Literature DB >> 33636799

Impact of Integrating Rumke Statistics to Assist with Choosing Between Automated Hematology Analyzer Differentials vs Manual Differentials.

Laura Stephens1, Wendy Hintz-Prunty1, Hans-Inge Bengtsson2, James A Proudfoot3, Sandip Pravin Patel4,5, H Elizabeth Broome1,4.   

Abstract

BACKGROUND: To optimize precision of nucleated blood cell counting, the clinical laboratory scientist should post the automated differential rather than the manual differential if the former is within the 95% CI of the latter, as determined by the "Rumke statistic." The objective of this study was to determine the potential impact of real-time, computer-assisted use of Rumke statistics for more judicious use of the automated vs digitally imaged, manual differential.
METHODS: Complete blood counts with automated differentials produced by a XE5000™ hematology analyzer (Sysmex) were compared with both the DM96 (CellaVision™ AB) preclassification differentials and the posted reclassified manual differentials, using the Rumke 95% CIs as calculated using the Clopper-Pearson method.
RESULTS: A total of 44.7% of manual differentials had no statistical or clinical justification over the automated differential. In addition, 31.1% of manual differentials had statistical discrepancies between the instrument absolute neutrophil count (IANC) and manual absolute neutrophil count (ANC). Nineteen of these IANC/manual ANC discrepant samples had ANCs below 1500/μL, a decision level for cancer treatment. Holding the IANC when it is less than 2000/μL until after manual smear review would have prevented the posting of any IANC vs manual ANC discrepant results at the 1500/μL ANC decision threshold.
CONCLUSIONS: A real-time operator alert concerning the statistical identity of imaging device differentials vs automated differentials could have reduced manual differentials by nearly 45%. Not posting unnecessary manual differentials for the cases with IANC/manual ANC discrepancies would have likely reduced clinical error/confusion.
© 2016 American Association for Clinical Chemistry.

Entities:  

Year:  2017        PMID: 33636799     DOI: 10.1373/jalm.2016.021030

Source DB:  PubMed          Journal:  J Appl Lab Med        ISSN: 2475-7241


  1 in total

1.  Choosing wisely during the COVID-19 pandemic: optimising outpatient cancer care while conserving resources with a new algorithm to report automated ANC results.

Authors:  Maly Fenelus; Tamiqua Graham; Ryan Golden; Jessica L Bautista; Rachel J So; Nora Plante; Ellinor I B Peerschke
Journal:  J Clin Pathol       Date:  2020-11-16       Impact factor: 3.411

  1 in total

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