Initial risk stratification and presenting characteristics of patients with evolving myocardial infarctions

Variation in chest pain emergency department admission rates and acute myocardial infarction and death within 30 days in the Medicare population

OBJECTIVES

The objective was to assess the relationship between emergency department (ED) admission rates for Medicare beneficiaries with chest pain and outcomes, specifically 30-day rates of acute myocardial infarction (AMI) and mortality.

METHODS

Using a 20% random sample of Medicare beneficiaries in 2009, 158,295 beneficiaries with a primary diagnosis of chest pain at the conclusion of their ED visits were selected to assess outcomes based on the decision to hospitalize or discharge home. The proportions of these patients admitted to inpatient or observation status at 2,219 U.S. hospitals were calculated, adjusting for differences in patient and hospital characteristics. Both bivariate analysis and multivariable logistic regression were used to estimate the effect of the adjusted admission rates (designed to be a measure of care intensity) on patient outcomes. Other covariates in the multivariable model included patient demographics, medical conditions, and hospital utilization in the 30 days prior to the ED visits. Results from the bivariate and multivariable analyses were compared for consistency.

RESULTS

The adjusted Medicare admission rate for ED patients with chest pain averaged 63% for the middle quintile of the patient sample and ranged from 38% to 81% in the lowest and highest quintiles. The multivariable model yielded estimates of 3.6 fewer cases of AMI (95% confidence interval [CI] = 1.5 to 5.1 cases) and 2.8 fewer deaths (95% CI = 0.6 to 4.1 deaths) per 1,000 chest pain patients associated with an admission rate of 81% versus 38%. The estimates from the bivariate analysis were of similar magnitude.

CONCLUSIONS

Considerable variation exists across U.S. hospitals in ED admission rates for Medicare patients with chest pain. Hospitals that approach admissions more conservatively (i.e., higher admission rates) in this population have lower rates of AMI and mortality.

Sensitivity, specificity, and sex differences in symptoms reported on the 13-item acute coronary syndrome checklist

Background

Clinical symptoms are part of the risk stratification approaches used in the emergency department (ED) to evaluate patients with suspected acute coronary syndromes (ACS). The objective of this study was to determine the sensitivity, specificity, and predictive value of 13 symptoms for a discharge diagnosis of ACS in women and men.

Methods and Results

The sample included 736 patients admitted to 4 EDs with symptoms suggestive of ACS. Symptoms were assessed with the 13‐item validated ACS Symptom Checklist. Mixed‐effects logistic regression models were used to estimate sensitivity, specificity, and predictive value of each symptom for a diagnosis of ACS, adjusting for age, obesity, diabetes, and functional status. Patients were predominantly male (63%) and Caucasian (70.5%), with a mean age of 59.7±14.2 years. Chest pressure, chest discomfort, and chest pain demonstrated the highest sensitivity for ACS in both women (66%, 66%, and 67%) and men (63%, 69%, and 72%). Six symptoms were specific for a non‐ACS diagnosis in both women and men. The predictive value of shoulder (odds ratio [OR]=2.53; 95% CI=1.29 to 4.96) and arm pain (OR 2.15; 95% CI=1.10 to 4.20) in women was nearly twice that of men (OR=1.11; 95% CI=0.67 to 1.85 and OR=1.21; 95% CI=0.74 to 1.99). Shortness of breath (OR=0.49; 95% CI=0.30 to 0.79) predicted a non‐ACS diagnosis in men.

Conclusions

There were more similarities than differences in symptom predictors of ACS for women and men.

The association between self-reported exercise intensity and acute coronary syndrome in emergency department chest pain patients

BACKGROUND

Regular exercise is thought to be protective against coronary artery disease. As a result, some physicians believe that the likelihood of acute coronary syndrome (ACS) in patients with acute chest pain is reduced in those who exercise regularly. We studied the association between self-reported frequency of exercising and the likelihood of ACS in patients presenting to the Emergency Department (ED) with chest pain.

METHODS

A multi-center prospective, descriptive, cohort study design was used in ED patients to determine whether the risk of ACS was reduced in patients who self-reported regular exercise.

RESULTS

There were 1093 patients enrolled. Median (interquartile range) age was 57 (48-67) years; 506 (45.7%) were female. ACS was diagnosed in 248 (22.7%) patients. Patients who did not exercise at least monthly were more likely to be diagnosed with ACS than those who did (129/466 [27.7%] vs. 119/627 [19.0%]; odds ratio 1.63, 95% CI 1.23-2.17). After adjusting for age, gender, body mass index, smoking, and prior history, limited exercise was still associated with ACS (adjusted odds ratio 1.52, 95% CI 1.10-2.10). There was no apparent association between frequency and intensity of exercise and risk of ACS.

CONCLUSION

Although self-reported frequency of exercise was significantly associated with a decrease in ACS in ED patients with chest pain, it should not be used to exclude ACS in symptomatic ED patients.

Classifying subgroups of patients with symptoms of acute coronary syndromes: A cluster analysis

The purpose of the study was to identify subgroups of patients presenting with acute coronary syndromes based on symptom clusters. Two hundred fifty-six patients completed a symptom assessment in their hospital rooms. Latent class cluster analysis and analysis of variance were used to classify subgroups of patients according to selected clinical characteristics. Four subgroups were identified and labeled as Heavy Symptom Burden, Chest Pain Only, Sweating and Weak, and Short of Breath and Weak (model fit χ(2) [130,891, n = 256] = 867.5, p = 1.00). The largest group of patients experienced classic symptoms of chest pain and shortness of breath but not sweating. Younger patients were more likely to cluster in the Heavy Symptom Burden group (F = 5.08, p = .002). Interpretation of the clinical significance of these groupings requires further study.