ArticlePractical laboratory medicine2026
Red blood cell subpopulation ratios identify samples at risk of dipstick-flow cytometry hematuria discordance in Sysmex UN-Series analyzers.
Article in Practical laboratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objectives: To evaluate whether erythrocyte subpopulation structure, particularly the small-to-total RBC ratio (SRR), explains dipstick-flow cytometry hematuria discordance (DSD). Methods: A retrospective study including 3399 urine samples from unique primary care patients analyzed using Sysmex UN-series analyzers. Three discrepancy metrics were defined: dipstick-flow cytometry discordance (DSD), negative dipstick hematuria with elevated flow-cytometric RBC counts (≥15 cells/μL in men and ≥25 cells/μL in women); quantitative discordance (qDSD), the difference between flow-cytometric RBC counts and dipstick categories expressed on a standardized scale; and extreme discordance (eDSD), the highest decile of qDSD. Multivariable regression models evaluated associations between SRR, the lysed-to-total RBC ratio (LyRR), their interaction term, age, sex and urinary matrix parameters (white blood cell count, bacteria, osmolality, pH, yeast, and urinary crystals), combined to minimize collinearity. Additional analyses assessed whether these variables and clinical covariates were associated with SRR, and complementary models included alternative interaction terms, whereas sensitivity analyses included adjustment for total RBC. Results: SRR showed the strongest association with increased odds of DSD, whereas LyRR was inversely associated, with a significant positive SRR×LyRR interaction. Debris and urinary pH were positively associated with DSD, while bacterial and leukocyte counts showed inverse associations. SRR was not associated with qDSD but remained consistently associated with eDSD. Associations remained robust across sensitivity analyses and were independent of absolute RBC counts; however, in eDSD models, total RBC burden emerged as the strongest determinant. Conclusions: DSD reflects a structured phenomenon largely driven by erythrocyte subpopulation heterogeneity rather than random analytical variability.
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