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Background: Automated urine sediment analysis has been developed to address the limitations of microscopic examination of dysmorphic red blood cells (RBCs). We evaluated the urinary RBC distribution (URD) parameter of a recently launched automated urinary flow cytometry analyzer, UF-5000 (Sysmex, Kobe, Japan), to differentiate glomerular hematuria (GH) from non-GH (NGH).
Methods: Samples submitted for urine sediment analysis from patients with hematuria (>20 RBCs/μL) were divided into derivation (N=156; 101 GH, 55 NGH) and validation cohorts (N=107; 60 GH, 47 NGH). The clinical diagnosis of GH or NGH was established based on clinical data review. Differences in UF-5000 parameters (URD, small RBC, lysed RBC, RBC-P70FSC, RBC-SF-FSC-W, mean forward-scattered light, and mean side-scattered light) between GH and NGH, and areas under the ROC curves (AUC) were analyzed in the derivation cohort. The derived ideal cut-off value was evaluated in the validation cohort. We applied the Kitasato criteria to compare the diagnostic performance.
Results: URD (%), differed significantly between GH and NGH (<0.001) in the two cohorts. The AUC of URD was 0.814 and 0.806 in the derivation and validation cohorts, respectively. Using a cut-off of >20.1%, the sensitivity was 99.0%/89.4% and the specificity was 50.9%/63.3% in the derivation/validation cohort. When the Kitasato criteria were applied, the sensitivity and specificity were 80.2% and 52.7%, respectively.
Conclusions: URD is a rapid, objective, and quantitative measure that can be used to differentiate GH and NGH.
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http://dx.doi.org/10.3343/alm.2022.42.2.160 | DOI Listing |
Pediatr Infect Dis J
September 2025
From the Pediatric Infectious Diseases Unit, Gregorio Marañón University Hospital, Madrid, Spain.
Background: Vaccination is a key strategy to reduce infectious disease mortality. In pediatric heart transplant recipients (HTRs), the use of immunosuppressive therapy weakens immune responses, increasing the risk of viral infections. This study aimed to evaluate the immunogenicity of hepatitis B virus (HBV) revaccination in this vulnerable population.
View Article and Find Full Text PDFJ Clin Lab Anal
September 2025
Department of Nursing, National Tainan Junior College of Nursing, Tainan, Taiwan.
Background: Improving efficiency and reducing turnaround time are crucial in clinical laboratories. While automated analyzers such as the Beckman Coulter DxH 900 streamline workflow, subtle abnormalities like blasts and immature granulocytes (IGs) may be missed, especially in the absence of WBC-related suspect messages. This study evaluated whether integrating cell population data (CPD) with instrument messages could enhance detection accuracy.
View Article and Find Full Text PDFSleep
September 2025
Center for Sleep Medicine, Hospices Civils de Lyon, Lyon 1 University, Lyon, F-69000, France.
Current treatments for narcolepsy type 1 (NT1) have little impact on psychiatric, cognitive and metabolic comorbidities. Here, we evaluated the feasibility, safety and efficacy of a prospective Exercise Training (ET) program on sleep-related symptoms and comorbidities in NT1. Sedentary adult with NT1 participated in a 6-week supervised ET program followed by a 18-week self-directed program.
View Article and Find Full Text PDFMol Cell Biol
September 2025
Department of Hematology, Tohoku University Graduate School of Medicine, Sendai, Japan.
Erythropoiesis, i.e., process of red blood cell (RBC) production, is highly dependent on iron, with 60-70% of the total body iron incorporated into hemoglobin.
View Article and Find Full Text PDFBiol Lett
September 2025
Department of Science, Roma Tre University, Rome, Italy.
In the past decades, several authors have investigated the possibility that genome size is correlated with metabolic rates, obtaining conflicting results. The main biological explanation among the supporters of this correlation was related to the nucleotypic effect of the genome size, which, determining the cellular volume and hence the surface area-to-volume ratio, influences cellular metabolism. In the present study, I tested a different hypothesis: genome size, influencing red blood cell (RBC) volume, is correlated with capillary density and diameter.
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