Ann Lab Med.  2024 Sep;44(5):401-409. 10.3343/alm.2023.0345.

Association Between the Red Blood Cell Distribution Width and 30-Day Mortality in Intensive Care Patients Undergoing Cardiac Surgery: A Retrospective Observational Study Based on the Medical Information Mart for Intensive Care-IV Database

Affiliations
  • 1Department of Anaesthesiology, Shantou Central Hospital, Shantou, Guangdong, China
  • 2Department of Anaesthesiology, Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, Chengdu, Sichuan, China
  • 3Department of Anaesthesiology, the Third Affiliated Hospital of Sun Yat-Sen University, Guangdong, China

Abstract

Background
Millions of patients undergo cardiac surgery each year. The red blood cell distribution width (RDW) could help predict the prognosis of patients who undergo percutaneous coronary intervention or coronary artery bypass surgery. We investigated whether the RDW has robust predictive value for the 30-day mortality among patients in an intensive care unit (ICU) after undergoing cardiac surgery.
Methods
Using the Medical Information Mart for Intensive Care-IV Database, we retrieved data for 11,634 patients who underwent cardiac surgery in an ICU. We performed multivariate Cox regression analysis to model the association between the RDW and 30-day mortality and plotted Kaplan–Meier curves. Subgroup analyses were stratified using relevant covariates. Receiver operating characteristic (ROC) curves were used to determine the predictive value of the RDWs.
Results
The total 30-day mortality rate was 4.2% (485/11,502). The elevated-RDW group had a higher 30-day mortality rate than the normal-RDW group (P < 0.001). The robustness of our data analysis was confirmed by performing subgroup analyses. Each unit increase in the RDW was associated with a 17% increase in 30-day mortality when the RDW was used as a continuous variable (adjusted hazard ratio = 1.17, 95% confidence interval, 1.10–1.25). Our ROC results showed the predictive value of the RDW.
Conclusions
An elevated RDW was associated with a higher 30-day mortality in patients after undergoing cardiac surgery in an ICU setting. The RDW can serve as an efficient and accessible method for predicting the mortality of patients in ICUs following cardiac surgery.

Keyword

Cardiac surgery; Intensive care unit; Medical Information Mart for Intensive Care-IV (MIMIC-IV); Mortality; Multivariate Cox regression; Red blood cell distribution width

Figure

  • Fig. 1 Study flow chart showing the inclusion and exclusion criteria. Abbreviations: ICU, intensive care unit; ICD, International Classification of Diseases; MIMIC-IV, Medical Information Mart for Intensive Care-IV; RDW, red blood cell distribution width.

  • Fig. 2 Kaplan–Meier curves showing the association between the red blood cell distribution width (RDW) and the 30-day mortality of patients after undergoing cardiac surgery.

  • Fig. 3 Forest plot showing subgroup analysis of the association between red blood cell distribution width (RDW) and 30-day mortality. Abbreviations: HR, hazard ratio; CI, confidence interval; Sepsis 3.0, the third international consensus definitions for sepsis and septic shock; SOFA, sequential organ failure assessment; AKI, acute kidney injury; MI, myocardial infarction; CHF, congestive heart failure; CVD, cerebrovascular disease; CPD, chronic pulmonary disease; DM, diabetes mellitus.


Reference

References

1. Mozaffarian D, Benjamin EJ, Go AS, Arnett DK, Blaha MJ, et al. Writing Group Members. 2016; Heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation. 133:e38–360. DOI: 10.1161/CIR.0000000000000350. PMID: 26673558.
2. Landoni G, Lomivorotov V, Silvetti S, Nigro Neto C, Pisano A, Alvaro G, et al. 2018; Nonsurgical strategies to reduce mortality in patients undergoing cardiac surgery: an updated consensus process. J Cardiothorac Vasc Anesth. 32:225–35. DOI: 10.1053/j.jvca.2017.06.017. PMID: 29122431.
Article
3. Lazam S, Vanoverschelde JL, Tribouilloy C, Grigioni F, Suri RM, Avierinos JF, et al. 2017; Twenty-year outcome after mitral repair versus replacement for severe degenerative mitral regurgitation: analysis of a large, prospective, multicenter, international registry. Circulation. 135:410–22. DOI: 10.1161/CIRCULATIONAHA.116.023340. PMID: 27899396.
Article
4. Pieri M, Belletti A, Monaco F, Pisano A, Musu M, Dalessandro V, et al. 2016; Outcome of cardiac surgery in patients with low preoperative ejection fraction. BMC Anesthesiol. 16:97. DOI: 10.1186/s12871-016-0271-5. PMID: 27760527. PMCID: PMC5069974.
Article
5. Nashef SAM, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, et al. 2012; EuroSCORE II. Eur J Cardiothorac Surg. 41:734–45. DOI: 10.1093/ejcts/ezs043. PMID: 22378855.
Article
6. Carino D, Denti P, Ascione G, Del Forno B, Lapenna E, Ruggeri S, et al. 2021; Is the EuroSCORE II reliable in surgical mitral valve repair? A single-centre validation study. Eur J Cardiothorac Surg. 59:863–8. DOI: 10.1093/ejcts/ezaa403. PMID: 33313790.
Article
7. Pinna A, Carlino P, Serra R, Boscia F, Dore S, Carru C, et al. 2021; Red cell distribution width (RDW) and complete blood cell count-derived measures in non-arteritic anterior ischemic optic neuropathy. Int J Med Sci. 18:2239–44. DOI: 10.7150/ijms.53668. PMID: 33859533. PMCID: PMC8040420.
Article
8. Qi X, Dong Y, Lin X, Xin W. 2021; Value of neutrophil to lymphocyte ratio, platelet to lymphocyte ratio, and red blood cell distribution width in evaluating the prognosis of children with severe pneumonia. Evid Based Complement Alternat Med. 2021:1818469. DOI: 10.1155/2021/1818469. PMID: 34603463. PMCID: PMC8486541.
Article
9. Salvagno GL, Sanchis-Gomar F, Picanza A, Lippi G. 2015; Red blood cell distribution width: a simple parameter with multiple clinical applications. Crit Rev Clin Lab Sci. 52:86–105. DOI: 10.3109/10408363.2014.992064. PMID: 25535770.
Article
10. Xanthopoulos A, Giamouzis G, Dimos A, Skoularigki E, Starling RC, Skoularigis J, et al. 2022; Red blood cell distribution width in heart failure: pathophysiology, prognostic role, controversies and dilemmas. J Clin Med. 11:1951. DOI: 10.3390/jcm11071951. PMID: 35407558. PMCID: PMC8999162. PMID: f95e06d778b84d5cac31e74e6900cfe5.
Article
11. Huang S, Zhou Q, Guo N, Zhang Z, Luo L, Luo Y, et al. 2021; Association between red blood cell distribution width and in-hospital mortality in acute myocardial infarction. Medicine. 100:e25404. DOI: 10.1097/MD.0000000000025404. PMID: 33847638. PMCID: PMC8052072.
Article
12. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. 2016; The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 315:801–10. DOI: 10.1001/jama.2016.0287. PMID: 26903338. PMCID: PMC4968574.
Article
13. Warwick R, Mediratta N, Shaw M, McShane J, Pullan M, Chalmers J, et al. 2013; Red cell distribution width and coronary artery bypass surgery. Eur J Cardiothorac Surg. 43:1165–9. DOI: 10.1093/ejcts/ezs609. PMID: 23277431.
Article
14. Frentiu AA, Mao K, Caruana CB, Raveendran D, Perry LA, Penny-Dimri JC, et al. 2023; The prognostic significance of red cell distribution width in cardiac surgery: a systematic review and meta-analysis. J Cardiothorac Vasc Anesth. 37:471–9. DOI: 10.1053/j.jvca.2022.11.015. PMID: 36635145.
Article
15. Johnson AEW, Bulgarelli L, Shen L, Gayles A, Shammout A, Horng S, et al. 2023; MIMIC-IV, a freely accessible electronic health record dataset. Sci Data. 10:1. DOI: 10.1038/s41597-022-01899-x. PMID: 36596836. PMCID: PMC9810617. PMID: 87ad030cf80044449c8297af0def7c70.
Article
16. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. 2007; Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 335:806–8. DOI: 10.1136/bmj.39335.541782.AD. PMID: 17947786. PMCID: PMC2034723.
Article
17. Yang Q, Zheng J, Chen W, Chen X, Wen D, Chen W, et al. 2021; Association between preadmission metformin use and outcomes in intensive care unit patients with sepsis and type 2 diabetes: a cohort study. Front Med (Lausanne). 8:640785. DOI: 10.3389/fmed.2021.640785. PMID: 33855034. PMCID: PMC8039324. PMID: 6e49fd9b118647e8b4a0e46370772e7e.
Article
18. Otero TM, Canales C, Yeh DD, Hou PC, Belcher DM, Quraishi SA. 2016; Elevated red cell distribution width at initiation of critical care is associated with mortality in surgical intensive care unit patients. J Crit Care. 34:7–11. DOI: 10.1016/j.jcrc.2016.03.005. PMID: 27288601. PMCID: PMC4903153.
Article
19. Shao Q, Korantzopoulos P, Letsas KP, Tse G, Hong J, Li G, et al. 2018; Red blood cell distribution width as a predictor of atrial fibrillation. J Clin Lab Anal. 32:e22378. DOI: 10.1002/jcla.22378. PMID: 29315856. PMCID: PMC6817116.
Article
20. Ling J, Liao T, Wu Y, Wang Z, Jin H, Lu F, et al. 2021; Predictive value of red blood cell distribution width in septic shock patients with thrombocytopenia: a retrospective study using machine learning. J Clin Lab Anal. 35:e24053. DOI: 10.1002/jcla.24053. PMID: 34674393. PMCID: PMC8649348.
Article
21. Pinho J, Silva L, Quintas-Neves M, Marques L, Amorim JM, Reich A, et al. 2021; Red cell distribution width is associated with 30-day mortality in patients with spontaneous intracerebral hemorrhage. Neurocrit Care. 34:825–32. DOI: 10.1007/s12028-020-01103-1. PMID: 32959199. PMCID: PMC8179905.
Article
22. Smirne C, Grossi G, Pinato DJ, Burlone ME, Mauri FA, Januszewski A, et al. 2015; Evaluation of the red cell distribution width as a biomarker of early mortality in hepatocellular carcinoma. Dig Liver Dis. 47:488–94. DOI: 10.1016/j.dld.2015.03.011. PMID: 25864774.
Article
23. Drakopoulou M, Toutouzas K, Stefanadi E, Tsiamis E, Tousoulis D, Stefanadis C. 2009; Association of inflammatory markers with angiographic severity and extent of coronary artery disease. Atherosclerosis. 206:335–9. DOI: 10.1016/j.atherosclerosis.2009.01.041. PMID: 19264307.
Article
24. Arbel Y, Birati EY, Finkelstein A, Halkin A, Berliner S, Katz BZ, et al. 2014; Red blood cell distribution width and 3-year outcome in patients undergoing cardiac catheterization. J Thromb Thrombolysis. 37:469–74. DOI: 10.1007/s11239-013-0964-2. PMID: 23836454.
Article
25. Maluf CB, Barreto SM, Giatti L, Ribeiro AL, Vidigal PG, Azevedo DRM, et al. 2020; Association between C reactive protein and all-cause mortality in the ELSA-Brasil cohort. J Epidemiol Community Health. 74:421–7. DOI: 10.1136/jech-2019-213289. PMID: 32102838. PMCID: PMC7307658.
Article
26. Lindmark E, Diderholm E, Wallentin L, Siegbahn A. 2001; Relationship between interleukin 6 and mortality in patients with unstable coronary artery disease: effects of an early invasive or noninvasive strategy. JAMA. 286:2107–13. DOI: 10.1001/jama.286.17.2107. PMID: 11694151.
Article
27. Fibach E, Rachmilewitz E. 2008; The role of oxidative stress in hemolytic anemia. Curr Mol Med. 8:609–19. DOI: 10.2174/156652408786241384. PMID: 18991647.
Article
28. Ghaffari S. 2008; Oxidative stress in the regulation of normal and neoplastic hematopoiesis. Antioxid Redox Signal. 10:1923–40. DOI: 10.1089/ars.2008.2142. PMID: 18707226. PMCID: PMC2932538.
Article
29. Weimann A, Braga M, Carli F, Higashiguchi T, Hübner M, Klek S, et al. 2021; ESPEN practical guideline: clinical nutrition in surgery. Clin Nutr. 40:4745–61. DOI: 10.1016/j.clnu.2021.03.031. PMID: 34242915.
Article
30. Devereaux PJ, Lamy A, Chan MTV, Allard RV, Lomivorotov VV, Landoni G, et al. 2022; High-sensitivity troponin I after cardiac surgery and 30-day mortality. N Engl J Med. 386:827–36. DOI: 10.1056/NEJMoa2000803. PMID: 35235725.
Article
31. Liu X, Xie L, Zhu W, Zhou Y. 2020; Association of body mass index and all-cause mortality in patients after cardiac surgery: a dose-response meta-analysis. Nutrition. 72:110696. DOI: 10.1016/j.nut.2019.110696. PMID: 32007807.
Article
32. Zante B, Reichenspurner H, Kubik M, Kluge S, Schefold JC, Pfortmueller CA. 2018; Base excess is superior to lactate-levels in prediction of ICU mortality after cardiac surgery. PLoS One. 13:e0205309. DOI: 10.1371/journal.pone.0205309. PMID: 30289956. PMCID: PMC6173442. PMID: ee629989b9aa4ab397e6409916e20812.
Article
33. Bouma HR, Mungroop HE, Scheeren TWL, Epema AH. 2021; Very early creatinine changes and 30-day mortality after cardiac surgery. Eur J Anaesthesiol. 38:665. DOI: 10.1097/EJA.0000000000001436. PMID: 33967257.
Article
34. Yu Y, Peng C, Zhang Z, Shen K, Zhang Y, Xiao J, et al. 2022; Machine learning methods for predicting long-term mortality in patients after cardiac surgery. Front Cardiovasc Med. 9:831390. DOI: 10.3389/fcvm.2022.831390. PMID: 35592400. PMCID: PMC9110683. PMID: ce2a375dab0f43a681805eb2e558676f.
Article
Full Text Links
  • ALM
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr