Search

Introduction: HEART score is widely used to stratify patients with chest pain in the emergency department but has never been validated for cocaine-associated chest pain (CACP). We sought to evaluate the performance of HEART score in risk stratifying patients with CACP compared to an age- and sex-matched cohort with non-CACP., Methods: The parent study was an observational cohort study that enrolled consecutive patients with chest pain. We identified patients with CACP and age/sex matched them to patients with non-CACP in 1:2 fashion. HEART score was calculated retrospectively from charts. The primary outcome was major adverse cardiac events (MACE) within 30 days of indexed encounter., Results: We included 156 patients with CACP and 312 age-and sex-matched patients with non-CACP (n = 468, mean age 51 ± 9, 22% females). There was no difference in rate of MACE between the groups (17.9% vs. 15.7%, p = 0.54). Compared to the non-CACP group, the HEART score had lower classification performance in those with CACP (AUC = 0.68 [0.56-0.80] vs. 0.84 [0.78-0.90], p = 0.022). In CACP group, Troponin score had the highest discriminatory value (AUC = 0.72 [0.60-0.85]) and Risk factors score had the lowest (AUC = 0.47 [0.34-0.59]). In patients deemed low-risk by the HEART score, those with CACP were more likely to experience MACE (14% vs. 4%, OR = 3.7 [1.3-10.7], p = 0.016)., Conclusion: In patients with CACP, HEART score performs poorly in stratifying risk and is not recommended as a rule out tool to identify those at low risk of MACE., Competing Interests: Declaration of Competing Interest This paper is not under consideration elsewhere; none of the paper's contents have been previously published; all authors have read and approved the manuscript; and none of the authors have any conflicts of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Emergency department (ED) nurses need to identify patients with potential acute coronary syndrome (ACS) rapidly because treatment delay could impact patient outcomes. Aims of this secondary analysis were to identify key patient factors that could be available at initial ED nurse triage that predict ACS. Consecutive patients with chest pain who called 9-1-1, received a 12-lead electrocardiogram in the prehospital setting, and were transported via emergency medical service were included in the study. A total of 750 patients were recruited. The sample had an average age of 59 years old, was 57% male, and 40% Black. One hundred and fifteen patients were diagnosed with ACS. Older age, non-Caucasian race, and faster respiratory rate were independent predictors of ACS. There was an interaction between heart rate by Type II diabetes receiving insulin in the context of ACS. Type II diabetics requiring insulin for better glycemic control manifested a faster heart rate. By identifying patient factors at ED nurse triage that could be predictive of ACS, accuracy rates of triage may improve, thus impacting patient outcomes., (© 2020 Wiley Periodicals LLC.)

Background: Delay in seeking medical treatment for suspected acute coronary syndrome can lead to negative patient outcomes., Objective: Our aim was to evaluate the prevalence and predictors of delay in seeking care in high-risk chest pain patients with or without acute coronary syndrome (ACS)., Methods: This was a secondary analysis of an observational cohort study of patients transported by Emergency Medical Services for a chief complaint of chest pain. Important demographic and clinical characteristics were extracted from electronic health records. Two independent reviewers adjudicated the presence of ACS. Logistic regression was used to model the predictors of delay in seeking care., Results: The final sample included 743 patients (99% non-Hispanic). Overall, 24% presented > 12 h from onset of symptoms. Among those with ACS (n = 115), 14% presented > 12 h after onset of symptoms. Race, smoking, diabetes, and related symptoms were associated with delayed seeking behavior. In multivariate analysis, non-Caucasian race (black or others) was the only independent predictor of > 12 h delay in seeking care (odds ratio 1.4; 95% confidence interval 1.0-1.9)., Conclusions: One in four patients with chest pain, including 14% of those with ACS, wait more than 12 h before seeking care. Compared to non-blacks, black patients are 40% more likely to delay seeking care > 12 h., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objectives: Chest pain is among the leading causes for emergency medical services (EMS) activation. Acute myocardial infarction (MI) is not only one of the most critical aetiologies of chest pain, but also one of few conditions encountered by EMS that has been shown to follow a circadian pattern. Understanding the diurnal relationship between the inflow of chest pain patients and the likelihood of acute MI may inform prehospital and emergency department (ED) healthcare providers regarding the prediction, and hence prevention, of dire outcomes., Methods: This was a secondary analysis of previously collected data from an observational prospective study that enrolled consecutive chest pain patients transported by a large metropolitan EMS system in the USA. We used the time of EMS call to determine the time-of-day of the indexed encounter. Two independent reviewers examined available medical data to determine our primary outcome, the presence of MI, and our secondary outcomes, infarct size and 30-day major adverse cardiac events (MACE). We estimated infarct size using peak troponin level., Results: We enrolled 2065 patients (age 56±17, 53% males, 7.5% with MI). Chest pain encounters increased from 9:00 AM to 2:00 PM, with a peak at 1:00 PM and a nadir at 6:00 AM. Acute MI had a bimodal distribution with two peaks: 10 AM in ST-elevation MI, and 10 PM in non-ST-elevation MI. ST-elevation MI with afternoon onset was an independent predictor of infarct size. Acute MI with winter and early spring presentation was an independent predictor of 30-day MACE., Conclusions: EMS-attended chest pain calls follow a diurnal pattern, with the most vulnerable patients encountered during afternoons and winter/spring seasons. These data can inform prehospital and ED healthcare providers regarding the time of presentation where patients are more likely to have an underlying MI and subsequently worse outcomes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Appropriate prehospital (PH) triage of patients with chest pain can significantly improve outcomes in acute myocardial infarction (MI). We sought to explore how PH providers triage chest pain as high versus low risk and to evaluate the accuracy and predictors of their triage decision., Methods: This was a prospective, observational cohort study that enrolled consecutive patients with chest pain transported by emergency medical services (EMS) to 3 tertiary care hospitals in the US. EMS triage decision (high risk versus low-risk) was defined based on the transmission of PH electrocardiogram (ECG) to a command center for medical consultation with or without catheter laboratory activation. Two independent reviewers examined in-hospital medical records to adjudicate the presence of acute MI and to audit the findings on the presenting ECG., Results: We enrolled 2,065 patients (aged 56 ± 17, 53% male) of whom 768 (37%) were triaged as high risk. Those triaged as high risk were older, were more likely to be men or have significant cardiac history, and had a higher rate of acute MI events (14.2% versus 3.5%). The sensitivity and specificity for triaging MI events as high risk were 70% and 97%, respectively. A total of 46/155 (30%) MI events were misclassified as low risk. No previous coronary revascularization and ECG misinterpretation were strong independent predictors of such undertriage., Conclusions: PH providers have moderate sensitivity in triaging high-risk patients; 1 in 3 MI events are undertriaged. Emergency nurses need to pay special attention to patients with benign past histories during transition of care and should always reinterpret ECGs for subtle ischemic changes., (Copyright © 2018 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.)

Background: Nonspecific ST-T repolarization (NST) abnormalities alter the ST-segment for reasons often unrelated to acute myocardial ischemia, which could contribute to misdiagnosis or inappropriate treatment. We sought to define the prevalence of NST patterns in patients with chest pain and evaluate how such patterns correlate with the eventual etiology of chest pain and course of hospitalization., Methods: This was a prospective observational study that included consecutive prehospital chest pain patients from three tertiary care hospitals in the U.S. Two independent reviewers blinded from clinical data audited the prehospital 12-lead ECG for the presence or absence of NST patterns (i.e., right or left bundle branch block, left ventricular hypertrophy with strain pattern, ventricular pacing, ventricular rhythm, or coarse atrial fibrillation). The primary outcome was 30-day major adverse cardiac events (MACE) defined as cardiac arrest, acute heart failure, post-discharge infarction, or all-cause death., Results: The final sample included 750 patients (age 59 ± 17, 58% males). A total of 40 patients (5.3%) experienced 30-MACE and 131 (17.5%) had NST patterns. The presence of NST patterns was an independent multivariate predictor of 30-day MACE (9.9% vs. 4.4%, OR = 2.2 [95% CI = 1.1-4.5]. Patients with NST patterns had increased median length of stay (1.0 [IQR 0.5-3] vs. 2.0 [IQR 1-4] days, p < 0.05) independent of the etiology of chest pain., Conclusions: One in six prehospital ECGs of patients with chest pain has NST patterns. This pattern is associated with increased length of stay and adverse cardiac outcomes, suggesting the need of preventive measures and close follow up in such patients., (Copyright © 2018 Elsevier Inc. All rights reserved.)

BackgroundAcute myocardial ischemia is a common cause of ventricular arrhythmias, yet recent ECG methods predicting susceptibility to ventricular tachyarrhythmia have not been fully evaluated during spontaneous ischemia. We sought to evaluate the clinical utility of alternans and non-alternans components of repolarization variability from the standard 10-second 12-lead ECG signals to risk stratify patients with acute chest pain.MethodsWe enrolled consecutive, non-traumatic, chest pain patients transported through Emergency Medical Services (EMS) to three tertiary care hospitals with cardiac catheterization lab capabilities in Pittsburgh, PA. ECG signals were manually annotated by an electrophysiologist, then automatically processed using a custom-written software. Both T wave alternans (TWA) and non-alternans repolarization variability (NARV) were calculated using the absolute RMS differences over the repolarization window between odd/even averaged beats and between consecutive averaged pairs, respectively. The primary study outcome was the presence of acute myocardial infarction (AMI) documented by cardiac angiography.ResultsAfter excluding patients with secondary repolarization changes (n=123) and those with excessive noise (n=90), our final sample included 537 patients (age 57±16years, 56% males). Patients with AMI (n=47, 9%) had higher TWA and NARV values (p

• Symptom clusters can be a valuable diagnostic and prognostic tool to triage patients with heart failure who present to the emergency department. • Using established unsupervised machine learning approaches, we demonstrated that symptoms of indigestion constitute a distinct phenotypic presentation that is seen in 23% of patients and were independently associated with acute decompensation and 30-day adverse cardiac events. • Emergency department clinicians should be sensitive to symptoms of indigestion in patients with known heart failure evaluated for cardiac complaints. • Screening for symptoms of indigestion can be a simple triage aid that can augment other risk stratification tools and help prioritize resource allocations. • The absence of dyspnea and indigestion in patients with known heart failure who present to the emergency department with cardiac complaints indicates a low-risk presentation. Patients with known heart failure (HF) present to emergency departments (ED) with a plethora of symptoms. Although symptom clusters have been suggested as prognostic features, accurately triaging HF patients is a longstanding challenge. We sought to use machine learning to identify subtle phenotypes of patient symptoms and evaluate their diagnostic and prognostic value among HF patients seeking emergency care. This was a secondary analysis of a prospective cohort study of consecutive patients seen in the ED for chest pain or equivalent symptoms. Independent reviewers extracted clinical data from charts, including nine categories of subjective symptoms reported during initial evaluation. The diagnostic outcome was acute HF exacerbation and prognostic outcome was 30-day major adverse cardiac events (MACE). Outcomes were adjudicated by two independent reviewers. K-means clustering was used to derive latent patient symptom clusters, and their associations with outcomes were assessed using multivariate logistic regression. Sample included 438 patients (age 65±14 years; 45% female, 49% Black, 18% HF exacerbation, 32% MACE). K-means clustering identified three presentation phenotypes: patients with dyspnea only (Cluster A, 40%); patients with indigestion, with or without dyspnea (Cluster B, 23%); patients with neither dyspnea nor indigestion (Cluster C, 37%). Compared to Cluster C, indigestion was a significant predictor of acute HF exacerbation (OR=1.8, 95%CI=1.0–3.4) and 30-day MACE (OR=1.8, 95%CI=1.0–3.1), independent of age, sex, race, and other comorbidities. Indigestion symptoms in patients with known HF signify excess risk of adverse events, suggesting that these patients should be triaged as high-risk during initial ED evaluation. [ABSTRACT FROM AUTHOR]

Healthcare disparities in the initial management of patients with acute coronary syndrome (ACS) exist. Yet, the complexity of interactions between demographic, social, economic, and geospatial determinants of health hinders incorporating such predictors in existing risk stratification models. We sought to explore a machine‐learning‐based approach to study the complex interactions between the geospatial and social determinants of health to explain disparities in ACS likelihood in an urban community. This study identified consecutive patients transported by Pittsburgh emergency medical service for a chief complaint of chest pain or ACS‐equivalent symptoms. We extracted demographics, clinical data, and location coordinates from electronic health records. Median income was based on US census data by zip code. A random forest (RF) classifier and a regularized logistic regression model were used to identify the most important predictors of ACS likelihood. Our final sample included 2400 patients (age 59 ± 17 years, 47% Females, 41% Blacks, 15.8% adjudicated ACS). In our RF model (area under the receiver operating characteristic curve of 0.71 ± 0.03) age, prior revascularization, income, distance from hospital, and residential neighborhood were the most important predictors of ACS likelihood. In regularized regression (akaike information criterion = 1843, bayesian information criterion = 1912, χ2 = 193, df = 10, p < 0.001), residential neighborhood remained a significant and independent predictor of ACS likelihood. Findings from our study suggest that residential neighborhood constitutes an upstream factor to explain the observed healthcare disparity in ACS risk prediction, independent from known demographic, social, and economic determinants of health, which can inform future work on ACS prevention, in‐hospital care, and patient discharge. [ABSTRACT FROM AUTHOR]

Background: The Emergency Severity Index (ESI) is a widely used tool to triage patients in emergency departments. The ESI tool is used to assess all complaints and has significant limitation for accurately triaging patients with suspected acute coronary syndrome (ACS). Objective: We evaluated the accuracy of ESI in predicting serious outcomes in suspected ACS and aimed to assess the incremental reclassification performance if ESI is supplemented with a clinically validated tool used to risk-stratify suspected ACS. Methods:We used existing data from an observational cohort study of patients with chest pain. We extracted ESI scores documented by triage nurses during routine medical care. Two independent reviewers adjudicated the primary outcome, incidence of 30-day major adverse cardiac events. We compared ESI with the well-established modified HEAR/T (patient History, Electrocardiogram, Age, Risk factors, but without Troponin) score. Results: Our sample included 750 patients (age, 59 ± 17 years; 43%female; 40%black). A total of 145 patients (19%) experienced major adverse cardiac event. The area under the receiver operating characteristic curve for ESI score for predicting major adverse cardiac event was 0.656, compared with 0.796 for the modified HEAR/T score. Using the modified HEAR/T score, 181 of the 391 false positives (46%) and 16 of the 19 false negatives (84%) assigned by ESI could be reclassified correctly. Conclusion: The ESI score is poorly associated with serious outcomes in patients with suspected ACS. Supplementing the ESI tool with input from other validated clinical tools can greatly improve the accuracy of triage in patients with suspected ACS. [ABSTRACT FROM AUTHOR]

Background: Many of the clinical risk scores routinely used for chest pain assessment have not been validated in patients at high risk for acute coronary syndrome (ACS). We performed an independent comparison of HEART, TIMI, GRACE, FRISC, and PURSUIT scores for identifying chest pain due to ACS and for predicting 30-day death or re-infarction in patients arriving through Emergency Medical Services (EMS).Methods and Results: We enrolled consecutive EMS patients evaluated for chest pain at three emergency departments. A reviewer blinded to outcome data retrospectively reviewed patient charts to compute each risk score. The primary outcome was ACS diagnosed during the primary admission, and the secondary outcome was death or re-infarction within 30-days of initial presentation. Our sample included 750 patients (aged 59 ± 17 years, 42% female), of whom 115 (15.3%) had ACS and 33 (4.4%) had 30-day death or re-infarction. The c-statistics of HEART, TIMI, GRACE, FRISC, and PURSUIT for identifying ACS were 0.87, 0.86, 0.73, 0.84, and 0.79, respectively, and for predicting 30-day death or re-infarction were 0.70, 0.73, 0.72, 0.72, and 0.62, respectively. Sensitivity/negative predictive value of HEART ≥ 4 and TIMI ≥ 3 for ACS detection were 0.94/0.98 and 0.87/0.97, respectively.Conclusions: In chest pain patients admitted through EMS, HEART and TIMI outperform other scores for identifying chest pain due to ACS. Although both have similar negative predictive value, HEART has better sensitivity and lower rate of false negative results, thus it can be used preferentially over TIMI in the initial triage of this population. [ABSTRACT FROM AUTHOR]

Background: Nearly a million people a year experience an acute myocardial infarction (AMI), with projections only increasing by 2030. It is known that when a person has chest pain, they should call 9-1-1 or seek immediate emergency treatment. Accredited chest pain centers across the United States are becoming the gold standard of care for these patients. With incidence increasing, pre-hospital providers need to be aware of the diversity in their community. We sought to investigate if geographic variation of persons who called 9-1-1 for chest pain or equivalent symptoms were diagnosed with acute coronary syndrome. Objective: To determine whether the AMI rates differ among zip codes within the area of the city of Pittsburgh and the impact of income on the AMI rates. Methods: A total of 2062 patients transferred with chest pain via the Pittsburgh Emergency Services were included in this analysis. In-hospital medical records were used to verify patient diagnosis of AMI. The US census data were used for extraction of the total population and median income for each zip code. Next, the Standardized Morbidity Ratio (SMR) were calculated as the ratio of the observed to expected cases of AMI. P-values were calculated to identify zip codes with AMI rates at more than twice the expected rate. A Poisson generalized linear model (GLM) was fitted to evaluate the impact of median income per zip code on AMI rates. Results: Of the sample, 155 (7.5%) patients were ultimately diagnosed with AMI. The global incidence rate for the entire region was 2.7 cases per 10,000. The geospatial analysis revealed that the industrial downtown region was more than twice likely to have higher AMI rate than the expected global rate (Figure 1, darker regions). The GLM model showed a significant, but weak, negative impact of median income on AMI rate (B= -5.551e-05, p<.001). Conclusion: Patients that dial 9-1-1 in the city of Pittsburgh for chest pain in the downtown region are at higher risk for being diagnosed with an AMI. EMS providers can potentially use this and similar geographic data to help expedite appropriate patient care. [ABSTRACT FROM AUTHOR]

Background: Sublingual nitroglycerin (NTG) is frequently used in the prehospital setting in patients with suspected acute myocardial infarction. Current AHA/ACC guidelines recommends against administering NTG to those with marked tachycardia due to the adverse risks associated with severe hypotension. However, there are no clear outcome data to support that patients with tachycardia should not receive NTG. We sought to evaluate the incidence of severe hypotension among patients with prehospital chest pain who received NTG. Methods: This was a prospective, observational, cohort study that enrolled consecutive chest pain patients transported by Emergency Medical Services to three tertiary hospitals in the U.S. For this analysis, we only included patients who received sublingual NTG during the prehospital transport (n=316 / 750, 42%). We used the vital signs obtained by paramedics to determine if the patient had tachycardia (heart rate > 100) upon the time of administration. We also computed the difference in systolic blood pressure (SBP) readings between prehospital vital signs and emergency department initial vital signs to determine the incidence of severe hypotension (significant drop in SBP > 30 mmHg or post-NTG SBP < 90 mmHg). Results: This study enrolled 316 patients (Age 59 ± 14, 60% male, 41% Black). Significant drop of SBP occurred in 102 patients (32.2%). Compared to those with normal heart rate (n=239, 76%), patients with tachycardia (n=77, 24.3%) were not at increased risk of developing a significant drop in SBP > 30 after NTG administration (35% vs. 31%, Relative Risk = 1.11 [95% CI 0.78–1.59], p = NS). Similarly, patients with tachycardia were not at increased risk of developing post-NTG SBP < 90 mmHg (2.6% vs. 1.3%, Relative Risk = 2.0 [95% CI 0.59-7.1], p = NS). Conclusion: In this cohort of prehospital chest pain patients, tachycardia does not seem to increase the risk of NTG-induced severe hypotension. [ABSTRACT FROM AUTHOR]