The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
A robust scoring system to evaluate sepsis severity in an animal model
Open accessAbstract
BACKGROUND: The lack of a reliable scoring system that predicts the development of septic shock and death precludes comparison of disease and/or treatment outcomes in animal models of sepsis. We developed a murine sepsis score (MSS) that evaluates seven clinical variables, and sought to assess its validity and reliability in an experimental mouse model of polymicrobial sepsis. METHODS: Stool collected from the cecum of C57BL/6 (B6) mice was dissolved in 0.9% normal saline (NS) and filtered, resulting in a fecal solution (FS) which was injected intraperitoneally into B6 mice. Disease severity was monitored by MSS during the experimental timeline. Blood and tissue samples were harvested for the evaluation of inflammatory changes after sepsis induction. The correlation between pro-inflammatory markers and MSS was assessed by the Spearman rank correlation coefficient. RESULTS: Mice injected with FS at a concentration of 90 mg/mL developed polymicrobial sepsis with a 75% mortality rate at 24 hours. The MSS was highly predictive of sepsis progression and mortality, with excellent discriminatory power, high internal consistency (Cronbach alpha coefficient = 0.92), and excellent inter-rater reliability (intra-class coefficient = 0.96). An MSS of 3 had a specificity of 100% for predicting onset of septic shock and death within 24 hours. Hepatic dysfunction and systemic pro-inflammatory responses were confirmed by biochemical and cytokine analyses where the latter correlated well with the MSS. Significant bacterial dissemination was noted in multiple organs. Furthermore, the liver, spleen, and intestine demonstrated histopathological evidence of injury. CONCLUSIONS: The MSS reliably predicts disease progression and mortality in an animal model of polymicrobial sepsis. More importantly, it may be used to assess and compare outcomes among various experimental models of sepsis, and serve as an ethically acceptable alternative to death as an endpoint.
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Cites
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
APACHE II: A severity of disease classification system
KNAUS, W. A., DRAPER, E. A., WAGNER, D. P., & ZIMMERMAN, J. E. (1985) · Critical Care Medicine · doi:10.1097/00003246-198510000-00009 · Cited by 13,664
APACHE II-A Severity of Disease Classification System: Reply
Knaus, W. A., Draper, E. A., Wagner, D. P., & Zimmerman, J. E. (1986) · Critical Care Medicine · doi:10.1097/00003246-198608000-00028 · Cited by 13,376
Bone, R. C., Balk, R. A., Cerra, F. B., Dellinger, R. P., Fein, A. M., Knaus, W. A., Schein, R. M. H., & Sibbald, W. J. (1992) · Chest · doi:10.1378/chest.101.6.1644 · Cited by 13,198
Identification of programmed cell death in situ via specific labeling of nuclear DNA fragmentation.
Gavrieli, Y., Sherman, Y., & Ben-Sasson, S. A. (1992) · The Journal of cell biology · doi:10.1083/jcb.119.3.493 · Cited by 9,444
APACHE II: a severity of disease classification system.
Knaus, W. A., Draper, E. S., Wagner, D. P., & Zimmerman, J. E. (1985) · PubMed · Cited by 6,034
2001 SCCM/ESICM/ACCP/ATS/SIS International Sepsis Definitions Conference
Levy, M. M., Fink, M. P., Marshall, J. C., Abraham, E., Angus, D., Cook, D., Cohen, J., Opal, S. M., Vincent, J.-L., & Ramsay, G. (2003) · Critical Care Medicine · doi:10.1097/01.ccm.0000050454.01978.3b · Cited by 5,995
The epidemiology of sepsis in the United States from 1979 through 2000
Martin, G. S., Mannino, D. M., Eaton, S., & Moss, M. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022139 · Cited by 5,841
The Pathophysiology and Treatment of Sepsis
Hotchkiss, R. S., & Karl, I. E. (2003) · New England Journal of Medicine · doi:10.1056/nejmra021333 · Cited by 4,097
International Study of the Prevalence and Outcomes of Infection in Intensive Care Units
Vincent, J.-L. (2009) · JAMA · doi:10.1001/jama.2009.1754 · Cited by 3,618
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Wong, C. K., McLean, B. A., Baggio, L. L., Koehler, J. A., Hammoud, R., Rittig, N., Yabut, J. M., Seeley, R. J., Brown, T. J., & Drucker, D. J. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2023.11.009 · Cited by 304
Kupffer cell–like syncytia replenish resident macrophage function in the fibrotic liver
Peiseler, M., Araujo David, B., Zindel, J., Surewaard, B. G. J., Lee, W.-Y., Heymann, F., Nusse, Y., Castanheira, F. V. S., Shim, R., Guillot, A., et al. (2023) · Science · doi:10.1126/science.abq5202 · Cited by 123
Inflammasome-mediated GSDMD activation facilitates escape of Candida albicans from macrophages
Ding, X., Kambara, H., Guo, R., Kanneganti, A., Acosta-Zaldívar, M., Li, J., Liu, F., Bei, T., Qi, W., Xie, X., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27034-9 · Cited by 115
Lactobacillus paracasei feeding improves immune control of influenza infection in mice
Belkacem, N., Serafini, N., Wheeler, R., Derrien, M., Boucinha, L., Couesnon, A., Cerf-Bensussan, N., Gomperts Boneca, I., Di Santo, J. P., Taha, M.-K., et al. (2017) · PLOS ONE · doi:10.1371/journal.pone.0184976 · Cited by 108
Metadata
- Authors
- Shrum, B., Anantha, R. V., Xu, S. X., Donnelly, M., Haeryfar, S. M., McCormick, J. K., & Mele, T.
- Venue
- BMC Research Notes
- Published
- 2014-04-12
- Volume
- 7
- Issue
- 1
- Pages
- 233-233
- ISSN
- 1756-0500 (ISSN-L)
- OpenAlex
- W2036607436
- Cited by
- 520
- References
- 37
- FWCI
- 7.42
- Type
- journal article
- Language
- en
- Open access
- gold
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