The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A prospective, multicenter derivation of a biomarker panel to assess risk of organ dysfunction, shock, and death in emergency department patients with suspected sepsis
Abstract
OBJECTIVE: To define a biomarker panel to predict organ dysfunction, shock, and in-hospital mortality in emergency department (ED) patients with suspected sepsis. DESIGN: Prospective observational study. SETTING: EDs of ten academic medical centers. PATIENTS: There were 971 patients enrolled. INCLUSION CRITERIA: 1) ED patients age > 18; 2) suspected infection or a serum lactate level > 2.5 mmol/L; and 3) two or more systemic inflammatory response syndrome criteria. EXCLUSION CRITERIA: pregnancy, do-not-resuscitate status, or cardiac arrest. MEASUREMENTS AND MAIN RESULTS: Nine biomarkers were assayed from blood draws obtained on ED presentation. Multivariable logistic regression was used to identify an optimal combination of biomarkers to create a panel. The derived formula for weighting biomarker values was used to calculate a "sepsis score," which was the predicted probability of the primary outcome of severe sepsis (sepsis plus organ dysfunction) within 72 hrs. We also assessed the ability of the sepsis score to predict secondary outcome measures of septic shock within 72 hrs and in-hospital mortality. The overall rates of each outcome were severe sepsis, 52%; septic shock, 39%; and in-hospital mortality 7%. Among the nine biomarkers tested, the optimal 3-marker panel was neutrophil gelatinase-associated lipocalin, protein C, and interleukin-1 receptor antagonist. The area under the curve for the accuracy of the sepsis score derived from these three biomarkers was 0.80 for severe sepsis, 0.77 for septic shock, and 0.79 for death. When included in multivariate models with clinical variables, the sepsis score remained highly significant (p < 0.001) for all the three outcomes. CONCLUSIONS: A biomarker panel of neutrophil gelatinase-associated lipocalin, interleukin-1ra, and Protein C was predictive of severe sepsis, septic shock, and death in ED patients with suspected sepsis. Further study is warranted to prospectively validate the clinical utility of these biomarkers and the sepsis score in risk-stratifying patients with suspected sepsis.
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-citationKumar, A., Roberts, D., Wood, K. E., Light, B., Parrillo, J. E., Sharma, S., Suppes, R., Feinstein, D., Zanotti, S., Taiberg, L., et al. (2006) · Critical Care Medicine · doi:10.1097/01.ccm.0000217961.75225.e9 · Cited by 6,109
Mishra, J., Ma, Q., Prada, A., Mitsnefes, M., Zahedi, K., Yang, J., Barasch, J., & Devarajan, P. (2003) · Journal of the American Society of Nephrology · doi:10.1097/01.asn.0000088027.54400.c6 · Cited by 1,749
Update on Mechanisms of Ischemic Acute Kidney Injury
Devarajan, P. (2006) · Journal of the American Society of Nephrology · doi:10.1681/asn.2006010017 · Cited by 1,026
Cited by
Pierrakos, C., & Vincent, J.-L. (2010) · Critical Care · doi:10.1186/cc8872 · Cited by 1,377
Faix, J. D. (2013) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408363.2013.764490 · Cited by 663
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
Chakraborty, S., Kaur, S., Guha, S., & Batra, S. K. (2012) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2012.03.008 · Cited by 503
Levin, S., Toerper, M., Hamrock, E., Hinson, J. S., Barnes, S., Gardner, H., Dugas, A., Linton, B., Kirsch, T., & Kelen, G. (2018) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2017.08.005 · Cited by 424
Metadata
- Authors
- Shapiro, N. I., Trzeciak, S., Hollander, J. E., Birkhahn, R., Otero, R., Osborn, T. M., Moretti, E., Nguyen, H. B., Gunnerson, K. J., Milzman, D., Gaieski, D. F., Goyal, M., Cairns, C. B., Ngo, L., & Rivers, E. P.
- Venue
- Critical Care Medicine
- Published
- 2009-01
- Volume
- 37
- Issue
- 1
- Pages
- 96-104
- ISSN
- 0090-3493 (ISSN-L)
- OpenAlex
- W2063333923
- Cited by
- 242
- References
- 4
- FWCI
- 11.61
- 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: A prospective, multicenter derivation of a biomarker panel to assess risk of organ dysfunction, shock, and death in emergency department patients with suspected sepsis. https://app.cochat.ai/papers/10.1097/ccm.0b013e318192fd9d
- The paper
- Shapiro, N. I., Trzeciak, S., Hollander, J. E., Birkhahn, R., Otero, R., Osborn, T. M., Moretti, E., Nguyen, H. B., Gunnerson, K. J., Milzman, D., Gaieski, D. F., Goyal, M., Cairns, C. B., Ngo, L., & Rivers, E. P. (2009). A prospective, multicenter derivation of a biomarker panel to assess risk of organ dysfunction, shock, and death in emergency department patients with suspected sepsis. Critical Care Medicine. https://doi.org/10.1097/ccm.0b013e318192fd9d
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.