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Cited by 200

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Toward Resolving the Challenges of Sepsis Diagnosis

Carrigan, Shawn D, Scott, George, Tabrizian, Maryam·2004·Clinical Chemistry

Abstract

Sepsis in the United States has an estimated annual healthcare cost of $16.7 billion and leads to 120 000 deaths. Insufficient development in both medical diagnosis and treatment of sepsis has led to continued growth in reported cases of sepsis over the past two decades with little improvement in mortality statistics. Efforts over the last decade to improve diagnosis have unsuccessfully sought to identify a “magic bullet” proteic biomarker that provides high sensitivity and specificity for infectious inflammation. More recently, genetic methods have made tracking regulation of the genes responsible for these biomarkers possible, giving current research new direction in the search to understand how host immune response combats infection. Despite the breadth of research, inadequate treatment as a result of delayed diagnosis continues to affect approximately one fourth of septic patients. In this report we review past and present diagnostic methods for sepsis and their respective limitations, and discuss the requirements for more timely diagnosis as the next step in curtailing sepsis-related mortality. We also present a proposal toward revision of the current diagnostic paradigm to include real-time immune monitoring.

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Metadata

Authors
Carrigan, S. D., Scott, G., & Tabrizian, M.
Venue
Clinical Chemistry
Published
2004-08-01
Volume
50
Issue
8
Pages
1301-1314
ISSN
  • 0009-9147 (ISSN-L)
  • 1530-8561
OpenAlex
W2026466007
Cited by
200
References
2
FWCI
7.20
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Toward Resolving the Challenges of Sepsis Diagnosis. https://app.cochat.ai/papers/10.1373/clinchem.2004.032144
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Carrigan, S. D., Scott, G., & Tabrizian, M. (2004). Toward Resolving the Challenges of Sepsis Diagnosis. Clinical Chemistry. https://doi.org/10.1373/clinchem.2004.032144

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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.