Abstract

BackgroundOlder patients is a complex group at increased risk of adverse outcomes compared to younger patients, which should be considered in the risk assessment performed in emergency departments. We evaluated whether the predictive ability of different risk assessment models for acutely admitted patients is affected by age.MethodsCohort study of middle-aged and older patients. We investigated the accuracy in discriminating between survivors and non-survivors within 7 days of different risk assessment models; a traditional triage algorithm, a triage algorithm with clinical assessment, vital signs, routine biomarkers, and the prognostic biomarker soluble urokinase plasminogen activator receptor (suPAR).ResultsThe cohort included 22,653 (53.2%) middle-aged patients (age 40–69 years), and 19,889 (46.8%) older patients (aged 70+ years). Death within 7 days occurred in 139 patients (0.6%) in middle-aged patients and 596 (3.0%) of the older patients. The models based on vital signs and routine biomarkers had the highest area under the curve (AUC), and both were significantly better at discriminating 7-day mortality in middle-aged patients compared to older patients; AUC (95% CI): 0.88 (0.84–0.91), 0.75 (0.72–0.78), P < 0.01, and 0.86 (0.82–0.90), 0.76 (0.73–0.78), P < 0.001. In a subgroup of the total cohort (6.400 patients, 15.0%), the suPAR level was available. suPAR had the highest AUC of all individual predictors with no significant difference between the age groups, but further research in this biomarker is required before it can be used.ConclusionThe predictive value was lower in older patients compared to middle-aged patients for all investigated models. Vital signs or routine biomarkers constituted the best models for predicting 7-day mortality and were better than the traditional triage model. Hence, the current risk assessment for short-term mortality can be strengthened, but modifications for age should be considered when constructing new risk assessment models in the emergency department.

Highlights

  • Older patients is a complex group at increased risk of adverse outcomes compared to younger patients, which should be considered in the risk assessment performed in emergency departments

  • Vital signs or routine biomarkers constituted the best models for predicting 7-day mortality and were better than the traditional triage model

  • In this study of 42,452 acutely presenting patients, we found that risk assessment models based on vital signs and routine biomarkers, had the best predictive abilities compared to the other risk assessment models tested; both models were significantly better at discriminating on short-term mortality in middle-aged patients compared to older patients

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Summary

Introduction

Older patients is a complex group at increased risk of adverse outcomes compared to younger patients, which should be considered in the risk assessment performed in emergency departments. EDs commonly employ triage algorithms to assess risk and prioritise according to the perceived urgency of patients’ conditions. These algorithms typically consist of a combination of vital signs and primary complaints for risk assessment [3]. Age-related changes in physiology may result in reduced variability and decreased response to stress [10], rendering vital signs less useful for assessment of urgency and severity of acute illness in the older [10, 11]. None of the currently used triage algorithms stratifies patients according to age [12]

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