Development and prospective validation of a risk stratification system for patients with syncope in the emergency department: the OESIL risk score

Colivicchi, Furio; Ammirati, Fabrizio; Melina, D; Guido, Vincenzo; Imperoli, Giuseppe; Santini, Massimo

doi:10.1016/j.accreview.2003.08.093

Cited by 46 publications

(86 citation statements)

References 9 publications

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“…OESIL risk score OESIL was published in 2003 23 based on a derivation cohort in which Colivicchi and colleagues 23 recruited 270 patients presenting to ED for syncope. The validation cohort was subsequently based on 328 individuals.…”

Section: Scoresmentioning

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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Section: Scoresmentioning

confidence: 99%

Syncope Risk Stratification in the Emergency Department

Costantino

Furlan

2013

Cardiology Clinics

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“…[1][2][3][4][5] It represents a common clinical problem, accounting for 1%-3% of visits to the emergency department and up to 6% of admissions to acute care hospitals. 6,7 Assessment of syncope in patients presenting to the emergency department is challenging because of the heterogeneity of underlying pathophysiologic processes and diseases.…”

mentioning

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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“…Age has been shown to be an important predictor of SAEs. 2,19,[25][26][27] Shortness of breath has been found to be an important variable in both our study and the San Francisco Syncope Rule (SFSR) study, and in our study, it was a marker of underlying life-threatening conditions such as pulmonary embolism or massive pleural effusion. We found that patients with systolic BP , 80 mm Hg during the ED stay typically had ongoing gastrointestinal bleeding or sepsis.…”

Section: Discussionmentioning

confidence: 83%

“…1,2,17,19,20 The principal investigator (V.T.) and a trained research assistant blinded to the patient outcomes collected patient demographics, event characteristics, comorbidities, vital signs, physical examination findings, ambulance ECG strip, ED ECG characteristics, ambulance and ED cardiac monitor abnormalities, results of investigations, and disposition from photocopies of patients' prehospital, nursing, and physician medical records.…”

Section: Study Protocol and Data Abstractionmentioning

confidence: 99%

Derivation of a risk scale and quantification of risk factors for serious adverse events in adult emergency department syncope patients

Thiruganasambandamoorthy

Wells

Hess

et al. 2014

CJEM

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Background: Determining the appropriate disposition of emergency department (ED) syncope patients is challenging. Previously developed decision tools have poor diagnostic test characteristics and methodological flaws in their derivation that preclude their use. We sought to develop a scale to risk-stratify adult ED syncope patients at risk for serious adverse events (SAEs) within 30 days. Methods: We conducted a medical record review to include syncope patients age $ 16 years and excluded patients with ongoing altered mental status, alcohol or illicit drug use, seizure, head injury leading to loss of consciousness, or severe trauma requiring admission. We collected 105 predictor variables (demographics, event characteristics, comorbidities, medications, vital signs, clinical examination findings, emergency medical services and ED electrocardiogram/monitor characteristics, investigations, and disposition variables) and information on the occurrence of predefined SAEs. Univariate and multiple logistic regression analyses were performed. Results: Among 505 enrolled patient visits, 49 (9.7%) suffered an SAE. Predictors of SAE and their resulting point scores were as follows: age $ 75 years (1), shortness of breath (2), lowest ED systolic blood pressure , 80 mm Hg (2), Ottawa Electrocardiographic Criteria present (2), and blood urea nitrogen . 15 mmol/L (3). The final score calculated by addition of the individual scores for each variable (range 0-10) was found to accurately stratify patients into low risk (score , 1, 0% SAE risk), moderate risk (score 1, 3.7% SAE risk), or high risk (score . 1, $ 10% SAE risk). Conclusion: We derived a risk scale that accurately predicts SAEs within 30 days in ED syncope patients. If validated, this

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Development and prospective validation of a risk stratification system for patients with syncope in the emergency department: the OESIL risk score

Cited by 46 publications

References 9 publications

Syncope Risk Stratification in the Emergency Department

Syncope Risk Stratification in the Emergency Department

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

Derivation of a risk scale and quantification of risk factors for serious adverse events in adult emergency department syncope patients

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