Lucas Oliveira J E Silva1, Jessica A Stanich1, Molly M Jeffery1,2, Aidan F Mullan3, Susan M Bower1,4, Ronna L Campbell1, Alejandro A Rabinstein5, Robert J Pignolo6, Fernanda Bellolio1,2. 1. Department of Emergency Medicine, Mayo Clinic, Rochester, Minnesota, USA. 2. Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota, USA. 3. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA. 4. Department of Nursing, Mayo Clinic, Rochester, Minnesota, USA. 5. Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA. 6. Department of Hospital Internal Medicine, Division of Geriatric Medicine and Gerontology, Mayo Clinic, Rochester, Minnesota, USA.
Abstract
OBJECTIVE: The objective was to derive a risk score that uses variables available early during the emergency department (ED) encounter to identify high-risk geriatric patients who may benefit from delirium screening. METHODS: This was an observational study of older adults age ≥ 75 years who presented to an academic ED and who were screened for delirium during their ED visit. Variable selection from candidate predictors was performed through a LASSO-penalized logistic regression. A risk score was derived from the final prediction model, and predictive accuracy characteristics were calculated with 95% confidence intervals (CIs). RESULTS: From the 967 eligible ED visits, delirium was detected in 107 (11.1%). The area under the curve for the REcognizing DElirium in Emergency Medicine (REDEEM) score was 0.901 (95% CI = 0.864-0.938). The REEDEM risk score included 10 different variables (seven based on triage information and three obtained during early history taking) with a score ranging from -3 to 66. Using an optimal cutoff of ≥11, we found a sensitivity of 84.1% (90 of 107 ED delirium patients, 95% CI = 75.5%-90.2%) and a specificity of 86.6% (745 of 860 non-ED delirium patients, 95% CI = 84.1%-88.8%). A lower cutoff of ≥5 was found to minimize false negatives with an improved sensitivity at 91.6% (98 of 107 ED delirium patients, 95% CI = 84.2%-95.8%). CONCLUSION: A risk stratification score was derived with the potential to augment delirium recognition in geriatric ED patients. This has the potential to assist on delirium-targeted screening of high-risk patients in the ED. Validation of REDEEM, however, is needed prior to implementation.
OBJECTIVE: The objective was to derive a risk score that uses variables available early during the emergency department (ED) encounter to identify high-risk geriatric patients who may benefit from delirium screening. METHODS: This was an observational study of older adults age ≥ 75 years who presented to an academic ED and who were screened for delirium during their ED visit. Variable selection from candidate predictors was performed through a LASSO-penalized logistic regression. A risk score was derived from the final prediction model, and predictive accuracy characteristics were calculated with 95% confidence intervals (CIs). RESULTS: From the 967 eligible ED visits, delirium was detected in 107 (11.1%). The area under the curve for the REcognizing DElirium in Emergency Medicine (REDEEM) score was 0.901 (95% CI = 0.864-0.938). The REEDEM risk score included 10 different variables (seven based on triage information and three obtained during early history taking) with a score ranging from -3 to 66. Using an optimal cutoff of ≥11, we found a sensitivity of 84.1% (90 of 107 ED delirium patients, 95% CI = 75.5%-90.2%) and a specificity of 86.6% (745 of 860 non-ED delirium patients, 95% CI = 84.1%-88.8%). A lower cutoff of ≥5 was found to minimize false negatives with an improved sensitivity at 91.6% (98 of 107 ED delirium patients, 95% CI = 84.2%-95.8%). CONCLUSION: A risk stratification score was derived with the potential to augment delirium recognition in geriatric ED patients. This has the potential to assist on delirium-targeted screening of high-risk patients in the ED. Validation of REDEEM, however, is needed prior to implementation.
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