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Prospectively validated prediction of physiologic variables and organ failure in septic patients: The Systemic
1Department of Surgery, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School-Camden, Cooper Hospital/University Medical Center, Camden, NJ, USA. slotman@umdnj.edu
Objective:
Conventional outcomes research provides only percentage risk of such end points as mortality rate, utilization of resources, and/or broad groupings of multiple organ system dysfunction. These prognostications generally are not applicable to individual patients. The purpose of the present study was to determine whether the Systemic Mediator Associated Response Test (SMART) methodology could identify interactions among demographics, physiologic variables, standard hospital laboratory tests, and circulating cytokine concentrations that predicted continuous and dichotomous dependent clinical variables, in advance, in individual patients with severe sepsis and septic shock, and whether these independent variables could be integrated into prospectively validated predictive models.
Design:
Data review and multivariate stepwise logistic regression.
Setting:
University research laboratory.
Patients:
Three hundred three patients with severe sepsis or septic shock who comprised the placebo arm of a multiple-institution clinical trial, who were randomly separated into a model building training cohort (n = 200) and a predictive cohort (n = 103).
Interventions:
None.
Measurements And Main Results:
From baseline data and baseline plus serial input, including patient demographics, hospital laboratory tests, and plasma concentrations of interleukin-6, interleukin-8, and granulocyte colony stimulating factor, multiple regression models were developed that predicted clinically important continuous dependent variables quantitatively, in individual patients. Multivariate stepwise logistic regression was used to develop models that prognosticated dichotomous dependent end points. Data from individual patients in the predictive cohort were inserted into each predictive model for each day, with prospective validation accomplished by simple linear regression of individual predicted vs. observed values for continuous dependent variables, and by establishing the receiver operator characteristics area under the curve for logistic regression models that predicted dichotomous end points. Of SMART models for continuous dependent variables, 100 of 143 (70%) were validated at r values >.7 through day 3, and 184 of 259 (71%) above r =.5 through day 5. SMART predictions of dichotomous end points achieved receiver operator characteristics areas under the curve >.7 for up to 84% of the equations in the first week. Many SMART models for both continuous and dichotomous dependent variables were validated at clinically useful levels of accuracy as far as 28 days after baseline.
Conclusions:
SMART integration of demographics, bedside physiology, hospital laboratory tests, and circulating cytokines predicts organ failure and physiologic function indicators in individual patients with severe sepsis and septic shock.