Somlak Vanavanan

Prevalence and risk factors of chronic kidney disease in the Thai adult population: Thai SEEK study

BACKGROUND Previous reports of chronic kidney disease (CKD) prevalence in Thailand varied from 4.3% to 13.8%. However, there were methodological concerns with these reports in terms of generalization and the accuracy of estimation. This study was, therefore, conducted to determine CKD prevalence and its risk factors in Thai adult populations. METHODS The population-based Thai Screening and Early Evaluation of Kidney Disease (SEEK) study was conducted with cross-sectional stratified-cluster sampling. Serum creatinine was analysed using the modified Jaffe method and then standardized with isotope dilution mass spectrometry. RESULTS The study included 3,459 subjects were included in the study. The mean age was 45.2 years (SE = 0.8), and 54.5% were female. Six hundred and twenty-six subjects were identified as having CKD, which evidenced an overall CKD prevalence of 17.5% [95% confidence interval (95% CI) = 14.6-20.4%]. The CKD prevalence of Stages I, II, III and IV were 3.3% (95% CI = 2.5%, 4.1%), 5.6% (95% CI = 4.2%, 7.0%), 7.5% (95% CI = 6.2%, 8.8%) and 1.1% (95% CI = 0.7%, 1.5%), respectively. The prevalence of CKD was higher in Bangkok, the Northern and Northeastern regions than in the Central and Southern regions. Seven factors (i.e. age, gender, diabetes, hypertension, hyperuricaemia, history of kidney stones and the use of traditional medicines) were associated with CKD. Only 1.9% of the subjects were aware that they had CKD. CONCLUSIONS CKD prevalence in the Thai population is much higher than previously known and published. Early stages of CKD seem to be as common as later stages. However, albuminuria measurement was not confirmed and adjusting for persistent positive rates resulted in the prevalence of 14.4%. Furthermore, the awareness of CKD was quite low in the Thai population.

The effect of renal dysfunction on BNP, NT-proBNP, and their ratio.

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 impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines

BackgroundRecently, the Kidney Disease: Improving Global Outcomes (KDIGO) group recommended that patients with CKD should be assigned to stages and composite relative risk groups according to GFR (G) and proteinuria (A) criteria. Asians have among the highest rates of ESRD in the world, but establishing the prevalence and prognosis CKD is a problem for Asian populations since there is no consensus on the best GFR estimating (eGFR) equation. We studied the effects of the choice of new Asian and Caucasian eGFR equations on CKD prevalence, stage distribution, and risk categorization using the new KDIGO classification.MethodsThe prevalence of CKD and composite relative risk groups defined by eGFR from with Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI); standard (S) or Chinese(C) MDRD; Japanese CKD-EPI (J-EPI), Thai GFR (T-GFR) equations were compared in a Thai cohort (n = 5526)ResultsThere was a 7 fold difference in CKD3-5 prevalence between J-EPI and the other Asian eGFR formulae. CKD3-5 prevalence with S-MDRD and CKD-EPI were 2 - 3 folds higher than T-GFR or C-MDRD. The concordance with CKD-EPI to diagnose CKD3-5 was over 90% for T-GFR or C-MDRD, but they only assigned the same CKD stage in 50% of the time. The choice of equation also caused large variations in each composite risk groups especially those with mildly increased risks. Different equations can lead to a reversal of male: female ratios. The variability of different equations is most apparent in older subjects. Stage G3aA1 increased with age and accounted for a large proportion of the differences in CKD3-5 between CKD-EPI, S-MDRD and C-MDRD.ConclusionsCKD prevalence, sex ratios, and KDIGO composite risk groupings varied widely depending on the equation used. More studies are needed to define the best equation for Asian populations.

Cohort Profile: The electricity generating authority of Thailand study

During the past 30–40 years, there has been a tremendous increase in the prevalence of cardiovascular disease (CVD), especially in developing countries. The change from an agricultural to an industrial society, and the introduction of new technology, make people less likely to engage in physical activity and more likely to adopt a sedentary lifestyle. Modern medicine has markedly reduced the mortality from infectious disease and has improved human longevity, consequently leading to more deaths from chronic diseases, particularly cancer and CVD. Thailand, a mediumsized middle-income country, is one of those nations that is encountering this epidemiological transition and is anticipated to experience much greater increases in CVD compared with Western countries over the next 20 years. Observational studies in Western populations suggest that the well-established risk factors for CVD (obesity, diabetes mellitus, elevated blood pressure, dyslipidemia and cigarette smoking) account for most of the attributable risk for CVD. But the manifestations of CVD and prevalence of its risk factors are often different among Western and Asian populations. For instance, stroke is much more common among many Asian populations compared with the USA or European Union. Most CVD events are potentially preventable through modification of risk factors. To prioritize the preventive measures for maximum benefit, and influence change, a clear understanding of the attribution of risk factors in the local environment is needed. Consequently, following the model of the Framingham study, the first cohort study of chronic disease in Thailand was set up by a group of cardiologists at Ramathibodi Hospital, Bangkok, in 1985. Their basic aim was to examine the effects of cardiovascular risk factors, as identified by Framingham and other studies, on health in the Thai population, specifically to see if the same risk factors worked in the same way as elsewhere. Due to issues with contacting participants in a general population setting within Thailand, it was decided to site this study within an occupational workforce. Initial funding was provided by Mahidol University, the Thai Heart Association and the Electricity Generating Authority of Thailand (EGAT) corporation. Later, the National Research Council, Thailand Research Fund and Praman Chansue Foundation became major funders.

Update on value of the anion gap in clinical diagnosis and laboratory evaluation

Anion gap (AG) is a calculated value commonly used in clinical practice. It approximates the difference between the concentration of unmeasured anions (UA) and unmeasured cations (UC) in serum. At present, the reference range of anion gap has been lowered from 8-16 to 3-11 mmol/l because of the changes in technique for measuring electrolyte. However, clinicians and textbooks still refer and use the old reference value of 8-16 mmol/l. This may lead to misinterpretation of the value of anion gap. Our study updated the value of anion gap in clinical diagnosis and laboratory evaluation. Criteria for using anion gap were also suggested. We analyzed serum electrolyte using the Beckman Synchron CX5. The anion gap was calculated from the formula: [Na(+)-(Cl(-)+HCO(3)(-))]. We estimated the reference range using the non-parametric percentile estimation method. The reference range of anion gap obtained from 124 healthy volunteers was 5-12 mmol/l, which was low and confirmed the reports from other studies (3-11 mmol/l) using ion-selective electrode. From the retrospective study on the 6868 sets of serum electrolyte among hospitalized patients, we found the incidences of normal, increased, and decreased anion gaps were 59.5%, 37.6%, and 2.9%, respectively. The mean and central 90% range of increased anion gap were 16 and 13-20 mmol/l, which was lower than those reported in previous study (25 and 19-28 mmol/l). Anion gap exceeding 24 mmol/l was rare. The mean and central 90% range of decreased anion gap were 3 and 2-4 mmol/l, which were lower than those reported in previous study (6 and 3-8 mmol/l). The value of less than 2 mmol/l was rare. The most common causes of increased anion gap (hypertensive disease, chronic renal failure, malignant neoplasms, diabetes mellitus and heart diseases) and decreased anion gap (liver cirrhosis and nephrotic syndrome) in this study were similar to those in previous studies. We found two cases of IgG multiple myeloma with anion gap of 2 mmol/l. In conclusion, clinicians and laboratorians can use the anion gap as clue in quality control. They can check the incidences of increased and decreased anion gap. If one finds high incidence of increased anion gap (>24 mmol/l) or decreased anion gap (<2 mmol/l), one should check the quality control of electrolyte and whether the patients were hypoalbuminemia or hyperglobulinemia. An anion gap exceeding 24 mmol/l will suggest the presence of metabolic acidosis. It is very rare to find anion gap with the negative sign.

Estimation of Plasma Small Dense LDL Cholesterol From Classic Lipid Measures

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.

Performance of a new interference-resistant glucose meter.

OBJECTIVES Glucose meters are widely used in self and hospital monitoring of blood glucose. We examined the analytical performance of a StatStrip glucose monitoring system. DESIGN AND METHODS Linearity, % recovery and within-run imprecision were studied using glucose-spiked whole blood. A total of 120 heparinized samples were used in method comparison using a plasma hexokinase on the Dimension RxL MAX analyzer as the comparison method. Common interferences were tested on the StatStrip, Accu-Chek Advantage and the MediSense Optium glucose meters at low, middle and high glucose levels. RESULTS The StatStrip assay showed excellent linearity and recovery. The coefficient of variations for imprecision were <5%. This meter correlated well with the comparison method (y=0.994X+0.03; r=0.995, S(y/x)=0.05 mmol/L, bias=-0.01 mmol/L). Of the three meters tested, only the StatStrip showed interference <10% for all spiked levels of acetaminophen, ascorbic acid, maltose and hematocrit at three levels of glucose tested. CONCLUSIONS The StatStrip meter showed good performance and is suitable for point-of-care hospital glucose testing.

Exogenous interferences with Jaffe creatinine assays: addition of sodium dodecyl sulfate to reagent eliminates bilirubin and total protein interference with Jaffe methods

Background: The study evaluated the impact of interferences on the analytical specificity of three commercial and commonly used creatinine methods (two Jaffe and one enzymatic).

Reference ranges of electrolyte and anion gap on the Beckman E4A, Beckman Synchron CX5, Nova CRT, and Nova Stat Profile Ultra

The widespread use of ion-selective electrode causes the reference range of the anion gap (AG) to be lowered from 8-16 to 3-11 mmol/l. The use of the outdated reference range (8-16 mmol/l) leads to the misinterpretation of the value of the anion gap. To interpret the anion gap accurately, one must use an analyzer-specific reference range. This study established the reference ranges of the electrolyte and anion gap in four ion-selective electrode analyzers. We collected clotted and lithium-heparinized blood from 124 healthy volunteers. We determined the electrolyte in the Beckman E4A (serum), Beckman Synchron CX5 (serum), and Nova CRT (serum and plasma). The anion gap was calculated from the formula: [Na(+)-(Cl(-)+HCO3(-))]. Blood sodium, potassium and bicarbonate were determined using the Nova Stat Profile Ultra. We used the plasma chloride from the Nova CRT to calculate the value of the anion gap in the Nova Stat Profile Ultra. We established the reference ranges using the non-parametric percentile estimation method. Accuracy and precision of the electrolyte performances obtained from all analyzers were acceptable. Reference values of serum and plasma sodium, potassium, and chloride were similar in all analyzers. The value of blood sodium obtained from the Nova Stat Profile Ultra was slightly higher than the values for the serum and plasma sodium obtained from the other analyzers. The bicarbonate ranges obtained from the Nova analyzers were higher than the values obtained from the Beckman analyzers. For the anion gap, the reference ranges in this study were low but similar to other studies (3-11 mmol/l) using ion-selective electrode. However, our reference ranges were lower than the previous reference ranges obtained from the continuous-flow analyzer (8-16 or 9-18 mmol/l) incorporated with flame photometry and colorimetry techniques.

Comparative study of calculated and measured total carbon dioxide

Abstract Background: Total carbon dioxide content (TCO2) can be calculated from measured values of pH and pCO2 according to a simplified and standardized form of the Henderson-Hasselbalch equation, or measured directly. Methods: We assessed the agreement between calculated TCO2 and measured TCO2 using a total of 74 blood samples. Calculated TCO2 was obtained using blood gas analysis of pH and pCO2 in arterial whole blood on a Nova Stat Profile Critical Care Xpress analyzer. Measured TCO2 was determined using a Dimension RxL analyzer on arterial plasma, and was used as the comparative method. Deming regression analysis, correlation coefficients, bias (Bland-Altman method) and Students t-test were used for statistical analysis. Results: Deming regression analysis showed a high degree of correlation between calculated and measured TCO2 (r=0.97). The slope (0.96; 95% CI=0.90– 1.02) of the regression line was close to 1 with a positive intercept (2.86 mmol/L; 95% CI=1.44–4.27), and the standard error of the estimate was 0.20 mmol/L. The mean bias was 1.94 mmol/L with a standard deviation of 1.69 mmol/L. The pCO2 values showed a significant effect on calculated TCO2. Most paired differences were within the 95% limits of agreement (−1.45 to 5.33 mmol/L). Conclusions: Calculated TCO2 determined using blood gas analysis agreed with measured TCO2 and may be used to assess acid-base imbalance. However, clinicians should be cautious if using this calculated value in the critically ill patient. Clin Chem Lab Med 2008;46:15–7.