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Identification of a sub-group of critically ill patients with high risk of intensive care unit-acquired infections and poor clinical course using a transcriptomic score
- Source :
- Critical Care, Vol 27, Iss 1, Pp 1-14 (2023)
- Publication Year :
- 2023
- Publisher :
- BMC, 2023.
-
Abstract
- Abstract Background The development of stratification tools based on the assessment of circulating mRNA of genes involved in the immune response is constrained by the heterogeneity of septic patients. The aim of this study is to develop a transcriptomic score based on a pragmatic combination of immune-related genes detected with a prototype multiplex PCR tool. Methods As training cohort, we used the gene expression dataset obtained from 176 critically ill patients enrolled in the REALISM study (NCT02638779) with various etiologies and still hospitalized in intensive care unit (ICU) at day 5–7. Based on the performances of each gene taken independently to identify patients developing ICU-acquired infections (ICU-AI) after day 5–7, we built an unweighted score assuming the independence of each gene. We then determined the performances of this score to identify a subgroup of patients at high risk to develop ICU-AI, and both longer ICU length of stay and mortality of this high-risk group were assessed. Finally, we validated the effectiveness of this score in a retrospective cohort of 257 septic patients. Results This transcriptomic score (TScore) enabled the identification of a high-risk group of patients (49%) with an increased rate of ICU-AI when compared to the low-risk group (49% vs. 4%, respectively), with longer ICU length of stay (13 days [95% CI 8–30] vs. 7 days [95% CI 6–9], p
Details
- Language :
- English
- ISSN :
- 13648535
- Volume :
- 27
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Critical Care
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.79f8118eff430eb3627a8e0a39d2af
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s13054-023-04436-3