Evaluation of automated synovial fluid total cell count and percent polymorphonuclear leukocytes on a Sysmex XN-1000 analyzer for identifying patients at risk of septic arthritis.


Journal

Clinica chimica acta; international journal of clinical chemistry
ISSN: 1873-3492
Titre abrégé: Clin Chim Acta
Pays: Netherlands
ID NLM: 1302422

Informations de publication

Date de publication:
Nov 2020
Historique:
received: 01 06 2020
revised: 23 06 2020
accepted: 31 07 2020
pubmed: 9 8 2020
medline: 22 6 2021
entrez: 9 8 2020
Statut: ppublish

Résumé

Total cell counts (TC-BF) and percent polymorphonuclear cells (%PMN) of synovial fluid (SF) aspirates provide important cues for the timely diagnosis and management of septic arthritis. To facilitate faster turnaround time, we compared automated to manual TC-BF and differential counts in order to identify reporting cut-offs for automated TC-BF and %PMN that would allow release of automated results concordant with manual counts and differentials. Automated TC-BF and %PMN counts of a non-validated analyzer (Analyzer-B in STAT laboratory) were compared to a validated analyzer (Analyzer-A) and manual TC-BF counts and cytospin differentials. Concordance and %differences of Analyzer-B versus Analyzer-A and manual counts were assessed by linear regression analysis and Bland-Altman comparison. Overall, automated and manual counts displayed good correlation. A majority of samples demonstrated unacceptable (>20%) differences between automated and manual counts at lower TC-BF (<10,000 cells/μl) and %PMN (<60%). Based on good overall correlation and fewer samples with unacceptable (>20%) differences between automated and manual counts, we adopted TC-BF > 10,000 cells/μl and %PMN > 60% as cutoffs for reporting automated counts. These cutoffs minimize differences between automated and manual cell counts and differentials and would allow rapid automated reporting in the vast majority of septic arthritis cases.

Sections du résumé

BACKGROUND BACKGROUND
Total cell counts (TC-BF) and percent polymorphonuclear cells (%PMN) of synovial fluid (SF) aspirates provide important cues for the timely diagnosis and management of septic arthritis. To facilitate faster turnaround time, we compared automated to manual TC-BF and differential counts in order to identify reporting cut-offs for automated TC-BF and %PMN that would allow release of automated results concordant with manual counts and differentials.
METHODS METHODS
Automated TC-BF and %PMN counts of a non-validated analyzer (Analyzer-B in STAT laboratory) were compared to a validated analyzer (Analyzer-A) and manual TC-BF counts and cytospin differentials. Concordance and %differences of Analyzer-B versus Analyzer-A and manual counts were assessed by linear regression analysis and Bland-Altman comparison.
RESULTS RESULTS
Overall, automated and manual counts displayed good correlation. A majority of samples demonstrated unacceptable (>20%) differences between automated and manual counts at lower TC-BF (<10,000 cells/μl) and %PMN (<60%).
CONCLUSIONS CONCLUSIONS
Based on good overall correlation and fewer samples with unacceptable (>20%) differences between automated and manual counts, we adopted TC-BF > 10,000 cells/μl and %PMN > 60% as cutoffs for reporting automated counts. These cutoffs minimize differences between automated and manual cell counts and differentials and would allow rapid automated reporting in the vast majority of septic arthritis cases.

Identifiants

pubmed: 32763227
pii: S0009-8981(20)30382-X
doi: 10.1016/j.cca.2020.07.058
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

416-420

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

Abdulrahman Saadalla (A)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Jose Jara Aguirre (J)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Amy M Wockenfus (AM)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Brandon R Kelley (BR)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Rebecca L Swanson (RL)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Matthew T Howard (MT)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States.

Brad S Karon (BS)

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States. Electronic address: Karon.bradley@mayo.edu.

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