Trial reportBMC geriatrics2019
Risk assessment models for potential use in the emergency department have lower predictive ability in older patients compared to the middle-aged for short-term mortality - a retrospective cohort study.
Trial report in BMC geriatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
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Who cites it
10 citing papers in PubMed.
- Physiological scoring systems for early identification of critically ill older adults in the emergency department: a prospective observational cohort study.BMC emergency medicine · 2025Observational
- SEPSIGN: early identification of sepsis signs in emergency department.Internal and emergency medicine · 2025Observational
- New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding.Scientific reports · 2025Article
- Article
- Prevalence and clinical significance of point of care elevated lactate at emergency admission in older patients: a prospective study.Internal and emergency medicine · 2022Article
- Circulating suPAR associates with severity and in-hospital progression of COVID-19.European journal of clinical investigation · 2022Observational
- Soluble urokinase plasminogen activator receptor (suPAR) in the emergency department: An update.Caspian journal of internal medicine · 2022Article
- Pre-hospital suPAR, lactate and CRP measurements for decision-making: a prospective, observational study of patients presenting non-specific complaints.Scandinavian journal of trauma, resuscitation and emergency medicine · 2021Observational
- Soluble Urokinase Plasminogen Activator Receptor: A Biomarker for Predicting Complications and Critical Care Admission of COVID-19 Patients.Molecular diagnosis & therapy · 2020Article
- Soluble urokinase plasminogen activator receptor level in individuals of advanced age.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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