Predicting Adverse Outcomes in Syncope

Grossman, Shamai A.; Fischer, Christopher; Lipsitz, Lewis A.; Mottley, Lawrence; Sands, Kenneth; Thompson, S; Zimetbaum, Peter; Shapiro, Nathan I.

doi:10.1016/j.jemermed.2007.04.001

Cited by 136 publications

(112 citation statements)

References 20 publications

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“…However, the authors excluded patients with acute identifiable events such as stroke, pneumonia, or myocardial infarction, which renders the algorithm useful only in patients with fall or unknown cause of syncope. The Boston Syncope Criteria was proposed to triage patients with syncope and was shown to have a sensitivity of 97% and specificity of 62% in predicting 30‐day adverse outcomes or critical interventions; however, readmission was not included as an adverse outcome 26. Other models, such as the San Francisco Syncope Rule and Osservatorio Epidemiologico sulla Sincope nel Lazio scores, have been used to risk‐stratify patients for long‐term adverse outcomes.…”

Section: Discussionmentioning

confidence: 99%

Causes and Predictors of 30‐Day Readmission in Patients With Syncope/Collapse: A Nationwide Cohort Study

Kadri

Abuamsha

Nusairat

et al. 2018

JAHA

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BackgroundSyncope accounts for 0.6% to 1.5% of hospitalizations in the United States. We sought to determine the causes and predictors of 30‐day readmission in patients with syncope.Methods and ResultsWe identified 323 250 encounters with a primary diagnosis of syncope/collapse in the 2013–2014 Nationwide Readmissions Database. We excluded patients younger than 18 years, those discharged in December, those who died during hospitalization, hospital transfers, and those whose length of stay was missing. We used multivariable logistic regression analysis to evaluate the association between baseline characteristics and 30‐day readmission. A total of 282 311 syncope admissions were included. The median age was 72 years (interquartile range, 58–83), 53.9% were women, and 9.3% had 30‐day readmission. The most common cause of 30‐day readmissions was syncope/collapse, followed by cardiac, neurological, and infectious causes. Characteristics associated with 30‐day readmissions were age 65 years and older (odds ratio [OR], 0.7; 95% confidence interval [CI], 0.6–0.7), female sex (OR, 0.9; 95% CI, 0.8–0.9), congestive heart failure (OR, 1.5; 95% CI, 1.2–1.9), atrial fibrillation/flutter (OR, 1.3; 95% CI, 1.3–1.4), diabetes mellitus (OR, 1.2; 95% CI, 1.2–1.3), coronary artery disease (OR, 1.2; 95% CI, 1.2–1.3), anemia (OR, 1.4; 95% CI, 1.4–1.5), chronic obstructive pulmonary disease (OR, 1.4; 95% CI, 1.3–1.4), home with home healthcare disposition (OR, 1.5; 95% CI, 1.5–1.6), leaving against medical advice (OR, 1.7; 95% CI, 1.6–1.9), length of stay of 3 to 5 days (OR, 1.5; 95% CI, 1.4–1.6) or >5 days (OR, 2; 95% CI, 1.8–2), and having private insurance (OR, 0.6; 95% CI, 0.6–0.7).ConclusionsThe 30‐day readmission rate after syncope/collapse was 9.3%. We identified causes and risk factors associated with readmission. Future prospective studies are needed to derive risk‐stratification models to reduce the high burden of readmissions.

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Section: Discussionmentioning

confidence: 99%

Causes and Predictors of 30‐Day Readmission in Patients With Syncope/Collapse: A Nationwide Cohort Study

Kadri

Abuamsha

Nusairat

et al. 2018

JAHA

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“…Examples of such rules are the risk stratification of syncope in the emergency department (Rose), San Francisco Syncope Rule (SFSR), and Boston Syncope Rules, 7,8,15 with the SFSR 8 being the only rules that are externally validated.…”

Section: Rulesmentioning

confidence: 99%

“…15 The investigators recruited 362 patients and considered the variables (risk factors) reported in the American College of Emergency Physicians' clinical policy on syncope. 22 Given the presence of at least 1 of the variables, the sensitivity and specificity of the rule was 97% (95% CI 93-100) and 62% (95% CI 56-69), respectively (see Tables 1-3).…”

Section: The Boston Syncope Rulementioning

confidence: 99%

Syncope Risk Stratification in the Emergency Department

Costantino

Furlan

2013

Cardiology Clinics

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An 89-year-old What steps should be taken to deal with a patient presenting at the ED because of a transient loss of consciousness? THE FIRST STEP: IDENTIFYING PATIENTS WITH SYNCOPETo identify the patient with syncope, 3 major issues have to be addressed:Distinguish patients with syncope from those with a transient loss of consciousness (T-LoC) of nonsyncopal origin Differentiate patients with syncope from those having falls Determine how to manage patients presenting with near syncopeThe authors have nothing to disclose.

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“…12,13 In recent years, various prediction rules based on the probability of an adverse outcome after an episode of syncope have been proposed. 3,[14][15][16] However, the San Francisco Syncope Rule, derived by Quinn and colleagues in 2004, 3 is the only prediction rule for serious outcomes that has been validated in a variety of populations and settings. This simple, five-step clinical decision rule is intended to identify patients at low risk of short-term serious outcomes 3,17 (Box 1).…”

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confidence: 99%

San Francisco Syncope Rule to predict short-term serious outcomes: a systematic review

Saccilotto

Nickel²,

Bucher³

et al. 2011

CMAJ

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Background:The San Francisco Syncope Rule has been proposed as a clinical decision rule for risk stratification of patients presenting to the emergency department with syncope. It has been valid ated across various populations and settings. We undertook a systematic review of its accuracy in predicting short-term serious outcomes. Methods:We identified studies by means of systematic searches in seven electronic databases from inception to January 2011. We extracted study data in duplicate and used a bivariate random-effects model to assess the predictive accuracy and test characteristics. Results:We included 12 studies with a total of 5316 patients, of whom 596 (11%) experienced a serious outcome. The prevalence of serious outcomes across the studies varied between 5% and 26%. The pooled estimate of sensitivity of the San Francisco Syncope Rule was 0.87 (95% confidence interval [CI] 0.79-0.93), and the pooled estimate of specificity was 0.52 (95% CI 0.43-0.62). There was substantial between-study heterogeneity (resulting in a 95% prediction interval for sensitivity of 0.55-0.98). The probability of a serious outcome given a negative score with the San Francisco Syncope Rule was 5% or lower, and the probability was 2% or lower when the rule was applied only to patients for whom no cause of syncope was identified after initial evaluation in the emergency department. The most common cause of false-negative classification for a serious outcome was cardiac arrhythmia. Interpretation:The San Francisco Syncope Rule should be applied only for patients in whom no cause of syncope is evident after in itial evaluation in the emergency department. Consideration of all available electrocardiograms, as well as arrhythmia monitoring, should be included in application of the San Francisco Syncope Rule. Between-study hetero geneity was likely due to inconsistent classification of arrhythmia. AbstractSee related commentary by Parry at www.cmaj.ca/lookup

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Predicting Adverse Outcomes in Syncope

Cited by 136 publications

References 20 publications

Causes and Predictors of 30‐Day Readmission in Patients With Syncope/Collapse: A Nationwide Cohort Study

Causes and Predictors of 30‐Day Readmission in Patients With Syncope/Collapse: A Nationwide Cohort Study

Syncope Risk Stratification in the Emergency Department

San Francisco Syncope Rule to predict short-term serious outcomes: a systematic review

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