A new simplified model for predicting 30-day mortality in older medical emergency department patients: The rise up score

Zelis, Noortje; Buijs, Jacqueline; Leeuw, Peter W. de; Kuijk, Sander M. J. van; Stassen, Patricia M.

doi:10.1016/j.ejim.2020.02.021

Cited by 18 publications

(27 citation statements)

References 33 publications

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“…The score consists of six easily and readily available items during the ED visit. 7 The RISE UP score can be easily implemented in routine practice with an online calculator (https:// jscalc. io/ calc/ o1vzp36bIDGQUCYl).…”

Section: Discussionmentioning

confidence: 99%

“…The original research article concerning the RISE UP score showed a better predictive performance compared with our current study (AUC 0.83 vs 0.77). 7 The difference can be explained in several ways. First, 30-day mortality was around 11% in the original cohort, while in our cohort it was 26.0%.…”

Section: Discussionmentioning

confidence: 99%

“…Many risk prediction models have been developed for patients with COVID-19, most of which still need rigorous external validation efforts to assess their added value to clinical practice; however, our group developed and validated the Risk Stratification in the Emergency Department in Acutely ill Older Patients (RISE UP) score, an accurate and easy to use model, predicting mortality in medical patients older than 65 years in the emergency department (ED). 7 The model had very good discriminatory value with an area under the receiver operating characteristic curve (AUC) of 0.84 in the derivation and 0.83 in the validation cohort.…”

Section: Introductionmentioning

confidence: 95%

“…The original formula of the RISE UP score to calculate an individual's probability of 30-day mortality is P(30-day mortality)=1/(1+exp (-(−3.908+0.050*Age +1.115*≥2 Abnormal Vital Signs (yes=1, no=0)-0.112*Albumin (in g/L)+0.284*(BUN (in mmol/L)/5)+0.120*(LDH (in U/L)/100)+0.875*Bilirubin>20 µmol/L (yes=1, no=0))). 7 The RISE UP score is shown as a percentage.…”

Section: Data Collectionmentioning

confidence: 99%

“…This could at least in part be due to the fact that in the derivation and validation cohort of the RISE UP score, we observed a 30-day mortality of 10.9% and 13.3%, respectively; therefore, we performed recalibration of the model. 7 The formula was adjusted by changing the intercept to −2.083 and multiplying the linear sum of regression coefficients multiplied by their respective predictor values by 0.795. The adjusted formula for the RISE UP score in patients with COVID-19 was P(30-day mortality)=1/(1+exp (-(−2.083+0.795 *…”

Section: Rise Up Scorementioning

confidence: 99%

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Validating the RISE UP score for predicting prognosis in patients with COVID-19 in the emergency department: a retrospective study

et al. 2021

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ObjectiveTo mitigate the burden of COVID-19 on the healthcare system, information on the prognosis of the disease is needed. The recently developed Risk Stratification in the Emergency Department in Acutely ill Older Patients (RISE UP) score has very good discriminatory value for short-term mortality in older patients in the emergency department (ED). It consists of six readily available items. We hypothesised that the RISE UP score could have discriminatory value for 30-day mortality in ED patients with COVID-19.DesignRetrospective analysis.SettingTwo EDs of the Zuyderland Medical Centre, secondary care hospital in the Netherlands.ParticipantsThe study sample consisted of 642 adult ED patients diagnosed with COVID-19 between 3 March and until 25 May 2020. Inclusion criteria were (1) admission to the hospital with symptoms suggestive of COVID-19 and (2) positive result of the PCR or (very) high suspicion of COVID-19 according to the chest CT scan.OutcomePrimary outcome was 30-day mortality, secondary outcome was a composite of 30-day mortality and admission to intensive care unit (ICU).ResultsWithin 30 days after presentation, 167 patients (26.0%) died and 102 patients (15.9%) were admitted to ICU. The RISE UP score showed good discriminatory value for 30-day mortality (area under the receiver operating characteristic curve (AUC) 0.77, 95% CI 0.73 to 0.81) and for the composite outcome (AUC 0.72, 95% CI 0.68 to 0.76). Patients with RISE UP scores below 10% (n=121) had favourable outcome (zero deaths and six ICU admissions), while those with scores above 30% (n=221) were at high risk of adverse outcome (46.6% mortality and 19.0% ICU admissions).ConclusionThe RISE UP score is an accurate prognostic model for adverse outcome in ED patients with COVID-19. It can be used to identify patients at risk of short-term adverse outcome and may help guide decision-making and allocating healthcare resources.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Data Collectionmentioning

confidence: 99%

Section: Rise Up Scorementioning

confidence: 99%

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Validating the RISE UP score for predicting prognosis in patients with COVID-19 in the emergency department: a retrospective study

et al. 2021

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Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions

et al. 2021

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IMPORTANCE Triage in the emergency department (ED) is a complex clinical judgment based on the tacit understanding of the patient's likelihood of survival, availability of medical resources, and local practices. Although a scoring tool could be valuable in risk stratification, currently available scores have demonstrated limitations. OBJECTIVES To develop an interpretable machine learning tool based on a parsimonious list of variables available at ED triage; provide a simple, early, and accurate estimate of patients' risk of death; and evaluate the tool's predictive accuracy compared with several established clinical scores. DESIGN, SETTING, AND PARTICIPANTS This single-site, retrospective cohort study assessed all ED patients between January 1, 2009, and December 31, 2016, who were subsequently admitted to a tertiary hospital in Singapore. The Score for Emergency Risk Prediction (SERP) tool was derived using a machine learning framework. To estimate mortality outcomes after emergency admissions, SERP was compared with several triage systems, including Patient Acuity Category Scale, Modified Early Warning Score, National Early Warning Score, Cardiac Arrest Risk Triage, Rapid Acute Physiology Score, and Rapid Emergency Medicine Score. The initial analyses were completed in October 2020, and additional analyses were conducted in May 2021. MAIN OUTCOMES AND MEASURESThree SERP scores, namely SERP-2d, SERP-7d, and SERP-30d, were developed using the primary outcomes of interest of 2-, 7-, and 30-day mortality, respectively.Secondary outcomes included 3-day mortality and inpatient mortality. The SERP's predictive power was measured using the area under the curve in the receiver operating characteristic analysis. RESULTSThe study included 224 666 ED episodes in the model training cohort (mean [SD] patient age, 63.60 [16.90] years; 113 426 [50.5%] female), 56 167 episodes in the validation cohort (mean [SD] patient age, 63.58 [16.87] years; 28 427 [50.6%] female), and 42 676 episodes in the testing cohort (mean [SD] patient age, 64.85 [16.80] years; 21 556 [50.5%] female). The mortality rates inthe training cohort were 0.8% at 2 days, 2.2% at 7 days, and 5.9% at 30 days. In the testing cohort, the areas under the curve of SERP-30d were 0.821 (95% CI, 0.796-0.847) for 2-day mortality, 0.826 (95% CI, 0.811-0.841) for 7-day mortality, and 0.823 (95% CI, 0.814-0.832) for 30-day mortality and outperformed several benchmark scores. CONCLUSIONS AND RELEVANCEIn this retrospective cohort study, SERP had better prediction performance than existing triage scores while maintaining easy implementation and ease of ascertainment in the ED. It has the potential to be widely applied and validated in different circumstances and health care settings.

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A New Model of an Emergency Room for Elderly Patients

Vargas,

Fabbo,

Esquinas

2023

Acute Geriatric Care: From Hospital to Territorial Charge

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A new simplified model for predicting 30-day mortality in older medical emergency department patients: The rise up score

Cited by 18 publications

References 33 publications

Validating the RISE UP score for predicting prognosis in patients with COVID-19 in the emergency department: a retrospective study

Validating the RISE UP score for predicting prognosis in patients with COVID-19 in the emergency department: a retrospective study

Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions

A New Model of an Emergency Room for Elderly Patients

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