The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
The influence of early hemodynamic optimization on biomarker patterns of severe sepsis and septic shock*
Abstract
BACKGROUND: Despite abundant experimental studies of biomarker patterns in early severe sepsis and septic shock, human data are few. Further, the impact of the severity of global tissue hypoxia resulting from resuscitative strategies on these early biomarker patterns remains unknown. METHODS: The temporal patterns of interleukin-1 receptor antagonist, intercellular adhesion molecule-1, tumor necrosis factor-alpha, caspase-3, and interleukin-8 were serially examined over the first 72 hrs of hospitalization after early hemodynamic optimization strategies of early goal-directed vs. standard therapy for severe sepsis and septic shock patients. The relationship of these biomarker patterns to each hemodynamic optimization strategy, severity of global tissue hypoxia (reflected by lactate and central venous oxygen saturation), organ dysfunction, and mortality were examined. RESULTS: Abnormal biomarker levels were present upon hospital presentation and modulated to distinct patterns within 3 hrs based on the hemodynamic optimization strategy. The temporal expression of these patterns over 72 hrs was significantly associated with the severity of global tissue hypoxia, organ dysfunction, and mortality. CONCLUSION: In early severe sepsis and septic shock, within the first 3 hrs of hospital presentation, distinct biomarker patterns emerge in response to hemodynamic optimization strategies. A significant association exists between temporal biomarker patterns in the first 72 hrs, severity of global tissue hypoxia, organ dysfunction, and mortality. These findings identify global tissue hypoxia as an important contributor to the early inflammatory response and support the role of hemodynamic optimization in supplementing other established therapies during this diagnostic and therapeutic "window of opportunity."
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Early goal-directed therapy in the treatment of severe sepsis and septic shock
Rivers, E., Nguyen, B., Havstad, S., Ressler, J., Muzzin, A., Knoblich, B., Peterson, E., & Tomlanovich, M. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa010307 · Cited by 10,743
Self-citationComparison of Two Fluid-Management Strategies in Acute Lung Injury
(2006) · New England Journal of Medicine · doi:10.1056/nejmoa062200 · Cited by 3,538
Bone, R. C. (1996) · Annals of Internal Medicine · doi:10.7326/0003-4819-125-8-199610150-00009 · Cited by 718 · cited 1×
“These delayed peaks or second hits have been described previously and associated with increased organ dysfunction in vitro (57, 58) and in vivo (31, 32, 59, 60).”
BackgroundGao, F., Melody, T., Daniels, D. F., Giles, S., & Fox, S. (2005) · Critical Care · doi:10.1186/cc3909 · Cited by 461
Cited by
New Approaches to Sepsis: Molecular Diagnostics and Biomarkers
Reinhart, K., Bauer, M., Riedemann, N. C., & Hartog, C. S. (2012) · Clinical Microbiology Reviews · doi:10.1128/cmr.00016-12 · Cited by 533
The Importance of Fluid Management in Acute Lung Injury Secondary to Septic Shock
Murphy, C. V., Schramm, G. E., Doherty, J. A., Reichley, R. M., Gajic, O., Afessa, B., Micek, S. T., & Kollef, M. H. (2009) · Chest · doi:10.1378/chest.08-2706 · Cited by 441
Pathophysiology of microcirculatory dysfunction and the pathogenesis of septic shock
De Backer, D., Orbegozo Cortes, D., Donadello, K., & Vincent, J.-L. (2014) · Virulence · doi:10.4161/viru.26482 · Cited by 393
Cecconi, M., Corredor, C., Arulkumaran, N., Abuella, G., Ball, J., Grounds, R. M., Hamilton, M., & Rhodes, A. (2012) · Critical Care · doi:10.1186/cc11823 · Cited by 339
Fluid resuscitation in sepsis: the great 30 mL per kg hoax
Marik, P. E., Byrne, L., & van Haren, F. (2020) · Journal of Thoracic Disease · doi:10.21037/jtd.2019.12.84 · Cited by 116
Metadata
- Authors
- Rivers, E. P., Kruse, J. A., Jacobsen, G., Shah, K., Loomba, M., Otero, R., & Childs, E. W.
- Venue
- Critical Care Medicine
- Published
- 2007-09
- Volume
- 35
- Issue
- 9
- Pages
- 2016-2024
- ISSN
- 0090-3493 (ISSN-L)
- OpenAlex
- W2091933839
- Cited by
- 210
- References
- 4
- FWCI
- 17.38
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The influence of early hemodynamic optimization on biomarker patterns of severe sepsis and septic shock*. https://app.cochat.ai/papers/10.1097/01.ccm.0000281637.08984.6e
- The paper
- Rivers, E. P., Kruse, J. A., Jacobsen, G., Shah, K., Loomba, M., Otero, R., & Childs, E. W. (2007). The influence of early hemodynamic optimization on biomarker patterns of severe sepsis and septic shock*. Critical Care Medicine. https://doi.org/10.1097/01.ccm.0000281637.08984.6e
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.