ROC curves for predicting adverse event.

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM prediction model compared to PSI</p

Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.

<p>Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.</p

Multivariate predictive models of adverse event and 90-day mortality.

<p>MaxM: Maximum Model: includes significant independent variables in the univariate analysis with AUC higher than 0.7.</p><p>OR: Odds Ratio and HR: Hazard Ratio.</p><p>CI 95%: confidence interval of 95%.</p><p>p: level of statistical significance.</p><p>AIC: Akaike Information Criterion (better fit of the model when AIC lower).</p><p>McFadden´s and Atkinson R2: proportion of uncertainty data explained by the model.</p><p>Calibration χ2 (p value): Hosmer and Lemeshow test.</p><p>Multivariate predictive models of adverse event and 90-day mortality.</p

MR-proADM and CAP severity.

<p>Fig 2a. Relationship between MR-proADM and severity as established by the PSI. Analysis performed with the Jonckheere-Terpstra trend test. Tau b: Kendall’s rank correlation. p: level of statistical significance. Fig 2b. MR-proADM levels according to hospital admission, bacteremia, ICU admission, hospital readmission and 30-day mortality.</p

Baseline characteristics of the NACURG cohort.

<p>Differences between patients who died and those who survived were assessed by Cox regression survival analysis for independent continuous variables, and a Kaplan-Meyer survival curve with log-rank tests for independent categorical variables. Differences between patients with or without adverse event were assessed by the Student t test or the non-parametric Mann-Whitney U test for continuous variables and the [χ²] test or the Fisher exact test for dichotomous categorical variables.</p><p>*p: degree of statistical significance.</p><p>**Lactate levels only available for 122 patients (54%) and not therefore included in the multivariate analysis.</p><p>***The percentage of readmissions out of the total number of patients discharged (221; 4 patients died while in hospital and 1 was still inpatient at 30 days).</p><p>Relationship between different independent variables and adverse event and 90-day mortality after consulting the Emergency Department.</p

Patients included in the study.

<p>Patients included in the study.</p

ROC curves for predicting 90-day mortality.

<p>Fig 5a. ROC curves for different biomarkers and PSI. Fig 5b. ROC curves for the PSI & MR-proADM prediction model compared to PSI.</p