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Prospective Validation of a Checklist to Predict Short‐term Death in Older Patients After Emergency Department Admission in Australia and Ireland
Author(s) -
Cardona Magnolia,
O'Sullivan Michael,
Lewis Ebony T.,
Turner Robin M.,
Garden Frances,
Alkhouri Hatem,
Asha Stephen,
Mackenzie John,
Perkins Margaret,
Suri Sam,
Holdgate Anna,
Winoto Luis,
Chang David C. W.,
GallegoLuxan Blanca,
McCarthy Sally,
Hillman Ken,
Breen Dorothy
Publication year - 2019
Publication title -
academic emergency medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.221
H-Index - 124
eISSN - 1553-2712
pISSN - 1069-6563
DOI - 10.1111/acem.13664
Subject(s) - medicine , checklist , emergency department , confidence interval , logistic regression , prospective cohort study , emergency medicine , pediatrics , psychology , psychiatry , cognitive psychology
Background Emergency departments ( ED s) are pressured environment where patients with supportive and palliative care needs may not be identified. We aimed to test the predictive ability of the Cri STAL (Criteria for Screening and Triaging to Appropriate aL ternative care) checklist to flag patients at risk of death within 3 months who may benefit from timely end‐of‐life discussions. Methods Prospective cohorts of >65‐year‐old patients admitted for at least one night via ED s in five Australian hospitals and one Irish hospital. Purpose‐trained nurses and medical students screened for frailty using two instruments concurrently and completed the other risk factors on the Cri STAL tool at admission. Postdischarge telephone follow‐up was used to determine survival status. Logistic regression and bootstrapping techniques were used to test the predictive accuracy of Cri STAL for death within 90 days of admission as primary outcome. Predictability of in‐hospital death was the secondary outcome. Results A total of 1,182 patients, with median age 76 to 80 years ( IRE ‐ AUS ), were included. The deceased had significantly higher mean Cri STAL with Australian mean of 8.1 (95% confidence interval [ CI ] = 7.7–8.6) versus 5.7 (95% CI = 5.1–6.2) and Irish mean of 7.7 (95% CI = 6.9–8.5) versus 5.7 (95% CI = 5.1–6.2). The model with Fried frailty score was optimal for the derivation (Australian) cohort but prediction with the Clinical Frailty Scale ( CFS ) was also good (areas under the receiver‐operating characteristic [ AUROC ] = 0.825 and 0.81, respectively). Values for the validation (Irish) cohort were AUROC = 0.70 with Fried and 0.77 using CFS . A minimum of five of 29 variables were sufficient for accurate prediction, and a cut point of 7+ or 6+ depending on the cohort was strongly indicative of risk of death. The most significant independent predictor of short‐term death in both cohorts was frailty, carrying a twofold risk of death. Cri STAL 's accuracy for in‐hospital death prediction was also good ( AUROC = 0.795 and 0.81 in Australia and Ireland, respectively), with high specificity and negative predictive values. Conclusions The modified Cri STAL tool (with CFS instead of Fried's frailty instrument) had good discriminant power to improve certainty of short‐term mortality prediction in both health systems. The predictive ability of models is anticipated to help clinicians gain confidence in initiating earlier end‐of‐life discussions. The practicalities of embedding screening for risk of death in routine practice warrant further investigation.