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PLoS One. 2016 Dec 22;11(12):e0168076. doi: 10.1371/journal.pone.0168076. eCollection 2016.

The TRIAGE-ProADM Score for an Early Risk Stratification of Medical Patients in the Emergency Department - Development Based on a Multi-National, Prospective, Observational Study.

Author information

1
Division of General and Emergency Medicine; University Department of Medicine, Kantonsspital Aarau, Aarau, Switzerland.
2
Emergency Department, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris (APHP), Paris, France.
3
Sorbonne Universités UPMC-Univ Paris06, UMRS INSERM 1166, IHUC ICAN, Paris, France.
4
Morton Plant Hospital, Clearwater, FL, United States of America.
5
Biochemistry Department, Hôpital Pitié-Salpêtrière and Univ-Paris Descartes, Paris, France.
6
Department of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland.

Abstract

INTRODUCTION:

The inflammatory biomarker pro-adrenomedullin (ProADM) provides additional prognostic information for the risk stratification of general medical emergency department (ED) patients. The aim of this analysis was to develop a triage algorithm for improved prognostication and later use in an interventional trial.

METHODS:

We used data from the multi-national, prospective, observational TRIAGE trial including consecutive medical ED patients from Switzerland, France and the United States. We investigated triage effects when adding ProADM at two established cut-offs to a five-level ED triage score with respect to adverse clinical outcome.

RESULTS:

Mortality in the 6586 ED patients showed a step-wise, 25-fold increase from 0.6% to 4.5% and 15.4%, respectively, at the two ProADM cut-offs (≤0.75nmol/L, >0.75-1.5nmol/L, >1.5nmol/L, p ANOVA <0.0001). Risk stratification by combining ProADM within cut-off groups and the triage score resulted in the identification of 1662 patients (25.2% of the population) at a very low risk of mortality (0.3%, n = 5) and 425 patients (6.5% of the population) at very high risk of mortality (19.3%, n = 82). Risk estimation by using ProADM and the triage score from a logistic regression model allowed for a more accurate risk estimation in the whole population with a classification of 3255 patients (49.4% of the population) in the low risk group (0.3% mortality, n = 9) and 1673 (25.4% of the population) in the high-risk group (15.1% mortality, n = 252).

CONCLUSIONS:

Within this large international multicenter study, a combined triage score based on ProADM and established triage scores allowed a more accurate mortality risk discrimination. The TRIAGE-ProADM score improved identification of both patients at the highest risk of mortality who may benefit from early therapeutic interventions (rule in), and low risk patients where deferred treatment without negatively affecting outcome may be possible (rule out).

PMID:
28005916
PMCID:
PMC5179054
DOI:
10.1371/journal.pone.0168076
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: AK, BM, and PS received support from B·R·A·H·M·S AG (now Thermo Fisher Scientific Biomarkers) to attend meetings and fulfill speaking engagements. BM and PS received support from bioMérieux to attend meetings and fulfill speaking engagements and received research grants from both firms, and BM has served as a consultant to both companies. PH received research grants and support from ThermoFisher Scientific BRAHMS to attend meetings and fulfill speaking engagements. All other authors have no conflicts of interest relevant to this paper. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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