Added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection

Toshihiko Takada, J. Hoogland, Tetsuhiro Yano, Kotaro Fujii, Ryuto Fujiishi, Jun Miyashita, Taro Takeshima, Michio Hayashi, Teruhisa Azuma, Karel G.M. Moons

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6 Citations (Scopus)

Abstract

Objective: To evaluate the added value of inflammatory markers to vital signs to predict mortality in patients suspected of severe infection. Methods: This study was conducted at an acute care hospital (471-bed capacity). Consecutive adult patients suspected of severe infection who presented to either ambulatory care or the emergency department from April 2015 to March 2017 were retrospectively evaluated. A prognostic model for predicting 30-day in-hospital mortality based on previously established vital signs (systolic blood pressure, respiratory rate, and mental status) was compared with an extended model that also included four inflammatory markers (C-reactive protein, neutrophil-lymphocyte ratio, mean platelet volume, and red cell distribution width). Measures of interest were model fit, discrimination, and the net percentage of correctly reclassified individuals at the pre-specified threshold of 10% risk. Results: Of the 1015 patients included, 66 (6.5%) died. The extended model including inflammatory markers performed significantly better than the vital sign model (likelihood ratio test: p < 0.001), and the c-index increased from 0.69 (range 0.67–0.70) to 0.76 (range 0.75–0.77) (p = 0.01). All included markers except C-reactive protein showed significant contribution to the model improvement. Among those who died, 9.1% (95% CI −2.8–21.8) were correctly reclassified by the extended model at the 10% threshold. Conclusions: The inflammatory markers except C-reactive protein showed added predictive value to vital signs. Future studies should focus on developing and validating prediction models for use in individualized predictions including both vital signs and the significant markers.

Original languageEnglish
Pages (from-to)1389-1395
Number of pages7
JournalAmerican Journal of Emergency Medicine
Volume38
Issue number7
DOIs
Publication statusPublished - Jul 2020

Keywords

  • Biomarkers
  • Clinical decision-making
  • Decision support techniques
  • Infection
  • Prognosis
  • Sepsis

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