Red Blood Cell Distribution Width Improves Reclassification of Patients Admitted to the Emergency Department with Acute Decompensated Heart Failure

Open access


The usual history of chronic heart failure (HF) is characterized by frequent episodes of acute decompensation (ADHF), needing urgent management in the emergency department (ED). Since the diagnostic accuracy of routine laboratory tests remains quite limited for predicting short-term mortality in ADHF, this retrospective study investigated the potential significance of combining red blood cell distribution width (RDW) with other conventional tests for prognosticating ADHF upon ED admission. We conducted a retrospective study including visits for episodes of ADHF recorded in the ED of the Uni versity Hospital of Verona throughout a 4-year period. Demo - graphic and clinical features were recorded upon patient presentation. All patients were subjected to standard Chest X-ray, electrocardiogram (ECG) and laboratory testing in - cluding creatinine, blood urea nitrogen, B-type natriuretic peptide (BNP), complete blood cell count (CBC), sodium, chloride, potassium and RDW. The 30-day overall mortality after ED presentation was defined as primary endpoint. Results: The values of sodium, creatinine, BNP and RDW were higher in patients who died than in those who survived, whilst hypochloremia was more frequent in patients who died than in those who survived. The multivariate model, incorporating these parameters, displayed a modest efficiency for predicting 30-day mortality after ED admission (AUC, 0.701; 95% CI, 0.662-0.738; p=0.001). Notably, the inclusion of RDW in the model significantly enhanced prediction efficiency, with an AUC of 0.723 (95% CI, 0.693-0.763; p<0.001). These results were confirmed with net reclassification improvement (NRI) analysis, showing that combination of RDW with conventional laboratory tests resulted in a much better prediction performance (net reclassification index, 0.222; p=0.001). The results of our study show that prognostic assessment of ADHF patients in the ED can be significantly improved by combining RDW with other conventional laboratory tests.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • 1. Blecker S Paul M Taksler G Ogedegbe G Katz S. Heart failure-associated hospitalizations in the United States. J Am Coll Cardiol 2013; 61: 1259-67.

  • 2. Munir MB Sharbaugh MS Thoma FW Nisar MU Kam - ran AS Althouse AD et al. Trends in hospitalization for congestive heart failure 1996-2009. Clin Cardiol 2017; 40: 109-19.

  • 3. Roger VL. Epidemiology of heart failure. Circ Res 2013; 113: 646-59.

  • 4. Castello LM Molinari L Renghi A Peruzzi E Capponi A Avanzi GC et al. Acute decompensated heart failure in the emergency department: identification of early predictors of outcome. Medicine (Baltimore) 2017; 96: e7401.

  • 5. Lassus JP Siirilä-Waris K Nieminen MS Tolonen J Tarv - asmäki T Peuhkurinen K et al. Long-term survival after hospitalization for acute heart failure - differences in prog - nosis of acutely decompensated chronic and new-onset acute heart failure. Int J Cardiol 2013; 168: 458-62.

  • 6. McIlvennan CK Allen LA. Outcomes in acute heart failure: 30-day readmission versus death. Curr Heart Fail Rep 2014; 11: 445-52.

  • 7. Sperry BW Ruiz G Najjar SS. Hospital readmission in heart failure a novel analysis of a longstanding problem. Heart Fail Rev 2015; 20: 251-8.

  • 8. Demissei BG Postmus D Cleland JG O'Connor CM Metra M Ponikowski P et al. Plasma biomarkers to predict or rule out early post-discharge events after hospitalization for acute heart failure. Eur J Heart Fail 2017; 19: 728-38.

  • 9. Novack V Pencina M Zahger D Fuchs L Nevzorov R Jotkowitz A et al. Routine laboratory results and thirty day and one-year mortality risk following hospitalization with acute decompensated heart failure. PLoS One 2010; 5: e12184.

  • 10. Hill SA Booth RA Santaguida PL Don-Wauchope A Brown JA Oremus M et al. Use of BNP and NT-proBNP for the diagnosis of heart failure in the emergency department: a systematic review of the evidence. Heart Fail Rev 2014; 19: 421-38.

  • 11. Meijers WC de Boer RA van Veldhuisen DJ Jaarsma T Hillege HL Maisel AS et al. Biomarkers and low risk in heart failure. Data from COACH and TRIUMPH. Eur J Heart Fail 2015; 17: 1271-82.

  • 12. de Boer RA Daniels LB Maisel AS Januzzi JL Jr. State of the Art: Newer biomarkers in heart failure. Eur J Heart Fail 2015; 17: 559-69.

  • 13. Danese E Lippi G Montagnana M. Red blood cell distribution width and cardiovascular diseases. J Thorac Dis 2015; 7: E402-11.

  • 14. Allen LA Felker GM Mehra MR Chiong JR Dunlap SH Ghali JK et al. Validation and potential mechanisms of red cell distribution width as a prognostic marker in heart failure. J Card Fail 2010; 16: 230-8.

  • 15. Imai R Uemura Y Okumura T Takemoto K Uchikawa T Koyasu M et al. Impact of red blood cell distribution width on non-cardiac mortality in patients with acute decompensated heart failure with preserved ejection fraction. J Cardiol 2017; 70: 591-7.

  • 16. Ponikowski P Voors AA Anker SD Bueno H Cleland JG Coats AJ et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) developed with the special contribution of the Heart Failure Association (HFA) of the ESC Eur J Heart Fail 2016; 18: 891-975.

  • 17. Roffi M Patrono C Collet JP Mueller C Valgimigli M Andreotti F et al. Management of Acute Coronary Syn - dromes in Patients Presenting without Persistent STSegment Elevation of the European Society of Car - diology. 2015 ESC Guidelines for the management of acute co ronary syndromes in patients presenting without persistent ST-segment elevation: Task Force for the Mana ge ment of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology (ESC). Eur Heart J 2016; 37: 267-315.

  • 18. Schnabel RB Larson MG Yamamoto JF Sullivan LM Pencina MJ Meigs JB et al. Relations of biomarkers of distinct pathophysiological pathways and atrial fibrillation in - cidence in the community. Circulation 2010; 121: 200-7.

  • 19. Pencina MJ D’Agostino RB Sr D’Agostino RB Jr Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 2008; 27: 157-72.

  • 20. Steyerberg EW Vickers AJ Cook NR Gerds T Gonen M Obuchowski N et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 2010; 21: 128-38.

  • 21. Willeit P Kiechl S Kronenberg F Witztum JL Santer P Mayr M et al. Discrimination and net reclassification of cardiovascular risk with lipoprotein(a): prospective 15- year outcomes in the Bruneck Study. J Am Coll Cardiol 2014; 64: 851-60.

  • 22. Kahraman A Emre Mutlu E Aldag M. ADMA SDMA and l-arginine may be novel targets in pharmacotherapy for complications due to cardiopulmonary bypass. J Med Biochem 2017; 36: 8-17.

  • 23. Miró Ò Rossello X Gil V Martín-Sánchez FJ Llorens P Herrero-Puente P et al. ICA-SEMES Research Group. Predicting 30-Day Mortality for Patients With Acute Heart Failure in the Emergency Department: A Cohort Study. Ann Intern Med 2017; 167: 698-705.

  • 24. Gungor ZB Sipahioglu N Sonmez H Ekmekci H Toprak S Ayaz G Bayram C Gurel Mutlu T Ulutin T Sipahioglu F Ilerigelen B. Endothelial dysfunction markers in low cardiovascular risk individuals: comparison of males and females. J Med Biochem 2017; 36: 62-71.

  • 25. Wong YW Fonarow GC Mi X Peacock WF 4th Mills RM Curtis LH et al. Early intravenous heart failure therapy and outcomes among older patients hospitalized for acute decompensated heart failure: findings from the Acute Decompensated Heart Failure Registry Emergency Module (ADHERE-EM). Am Heart J 2013; 166: 349-56.

  • 26. Rahko PS. Acute Heart Failure in the Emergency Depart - ment: What Is the Prognosis? Ann Intern Med 2017 21; 167: 744-5.

  • 27. De Denus S White M Tardif JC Bourassa MG Racine N Levesque S et al. Temporal increases in subclinical levels of inflammation are associated with adverse clinical outcomes in patients with left ventricular dysfunction. J Card Fail 2006; 12: 353-9.

  • 28. Grodin JL Simon J Hachamovitch R Wu Y Jackson G Halkar M et al. Prognostic Role of Serum Chloride Levels in Acute Decompensated Heart Failure. J Am Coll Cardiol 2015 11; 66: 659-66.

  • 29. Amin A Chitsazan M Shiukhi Ahmad Abad F Taghavi S Naderi N. On admission serum sodium and uric acid levels predict 30 day rehospitalization or death in patients with acute decompensated heart failure. ESC Heart Fail 2017; 4: 162-8.

  • 30. Smith GL Lichtman JH Bracken MB Shlipak MG Phillips CO Di Capua P et al. Renal impairment and outcomes in heart failure: systematic review and meta-analysis. J Am Coll Cardiol 2006; 47: 1987-96.

  • 31. Noveanu M Breidthardt T Potocki M Reichlin T Tweren - bold R Uthoff H et al. Direct comparison of serial B-type natriuretic peptide and NT-proBNP levels for prediction of short- and long-term outcome in acute decompensated heart failure. Crit Care 2011; 15: R1.

  • 32. Suzuki T Israr MZ Heaney LM Takaoka M Squire IB Ng LL. Prognostic Role of Molecular Forms of B-Type Natriuretic Peptide in Acute Heart Failure. Clin Chem 2017; 63: 880-6.

  • 33. Lam LL Cameron PA Schneider HG Abramson MJ Muller C Krum H. Meta-analysis: effect of B-type natriuretic peptide testing on clinical outcomes in patients with acute dyspnea in the emergency setting. Annals of internal medicine 2010; 153: 728-35.

  • 34. Trinquart L Ray P Riou B Teixeira A. Natriuretic peptide testing in EDs for managing acute dyspnea: a metaanalysis. Am J Emerg Med 2011; 29: 757-67.

  • 35. Hernandez MB Schwartz RS Asher CR Navas EV Totfalusi V Buitrago I et al. Predictors of 30-day readmission in patients hospitalized with decompensated heart failure. Clin Cardiol 2013; 36: 542-7.

  • 36. Jackson CE Dalzell JR Bezlyak V Tsorlalis IK Myles RC Spooner R et al. Red cell distribution width has incremental prognostic value to B-type natriuretic peptide in acute heart failure. Eur J Heart Fail 2009; 11: 1152-4.

  • 37. Pascual-Figal DA Bonaque JC Redondo B Caro C Man zano-Fernandez S Sánchez-Mas J et al. Red blood cell distribution width predicts long-term outcome re - gardless of anaemia status in acute heart failure patients. Eur J Heart Fail 2009; 11: 840-6.

  • 38. van Kimmenade RR Mohammed AA Uthamalingam S van der Meer P Felker GM Januzzi JL Jr. Red blood cell distribution width and 1-year mortality in acute heart failure. Eur J Heart Fail 2010; 12: 129-36.

  • 39. Xanthopoulos A Giamouzis G Tryposkiadis K Para ske - vo poulou E Paraskevopoulou P Karagiannis G et al. A simple score for early risk stratification in acute heart failure. Int J Cardiol 2017; 230: 248-54.

  • 40. Dai Y Konishi H Takagi A Miyauchi K Daida H. Red cell distribution width predicts short- and long-term outcomes of acute congestive heart failure more effectively than hemoglobin. Exp Ther Med 2014; 8: 600-6.

  • 41. Zhang Y Wang Y Kang JS Yu JX Yin SJ Cong XF et al. Differences in the predictive value of red cell distribution width for the mortality of patients with heart failure due to various heart diseases. J Geriatr Cardiol 2015; 12: 647-54.

  • 42. Sotiropoulos K Yerly P Monney P Garnier A Regamey J Hugli O et al. Red cell distribution width and mortality in acute heart failure patients with preserved and reduced ejection fraction. ESC Heart Fail 2016; 3: 198-204.

  • 43. Muhlestein JB Lappe DL Anderson JL Muhlestein JB Budge D May HT et al. Both initial red cell distribution width (RDW) and change in RDW during heart failure hospitalization are associated with length of hospital stay and 30-day outcomes. Int J Lab Hematol 2016; 38: 328-37.

  • 44. Turcato G Zorzi E Prati D Ricci G Bonora A Zannoni M et al. Early in-hospital variation of red blood cell distribution width predicts mortality in patients with acute heart failure. Int J Cardiol 2017; 243: 306-10.

Journal information
Impact Factor

IMPACT FACTOR 2018: 2.000
5-year IMPACT FACTOR: 1.075

CiteScore 2018: 1.47

SCImago Journal Rank (SJR) 2018: 0.523
Source Normalized Impact per Paper (SNIP) 2018: 0.581

Cited By
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 438 286 8
PDF Downloads 251 128 8