Syncope is a common reason for emergency department (ED) visits, and patients are often admitted to exclude syncope of cardiovascular origin. Population-based data on patterns and predictors of cardiac outcomes may improve decision-making. Our objective was to identify patterns and predictors of short-term cardiac outcomes in ED patients with syncope. Administrative data from an integrated health system of 11 Southern California EDs were used to identify cardiac outcomes after ED presentation for syncope from January 1, 2002, to December 31, 2005. Syncope and cause of death were identified by codes from the International Classification of Disease, Ninth Revision . Cardiac outcomes included cardiac death and hospitalization or procedure consistent with ischemic heart disease, valvular disease, or arrhythmia. Predictors of cardiac outcomes were identified through multivariate logistic regression. There were 35,330 adult subjects who accounted for 39,943 ED visits for syncope. Risk of cardiac outcome sharply decreased following the 7 days after syncope. A 7-day cardiac outcome occurred in 893 cases (3%). Positive predictors of 7-day cardiac outcomes included age ≥60 years, male gender, congestive heart failure, ischemic heart disease, cardiac arrhythmia, and valvular heart disease. Negative predictors included dementia, pacemaker, coronary revascularization, and cerebrovascular disease. There was an age-dependent relation between 7-day cardiac outcomes and arrhythmia and valvular disease, with younger patients (<60 years of age) having greater risk of an event compared to their same-age counterparts. In conclusion, ED decision-making should focus on risk of cardiac event in the first 7 days after syncope and special attention should be given to younger patients with cardiac co-morbidities.
Emergency department (ED) evaluation of syncope may benefit from improved epidemiologic understanding of patterns and predictors of short-term cardiac events. Previous studies have examined risk factors at 1 year after an episode of syncope, a time frame not ideal for decision-making in the acute-care setting. Recent cohort studies identifying predictors of short-term (7 to 30 days) events after syncope are relatively small (n = 444 to 791) and reported prediction models have limited stability and generalizability. In this retrospective cohort study, we describe patterns and predictors of short-term cardiac outcomes after ED visits for syncope. We studied a population-based, managed-care cohort receiving care from a regional, integrated health system. Cardiac outcomes included cardiac death and hospitalizations and procedures consistent with a diagnosis of arrhythmia, ischemic heart disease, and valvular heart disease.
Methods
Kaiser Permanente Southern California (Pasadena, California) is an integrated health system that provides comprehensive care to 3.1 million members throughout Southern California. Health care is delivered at 12 medical centers and >100 outpatient clinics. At the time of the study, 11 health system EDs were available to members. All members have similar health care benefits, including coverage of emergency services within and outside the health system. Electronic administrative databases track all health care encounters within the health system. A claims reimbursement system tracks health care provided at outside facilities. Detailed information on diagnoses and procedures are available regardless of setting. Laboratory, pharmacy, and other specialized databases provide information on clinical care. All members are assigned a unique medical record number that is used for data linkage.
Study subjects were members of Kaiser Permanente Southern California with ≥1 ED visit for syncope from January 1, 2002, to December 31, 2005. Subjects were restricted to an age ≥18 years due to the different nature of syncope in children. ED visits within and external to the health system were included. A subject had to be a member of the health plan at the time of the ED visit; however, no minimum health plan enrollment period was required.
Syncope was identified by International Classification of Disease, Ninth Revision (ICD-9) code 780.2, “syncope and collapse,” among all ED diagnoses of Kaiser and non-Kaiser facilities. Cases with multiple diagnoses in addition to syncope were included. To validate the accuracy of these codes, blinded physician chart review was performed on consecutive ED visits (n = 100) with and without a diagnosis code consistent with syncope. Compared to physician chart review, ICD-9 codes demonstrated a positive predictive value of 92% and a negative predictive value of 100%.
Demographic information on date of birth, age, gender, and race were obtained from administrative databases. Co-morbid conditions were used to classify risk in subanalyses. We obtained information on major co-morbid conditions related to syncope using data available from the health plan within the observation period and during the ED visit. Case-identification criteria for diabetes included a combination of inpatient and outpatient diagnosis and procedural codes, medications, and laboratory tests. Identification of other co-morbidities was based solely on diagnosis and procedural codes. History of arrhythmia was based on ICD-9 codes signifying ventricular tachycardia, ventricular fibrillation/flutter, type II Mobitz heart block, anomalous atrioventricular excitation, paroxysmal atrial tachycardia, atrial flutter, atrial fibrillation, or sinoatrial node dysfunction. A subject was noted to have a history of syncope if there was an ED visit for syncope within 30 days preceding the index ED visit.
The primary outcome was a 7-day cardiac outcome occurring after an ED visit for syncope. Cardiac outcomes included cardiac death and hospitalizations or procedures consistent with an arrhythmia, ischemic heart disease, and valvular heart disease. Mortality and cause-of-death data were identified through linked California vital statistics files. A death was classified as cardiac in origin if the ICD-9 cause of death code indicated ischemic heart disease, arrhythmia, cardiac valve disease, or congestive heart failure.
We defined arrhythmic events as a hospitalization with primary discharge code consistent with arrhythmia or procedure codes consistent with insertion or revision of a cardiac pacemaker or an implantable cardioverter–defibrillator (AICD). Ischemic heart events included hospitalization with a primary discharge diagnosis of myocardial infarction or unstable angina or procedure codes consistent with coronary artery bypass graft surgery or percutaneous transluminal coronary angioplasty. We defined valvular heart events as hospitalization with a primary discharge diagnosis of valve disease or procedure codes consistent with valve replacement or revision.
Analyses were conducted to identify the risk of a cardiac outcome after an ED visit for syncope. For subjects with multiple ED visits for syncope, counts over time were determined using the first visit within the study period. The association of co-morbidities and a cardiac outcome at 7 days was examined by Fischer’s exact test. Hazard functions were prepared for age groups to examine the absolute probability of an event as a function of time after syncope. Risk by age was examined for ages 18 to 39, 40 to 59, 60 to 79, and ≥80 years. Cause of death was examined using ICD-9 and ICD-10 codes from death certificates. Reliability of ICD grouping to identify cardiac death was assessed by physician chart review (blinded to ICD cause of death code) of 60 inpatient deaths occurring after syncope (kappa = 0.7).
Hazard plots were examined for 7, 30, 180, and 365 days and suggested that excess cardiac risk was concentrated in the first 7 days after syncope, the time frame used for subsequent risk modeling. Logistic regression results were used to help guide subgroup analysis of hazard functions, such as the risk relation between age groups and having a cardiac co-morbidity. Multiple ED visits by the same subject were controlled for in regression analyses. Coefficient SEs were adjusted for subject correlation (i.e., clustering) using robust variance estimates. Predictors of 7-day cardiac outcomes were identified through multivariate logistic regression. Univariate analyses suggested a step increase in risk at 60 years of age, and subsequent models dichotomized age at this threshold. Interactions were tested between age and cardiac co-morbidities. The final model used statistically (i.e., p <0.05) and clinically significant covariates and interactions to identify the predictors of a 7-day cardiac outcome.
Sensitivity analyses were conducted to evaluate the robustness of our model. Additional models were constructed with the same predictors and distinct outcomes of cardiac death, atherosclerotic event, or arrhythmic event. The 3 models were qualitatively similar to the combined-outcomes model. Valvular events were not modeled because of too few events to perform reliable modeling. Our model also evaluated 30-day combined cardiac outcomes. The predictors in this modified model were also very similar in their significance and direction of effect. To improve interpretability of our findings, we present only results of the combined 7-day cardiac events model.
All analyses were conducted at Kaiser Permanente Southern California’s department of research using SAS 9.1 (SAS Institute, Cary, North Carolina). The study protocol was reviewed and approved by the institutional review board of Kaiser Permanente Southern California and the University of California, Los Angeles.
Results
Over the 4-year observation period, there were 35,330 subjects who accounted for 39,943 ED visits for syncope. There were 893 7-day cardiac outcomes, representing an event rate of 2.5% ( Table 1 ). Ninety percent of subjects had 1 visit for syncope; the number of syncope visits was 1 to 12 per subject. Table 2 lists types of cardiac events at 7 days. Of the 893 subjects who had a cardiac event, most outcomes were caused by arrhythmias (63%). There were several subjects who had multiple categories of cardiac outcomes.
| Characteristics | Cohort | Developed 7-d Cardiac Outcome | No 7-d Cardiac Outcome | p Value |
|---|---|---|---|---|
| (n = 35,330) | (n = 893) | (n = 34,437) | ||
| Age (years), mean ± SD | 60.1 ± 21 | 73.3 ± 13 | 59.8 ± 21 | <0.0001 |
| Women | 19,751 (56%) | 369 (41%) | 19,382 (56%) | <0.0001 |
| White | 16,583 (47%) | 582 (65%) | 16,001 (46%) | <0.0001 |
| Black | 4,140 (12%) | 104 (12%) | 4,036 (12%) | <0.0001 |
| Asian or Pacific Islander | 1,590 (5%) | 44 (5%) | 1,546 (4%) | <0.0001 |
| Hispanic | 5,756 (16%) | 112 (13%) | 5,644 (16%) | <0.0001 |
| Other, multiple, unknown | 7,261 (21%) | 51 (6%) | 7,210 (21%) | <0.0001 |
| Diabetes mellitus | 7,425 (21%) | 301 (34%) | 7,124 (21%) | <0.0001 |
| Hypertension | 19,293 (55%) | 711 (80%) | 18,582 (54%) | <0.0001 |
| Heart failure | 4,709 (13%) | 347 (39%) | 4,362 (13%) | <0.0001 |
| Arrhythmia | 5,996 (17%) | 512 (57%) | 5,484 (16%) | <0.0001 |
| Pacemaker or implantable cardioverter–defibrillator | 1,538 (4%) | 99 (11%) | 1,439 (4%) | <0.0001 |
| Valvular heart disease | 3,051 (9%) | 212 (24%) | 2,839 (8%) | <0.0001 |
| Percutaneous transluminal coronary angioplasty or coronary artery bypass graft surgery | 1,622 (5%) | 109 (12%) | 1,513 (4%) | <0.0001 |
| Myocardial infarction | 2,386 (7%) | 246 (28%) | 2,140 (6%) | <0.0001 |
| Cerebrovascular disease | 3,124 (9%) | 124 (14%) | 3,000 (9%) | <0.0001 |
| Seizure history | 2,004 (6%) | 65 (7%) | 1,939 (6%) | 0.0355 |
| Dementia | 2,373 (7%) | 70 (8%) | 2,303 (7%) | 0.1748 |
| Outcome Type | No. (%) ⁎ |
|---|---|
| Total cardiac events | 893 |
| Cardiac death | 135 (15%) |
| Arrhythmia | |
| Hospital admission | 560 (63%) |
| Device placement | 269 (30%) |
| Ischemic heart disease | |
| Hospital admission | 231 (26%) |
| Revascularization | 117 (13%) |
| Valvular heart disease | |
| Hospital admission | 27 (3%) |
| Valve procedure | 27 (3%) |
Figures 1 and 2 illustrate the absolute probability of cardiac event after ED visit for syncope. There is a marked increase in risk within the first 3 days, with return to baseline risk across all age groups following the first 7 days.
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
