As the Surviving Sepsis Campaign was assessing patient-level data over multiple countries, we sought to evaluate the use of a pragmatic and parsimonious severity-of-illness scoring system for patients with sepsis in an attempt to provide appropriate comparisons with practical application.
Prospective, observational evaluation.
Data from 23,438 patients with suspected or confirmed sepsis from 218 hospitals in 18 countries were evaluated.
This analysis was conducted on prospective data submitted to a database from January 2005 through March 2010.
Maximum likelihood logistic regression was used to estimate model coefficients, and these were then used to develop a Sepsis Severity Score. The probability of hospital mortality was estimated using the Sepsis Severity Score as the sole variable in a logistic regression model. Univariable logistic regression determined which variables were included in the multivariable predictor model. The scale of continuous variables was assessed using fractional polynomials. Two-way interactions between variables were considered for model inclusion if the interaction p value is less than 0.05. The prediction model was developed based on randomly selecting 90% of available patients and was validated on the remaining 10%, as well as by using a bootstrapping technique. The p values for the Hosmer-Lemeshow goodnessof-fit statistic in the developmental and validation datasets were considerably greater than 0.05, suggesting good calibration. Development and validation areas under the receiver operator curve curves were 0.736 and 0.748, respectively. Observed and estimated probabilities of hospital mortality for the total population were both 0.334. The validation and the developmental datasets were gradually compared over deciles of predicted mortality and found to be very similar.
The Sepsis Severity Score accurately estimated the probability of hospital mortality in severe sepsis and septic shock patients. It performed well with respect to calibration and discrimination, which remained consistent over deciles. It functioned well over international geographic regions. This robust, population-specific evaluation of international severe sepsis patients provides an effective and accurate mortality estimate allowing for appropriate quality comparisons with practical clinical and research application.
1Division 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.
* See also p. 2126.
Dr. Osborn and Mr. Phillips contributed equally to this work.
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Dr. Osborn received grant support from the Gordon and Betty Moore Foundation, Philips Medical Systems, Baxter Lifesciences, Eli Lilly, Society of Critical Care Medicine (SCCM), and the European Society of Intensive Care Medicine; consulted for the Institute of Healthcare Improvement; received support for travel from the American College of Emergency Physicians; and received support for article research from the Moore Foundation. Mr. Phillips received support for participation in review activities from Rhode Island Hospital, a Lifespan Partner. His institution received grant support from National Institutes of Health and the Murdoch Children’s Research Institution. Dr. Towsend received support for article research from the Gordon and Betty Moore Foundation. Ms. Schorr consulted for SCCM (Honoraria for Webinars). Dr. Levy’s institution received grant support from Asahi KASEI (Ocean State Clinical Coordinating Center). The remaining authors have disclosed that they do not have any potential conflicts of interest.
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