Send to

Choose Destination
See comment in PubMed Commons below
Crit Care Med. 2014 Apr;42(4):781-9. doi: 10.1097/CCM.0000000000000106.

A multibiomarker-based outcome risk stratification model for adult septic shock*.

Author information

1Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Hospital Research Foundation, Cincinnati, OH. 2Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH. 3Department of Emergency Medicine, University of Cincinnati College of Medicine, Cincinnati, OH. 4Intensive Care Units, Division of Anaesthesia and Intensive Care Medicine, Department of Surgery, Helsinki University Central Hospital, Helsinki, Finland. 5Pulmonary, Allergy, and Critical Care Division, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 6University of British Columbia, Vancouver, BC, Canada. 7Critical Care Research Laboratories, Centre for Heart Lung Innovation, St. Paul's Hospital, Vancouver, BC, Canada. 8Department of Intensive Care Medicine, Tampere University Hospital, Tampere, Finland. 9Department of Intensive Care Medicine, Kuopio University Hospital, Kuopio, Finland. 10Department of Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA.



Clinical trials in septic shock continue to fail due, in part, to inequitable and sometimes unknown distribution of baseline mortality risk between study arms. Investigators advocate that interventional trials in septic shock require effective outcome risk stratification. We derived and tested a multibiomarker-based approach to estimate mortality risk in adults with septic shock.


Previous genome-wide expression studies identified 12 plasma proteins as candidates for biomarker-based risk stratification. The current analysis used banked plasma samples and clinical data from existing studies. Biomarkers were assayed in plasma samples obtained from 341 subjects with septic shock within 24 hours of admission to the ICU. Classification and regression tree analysis was used to generate a decision tree predicting 28-day mortality based on a combination of both biomarkers and clinical variables. The derived tree was first tested in an independent cohort of 331 subjects, then calibrated using all subjects (n = 672), and subsequently validated in another independent cohort (n = 209).


Multiple ICUs in Canada, Finland, and the United States.


Eight hundred eighty-one adults with septic shock or severe sepsis.




The derived decision tree included five candidate biomarkers, admission lactate concentration, age, and chronic disease burden. In the derivation cohort, sensitivity for mortality was 94% (95% CI, 87-97), specificity was 56% (50-63), positive predictive value was 50% (43-57), and negative predictive value was 95% (89-98). Performance was comparable in the test cohort. The calibrated decision tree had the following test characteristics in the validation cohort: sensitivity 85% (76-92), specificity 60% (51-69), positive predictive value 61% (52-70), and negative predictive value 85% (75-91).


We have derived, tested, calibrated, and validated a risk stratification tool and found that it reliably estimates the probability of mortality in adults with septic shock.

[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Lippincott Williams & Wilkins Icon for PubMed Central
    Loading ...
    Support Center