Dataset Information

Routine blood tests are associated with short term mortality and can improve emergency department triage: a cohort study of >12,000 patients.

ABSTRACT: Prioritization of acutely ill patients in the Emergency Department remains a challenge. We aimed to evaluate whether routine blood tests can predict mortality in unselected patients in an emergency department and to compare risk prediction with a formalized triage algorithm.A prospective observational cohort study of 12,661 consecutive admissions to the Emergency Department of Nordsjælland University Hospital during two separate periods in 2010 (primary cohort, n?=?6279) and 2013 (validation cohort, n?=?6383). Patients were triaged in five categories by a formalized triage algorithm. All patients with a full routine biochemical screening (albumin, creatinine, c-reactive protein, haemoglobin, lactate dehydrogenase, leukocyte count, potassium, and sodium) taken at triage were included. Information about vital status was collected from the Danish Central Office of Civil registration. Multiple logistic regressions were used to predict 30-day mortality. Validation was performed by applying the regression models on the 2013 validation cohort.Thirty-day mortality was 5.3%. The routine blood tests had a significantly stronger discriminative value on 30-day mortality compared to the formalized triage (AUC 88.1 [85.7;90.5] vs. 63.4 [59.1;67.5], p?

SUBMITTER: Kristensen M

PROVIDER: S-EPMC5704435 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Routine blood tests are associated with short term mortality and can improve emergency department triage: a cohort study of >12,000 patients.

Kristensen Michael M Iversen Anne Kristine Servais AKS Gerds Thomas Alexander TA Østervig Rebecca R Linnet Jakob Danker JD Barfod Charlotte C Lange Kai Henrik Wiborg KHW Sölétormos György G Forberg Jakob Lundager JL Eugen-Olsen Jesper J Rasmussen Lars Simon LS Schou Morten M Køber Lars L Iversen Kasper K

Scandinavian journal of trauma, resuscitation and emergency medicine 20171128 1

<h4>Background</h4>Prioritization of acutely ill patients in the Emergency Department remains a challenge. We aimed to evaluate whether routine blood tests can predict mortality in unselected patients in an emergency department and to compare risk prediction with a formalized triage algorithm.<h4>Methods</h4>A prospective observational cohort study of 12,661 consecutive admissions to the Emergency Department of Nordsjælland University Hospital during two separate periods in 2010 (primary cohort, ...[more]

PMID: 29179764

Similar Datasets

Project description:BackgroundUrgency triage in the emergency department (ED) is important for early identification of potentially lethal conditions and extensive resource utilization. However, in older patients, urgency triage systems could be improved by taking geriatric vulnerability into account. We investigated the association of geriatric vulnerability screening in addition to triage urgency levels with 30-day mortality in older ED patients.DesignSecondary analysis of the observational multicenter Acutely Presenting Older Patient (APOP) study.SettingEDs within four Dutch hospitals.ParticipantsConsecutive patients, aged 70 years or older, who were prospectively included.MeasurementsPatients were triaged using the Manchester Triage System (MTS). In addition, the APOP screener was used as a geriatric screening tool. The primary outcome was 30-day mortality. Comparison was made between mortality within the geriatric high- and low-risk screened patients in every urgency triage category. We calculated the difference in explained variance of mortality by adding the geriatric screener (APOP) to triage urgency (MTS) by calculating Nagelkerke R2 .ResultsWe included 2,608 patients with a median age of 79 (interquartile range = 74-84) years, of whom 521 (20.0%) patients were categorized as high risk according to geriatric screening. Patients were triaged on urgency as standard (27.2%), urgent (58.5%), and very urgent (14.3%). In total, 132 (5.1%) patients were deceased within a period of 30 days. Within every urgency triage category, 30-day mortality was threefold higher in geriatric high-risk compared to low-risk patients (overall = 11.7% vs 3.4%; P < .001). The explained variance of 30-day mortality with triage urgency was 1.0% and increased to 6.3% by adding the geriatric screener.ConclusionCombining triage urgency with geriatric screening has the potential to improve triage, which may help clinicians to deliver early appropriate care to older ED patients. J Am Geriatr Soc 68:1755-1762, 2020.

Project description:Preventing death is the most important outcome pursued in the Emergency Department. Prompt accurate assessment, followed by competent and efficient investigation and treatment is the recipe sought. Abnormal physiological measurements are common antecedents to deterioration and therefore a cornerstone in many risk stratification tools. Some risk factors have their impact during the first few days after admittance, others have higher impact on 30 day mortality. Understanding the variance in impact of risk factors is relevant for future composition of risk stratification models.We included patients aged 18 years or older, registered at the Emergency Department at Odense University Hospital from April 1st 2012 to September 30th 2014. We performed multivariate logistic regressions, adjusted for age, gender and comorbidity, to describe the relationship between potential risk factors and measures of short term mortality.A total of 43,178 were eligible for analysis. Median age was 56 (IQR 36-72) and 48.3% were males. The over-all 30-day-mortality was 4%. One third of deaths occurred within the first 2 days. Higher age, male gender and comorbidity are all associated with immediate, 0-2 day, 3-7 day and 8-30 day mortality. The degree of acuteness at arrival defined by urgency-level, physician-assisted transfer to the Emergency Department and abnormal vital parameters are associated with 0-2 day mortality. High temperature at arrival shows no association in either mortality-group. Missing values are associated with immediate and 0-2 day mortality, but no association with mortality after 7 days.Abnormal vital parameters and degree of acuity at admission were strongly associated with mortality in the first hours and days after admission, where after the association decreased. The effect of other risk factors such as male gender, comorbidity and high age were time stable or even increasing over time..The over-all 30-day mortality was 4%. Physiology-related risk factors varied in strength of association throughout different mortality outcome measures.

Project description:BackgroundEmergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcomes. Triage scores aim to optimize the waiting time and prioritize the resource usage. Artificial intelligence (AI) algorithms offer advantages for creating predictive clinical applications.ObjectiveEvaluate a state-of-the-art machine learning model for predicting mortality at the triage level and, by validating this automatic tool, improve the categorization of patients in the ED.DesignAn institutional review board (IRB) approval was granted for this retrospective study. Information of consecutive adult patients (ages 18-100) admitted at the emergency department (ED) of one hospital were retrieved (January 1, 2012-December 31, 2018). Features included the following: demographics, admission date, arrival mode, referral code, chief complaint, previous ED visits, previous hospitalizations, comorbidities, home medications, vital signs, and Emergency Severity Index (ESI). The following outcomes were evaluated: early mortality (up to 2 days post ED registration) and short-term mortality (2-30 days post ED registration). A gradient boosting model was trained on data from years 2012-2017 and examined on data from the final year (2018). The area under the curve (AUC) for mortality prediction was used as an outcome metric. Single-variable analysis was conducted to develop a nine-point triage score for early mortality.Key resultsOverall, 799,522 ED visits were available for analysis. The early and short-term mortality rates were 0.6% and 2.5%, respectively. Models trained on the full set of features yielded an AUC of 0.962 for early mortality and 0.923 for short-term mortality. A model that utilized the nine features with the highest single-variable AUC scores (age, arrival mode, chief complaint, five primary vital signs, and ESI) yielded an AUC of 0.962 for early mortality.ConclusionThe gradient boosting model shows high predictive ability for screening patients at risk of early mortality utilizing data available at the time of triage in the ED.

Dataset Information

Routine blood tests are associated with short term mortality and can improve emergency department triage: a cohort study of >12,000 patients.

Publications

Routine blood tests are associated with short term mortality and can improve emergency department triage: a cohort study of >12,000 patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets