High myoglobin level as an independent risk factor for death in elderly patients with critical COVID-19 infection: a retrospective case-control study

High myoglobin level is an independent risk factor for death and is therefore a prognostic marker in elderly patients with severe COVID-19 infection.

Authors

Institutions

Publication Details

Journal
BMC Infectious Diseases
Published
2024-08-20
DOI
https://doi.org/10.1186/s12879-024-09621-5
Citations
1
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
0.37

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High myoglobin level as an independent risk factor for death in elderly patients with critical COVID-19 infection: a retrospective case-control study

Lize Xiong, Cheng Li, Xiaoxiao Sun, Miaomiao Fei et al.
1 citations
BMC Infectious Diseases
Long-Term Effects of COVID-19
0.37
article

High myoglobin level as an independent risk factor for death in elderly patients with critical COVID-19 infection: a retrospective case-control study

Lize Xiong, Cheng Li, Xiaoxiao Sun, Miaomiao Fei, Meixian Zhang, Hui Zhang
article en
1 citations

Abstract

High myoglobin level is an independent risk factor for death and is therefore a prognostic marker in elderly patients with severe COVID-19 infection.

BMC Infectious DiseasesVol. 24(1)
Tongji University (CN), Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
National Natural Science Foundation of China
Good health and well-being
Openalex Percentile: Top 37%
Long-Term Effects of COVID-19
0.37
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.