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Discriminative value of inflammatory biomarkers for suspected sepsis.

Publication ,  Journal Article
Tsalik, EL; Jaggers, LB; Glickman, SW; Langley, RJ; van Velkinburgh, JC; Park, LP; Fowler, VG; Cairns, CB; Kingsmore, SF; Woods, CW
Published in: J Emerg Med
July 2012

BACKGROUND: Circulating biomarkers can facilitate sepsis diagnosis, enabling early management and improved outcomes. Procalcitonin (PCT) has been suggested to have superior diagnostic utility compared to other biomarkers. STUDY OBJECTIVES: To define the discriminative value of PCT, interleukin-6 (IL-6), and C-reactive protein (CRP) for suspected sepsis. METHODS: PCT, CRP, and IL-6 were correlated with infection likelihood, sepsis severity, and septicemia. Multivariable models were constructed for length-of-stay and discharge to a higher level of care. RESULTS: Of 336 enrolled subjects, 60% had definite infection, 13% possible infection, and 27% no infection. Of those with infection, 202 presented with sepsis, 28 with severe sepsis, and 17 with septic shock. Overall, 21% of subjects were septicemic. PCT, IL6, and CRP levels were higher in septicemia (median PCT 2.3 vs. 0.2 ng/mL; IL-6 178 vs. 72 pg/mL; CRP 106 vs. 62 mg/dL; p < 0.001). Biomarker concentrations increased with likelihood of infection and sepsis severity. Using receiver operating characteristic analysis, PCT best predicted septicemia (0.78 vs. IL-6 0.70 and CRP 0.67), but CRP better identified clinical infection (0.75 vs. PCT 0.71 and IL-6 0.69). A PCT cutoff of 0.5 ng/mL had 72.6% sensitivity and 69.5% specificity for bacteremia, as well as 40.7% sensitivity and 87.2% specificity for diagnosing infection. A combined clinical-biomarker model revealed that CRP was marginally associated with length of stay (p = 0.015), but no biomarker independently predicted discharge to a higher level of care. CONCLUSIONS: In adult emergency department patients with suspected sepsis, PCT, IL-6, and CRP highly correlate with several infection parameters, but are inadequately discriminating to be used independently as diagnostic tools.

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Published In

J Emerg Med

DOI

ISSN

0736-4679

Publication Date

July 2012

Volume

43

Issue

1

Start / End Page

97 / 106

Location

United States

Related Subject Headings

  • Systemic Inflammatory Response Syndrome
  • Statistics, Nonparametric
  • Severity of Illness Index
  • Sepsis
  • ROC Curve
  • Protein Precursors
  • Patient Discharge
  • Multivariate Analysis
  • Middle Aged
  • Male
 

Citation

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Tsalik, E. L., Jaggers, L. B., Glickman, S. W., Langley, R. J., van Velkinburgh, J. C., Park, L. P., … Woods, C. W. (2012). Discriminative value of inflammatory biomarkers for suspected sepsis. J Emerg Med, 43(1), 97–106. https://doi.org/10.1016/j.jemermed.2011.05.072
Tsalik, Ephraim L., L Brett Jaggers, Seth W. Glickman, Raymond J. Langley, Jennifer C. van Velkinburgh, Lawrence P. Park, Vance G. Fowler, Charles B. Cairns, Stephen F. Kingsmore, and Christopher W. Woods. “Discriminative value of inflammatory biomarkers for suspected sepsis.J Emerg Med 43, no. 1 (July 2012): 97–106. https://doi.org/10.1016/j.jemermed.2011.05.072.
Tsalik EL, Jaggers LB, Glickman SW, Langley RJ, van Velkinburgh JC, Park LP, et al. Discriminative value of inflammatory biomarkers for suspected sepsis. J Emerg Med. 2012 Jul;43(1):97–106.
Tsalik, Ephraim L., et al. “Discriminative value of inflammatory biomarkers for suspected sepsis.J Emerg Med, vol. 43, no. 1, July 2012, pp. 97–106. Pubmed, doi:10.1016/j.jemermed.2011.05.072.
Tsalik EL, Jaggers LB, Glickman SW, Langley RJ, van Velkinburgh JC, Park LP, Fowler VG, Cairns CB, Kingsmore SF, Woods CW. Discriminative value of inflammatory biomarkers for suspected sepsis. J Emerg Med. 2012 Jul;43(1):97–106.
Journal cover image

Published In

J Emerg Med

DOI

ISSN

0736-4679

Publication Date

July 2012

Volume

43

Issue

1

Start / End Page

97 / 106

Location

United States

Related Subject Headings

  • Systemic Inflammatory Response Syndrome
  • Statistics, Nonparametric
  • Severity of Illness Index
  • Sepsis
  • ROC Curve
  • Protein Precursors
  • Patient Discharge
  • Multivariate Analysis
  • Middle Aged
  • Male