Biological Variation of Creatinine, Cystatin C, and eGFR over 24 Hours.

BACKGROUND: Estimated glomerular filtration rate (eGFR) is widely used in clinical practice. This study assessed the within-subject biological variation (CVI) of different eGFR equations in people with chronic kidney disease (CKD) and people without CKD. The aims of this study were (a) to determine the 24-h biological variation profiles of creatinine, cystatin C, and eGFR and (b) to determine whether CVI of creatinine, cystatin C, and eGFR changes on deterioration of glomerular filtration. METHODS: Hourly blood samples were analyzed from 37 individuals (17 without CKD, 20 with CKD) during 24 h. Creatinine (enzymatic method) and cystatin C were measured using a Cobas 8000 (Roche Diagnostics). eGFR was estimated using the Modification of Diet in Renal Disease and the Chronic Kidney Disease Epidemiology Collaboration based on creatinine and/or cystatin C. Plasma samples were stored at -80 °C before analysis. Outlier and homogeneity analyses were checked before performing a nested ANOVA to determine biological variation. RESULTS: CVI of creatinine was higher in people without CKD than in those with CKD (6.4% vs 2.5%) owing primarily to the more profound effect of meat consumption on creatinine variability in individuals with lower baseline creatinine concentrations. Unlike creatinine, cystatin C concentrations were unaffected by meat consumption. Cystatin C showed some diurnal rhythmic variation and less in people with CKD. Reference change values (RCVs) of all eGFR equations were within 13% to 20% in both study groups. CONCLUSIONS: Despite differences in CVI of creatinine, the CVI and RCV of the eGFR equations were relatively similar for people with or without CKD.

Within-day biological variation and hour-to-hour reference change values for hematological parameters.

BACKGROUND: Middle- and long-term biological variation data for hematological parameters have been reported in the literature. Within-day 24-h variability profiles for hematological parameters are currently lacking. However, comprehensive hour-to-hour variability data are critical to detect diurnal cyclical rhythms, and to take into account the 'time of sample collection' as a possible determinant of natural fluctuation. In this study, we assessed 24-h variation profiles for 20 hematological parameters. METHODS: Blood samples were collected under standardized conditions from 24 subjects every hour for 24 h. At each measurement, 20 hematological parameters were determined in duplicate. Analytical variation (CVA), within-subject biological variation (CVI), between-subject biological variation (CVG), index of individuality (II), and reference change values (RCVs) were calculated. For the parameters with a diurnal rhythm, hour-to-hour RCVs were determined. RESULTS: All parameters showed higher CVG than CVI. Highest CVG was found for eosinophils (46.6%; 95% CI, 34.9%-70.1%) and the lowest value was mean corpuscular hemoglobin concentration (MCHC) (3.2%; 95% CI, 2.4%-4.8%). CVI varied from 0.4% (95% CI, 0.32%-0.42%) to 20.9% (95% CI, 19.4%-22.6%) for red cell distribution width (RDW) and eosinophils, respectively. Six hematological parameters showed a diurnal rhythm. CONCLUSIONS: We present complete 24-h variability profiles for 20 hematological parameters. Hour-to-hour reference changes values may help to better discriminate between random fluctuations and true changes in parameters with rhythmic diurnal oscillations.

Labtracker+, a medical smartphone app for the interpretation of consecutive laboratory results: an external validation study.

OBJECTIVES: When monitoring patients over time, clinicians may struggle to distinguish 'real changes' in consecutive blood parameters from so-called natural fluctuations. In practice, they have to do so by relying on their clinical experience and intuition. We developed Labtracker+, a medical app that calculates the probability that an increase or decrease over time in a specific blood parameter is real, given the time between measurements. DESIGN: We presented patient cases to 135 participants to examine whether there is a difference between medical students, residents and experienced clinicians when it comes to interpreting changes between consecutive laboratory results. Participants were asked to interpret if changes in consecutive laboratory values were likely to be 'real' or rather due to natural fluctuations. The answers of the study participants were compared with the calculated probabilities by the app Labtracker+ and the concordance rates were assessed. SETTING AND PARTICIPANTS: Medical students (n=92), medical residents from the department of internal medicine (n=19) and internists (n=24) at a Dutch University Medical Centre. PRIMARY AND SECONDARY OUTCOME MEASURES: Concordance rates between the study participants and the calculated probabilities by the app Labtracker+ were compared. Besides, we tested whether physicians with clinical experience scored better concordance rates with the app Labtracker+ than inexperienced clinicians. RESULTS: Medical residents and internists showed significantly better concordance rates with the calculated probabilities by the app Labtracker+ than medical students, regarding their interpretation of differences between consecutive laboratory results (p=0.009 and p<0.001, respectively). CONCLUSION: The app Labtracker+ could serve as a clinical decision tool in the interpretation of consecutive laboratory test results and could contribute to rapid recognition of parameter changes by physicians.

Variación biológica de Creatinina, Cistatina C y Tasa de Filtrado Glomerular Estimada a lo largo de 24 horas / Biological Variation of Creatinine, Cystatin C, and Estimated Glomerular Filtration Rate over 24 hours

Antecedentes: La tasa de filtración glomerular estimada (TFGe) es ampliamente utilizada en la práctica clínica. El presente estudio evaluó la variación biológica intraindividual (CVI) de diferentes ecuaciones de TFGe en sujetos con enfermedad renal crónica (ERC) y sin ERC. Los objetivos de este estudio fueron (a) determinar los perfiles de variación biológica durante 24 horas de creatinina, cistatina C y TFGe y (b) determinar si el CVI de la creatinina, la cistatina C y la TFGe cambia el deterioro de la filtración glomerular. Métodos: Se analizaron muestras de sangre cada hora de 37 individuos (17 sin ERC, 20 con ERC) durante 24 h. La creatinina (método enzimático) y la cistatina C se midieron usando un Cobas 8000 (Roche Diagnostics). La TFGe se estimó utilizando la Modificación de la Dieta en la Enfermedad Renal y la Colaboración de Epidemiología de la Enfermedad Renal Crónica basada en creatinina y/o cistatina C. Las muestras de plasma se almacenaron a -80 °C antes del análisis. Se verificaron los análisis de valores atípicos y de homogeneidad antes de realizar un ANOVA anidado para determinar la variación biológica. Resultados: La CVI de creatinina fue más alta en sujetos sin ERC que en aquellos con ERC (6.4% frente a 2.5%) debido principalmente al efecto más marcado del consumo de carne sobre la variabilidad de creatinina en individuos con concentraciones iniciales de creatinina más bajas. A diferencia de la creatinina, las concentraciones de cistatina C no se vieron afectadas por el consumo de carne. La cistatina C mostró alguna variación rítmica diurna y menor en los sujetos con ERC. Los valores de referencia del cambio (VCR) de todas las ecuaciones de TFGe estuvieron dentro del 13% al 20% en ambos grupos de estudio. Conclusiones: A pesar de las diferencias en el CVI de la creatinina, el CVI y el VRC de las ecuaciones de TFGe fueron relativamente similares para los sujetos con o sin ERC.

Background: Estimated glomerular filtration rate (eGFR) is widely used in clinical practice. This study assessed the within-subject biological variation (CVI) of different eGFR equations in people with chronic kidney disease (CKD) and people without CKD. The aims of this study were (a) to determine the 24-h biological variation profiles of creatinine, cystatin C, and eGFR and (b) to determine whether CVI of creatinine, cystatin C, and eGFR changes on deterioration of glomerular filtration. Methods: Hourly blood samples were analyzed from 37 individuals (17 without CKD, 20 with CKD) during 24 h. Creatinine (enzymatic method) and cystatin C were measured using a Cobas 8000 (Roche Diagnostics). eGFR was estimated using the Modification of Diet in Renal Disease and the Chronic Kidney Disease Epidemiology Collaboration based on creatinine and/or cystatin C. Plasma samples were stored at -80 °C before analysis. Outlier and homogeneity analyses were checked before performing a nested ANOVA to determine biological variation. Results: CVI of creatinine was higher in people without CKD than in those with CKD (6.4% vs. 2.5%) owing primarily to the more profound effect of meat consumption on creatinine variability in individuals with lower baseline creatinine concentrations. Unlike creatinine, cystatin C concentrations were unaffected by meat consumption. Cystatin C showed some diurnal rhythmic variation and less in people with CKD. Reference change values (RCVs) of all eGFR equations were within 13% to 20% in both study groups. Conclusions: Despite differences in CVI of creatinine, the CVI and RCV of the eGFR equations were relatively similar for people with or without CKD.