Significant association between methyl mercury level and latent tuberculosis infection risk: a cross-sectional study.

OBJECTIVES: This cross-sectional study aimed to explore the association between methyl mercury (MeHg) level and latent tuberculosis infection (LTBI) risk based on the data from National Health and Nutrition Examination Survey (NHANES 2011-2012). METHODS: A total of 5243 participants with 20 variables were enrolled. The importance of these variables on TB infection was first ranked by XGBoost and Random Forest methods. Then the association between MeHg level and infection risk was evaluated by restricted cubic spline, threshold effect, and generalized linear regression analyses. We also explored the factors correlated with the difference in MeHg level and finally conducted a mediation analysis to assess the mediating effect of MeHg in LTBI. RESULTS: 521 participants were experiencing the LTBI, and 12 variables showed the differences between infection and non-infection groups (all P < 0.05). Of them, MeHg presented the highest importance on the LTBI. Restricted cubic spline (RCS) next revealed a significant non-linear correlation of MeHg with LTBI (all P < 0.05). Adjusted regression models further indicated their independent association (all P < 0.05), and infection risk increased with the increase of MeHg (P for trend < 0.05). We also found a significant turning point, and their association was significantly observed when MeHg > 5.75 µg/L (P < 0.05). In addition, asthma history was related to the difference in MeHg levels between LTBI and non-LTBI groups. Mediation analysis found that MeHg level partially mediated the association of asthma and LTBI risk (all P < 0.05). CONCLUSIONS: Our study identified MeHg as an independent risk factor for LTBI risk. Their causal relationship needs more investigation to verify.

Artificial Intelligence Machine Learning Algorithms Versus Standard Linear Demographic Analysis in Predicting Implant Size of Anatomic and Reverse Total Shoulder Arthroplasty.

BACKGROUND: Accurate and precise templating is paramount for anatomic total shoulder arthroplasty (TSA) and reverse total shoulder arthroplasty (RSA) to enhance preoperative planning, streamline surgery, and improve implant positioning. We aimed to evaluate the predictive potential of readily available patient demographic data in TSA and RSA implant sizing, independent of implant design. METHODS: A total of 578 consecutive, primary, noncemented shoulder arthroplasty cases were retrospectively reviewed. Demographic variables and implant characteristics were recorded. Multivariate linear regressions were conducted to predict implant sizes using patient demographic variables. RESULTS: Linear models accurately predict TSA implant sizes within 2 millimeters of humerus stem sizes 75.3% of the time, head diameter 82.1%, head height 82.1%, and RSA glenosphere diameter 77.6% of the time. Linear models predict glenoid implant sizes accurately 68.2% and polyethylene thickness 76.6% of the time and within one size 100% and 95.7% of the time, respectively. CONCLUSION: Linear models accurately predict shoulder arthroplasty implant sizes from demographic data. No significant statistical differences were observed between linear models and machine learning algorithms, although the analysis was underpowered. Future sufficiently powered studies are required for more robust assessment of machine learning models in predicting primary shoulder arthroplasty implant sizes based on patient demographics.

Improving prediction of linear regression models by integrating external information from heterogeneous populations: James-Stein estimators.

We consider the setting where (1) an internal study builds a linear regression model for prediction based on individual-level data, (2) some external studies have fitted similar linear regression models that use only subsets of the covariates and provide coefficient estimates for the reduced models without individual-level data, and (3) there is heterogeneity across these study populations. The goal is to integrate the external model summary information into fitting the internal model to improve prediction accuracy. We adapt the James-Stein shrinkage method to propose estimators that are no worse and are oftentimes better in the prediction mean squared error after information integration, regardless of the degree of study population heterogeneity. We conduct comprehensive simulation studies to investigate the numerical performance of the proposed estimators. We also apply the method to enhance a prediction model for patella bone lead level in terms of blood lead level and other covariates by integrating summary information from published literature.

Clinical trials with mechanism evaluation of intervention(s): mind the power and sample size calculation.

BACKGROUND: Mediation analysis, often completed as secondary analysis to estimating the main treatment effect, investigates situations where an exposure may affect an outcome both directly and indirectly through intervening mediator variables. Although there has been much research on power in mediation analyses, most of this has focused on the power to detect indirect effects. Little consideration has been given to the extent to which the strength of the mediation pathways, i.e., the intervention-mediator path and the mediator-outcome path respectively, may affect the power to detect the total effect, which would correspond to the intention-to-treat effect in a randomized trial. METHODS: We conduct a simulation study to evaluate the relation between the mediation pathways and the power of testing the total treatment effect, i.e., the intention-to-treat effect. Consider a sample size that is computed based on the usual formula for testing the total effect in a two-arm trial. We generate data for a continuous mediator and a normal outcome using the conventional mediation models. We estimate the total effect using simple linear regression and evaluate the power of a two-sided test. We explore multiple data generating scenarios by varying the magnitude of the mediation paths whilst keeping the total effect constant. RESULTS: Simulations show the estimated total effect is unbiased across the considered scenarios as expected, but the mean of its standard error increases with the magnitude of the mediator-outcome path and the variability in the residual error of the mediator, respectively. Consequently, this affects the power of testing the total effect, which is always lower than planned when the mediator-outcome path is non-trivial and a naive sample size was employed. Analytical explanation confirms that the intervention-mediator path does not affect the power of testing the total effect but the mediator-outcome path. The usual effect size consideration can be adjusted to account for the magnitude of the mediator-outcome path and its residual error. CONCLUSIONS: The sample size calculation for studies with efficacy and mechanism evaluation should account for the mediator-outcome association or risk the power to detect the total effect/intention-to-treat effect being lower than planned.

Osteoarthritis, osteoarthritis treatment and risk of incident dementia: a prospective cohort study based on UK Biobank.

BACKGROUND: We aimed to investigate the association between OA and treatment with dementia risk and structural brain abnormalities. METHODS: We recruited a total of 466,460 individuals from the UK Biobank to investigate the impact of OA on the incidence of dementia. Among the total population, there were 63,081 participants diagnosed with OA. We subsequently categorised the OA patients into medication and surgery groups based on treatment routes. Cox regression models explored the associations between OA/OA treatment and dementia risk, with the results represented as hazard ratios (HRs) and 95% confidence intervals (95% CI). Linear regression models assessed the associations of OA/OA therapy with alterations in cortical structure. RESULTS: During an average of 11.90 (± 1.01) years of follow-up, 5,627 individuals were diagnosed with all-cause dementia (ACD), including 2,438 AD (Alzheimer's disease), and 1,312 VaD (vascular dementia) cases. Results revealed that OA was associated with the elevated risk of ACD (HR: 1.116; 95% CI: 1.039-1.199) and AD (HR: 1.127; 95% CI: 1.013-1.254). OA therapy lowered the risk of dementia in both medication group (HR: 0.746; 95% CI: 0.652-0.854) and surgery group (HR: 0.841; 95% CI: 0.736-0.960). OA was negatively associated with cortical area, especially precentral, postcentral and temporal regions. CONCLUSIONS: Osteoarthritis increased the likelihood of developing dementia, and had an association with regional brain atrophy. OA treatment lowered the dementia risk. OA is a promising modifiable risk factor for dementia.

The relationship between cardiometabolic index and pulmonary function among U.S. adults: insights from the National Health and Nutrition Examination Survey (2007-2012).

BACKGROUND: Previous findings have revealed that disorders of lipid metabolism may be a risk factor for pulmonary function damage; however, the combined effect of dyslipidemia and central obesity on pulmonary function is unclear. The cardiometabolic index (CMI) is a composite of serum lipids (triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C)) and visceral fat parameters (waist-to-height ratio (WHtR)). This research aimed to investigate the link between CMI and pulmonary function, employing large-scale demographic data sourced from the National Health and Nutrition Examination Survey (NHANES) database. METHODS: This cross-sectional study used data involving 4125 adults aged 20 and above collected by NHANES between 2007 and 2012. We defined CMI as the exposure variable and measured outcomes using forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC to evaluate pulmonary function. Weighted multiple linear regression models and subgroup analyses were employed to investigate separate relationships between CMI and pulmonary function. In addition, to investigate variations across different strata and evaluate the robustness of the findings, interaction tests and sensitivity analyses were conducted. RESULTS: Results from the weighted multiple linear regression analysis indicated a unit increase in log2-CMI was associated with a reduction of 82.63 mL in FEV1 and 112.92 mL in FVC. The negative association remained significant after transforming log2-CMI by quartile (Q). When the log2-CMI level reached Q4, ß coefficients (ß) were -128.49 (95% CI: -205.85, -51.13), -169.01 (95% CI: -266.72, -71.30), respectively. According to the interaction test findings, the negative association linking log2-CMI with FEV1 and FVC persists regardless of confounding factors including age, gender, BMI, physical activity (PA), and smoking status. A subsequent sensitivity analysis provided additional confirmation of the stability and reliability of the results. For females, the inflection points for the nonlinear relationships between log2-CMI and FEV1, as well as log2-CMI and FVC, were identified at 2.33 and 2.11, respectively. While in males, a consistent negative association was observed. CONCLUSIONS: Our findings suggest that higher CMI is associated with lower FEV1 and FVC. CMI may serve as a complementary consideration to the assessment and management of pulmonary function in clinical practice.

The Nonlinear Relationship Between High-Density Lipoprotein and Changes in Pulmonary Structure Function and Pulmonary Function in COPD Patients in China.

Background: The previous findings on the correlation between spirometry and high-density lipoprotein (HDL) cholesterol are intriguing yet conflicting. The aim of this research is to evaluate the relationship between HDL levels and spirometry as well as imaging parameters in patients with chronic obstructive pulmonary disease (COPD) in China. Methods: This study encompasses a total of 907 COPD patients. Participants with complete data from questionnaire interviews, lipid profile examinations, spirometry testing, and computed tomography (CT) scans were included in the analysis. A generalized additive model was employed to identify the non-linear relationship between HDL levels and both spirometry and imaging parameters. In the presence of non-linear correlations, segmented linear regression model was applied to ascertain threshold effects. Results: After adjusting for various factors, we found a non-linear correlation between HDL levels and spirometry/imaging parameters, with an inflection point at 4.2 (66 mg/dL). When Ln (HDL) was below 4.2, each unit increase correlated significantly with reduced post-bronchodilator FEV1 (0.32L, 95% CI: 0.09-0.55), decreased predicted FEV1% (11.0%, 95% CI: 2.7-19.3), and lowered FEV1/FVC (8.0%, 95% CI: 4.0-12.0), along with notable increases in Ln (LAA-950) by 1.20 (95% CI: 0.60-1.79) and Ln (LAA-856) by 0.77 (95% CI: 0.37-1.17). However, no significant associations were observed when Ln (HDL) was greater than or equal to 4.2. Conclusion: A non-linear correlation existed between HDL levels with lung function and CT imaging in COPD patients. Prior to reaching 66 mg/dL, an elevation in HDL was significantly associated with impaired lung function, more severe gas trapping and emphysema.

Novel method for monitoring of carcinogenic impurity of N-nitrosamine in nizatidine pharmaceutical products using ultra high-pressure liquid chromatography triple quadrupole mass spectrometry.

Nitrosamine compounds pose a significant concern as potential carcinogens, prompting heightened scrutiny from regulatory bodies, particularly regarding their presence in pharmaceuticals. The detection of unacceptable levels of N-nitrosodiethylamine (NDMA) in ranitidine has led to widespread recalls, driving interest in alternative medications such as nizatidine, which shares a similar pharmacological class and is used to treat various gastrointestinal conditions. Despite fewer reports on NDMA levels in nizatidine, its structural similarity to ranitidine, characterized by a tertiary amine, underscores the potential for NDMA formation. Addressing the analytical challenges associated with nitrosamine detection, this study focuses on developing and validating an ultra-high pressure liquid chromatography triple quadrupole mass spectrometry (UHPLC-MS/MS) method for quantifying NDMA in both nizatidine active pharmaceutical ingredients and tablet formulations. Method validation adheres to International Council for Harmonisation recommendations, with a demonstrated linear range of 0.25-100 ng/mL for NDMA, exhibiting excellent linearity (regression coefficient >0.999) and efficient recovery rates ranging from 95.98% to 109.57%. The method shows high sensitivity, with limits of detection and quantification of 0.25 and 0.5 ng/mL, respectively. The developed UHPLC-MS/MS method offers a simple, precise, accurate, and selective approach for monitoring NDMA levels in nizatidine formulations available in Australia, promising enhanced sensitivity and specificity with limits of quantification in the ppb and sub-ppb ranges.

Simultaneous determination of total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots by ultra-performance liquid chromatography-tandem mass spectrometry.

Homocysteine, methionine, methylmalonic acid and 2-methylcitric acid are clinically relevant markers in the methionine, propionate, and cobalamin metabolism. This study aimed to develop and validate an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for simultaneously determining total homocysteine, methionine, methylmalonic acid and 2-methylcitric acid in dried blood spots. Three 3.2 mm discs were punched from each calibrator, quality control, and sample dried blood spot into a 96-well U-plate. Each sample was spiked with internal standards and extracted. Then the supernatant was transferred to another 96-well U-plate. After nitrogen drying, the dried residues were reconstituted, centrifuged, and the resulting supernatant was transferred to another 96-well plate for analysis. The method was performed using UPLC-MS/MS within 3 min, validated according to guidance documents, and applied to 72 samples from confirmed patients with methionine, propionate, and cobalamin metabolism disorders. The UPLC-MS/MS method provided satisfactory separation of the four analytes. The R2 values were ≥ 0.9937 for all analytes. The recoveries ranged from 94.17 to 114.29 %, and the coefficients of variation for intraday and interday precision were 0.19 % to 5.23 % and 1.02 % to 6.89 %, respectively. No significant carry-over was detected for the four analytes, and most of confirmed samples exhibited biomarker patterns characteristic of the relevant disorders. A simple and fast UPLC-MS/MS method was successfully developed, validated, and applied to clinical samples for the simultaneous determination of total homocysteine, methionine, methylmalonic acid, and 2-methylcitric acid in dried blood spots.

A linear positive association between high-sensitivity C-reactive protein and the prevalence of cardiovascular disease among individuals with diabetes.

AIMS: To assess the correlation between high-sensitivity C-reactive protein (Hs-CRP) and the prevalence of cardiovascular disease (CVD) among individuals with diabetes. METHODS: A total of 1,555 participants from the National Health and Nutrition Examination Survey were enrolled in this cross-sectional study after excluding individuals without diabetes and those who lacked data on Hs-CRP, diabetes and CVD. All participants were divided into four groups based on quartiles of Hs-CRP: Q1 (≤ 1.20 mg/L), Q2 (1.20-2.86 mg/L), Q3 (2.86-6.40 mg/L), and Q4 (> 6.40 mg/L). Logistic regression analysis, subgroup analysis and restricted cubic spline (RCS) analysis were used to evaluate the correlation between Hs-CRP and the prevalence of CVD in individuals with diabetes. RESULTS: In univariate logistic regression analysis, a higher level of Hs-CRP was associated with a higher prevalence of CVD (P < 0.05). In the multivariate logistic regression analysis adjusting for confounders, the correlation between Hs-CRP and the prevalence of CVD remained significant (Q3 vs. Q1, OR: 1.505, 95% CI: 1.056-2.147, P = 0.024; Q4 vs. Q1, OR: 1.711, 95% CI: 1.171-2.499, P = 0.006; log10(Hs-CRP), OR: 1.504, 95% CI: 1.168-1.935, P = 0.002). Further subgroup analysis showed that a higher Hs-CRP was independently associated with a higher prevalence of CVD in the < 60 years, male, non-hypertension and non-hypercholesterolemia subgroups (P < 0.05). Additionally, RCS analysis revealed a linear positive correlation between Hs-CRP and CVD prevalence (P for nonlinearity = 0.244). CONCLUSION: A higher level of Hs-CRP was closely related to a higher prevalence of CVD in people with diabetes.

Association between plasma trans fatty acids and serum α-klotho levels in adults in the United States of America: an analysis of the NHANES 2009-2010 datasets.

BACKGROUND: This study aimed to explore the potential associations between trans fatty acid (TFA) and α-klotho levels. METHODS: Datasets from the 2009-2010 National Health and Nutrition Examination Survey (NHANES) were analysed for this study. Multivariable linear regression and restricted cubic spline (RCS) analyses were performed to examine the relationships between plasma TFA and serum α-klotho levels. RESULTS: A total of 1,205 participants were included, with a geometric mean (GM) of 803.60 (95% CI: 787.45, 820.00) pg/mL for serum α-klotho levels. RCS analysis revealed L-shaped relationships between TFA and α-klotho levels. The inflection points for palmitelaidic acid (PA), vaccinic acid (VA), elaidic acid (EA), and total TFA levels were 4.55, 20.50, 18.70, and 46.40 µmol/L, respectively. Before reaching the inflection point, serum α-klotho levels were negatively correlated with plasma PA, VA, EA and total TFA levels, with ß values (95% CI) of -0.15 (-0.24, -0.06), -0.16 (-0.23, -0.09), -0.14 (-0.22, -0.05) and - 0.19 (-0.27, -0.11), respectively. Linolelaidic acid (LA) levels exhibited an inverse and linear association with α-klotho levels ( Pnonlinearity=0.167, Poverall<0.001). L-shaped relationships between TFA and α-klotho levels were also observed in the subgroups of participants who were aged < 65 years, were male, did not exercise, were ex-smokers, and were overweight/obese. CONCLUSIONS: L-shaped correlations between plasma PA, VA, EA, and total TFA levels and serum α-klotho levels were observed among adults in the United States.

Moderating effect of social risk on the relationship between biological risk and child development.

Human development is influenced by the interaction between biological and social factors. This study aimed to verify the moderating effect of social risk on the relationship between biological risk and child development. Data were collected on 201 children, aged 6 to 72 months. The independent variable was measured by the biological risk index, and the moderator variable by the social risk index was assessed by the Denver II test. Linear regression, effect size, and analysis of moderation were used to verify the relationship between BRI and the child development (Denver II), and the moderating effect of the SRI. BRI was negatively associated with child development, the interaction between the BRI and SRI increased the explained variance in the Denver II result to 14%. The SRI was also a significant moderator of the Language and Gross Motor domains. This research evidence that social risk moderates the relationship between biological risk and child development, the more social risk factors, the stronger this relationship becomes. On the other hand, it can be said that some social factors favor child development, even in the presence of biological risk factors.

Hyperspectral Characteristics and SPAD Estimation of Wheat Leaves under CO2 Microleakage Stress.

To non-destructively and rapidly monitor the chlorophyll content of winter wheat leaves under CO2 microleakage stress, and to establish the quantitative relationship between chlorophyll content and sensitive bands in the winter wheat growing season from 2023 to 2024, the leakage rate was set to 1 L/min, 3 L/min, 5 L/min, and 0 L/min through field experiments. The dimensional reduction was realized, fractional differential processing of a wheat canopy spectrum was carried out, a multiple linear regression (MLR) and partial least squares regression (PLSR) estimation model was constructed using a SPA selection band, and the model's accuracy was evaluated. The optimal model for hyperspectral estimation of wheat SPAD under CO2 microleakage stress was screened. The results show that the spectral curves of winter wheat leaves under CO2 microleakage stress showed a "red shift" of the green peak and a "blue shift" of the red edge. Compared with 1 L/min and 3 L/min, wheat leaves were more affected by CO2 at 5 L/min. Evaluation of the accuracy of the MLR and PLSR models shows that the MLR model is better, where the MLR estimation model based on 1.1, 1.8, 0.4, and 1.7 differential SPAD is the best for leakage rates of 1 L/min, 3 L/min, 5 L/min, and 0 L/min, with validation set R2 of 0.832, 0.760, 0.928, and 0.773, which are 11.528, 14.2, 17.048, and 37.3% higher than the raw spectra, respectively. This method can be used to estimate the chlorophyll content of winter wheat leaves under CO2 trace-leakage stress and to dynamically monitor CO2 trace-leakage stress in crops.

Association Between Urinary Phthalate Metabolites and Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Objective: To determine the association of urinary phthalate metabolites with chronic obstructive pulmonary disease (COPD), airflow obstruction, lung function and respiratory symptoms. Methods: Our study included a total of 2023 individuals aged ≥ 40 years old in the National Health and Nutrition Examination Survey (NHANES). Multivariate logistic regression was conducted to explore the correlation of eleven urinary phthalate metabolites (MCNP, MCOP, MECPP, MnBP, MCPP, MEP, MEHHP, MEHP, MiBP, MEOHP, and MBzP) with COPD, airflow obstruction and respiratory symptoms. Linear regression analyses were used to evaluate the relationship between urinary phthalate metabolites and lung function. Results: When compared to the first tertile, the third tertile of MEHHP was associated with the risk of COPD [OR: 2.779; 95% confidence interval (CI): 1.129-6.840; P = 0.026]. Stratified analysis showed that MEHHP increased the risk of COPD by 7.080 times in male participants. Both MCPP and MBzP were positively correlated with the risk of airflow obstruction. The third tertile of MBzP increased the risk of cough by 1.545 (95% CI: 1.030-2.317; P = 0.035) times. Both FEV1 and FVC were negatively associated with MEHHP, MECPP, MnBP, MEP, MiBP and MEOHP. Conclusion: Higher levels of MEHHP are associated with increased risk of COPD, and lower measures of FEV1 and FVC. MBzP is positively related to airflow obstruction and cough.

Bayesian inference for multivariate probit model with latent envelope.

The response envelope model proposed by Cook et al. (2010) is an efficient method to estimate the regression coefficient under the context of the multivariate linear regression model. It improves estimation efficiency by identifying material and immaterial parts of responses and removing the immaterial variation. The response envelope model has been investigated only for continuous response variables. In this paper, we propose the multivariate probit model with latent envelope, in short, the probit envelope model, as a response envelope model for multivariate binary response variables. The probit envelope model takes into account relations between Gaussian latent variables of the multivariate probit model by using the idea of the response envelope model. We address the identifiability of the probit envelope model by employing the essential identifiability concept and suggest a Bayesian method for the parameter estimation. We illustrate the probit envelope model via simulation studies and real-data analysis. The simulation studies show that the probit envelope model has the potential to gain efficiency in estimation compared to the multivariate probit model. The real data analysis shows that the probit envelope model is useful for multi-label classification.

Multifactorial assessment of braking time predictors in a driving simulator among older adults according to gender.

CONTEXT: Vehicle driving depends on the integration of motor, visual, and cognitive skills to respond appropriately to different situations that occur in traffic. OBJECTIVES: To analyze a model of performance predictor for braking time in the driving simulator, using a battery of tests divided by gender. METHODS: Selected were 100 male drivers with a mean age of 72.6 ± 5.7 years. Sociodemographic variables, braking time in the driving simulator, and motor, visual, and cognitive skills were evaluated. RESULTS: Comparing genders, men were older than women (p = 0.002) and had longer driving times (p = 0.001). Men had more strength in hand grip (p ≤ 0.001). In the linear regression analysis, the model explained 68 % of the braking time in men and 50.8 % in women. In the stepwise multiple linear regression analysis, the variable that remained in the model was the strength of the right plantar flexors, which explained 13 % of the braking time in women and men, and the cognitive variables explained 38.9 %. CONCLUSION: Sociodemographic, motor, visual, and cognitive variables, explained a substantial portion of the variability in braking time for both older women and men, the specific variables driving this performance differed between the sexes. For older women, factors such as muscle strength emerged as critical determinants of braking ability, highlighting the importance of physical health in maintaining driving skills. On the other hand, cognitive conditions emerged as the primary predictor of braking performance in older men, underscoring the role of mental acuity and decision-making processes in safe driving.

Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET.

Purpose: The aim of this study was to evaluate the association between computed tomography (CT) quantitative pulmonary vessel morphology and lung function, disease severity, and mortality risk in patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: Participants of the prospective nationwide COSYCONET cohort study with paired inspiratory-expiratory CT were included. Fully automatic software, developed in-house, segmented arterial and venous pulmonary vessels and quantified volume and tortuosity on inspiratory and expiratory scans. The association between vessel volume normalised to lung volume and tortuosity versus lung function (forced expiratory volume in 1 sec [FEV1]), air trapping (residual volume to total lung capacity ratio [RV/TLC]), transfer factor for carbon monoxide (TLCO), disease severity in terms of Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D, and mortality were analysed by linear, logistic or Cox proportional hazard regression. Results: Complete data were available from 138 patients (39% female, mean age 65 years). FEV1, RV/TLC and TLCO, all as % predicted, were significantly (p < 0.05 each) associated with expiratory vessel characteristics, predominantly venous volume and arterial tortuosity. Associations with inspiratory vessel characteristics were absent or negligible. The patterns were similar for relationships between GOLD D and mortality with vessel characteristics. Expiratory venous volume was an independent predictor of mortality, in addition to FEV1. Conclusion: By using automated software in patients with COPD, clinically relevant information on pulmonary vasculature can be extracted from expiratory CT scans (although not inspiratory scans); in particular, expiratory pulmonary venous volume predicted mortality. Trial Registration: NCT01245933.

The Effects of Different Blood Sample and Anticoagulant Types on Quantitative Tests of B-Type Natriuretic Peptide.

BACKGROUND: BNP is a sensitive and widely used biomarker for an early diagnosis of heart failure. Currently, most commercial BNP detection products use EDTA plasma samples. The aim of this study was to evaluate the clinical performance of the BNP test by using whole blood samples compared to plasma samples, and to evaluate the effect of the anticoagulant type on the BNP test result. METHODS: In total, 106 patients with different BNP levels from the Dahua Hospital volunteered for this study. Clinically homogenous samples, including EDTA anticoagulant plasma, EDTA whole blood, and heparin anticoagulant plasma, were collected and analyzed by using i-Reader S automatic immuno-analyzer and its supporting reagent kits. Pearson's correlation and weighted least squares linear regression analysis, Bland-Altman plotting, and Kappa test were used for statistical analysis. RESULTS: Correlation analysis showed that BNP concentrations, measured from EDTA anticoagulated plasma samples, had a good linear regression relationship with BNP from whole blood samples, with a slope of 0.9477, r = 0.9978, p < 0.05. A similar correlation was observed between EDTA anticoagulated plasma samples and heparin anticoagulant plasma, with a slope of 0.8413, r = 0.9793, p < 0.05. The BNP concentration measured from the heparin plasma samples were lower than of the EDTA plasma samples. Bland-Altman analysis for assessing BNP concentration agreement showed there was no outlier ratio between EDTA whole blood and EDTA plasma within the range of the detection system, as well as no outlier between EDTA anticoagulated and heparin anticoagulant plasma. Kappa coefficient of BNP concentration between homologous EDTA anticoagulated and heparin anticoagulant plasma was 0.8553 (p < 0.001), and for EDTA anticoagulated plasma and homologous whole blood it was 0.8941 (p < 0.001). CONCLUSIONS: The diagnostic performance of EDTA anticoagulated whole blood samples did not differ significantly from EDTA anticoagulated plasma samples for the BNP test. This study showed no big significant difference between EDTA anticoagulated and heparin anticoagulated plasma measurements within 2 hours. The type of anticoagulant should be carefully chosen when performing the BNP test if BNP samples were in vitro for a long time.

Development and validation of an ultrafast method of quantification of rivaroxaban in human serum using laser diode thermal desorption coupled to triple quadrupole mass spectrometry.

RATIONALE: Rivaroxaban is an anticoagulant prescribed to patients who are at risk of medical conditions such as deep-vein thrombosis, pulmonary embolisms, and strokes caused by blood clots. The administration of this drug is monitored to adjust the dosage and evaluate patients' blood concentration. Rapid quantification of this drug in plasma could make it possible to ensure that the dose present in the blood of patients does not represent a danger for the medical intervention to be carried out. METHODS: Liquid chromatography-tandem mass spectrometry is usually employed to quantify rivaroxaban in blood, plasma, and serum. Here, an alternative method of analysis based on laser diode thermal desorption-triple quadrupole mass spectrometry (LDTD-QqQMS) was developed and comprehensively validated. This new method allows the quantification of rivaroxaban in less than 13 s from sample to sample. The extraction of rivaroxaban in human serum was done by a salting-out liquid-liquid extraction with acetonitrile and a saturated sodium chloride solution. RESULTS: The proposed method allows the quantification of rivaroxaban in less than 13 s from sample to sample. During validation, all criteria were respected. The accuracy was <15% of the nominal value, the precision was <15%CV, and the recovery was ≥89.9%. There were no observed carryover or matrix effects. Analysis of the extracted samples established the stability of dry (24 h) and wet samples (1 week) when samples cannot be analyzed immediately, a considerable advantage in a clinical setting. CONCLUSIONS: This method improves sample throughput by more than 1200% compared to liquid chromatography-tandem mass spectrometry methods of analysis of rivaroxaban and decreases analysis costs by reducing solvent consumption and instrument time.

Association Between Osteoporosis Self-Assessment Tool for Asians and Airflow Limitation in Japanese Post-Menopausal Women.

Purpose: This study aimed to reveal the association between the osteoporosis self-assessment tool for Asians (OSTA) and airflow limitation (AL) in post-menopausal Japanese women. Participants and Methods: This cross-sectional study included 1580 participants undergoing a comprehensive health examination using spirometry and dual-energy X-ray absorptiometry. The OSTA was calculated by subtracting the age in years from the body weight (BW) in kilograms, and the result was multiplied by 0.2. The OSTA risk level was defined as low (>-1), moderate (-4 to -1), or high (<-4). AL was defined as forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) <0.7. The association between the OSTA and AL was assessed using logistic regression analysis. Results: The prevalence of AL was significantly higher in the high OSTA group (15.3%) than in the low OSTA group (3.1%) (p<0.001). In multiple linear regression analysis, the OSTA was independently associated with FEV1/FVC. In logistic regression models adjusted for smoking status, alcohol consumption, current use of medication for diabetes, hyperglycemia, rheumatoid arthritis, second-hand smoke, and ovary removal showed a significantly higher risk of AL (odds ratio: 5.48; 95% confidence interval: 2.90-10.37; p<0.001) in participants with OSTA high risk than in those with OSTA low risk. Conclusion: These results suggest that the OSTA high risk indicates reduced BMD at the femoral neck and presence of AL in Japanese post-menopausal women aged ≥45 years.