Comparison of Monocyte Distribution Width (MDW) and Procalcitonin for early recognition of sepsis
Autoři:
Ennio Polilli aff001; Federica Sozio aff002; Antonella Frattari aff003; Laura Persichitti aff001; Marina Sensi aff004; Raffaella Posata aff004; Marco Di Gregorio aff002; Antonina Sciacca aff002; Maria Elena Flacco aff005; Lamberto Manzoli aff006; Giancarlo Di Iorio aff001; Giustino Parruti aff002
Působiště autorů:
Clinical Pathology Unit, Pescara General Hospital, Pescara, Italy
aff001; Infectious Diseases Unit, Pescara General Hospital, Pescara, Italy
aff002; Unit of Intensive Care, Pescara General Hospital, Pescara, Italy
aff003; Clinical Pathology Department, University of Chieti, Chieti, Italy
aff004; Local Health Unit of Pescara, Pescara, Italy
aff005; Department of Medical Sciences, University of Ferrara, Ferrara, Italy
aff006
Vyšlo v časopise:
PLoS ONE 15(1)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0227300
Souhrn
We carried out a prospective observational study to evaluate whether Monocyte Distribution Width (MDW) may play a role in identifying patients with sepsis in comparison with Procalcitonin (PCT). We prospectively enrolled all consecutive patients hospitalized at the Infectious Diseases Unit of Pescara General Hospital for bacterial infection or sepsis. MDW values were collected for all patients. Clinical characteristics, demographic data, past and present medical history, microbiological results, PCT, as well as neutrophil and monocytes indices at entry were compared in the 2 groups. Two-hundred-sixty patients were enrolled, 63.5% males, aged 59.1±19.5 years. Sepsis was diagnosed in 105 (40.4%); in 60 (57.1%) at least 1 microorganism was isolated from blood cultures. In multivariate models, MDW as a continuous variable (OR:1.57 for each unit increase; 95%CI: 1.31–1.87, p<0.001) and PCT˃1 ng/mL (OR: 48.5; 95%CI: 14.7–160.1, p<0.001) were independently associated with sepsis. Statistical best cut points associated with sepsis were 22.0 for MDW and 1.0 ng/mL for PCT whereas MDW values<20 were invariably associated with negative blood cultures. At ROC curve analysis, the AUC of MDW (0.87) was nearly overlapping that of PCT (0.88). Our data suggest that incorporating MDW within current routine WBC counts and indices may be of remarkable use for detection of sepsis. Further research is warranted.
Klíčová slova:
Blood – Respiratory infections – Hematology – Blood cells – Monocytes – Neutrophils – Sepsis – Blood counts
Zdroje
1. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315: 801–810. doi: 10.1001/jama.2016.0287 26903338
2. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med. 2013;41: 580–637. doi: 10.1097/CCM.0b013e31827e83af 23353941
3. Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis. 2013;13: 426–435. doi: 10.1016/S1473-3099(12)70323-7 23375419
4. Uzzan B, Cohen R, Nicolas P, Cucherat M, Perret G-Y. Procalcitonin as a diagnostic test for sepsis in critically ill adults and after surgery or trauma: a systematic review and meta-analysis. Crit Care Med. 2006;34: 1996–2003. doi: 10.1097/01.CCM.0000226413.54364.36 16715031
5. Sager R, Kutz A, Mueller B, Schuetz P. Procalcitonin-guided diagnosis and antibiotic stewardship revisited. BMC Med. 2017;15: 15. doi: 10.1186/s12916-017-0795-7 28114931
6. Aydemir H, Piskin N, Akduman D, Kokturk F, Aktas E. Platelet and mean platelet volume kinetics in adult patients with sepsis. Platelets. 2015;26: 331–335. doi: 10.3109/09537104.2012.701027 22731700
7. Shalaby MM, Sobeih AA, Abdulghany WE, Behiry EG, Ismail YM, Abd-El-Aziz MA. Mean platelet volume and serum uric acid in neonatal sepsis: A case-control study. Ann Med Surg 2012. 2017;20: 97–102. doi: 10.1016/j.amsu.2017.06.015 28761638
8. Wang A-Y, Ma H-P, Kao W-F, Tsai S-H, Chang C-K. Red blood cell distribution width is associated with mortality in elderly patients with sepsis. Am J Emerg Med. 2018;36: 949–953. doi: 10.1016/j.ajem.2017.10.056 29133071
9. Crouser ED, Parrillo JE, Seymour C, Angus DC, Bicking K, Tejidor L, et al. Improved Early Detection of Sepsis in the ED With a Novel Monocyte Distribution Width Biomarker. Chest. 2017;152: 518–526. doi: 10.1016/j.chest.2017.05.039 28625579
10. Sinapidis D, Kosmas V, Vittoros V, Koutelidakis IM, Pantazi A, Stefos A, et al. Progression into sepsis: an individualized process varying by the interaction of comorbidities with the underlying infection. BMC Infect Dis. 2018;18: 242. doi: 10.1186/s12879-018-3156-z 29843641
11. Wang HE, Shapiro NI, Griffin R, Safford MM, Judd S, Howard G. Chronic medical conditions and risk of sepsis. PLoS One. 2012;7(10):e48307. doi: 10.1371/journal.pone.0048307 23118977
12. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40: 373–383. doi: 10.1016/0021-9681(87)90171-8 3558716
13. Hall WH, Ramachandran R, Narayan S, Jani AB, Vijayakumar S. An electronic application for rapidly calculating Charlson comorbidity score. BMC Cancer. 2004;4: 94. doi: 10.1186/1471-2407-4-94 15610554
14. Vincent J-L, Martin GS, Levy MM. qSOFA does not replace SIRS in the definition of sepsis. Crit Care Lond Engl. 2016;20: 210. doi: 10.1186/s13054-016-1389-z 27423462
15. Tian H, Zhou J, Weng L, Hu X, Peng J, Wang C, et al. Accuracy of qSOFA for the diagnosis of sepsis-3: a secondary analysis of a population-based cohort study. J Thorac Dis. 2019;11: 2034–2042. doi: 10.21037/jtd.2019.04.90 31285896
16. Dorsett M, Kroll M, Smith CS, Asaro P, Liang SY, Moy HP. qSOFA Has Poor Sensitivity for Prehospital Identification of Severe Sepsis and Septic Shock. Prehospital Emerg Care Off J Natl Assoc EMS Physicians Natl Assoc State EMS Dir. 2017;21: 489–497. doi: 10.1080/10903127.2016.1274348 28121217
17. Celik IH, Demirel G, Aksoy HT, Erdeve O, Tuncer E, Biyikli Z, et al. Automated determination of neutrophil VCS parameters in diagnosis and treatment efficacy of neonatal sepsis. Pediatr Res. 2012;71: 121–125. doi: 10.1038/pr.2011.16 22289860
18. Chaves F, Tierno B, Xu D. Quantitative determination of neutrophil VCS parameters by the Coulter automated hematology analyzer: new and reliable indicators for acute bacterial infection. Am J Clin Pathol. 2005;124: 440–444. doi: 10.1309/LLF7-5W0F-WQQ8-TCC5 16191513
19. Mardi D, Fwity B, Lobmann R, Ambrosch A. 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: 410–418. doi: 10.1111/j.1751-553X.2009.01202.x 19919621
20. Buoro S, Seghezzi M, Vavassori M, Dominoni P, Apassiti Esposito S, Manenti B, et al. Clinical significance of cell population data (CPD) on Sysmex XN-9000 in septic patients with our without liver impairment. Ann Transl Med. 2016;4: 418. doi: 10.21037/atm.2016.10.73 27942509
21. Lee A-J, Kim S-G. Mean cell volumes of neutrophils and monocytes are promising markers of sepsis in elderly patients. Blood Res. 2013;48: 193–197. doi: 10.5045/br.2013.48.3.193 24086939
22. Siegel JD, Rhinehart E, Jackson M, Chiarello L, Healthcare Infection Control Practices Advisory Committee. Management of multidrug-resistant organisms in health care settings, 2006. Am J Infect Control. 2007;35: S165–193. doi: 10.1016/j.ajic.2007.10.006 18068814
23. DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988;44: 837–845. 3203132
24. Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3: 32–35. doi: 10.1002/1097-0142(1950)3:1<32::aid-cncr2820030106>3.0.co;2-3 15405679
25. Schuetz P, Albrich W, Mueller B. Procalcitonin for diagnosis of infection and guide to antibiotic decisions: past, present and future. BMC Med. 2011;9: 107. doi: 10.1186/1741-7015-9-107 21936959
26. Wang SY, Mak KL, Chen LY, Chou MP, Ho CK. Heterogeneity of human blood monocyte: two subpopulations with different sizes, phenotypes and functions. Immunology. 1992;77: 298–303. 1427982
27. Tak T, van Groenendael R, Pickkers P, Koenderman L. Monocyte Subsets Are Differentially Lost from the Circulation during Acute Inflammation Induced by Human Experimental Endotoxemia. J Innate Immun. 2017;9: 464–474. doi: 10.1159/000475665 28641299
28. Fingerle G, Pforte A, Passlick B, Blumenstein M, Ströbel M, Ziegler-Heitbrock HW. The novel subset of CD14+/CD16+ blood monocytes is expanded in sepsis patients. Blood. 1993;82: 3170–3176. 7693040
29. Crouser ED, Parrillo JE, Seymour CW, Angus DC, Bicking K, Esguerra VG, et al. Monocyte Distribution Width: A Novel Indicator of Sepsis-2 and Sepsis-3 in High-Risk Emergency Department Patients. Crit Care Med. 2019;47: 1018–1025. doi: 10.1097/CCM.0000000000003799 31107278
30. Lopez-Molina M, Tejedor Ganduxé X, Martínez Iribarren A, Espinosa M, Torres S, Sala M, et al. Influence of K2-EDTA and K3-EDTA tubes for monocyte distribution width measurement. Clinica Chimica Acta. 2019; 493: S379 –S433. doi: 10.1016/j.cca.2019.03.819
31. Zaccone V, Tosoni A, Passaro G, Vallone CV, Impagnatiello M, Li Puma DD, et al. Sepsis in Internal Medicine wards: current knowledge, uncertainties and new approaches for management optimization. Ann Med. 2017;49: 582–592. doi: 10.1080/07853890.2017.1332776 28521523
32. Moore LJ, Moore FA, Todd SR, Jones SL, Turner KL, Bass BL. Sepsis in general surgery: the 2005–2007 national surgical quality improvement program perspective. Arch Surg Chic Ill 1960. 2010;145: 695–700. doi: 10.1001/archsurg.2010.107 20644134
33. Haydar S, Spanier M, Weems P, Wood S, Strout T. Comparison of QSOFA score and SIRS criteria as screening mechanisms for emergency department sepsis. Am J Emerg Med. 2017;35: 1730–1733. doi: 10.1016/j.ajem.2017.07.001 28712645
34. Williams JM, Greenslade JH, McKenzie JV, Chu K, Brown AFT, Lipman J. Systemic Inflammatory Response Syndrome, Quick Sequential Organ Function Assessment, and Organ Dysfunction: Insights From a Prospective Database of ED Patients With Infection. Chest. 2017;151: 586–596. doi: 10.1016/j.chest.2016.10.057 27876592
35. Brink A, Alsma J, Verdonschot RJCG, Rood PPM, Zietse R, Lingsma HF, et al. Predicting mortality in patients with suspected sepsis at the Emergency Department; A retrospective cohort study comparing qSOFA, SIRS and National Early Warning Score. PloS One. 2019;14: e0211133. doi: 10.1371/journal.pone.0211133 30682104
36. Song J-U, Sin CK, Park HK, Shim SR, Lee J. Performance of the quick Sequential (sepsis-related) Organ Failure Assessment score as a prognostic tool in infected patients outside the intensive care unit: a systematic review and meta-analysis. Crit Care Lond Engl. 2018;22: 28. doi: 10.1186/s13054-018-1952-x 29409518
37. Usman OA, Usman AA, Ward MA. Comparison of SIRS, qSOFA, and NEWS for the early identification of sepsis in the Emergency Department. Am J Emerg Med. 2018; doi: 10.1016/j.ajem.2018.10.058 30470600
Článok vyšiel v časopise
PLOS One
2020 Číslo 1
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Ne každé mimoděložní těhotenství musí končit salpingektomií
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
- Masturbační chování žen v ČR − dotazníková studie
Najčítanejšie v tomto čísle
- Psychometric validation of Czech version of the Sport Motivation Scale
- Comparison of Monocyte Distribution Width (MDW) and Procalcitonin for early recognition of sepsis
- Effects of supplemental creatine and guanidinoacetic acid on spatial memory and the brain of weaned Yucatan miniature pigs
- Accelerated sparsity based reconstruction of compressively sensed multichannel EEG signals