Long Chain Non-Coding RNA Genes in Sepsis Diagnosis and Management
Author Information
Author(s): Bai Yong, Gao Jing, Yan Yuwen, Zhao Xu
Primary Institution: Hubei University of Medicine, Renmin Hospital, Shiyan, Hubei, China
Hypothesis
The study aims to determine the value of specific long chain non-coding RNAs in diagnosing adult sepsis patients and to develop a prediction model.
Conclusion
LncRNAs RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 can aid in the diagnosis and treatment of adult sepsis patients.
Supporting Evidence
- 1069 genes were identified in the GSE95233 dataset, with 102 being sepsis-related.
- 467 genes were up-regulated and 432 down-regulated in the GSE57065 dataset.
- ROC analysis showed that RP3-508I15.21, RP11-295G20.2, and LDLRAD4-AS1 had AUC values greater than 0.7, indicating diagnostic significance.
Takeaway
This study found that certain genes can help doctors figure out if someone has sepsis, which is a serious infection.
Methodology
The study used microarray datasets, machine learning methods, and statistical analyses to identify sepsis-related genes and build a prediction model.
Limitations
The study may have limitations related to the generalizability of the findings due to the specific datasets used.
Participant Demographics
Adult sepsis patients
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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