Background and importance Although aging societies in Western Europe use presenting complaints (PCs) in emergency departments (EDs) triage systems to determine the urgency and severity of the care... Show moreBackground and importance Although aging societies in Western Europe use presenting complaints (PCs) in emergency departments (EDs) triage systems to determine the urgency and severity of the care demand, it is unclear whether their prognostic value is age-dependent.Objective To assess the frequency and association of PCs with hospitalization and mortality across age categories.Methods An observational multicenter study using all consecutive visits of three EDs in the Netherlands Emergency department Evaluation Database. Patients were stratified by age category (0-18; 19-50; 51-65; 66-80; >80 years), in which the association between PCs and case-mix adjusted hospitalization and mortality was studied using multivariable logistic regression analysis (adjusting for demographics, hospital, disease severity, comorbidity and other PCs)Results We included 172 104 ED-visits. The most frequent PCs were 'extremity problems' [range across age categories (13.5-40.8%)], 'feeling unwell' (9.5-23.4%), 'abdominal pain' (6.0-13.9%), 'dyspnea' (4.5-13.3%) and 'chest pain' (0.6-10.7%). For most PCs, the observed and the case-mix-adjusted odds for hospitalization and mortality increased the higher the age category. The most common PCs with the highest adjusted odds ratios (AORs, 95% CI) for hospitalization were 'diarrhea and vomiting' [2.30 (2.02-2.62)] and 'feeling unwell' [1.60 (1.48-1.73)]. Low hospitalization risk was found for 'chest pain' [0.58 (0.53-0.63)] and `palpitations' [0.64 (0.58-0.71)].Conclusions Frequency of PCs in ED patients varies with age, but the same PCs occur in all age categories. For most PCs, (case-mix adjusted) hospitalization and mortality vary across age categories. 'Chest pain' and 'palpitations,' usually triaged 'very urgent', carry a low risk for hospitalization and mortality. European Journal of Emergency Medicine 29: 33-41 Copyright (c) 2021 Wolters Kluwer Health, Inc. All rights reserved. Show less
Candel, B.G.J.; Khoudja, J.; Gaakeer, M.I.; Avest, E. ter; Sir, O.; Lameijer, H.; ... ; Groot, B. de 2022
Appropriate interpretation of blood tests is important for risk stratification and guidelines used in the Emergency Department (ED) (such as SIRS or CURB-65). The impact of abnormal blood test... Show moreAppropriate interpretation of blood tests is important for risk stratification and guidelines used in the Emergency Department (ED) (such as SIRS or CURB-65). The impact of abnormal blood test values on mortality may change with increasing age due to (patho)-physiologic changes. The aim of this study was therefore to assess the effect of age on the case-mix adjusted association between biomarkers of renal function and homeostasis, inflammation and circulation and in-hospital mortality. This observational multi-center cohort study has used the Netherlands Emergency department Evaluation Database (NEED), including all consecutive ED patients >= 18 years of three hospitals. A generalized additive logistic regression model was used to visualize the association between in-hospital mortality, age and five blood tests (creatinine, sodium, leukocytes, C-reactive Protein, and hemoglobin). Multivariable logistic regression analyses were used to assess the association between the number of abnormal blood test values and mortality per age category (18-50; 51-65; 66-80; > 80 years). Of the 94,974 included patients, 2550 (2.7%) patients died in-hospital. Mortality increased gradually for C-reactive Protein (CRP), and had a U-shaped association for creatinine, sodium, leukocytes, and hemoglobin. Age significantly affected the associations of all studied blood tests except in leukocytes. In addition, with increasing age categories, case-mix adjusted mortality increased with the number of abnormal blood tests. In summary, the association between blood tests and (adjusted) mortality depends on age. Mortality increases gradually or in a U-shaped manner with increasing blood test values. Age-adjusted numerical scores may improve risk stratification. Our results have implications for interpretation of blood tests and their use in risk stratification tools and acute care guidelines. Show less
Candel, B.G.J.; Duijzer, R.; Gaakeer, M.I.; Avest, E. ter; Sir, O.; Lameijer, H.; ... ; Groot, B. de 2022
Background Appropriate interpretation of vital signs is essential for risk stratification in the emergency department (ED) but may change with advancing age. In several guidelines, risk scores such... Show moreBackground Appropriate interpretation of vital signs is essential for risk stratification in the emergency department (ED) but may change with advancing age. In several guidelines, risk scores such as the Systemic Inflammatory Response Syndrome (SIRS) and Quick Sequential Organ Failure Assessment (qSOFA) scores, commonly used in emergency medicine practice (as well as critical care) specify a single cut-off or threshold for each of the commonly measured vital signs. Although a single cut-off may be convenient, it is unknown whether a single cut-off for vital signs truly exists and if the association between vital signs and in-hospital mortality differs per age-category. Aims To assess the association between initial vital signs and case-mix adjusted in-hospital mortality in different age categories. Methods Observational multicentre cohort study using the Netherlands Emergency Department Evaluation Database (NEED) in which consecutive ED patients >= 18 years were included between 1 January 2017 and 12 January 2020. The association between vital signs and case-mix adjusted mortality were assessed in three age categories (18-65; 66-80; >80 years) using multivariable logistic regression. Vital signs were each divided into five to six categories, for example, systolic blood pressure (SBP) categories (<= 80, 81-100, 101-120, 121-140, >140 mm Hg). Results We included 101 416 patients of whom 2374 (2.3%) died. Adjusted ORs for mortality increased gradually with decreasing SBP and decreasing peripheral oxygen saturation (SpO(2)). Diastolic blood pressure (DBP), mean arterial pressure (MAP) and heart rate (HR) had quasi-U-shaped associations with mortality. Mortality did not increase for temperatures anywhere in the range between 35.5 degrees C and 42.0 degrees C, with a single cut-off around 35.5 degrees C below which mortality increased. Single cut-offs were also found for MAP 22/min. For all vital signs, older patients had larger increases in absolute mortality compared with younger patients. Conclusion For SBP, DBP, SpO(2) and HR, no single cut-off existed. The impact of changing vital sign categories on prognosis was larger in older patients. Our results have implications for the interpretation of vital signs in existing risk stratification tools and acute care guidelines. Show less
Hond, A. de; Raven, W.; Schinkelshoek, L.; Gaakeer, M.; Avest, E. ter; Sir, O.; ... ; Groot, B. de 2021
Objective: Early identification of emergency department (ED) patients who need hospitalization is essential for quality of care and patient safety. We aimed to compare machine learning (ML) models... Show moreObjective: Early identification of emergency department (ED) patients who need hospitalization is essential for quality of care and patient safety. We aimed to compare machine learning (ML) models predicting the hospitalization of ED patients and conventional regression techniques at three points in time after ED registration.Methods: We analyzed consecutive ED patients of three hospitals using the Netherlands Emergency Department Evaluation Database (NEED). We developed prediction models for hospitalization using an increasing number of data available at triage, similar to 30 min (including vital signs) and similar to 2 h (including laboratory tests) after ED registration, using ML (random forest, gradient boosted decision trees, deep neural networks) and multivariable logistic regression analysis (including spline transformations for continuous predictors). Demographics, urgency, presenting complaints, disease severity and proxies for comorbidity, and complexity were used as covariates. We compared the performance using the area under the ROC curve in independent validation sets from each hospital.Results: We included 172,104 ED patients of whom 66,782 (39 %) were hospitalized. The AUC of the multi-variable logistic regression model was 0.82 (0.78-0.86) at triage, 0.84 (0.81-0.86) at similar to 30 min and 0.83 (0.75-0.92) after similar to 2 h. The best performing ML model over time was the gradient boosted decision trees model with an AUC of 0.84 (0.77-0.88) at triage, 0.86 (0.82-0.89) at similar to 30 min and 0.86 (0.74-0.93) after similar to 2 h.Conclusions: Our study showed that machine learning models had an excellent but similar predictive performance as the logistic regression model for predicting hospital admission. In comparison to the 30-min model, the 2-h model did not show a performance improvement. After further validation, these prediction models could support management decisions by real-time feedback to medical personal. Show less
