serum and a discriminant analysis for all indicators combined showed that viral diseases successfully differ, mainly in terms of ferritin and C-reactive protein values.

Zenodo (CERN European Organization for Nuclear Research)
Kuban State University (RU), First Pavlov State Medical University of St. Petersburg (RU), Regional Clinical Research (US), Helix (United States) (US), Children's Specialized Hospital (US)
Reduced inequalities
Openalex Percentile: Top 33%
Coronary Interventions and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.