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Safely Identifying Emergency Department Patients With Acute Chest Pain for Early Discharge.

ABSTRACT: BACKGROUND:The HEART Pathway (history, ECG, age, risk factors, and initial troponin) is an accelerated diagnostic protocol designed to identify low-risk emergency department patients with chest pain for early discharge without stress testing or angiography. The objective of this study was to determine whether implementation of the HEART Pathway is safe (30-day death and myocardial infarction rate <1% in low-risk patients) and effective (reduces 30-day hospitalizations) in emergency department patients with possible acute coronary syndrome. METHODS:A prospective pre-post study was conducted at 3 US sites among 8474 adult emergency department patients with possible acute coronary syndrome. Patients included were ?21 years old, investigated for possible acute coronary syndrome, and had no evidence of ST-segment-elevation myocardial infarction on ECG. Accrual occurred for 12 months before and after HEART Pathway implementation from November 2013 to January 2016. The HEART Pathway accelerated diagnostic protocol was integrated into the electronic health record at each site as an interactive clinical decision support tool. After accelerated diagnostic protocol integration, ED providers prospectively used the HEART Pathway to identify patients with possible acute coronary syndrome as low risk (appropriate for early discharge without stress testing or angiography) or non-low risk (appropriate for further in-hospital evaluation). The primary safety and effectiveness outcomes, death, and myocardial infarction (MI) and hospitalization rates at 30 days were determined from health records, insurance claims, and death index data. RESULTS:Preimplementation and postimplementation cohorts included 3713 and 4761 patients, respectively. The HEART Pathway identified 30.7% as low risk; 0.4% of these patients experienced death or MI within 30 days. Hospitalization at 30 days was reduced by 6% in the postimplementation versus preimplementation cohort (55.6% versus 61.6%; adjusted odds ratio, 0.79; 95% CI, 0.71-0.87). During the index visit, more MIs were detected in the postimplementation cohort (6.6% versus 5.7%; adjusted odds ratio, 1.36; 95% CI, 1.12-1.65). Rates of death or MI during follow-up were similar (1.1% versus 1.3%; adjusted odds ratio, 0.88; 95% CI, 0.58-1.33). CONCLUSIONS:HEART Pathway implementation was associated with decreased hospitalizations, increased identification of index visit MIs, and a very low death and MI rate among low-risk patients. These findings support use of the HEART Pathway to identify low-risk patients who can be safely discharged without stress testing or angiography. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov . Unique identifier: NCT02056964.

SUBMITTER: Mahler SA

PROVIDER: S-EPMC6309794 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Safely Identifying Emergency Department Patients With Acute Chest Pain for Early Discharge.

Mahler Simon A SA Lenoir Kristin M KM Wells Brian J BJ Burke Gregory L GL Duncan Pamela W PW Case L Douglas LD Herrington David M DM Diaz-Garelli Jose-Franck JF Futrell Wendell M WM Hiestand Brian C BC Miller Chadwick D CD

Circulation 20181101 22

<h4>Background</h4>The HEART Pathway (history, ECG, age, risk factors, and initial troponin) is an accelerated diagnostic protocol designed to identify low-risk emergency department patients with chest pain for early discharge without stress testing or angiography. The objective of this study was to determine whether implementation of the HEART Pathway is safe (30-day death and myocardial infarction rate <1% in low-risk patients) and effective (reduces 30-day hospitalizations) in emergency depar ...[more]

PMID: 30571347

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Project description:ImportanceNoninvasive testing and coronary angiography are used to evaluate patients who present to the emergency department (ED) with chest pain, but their effects on outcomes are uncertain.ObjectiveTo determine whether cardiovascular testing-noninvasive imaging or coronary angiography-is associated with changes in the rates of coronary revascularization or acute myocardial infarction (AMI) admission in patients who present to the ED with chest pain without initial findings of ischemia.Design, setting, and participantsThis retrospective cohort analysis used weekday (Monday-Thursday) vs weekend (Friday-Sunday) presentation as an instrument to adjust for unobserved case-mix variation (selection bias) between 2011 and 2012. National claims data (Truven MarketScan) was used. The data included a total of 926 633 privately insured patients ages 18 to 64 years who presented to the ED with chest pain without initial diagnosis consistent with acute ischemia.ExposuresNoninvasive testing or coronary angiography within 2 days or 30 days of presentation.Main outcomes and measuresThe primary end points were coronary revascularization (percutaneous coronary intervention or coronary artery bypass graft surgery) and AMI admission at 7, 30, 180, and 365 days. The secondary end points were coronary angiography and coronary artery bypass grafting in those who underwent angiography.ResultsThe patients were ages 18 to 64 years with an average age of 44.4 years. A total of 536 197 patients (57.9%) were women. Patients who received testing (224 973) had increased risk at baseline and had greater risk of AMI admission than those who did not receive testing (701 660) (0.35% vs 0.14% at 30 days). Weekday patients (571 988) had similar baseline comorbidities to weekend patients (354 645) but were more likely to receive testing. After risk factor adjustment, testing within 30 days was associated with a significant increase in coronary angiography (36.5 per 1000 patients tested; 95% CI, 21.0-52.0) and revascularization (22.8 per 1000 patients tested; 95% CI, 10.6-35.0) at 1 year but no significant change in AMI admissions (7.8 per 1000 patients tested; 95% CI, -1.4 to 17.0). Testing within 2 days was also associated with a significant increase in coronary revascularization but no difference in AMI admissions.Conclusions and relevanceCardiac testing in patients with chest pain was associated with increased downstream testing and treatment without a reduction in AMI admissions, suggesting that routine testing may not be warranted. Further research into whether specific high-risk subgroups benefit from testing is needed.

Project description:BackgroundDue to an aging population and the increasing proportion of patients with various comorbidities, the number of patients with acute ischemic heart disease (AIHD) who present to the emergency department (ED) with atypical chest pain is increasing. The aim of this study was to develop and validate a prediction model for AIHD in patients with atypical chest pain.Methods and resultsA chest pain workup registry, ED administrative database, and clinical data warehouse database were analyzed and integrated by using nonidentifiable key factors to create a comprehensive clinical dataset in a single academic ED from 2014 to 2018. Demographic findings, vital signs, and routine laboratory test results were assessed for their ability to predict AIHD. An extreme gradient boosting (XGB) model was developed and evaluated, and its performance was compared to that of a single-variable model and logistic regression model. The area under the receiver operating characteristic curve (AUROC) was calculated to assess discrimination. A calibration plot and partial dependence plots were also used in the analyses. Overall, 4,978 patients were analyzed. Of the 3,833 patients in the training cohort, 453 (11.8%) had AIHD; of the 1,145 patients in the validation cohort, 166 (14.5%) had AIHD. XGB, troponin (single-variable), and logistic regression models showed similar discrimination power (AUROC [95% confidence interval]: XGB model, 0.75 [0.71-0.79]; troponin model, 0.73 [0.69-0.77]; logistic regression model, 0.73 [0.70-0.79]). Most patients were classified as non-AIHD; calibration was good in patients with a low predicted probability of AIHD in all prediction models. Unlike in the logistic regression model, a nonlinear relationship-like threshold and U-shaped relationship between variables and the probability of AIHD were revealed in the XGB model.ConclusionWe developed and validated an AIHD prediction model for patients with atypical chest pain by using an XGB model.

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Safely Identifying Emergency Department Patients With Acute Chest Pain for Early Discharge.

Publications

Safely Identifying Emergency Department Patients With Acute Chest Pain for Early Discharge.

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