Clin Chem Lab Med. 2026 Jan 2. doi: 10.1515/cclm-2025-1202. Online ahead of print.
ABSTRACT
OBJECTIVES: The performance of a novel urine particle analyzer, fluidlab 2 (Anvajo GmbH, Dresden, Germany), was evaluated against phase-contrast visual microscopy according to the most recent EFLM European Urinalysis Guideline.
METHODS: The fluidlab 2 device combines digital holographic microscopy with neural network-based object detection for particle classification. Its compact benchtop design is suitable for bedside use, reducing turnaround times. The analytical performance (imprecision, linearity, LoQ) was evaluated according to the 2023 EFLM Urinalysis Guideline. Method comparison involved the analysis of 450 urine samples, assessing RBC, WBC, and SEC counts against visual microscopy using Passing-Bablok regression and Spearman’s correlation. Bland-Altman plots were used to evaluate the agreement with clinical performance standards, while weighted Cohen’s kappa was used to measure diagnostic agreement on an ordinal scale.
RESULTS: By applying Dahlberg’s procedure, a desirable relative coefficient of variation R(CV) ≤2.0 was obtained for RBC and WBC. Linearity of up to 7 × 106/L and 6 × 106/L was achieved. The estimated LoQ at CV=30 % reached 20 × 106/L for RBC and 5 × 106/L for WBC. Spearman’s correlation coefficient against visual microscopy was 0.86, 0.92 and 0.94 for RBC, WBC and SEC, respectively. Agreement with visual microscopy (Cohen’s weighted kappa) was 0.92 for RBC, 0.93 for WBC, 0.96 for SEC, 0.86 for casts, 0.82 for non-SEC, 0.33 for crystals and 0.51 for bacterial counts.
CONCLUSIONS: Fluidlab 2 provides desirable imprecision for RBC and WBC, and meets the criteria for linearity and LoQ. Cohen’s weighted kappa coefficients show an optimal comparison to visual microscopy for RBC, WBC and SEC and a minimum comparison for casts and non-SEC. This evaluation demonstrated promising results for the use of the fluidlab 2 analyzer in a clinical setting to detect kidney-related diseases based on urine particle analysis.
PMID:41479135 | DOI:10.1515/cclm-2025-1202