- Poster presentation
- Open Access
- Published:
Effect of including procalcitonin and C-reactive protein in the Mortality in Emergency Department Sepsis risk prediction model
Critical Care volume 15, Article number: P273 (2011)
Introduction
The Mortality in Emergency Department Sepsis (MEDS) score has been gradually accepted as a reliable tool for bedside risk prediction of sepsis patients in the emergency department. Despite its clinical usefulness, the MEDS score did not take advantage of the prognostic information of biomarkers.
Methods
We compared the clinical utility of MEDS score with and without CRP or PCT among participants in a prospective cohort of patients. All adult patients fulfilling the criteria for SIRS with a presumed infectious etiology were eligible for inclusion. Serum PCT and CRP were evaluated at admission. Initial severity was assessed with the MEDS score. Each patient was followed for at least 30 days for the 30-day survival. We built three extended models, including MEDS plus natural log PCT model (MEDS-LnPCT), MEDS plus natural log CRP model (MEDS-LnCRP), and MEDS plus natural log PCT and natural log CRP model (MEDS-LnPCT & LnCRP) for comparison. The values of CRP and PCT were transformed to natural log scale to normalize the distributions. We assessed whether adding CRP, PCT or both biomarkers to the MEDS model significantly reclassified patients into more appropriate risk categories. The reclassification was then evaluated by comparison of the observed incidence of events in the cells of the reclassification table with the predicted probability from the original MEDS model.
Results
The 63 patients who died (10.6%) had significantly increased levels of PCT and CRP. Adjusting for MEDS predictors, either high levels of CRP or PCT was independently associated with 30-day mortality. We fitted PCT-incorporated (MEDS-PCT), CRP-incorporated (MEDS-CRP), and PCT & CRP incorporated (MEDS-PCT & CRP) models for comparison. The MEDS-PCT model was the favored model as it improved model fit and calibration as measured by the Net Reclassification Improvement (NRI) score (14.1%, P = 0.047). MEDS-CRP and MEDS-CRP & PCT models improved model fit (likelihood ratio test P = 0.03, 0.009, respectively) but did not improve calibration (NRI 5.4%, P = 0.204; 13.2%, P = 0.055). All three models did not improve model discrimination as measured by c-statistics.
Conclusions
Adding PCT levels to the MEDS score reclassified patients into groups that better predict actual 30-day mortality. Inclusion of CRP or both biomarkers offers limited additional predictive value. Further validation studies are needed to corroborate these findings.
Author information
Authors and Affiliations
Rights and permissions
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
About this article
Cite this article
Lee, C., Liu, J., Chen, S. et al. Effect of including procalcitonin and C-reactive protein in the Mortality in Emergency Department Sepsis risk prediction model. Crit Care 15 (Suppl 1), P273 (2011). https://doi.org/10.1186/cc9693
Published:
DOI: https://doi.org/10.1186/cc9693
Keywords
- Risk Prediction
- Procalcitonin
- Sepsis Patient
- Risk Prediction Model
- Favored Model