For less frequent events, the clinician can consider an implantable loop recorder (ILR).3 In a study of 167 individuals without a clear cause of syncope after initial evaluation, diagnosis was achieved in 90% of patients after one year of monitoring by ILR.9
Among individuals in whom the etiology remains unclear, tilt-table testing is often considered. This modality remains controversial and is unlikely to establish a diagnosis in individuals with an otherwise normal evaluation.3 Electrophysiologic testing is of similarly low yield in individuals with otherwise normal evaluation and is generally not recommended, except in individuals with known heart disease, including history of MI, congestive heart failure (CHF), and pre-excitation.10
Diagnostic algorithms: Algorithm-driven diagnostic protocols for evaluation of syncope do exist, but they are generally based on expert consensus opinion rather than large-scale studies. There are evidence-based syncope risk scores under development, but definitive validation is forthcoming. Examination of two such protocols is provided here.
The San Francisco Syncope Rule is among the most well-known algorithms, and predicts adverse outcomes at seven days. The study cohort included 684 patients presenting with syncope to an academic ED. Adverse outcomes, including death, myocardial infarction, arrhythmia, pulmonary embolus, stroke, subarachnoid hemorrhage, ED return, or hospitalization at seven days, were identified. History of CHF, hematocrit less than 30%, ECG abnormality, shortness of breath, and SBP less than 90 mmHg at presentation were associated with increased risk of an adverse outcome. If any of these findings is present, a patient is considered at high risk for adverse outcome at one week.2 The rule is simple to use; however, external validation has been controversial.
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In another risk-prediction study—a large multicenter study of patients older than 60—age greater than 90 years, male sex, history of arrhythmia, SBP greater than 160 mm Hg, ECG abnormality, and elevated troponin I were used to construct a score for risk stratification.11 Specific ECG abnormalities included nonsinus rhythm, heart rate less than 40 beats per minute, evidence of acute or chronic ischemic heart disease, prolonged QRS or QT, left or right ventricular hypertrophy, left-axis deviation, and bundle-branch block. Notably, in this older cohort, CHF (specifically, systolic dysfunction with ejection fraction less than 40%) was not significantly associated with risk of adverse event at 30 days. Study authors stratified participants into low- (score ≤0), intermediate- (score 1-2), and high-risk groups (score >2), with 30-day risk of an adverse event ranging from 2.5% to 20%.
One caveat to the interpretation of these data is the fact that even in the “low risk” group, risk of adverse event was still 2.5%, a figure that many clinicians might consider intolerably high.11 This risk score has not been externally validated.
Back to the Case
Our patient was admitted to the inpatient medicine service. She was monitored overnight on telemetry without evidence of arrhythmia. Collateral history revealed new use of multiple antihypertensives prescribed by outside providers, including both atenolol and propranolol. Her subdural hematoma was managed conservatively and she remained free of neurologic deficits. On discharge, her hypertension regimen was simplified. She was referred for outpatient stress echocardiogram.
Bottom Line
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Detailed history and physical exam, including postural vital signs, should form the backbone of the routine evaluation of syncope. An ECG is a critical—and inexpensive—initial diagnostic test, while inpatient telemetry, although a routine component of inpatient evaluation, is expensive and relatively low-yield. Risk prediction rules might ultimately help guide admission decisions and inpatient workup, but definitive external validation of these rules has yet to be accomplished. TH
Dr. Wander is a resident in the Department of Medicine at the University of Washington School of Medicine in Seattle. Dr. Best is an assistant professor of medicine in the Division of General Internal Medicine at the University of Washington School of Medicine.