2021, Number 3
<< Back Next >>
Medicina & Laboratorio 2021; 25 (3)
Red cell distribution width as a marker associated with mortality risk in children in intensive care
Rocha-Arrieta MC, De la Hoz-Bequis F, Guzmán-Corena Á, Muñoz-Mejía C, Castro-Dager Á
Language: Spanish
References: 53
Page: 633-647
PDF size: 107.43 Kb.
ABSTRACT
Introduction. Red cell distribution width (RDW) has recently emerged as
a prognostic biomarker for mortality and other outcomes in critically ill adult patients,
but there are few reports in children. The aim of this study was to evaluate
the association between RDW and the risk of mortality in children admitted to a pediatric
intensive care unit (PICU).
Methodology. Prospective cohort study with 266
patients who met the inclusion criteria between January and September 2018. For
the statistical analysis, multivariate logistic regression was used to evaluate the association
of RDW on the first day and mortality. The areas under the ROC curve for
ADE and the Pediatric Mortality Index 2 (PIM2) were compared.
Results. A RDW at
admission greater than 16.4% increased the probability of death, with an OR of 2.6
(95%CI 1.17-5.9; p=0.019). The ability of ADE to discriminate mortality was moderate
(ROC 0.68; 95%CI 0.59-0.76), lower than that of the PIM2 (ROC 0.8; 95%CI
0.73-0.86). ADE and PIM2 were significantly correlated, albeit weakly (r=0.186;
p‹0.002). The correlation between RDW and mechanical ventilation-free days was
weak but significant (r=-0.23; p‹0.001). The RDW was not related to the days of use
of vasoactive drugs (r=0.042; p=0.63) or to the days of stay in the PICU (r=0.11;
p=0.07).
Conclusion. RDW on admission was associated with a moderate risk of
mortality during the stay in the PICU. Although it did not prove to be better than
PIM2 in predicting mortality, as it is an affordable and low-cost biomarker, it could
be used in conjunction with PIM2 or with other biomarkers, in order to increase its
predictive ability for mortality in critically ill children. More studies are required to
evaluate this possibility in our setting.
REFERENCES
Bazick HS, Chang D, Mahadevappa K,Gibbons FK, Christopher KB. Red celldistribution width and all-cause mortalityin critically ill patients. Crit Care Med 2011;39:1913-1921. https://doi.org/10.1097/CCM.0b013e31821b85c6.
Riley C, Poss WB, Wheeler DS. The evolvingmodel of pediatric critical care deliveryin North America. Pediatr Clin North Am2013;60:545-562. https://doi.org/10.1016/j.pcl.2013.02.001.
Heneghan JA, Pollack MM. Morbidity: Changingthe outcome paradigm for pediatric criticalcare. Pediatr Clin North Am 2017;64:1147-1165.https://doi.org/10.1016/j.pcl.2017.06.011.
Arias-Lopez MP, Fernández AL, Ratto ME, SaligariL, Serrate AS, Ko IJ, et al. Pediatric Indexof Mortality 2 as a predictor of death risk in childrenadmitted to pediatric intensive care unitsin Latin America: A prospective, multicenter study.J Crit Care 2015;30:1324-1330. https://doi.org/10.1016/j.jcrc.2015.08.001.
Rojas M DV, Ramos J, Molano M. Predictoresde mortalidad en la unidad de cuidados intensivospediátricos del Hospital Universitariode Neiva. 2014. Acta Colomb de Cuid Intensivo2016;16:1-7. https://doi.org/10.1016/j.acci.2015.10.001.
Gulla KM, Sachdev A. Illness severity and organdysfunction scoring in pediatric intensivecare unit. Indian J Crit Care Med 2016;20:27-35.https://doi.org/10.4103/0972-5229.173685.
Lee OJ, Jung M, Kim M, Yang HK, Cho J. Validationof the Pediatric Index of Mortality 3 ina Single Pediatric Intensive Care Unit in Korea.J Korean Med Sci 2017;32:365-370. https://doi.org/10.3346/jkms.2017.32.2.365.
Slater A, Shann F. The suitability of the PediatricIndex of Mortality (PIM), PIM2, the PediatricRisk of Mortality (PRISM), and PRISM III formonitoring the quality of pediatric intensivecare in Australia and New Zealand. PediatrCrit Care Med 2004;5:447-454. https://doi.org/10.1097/01.Pcc.0000138557.31831.65.
Vincent JL, Opal SM, Marshall JC. Ten reasonswhy we should NOT use severity scores as entrycriteria for clinical trials or in our treatment decisions.Crit Care Med 2010;38:283-287. https://doi.org/10.1097/CCM.0b013e3181b785a2.
Wong HR, Salisbury S, Xiao Q, CvijanovichNZ, Hall M, Allen GL, et al. The pediatric sepsisbiomarker risk model. Crit Care 2012;16:R174.https://doi.org/10.1186/cc11652.
Wong HR, Cvijanovich NZ, Anas N, AllenGL, Thomas NJ, Bigham MT, et al. PediatricSepsis Biomarker Risk Model-II: Redefiningthe pediatric sepsis biomarker risk modelwith septic shock phenotype. Crit Care Med2016;44:2010-2017. https://doi.org/10.1097/ccm.0000000000001852.
Wong HR, Weiss SL, Giuliano JS, WainwrightMS, Cvijanovich NZ, Thomas NJ, et al. Testingthe prognostic accuracy of the updatedpediatric sepsis biomarker risk model. PLoSOne 2014;9:e86242. https://doi.org/10.1371/journal.pone.0086242.
Liu J, Bai C, Li B, Shan A, Shi F, Yao C, et al.Mortality prediction using a novel combinationof biomarkers in the first day of sepsis in intensivecare units. Sci Rep 2021;11:1275. https://doi.org/10.1038/s41598-020-79843-5.
Constantino BT. Red cell distribution width,revisited. Lab Med 2013;44:e2-e9. https://doi.org/10.1309/lmz1gky9lqtvfbl7.
Parker RI. RBC distribution width: Olddog, new trick? Pediatr Crit Care Med2017;18:193-194. https://doi.org/10.1097/pcc.0000000000001033.
Allen LA, Felker GM, Mehra MR, Chiong JR,Dunlap SH, Ghali JK, et al. Validation andpotential mechanisms of red cell distributionwidth as a prognostic marker in heart failure.J Card Fail 2010;16:230-238. https://doi.org/10.1016/j.cardfail.2009.11.003.
Ani C, Ovbiagele B. Elevated red blood celldistribution width predicts mortality in personswith known stroke. J Neurol Sci 2009;277:103-108. https://doi.org/10.1016/j.jns.2008.10.024.
Perlstein TS, Weuve J, Pfeffer MA, BeckmanJA. Red blood cell distribution width and mortalityrisk in a community-based prospective cohort.Arch Intern Med 2009;169:588-594. https://doi.org/10.1001/archinternmed.2009.55.
Zhang L, Yu CH, Guo KP, Huang CZ, Mo LY.Prognostic role of red blood cell distributionwidth in patients with sepsis: a systematicreview and meta-analysis. BMC Immunol
2020;21:40. https://doi.org/10.1186/s12865-020-00369-6.20. Krishna V, Pillai G, Velickakathu-SukumaranS. Red cell distribution width as a predictorof mortality in patients with sepsis. Cureus2021;13:e12912. https://doi.org/10.7759/cureus.12912.
Ghimire R, Shakya YM, Shrestha TM, NeupaneRP. The utility of red cell distribution width topredict mortality of septic patients in a tertiaryhospital of Nepal. BMC Emerg Med 2020;20:43.https://doi.org/10.1186/s12873-020-00337-8.
Bateman RM, Sharpe MD, Singer M, Ellis CG.The effect of sepsis on the erythrocyte. Int J MolSci 2017;18:1932. https://doi.org/10.3390/ijms18091932.
Sadaka F, O'Brien J, Prakash S. Red cell distributionwidth and outcome in patients with septicshock. J Intensive Care Med 2013;28:307-313.https://doi.org/10.1177/0885066612452838.
Kim CH, Park JT, Kim EJ, Han JH, Han JS, ChoiJY, et al. An increase in red blood cell distributionwidth from baseline predicts mortality inpatients with severe sepsis or septic shock. CritCare 2013;17:R282. https://doi.org/10.1186/cc13145.
Henry BM, Benoit JL, Benoit S, Pulvino C, BergerBA, Olivera MHS, et al. Red blood cell distributionwidth (RDW) predicts COVID-19 severity:A prospective, observational study from theCincinnati SARS-CoV-2 emergency departmentcohort. Diagnostics (Basel) 2020;10:618.https://doi.org/10.3390/diagnostics10090618.
Wang C, Zhang H, Cao X, Deng R, Ye Y, Fu Z,et al. Red cell distribution width (RDW): a prognosticindicator of severe COVID-19. Ann TranslMed 2020;8:1230. https://doi.org/10.21037/atm-20-6090.
Lee JJ, Montazerin SM, Jamil A, Jamil U,Marszalek J, Chuang ML, et al. Associationbetween red blood cell distribution width andmortality and severity among patients with COVID-19: A systematic review and meta-analysis.J Med Virol 2021;93:2513-2522. https://doi.org/10.1002/jmv.26797.
Zinellu A, Mangoni AA. Red blood cell distributionwidth, disease severity, and mortality inhospitalized patients with sars-cov-2 infection:A systematic review and meta-analysis. J ClinMed 2021;10:286. https://doi.org/10.3390/jcm10020286.
Pouladzadeh M, Safdarian M, ChoghakabodiPM, Amini F, Sokooti A. Validation of red celldistribution width as a COVID-19 severity screeningtool. Future Sci OA 2021:FSO712. https://doi.org/10.2144/fsoa-2020-0199.
Foy BH, Carlson JCT, Reinertsen E, PadrosIVR, Pallares Lopez R, Palanques-Tost E,et al. Association of red blood cell distributionwidth with mortality risk in hospitalizedadults with SARS-CoV-2 infection. JAMANetw Open 2020;3:e2022058. https://doi.org/10.1001/jamanetworkopen.2020.22058.
Abdelaleem NA, Makhlouf HA, NagiubEM, Bayoumi HA. Prognostic biomarkersin predicting mortality in respiratory patientswith ventilator-associated pneumonia.Egypt J Bronchol 2021;15:16. https://doi.org/10.1186/s43168-021-00062-1.
Hashemi SM, Khanbabaee G, Salarian S,Fariborzi M, Kiumarsi A. Association betweenred cell distribution width and mortalityin pediatric patients admitted to intensivecare units. Iran J Blood Cancer 2017;9:54-58.
Schepens T, De Dooy JJ, Verbrugghe W,Jorens PG. Red cell distribution width (RDW)as a biomarker for respiratory failure in apediatric ICU. J Inflamm (Lond) 2017;14:12.https://doi.org/10.1186/s12950-017-0160-9.
Kim DH, Ha EJ, Park SJ, Jhang WK. Evaluationof the usefulness of red blood celldistribution width in critically ill pediatricpatients. Medicine 2020;99:e22075. https://doi.org/10.1097/MD.0000000000022075.
Sachdev A, Simalti A, Kumar A, Gupta N,Gupta D, Chugh P. Outcome prediction valueof red cell distribution width in criticallyillchildren. Indian Pediatr 2018;55:414-416.
Said AS, Spinella PC, Hartman ME, SteffenKM, Jackups R, Holubkov R, et al. RBC distributionwidth: Biomarker for red cell dysfunctionand critical illness outcome? PediatrCrit Care Med 2017;18:134-142. https://doi.org/10.1097/PCC.0000000000001017.
Ramby AL, Goodman DM, Wald EL, WeissSL. Red blood cell distribution width as a pragmaticmarker for outcome in pediatric criticalillness. PLoS One 2015;10:e0129258. https://doi.org/10.1371/journal.pone.0129258.
Ellahony DM, El-Mekkawy MS, FaragMM. A study of red cell distribution widthin neonatal sepsis. Pediatr Emerg Care2020;36:378-383. https://doi.org/10.1097/pec.0000000000001319.
Guo BF, Sun SZ. Diagnostic accuracy of adynamically increased red blood cell distributionwidth in very low birth weight infantswith serious bacterial infection. Ital J Pediatr2021;47:44. https://doi.org/10.1186/s13052-021-00994-w.
Bulut O, Akcakaya A, Bulut N, Ovali F. Elevatedred cell distribution width as a usefulmarker in neonatal sepsis. J Pediatr HematolOncol 2021;43:180-185. https://doi.org/10.1097/mph.0000000000002070.
Wang F, Pan W, Pan S, Ge J, Wang S, ChenM. Red cell distribution width as a novel predictorof mortality in ICU patients. Ann Med2011;43:40-46. https://doi.org/10.3109/07853890.2010.521766.
Ministerio de Salud y la Protección Social,Instituto Colombiano de Bienestar Familiary colaboradores. Encuesta Nacional dela Situación Nutricional en Colombia 2015.ENSIN. Bogotá D.C.: Ministerio de salud y laProtección Social; 2015. Acceso 15 de marzode 2021. Disponible en https://www.icbf.gov.co/sites/default/files/infografia_situacion_nutricional_0_a_4_anos.pdf.
Hulst J, Joosten K, Zimmermann L, Hop W, vanBuuren S, Büller H, et al. Malnutrition in criticallyill children: from admission to 6 months after discharge.Clin Nutr 2004;23:223-232. https://doi.org/10.1016/s0261-5614(03)00130-4.
de Souza Menezes F, Leite HP, Koch NogueiraPC. Malnutrition as an independentpredictor of clinical outcome in critically ill children.Nutrition 2012;28:267-270. https://doi.org/10.1016/j.nut.2011.05.015.
Leite HP, Rodrigues da Silva AV, de OliveiraIglesias SB, Koch Nogueira PC. Serumalbumin is an independent predictor of clinicaloutcomes in critically ill children. PediatrCrit Care Med 2016;17:e50-57. https://doi.org/10.1097/pcc.0000000000000596.
Durward A, Mayer A, Skellett S, Taylor D,Hanna S, Tibby SM, et al. Hypoalbuminaemiain critically ill children: incidence, prognosis,and influence on the anion gap. Arch Dis Child2003;88:419-422. https://doi.org/10.1136/adc.88.5.419.
Förhécz Z, Gombos T, Borgulya G, PozsonyiZ, Prohászka Z, Jánoskuti L. Red cell distributionwidth in heart failure: prediction ofclinical events and relationship with markersof ineffective erythropoiesis, inflammation, renalfunction, and nutritional state. Am Heart J2009;158:659-666. https://doi.org/10.1016/j.ahj.2009.07.024.
Ong C, Han WM, Wong JJ, Lee JH. Nutritionbiomarkers and clinical outcomes in criticallyill children: A critical appraisal of the literature.Clin Nutr 2014;33:191-197. https://doi.org/10.1016/j.clnu.2013.12.010.
Breslow MJ, Badawi O. Severity scoring inthe critically ill: part 2: maximizing value fromoutcome prediction scoring systems. Chest2012;141:518-527. https://doi.org/10.1378/chest.11-0331.
Pollack MM, Holubkov R, Reeder R, DeanJM, Meert KL, Berg RA, et al. PICU length ofstay: Factors associated with bed utilization anddevelopment of a benchmarking model. PediatrCrit Care Med 2018;19:196-203. https://doi.org/10.1097/pcc.0000000000001425.
Kramer AA, Zimmerman JE. The relationshipbetween hospital and intensivecare unit length of stay. Crit Care Med2011;39:1015-1022. https://doi.org/10.1097/CCM.0b013e31820eabab.
Shaikh MA, Yadavalli DR. Red cell distributionwidth as a prognostic marker in severesepsis and septic shock. Int J Adv Med2017;4:5. https://doi.org/10.18203/2349-3933.ijam20172266.
Zurauskaite G, Meier M, Voegeli A, Koch D,Haubitz S, Kutz A, et al. Biological pathwaysunderlying the association of red cell distributionwidth and adverse clinical outcome: Resultsof a prospective cohort study. PLoS One2018;13:e0191280. https://doi.org/10.1371/journal.pone.0191280.