Test-retest reliability of 3D velocity-selective arterial spin labeling for detecting normal variations of cerebral blood flow.

Velocity-selective inversion (VSI) based velocity-selective arterial spin labeling (VSASL) has been developed to measure cerebral blood flow (CBF) with low susceptibility to the prolonged arterial transit time and high sensitivity to brain perfusion signal. The purpose of this magnetic resonance imaging study is to evaluate the test-retest reliability of a VSI-prepared 3D VSASL protocol with whole-brain coverage to detect baseline CBF variations among cognitively normal participants in different brain regions. Coefficients of variation (CoV) of both absolute and relative CBF across scans or sessions, subjects, and gray matter regions were calculated, and corresponding intraclass correlation coefficients (ICC) were computed. The higher between-subject CoV of absolute CBF (13.4 ± 2.0%) over within-subject CoV (within-session: 3.8 ± 1.1%; between-session: 4.9 ± 0.9%) yielded moderate to excellent ICC (within-session: 0.88±0.08; between-session: 0.77±0.14) to detect normal variations of individual CBF. The higher between-region CoV of relative CBF (11.4 ± 3.0%) over within-region CoV (within-session: 2.3 ± 0.9%; between-session: 3.3 ± 1.0%) yielded excellent ICC (within-session: 0.92±0.06; between-session: 0.85±0.12) to detect normal variations of regional CBF. Age, blood pressure, end-tidal CO2, and hematocrit partially explained the variability of CBF across subjects. Together these results show excellent test-retest reliability of VSASL to detect both between-subject and between-region variations supporting its clinical utility.

Biological variation of plasma 25-Hydroxyvitamin D3, Serum vitamin B12, folate and ferritin in Turkish healthy subject.

Biological variation (BV) plays a crucial role in determining analytical performance specifications, assessing serial measurements of individuals, and establishing the use of population-based reference intervals. Our study aimed to calculate the BV and BV-based quality goals of 25-hydroxyvitamin D3 (25-OH D3), ferritin, folate and vitamin B12 tests. We included a total of 22 apparently healthy volunteers (9 women and 13 men) aged 18-55 years in the study that we conducted in Turkey. Blood samples were collected from the participants once a week for five weeks. Serum ferritin, folate and vitamin B12 levels were measured using immunochemical method, while plasma 25-OH D3 levels were determined using the high-performance liquid chromatography method. Analysis of variance (ANOVA) was used to estimate analytical variation(CVA), within-subject BV(CVI) and between-subject BV(CVG). The individuality index (II) and reference change value (RCV) were calculated based on these data. The CVI of 25-OH D3, ferritin, folate, and vitamin B12 were found to be 1.8% (0.6%-2.5%), 16.9% (14.4%-20.2%), 10.7% (9.2%-12.7%), and 8.6% (6.8%-10.5%), respectively. CVG were 44.2% (34.3%-69.9%), 132% (87.7%-238%), 19.4% (14.4%-28.8%), and 39.6% (29.8%-59.0%) for the same biomarkers, while CVA were 3.2% (2.81%-3.71%), 3.5% (3.1%-4.1%), 4.0% (3.5%-4.6%), and 7.5% (6.6%-8.6%), respectively. The II values for 25-OH D3, ferritin, folate, and vitamin B12 were calculated as 0.04, 0.13, 0.55, and 0.22, respectively. The RCV were 10.2%, 47.8%, 31.7%, and 31.6%, respectively. Because the tests analyzed in this study exhibit high individuality, RCV should be preferred rather than population-based reference ranges in clinical interpretation of results.

Physiological confounders of renal blood flow measurement.

OBJECTIVES: Renal blood flow (RBF) is controlled by a number of physiological factors that can contribute to the variability of its measurement. The purpose of this review is to assess the changes in RBF in response to a wide range of physiological confounders and derive practical recommendations on patient preparation and interpretation of RBF measurements with MRI. METHODS: A comprehensive search was conducted to include articles reporting on physiological variations of renal perfusion, blood and/or plasma flow in healthy humans. RESULTS: A total of 24 potential confounders were identified from the literature search and categorized into non-modifiable and modifiable factors. The non-modifiable factors include variables related to the demographics of a population (e.g. age, sex, and race) which cannot be manipulated but should be considered when interpreting RBF values between subjects. The modifiable factors include different activities (e.g. food/fluid intake, exercise training and medication use) that can be standardized in the study design. For each of the modifiable factors, evidence-based recommendations are provided to control for them in an RBF-measurement. CONCLUSION: Future studies aiming to measure RBF are encouraged to follow a rigorous study design, that takes into account these recommendations for controlling the factors that can influence RBF results.

Short-term biological variation of differential count in healthy subjects in a South Asian population.

Estimates of Within-Subject and between subject biological variation for the white blood cell differential count (DC) have not been reported in South Asia. Therefore, we attempted to measure the short-term biological variation estimates for DC. The study was conducted on 28 healthy volunteers (15 males and 13 females). Blood from the volunteers was collected in the morning in K3-EDTA vials and analyzed in triplicate on the Sysmex XN-1000 analyzer, for six consecutive days. The Within subject, between subject and analytical coefficient of variation of the DC was calculated from the results by nested repeated measures ANOVA after outlier exclusion. The Reference change values (RCV) were also calculated. The within-subject variation for eosinophil Count and between subject variation for basophils in our study from South Asia was greater than the published European and American studies. Males and females showed similar biological variation for DC. The within-subject variation of other parameters (Neutrophils, Lymphocytes, Monocytes and Basophils) were similar or showed only mild differences to the published studies. The markedly different within-subject variation for Eosinophil counts suggest that the RCV for DC in South Asians need to be different from the published data in order to have clinical relevance. The Within-subject variation values of the other parameters seem transportable from the published European and American studies, but the small differences found mean that further regional estimates need to be reported for robust evidence of the same.

The individual systematic difference between CoaguChek and STA-SPA.

Using CoaguChek to measure PT-INR and comparing the results with those from the hospital laboratory, some patients get consistent results while others do not. The extent of this problem is unknown. Our study aimed to quantify the between-subject variation of the systematic PT-INR difference between CoaguChek and a hospital laboratory method. We used register data with PT-INR results from both CoaguChek and a hospital laboratory method (STA-SPA+) in samples taken simultaneously from 108 patients. After excluding five patients with outlying results, we used mixed-effects models to estimate individual slopes and intercepts to describe the systematic relationship between the two methods for each patient, and calculated the fraction of patients having a systematic difference greater than 0.3 INR units. The included 103 patients had from 3 to 16, median seven data pairs measured over a time span from 15 to 2319, median 234 days. The mean of individual slopes was 1.113, with a standard deviation of 0.137. Corresponding values for the intercept were -0.151 and 0.208, respectively. Adjusted for the average systematic difference, the proportion of patients with a systematic difference greater than 0.3 INR units increased from 15% at a PT-INR level of 2.5 to 50% at a PT-INR level of 4. The systematic difference between CoaguChek and STA-SPA + varies considerably between patients. This precludes using a single, common formula to make the CoaguChek results directly comparable to the results from the hospital laboratory.

Evaluation of biological variation of glycated hemoglobin and glycated albumin in healthy Chinese subjects.

BACKGROUND: Glycated hemoglobin (HbA1c) and glycated serum albumin (GSA) are used to evaluate the mean blood glucose levels. To ensure safe clinical application of HbA1c and GSA, reliable biological variation (BV) data are required. The aim of this research was to define the BV of HbA1c and GSA employing stringent rules. METHODS: Blood samples were drawn from 19 healthy subjects (10 females, nine males) once per week for 5 weeks. All samples were analyzed using enzymatic method for GSA and HPLC for HbA1c. The data were assessed for outliers, normality and variance homogeneity, and coefficient of variation (by ANOVA) for BV. Sex-stratified BV including within-subject (CVI ) and between-subject (CVG ) was defined for HbA1c and GSA. RESULTS: The following estimates for BV values for CVI and CVG , respectively, were GSA: 1.23% and 4.67%, Alb: 0.75% and 3.18%, and HbA1c: 0.12% and 2.91%. The RCV of GSA was 3.61%, and HbA1c was 1.41%. And the II was 0.26 for GSA, and 0.07 for HbA1c, both of them less than 0.6. According to the 95% CI, the CVI of HbA1c was statistically different between females and males. And both the CVG of HbA1c and GSA were statistically different between females and males. CONCLUSION: All CVI and CVG estimates were lower than those reported in the online BV database. And there is a significant difference between males and females. Analytical performance specifications derived from BV of this research can be applied internationally.

Analytical and between-subject variation of thrombin generation measured by calibrated automated thrombography on plasma samples.

BACKGROUND: The Calibrated Automated Thrombography (CAT) is an in vitro thrombin generation (TG) assay that holds promise as a valuable tool within clinical diagnostics. However, the technique has a considerable analytical variation, and we therefore, investigated the analytical and between-subject variation of CAT systematically. Moreover, we assess the application of an internal standard for normalization to diminish variation. METHODS: 20 healthy volunteers donated one blood sample which was subsequently centrifuged, aliquoted and stored at -80 °C prior to analysis. The analytical variation was determined on eight runs, where plasma from the same seven volunteers was processed in triplicates, and for the between-subject variation, TG analysis was performed on plasma from all 20 volunteers. The trigger reagents used for the TG assays included both PPP reagent containing 5 pM tissue factor (TF) and PPPlow with 1 pM TF. Plasma, drawn from a single donor, was applied to all plates as an internal standard for each TG analysis, which subsequently was used for normalization. RESULTS: The total analytical variation for TG analysis performed with PPPlow reagent is 3-14% and 9-13% for PPP reagent. This variation can be minimally reduced by using an internal standard but mainly for ETP (endogenous thrombin potential). The between-subject variation is higher when using PPPlow than PPP and this variation is considerable higher than the analytical variation. CONCLUSION: TG has a rather high inherent analytical variation but considerable lower than the between-subject variation when using PPPlow as reagent.

Biological variation of 16 biochemical analytes estimated from a large clinicopathologic database of dogs and cats.

BACKGROUND: Biochemical measurements are commonly evaluated using population-based reference intervals; however, there is a growing trend toward reassessing results with within-subject variation (CVI). OBJECTIVES: We aimed to estimate the CVI of 16 biochemical analytes using a large database of dogs and cats, which refers to the results of routine health checkups. METHODS: Pairs of sequential results for 16 analytes were extracted from a database of adult patients. The second result was divided by the first result to produce the ratio of sequential results (rr), and the frequency distribution of rr was plotted. From the plots, the coefficient of variation (CVrr) was calculated. Analytical variation (CVA) was calculated using quality control data, and CVI was estimated as follows: CV I = CV rr / 2 1 / 2 2 - CV A 2 1 / 2 . Estimated CVI was compared with previously reported CVI using the Bland-Altman plot analysis. RESULTS: From the database, 9078 data points from 3610 dogs and 3743 data points from 1473 cats were extracted, with 5468 data pairs for dogs and 2270 for cats. Sampling intervals ranged from 10 to 1970 days (median 366) for dogs and 23 to 1862 days (median 365) for cats. Bland-Altman analysis showed most CVI plots fell within the limits of agreement; however, positive fixed biases were observed in both dogs and cats. CONCLUSIONS: Our study introduces a novel approach of estimating CVI using routine health checkup data in dogs and cats. Despite biases, our method holds promise for clinical application in assessing the significance of measurement result differences.

Corrigendum: Between-Subject and Within-Subject Variation of Muscle Atrophy and Bone Loss in Response to Experimental Bed Rest.

[This corrects the article DOI: 10.3389/fphys.2021.743876.].

Biological variation of thyroid function biomarkers over 24 hours.

BACKGROUND: Thyroid-stimulating hormone (TSH), triiodothyronine (T3), thyroxine (T4), free T3 (FT3), and free T4 (FT4) are used to diagnose thyroid diseases and monitor treatment effects. Reliable biological variation (BV) data is required to ensure accurate clinical decisions. METHODS: Blood samples were collected from 31 healthy subjects at 00:00, 04:00, 08:00, 12:00, 16:00, and 20:00; each sample was analyzed twice for TSH, T3, T4, FT3, and FT4. After outlier exclusion, normality assessment, and variance homogeneity, sex-stratified BV, including within-subject (CVI) and between-subject (CVG), was defined using nested ANOVA. RESULTS: Concentrations of five biomarkers were significantly different between sexes. The CVI and CVG estimates were 34.54% and 34.43% for TSH, 5.89% and 14.18% for T3, 4.48% and 14.96% for T4, 5.37% and 11.23% for FT3, and 3.57% and 8.03% for FT4, respectively. The individual indexes (IIs) of all the biomarkers (except TSH) were ≤ 0.63. Males had lower CVIs and IIs than females. CONCLUSION: CVI estimates of all hormones, except TSH, were lower than those reported on the BV website, showing low IIs and differences between sexes. We provide updated data on the short-term BV of thyroid function biomarkers according to sex and complement BV data of thyroid function biomarkers.

Between-Subject and Within-Subject Variaton of Muscle Atrophy and Bone Loss in Response to Experimental Bed Rest.

To improve quantification of individual responses to bed rest interventions, we analyzed peripheral quantitative computer tomography (pQCT) datasets of the lower leg of 76 participants, who took part in eight different bed rest studies. A newly developed statistical approach differentiated measurement uncertainty U Meas from between-subject-variation (BSV) and within-subject variation (WSV). The results showed that U Meas decreased 59.3-80% over the two decades of bed rest studies (p < 0.01), and that it was higher for muscles than for bones. The reduction of U Meas could be explained by improved measurement procedures as well as a higher standardization. The vast majority (89.6%) of the individual responses pc i exceeded the 95% confidence interval defined by U Meas , indicating significant and substantial BSV, which was greater for bones than for muscles, especially at the epiphyseal measurement sites. Non-significant to small positive inter-site correlations between bone sites, but very large positive inter-site correlation between muscle sites suggests that substantial WSV exists in the tibia bone, but much less so in the calf musculature. Furthermore, endocortical circumference, an indicator of the individual's bone geometry could partly explain WSV and BSV. These results demonstrate the existence of substantial BSV bone, and that it is partly driven by WSV, and likely also by physical activity and dietary habits prior to bed rest. In addition, genetic and epigenetic variation could potentially explain BSV, but not WSV. As to the latter, differences of bone characteristics and the bone resorption process could offer an explanation for its existence. The study has also demonstrated the importance of duplicate baseline measurements. Finally, we provide here a rationale for worst case scenarios with partly effective countermeasures in long-term space missions.

Children's nutrient intake variability is affected by age and body weight status according to results from a Brazilian multicenter study.

A major challenge in nutritional studies focusing on children is estimating "true" intake because the type and amount of foods eaten change throughout growth and development, thereby affecting the variability of intake. The present study investigated the hypothesis that age and body weight status affect the ratio of the within- and between-subject variation of intakes (VR) as well as the number of days of dietary assessment (D) of energy and nutrients. A total of 2,981 Brazilian preschoolers aged 1-6 years were evaluated in a cross-sectional study. Weighed food records and estimated food records were used to assess dietary intake inside and outside of school. Within- and between-subject variations of intakes were estimated by multilevel regression models. VR and D were calculated according to age group and body weight status. VR ranged from 1.17 (calcium) to 8.70 (fat) in the 1- to 2-year-old group, and from 1.47 (calcium) to 8.95 (fat) in the 3- to 6-year-old group. Fat, fiber, riboflavin, folate, calcium, phosphorus, and iron exhibited greater VR and D in the 3- to 6-year-old group. For energy, carbohydrates, and protein, both within- and between-subject variation increased with increasing age. In both body weight groups, calcium showed the lowest VR. Fat showed the highest VR in nonoverweight/obese children (9.47), and fiber showed the highest VR in overweight/obese children (8.74). For most nutrients, D = 7 was sufficient to correctly rank preschoolers into tertiles of intake. In conclusion, age and body weight status affected the within- and between-subject variation and the VR of energy and nutrient intakes among Brazilian preschool children.