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2000
Volume 6, Issue 2
  • ISSN: 2666-7967
  • E-ISSN: 2666-7975

Abstract

Objective

To determine the association between changes in haematological parameters and mortality in patients hospitalized due to severe COVID-19 at a Peruvian reference hospital from April to December 2020.

Materials and Methods

Observational, analytical, historical cohort study based on the review of clinical records of patients hospitalized due to severe COVID-19 from April to December 2020. We evaluated changes in common haematological parameters, including white blood cells (WBCs), lymphocytes, neutrophils, and platelet counts, as well as the neutrophil-to-lymphocyte ratio (NLR) on the third and seventh days of hospitalization compared with admission values in the deceased and non-deceased groups. Changes in haematological parameters were expressed as median and interquartile ranges (IQR). Multivariate Poisson regression analysis was further done to evaluate the effect of haematological changes in mortality, adjusting for gender, age, and comorbidities.

Results

We included 1033 cases, of which 68.05% were male. Deceased patients had a significant increase in total WBC on the third day (1.0 *103/µL; IQR -1.7 to 5.4) and the seventh day (1.6*103/µL; IQR -1.9 to 4.9) compared to their admission values. The neutrophil count in the deceased patients also increased on the third day (1.2; IQR -1.7 to 4.9) and seventh day (1.9; IQR-1.5 to 5.8), as did the NLR ratio on the third day (0.2; IQR -0.4 to 1.6) and seventh day (0.7; IQR -0.2 to 2.2). Surviving patients showed an opposite trend in these parameters. In contrast, platelet counts increased on the third day (49*105/µL; IQR -0.3 to 1.3) and the seventh day (90*105; IQR 0.0 to 2.0) in surviving patients, whereas deceased patients did not show significant changes. All these differences remained statistically significant in the adjusted analysis.

Conclusion

An increase in total WBC, neutrophils, and NLR at the third and seventh days compared to admission values was associated with higher mortality in patients hospitalized due to COVID-19, while an increase in platelet count was associated with decreased mortality. Monitoring these changes can help in identifying those patients with higher mortality risk.

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References

  1. Timeline: WHO’s COVID-19 response.Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/interactive-timeline (Accessed on 2024 Feb 20).
  2. ZhuN. ZhangD. WangW. A novel coronavirus from patients with pneumonia in China, 2019.N. Engl. J. Med.2020382872773310.1056/NEJMoa2001017 31978945
     [Google Scholar]
  3. BurkiT. Outbreak of coronavirus disease 2019.Lancet Infect. Dis.202020329229310.1016/S1473‑3099(20)30076‑1 32078809
     [Google Scholar]
  4. SchwalbA. SeasC. The COVID-19 pandemic in Peru: What went wrong?Am. J. Trop. Med. Hyg.202110441176117810.4269/ajtmh.20‑1323 33591940
     [Google Scholar]
  5. GhinaiI. WoodsS. RitgerK.A. Community transmission of SARS-CoV-2 at two family gatherings: Chicago, Illinois, February–March 2020.MMWR Morb. Mortal. Wkly. Rep.2020691544645010.15585/mmwr.mm6915e1
     [Google Scholar]
  6. AhmedF. AhmedN. PissaridesC. StiglitzJ. Why inequality could spread COVID-19.Lan Pub Hea202055e24010.1016/S2468‑2667(20)30085‑2 32247329
     [Google Scholar]
  7. TerposE. Ntanasis-StathopoulosI. ElalamyI. Hematological findings and complications of COVID‐19.Am. J. Hematol.202095783484710.1002/ajh.25829 32282949
     [Google Scholar]
  8. BritoA.E. COVID-19: Rapida revision general.An Acad Cienc Cuba20201021828
     [Google Scholar]
  9. BahceciI. MercantepeF. DuranO.F. YildizS. SahinK. The relationship between laboratory findings and mortality in COVID-19 patients requiring intensive care.Cureus2023156e4119410.7759/cureus.41194 37525784
     [Google Scholar]
  10. XuJ. HeB. CarverK. Heterogeneity of neutrophils and inflammatory responses in patients with COVID-19 and healthy controls.Front. Immunol.20221397028710.3389/fimmu.2022.970287 36466858
     [Google Scholar]
  11. SiddiqiH.K. MehraM.R. COVID-19 illness in native and immunosuppressed states: A clinical–therapeutic staging proposal.J. Heart Lung Transplant.202039540540710.1016/j.healun.2020.03.012 32362390
     [Google Scholar]
  12. LippiG. PlebaniM. Laboratory abnormalities in patients with COVID-2019 infection.Clin. Chem. Lab. Med.20205871131113410.1515/cclm‑2020‑0198 32119647
     [Google Scholar]
  13. Sánchez VeraN. Saavedra HernándezD. Hidalgo MesaC.J. Aguila LópezM. Abreu GutiérrezG. Herrera GonzálezV. Clinical laboratory parameters in patients with COVID-19.Rev. Cuba. Med. Mil.2021502
     [Google Scholar]
  14. AggarwalS. Garcia-TellesN. AggarwalG. LavieC. LippiG. HenryB.M. Clinical features, laboratory characteristics, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19): Early report from the United States.Diagnosis 202072919610.1515/dx‑2020‑0046 32352401
     [Google Scholar]
  15. WangK. ZuoP. LiuY. Clinical and laboratory predictors of in-hospital mortality in patients with coronavirus disease-2019: A cohort study in Wuhan, China.Clin. Infect. Dis.202071162079208810.1093/cid/ciaa538 32361723
     [Google Scholar]
  16. SorayaG.V. UlhaqZ.S. Crucial laboratory parameters in COVID-19 diagnosis and prognosis: An updated meta-analysis.Med Clin2020155414315110.1016/j.medcli.2020.05.017 32586670
     [Google Scholar]
  17. FanB.E. ChongV.C.L. ChanS.S.W. Hematologic parameters in patients with COVID‐19 infection.Am. J. Hematol.2020956E131E13410.1002/ajh.25774 32129508
     [Google Scholar]
  18. SegaloS. KiseljakovicE. PapicE. The role of hemogram-derived ratios in COVID-19 severity stratification in a primary healthcare facility.Acta Inform. Med.2023311414710.5455/aim.2023.31.41‑47 37038490
     [Google Scholar]
  19. KazemiE. Soldoozi NejatR. AshkanF. SheibaniH. The laboratory findings and different COVID-19 severities: A systematic review and meta-analysis.Ann. Clin. Microbiol. Antimicrob.20212011710.1186/s12941‑021‑00420‑3 33726761
     [Google Scholar]
  20. LippiG. PlebaniM. HenryB.M. Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: A meta-analysis.Clin. Chim. Acta202050614514810.1016/j.cca.2020.03.022 32178975
     [Google Scholar]
  21. MehtaP. McAuleyD.F. BrownM. SanchezE. TattersallR.S. MansonJ.J. COVID-19: Consider cytokine storm syndromes and immunosuppression.Lancet2020395102291033103410.1016/S0140‑6736(20)30628‑0 32192578
     [Google Scholar]
  22. JoseR.J. ManuelA. COVID-19 cytokine storm: The interplay between inflammation and coagulation.Lancet Respir. Med.202086e46e4710.1016/S2213‑2600(20)30216‑2 32353251
     [Google Scholar]
  23. TangN. LiD. WangX. SunZ. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia.J. Thromb. Haemost.202018484484710.1111/jth.14768 32073213
     [Google Scholar]
  24. FilizM. YilmazG. FidanG. KosgerS. SavasciU. CekliY. A tertiary care hospital experience during the COVID-19 pandemic.Flo Inf Dis Clin Microb J202126225726610.5578/flora.20219805
     [Google Scholar]
  25. FerrariD. SevesoA. SabettaE. Role of time-normalized laboratory findings in predicting COVID-19 outcome.Diagnosis20207438739410.1515/dx‑2020‑0095 33035183
     [Google Scholar]
  26. LassoG. KhanS. AllenS.A. Longitudinally monitored immune biomarkers predict the timing of COVID-19 outcomes.PLOS Comput. Biol.2022181e100977810.1371/journal.pcbi.1009778 35041647
     [Google Scholar]
  27. Velez PaezJ.L. Prediction of mortality with immunological-inflammatory and hematological markers in critically ill patients with COVID-19 living at high altitude.2022Available from: https://repositorio.upch.edu.pe/handle/20.500.12866/11954 (Accessed on 2024 Feb 20).
  28. SotoA. Quiñones-LaverianoD.M. AzañeroJ. Mortality and associated risk factors in patients hospitalized due to COVID-19 in a Peruvian reference hospital.PLoS One2022173e026478910.1371/journal.pone.0264789 35235613
     [Google Scholar]
  29. SilvaM.J.A. RibeiroL.R. GouveiaM.I.M. Hyperinflammatory response in COVID-19: A systematic review.Viruses202315255310.3390/v15020553 36851766
     [Google Scholar]
  30. HuangC. WangY. LiX. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.Lancet20203951022349750610.1016/S0140‑6736(20)30183‑5 31986264
     [Google Scholar]
  31. YangX. YangQ. WangY. Thrombocytopenia and its association with mortality in patients with COVID‐19.J. Thromb. Haemost.20201861469147210.1111/jth.14848 32302435
     [Google Scholar]
  32. ChenG. WuD. GuoW. Clinical and immunological features of severe and moderate coronavirus disease 2019.J. Clin. Invest.202013052620262910.1172/JCI137244 32217835
     [Google Scholar]
  33. DingL. ZhangW. ZhangF. Prognostic role and diagnostic power of seven indicators in COVID-19 patients.Front. Med.2021873327410.3389/fmed.2021.733274 34778296
     [Google Scholar]
  34. ZhangJ. CaoY. TanG. Clinical, radiological, and laboratory characteristics and risk factors for severity and mortality of 289 hospitalized COVID‐19 patients.Allergy202176253355010.1111/all.14496 32662525
     [Google Scholar]
  35. AlthausK. MariniI. ZlamalJ. Antibody-induced procoagulant platelets in severe COVID-19 infection.Blood202113781061107110.1182/blood.2020008762 33512415
     [Google Scholar]
  36. ZaidY. PuhmF. AllaeysI. Platelets can associate with SARS-CoV-2 RNA and are hyperactivated in COVID-19.Circ. Res.2020127111404141810.1161/CIRCRESAHA.120.317703 32938299
     [Google Scholar]
  37. Al-SamkariH. Karp LeafR.S. DzikW.H. COVID-19 and coagulation: Bleeding and thrombotic manifestations of SARS-CoV-2 infection.Blood2020136448950010.1182/blood.2020006520 32492712
     [Google Scholar]
  38. UrbanoM. CostaE. GeraldesC. Hematological changes in SARS-COV-2 positive patients.Hematol. Transfus. Cell Ther.202244221822410.1016/j.htct.2021.12.001 35098036
     [Google Scholar]
  39. ChenZ. XuW. MaW. Clinical laboratory evaluation of COVID-19.Clin. Chim. Acta202151917218210.1016/j.cca.2021.04.022 33939954
     [Google Scholar]
  40. Cavalcante-SilvaL.H.A. CarvalhoD.C.M. LimaÉ.A. Neutrophils and COVID-19: The road so far.Int. Immunopharmacol.20219010723310.1016/j.intimp.2020.107233 33290963
     [Google Scholar]
  41. BarnesB.J. AdroverJ.M. Baxter-StoltzfusA. Targeting potential drivers of COVID-19: Neutrophil extracellular traps.J. Exp. Med.20202176e2020065210.1084/jem.20200652 32302401
     [Google Scholar]
  42. MiddletonE.A. HeX.Y. DenormeF. Neutrophil extracellular traps contribute to immunothrombosis in COVID-19 acute respiratory distress syndrome.Blood2020136101169117910.1182/blood.2020007008 32597954
     [Google Scholar]
  43. Ortega-RojasS. Salazar-TallaL. Romero-CerdánA. The neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio as predictors of mortality in older adults hospitalized with COVID-19 in Peru.Dis. Markers2022202211310.1155/2022/2497202 35937941
     [Google Scholar]
  44. MantaB. SarkisianA.G. FontanaB.G. PradoV.P. Pathophysiology of the disease COVID-19.Odontoestomatologia2022243911910.22592/ode2022n39e312
     [Google Scholar]
  45. SolimandoA.G. SuscaN. BorrelliP. Short-term variations in neutrophil-to-lymphocyte and urea-to-creatinine ratios anticipate intensive care unit admission of COVID-19 patients in the emergency department.Front. Med.2021762517610.3389/fmed.2020.625176 33553217
     [Google Scholar]
  46. ChenR. SangL. JiangM. Longitudinal hematologic and immunologic variations associated with the progression of COVID-19 patients in China.J. Allergy Clin. Immunol.202014618910010.1016/j.jaci.2020.05.003 32407836
     [Google Scholar]
  47. PanF. YangL. LiY. Factors associated with death outcome in patients with severe coronavirus disease-19 (COVID-19): A case-control study.Int. J. Med. Sci.20201791281129210.7150/ijms.46614 32547323
     [Google Scholar]
  48. ZiniG. BellesiS. RamundoF. d’OnofrioG. Morphological anomalies of circulating blood cells in COVID‐19.Am. J. Hematol.202095787087210.1002/ajh.25824 32279346
     [Google Scholar]
  49. ChelariuA.C. ComanA.E. LionteC. The value of early and follow-up elevated scores based on peripheral complete blood cell count for predicting adverse outcomes in COVID-19 patients.J. Pers. Med.20221212203710.3390/jpm12122037 36556258
     [Google Scholar]
  50. BurkeH. FreemanA. O’ReganP. Biomarker identification using dynamic time warping analysis: A longitudinal cohort study of patients with COVID-19 in a UK tertiary hospital.BMJ Open2022122e05033110.1136/bmjopen‑2021‑050331 35168965
     [Google Scholar]
  51. GavriilakiE. AnyfantiP. GavriilakiM. LazaridisA. DoumaS. GkaliagkousiE. Endothelial dysfunction in COVID-19: Lessons learned from coronaviruses.Curr. Hypertens. Rep.20202296310.1007/s11906‑020‑01078‑6 32852642
     [Google Scholar]
  52. McElvaneyO.J. McEvoyN.L. McElvaneyO.F. Characterization of the inflammatory response to severe COVID-19 illness.Am. J. Respir. Crit. Care Med.2020202681282110.1164/rccm.202005‑1583OC 32584597
     [Google Scholar]
  53. VabretN. BrittonG.J. GruberC. Immunology of COVID-19: Current state of the science.Immunity202052691094110.1016/j.immuni.2020.05.002 32505227
     [Google Scholar]
  54. Lozada-RequenaI. Núñez PonceC. COVID-19: Immune response and therapeutic perspectives.Rev. Peru. Med. Exp. Salud Publica202037231231910.17843/rpmesp.2020.372.5490 32876223
     [Google Scholar]
  55. QuintoNY LópezEC Tapia CartellanosV Maita VillavicencioY Quispe MamaniJQ Quispe CutipaAB COVID-19: Literature review on immunity.SITUA 202225110.51343/si.v25i1.876
     [Google Scholar]
  56. ZhouF. YuT. DuR. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study.Lancet2020395102291054106210.1016/S0140‑6736(20)30566‑3 32171076
     [Google Scholar]
  57. HenryB.M. de OliveiraM.H.S. BenoitS. PlebaniM. LippiG. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): A meta-analysis.Clin. Chem. Lab. Med.20205871021102810.1515/cclm‑2020‑0369 32286245
     [Google Scholar]
  58. Pulido-ArenasJ. Saa-GonzálezD. MuñozO.M. Cañas-ArboledaA. Serial measurements of lymphocytes, D-dimer, LDH, and CRP do not improve the ability to predict COVID-19 adverse outcomes.J. Int. Med. Res.202351510.1177/03000605231173795 37170749
     [Google Scholar]
  59. AghbashP.S. RasizadehR. ShirvalilooM. NahandJ.S. BaghiH.B. Dynamic alterations in white blood cell counts and SARS-CoV-2 shedding in saliva: An infection predictor parameter.Front. Med.202310120892810.3389/fmed.2023.1208928 37396915
     [Google Scholar]
  60. SharafiF. Jafarzadeh EsfehaniR. Moodi GhalibafA. JarahiL. ShamshirianA. MozdourianM. Leukopenia and leukocytosis as strong predictors of COVID‐19 severity: A cross‐sectional study of the hematologic abnormalities and COVID‐19 severity in hospitalized patients.Health Sci. Rep.2023610e157410.1002/hsr2.1574 37779668
     [Google Scholar]
  61. RahiM.S. JindalV. ReyesS.P. GunasekaranK. GuptaR. JaiyesimiI. Hematologic disorders associated with COVID-19: A review.Ann. Hematol.2021100230932010.1007/s00277‑020‑04366‑y 33415422
     [Google Scholar]
  62. SharifF. KhanS. JunaidA. Early hematological indicators of severe COVID‐19 disease in hospitalized patients: Data from a South Asian population.Int. J. Lab. Hematol.20214351237124210.1111/ijlh.13533 33837662
     [Google Scholar]
  63. Ali MudeA.S. Mohamed Agena MusaA.E. Exploring hematological parameters and their prognostic value in adult COVID-19 patients: Insights from Mogadishu, Somalia.Adv. Hematol.202320231710.1155/2023/8862457 37822646
     [Google Scholar]
  64. SejópolesM.D. Souza-SilvaJ.P. Silva-SantosC. Paula-DuarteM.M. FontesC.J.F. GomesL.T. Prognostic value of neutrophil and lymphocyte counts and neutrophil/lymphocyte ratio for predicting death in patients hospitalized for COVID-19.Heliyon202396e1696410.1016/j.heliyon.2023.e16964 37292322
     [Google Scholar]
  65. LiJ. ZhangK. Zhang, Gu Z, Huang C. Neutrophils in COVID-19: Recent insights and advances.Virol. J.202320116910.1186/s12985‑023‑02116‑w 37533131
     [Google Scholar]
  66. YangA.P. LiuJ. TaoW. LiH. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients.Int. Immunopharmacol.20208410650410.1016/j.intimp.2020.106504 32304994
     [Google Scholar]
  67. GuoZ. ZhangZ. PrajapatiM. LiY. Lymphopenia caused by virus infections and the mechanisms beyond.Viruses2021139187610.3390/v13091876 34578457
     [Google Scholar]
  68. KılıcJ. EbikB. BacaksızF. EkinN. KalınB.S.I.S. Is lymphopenia a predictor of mortality in patients with COVID-19?Acta Clin. Croat.2023621828710.20471/acc.2023.62.01.10 38304379
     [Google Scholar]
  69. ZhengY. ZhangY. ChiH. The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: A retrospective study.Clin. Chem. Lab. Med.20205871106111510.1515/cclm‑2020‑0377 32352397
     [Google Scholar]
  70. MeiJ. HuW. ChenQ. Development and external validation of a COVID-19 mortality risk prediction algorithm: A multicentre retrospective cohort study.BMJ Open20201012e04402810.1136/bmjopen‑2020‑044028 33361083
     [Google Scholar]
  71. RahmanT KhandakarA HoqueME Development and validation of an early scoring system for prediction of disease severity in COVID-19 using complete blood count parameters.IEEE Access 202191204224110.1109/ACCESS.2021.310532 34786318
     [Google Scholar]
  72. AggarwalS. BalajiS. SinghT. Association between ambient air pollutants and meteorological factors with SARS-CoV-2 transmission and mortality in India: An exploratory study.Environ. Health202120112010.1186/s12940‑021‑00804‑0 34794454
     [Google Scholar]
  73. CzwojdzińskaM TerpińskaM KuźniarskiA PłaczkowskaS PiwowarA. Exposure to PM2.5 and PM10 and COVID-19 infection rates and mortality: A one-year observational study in Poland.Biomed J 2021446)(1S253610.1016/j.bj.2021.11.006 34801766
     [Google Scholar]
  74. GajendraS. Spectrum of hematological changes in COVID-19.Am. J. Blood Res.20221214353 35291254
     [Google Scholar]
  75. Rostami-FarZ. RahmaniK. MansouriK. ErfanM.B.K. Shaveisi-ZadehF. NikkhooB. Complete blood count as an indicator of COVID-19 disease severity.J Clin Res Paramed Sci202211210.5812/jcrps‑133320
     [Google Scholar]
  76. HwangJ. HanY.J. YonD.K. Clinical significance of hepatosplenic thrombosis in vaccine-induced immune thrombotic thrombocytopenia after ChAdOx1 nCoV-19 vaccination.Int. J. Infect. Dis.202211611412110.1016/j.ijid.2021.12.352 34958931
     [Google Scholar]
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Association between Changes in Haematological Parameters and Mortality in Patients Hospitalized Due to Severe COVID-19 in a Peruvian Reference Hospital
Coronaviruses 6, e200324228179 (2025); https://doi.org/10.2174/0126667975298504240311064331
/content/journals/covid/10.2174/0126667975298504240311064331
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  • Article Type:     Research Article
Keyword(s): biomarkers; COVID-19; hematologic tests; mortality; NLR; SARS-CoV-2

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