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

Published online by Cambridge University Press:  04 March 2015

Venkatesh Thiruganasambandamoorthy ,
George A. Wells ,
Erik P. Hess ,
Ekaterina Turko ,
Jeffrey J. Perry  and
Ian G. Stiell
Venkatesh Thiruganasambandamoorthy*
Affiliation:
Department of Emergency Medicine, University of Ottawa, Ottawa, ON The Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON
George A. Wells
Affiliation:
Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON
Erik P. Hess
Affiliation:
Division of Emergency Medicine Research, Department of Emergency Medicine, Mayo Clinic College of Medicine, Rochester, MN
Ekaterina Turko
Affiliation:
Department of Emergency Medicine, University of Ottawa, Ottawa, ON
Jeffrey J. Perry
Affiliation:
Department of Emergency Medicine, University of Ottawa, Ottawa, ON The Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON
Ian G. Stiell
Affiliation:
Department of Emergency Medicine, University of Ottawa, Ottawa, ON The Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, ON Department of Epidemiology and Community Medicine, University of Ottawa, Ottawa, ON
*
Ottawa Health Research Institute, Clinical Epidemiology Unit, The Ottawa Hospital, Civic Campus, 1053 Carling Avenue, 6th Floor, Room F655, Ottawa, ON K1Y 4E9; [email protected]

Abstract

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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 will be a potentially useful clinical decision tool for emergency physicians, may allow judicious use of health care resources, and may improve patient care and safety.

Keywords

emergency departmentrisk scaleserious adverse eventsyncope
Type
Original Research • Recherche originale
Information
Canadian Journal of Emergency Medicine , Volume 16 , Issue 2 , March 2014 , pp. 120 - 130
Copyright
Copyright © Canadian Association of Emergency Physicians 2014

References

REFERENCES

1. Moya, A, Sutton, R, Ammirati, F, et al. Guidelines for the diagnosis and management of syncope (version 2009). Eur Heart J 2009;30:2631–71. [Epub 2009 Aug 27]Google ScholarPubMed
2. Quinn, JV, Stiell, IG, McDermott, DA, et al. Derivation of the San Francisco Syncope Rule to predict patients with shortterm serious outcomes. Ann Emerg Med 2004;43:224–32.CrossRefGoogle ScholarPubMed
3. Quinn, J, McDermott, D, Stiell, I, et al. Prospective validation of the San Francisco Syncope Rule to predict patients with serious outcomes. Ann Emerg Med 2006;47:448–54.Google Scholar
4. Thiruganasambandamoorthy, V, Hess, EP, Alreesi, A, et al. External validation of the San Francisco Syncope Rule in the Canadian setting. Ann Emerg Med 2010;55:464–72.CrossRefGoogle ScholarPubMed
5. Sun, BC, Mangione, CM, Merchant, G, et al. External validation of the San Francisco Syncope Rule. Ann Emerg Med 2007;49:420–7.CrossRefGoogle ScholarPubMed
6. Birnbaum, A, Esses, D, Bijur, P, et al. Failure to validate the San Francisco Syncope Rule in an independent emergency department population. Ann Emerg Med 2008;52:151–9.Google Scholar
7. Cosgriff, TM, Kelly, AM, Kerr, D. External validation of the San Francisco Syncope Rule in the Australian context. CJEM 2007;9:157–61.CrossRefGoogle ScholarPubMed
8. Reed, MJ, Newby, DE, Coull, AJ, et al. The ROSE (Risk Stratification of Syncope in the Emergency Department) study. J Am Coll Cardiol 2010;55:713–21.CrossRefGoogle ScholarPubMed
9. Reed, MJ, Newby, DE, Coull, AJ, et al. The Risk Stratification of Syncope in the Emergency Department (ROSE) pilot study: a comparison of existing syncope guidelines. Emerg Med J 2007;24:270–5.Google Scholar
10. Grossman, SA, Fischer, C, Lipsitz, LA, et al. Predicting adverse outcomes in syncope. J Emerg Med 2007;33:233–9.CrossRefGoogle ScholarPubMed
11. Quinn, J, McDermott, D, Kramer, N, et al. Death after emergency department visits for syncope: how common and can it be predicted? Ann Emerg Med 2008;51:585–90.Google Scholar
12. Rowe, BH, Bond, K, Ospina, MB, et al. Emergency department overcrowding in canada: what are the issues and what can be done? [Technology overview no 21]. Ottawa: Canadian Agency for Drugs and Technologies in Health; 2006. Available at:(accessed July 1, 2013).Google Scholar
13. Thiruganasambandamoorthy, V, Hess, EP, Turko, E, et al. Outcomes in Canadian emergency department syncope patients - are we doing a good job? J Emerg Med 2013;44:321–8.CrossRefGoogle Scholar
14. Costantino, G, Perego, F, Dipaola, F, et al. Short- and longterm prognosis of syncope, risk factors, and role of hospital admission: results from the STePS (Short-Term Prognosis of Syncope) study J Am Coll Cardiol 2008;51:276–83.Google Scholar
15. Sun, BC, Derose, SF, Liang, LJ, et al. Predictors of 30-day serious events in older patients with syncope. Ann Emerg Med 2009;54:769–78.e1-5.Google Scholar
16. Graham, ID, Stiell, IG, McAuley, L, et al. Potential areas for new clinical decision rules: comparison of North America and Europe [abstract]. Acad Emerg Med 1999;6:433.Google Scholar
17. Thiruganasambandamoorthy, V, Stiell, I, Perry, J. Systematic qualitative review of clinical decision rules for syncope in ED for predicting adverse outcomes [poster]. CJEM 2007;9:214.Google Scholar
18. Sheldon, RS, Morillo, CA, Krahn, AD, et al. Standardized approaches to the investigation of syncope: Canadian cardiovascular society position paper. Can J Cardiol 2011;27:246–53.Google Scholar
19. Colivicchi, F, Ammirati, F, Melina, D, et al. Development and prospective validation of a risk stratification system for patients with syncope in the emergency department: the OESIL risk score. Eur Heart J 2003;24:811–9.Google Scholar
20. Gregoratos, G, Abrams, J, Epstein, AE, et al. American College of Cardiology/American Heart Association Task Force on PracticeGuidelines American College ofCardiology/American Heart Association/North American Society for Pacing and Electrophysiology Committee. ACC/AHA/NASPE 2002 guideline update for implantation of cardiac pacemakers and antiarrhythmia devices: summary article. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/NASPE Committee to Update the 1998 Pacemaker Guidelines). J Cardiovasc Electrophysiol 2002;13:1183–99.Google Scholar
21. Thiruganasambandamoorthy, V, Hess, EP, Turko, E, et al. Defining abnormal electrocardiography in adult emergency department syncope patients: the Ottawa Electrocardiographic Criteria. CJEM 2012;14:248–58.Google Scholar
22. Le Gal , G, Righini, M, Roy, PM, et al. Prediction of pulmonary embolism in the emergency department: the revised Geneva score. Ann Intern Med 2006;144:165–71.Google Scholar
23. Hosmer, DW, Lemeshow, S. Applied logistic regression. Wiley; 2000.Google Scholar
24. Scheaffer, RL, Mendenhall, W, Ott, L. Elementary survey sampling. Duxbury Press; 1979.Google Scholar
25. Sarasin, FP, Louis-Simonet, M, Carballo, D, et al. Prospective evaluation of patients with syncope: a population-based study. Am J Med 2001;111:177–84.Google Scholar
26. Martin, TP, Hanusa, BH, Kapoor, WN. Risk stratification of patients with syncope. Ann Emerg Med 1997;29:459–66.Google Scholar
27. Sun, BC, Hoffman, JR, Mangione, CM, Mower, WR. Older age predicts short-term, serious events after syncope. J Am Geriatr Soc 2007;55:907–12.Google Scholar
28. Marti-Almor, J, Cladellas, M, Bazan, V, et al. Long-term mortality predictors in patients with chronic bifascicular block. Europace 2009;11:1201–7.Google Scholar
29. Gilbert, EH, Lowenstein, SR, Koziol-McLain, J, et al. Chart reviews in emergency medicine research: where are the methods? Ann Emerg Med 1996;27:305–8.Google Scholar
30. Worster, A, Bledsoe, RD, Cleve, P, et al. Reassessing the methods of medical record review studies in emergency medicine research. Ann Emerg Med 2005;45:448–51.Google Scholar
31. Badcock, D, Kelly, AM, Kerr, D, Reade, T. The quality of medical record review studies in the international emergency medicine literature. Ann Emerg Med 2005;45:444–7.CrossRefGoogle ScholarPubMed
32. Lowenstein, SR. Medical record reviews in emergency medicine: the blessing and the curse. Ann Emerg Med 2005;45:452–5.Google Scholar
33. Wasson, JH, Sox, HC, Neff, RK, Goldman, L. Clinical prediction rules. Applications and methodological standards. N Engl J Med 1985;313:793–9.Google Scholar
34. Stiell, IG, Wells, GA. Methodologic standards for the development of clinical decision rules in emergency medicine. Ann Emerg Med 1999;33:437–47.Google Scholar
35. Laupacis, A, Sekar, N, Stiell, IG. Clinical prediction rules. A review and suggested modifications of methodological standards. JAMA 1997;277:488–94.CrossRefGoogle ScholarPubMed