Clinical chemistry最新文献

Background: The reference change value (RCV) is calculated by combining the within-subject biological variation (CVI) and local analytical variation (CVA). These calculations do not account for the variation seen in preanalytical conditions in routine practice or CVI in patients presenting for treatment. As a result, the RCVs may not reflect routine practice or align with clinicians' experiences. We propose a novel RCV approach based on routine patient data that is potentially more clinically relevant.

Methods: This study used the refineR algorithm to determine RCVs using serial patient data extracted from a local Laboratory Information System (LIS). The model was applied to biomarkers with a range of result ratio distributions varying from normal to log-normal. Results were compared against conventional formula-based RCVs using CVI estimates from a state-of-the-art biological variation study. Monte Carlo simulations were also used to validate the LIS data approach.

Results: The RCVs estimated from LIS data were: 11-deoxycortisol (men): -70%/+196%, 17-hydroxyprogesterone (men): -49%/+100%, albumin: -10%/+11%, androstenedione (men): -47%/+96%, cortisol (men): -54%/+51%, cortisone (men): -32%/+51%, creatinine: -16%/+14%, phosphate (women): -23%/+29%, phosphate (men): -27%/+29%, testosterone (men): -38%/+60%. The formula-based RCV estimates showed similar but slightly lower results, and the Monte Carlo simulations confirmed the applicability of the new approach.

Conclusions: RCVs may be estimated from patient results without prior assumptions about the shape of the ratios between serial results. Laboratories can determine RCVs based on local practice and population.

Background: Psoriasis is a chronic inflammatory skin disorder often associated with obesity. Adiponectin, an anti-inflammatory protein-hormone secreted by adipose tissue, may be a link between obesity and psoriasis. We hypothesized that low plasma adiponectin is associated with an increased risk of psoriasis in observational and causal genetic studies.

Methods: In observational analyses, we used information on plasma adiponectin and psoriasis in 30 045 individuals from the Copenhagen General Population Study (CGPS). In one-sample Mendelian randomization analyses, we used genetic information on adiponectin and psoriasis in 107 308 individuals from the CGPS. In two-sample Mendelian randomization analyses, we used genetic information on adiponectin from the ADIPOGen consortium and genetic information on psoriasis in 373 338 and 462 933 individuals from the FinnGen study and UK Biobank (UKB).

Results: In observational analyses, a 1-unit log-transformed higher plasma adiponectin was associated with a hazard ratio (HR) for psoriasis of 0.67 (95% confidence interval: 0.48-0.94) in an age- and sex-adjusted model but not in a multivariable adjusted model including obesity measures with a HR of 0.95 (0.66-1.35). In genetic one-sample Mendelian randomization analysis, a 1-unit log-transformed higher plasma adiponectin was not associated with a causal risk ratio for psoriasis of 1.33 (0.77-2.32) in the CGPS. In two-sample Mendelian randomization analyses, a 1-unit log-transformed higher plasma adiponectin was not associated with causal risk ratios for psoriasis of 0.96 (0.81-1.14) in FinnGen and 1.00 (1.00-1.01) in UKB.

Conclusions: Low plasma adiponectin is associated with increased risk of psoriasis in age- and sex-adjusted observational analyses; however, this was not the case after adjustment for obesity measures or in causal genetic analyses.

Background: The increasing prevalence of xylazine in the illicit drug supply is a growing concern for major health consequences in individuals who use fentanyl mixed with xylazine, but limited data are available regarding the pharmacokinetics of xylazine in humans.

Methods: Xylazine was quantified in serial remnant plasmas collected from 28 patients starting at the initial patient encounter and continuing for up to 52 h from presentation, using LC-MS/MS to calculate the terminal half-life for xylazine. Xylazine metabolites were identified by product ion scanning, and multiple reaction monitoring was used to estimate the relative abundance of xylazine metabolites in 74 collected plasma samples.

Results: The median terminal half-life for xylazine was calculated to be 12.0 h (range: 5.9-20.8). Oxo-xylazine and sulfone-xylazine metabolites were detected in all plasma specimens that contained xylazine.

Conclusions: The half-life of xylazine in humans is longer than previously observed in animal studies, which furthers the current understanding of the expected duration of effects in individuals who use fentanyl mixed with xylazine and the window of detection. Both oxo-xylazine and sulfone-xylazine appear to circulate in plasma for as long as xylazine.