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Variability of Thyroid Measurements from Ultrasound and Laboratory in a Repeated Measurements Study
(2020)
Background: Variability of measurements in medical research can be due to different sources. Quantification of measurement errors facilitates probabilistic sensitivity analyses in future research to minimize potential bias in epidemiological studies. We aimed to investigate the variation of thyroid-related outcomes derived from ultrasound (US) and laboratory analyses in a repeated measurements study. Subjects and Methods: Twenty-five volunteers (13 females, 12 males) aged 22–70 years were examined once a month over 1 year. US measurements included thyroid volume, goiter, and thyroid nodules. Laboratory measurements included urinary iodine concentrations and serum levels of thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), free thyroxine (fT4), and thyroglobulin. Variations in continuous thyroid markers were assessed as coefficient of variation (CV) defined as mean of the individual CVs with bootstrapped confidence intervals and as intraclass correlation coefficients (ICCs). Variations in dichotomous thyroid markers were assessed by Cohen’s kappa. Results: CV was highest for urinary iodine concentrations (56.9%), followed by TSH (27.2%), thyroglobulin (18.2%), thyroid volume (10.5%), fT3 (8.1%), and fT4 (6.3%). The ICC was lowest for urinary iodine concentrations (0.42), followed by fT3 (0.55), TSH (0.64), fT4 (0.72), thyroid volume (0.87), and thyroglobulin (0.90). Cohen’s kappa values for the presence of goiter or thyroid nodules were 0.64 and 0.70, respectively. Conclusion: Our study provides measures of variation for thyroid outcomes, which can be used for probabilistic sensitivity analyses of epidemiological data. The low intraindividual variation of serum thyroglobulin in comparison to urinary iodine concentrations emphasizes the potential of thyroglobulin as marker for the iodine status of populations.
Objectives: An inverse relationship between education and cardiovascular risk has been described, however, the combined association of education, income, and neighborhood socioeconomic status with macrovascular disease is less clear. The aim of this study was to evaluate the association of educational level, equivalent household income and area deprivation with macrovascular disease in Germany.
Methods: Cross-sectional data from two representative German population-based studies, SHIP-TREND (n = 3,731) and KORA-F4 (n = 2,870), were analyzed. Multivariable logistic regression models were applied to estimate odds ratios and 95% confidence intervals for the association between socioeconomic determinants and macrovascular disease (defined as self-reported myocardial infarction or stroke).
Results: The study showed a higher odds of prevalent macrovascular disease in men with low and middle educational level compared to men with high education. Area deprivation and equivalent income were not related to myocardial infarction or stroke in any of the models.
Conclusion: Educational level, but not income or area deprivation, is significantly related to the macrovascular disease in men. Effective prevention of macrovascular disease should therefore start with investing in individual education.
Introduction
Neurofilament light (NfL) can be detected in blood of healthy individuals and at elevated levels in those with different neurological diseases. We investigated if the choice of biological matrix can affect results when using NfL as biomarker in epidemiological studies.
Method
We obtained paired serum and EDTA-plasma samples of 299 individuals aged 37–67 years (BiDirect study) and serum samples of 373 individuals aged 65–83 years (MEMO study). In BiDirect, Passing–Bablok analyses were performed to assess proportional and systematic differences between biological matrices. Associations between serum or EDTA-plasma NfL and renal function (serum creatinine, serum cystatin C, glomerular filtration rate, and kidney disease) were investigated using linear or logistic regression, respectively. All regression coefficients were estimated (1) per one ng/L increase and (2) per one standard deviation increase (standardization using z-scores). In MEMO, regression coefficients were estimated (1) per one ng/L increase of serum or calculated EDTA-plasma NfL and (2) per one standard deviation increase providing a comparison to the results from BiDirect.
Results
We found proportional and systematic differences between paired NfL measurements in BiDirect, i.e., serum NfL [ng/L] = −0.33 [ng/L] + 1.11 × EDTA-plasma NfL [ng/L]. Linear regression coefficients for the associations between NfL and renal function did not vary between the different NfL measurements. In MEMO, one standard deviation increase in serum NfL was associated with greater changes in the outcomes than in BiDirect.
Conclusion
Although there are differences between serum and EDTA-plasma NfL, results can be used interchangeably if standardized values are used.
Objective
Acute pancreatitis (AP) is an inflammatory disorder, the severe form of which is burdened with multi-organ dysfunction and high mortality. The pathogenesis of life –threatening organ complications, such as respiratory and renal failure, is unknown.
Design
Organ dysfunction was investigated in a mouse model of AP. The influence of monocytes and neutrophils on multi organ dysfunction syndrome (MODS) was investigated in vivo by antibody depletion. Using real-time-fluorescence and deformability-cytometry (RT-DC) analysis we determined the mechanical properties of neutrophils and monocytes during AP. Furthermore, blood samples of pancreatitis patients were used to characterize severity-dependent chemokine profiles according to the revised Atlanta classification.
Results
Similar to AP in humans, severe disease in the mouse model associates with organ dysfunction mainly of lung and kidney, which is triggered by a mobilisation of Ly6g-/CD11b+/Ly6c hi monocytes, but not of Ly6g+/CD11b+ neutrophils. Monocyte depletion by anti-CCR2 antibody treatment ameliorated lung function (oxygen consumption) without interfering with the systemic immune response. RT-DC analysis of circulation monocytes showed a significant increase in cell size during SAP, but without a compensatory increase in elasticity. Patient chemokine profiles show a correlation of AP severity with monocyte attracting chemokines like MCP-1 or MIG and with leukocyte mobilisation.
Conclusion
In AP, the physical properties of mobilized monocytes, especially their large size, result in an obstruction of the fine capillary systems of the lung and of the kidney glomeruli. A selective depletion of monocytes may represent a treatment strategy for pancreatitis as well as for other inflammation-related disorders.
Disregarded Measurement Uncertainty Contributions and Their Magnitude in Measuring Plasma Glucose
(2020)
Background:
Each measurement is subject to measurement uncertainty (MU). Consequently, each measurement of plasma glucose concentration used for diagnosis and monitoring of diabetes mellitus (DM) is affected. Although concepts and methods of MU are well established in many fields of science and technology, they are presently only incompletely implemented by medical laboratories, neglecting MU of target values of internal quality control (IQC) materials.
Methods:
An empirical and practical approach for the estimation of MU based on the analysis of routine IQC using control samples with assigned target values is presented. Its feasibility is demonstrated exemplarily by analyzing IQC data from one year obtained for glucose employing the hexokinase method with IQC of two different concentrations.
Results:
Combined relative extended (k = 2) MU comprising bias, coefficient of variation (CV), and MU of the target values assigned to control materials were about 9% with a lower (~ 56 mg/dL; ~3.1 mmol/L) and 8% with a higher (~ 346 mg/dL; ~19.2 mmol/L) concentration sample, analyzing IQC of one year from three different devices.
Conclusions:
Estimation of MU in this study is quite reliable due to the large number of IQC data from one year. The MU of the target values of the commercial control material in this study was considerably larger than other MU contributions, ie, standard deviation and bias. In the future, the contribution of MU of commercial IQC should be addressed more carefully and technologies to measure glucose should be geared toward smaller MU possible, as needed, especially for glucose concentration measurements in diagnosis and management of DM.
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
The aim of the present study was to construct a biological age score reflecting one’s physiologic capability and aging condition with respect to tooth loss over 10 y. From the follow-up to the population-based Study of Health in Pomerania (i.e., SHIP-2), 2,049 participants were studied for their baseline biomarker measures 10 y before (i.e., in SHIP-0). Metabolic and periodontal data were regressed onto chronological age to construct a score designated as “biological age.” For either sex separately, the impact of this individualized score was used to predict tooth loss in the follow-up cohort in comparison with each participant’s chronological age. Outcome data after 10 y with respect to tooth loss, periodontitis, obesity, and inflammation were shown to be better for biologically younger subjects than as expected by their chronological age, whereas for the older subjects, data were worse. Especially for tooth loss, a striking increase was observed in subjects whose biological age at baseline appeared to be higher than their chronological age. Biological age produced significantly better tooth loss predictions than chronological age (P < 0.001). Areas under receiver operating characteristic curves for tooth loss of ≥3 teeth in men during follow-up were 0.811 and 0.745 for biological and chronological age, respectively. For women, these figures were 0.788 and 0.724. For total tooth loss, areas under the curve were 0.890 and 0.749 in men and 0.872 and 0.752 in women. Biological age combines various measures into a single score and allows identifying individuals at increased risk of tooth loss.
Periodontitis is one of the most prevalent oral diseases worldwide and is caused by multifactorial interactions between host and oral bacteria. Altered cellular metabolism of host and microbes releases a number of intermediary end products known as metabolites. There is an increasing interest in identifying metabolites from oral fluids such as saliva to widen the understanding of the complex pathogenesis of periodontitis. It is believed that some metabolites might serve as indicators toward early detection and screening of periodontitis and perhaps even for monitoring its prognosis in the future. Because contemporary periodontal screening methods are deficient, there is an urgent need for novel approaches in periodontal screening procedures. To this end, we associated oral parameters (clinical attachment level, periodontal probing depth, supragingival plaque, supragingival calculus, number of missing teeth, and removable denture) with a large set of salivary metabolites (n = 284) obtained by mass spectrometry among a subsample (n = 909) of nondiabetic participants from the Study of Health in Pomerania (SHIP-Trend-0). Linear regression analyses were performed in age-stratified groups and adjusted for potential confounders. A multifaceted image of associated metabolites (n = 107) was revealed with considerable differences according to age groups. In the young (20 to 39 y) and middle-aged (40 to 59 y) groups, metabolites were predominantly associated with periodontal variables, whereas among the older subjects (≥60 y), tooth loss was strongly associated with metabolite levels. Metabolites associated with periodontal variables were clearly linked to tissue destruction, host defense mechanisms, and bacterial metabolism. Across all age groups, the bacterial metabolite phenylacetate was significantly associated with periodontal variables. Our results revealed alterations of the salivary metabolome in association with age and oral health status. Among our comprehensive panel of metabolites, periodontitis was significantly associated with the bacterial metabolite phenylacetate, a promising substance for further biomarker research.
For the goal of individualized medicine, it is critical to have clinical phenotypes at hand which represent the individual pathophysiology. However, for most of the utilized phenotypes, two individuals with the same phenotype assignment may differ strongly in their underlying biological traits. In this paper, we propose a definition for individualization and a corresponding statistical operationalization, delivering thereby a statistical framework in which the usefulness of a variable in the meaningful differentiation of individuals with the same phenotype can be assessed. Based on this framework, we develop a statistical workflow to derive individualized phenotypes, demonstrating that under specific statistical constraints the prediction error of prediction scores contains information about hidden biological traits not represented in the modeled phenotype of interest, allowing thereby internal differentiation of individuals with the same assigned phenotypic manifestation. We applied our procedure to data of the population-based Study of Health in Pomerania to construct a refined definition of obesity, demonstrating the utility of the definition in prospective survival analyses. Summarizing, we propose a framework for the individualization of phenotypes aiding personalized medicine by shifting the focus in the assessment of prediction models from the model fit to the informational content of the prediction error.