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

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

Eur J Intern Med. 2020 Feb 26;:

Authors: Zelis N, Buijs J, de Leeuw PW, van Kuijk SMJ, Stassen PM

Abstract
BACKGROUND/OBJECTIVES: Currently, accurate clinical models that predict short-term mortality in older (≥ 65 years) emergency department (ED) patients are lacking. We aimed to develop and validate a prediction model for 30-day mortality in older ED patients that is easy to apply using variables that are readily available and reliably retrievable during the short phase of an ED stay.
METHODS: Prospective multi-centre cohort study in older medical ED patients. The model was derived through logistic regression analyses, externally validated and compared with other well-known prediction models (Identification of Seniors at Risk (ISAR), ISAR-Hospitalised Patients, Acute Physiology and Chronic Health Evaluation II (APACHE II) and Modified Early Warning Score (MEWS)).
RESULTS: Within 30 days after presentation, 66 (10.9%) of 603 patients in the derivation cohort and 105 (13.3%) of 792 patients in the validation cohort died. The newly developed model included 6 predictors: age, ≥2 abnormal vital signs, serum albumin, blood urea nitrogen, lactate dehydrogenase, and bilirubin. The discriminatory value of the model for mortality was very good with an AUC of 0.84 in the derivation and 0.83 in the validation cohort. The final model was excellently calibrated (Hosmer-Lemeshow p-value 0.89). The discriminatory value of the model was significantly higher than that of the four risk stratification scores (highest AUC of 0.69 for ISAR score, p-value 0.007).
CONCLUSION: We developed and externally validated an accurate and simplified prediction model for 30-day mortality in older ED patients. This model may be useful to identify patients at risk of short-term mortality and to apply personalised medical care.

PMID: 32113943 [PubMed - as supplied by publisher]

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