Conta differenziale leucocitaria e parametri morfometrici determinati con Mindray BC-6800 Plus: un possibile strumento predittivo per lo screening di sepsi
Leucocyte differential count and morphometric parameters by Mindray BC-6800 Plus: a possible predictive tool for screening of sepsis

AUTORI

ABSTRACT

Leucocyte differential count and morphometric parameters by Mindray BC-6800 Plus: a possible predictive tool for screening of sepsis

Background: sepsis is a serious disease with high mortality rate, threatening human health. Clinicians need to diagnose the condition in time to develop an effective treatment plan; therefore, a quick and early screening to rule in or rule out sepsis has become an urgent problem in clinical laboratories. Different markers are used to diagnose sepsis, but they have limitations and require additional examination. The aim of this study is to use leucocyte count and other haematological parameters obtained by Mindray BC-6800-plus, to identify sepsis biomarkers that are early, quickly, conveniently, and at low cost.

Methods: a total of 479 venous whole blood samples were collected: 63 control samples (blood donors), and 416 samples hospitalized at the emergency department with symptoms attributable to sepsis with a procalcitonin request. Morphometric parameters are reported using Mindray BC-6800 plus analyzer: white blood cell count-related parameters like cell population data named X, Y, Z, neutrophil-lymphocyte ratio, and index of immature granulocytes. Statistical analysis was performed using the Kruskal-Wallis test to evaluate significative differences among the groups. ROC curves were also examined to extrapolate a cut-off of pathogenicity.

Results: we found a significant statistically difference between the control and the sepsis groups for a number of haematological parameters. The ROC curves highlight acceptable sensitivity and specificity values for some parameters, and suggest possible cut-offs.

Discussion: some qualitative and quantitative parameters of total count blood can be of help with the screening of sepsis upon admission to the emergency department.

BIBLIOGRAFIA

1. Unorthodox cancer medicine. CA Cancer J Clin 1989;39:62-3.
2. Chiu C, Legrand M. Epidemiology of sepsis and septic shock. Curr Opin Anaesthesiol 2021;34:71-6.
3. Meza-Escobar LE, Rehou S, Jeschke MG. Sepsis Definitions in Burns. Surg Infect (Larchmt) 2021;22:28-36.
4. Shankar-Hari M, Phillips GS, Levy ML, et al. Developing a New Definition and Assessing New Clinical Criteria for Septic Shock: For the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016;315:775-87.
5. Lin GL, McGinley JP, Drysdale SB, et al. Epidemiology and immune pathogenesis of viral sepsis. Front Immunol 2018;9:2147.
6. Gu X, Zhou F, Wang Y, et al. Respiratory viral sepsis: epidemiology, pathophysiology, diagnosis and treatment. Eur Respir Rev 2020;29:200038.
7. Kocak Tufan Z, Kayaaslan B, Mer M. COVID-19 and Sepsis. Turk J Med Sci 2021;51:3301-11.
8. Norse AB, Guirgis F, Black LP, et al. Updates and controversies in the early management of sepsis and septic shock. Emerg Med Pract 2021;23 Suppl 4-2:1-24.
9. Guirgis F, Black LP, DeVos EL. Updates and controversies in the early management of sepsis and septic shock. Emerg Med Pract 2018;20:1-28.
10. Keeley A, Hine P, Nsutebu E. The recognition and management of sepsis and septic shock: a guide for non-intensivists. Postgrad Med J 2017;93:626-34.
11. Evans T. Diagnosis and management of sepsis. Clin Med (London) 2018;18:146-9.
12. Taeb AM, Hooper MH, Marik PE. Sepsis: Current Definition, Pathophysiology, Diagnosis, and Management. Nutr Clin Pract 2017; 32:296-308.
13. Devia Jaramillo G, Ibanez Pinilla M. Quick Sequential Organ Failure Assessment, Sequential Organ Failure Assessment, and Procalcitonin for Early Diagnosis and Prediction of Death in Elderly Patients with Suspicion of Sepsis in the Emergency Department, Based on Sepsis-3 Definition. Gerontology 2022;68:171-80.
14. Gu X, Shao J, Zhang B, et al. Early identification value of quick sequential organ failure assessment score in patients with sepsis of different ages. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2021;33:798-802.
15. Schmoch T, Westhoff JH, Decker SO, et al. Next-generation sequencing diagnostics of bacteremia in pediatric sepsis. Medicine (Baltimore) 2021;100:e26403.
16. Riedel S, Melendez JH, An AT, et al. Procalcitonin as a marker for the detection of bacteremia and sepsis in the emergency department. Am J Clin Pathol 2011;135:182-9.
17. Spoto S, Cella E, de Cesaris M, et al. Procalcitonin and MR-Proadrenomedullin Combination with SOFA and qSOFA scores for sepsis diagnosis and prognosis: A diagnostic algorithm. Shock 2018;50:44-52.
18. Lee S, Song J, Park DW, et al. Diagnostic and prognostic value of presepsin and procalcitonin in non-infectious organ failure, sepsis, and septic shock: a prospective observational study according to the Sepsis-3 definitions. BMC Infect Dis 2022;22:8.
19. Liu B, Chen YX, Yin Q, et al. Diagnostic value and prognostic evaluation of Presepsin for sepsis in an emergency department. Crit Care 2013;17:R244.
20. Candel FJ, Borges Sa M, Belda S, et al. Current aspects in sepsis approach. Turning things around. Rev Esp Quimioter 2018;31:298-315.
21. Li P, Wang C, Pang S. The diagnostic accuracy of mid-regional pro-adrenomedullin for sepsis: a systematic review and meta-analysis. Minerva Anestesiol 2021;87:1117-27.
22. Zhao M, Duan M. Lactic acid, lactate clearance and procalcitonin in assessing the severity and predicting prognosis in sepsis. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue 2020;32:449-53.
23. Mardi D, Fwity B, Lobmann R, et al. Mean cell volume of neutrophils and monocytes compared with C-reactive protein, interleukin-6 and white blood cell count for prediction of sepsis and nonsystemic bacterial infections. Int J Lab Hematol 2010;32:410-8.
24. Boomer JS, Green JM, Hotchkiss RS. The changing immune system in sepsis: is individualized immuno-modulatory therapy the answer? Virulence 2014;5:45-56.
25. Luo Y, Lin J, Chen H,et al. Utility of neut-X, neut-Y and neut-Z parameters for rapidly assessing sepsis in tumor patients. Clin Chim Acta 2013;422:5-9.
26. Goyette RE, Key NS, Ely EW. Hematologic changes in sepsis and their therapeutic implications. Semin Respir Crit Care Med 2004;25:645-59.
27. Sinha H, Maitra S, Anand RK, et al. Epidemiology and Prognostic Utility of Cellular Components of Hematological System in Sepsis. Indian J Crit Care Med 2021;25:660-7.
28. Adane T, Worku M, Tigabu A, et al. Hematological Abnormalities in Culture Positive Neonatal Sepsis. Pediatric Health Med Ther 2022;13:217-25.
29. Seghezzi M, Buoro S, Previtali G, et al. A Preliminary Proposal for Quality Control Assessment and Harmonization of Leukocytes Morphology-structural Parameters (cell Population Data Parameters). J Med Biochem 2018;37:486-98.
30. Le Roux G, Vlad A, Eclache V, et al. Routine diagnostic procedures of myelodysplastic syndromes: value of a structural blood cell parameter (NEUT-X) determined by the Sysmex XE-2100. Int J Lab Hematol 2010;32:e237-43.
31. Urrechaga E, Boveda O, Aguirre U. Role of leucocytes cell population data in the early detection of sepsis. J Clin Pathol 2018;71:259-66.
32. Chaves F, Tierno B, Xu D. Neutrophil volume distribution width: a new automated hematologic parameter for acute infection. Arch Pathol Lab Med 2006;130:378-80.
33. Arora P, Gupta PK, Lingaiah R, et al. Volume, conductivity, and scatter parameters of leukocytes as early markers of sepsis and treatment response. J Lab Physicians 2019;11:29-33.
34. Ognibene A, Lorubbio M, Magliocca P, et al. Elevated monocyte distribution width in COVID-19 patients: The contribution of the novel sepsis indicator. Clin Chim Acta 2020;509:22-4.
35. Alsuwaidi L, Al Heialy S, Shaikh N, et al. Monocyte distribution width as a novel sepsis indicator in COVID-19 patients. BMC Infect Dis 2022;22:27.
36. Sinha M, Jupe J, Mack H, et al. Emerging Technologies for Molecular Diagnosis of Sepsis. Clin Microbiol Rev 2018;31:e00089.
37. Goudouris ES. Laboratory diagnosis of COVID-19. J Pediatr (Rio J) 2021;97:7-12.
38. Zini G, Cantelli F, Scavone F, et al. Hematological performance of a last generation automated blood cell counter: The Mindray BC-6800 Plus. Int J Lab Hematol 2020;42:439-49.
39. Wang N, Jiang J, Wang J, et al. Detection of nucleated red blood cells using the Mindray BC-6800Plus hematology analyzer: a clinical performance evaluation. Ann Palliat Med 2021;10:8808-17.
40. Lee HT, Park PW, Seo YH, et al. Performance evaluation of Mindray CAL 8000(BC-6800 and SC-120) hematology analyzer and slidemaker/stainer. J Clin Lab Anal 2017;31:e22065.
41. Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016;315:801-10.
42. Markwart R, Saito H, Harder T, et al. Epidemiology and burden of sepsis acquired in hospitals and intensive care units: a systematic review and meta-analysis. Intensive Care Med 2020;46:1536-51.
43. Fleischmann-Struzek C, Mellhammar L, Rose N, et al. Incidence and mortality of hospital- and ICU-treated sepsis: results from an updated and expanded systematic review and meta-analysis. Intensive Care Med 2020;46:1552-62.
44. Zhang W, Zhang Z, Pan S, et al. The clinical value of hematological neutrophil and monocyte parameters in the diagnosis and identification of sepsis. Ann Transl Med 2021;9:1680.
45. Al-Gwaiz LA, Babay HH. The diagnostic value of absolute neutrophil count, band count and morphologic changes of neutrophils in predicting bacterial infections. Med Princ Pract 2007;16:344-7.
46. Russell CD, Parajuli A, Gale HJ, et al. The utility of peripheral blood leucocyte ratios as biomarkers in infectious diseases: A systematic review and meta-analysis. J Infect 2019; 78:339-48.
47. Ayres LS, Sgnaolin V, Munhoz TP. Immature granulocytes index as early marker of sepsis. Int J Lab Hematol 2019;41:392-6.
48. Farkas JD. The complete blood count to diagnose septic shock. J Thorac Dis 2020;12 Suppl 1:S16-S21.
49. Urrechaga E. Reviewing the value of leukocytes cell population data (CPD) in the management of sepsis. Ann Transl Med 2020;8:953.
50. Biban P, Teggi M, Gaffuri M, et al. Cell population data (CPD) for early recognition of sepsis and septic shock in children: a pilot study. Front Pediatr 2021;9:642377.