Prognostic utility and characterization of cell-free DNA in patients with severe sepsis

Dhruva J Dwivedi,Laura L Swystun,Jeffrey I Weitz,Janice Pogue,Kao-Lee Liaw,Patricia C Liaw,Alison E Fox-Robichaud,Deborah J Cook,Lisa J Toltl

doi:10.1186/cc11466

Abstract

IntroductionAlthough sepsis is the leading cause of death in noncoronary critically ill patients, identification of patients at high risk of death remains a challenge. In this study, we examined the incremental usefulness of adding multiple biomarkers to clinical scoring systems for predicting intensive care unit (ICU) mortality in patients with severe sepsis.MethodsThis retrospective observational study used stored plasma samples obtained from 80 severe sepsis patients recruited at three tertiary hospital ICUs in Hamilton, Ontario, Canada. Clinical data and plasma samples were obtained at study inclusion for all 80 patients, and then daily for 1 week, and weekly thereafter for a subset of 50 patients. Plasma levels of cell-free DNA (cfDNA), interleukin 6 (IL-6), thrombin, and protein C were measured and compared with clinical characteristics, including the primary outcome of ICU mortality and morbidity measured with the Multiple Organ Dysfunction (MODS) score and Acute Physiology and Chronic Health Evaluation (APACHE) II scores.ResultsThe level of cfDNA in plasma at study inclusion had better prognostic utility than did MODS or APACHE II scores, or the biomarkers measured. The area under the receiver operating characteristic (ROC) curves for cfDNA to predict ICU mortality is 0.97 (95% CI, 0.93 to 1.00) and to predict hospital mortality is 0.84 (95% CI, 0.75 to 0.94). We found that a cfDNA cutoff value of 2.35 ng/μl had a sensitivity of 87.9% and specificity of 93.5% for predicting ICU mortality. Sequential measurements of cfDNA suggested that ICU mortality may be predicted within 24 hours of study inclusion, and that the predictive power of cfDNA may be enhanced by combining it with protein C levels or MODS scores. DNA-sequence analyses and studies with Toll-like receptor 9 (TLR9) reporter cells suggests that the cfDNA from sepsis patients is host derived.ConclusionsThese studies suggest that cfDNA provides high prognostic accuracy in patients with severe sepsis. The serial data suggest that the combination of cfDNA with protein C and MODS scores may yield even stronger predictive power. Incorporation of cfDNA in sepsis risk-stratification systems may be valuable for clinical decision making or for inclusion into sepsis trials.

Highlights

Sepsis is the leading cause of death in noncoronary critically ill patients, identification of patients at high risk of death remains a challenge
Prognostic utility of cell-free DNA (cfDNA) in severe sepsis patients The baseline characteristics of the 80 severe sepsis patients are shown in Table 1 (“baseline” is defined as within 24 hours of meeting the inclusion criteria for severe sepsis in the intensive care unit (ICU))
By using the variables created by the OUTROC option of the MODEL statement in the LOGISTIC procedure [22], the receiver operating characteristic (ROC) curves were drawn by using Excel, and the area under the curve (AUC) and their standard errors were computed by using SAS codes, based on the distribution-free formulas provided by Hanley and McNeil [8]

Summary

Introduction

Sepsis is the leading cause of death in noncoronary critically ill patients, identification of patients at high risk of death remains a challenge. The first class of scoring system assesses disease severity primarily through evaluation of physiological parameters (for example, Acute Physiology and Chronic Health Evaluation [APACHE] II score [5]). These scores are somewhat laborious to use and are primarily considered at the time of admission to the intensive care unit (ICU). Examples are the Multiple Organ Dysfunction Scores [MODS] [6] and Sequential Organ Failure Assessment [SOFA] [7] scores Both of these classes of scoring systems focus only on physiological abnormalities, and they are not exclusive to patients with sepsis syndrome. With receiver operating characteristic (ROC) curves [8], which measure the diagnostic accuracy of a given test, the area under the curve (AUC) for these scores ranges from 0.6 to 0.7 [9]

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