Evidence map›Paper›PMID 30459950›Full record

ArticleJournal of intensive care2018

Evaluating the discriminating capacity of cell death (apoptotic) biomarkers in sepsis.

Christopher Duplessis, Michael Gregory, Kenneth Frey, Matthew Bell, Luu Truong, Kevin Schully, James Lawler, Raymond J Langley, Stephen F Kingsmore, Christopher W Woods and 6 more

Open access · goldAbstract read
In one paragraph

Article in Journal of intensive care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
1.9field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 3 syntheses or guidelines pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Impaired peripheral mononuclear cell metabolism in patients at risk of developing sepsis: A cohort study.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2026
    Article
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
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  13. Comparison of Serum Nucleosomes and Tissue Inhibitor of Metalloproteinase1 (TIMP1) in Predicting Mortality in Adult Critically Ill Patients in Sepsis: Prospective Observational Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2022
    Article
  14. Observational
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 6 institutions in 1 country.

Christopher Duplessis1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.ORCID 0000-0003-3489-0913
Michael Gregory1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Kenneth Frey1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Matthew Bell1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Luu Truong1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Kevin Schully1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
James Lawler1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Raymond J Langley2Department of Pharmacology and Center for Lung Biology, University of South Alabama College of Medicine, Mobile, USA.
Stephen F Kingsmore3Rady Pediatric Genomic and Systems Medicine Institute, Rady Children's Hospital, Encinitas, USA.
Christopher W Woods4Division of Infectious Diseases and International Health, Department of Medicine, Duke University School of Medicine, Durham, USA.
Emanuel P Rivers7Department of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, USA.
Anja K Jaehne7Department of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, USA.
Eugenia B Quackenbush8Department of Emergency Medicine, University of North Carolina Health Care, Chapel Hill, USA.
Vance G Fowler4Division of Infectious Diseases and International Health, Department of Medicine, Duke University School of Medicine, Durham, USA.
Ephraim L Tsalik4Division of Infectious Diseases and International Health, Department of Medicine, Duke University School of Medicine, Durham, USA.
Danielle Clark1Biological Defense Research Directorate, Naval Medical Research Center, 503 Robert Grant Avenue, Silver Spring, MD 20910 USA.
Naval Medical Research Command · USDuke University · USWayne State University · USChildren’s Institute · USUniversity of North Carolina at Chapel Hill · USUniversity of South Alabama · US

Funding

ZUNI HEALTH INITIATIVE-PILOT STUDYP20RR016480 · NCRR · NEW MEXICO STATE UNIVERSITY LAS CRUCES · PI ZHANG, PENG F · 2001 to 2011
$33.7M
Plasma Protein Biomarker-Based Diagnostics Of Outcome In Sepsis and CAPU01AI066569 · NIAID · NATIONAL CENTER FOR GENOME RESOURCES · PI KINGSMORE, STEPHEN FRANCIS · 2005 to 2010
$2.9M
Data commons for 'omic, microscopy and analysis core facilitiesS10OD018164 · OD · DUKE UNIVERSITY · PI WRAY, GREGORY A. · 2014 to 2014
$598k
NCRR NIH HHS P20 RR016480NIAID NIH HHS U01 AI066569NIH HHS S10 OD018164
6 · The paper itself

Abstract

backgroundSepsis biomarker panels that provide diagnostic and prognostic discrimination in sepsis patients would be transformative to patient care. We assessed the mortality prediction and diagnostic discriminatory accuracy of two biomarkers reflective of cell death (apoptosis), circulating cell-free DNA (cfDNA), and nucleosomes.

methodsThe cfDNA and nucleosome levels were assayed in plasma samples acquired in patients admitted from four emergency departments with suspected sepsis. Subjects with non-infectious systemic inflammatory response syndrome (SIRS) served as controls. Samples were acquired at enrollment (T0) and 24 h later (T24). We assessed diagnostic (differentiating SIRS from sepsis) and prognostic (28-day mortality) predictive power. Models incorporating procalcitonin (diagnostic prediction) and APACHE II scores (mortality prediction) were generated.

resultsTwo hundred three subjects were included (107 provided procalcitonin measurements). Four subjects exhibited uncomplicated sepsis, 127 severe sepsis, 35 septic shock, and 24 had non-infectious SIRS. There were 190-survivors and 13 non-survivors. Mortality prediction models using cfDNA, nucleosomes, or APACHEII yielded AUC values of 0.61, 0.75, and 0.81, respectively. A model combining nucleosomes with the APACHE II score improved the AUC to 0.84. Diagnostic models distinguishing sepsis from SIRS using procalcitonin, cfDNA(T0), or nucleosomes(T0) yielded AUC values of 0.64, 0.65, and 0.63, respectively. The three parameter model yielded an AUC of 0.74.

conclusionsTo our knowledge, this is the first head-to-head comparison of cfDNA and nucleosomes in diagnosing sepsis and predicting sepsis-related mortality. Both cfDNA and nucleosome concentrations demonstrated a modest ability to distinguish sepsis survivors and non-survivors and provided additive diagnostic predictive accuracy in differentiating sepsis from non-infectious SIRS when integrated into a diagnostic prediction model including PCT and APACHE II. A sepsis biomarker strategy incorporating measures of the apoptotic pathway may serve as an important component of a sepsis diagnostic and mortality prediction tool.

Indexed as

Cell-free DNANucleosomesProcalcitoninSepsis diagnosisSepsis prognosticationSevere Sepsis

Identifiers

PMID30459950
PMCPMC6234551
OpenAlexW2901398437

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.