Usage Information
Abstract
For over a decade, sepsis phenotyping has identified hyperinflammatory and hypoinflammatory subphenotypes using host biomarkers and clinical variables, without factoring in contributions from infectious insults across patients. In this issue, Chanderraj and colleagues challenge this host-centric paradigm by demonstrating that pathogen characteristics independently contribute to sepsis subphenotypes. They reported that Enterobacterales infections, particularly Escherichia coli, strongly associated with hyperinflammatory subphenotypes, independent of illness severity. Bacterial burden, anatomic barrier breach, and circulating pathogen-associated molecular patterns influence phenotypic classification, with implications extending to culture-negative sepsis. Animal models supported causality, while reanalysis of an observational cohort and a clinical trial revealed that lactate clearance’s prognostic value and therapeutic effects of endotoxin removal with polymyxin B hemoadsorption vary by subphenotype and pathogen. These findings lay groundwork for integrative host-pathogen phenotyping; for precision medicine in critical illness, we must know not only who is sick, but what made them sick, and how the two interact.
Authors
Georgios D. Kitsios, Rebecca M. Baron
Usage data is cumulative from March 2026 through May 2026.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 1,243 | 0 |
| 346 | 0 | |
| Figure | 220 | 0 |
| Citation downloads | 85 | 0 |
| Totals | 1,894 | 0 |
| Total Views | 1,894 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)