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A Data-Driven Approach to Quantifying Immune States in Sepsis
Published on: February 7, 2025
Sepsis severity score: an internationally derived scoring system from the surviving sepsis campaign database*
Tiffany M Osborn1, Gary Phillips, Stanley Lemeshow
11Division of Acute and Critical Care Surgery, Department of Emergency Medicine and Department of Surgery, Barnes Jewish Hospital/Washington University, St. Louis, MO. 2The Ohio State University Center for Biostatistics, Columbus, OH. 3The Ohio State University College of Public Health, Columbus, OH. 4Division of Pulmonary & Critical Care, Department of Medicine, California Pacific Medical Center, San Francisco, CA. 5Division of Critical Care Medicine, Department of Medicine, Cooper University Hospital, Camden, NJ. 6Division of Pulmonary/Critical Care Medicine, Brown University/Rhode Island Hospital, Providence, RI.
A new Sepsis Severity Score accurately predicts hospital mortality in severe sepsis and septic shock patients. This validated tool offers reliable comparisons for clinical quality and research applications globally.
Area of Science:
- Critical Care Medicine
- Epidemiology
- Health Services Research
Background:
- The Surviving Sepsis Campaign requires robust patient-level data for international comparisons.
- Existing severity-of-illness scoring systems may lack the pragmatism and parsimony needed for widespread clinical application.
- Accurate mortality prediction is crucial for quality assessment in sepsis management.
Purpose of the Study:
- To evaluate a pragmatic and parsimonious severity-of-illness scoring system for patients with sepsis.
- To develop and validate a Sepsis Severity Score for accurate hospital mortality prediction.
- To enable appropriate quality comparisons using practical clinical and research applications.
Main Methods:
- Prospective, observational evaluation of data from 23,438 patients with suspected or confirmed sepsis across 218 hospitals in 18 countries (January 2005–March 2010).
- Development of the Sepsis Severity Score using maximum likelihood logistic regression, with model coefficients estimated.
- Model validation using a randomly selected 90% of patients for development and the remaining 10% for validation, supplemented by bootstrapping techniques.
Main Results:
- The Sepsis Severity Score demonstrated good calibration (Hosmer-Lemeshow p > 0.05) and discrimination (Area Under the Curve 0.736 development, 0.748 validation).
- Observed and estimated hospital mortality probabilities were both 0.334 for the total population.
- The score performed consistently across deciles of predicted mortality and international geographic regions.
Conclusions:
- The Sepsis Severity Score accurately estimates hospital mortality in severe sepsis and septic shock.
- The score exhibits robust calibration and discrimination, consistent across patient subgroups and international settings.
- This validated tool provides a practical and effective means for quality comparisons in sepsis research and clinical practice.
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