Relationship between a clear-cut alternative noncardiac diagnosis and 30-day outcome in emergency department patients with chest pain

Performance of digital early warning score (NEWS2) in a cardiac specialist setting: retrospective cohort study

INTRODUCTION

Patients with cardiovascular diseases (CVD) are at significant risk of developing critical events. Early warning scores (EWS) are recommended for early recognition of deteriorating patients, yet their performance has been poorly studied in cardiac care settings. Standardisation and integrated National Early Warning Score 2 (NEWS2) in electronic health records (EHRs) are recommended yet have not been evaluated in specialist settings.

OBJECTIVE

To investigate the performance of digital NEWS2 in predicting critical events: death, intensive care unit (ICU) admission, cardiac arrest and medical emergencies.

METHODS

Retrospective cohort analysis.

STUDY COHORT

Individuals admitted with CVD diagnoses in 2020; including patients with COVID-19 due to conducting the study during the COVID-19 pandemic.

MEASURES

We tested the ability of NEWS2 in predicting the three critical outcomes from admission and within 24 hours before the event. NEWS2 was supplemented with age and cardiac rhythm and investigated. We used logistic regression analysis with the area under the receiver operating characteristic curve (AUC) to measure discrimination.

RESULTS

In 6143 patients admitted under cardiac specialties, NEWS2 showed moderate to low predictive accuracy of traditionally examined outcomes: death, ICU admission, cardiac arrest and medical emergency (AUC: 0.63, 0.56, 0.70 and 0.63, respectively). Supplemented NEWS2 with age showed no improvement while age and cardiac rhythm improved discrimination (AUC: 0.75, 0.84, 0.95 and 0.94, respectively). Improved performance was found of NEWS2 with age for COVID-19 cases (AUC: 0.96, 0.70, 0.87 and 0.88, respectively).

CONCLUSION

The performance of NEWS2 in patients with CVD is suboptimal, and fair for patients with CVD with COVID-19 to predict deterioration. Adjustment with variables that strongly correlate with critical cardiovascular outcomes, that is, cardiac rhythm, can improve the model. There is a need to define critical endpoints, engagement with clinical experts in development and further validation and implementation studies of EHR-integrated EWS in cardiac specialist settings.

Predictive risk stratification using HEART (history, electrocardiogram, age, risk factors, and initial troponin) and TIMI (thrombolysis in myocardial infarction) scores in non-high risk chest pain patients: An African American urban community based hospital study

Validated risk scoring systems in African American (AA) population are under studied. We utilized history, electrocardiogram, age, risk factors, and initial troponin (HEART) and thrombolysis in myocardial infarction (TIMI) scores to predict major adverse cardiovascular events (MACE) in non-high cardiovascular (CV) risk predominantly AA patient population.A retrospective emergency department (ED) charts review of 1266 chest pain patients where HEART and TIMI scores were calculated for each patient. Logistic regression model was computed to predict 6-week and 1-year MACE and 90-day cardiac readmission. Decision curve analysis (DCA) was constructed to differentiate between clinical strategies in non-high CV risk patients.Of the 817 patients included, 500 patients had low HEART score vs. 317 patients who had moderate HEART score. Six hundred sixty-three patients had low TIMI score vs. 154 patients had high TIMI score. The univariate logistic regression model shows odds ratio of predicting 6-week MACE using HEART score was 3.11 (95% confidence interval [CI] 1.43-6.76, P = .004) with increase in risk category from low to moderate vs. 2.07 (95% CI 1.18-3.63, P = .011) using TIMI score with increase in risk category from low to high and c-statistic of 0.86 vs. 0.79, respectively. DCA showed net benefit of using HEART score is equally predictive of 6-week MACE when compared to TIMI.In non-high CV risk AA patients, HEART score is better predictive tool for 6-week MACE when compared to TIMI score. Furthermore, patients presenting to ED with chest pain, the optimal strategy for a 2% to 4% miss rate threshold probability should be to discharge these patients from the ED.

Peripheral neuropathic mimics of visceral abdominal pain: Can physical examination limit diagnostic testing?

BACKGROUND

The emergency department evaluation of patients with abdominal pain is most appropriately directed at identifying acute inflammation, infection, obstruction, or surgical disease. Doing so commonly involves "routine" (and often extensive) diagnostic imaging and laboratory testing. Benign mimics of serious visceral abdominal pain that can be diagnosed by physical exam and confirmed with local anesthetic injections have been identified over the last century. These syndromes derive from painful irritation of the intercostal nerves by a mobile rib below, or from impingement of the cutaneous branches of those same intercostal nerves as they penetrate the abdominal wall. These peripheral neuropathic mimics of visceral abdominal pain continue to go unrecognized and underdiagnosed.

METHODS

Our purpose is to review the affirmative diagnosis of non-visceral abdominal pain by physical examination.

RESULTS

The consequences of failure to identify these conditions are considerable. In the search for a diagnosis that is literally at the provider's fingertips, patients frequently undergo months to years of fruitless and often invasive diagnostic tests, not uncommonly including unsuccessful surgeries.

CONCLUSIONS

With proper consideration of and appropriate testing for visceral etiologies, a carefully directed physical examination may yield an affirmative diagnosis in a percentage of these common emergency department patients.

State-of-the-Art Evaluation of Emergency Department Patients Presenting With Potential Acute Coronary Syndromes

It is well established that clinicians cannot use clinical judgment alone to determine whether an individual patient who presents to the emergency department has an acute coronary syndrome. The history and physical examination do not distinguish sufficiently between the many conditions that can cause acute chest pain syndromes. Cardiac risk factors do not have sufficient discriminatory ability in symptomatic patients presenting to the emergency department. Most patients with non-ST-segment-elevation myocardial infarction do not present with electrocardiographic evidence of active ischemia. The improvement in cardiac troponin assays, especially in conjunction with well-validated clinical decision algorithms, now enables the clinician to rapidly exclude myocardial infarction. In patients in whom unstable angina remains a concern or there is a desire to evaluate for underlying coronary artery disease, coronary computed tomography angiography can be used in the emergency department. Once a process that took ≥24 hours, computed tomography angiography now can rapidly exclude myocardial infarction and coronary artery disease in patients in the emergency department.

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

BACKGROUND

The key aim of triage in chest pain patients is to identify those with high risk of adverse cardiac events as they require intensive monitoring and early intervention. In this study, we aim to discover the most relevant variables for risk prediction of major adverse cardiac events (MACE) using clinical signs and heart rate variability.

METHODS

A total of 702 chest pain patients at the Emergency Department (ED) of a tertiary hospital in Singapore were included in this study. The recruited patients were at least 30 years of age and who presented to the ED with a primary complaint of non-traumatic chest pain. The primary outcome was a composite of MACE such as death and cardiac arrest within 72 h of arrival at the ED. For each patient, eight clinical signs such as blood pressure and temperature were measured, and a 5-min ECG was recorded to derive heart rate variability parameters. A random forest-based novel method was developed to select the most relevant variables. A geometric distance-based machine learning scoring system was then implemented to derive a risk score from 0 to 100.

RESULTS

Out of 702 patients, 29 (4.1%) met the primary outcome. We selected the 3 most relevant variables for predicting MACE, which were systolic blood pressure, the mean RR interval and the mean instantaneous heart rate. The scoring system with these 3 variables produced an area under the curve (AUC) of 0.812, and a cutoff score of 43 gave a sensitivity of 82.8% and specificity of 63.4%, while the scoring system with all the 23 variables had an AUC of 0.736, and a cutoff score of 49 gave a sensitivity of 72.4% and specificity of 63.0%. Conventional thrombolysis in myocardial infarction score and the modified early warning score achieved AUC values of 0.637 and 0.622, respectively.

CONCLUSIONS

It is observed that a few predictors outperformed the whole set of variables in predicting MACE within 72 h. We conclude that more predictors do not necessarily guarantee better prediction results. Furthermore, machine learning-based variable selection seems promising in discovering a few relevant and significant measures as predictors.

Comprehensive standardized data definitions for acute coronary syndrome research in emergency departments in Australasia

Patients with chest discomfort or other symptoms suggestive of acute coronary syndrome are one of the most common categories seen in many Emergency Departments (EDs). Although the recognition of patients at high risk of acute coronary syndrome has improved steadily, identifying the majority of chest pain presentations who fall into the low-risk group remains a challenge. Research in this area needs to be transparent, robust, applicable to all hospitals from large tertiary centres to rural and remote sites, and to allow direct comparison between different studies with minimum patient spectrum bias. A standardized approach to the research framework using a common language for data definitions must be adopted to achieve this. The aim was to create a common framework for a standardized data definitions set that would allow maximum value when extrapolating research findings both within Australasian ED practice, and across similar populations worldwide. Therefore a comprehensive data definitions set for the investigation of non-traumatic chest pain patients with possible acute coronary syndrome was developed, specifically for use in the ED setting. This standardized data definitions set will facilitate 'knowledge translation' by allowing extrapolation of useful findings into the real-life practice of emergency medicine.

One-year outcomes following coronary computerized tomographic angiography for evaluation of emergency department patients with potential acute coronary syndrome

OBJECTIVES

Coronary computerized tomographic angiography (CTA) has high correlation with cardiac catheterization and has been shown to be safe and cost-effective when used for rapid evaluation of low-risk chest pain patients from the emergency department (ED). The long-term outcome of patients discharged from the ED with negative coronary CTA has not been well studied.

METHODS

The authors prospectively evaluated consecutive low- to intermediate-risk patients who received coronary CTA in the ED for evaluation of a potential acute coronary syndrome (ACS). Patients with cocaine use, known cancer, and significant comorbidity reducing life expectancy and those found to have significant disease (stenosis > or = 50% or ejection fraction < 30%) were excluded. Demographics, medical and cardiac history, labs, and electrocardiogram (ECG) results were collected. Patients were followed by telephone contact and record review for 1 year. The main outcome was 1-year cardiovascular death or nonfatal acute myocardial infarction (AMI).

RESULTS

Of 588 patients who received coronary CTA in the ED, 481 met study criteria. They had a mean (+/-SD) age of 46.1 (+/-8.8) years, 63% were black or African American, and 60% were female. There were 53 patients (11%) rehospitalized and 51 patients (11%) who received further diagnostic testing (stress or catheterization) over the subsequent year. There was one death (0.2%; 95% confidence interval [CI] = 0.01% to 1.15%) with unclear etiology, no AMI (0%; 95% CI = 0 to 0.76%), and no revascularization procedures (0%; 95% CI = 0 to 0.76%) during this time period.

CONCLUSIONS

Low- to intermediate-risk patients with a Thrombosis In Myocardial Infarction (TIMI) score of 0 to 2 who present to the ED with potential ACS and have a negative coronary CTA have a very low likelihood of cardiovascular events over the ensuing year.