The formation and design of the TRIAGE study - baseline data on 6005 consecutive patients admitted to hospital from the emergency department

Abstract

BackgroundPatient crowding in emergency departments (ED) is a common challenge and associated with worsened outcome for the patients. Previous studies on biomarkers in the ED setting has focused on identification of high risk patients, and and the ability to use biomarkers to identify low-risk patients has only been sparsely examined. The broader aims of the TRIAGE study are to develop methods to identify low-risk patients appropriate for early ED discharge by combining information from a wide range of new inflammatory biomarkers and vital signs, the present baseline article aims to describe the formation of the TRIAGE database and characteristize the included patients.MethodsWe included consecutive patients ≥ 17 years admitted to hospital after triage staging in the ED. Blood samples for a biobank were collected and plasma stored in a freezer (−80 °C). Triage was done by a trained nurse using the Danish Emergency Proces Triage (DEPT) which categorizes patients as green (not urgent), yellow (urgent), orange (emergent) or red (rescusitation). Presenting complaints, admission diagnoses, comorbidities, length of stay, and ‘events’ during admission (any of 20 predefined definitive treatments that necessitates in-hospital care), vital signs and routine laboratory tests taken in the ED were aslo included in the database.ResultsBetween September 5th 2013 and December 6th 2013, 6005 patients were included in the database and the biobank (94.1 % of all admissions). Of these, 1978 (32.9 %) were categorized as green, 2386 (39.7 %) yellow, 1616 (26.9 %) orange and 25 (0.4 %) red. Median age was 62 years (IQR 46–76), 49.8 % were male and median length of stay was 1 day (IQR 0–4). No events were found in 2658 (44.2 %) and 158 (2.6 %) were admitted to intensive or intermediate-intensive care unit and 219 (3.6 %) died within 30 days. A higher triage acuity level was associated with numerous events, including acute surgery, endovascular intervention, i.v. treatment, cardiac arrest, stroke, admission to intensive care, hospital transfer, and mortality within 30 days (p < 0.001).ConclusionThe TRIAGE database has been completed and includes data and blood samples from 6005 unselected consecutive hospitalized patients. More than 40 % experienced no events and were therefore potentially unnecessary hospital admissions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13049-015-0184-1) contains supplementary material, which is available to authorized users.

A simple clinical assessment is superior to systematic triage in prediction of mortality in the emergency department

“…However, one study by Barfod et al 12 16 investigated the relationship between the first Danish modified ADAPT model and in-hospital mortality in a comparable unselected ED patient group. The study had a similar distribution of patients to ADAPT categories as ours to DEPT categories, but with fewer patients in the orange triage group and more patients in the red triage group 9. The study found an overall 28-day mortality which was equal to the overall 30-day mortality found in our cohort.…”

“…All data derive from the ‘Triage study’, which is a prospective observational cohort study previously described in detail elsewhere 9. The aim of the study was to optimise risk stratification and develop methods to identify low-risk patients appropriate for early ED discharge.…”

Recommandations pour le fonctionnement des unités de surveillance continue dans les établissements de santé

“…La deuxième filière concerne des patients admis par les urgences ou à partir d'un secteur d'hospitalisation conventionnelle consécutivement à la survenue d'une complication. On estime que 3 % des patients admis aux urgences sont orientés vers les soins critiques, unités de surveillance continue (USC) ou réanimation [21]. L'enjeu est ici de dépister précocement les signes de gravité de ces patients afin de les affecter dans la structure qui leur est adaptée.…”

The Copenhagen Triage Algorithm: a randomized controlled trial

“…The cut-off points for vital signs (Fig. 1 ) of CTA were calculated using the results of the TRIAGE database [ 24 ]. This was done by defining either the 10 % highest (e.g.…”

“…Recently, data from ED visits have been collected over a period of 3 months at North Zealand Hospital giving a complete cohort of 6 000 patient ED visits [ 24 ]. This study confirmed earlier studies’ conclusion that vital signs at admission are strong predictors of acute patient outcomes [ 21 ], and further demonstrated that a quick clinical assessment of patients by phlebotomists and medical students was superior in predicting 30-day mortality than formalized DEPT triage [ 25 ].…”