We examined the effect of renal dysfunction on B-natriuretic peptide (BNP), N-terminal (NT)-proBNP, and their molar ratio at varying severities of cardiac function in 94 Thai patients with chest pain (52 men; 32 women), also measuring creatinine and left ventricular ejection fraction (LVEF). Renal function was classified into 5 stages by estimated glomerular filtration rate. The molar NT-proBNP/BNP ratio was calculated. Cardiac status was classified by LVEF (normal, >50%; moderate, 35%-50%; severe, <35%). BNP, NT-proBNP, and their ratio corresponded to renal disease stage exponential (0.51, 1.05, and 0.54, respectively; correlation coefficients, >or=0.95). BNP and the ratio are affected less than NT-proBNP by renal dysfunction, starting in stage III; NT-proBNP expresses effects starting in stage II. NT-proBNP is more sensitive than BNP to renal disease stage. For log of geometric means vs stage of renal disease, the BNP slopes and correlation coefficients vary considerably (slopes, 0.036-0.531; r(2), 0.017-0.99). The NT-proBNP slopes and regression coefficients vary considerably (slopes, 0.18-0.71; r(2), 0.33-0.99). For the ratio, the slopes show low variation (0.148-0.337), r(2) greater than 0.96, women differing from men (P = .012). The effect of renal disease differs by gender. BNP and NT-proBNP increase by stage III for women but not for men. One must consider renal function, gender, and LVEF when using BNP or NT-proBNP as cardiac biomarkers. The ratio of the 2 peptides is the most consistent marker across LVEFs.

The negative interference of conjugated, unconjugated, and delta bilirubin on patient serum creatinine determined by the kinetic Jaffe reaction is the unresolved problem. We compared bilirubin interference on thirty patients' serum creatinine obtained from four analyzers, with and without deprotenization before the Jaffe reaction, to the Vitros dry enzymatic method. We found significant negative interference from bilirubin on serum creatinine in all samples directly applied to four wet chemical methods, except the one incorporated with serum blank rate. The negative interferences linearly related to bilirubin concentration. However, bilirubin did not interfere on serum creatinine obtained from all wet chemical methods incorporated with deproteinization process before the reaction. We conclude that deproteinized serum before the reaction is the best approach to eliminate all forms of bilirubin interference on serum creatinine determined by the kinetic Jaffe reaction.

Calculated low-density lipoprotein cholesterol (cLDL-C) may differ from direct measurement (dLDL-C), and this difference may depend on presence of small, dense LDL (sdLDL) particles in addition to variation in triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) concentrations. The presence of such dependence would offer a simple means to estimate sdLDL. We studied dependence of sdLDL on cLDL-C, dLDL-C, and other variables. We measured the levels of glucose, creatinine, total cholesterol, TG, HDL-C, and dLDL-C using standardized methods in 297 samples. For sdLDL cholesterol (sdLDL-C), a novel homogeneous assay was used. The cLDL-C was calculated using the Friedewald formula for 220 subjects after excluding for liver or renal disease. Using stepwise regression analysis identified non-HDL-C, cLDL-C, and dLDL-C as significant variables (P < .001; R(2) = 0.88). The regression equation was as follows: sdLDL-C (mg/dL) = 0.580 (non-HDL-C) + 0.407 (dLDL-C) - 0.719 (cLDL-C) - 12.05. The sdLDL-C concentration can be estimated from non-HDL-C, dLDL-C, and cLDL-C values. Identification of a simple, inexpensive marker for sdLDL particles provides a cost-effective method for screening cardiovascular disease risk.

Endogenous interferences continue to plague creatinine accuracy measurement in both Jaffe and enzymatic methods, and consequentially the estimated glomerular filtration rate. The addition of SDS to the alkaline-pirate reagent was shown to be effective in reducing bilirubin and protein interferences.

BackgroundBody mass index (BMI) and percentage of body fat (PBF) are used to measure obesity; however, their performance in identifying cardiometabolic risk in Southeast Asians is unclear. Generally, Asian women have higher PBF and lower BMI than do men and other ethnic populations. This study was conducted to address whether a discord exists between these measures in predicting obesity-related cardiometabolic risk in a Thai population and to test whether associations between the measures and risk factors for cardiovascular disease have a sex-specific inclination.MethodsA total of 234 (76 men and 158 women) outpatients were recruited. BMI obesity cutoff points were ≥25.0 and ≥27.0 kg/m2 and PBF cutoff points were ≥35.0% and ≥25.0% for women and men, respectively. Blood samples were analyzed for total cholesterol, triglycerides, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, lipoprotein subclasses, apolipoprotein A-I, apolipoprotein B, glucose, hemoglobin A1c, insulin, high-sensitive C-reactive protein (hsCRP), adiponectin, leptin, and 25-hydroxyvitamin D.ResultsTwenty-five percent of participants classified as normal-BMI had excessive fat, whereas 9% classified as normal-PBF had excessive BMI. Good relationships were found between BMI and PBF using sex stratification (R2 >0.5). The prevalence of metabolic syndrome was markedly increased in overweight and/or excess body fat groups compared with lean group. Logistic regression analyses showed that BMI was the best predictor of hypertension. BMI was an independent predictor of insulin resistance, hyperglycemia, hypertriglyceridemia, and hyperleptinemia in women, whereas PBF was for men. However, PBF proved to be a good indicator for atherogenic lipoprotein particles in both sexes. Notably, neither index predicted increased hsCRP or 25-hydroxyvitamin D insufficiency.ConclusionConsiderable sex-specific variations were observed between BMI and PBF in their associations with and predictability of numerous cardiometabolic biomarkers. No single measure provides a comprehensive risk predication as shown herein with the Thai population, and therefore both should be applied in screening activities.

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Although our previous study revealed an association between prolactin level and risperidone dosage, data regarding the plasma concentration of risperidone are lacking. Therefore, this study aimed to investigate the association between plasma drug concentrations of risperidone, 9-hydroxyrisperidone and serum prolactin level in Thai children and adolescents with autism spectrum disorder (ASD). The individuals for this study were 103 children and adolescents with ASD (90 males and 13 females). In the 12th hour after the last risperidone dose, blood samples were collected for analysis. Serum prolactin, plasma risperidone and 9-hydroxyrisperidone levels were measured. Patients' clinical data were collected from medical records -age, weight, height, body mass index, dose of risperidone and duration of treatment. Serum prolactin level was significantly positively correlated with plasma 9-hydroxyrisperidone level (r s = 0.355, p < 0.001). The median concentration of 9-hydroxyrisperidone in individuals with hyperprolactinaemia (7.59 ng/ml; IQR 4.86-15.55) was significantly higher than non-hyperprolactinaemic individuals (5.18 ng/ml; IQR 2.10-8.99) after risperidone treatment (p = 0.006). By multivariate analysis, high prolactin level was correlated to high 9-hydroxyrisperidone level (p = 0.010). The results of this study showed that serum prolactin levels, especially in autistic individuals with hyperprolactinaemia during risperidone treatment, were significantly correlated with the level of 9-hydroxyrisperidone. These results suggest that hyperprolactinaemia may develop during risperidone treatment.Risperidone is the most used pharmacotherapy for irritability in autism spectrum disorder (ASD) and is currently approved by the US Food and Drug Administration (FDA) [1,2]. Moreover, risperidone has been demonstrated to have moderate and clinically significant benefits [3] in treatment of behavioural disturbances, including attention deficit hyperactivity disorder, anxiety disorders and obsessive-compulsive disorder [4].Primarily, risperidone is metabolized in the liver by the CYP2D6 enzyme. The main metabolite of risperidone, 9-hydroxyrisperidone, has similar pharmacological activity as its parent compound, and the serum concentration of the active moiety is thus the sum of the serum concentrations of risperidone and 9-hydroxyrisperidone [5]. Risperidone has high susceptibility to elevate prolactin levels compared with other atypical antipsychotic therapies [6] because these medications are known to have a potent antagonistic activity against serotonin 5HT2, but mild dopamine D2 antagonistic activity [7,8]. Elevation of prolactin concentration corresponds to dopamine D2 receptor blockade [9,10]. Most studies report that children and adolescents treated with risperidone have 38-50% incidence of hyperprolactinaemia [4,[11][12][13][14][15][16].Early studies reported adverse effects associated with prolactin elevation because hyperprolactinaemia is one of the most common endocrinological disorders of the hypothalamic-...

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