Sepsis subphenotypes, theragnostics and personalized sepsis care
Imperial College Healthcare NHS Trust · Imperial College London · +3 more institutions
Abstract
Heterogeneity between critically ill patients with sepsis is a major barrier to the discovery of effective therapies. The use of machine learning techniques, coupled with improved understanding of sepsis biology, has led to the identification of patient subphenotypes. This exciting development may help overcome the problem of patient heterogeneity and lead to the identification of patient subgroups with treatable traits. Re-analyses of completed clinical trials have demonstrated that patients with different subphenotypes may respond differently to treatments. This suggests that future clinical trials that take a precision medicine approach will have a higher likelihood of identifying effective therapeutics for…
Citation impact
- FWCI
- 44.38
- Percentile
- 100%
- References
- 78
Authors
6- DADavid AntcliffeCorresponding
Imperial College Healthcare NHS Trust, Imperial College London
- ABAidan Burrell
Australian and New Zealand Intensive Care Society
- ABAndrew Boyle
Queen's University Belfast, Belfast Health and Social Care Trust
- AGAnthony Gordon
Imperial College London
- DFDaniel F McAuley
Queen's University Belfast, Belfast Health and Social Care Trust
Topics & keywords
- Medicine
- Pain medicine
- Sepsis
- Anesthesiology
- Intensive care medicine
- Surviving Sepsis Campaign
- Septic shock
- Severe sepsis