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Prospective Validation and Comparative Analysis of Coronary Risk Stratification Strategies Among Emergency Department Patients With Chest Pain.

ABSTRACT: Background Coronary risk stratification is recommended for emergency department patients with chest pain. Many protocols are designed as "rule-out" binary classification strategies, while others use graded-risk stratification. The comparative performance of competing approaches at varying levels of risk tolerance has not been widely reported. Methods and Results This is a prospective cohort study of adult patients with chest pain presenting between January 2018 and December 2019 to 13 medical center emergency departments within an integrated healthcare delivery system. Using an electronic clinical decision support interface, we externally validated and assessed the net benefit (at varying risk thresholds) of several coronary risk scores (History, ECG, Age, Risk Factors, and Troponin [HEART] score, HEART pathway, Emergency Department Assessment of Chest Pain Score Accelerated Diagnostic Protocol), troponin-only strategies (fourth-generation assay), unstructured physician gestalt, and a novel risk algorithm (RISTRA-ACS). The primary outcome was 60-day major adverse cardiac event defined as myocardial infarction, cardiac arrest, cardiogenic shock, coronary revascularization, or all-cause mortality. There were 13 192 patient encounters included with a 60-day major adverse cardiac event incidence of 3.7%. RISTRA-ACS and HEART pathway had the lowest negative likelihood ratios (0.06, 95% CI, 0.03-0.10 and 0.07, 95% CI, 0.04-0.11, respectively) and the greatest net benefit across a range of low-risk thresholds. RISTRA-ACS demonstrated the highest discrimination for 60-day major adverse cardiac event (area under the receiver operating characteristic curve 0.92, 95% CI, 0.91-0.94, P<0.0001). Conclusions RISTRA-ACS and HEART pathway were the optimal rule-out approaches, while RISTRA-ACS was the best-performing graded-risk approach. RISTRA-ACS offers promise as a versatile single approach to emergency department coronary risk stratification. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03286179.

SUBMITTER: Mark DG

PROVIDER: S-EPMC8174350 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:High-sensitivity troponin assay brought new challenges as we detect elevated concentration in many other diseases, and it became difficult to distinguish the real cause of this elevation. In this notion, diagnosis of acute coronary syndrome (ACS) remains a challenge in emergency department (ED). We aim to examine different approaches for rule-in and rule-out of ACS using risk scores, copeptin, and coronary computed tomography angiography (CCTA). A prospective observational study was designed to evaluate chest pain patients. Consecutive adult patients admitted to the ED with a chief complaint of chest pain due to any cause were included. All patients were followed-up for 6 months after discharge for major adverse cardiovascular events and readmissions. Admission data, ED processes, and diagnoses were analyzed. One hundred forty-six patients were included, average age was 63 ± 13.4 years, and 95 (65.1%) were male. Global Registry of Acute Coronary Events (GRACE) and History, ECG, Age, Risk factors, Troponin (HEART) scores showed good prognostic abilities, but HEART combination with copeptin improves diagnoses of myocardial infarction (area under the curve [AUC] 0.764 vs AUC 0.864 P = .0008). Patients with elevated copeptin were older, had higher risk scores, and were more likely to be admitted to hospital and diagnosed with ACS in ED. For copeptin, AUC was 0.715 (95% confidence interval 0.629-0.803), and for combination with troponin, AUC of 0.770 (0.703-0.855) did not improve rule-in of myocardial infarction. High-sensitivity troponin I assay alongside prior stroke, history of carotid stenosis, dyslipidemia, use of diuretics, and electrocardiogram changes (left bundle branch block or ST depression) are good predictors of myocardial infarction (χ² = 52.29, AUC = 0.875 [0.813-0.937], P < .001). The regression analysis showed that combination of copeptin and CCTA without significant stenosis can be used for ACS rule-out (χ² = 26.36, P < .001, AUC = 0.772 [0.681-0.863], negative predictive value of 96.25%). For rule-in of ACS, practitioner should consider not only scores for risk stratification but carefully analyze medical history and nonspecific electrocardiogram changes and even with normal troponin results, we strongly suggest thorough evaluation in chest pain unit. For rule-out of ACS combination of copeptin and CCTA holds great potential.

Project description:Objective:Chest pain scores allow emergency department (ED) physicians to identify low-risk patients for whom discharge can be safely expedited. Although these have been extensively validated in Western cohorts, data in patients of Asian heritage are lacking. This study aimed to determine the accuracy of HEART, ED Assessment of Chest Pain Score (EDACS), and Global Registry of Acute Coronary Events (GRACE) in risk-stratifying which chest pain patients are at risk of major adverse cardiovascular events within 30 days (composite of all-cause mortality, acute myocardial infarction and coronary revascularization). Methods:This single-center prospective cohort-study that enrolled 1200 patients was conducted by a large urban tertiary center in Singapore. Chest pain scores were reported before disposition by research assistants blinded to the physician's clinical assessment. Outcomes were assessed independently by a blinded cardiologist and emergency physician, while another cardiologist adjudicated in the case of discrepancies. Results:Of the 1195 patients analyzed, 135 (11.3%) suffered major adverse cardiovascular events within 30 days. HEART, which ruled out major adverse cardiovascular events in 52.8% of patients with 88.1% sensitivity, and EDACS, which ruled out major adverse cardiovascular events in 57.5% of patients with 83.7% sensitivity, proved comparable to clinical judgment that ruled out major adverse cardiovascular events in 73.0% of patients with 85.5% sensitivity. GRACE was weaker-ruling out major adverse cardiovascular events in 79.2% of patients with a dismal sensitivity of 45.0%. The correlation-statistic for HEART (79.4%) was superior to EDACS (69.9%) and GRACE (69.2%). Conclusions:HEART more accurately identified low-risk chest pain patients in an Asian ED, demonstrating comparable performance characteristics to clinical judgment. This has major implications on the use of chest pain scores to safely expedite disposition decisions for low-risk chest pain patients.

Project description:BackgroundThe Global Registry of Acute Coronary Events (GRACE) score is recommended for stratifying chest pain. However, there are six formulas used to calculate the GRACE score for different outcomes of acute coronary syndrome (ACS), including death (Dth) or composite of death and myocardial infarction (MI), while in hospital (IH), within 6 months after discharge (OH6m) or from admission to 6 months later (IH6m). We aimed to perform the first comprehensive evaluation and comparison of six GRACE models to predict 30-day major adverse cardiac events (MACEs) in patients with acute chest pain in the emergency department (ED).MethodsPatients with acute chest pain were consecutively recruited from August 24, 2015 to September 30, 2017 from the EDs of two public hospitals in China. The 30-day MACEs included death, acute myocardial infarction (AMI), emergency revascularization, cardiac arrest and cardiogenic shock. The correlation, calibration, discrimination, reclassification and diagnostic accuracy at certain cutoff values of six GRACE models were evaluated. Comparisons with the History, ECG, Age, Risk Factors, and Troponin (HEART) and Thrombolysis in Myocardial Infarction (TIMI) scores were conducted.ResultsA total of 2886 patients were analyzed, with 590 (20.4%) patients experiencing outcomes. The GRACE (IHDthMI), GRACE (IH6mDthMI), GRACE (IHDth), GRACE (IH6mDth), GRACE (OH6mDth) and GRACE (OH6mDthMI) showed positive linear correlations with the actual MACE rates (r ≥ 0.568, P < 0.001). All these models had good calibration (Hosmer-Lemeshow test, P ≥ 0.073) except GRACE (IHDthMI) (P < 0.001). The corresponding C-statistics were 0.83(0.81,0.84), 0.82(0.81,0.83), 0.75(0.73,0.76), 0.73(0.72,0.75), 0.72(0.70,0.73) and 0.70(0.68,0.71), respectively, first two of which were comparable to HEART (0.82, 0.80-0.83) and superior to TIMI (0.71, 0.69-0.73). With a sensitivity ≥95%, GRACE (IHDthMI) ≤81 and GRACE (IH6mDthMI) ≤79 identified 868(30%) and 821(28%) patients as low risk, respectively, which were significantly better than other GRACEs and HEART ≤3(22%). With a specificity ≥95%, GRACE (IHDthMI) > 186 and GRACE (IH6mDthMI) > 161 could recognize 12% and 11% patients as high risk, which were greater than other GRACEs, HEART ≥8(9%) and TIMI ≥5(8%).ConclusionsIn this Chinese setting, certain strengths of GRACE models beyond HEART and TIMI scores were still noteworthy for stratifying chest pain patients. The validation and reasonable application of appropriate GRACE models in the evaluation of undifferentiated chest pain should be recommended.

Project description:BACKGROUND:Chest pain is one of the most common complaints among patients presenting to the emergency department (ED). Causes of chest pain can be benign or life threatening, making accurate risk stratification a critical issue in the ED. In addition to the use of established clinical scores, prior studies have attempted to create predictive models with heart rate variability (HRV). In this study, we proposed heart rate n-variability (HRnV), an alternative representation of beat-to-beat variation in electrocardiogram (ECG), and investigated its association with major adverse cardiac events (MACE) in ED patients with chest pain. METHODS:We conducted a retrospective analysis of data collected from the ED of a tertiary hospital in Singapore between September 2010 and July 2015. Patients >?20?years old who presented to the ED with chief complaint of chest pain were conveniently recruited. Five to six-minute single-lead ECGs, demographics, medical history, troponin, and other required variables were collected. We developed the HRnV-Calc software to calculate HRnV parameters. The primary outcome was 30-day MACE, which included all-cause death, acute myocardial infarction, and revascularization. Univariable and multivariable logistic regression analyses were conducted to investigate the association between individual risk factors and the outcome. Receiver operating characteristic (ROC) analysis was performed to compare the HRnV model (based on leave-one-out cross-validation) against other clinical scores in predicting 30-day MACE. RESULTS:A total of 795 patients were included in the analysis, of which 247 (31%) had MACE within 30?days. The MACE group was older, with a higher proportion being male patients. Twenty-one conventional HRV and 115 HRnV parameters were calculated. In univariable analysis, eleven HRV and 48 HRnV parameters were significantly associated with 30-day MACE. The multivariable stepwise logistic regression identified 16 predictors that were strongly associated with MACE outcome; these predictors consisted of one HRV, seven HRnV parameters, troponin, ST segment changes, and several other factors. The HRnV model outperformed several clinical scores in the ROC analysis. CONCLUSIONS:The novel HRnV representation demonstrated its value of augmenting HRV and traditional risk factors in designing a robust risk stratification tool for patients with chest pain in the ED.

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Prospective Validation and Comparative Analysis of Coronary Risk Stratification Strategies Among Emergency Department Patients With Chest Pain.

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