Relationship Between Electrical Risk Score and Obstructive Sleep Apnea

Year 2025, Volume: 15 Issue: 3, 364 - 370, 05.01.2026

Doğan İliş , Ayça Arslan , İnanç Artaç , Muammer Karakayalı , Ömer Kertmen , İhsan Topaloğlu , Çağrı Atasoy , Yüksel Erata , Yavuz Karabağ , İbrahim Rencüzoğulları

Abstract

Aim: The most common type of sleep disordered breathing in industrial societies is obstructive sleep apnea (OSA). The Electrical Risk Score (ERS) comprises 6 distinct electrocardiographic parameters, each representing aspects of the heart’s electrical activity and structural damage. Our study aimed to investigate the association between the ERS and the severity of OSA in patients diagnosed with OSA.
Material and Methods: This retrospective study included 255 patients diagnosed with OSA after polysomnography. The patients were then divided into three groups based on apnea-hypopnea index (AHI). The groups were analyzed based on clinical, laboratory, and electrocardiogram (ECG) characteristics.
Results: When we compared the groups, OSA was significantly associated with hypertension (HT) (p <0.001) and a higher body mass index (BMI) (p=0.003). Group 3 showed a statistically higher ERS value (p <0.001), higher heart rate (p <0.001), increased electrocardiographic left ventricular hypertrophy (LVH) rates (p <0.001), a delayed QRS transition zone (p <0.001), prolonged QTc (p <0.001), a larger QRS-T angle (p=0.005), and a longer Tpeak- Tend interval (p <0.001).
Conclusion: Our study showed that ERS is linked to OSA severity and acts as an independent predictor of severe OSA.

Keywords

obstructive sleep apnea OSA , electrical risk score ERS , sleep disorders

References

• 1. Somers VK, White DP, Amin R, Abraham WT, Costa F, Culebras A, et al. Sleep apnea and cardiovascular disease: an American Heart Association/American College of Cardiology Foundation Scientific Statement from the American Heart Association Council for High Blood Pressure Research Professional Education Committee, Council on Clinical Cardiology, Stroke Council, and Council on Cardiovascular Nursing. J Am Coll Cardiol. 2008;52(8):686–717.
• 2. Punjabi NM. The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc. 2008;5(2):136–43.
• 3. Morsy NE, Farrag NS, Zaki NFW, Badawy AY, Abdelhafez SA, El-Gilany AH, et al. Obstructive sleep apnea: personal, societal, public health, and legal implications. Rev Environ Health. 2019;34(2):153–169.
• 4. Sharma H, Sharma KK. An algorithm for sleep apnea detection from single-lead ECG using Hermite basis functions. Comput Biol Med. 2016;77:116–24.
• 5. Wang L, Lin Y, Wang J. Computer Methods and Programs in Biomedicine A RR interval based automated apnea detection approach using residual network. Comput Methods Programs Biomed. 2019;176:93–104.
• 6. Hassan AR, Haque MA. Computer-aided obstructive sleep apnea screening from single-lead electrocardiogram using statistical and spectral features and bootstrap aggregating. Biocybernetics and Biomedical Engineering. 2016;36(1):25666.
• 7. Sharma H, Sharma KK. Sleep apnea detection from ECG using variational mode decomposition. Biomed Phys Eng Express. 2020;6(1):015026.
• 8. Elmas AN, Fedai H, Toprak K, Taşcanov MB, Altıparmak İH, Biçer A, et al. The Association of Electrical Risk Score with Prognosis in Patients with Non-ST Elevation Myocardial Infarction Undergoing Coronary Angiography. Anatol J Cardiol. 2024;29(1):11–8.
• 9. Aro AL, Reinier K, Rusinaru C, Uy-Evanado A, Darouian N, Phan D, et al. Electrical risk score beyond the left ventricular ejection fraction: prediction of sudden cardiac death in the Oregon Sudden Unexpected Death Study and the Atherosclerosis Risk in Communities Study. Eur Heart J. 2017;38(40):3017–3025.
• 10. Öncel CR, Çoner A, Köseoğlu C. Determining ECG Parameters for Electrical Risk Score in Patients with Non-ST Elevation Myocardial Infarction. Anatol J Cardiol. 2025;29(5):265–6.
• 11. Piccirillo G, Moscucci F, Mastropietri F, Di Iorio C, Mariani MV, Fabietti M, et al. Possible predictive role of electrical risk score on transcatheter aortic valve replacement outcomes in older patients: preliminary data. Clin Interv Aging. 2018;13:16571667.
• 12. Atilan Fedai U, Fedai H, Tanriverdi Z. Cardiac Clues in Major Depressive Disorder: Evaluating Electrical Risk Score as a Predictive Electrocardiography Biomarker. Medicina (Kaunas). 2025;61(6):1026.
• 13. Rautaharju PM, Surawicz B, Gettes LS, Bailey JJ, Childers R, Deal BJ, et al. American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; American College of Cardiology Foundation; Heart Rhythm Society. AHA/ACCF/HRS recommendations for the standardization and interpretation of the electrocardiogram: Part IV. the ST segment, T and U waves, and the QT interval: a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society. Endorsed by the International Society for Computerized Electrocardiology. J Am Coll Cardiol. 2009;53(11):982–91.
• 14. You Z, He T, Ding Y, Yang L, Jiang X, Huang L. Predictive value of electrocardiographic left ventricular hypertrophy in the general population: A meta-analysis. J Electrocardiol. 2020 SepOct;62:14–19.
• 15. Mirvis DM, Goldberger AL. Electrocardiography. In: Libby P, Bonow RO, Mann DL, Zipes DP, eds. Braunwald’s Heart Disease. A Textbook of Cardiovascular Medicine. 8th ed. Philadelphia: Saunders Elsevier;2008:149 193.
• 16. Colluoglu T, Tanriverdi Z, Unal B, Ozcan EE, Dursun H, Kaya D. The role of baseline and post-procedural frontal plane QRS-T angles for cardiac risk assessment in patients with acute STEMI. Ann Noninvasive Electrocardiol. 2018;23(5):e12558. (10. 1111/anec. 12558)
• 17. Jennum, Pc, and Renata L. Riha. “Epidemiology of sleep apnoea/hypopnoea syndrome and sleep-disordered breathing. ” European Respiratory Journal 33. 4(2009):907–914.
• 18. American Academy of Sleep Medicine. “International classification of sleep disorders—third edition (ICSD-3). ” AASM Resour Libr 281(2014):2313.
• 19. Riha, Renata L. “Diagnostic approaches to respiratory sleep disorders. ” Journal of thoracic disease 7. 8(2015):1373.
• 20. Hou H, Zhao Y, Yu W, Dong H, Xue X, Ding J, Xing W, Wang W. Association of obstructive sleep apnea with hypertension: A systematic review and meta-analysis. J Glob Health. 2018;8(1):010405.
• 21. Foster GE, Brugniaux JV, Pialoux V, Duggan CT, Hanly PJ, Ahmed SB, Poulin MJ. Cardiovascular and cerebrovascular responses to acute hypoxia following exposure to intermittent hypoxia in healthy humans. J Physiol. 2009;587(Pt 13):328799.
• 22. Dudenbostel T, Calhoun DA. Resistant hypertension, obstructive sleep apnoea and aldosterone. J Hum Hypertens. 2012;26(5):281–7.
• 23. Loube DI, Loube AA, Erman MK. Continuous positive airway pressure treatment results in weight less in obese and overweight patients with obstructive sleep apnea. J Am Diet Assoc. 1997;97(8):896–7.
• 24. Peppard PE, Young T, Palta M, Dempsey J, Skatrud J. Longitudinal study of moderate weight change and sleepdisordered breathing. JAMA. 2000b;284(23):3015–21.
• 25. Tasali E, Pamidi S, Covassin N, Somers VK. Obstructive Sleep Apnea and Cardiometabolic Disease: Obesity, Hypertension, and Diabetes. Circ Res. 2025;137(5):764–787.
• 26. Fathima S, Ahmed M. Data driven phenotyping and longitudinal feature modeling of sleep apnea subtypes using interpretable machine learning. Sleep Epidemiology. 2025;5:100113.
• 27. Patel N, Donahue C, Shenoy A, Patel A, El-Sherif N. Obstructive sleep apnea and arrhythmia: a systemic review. Int J Cardiol. 2017;228:967–970