Emergency department admissions to inpatient cardiac telemetry beds: a prospective cohort study of risk stratification and outcomes.

PURPOSE: Little is known about physicians' use of inpatient cardiac telemetry units among emergency department patients at risk for cardiac complications. We therefore studied the outcomes of patients admitted to inpatient telemetry beds to identify a subset of patients from whom cardiac monitoring could be withheld safely. SUBJECTS AND METHODS: We conducted a prospective cohort study of 1, 033 consecutive adult patients admitted to an inpatient telemetry unit from the emergency department of a 700-bed urban public teaching hospital. Subjects with or without chest pain were risk-stratified using a prediction rule and observed for in-hospital cardiac complications, acute myocardial infarction, and transfer to an intensive care unit (ICU). RESULTS: There were no significant differences between patients with (n = 677) or patients without chest pain (n = 356) in the rates of major cardiac complications, myocardial infarctions, or transfers to an ICU. Among 318 patients with chest pain who were classified as being very low risk, none suffered major complications (negative predictive value 100%; 95% confidence interval [CI]: 98.8% to 100%). Among 214 very low risk patients without chest pain, 1 (0.5%) had a major complication (negative predictive value 99.5%; 95% CI: 97.4% to 99.9%). CONCLUSIONS: The prediction rule accurately identified patients with or without chest pain who were at very low risk of major complications, identifying a subset from whom cardiac monitoring could be withheld safely.

Performance and potential impact of a chest pain prediction rule in a large public hospital.

PURPOSE: To evaluate the performance of a previously validated prediction rule for patients presenting to the emergency department with chest pain and the potential impact of the rule on triage decisions. SUBJECTS AND METHODS: In a prospective cohort study, physician investigators interviewed consecutive patients admitted for suspected acute ischemic heart disease (n = 207) by emergency department attending physicians who had not used the prediction rule. We measured the accuracy of the rule in predicting cardiac complications in these patients, and compared actual triage decisions with those that might have been recommended by use of the prediction rule. We also measured comorbid illnesses among patients stratified as very low risk by the prediction rule, as well as the effect of standardizing the definition of unstable angina and interpretation of electrocardiograms (ECG) on the rule's sensitivity and specificity. RESULTS: Overall, the rate of major cardiac complications (4.3%) was similar to that reported in the original study (3.6%). The prediction rule performed well in predicting these complications in our patients (area under receiver operating characteristic curve 0.84 versus 0.80 in the original study; difference 0.04, 95% confidence interval [CI] -0.07, 0.14). Standardized definitions of unstable angina and interpretation of ECGs improved the specificity of the prediction rule in predicting complications (55% versus 47%; difference 8%, 95% CI 1.5%, 13.7%). The prediction rule recommended admission to telemetry units in 65 fewer patients than actually occurred (31% of the entire cohort). None of these patients had major complications. A substantial minority of "very low risk" patients (27%) had comorbid illnesses requiring inpatient treatment. CONCLUSIONS: This independent validation of the prediction rule suggests that it can improve triage decisions for patients admitted with suspected acute ischemic heart disease. Additional studies are needed to test prospectively the performance of the prediction rule in actual decision making, its acceptance by clinicians, and its cost effectiveness.