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Unlabelled: Previous research demonstrated that shock index and respiratory rate are highly predictive of intensive care unit admissions., Objective: The objective of the study is to evaluate the integration of the prehospital sepsis project score (PSP-S) and point-of-care lactate in assisting prediction of severity of illness using Bayesian statistical modeling., Methods: The PSP-S incorporates fever (38°C [100.4°F]) allotted with 1 point, shock index greater than or equal to 0.7 given 2 points, and a respiratory rate greater than or equal to 22 breaths per minute given 1 point for a total maximum score of 4 points. The patient population was stratified based on the PSP-S: 1 point is low risk, 2 points is moderate risk, and 3 to 4 points is high risk. Percentage risk was obtained based on intensive care unit admissions and used as pretest probability. Prehospital lactate pooled data were obtained and used to calculate likelihood ratio (LR). Percentage risk used as pretest probability and LRs for prehospital lactate were charted into the Bayesian nomogram to obtain posttest probabilities. Absolute diagnostic gain (ADG) and relative diagnostic gains (RDG) were then calculated., Results: Pooled data for prehospital point of care lactate demonstrated a positive LR of 1.6 and negative LR of 0.44. Posttest probability for low risk was 16% with an ADG of 6% and RDG of 160%. Moderate risk population yielded a posttest probability of 47%, ADG of 12.5%, and RDG of 136.2%. High-risk population resulted in a posttest probability of 72%, ADG of 12%, and RDG of 120%., Conclusion: We found that PSP-S can be clinically complemented with the use of point-of-care lactate., (Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.)

Introduction: Severe sepsis and septic shock are common, expensive and often fatal medical problems. The care of the critically sick and injured often begins in the prehospital setting; there is limited data available related to predictors and interventions specific to sepsis in the prehospital arena. The objective of this study was to assess the predictive effect of physiologic elements commonly reported in the out-of-hospital setting in the outcomes of patients transported with sepsis., Methods: This was a cross-sectional descriptive study. Data from the years 2004-2006 were collected. Adult cases (≥18 years of age) transported by Emergency Medical Services to a major academic center with the diagnosis of sepsis as defined by ICD-9-CM diagnostic codes were included. Descriptive statistics and standard deviations were used to present group characteristics. Chi-square was used for statistical significance and odds ratio (OR) to assess strength of association. Statistical significance was set at the .05 level. Physiologic variables studied included mean arterial pressure (MAP), heart rate (HR), respiratory rate (RR) and shock index (SI)., Results: Sixty-three (63) patients were included. Outcome variables included a mean hospital length of stay (HLOS) of 13.75 days (SD = 9.97), mean ventilator days of 4.93 (SD = 7.87), in-hospital mortality of 22 out of 63 (34.9%), and mean intensive care unit length-of-stay (ICU-LOS) of 7.02 days (SD = 7.98). Although SI and RR were found to predict intensive care unit (ICU) admissions, [OR 5.96 (CI, 1.49-25.78; P = .003) and OR 4.81 (CI, 1.16-21.01; P = .0116), respectively] none of the studied variables were found to predict mortality (MAP <65 mmHg: P = .39; HR >90: P = .60; RR >20 P = .11; SI >0.7 P = .35)., Conclusions: This study demonstrated that the out-of-hospital shock index and respiratory rate have high predictability for ICU admission. Further studies should include the development of an out-of-hospital sepsis score.