Table 1.
Patient characteristics.
Fig 1.
Definition of ProADM cut-off values for 30-day mortality prediction.
p (goodness of fit) = 0.494; ProADM, pro-adrenomedullin.
Table 2.
30-day mortality according to predefined ProADM categories.
Table 3.
Mortality risk prediction according to predefined ProADM categories.
Fig 2.
Observed risk assessment combining initial emergency department triage score information and ProADM cut-off values.
ProADM, pro-adrenomedullin.
Fig 3.
Derivation of a biomarker based algorithm combining the triage score and ProADM to more efficiently triage patients at risk for 30-day mortality.
(A) Triage score based risk stratification, (B) ProADM based risk stratification, (C) Combined model. ProADM, pro-adrenomedullin.
Fig 4.
Effect of reclassification on overall identification rate of non-survivors 30 days after emergency department admission.
This figure shows mortality in patients classified as “low risk”, “moderate risk” and “high risk” based on the triage score only (left panel), the ProADM cut-offs only (second from left panel), and the triage/ProADM cut-offs combination (second from right panel). Use of the triage score only, identified 147/315 (46.7%) non-survivors in the group of patients classified as “high risk”. The combined model however identified 214/315 (67.9%) non-survivors which corresponds to a relative risk increase of 45.6% with the addition of ProADM. Similarly, the number of non-survivors in the low risk “not urgent” population was reduced from 2.3% in the triage score classification to 1.1% in the combined model, resulting in an improvement of 53.5%. ProADM, pro-adrenomedullin.
Table 4.
30-day mortality risk reclassification stratified by survival status.