Model for predicting short-term mortality of severe sepsis

Abstract

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 >or= 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, >or= 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.

Figure 1

Flow diagram of the 2268 patients with severe sepsis who formed the basis for the study and were identified among the 7719 patients included in the Outcomerea^® Database. Data are expressed as counts (number of episodes of severe sepsis (SS)) or percentages. Mortality is defined as death within 14 days after the diagnosis of severe sepsis. community-acquired infection = infection manifesting before or within 48 hours after hospital admission; hospital-acquired infection = infection manifesting at least 48 hours after hospital admission but before ICU admission; ICU = intensive care unit; ICU-acquired infection = infection manifesting at least 48 hours after ICU admission; N = number of patients (number of episode); Sepsis = SIRS with infection; SIRS = systemic inflammatory response syndrome. ✞ Mortality (percentage %).

Figure 2

Receiver-Operating Characteristics (ROC) curves and Hosmer-Lemeshow (HL) chi-squared test results of the prediction model in the training cohort. n = 1458 patients, 1716 episodes, according to the type of severe sepsis (community-, hospital- or ICU-acquired). Dashed curves represent 95% confidence intervals (CI) of the area under the curve (AUC) of the ROC curve.

Figure 3

Receiver-Operating Characteristics (ROC) curves and Hosmer-Lemeshow (HL) chi-square test results of the prediction model in the validation cohort. n = 810, 1021 episodes, according to the day of severe sepsis. Dashed curves represent 95% confidence intervals (CI) of the area under the curve (AUC) of the ROC curve.

Figure 4

Comparison of our prediction model with other, widely used models. The final study model (blue line) used on all episodes of severe sepsis showed good calibration (Hosmer-Lemeshow (HL) chi-squared 15.3, P = 0.06) and good discrimination (area under the curve (AUC)- receiver-operating characteristics (ROC) curve, 0.76). Acute Physiologic and Chronic Health Evaluation (APACHE) II, Mortality Probability models II₀ (MPM0 II) and Simplified Acute Physiology Score (SAPS) II scores were significantly less accurate than our model, with AUCs of 0.73, 0.66 and 0.72, respectively (P value < 10^-4 in all cases), and poor calibration (HL chi-squared P values of 0.03, < 10^-4 and 0.02, respectively).