Performance of risk scores for predicting short-term mortality in acute heart failure patients presenting to the emergency department: a systematic review

Authors

  • Mazi Mohammed Alanazi Emergency Medicine Consultant, Head of Emergency Research Unit, Emergency Department, Riyadh First Health Cluster, Riyadh, Saudi Arabia. ORCID: 0009-0003-5836-8086. Author
  • Abrar Mohammed Albalooshy Medical Intern, College of Medicine, Taibah University, Medina, Saudi Arabia. ORCID: 0009-0000-5258-5440. Email: abrar.m.albaloshi@gmail.com. Author
  • Eithar Khalid Alamri Medical Intern, College of Medicine, Taibah University, Medina, Saudi Arabia. ORCID: 0009-0007-9321-6503. Email: Ethar.k.alamri@gmail.com. Author
  • Mohammed Abdullah Alanazi Medical Intern, College of Medicine, Northern Border University, Arar, Saudi Arabia. ORCID: 0009-0005-7857-7656. Email: mohammed.aalenezii@gmail.com. Author
  • Abdulaziz Mohammed Alsahli Medical Intern, College of Medicine, Shaqra University, Dawadmi, Saudi Arabia. ORCID: 0009-0008-4393-2568. Email: drabdulaziz211200@gmail.com. Author
  • Sultan Haif Aladhyani Medical Student, College of Medicine, Shaqra University, Dawadmi, Saudi Arabia. Email: sltanrooji@icloud.com. Author
  • Mais Abdulrahman Joumani Medical Intern at King Saud University and graduate of Medipol University. Author
  • Taif Ibrahim Alharbi Medical Intern, College of Medicine, Qassim University, Qassim, Saudi Arabia. ORCID: 0009-0001-6350-9088. Email: Taifharbi88@gmail.com. Author
  • Muath Thaar Aladhyani Medical Intern , College of Medicine, Shaqra University, Dawadmi, Saudi Arabia . ORCID :0009-0001-3382-4722 Author

DOI:

https://doi.org/10.65759/aeyemx64

Keywords:

acute heart failure, emergency department, short-term mortality, risk score, prediction model

Abstract

Background: Acute heart failure (AHF) necessitate emergency department (ED) evaluation, where early mortality risk affect monitoring, admission, discharge, and follow-up decisions. Several scores have been proposed and their target outcomes, predictors, and validation settings differ. Objective: To synthesize the discrimination, calibration, and utility of risk scores predicting short-term mortality in patients presenting to EDs with AHF. Methods: Records were identified through PubMed/MEDLINE, Scopus and WOS and citation tracking, with strategies prepared for Scopus, Web of Science, and Cochrane Library through Jun 20, 2026. Eligible studies validated or compared multivariable scores for mortality within 30 days of emergency presentation. Study characteristics, performance and calibration findings, and risk-of-bias domains were narratively synthesized because outcome windows and populations were heterogeneous. Results: We include 19 reports. EHMRG was the most validated score for 7-day mortality, with statistics ranging from 0.73 to 0.81 in Canadian, Spanish, and United States cohorts. MEESSI-AHF showed a strong discrimination for 30-day mortality, between 0.80 and 0.84, although external cohorts identified overprediction in higher-risk groups before recalibration. EAHFE-3D show moderate discrimination for 3-day mortality, with imprecision in smaller external samples. Broader disposition scores incorporated mortality into composite outcomes and offered less direct evidence for death prediction. Conclusions: EHMRG and MEESSI-AHF have the strongest external-validation evidence. Local calibration, predictor availability, and prospective impact evaluation remain essential before disposition use.

References

1. McDonagh TA, Metra M, Adamo M, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J. 2021;42(36):3599–3726. doi:10.1093/eurheartj/ehab368.

2. Ambrosy AP, Fonarow GC, Butler J, et al. The global health and economic burden of hospitalizations for heart failure: lessons learned from hospitalized heart failure registries. J Am Coll Cardiol. 2014;63(12):1123–1133.

3. Lee DS, Schull MJ, Alter DA, et al. Early deaths in patients with heart failure discharged from the emergency department: a population-based analysis. Circ Heart Fail. 2010;3(2):228–235. doi:10.1161/CIRCHEARTFAILURE.109.885285.

4. Miró Ò, Levy PD, Möckel M, et al. Disposition of emergency department patients diagnosed with acute heart failure: an international emergency medicine perspective. Eur J Emerg Med. 2017;24(1):2–12.

5. Michaud AM, Parker SIA, Ganshorn H, et al. Prediction of early adverse events in emergency department patients with acute heart failure: a systematic review. Canadian Journal of Cardiology. 2018;34(2):168–179.

6. Miró Ò, Rossello X, Gil V, et al. Risk stratification scores for patients with acute heart failure in the emergency department: a systematic review. Eur Heart J Acute Cardiovasc Care. 2020;9(5):375–398. doi:10.1177/2048872620930889.

7. Fountoulaki K, Ventoulis I, Dourakis E, et al. Emergency department risk assessment and disposition of acute heart failure patients: existing evidence and ongoing challenges. Heart Fail Rev. 2023;28(4):781–793. doi:10.1007/s10741-022-10272-4.

8. Hsieh M, Auble TE, Yealy DM. Validation of the Acute Heart Failure Index. Ann Emerg Med. 2008;51(1):37–44. doi:10.1016/j.annemergmed.2007.07.026.

9. Lee DS, Stitt A, Austin PC, et al. Prediction of heart failure mortality in emergent care: a cohort study. Ann Intern Med. 2012;156(11):767–775.

10. Stiell IG, Clement CM, Brison RJ, et al. A risk scoring system to identify emergency department patients with heart failure at high risk for serious adverse events. Acad Emerg Med. 2013;20(1):17–26.

11. Collins SP, Jenkins CA, Harrell FE Jr, et al. Identification of emergency department patients with acute heart failure at low risk for 30-day adverse events: the STRATIFY Decision Tool. JACC Heart Fail. 2015;3(10):737–747. doi:10.1016/j.jchf.2015.05.007.

12. Jacob J, Miró Ò, Herrero P, et al. Predicting short-term mortality in patients with acute exacerbation of chronic heart failure: the EAHFE-3D scale. Med Intensiva. 2016;40(6):348–355.

13. Garcia-Gutierrez S, Quintana JM, Antón-Ladislao A, et al. Creation and validation of the acute heart failure risk score: AHFRS. Intern Emerg Med. 2017;12(8):1197–1206. doi:10.1007/s11739-016-1541-4.

14. Miró Ò, Rossello X, Gil V, et al. Predicting 30-day mortality for patients with acute heart failure in the emergency department: a cohort study. Ann Intern Med. 2017;167(10):698–705. doi:10.7326/M16-2726.

15. Stiell IG, Perry JJ, Clement CM, et al. Prospective and explicit clinical validation of the Ottawa Heart Failure Risk Scale, with and without use of quantitative NT-proBNP. Acad Emerg Med. 2017;24(3):316–327. doi:10.1111/acem.13141.

16. Gil V, Miró Ò, Schull MJ, et al. Emergency Heart Failure Mortality Risk Grade score performance for 7-day mortality prediction in patients with heart failure attended at the emergency department: validation in a Spanish cohort. Eur J Emerg Med. 2018;25(3):169–177.

17. García-Gutiérrez S, Quintana López JM, Antón-Ladislao A, et al. External validity of a prognostic score for acute heart failure based on the Epidemiology of Acute Heart Failure in Emergency Departments Registry: the EAHFE-3D scale. Emergencias. 2018;30(2):84–90.

18. Lee DS, Lee JS, Schull MJ, et al. Prospective validation of the Emergency Heart Failure Mortality Risk Grade for acute heart failure. Circulation. 2019;139(9):1146–1156. doi:10.1161/CIRCULATIONAHA.118.035509.

19. Wussler D, Kozhuharov N, Sabti Z, et al. External validation of the MEESSI Acute Heart Failure Risk Score: a cohort study. Ann Intern Med. 2019;170(4):248–256. doi:10.7326/M18-1967.

20. Sepehrvand N, Youngson E, Bakal JA, et al. External validation and refinement of Emergency Heart Failure Mortality Risk Grade risk model in patients with heart failure in the emergency department. CJC Open. 2019;1(3):123–130. doi:10.1016/j.cjco.2019.03.003.

21. Rossello X, Bueno H, Gil V, et al. MEESSI-AHF risk score performance to predict multiple post-index event and post-discharge short-term outcomes. Eur Heart J Acute Cardiovasc Care. 2021;10(2):142–152.

22. Garg N, Pekmezaris R, Stevens G, et al. Performance of Emergency Heart Failure Mortality Risk Grade in the emergency department. West J Emerg Med. 2021;22(3):672–677. doi:10.5811/westjem.2021.1.48978.

23. Austin DE, Lee DS, Wang CX, et al. Comparison of machine learning and the regression-based EHMRG model for predicting early mortality in acute heart failure. Int J Cardiol. 2022;365:78–84. doi:10.1016/j.ijcard.2022.07.035.

24. Nelson DM, Madsen BE, Kopecky SL, et al. Retrospective validation of acute heart failure risk stratification in the emergency department. Heart Lung. 2023;57:31–40. doi:10.1016/j.hrtlng.2022.08.005.

25. Stiell IG, Perry JJ, Clement CM, et al. The HEARTRISK6 Scale: predicting short-term serious outcomes for emergency department patients with acute heart failure. JACC Adv. 2024;3(7):100988. doi:10.1016/j.jacadv.2024.100988.

26. Ünlü B, Demir O, Özpolat Ç, et al. External prognostic validation of the EHMRG score for risk stratification and disposition decisions in acute heart failure. BMC Emerg Med. 2026;26(1):145. doi:10.1186/s12873-026-01573-0.

27. Van Calster B, McLernon DJ, van Smeden M, Wynants L, Steyerberg EW. Calibration: the Achilles heel of predictive analytics. BMC Med. 2019;17(1):230. doi:10.1186/s12916-019-1466-7.

28. Moons KGM, Wolff RF, Riley RD, et al. PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration. Ann Intern Med. 2019;170(1):W1–W33. doi:10.7326/M18-1377.

29. Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis: the TRIPOD Statement. Ann Intern Med. 2015;162(1):55–63. doi:10.7326/M14-0697.

Downloads

Published

2026-08-30

Issue

Vol. 3 No. 3 (2026): Journal of Tazeez for Public Health

Section

Articles