Research
Model for predicting short-term mortality of severe sepsis
-
* Corresponding author: Jean-Francois Timsit jf.timsit@outcomerea.org
1 Medical-Surgical Intensive Care Unit, Delafontaine Hospital, 2 rue du Dr Lamaze, 93205 Saint Denis, France
2 Department of Physiology, Cochin Hospital, Paris Descartes University, Assistance Publique des Hôpitaux de Paris, 27 rue du Faubourg Saint Jacques, 75014 Paris, France
3 INSERM U823, Epidemiology of Cancer and Severe Illnesses, Albert Bonniot Institute, BP 217, 38043 Grenoble, France
4 Medical Intensive Care Unit, Hôpital Louis Mourier, 178, rue des Renouillers, 92701 Colombes, France
5 Medical Intensive Care Unit, Saint Louis Teaching Hospital, 1 rue Claude Vellefaux, 75011 Paris, France
6 Department of Microbiology, Necker Teaching Hospital, 149, rue de Sèvres, 75743 Paris Cedex 15, France
7 Medical-Surgical Intensive Care Unit, Avicenne Teaching Hospital, 125, rue de Stalingrad, 93009 Bobigny Cedex, France
8 Medical-Surgical Intensive Care Unit, Gonesse Hospital, 25 rue Pierre de Theilley, BP 30071, 95503 Gonesse, France
9 Medical Intensive Care Unit, Albert Michallon Teaching Hospital, Joseph Fournier University, BP 217, 38043 Grenoble cedex 09, France
10 Surgical Intensive Care Unit, Antoine Béclère Teaching Hospital, 157, rue de la Porte de Trivaux, 92141 Clamart Cedex, France
11 Medical-Surgical Intensive Care Unit, Dourdan Hospital, 2, rue du Potelet B.P. 102, 91415 Dourdan Cedex, France
Critical Care 2009, 13:R72 doi:10.1186/cc7881
Published: 19 May 2009Abstract
Introduction
To establish a prognostic model for predicting 14-day mortality in ICU patients with severe sepsis overall and according to place of infection acquisition and to sepsis episode number.
Methods
In this prospective multicentre observational study on a multicentre database (OUTCOMEREA) including data from 12 ICUs, 2268 patients with 2737 episodes of severe sepsis were randomly divided into a training cohort (n = 1458) and a validation cohort (n = 810). Up to four consecutive severe sepsis episodes per patient occurring within the first 28 ICU days were included. We developed a prognostic model for predicting death within 14 days after each episode, based on patient data available at sepsis onset.
Results
Independent predictors of death were logistic organ dysfunction (odds ratio (OR), 1.22 per point, P < 10-4), septic shock (OR, 1.40; P = 0.01), rank of severe sepsis episode (1 reference, 2: OR, 1.26; P = 0.10 ≥ 3: OR, 2.64; P < 10-3), multiple sources of infection (OR; 1.45, P = 0.03), simplified acute physiology score II (OR, 1.02 per point; P < 10-4), McCabe score ([greater than or equal to]2) (OR, 1.96; P < 10-4), and number of chronic co-morbidities (1: OR, 1.75; P < 10-3, ≥ 2: OR, 2.24, P < 10-3). Validity of the model was good in whole cohorts (AUC-ROC, 0.76; 95%CI, 0.74 to 0.79; and HL Chi-square: 15.3 (P = 0.06) for all episodes pooled).
Conclusions
In ICU patients, a prognostic model based on a few easily obtained variables is effective in predicting death within 14 days after the first to fourth episode of severe sepsis complicating community-, hospital-, or ICU-acquired infection.