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A multibiomarker-based outcome risk stratification model for adult septic shock*
Hector R Wong1, Christopher J Lindsell, Ville Pettilä
11Division 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.
A new multibiomarker approach accurately predicts mortality risk in adults with septic shock. This tool aids clinical trials by improving risk stratification and patient selection for better outcomes.
Area of Science:
- Critical Care Medicine
- Biomarker Discovery
- Translational Research
Background:
- Clinical trials for septic shock frequently fail due to imbalanced baseline mortality risk.
- Effective risk stratification is crucial for the success of interventional trials in septic shock.
- Previous research identified 12 candidate plasma proteins for risk stratification.
Purpose of the Study:
- To derive and validate a multibiomarker-based approach for estimating mortality risk in adults with septic shock.
- To develop a decision tree model incorporating biomarkers and clinical variables for predicting 28-day mortality.
- To improve the reliability of risk stratification in septic shock patient populations.
Main Methods:
- Plasma samples from 341 adults with septic shock were analyzed for 12 candidate biomarkers.
- Classification and regression tree analysis was used to create a predictive decision tree.
- The model was tested in an independent cohort (n=331), calibrated (n=672), and validated (n=209).
Main Results:
- The derived decision tree included five biomarkers, lactate, age, and chronic disease burden.
- In the derivation cohort, mortality sensitivity was 94% and negative predictive value was 95%.
- The validated model demonstrated 85% sensitivity and 85% negative predictive value for mortality in the validation cohort.
Conclusions:
- A multibiomarker and clinical variable-based risk stratification tool has been successfully developed and validated.
- This tool reliably estimates the probability of mortality in adult patients with septic shock.
- The validated tool can enhance the design and execution of future clinical trials in septic shock.
