An equation to explain variations in blood NT-proBNP in ambulatory cardiac subjects.

BACKGROUND: NT-proBNP is being used as a biomarker for prognosticating and delineating cardiac dysfunction. The cut-off value for deciding normal versus abnormal levels has always been a point of contention since it depends on the degree of dysfunction as well as other associated conditions often termed non-cardiac factors and parameters. Such association had not been formally presented. OBJECTIVE: To determine the direction and magnitude of effect of cardiac and non-cardiac parameters on NT-proBNP variability. MATERIAL AND METHOD: The present study included 78 cardiac ambulatory patients with a history of heart failure and/or low left ventricular ejection fraction. Their cardiac and non-cardiac parameters were recorded at the time of blood sampling for NT-proBNP. Multivariate linear regression analysis was used to correlate cardiac and non-cardiac parameters with NT-proBNP level and, from this, a predictive equation was derived. RESULTS: Log [NT-proBNP (pmol/l)] was 1.424 + 0.348 (for EF of 18-27) + 0.636 (for EF < 18) + 0.021 CTR - 0.002 SMW- 0.326 for female + 0.430 Cr - 0.010 BW [EF = LV ejectionfraction in %; CTR = cardio-thoracic ratio in %; SMW = 6-minute walking distance in meters; Cr = serum creatinine in mg/dl; BW = body weight in kg]. The adjusted R-square for this regression was 0.659. Omitting the non-cardiac variables (sex, Cr, BW) would decrease the adjusted R-square to 0.493. CONCLUSION: Cut-off value for NT-proBNP concentration in subjects without severe systolic heart failure has to account for these non-cardiac factors.

Costs of payment in Thai acute coronary syndrome patients.

BACKGROUND: Acute coronary syndrome (ACS) is a major health care syndrome that can financially burden patients throughout the world, including Thailand. Few studies purposed estimating the costs of treatment. The data from the ACS registry database represented the costs of hospital charges paid by ACS patients. Although these were not the actual treatment costs, the authors can approximately estimate the total expenditure for the first admission. OBJECTIVES: First, calculate the cost of ACS to the patients, including diagnostic, demographic data, treatment modalities, type of payers, hospital profile, and outcomes. Second, find the appropriate model to identify the independent factors for predicting the treatment costs. MATERIAL AND METHOD: The present study collected data from the second and third phase of a national multicenter prospective registry of ACS in Thailand, Thai ACS registry (TACSR). 3,552 patients with new onset of ACS were analyzed. RESULTS: Median age was 67 years (range 26.5-105.5) with predominately male and median length of stay (LOS) was 7 days (range, 1-184). 42% referred from other hospitals. The median cost of the total population was 47,908 baht (range, 633-1,279,679). When classified into those of STEMI, NSTEMI, and UA, the costs were 82,848.5, 40,531 and 26,116 baht respectively, p < 0.0001. Patients in the government hospital had to pay the total cost with PCI and CABG, 152,081-161,374 baht and 203,139-223,747 baht respectively, while the private hospital charged almost twice as much. For the types of payers, private insurance including private employee security fund paid significantly more than others. Costs in patients paid by "30 baht na tional health scheme and social security fund" were significantly less than those of others. For modality of treatment in STEMI, primary PCI was significantly more costly than thrombolytics and no reperfusion therapy, 161,096.5 vs. 60,043.0 and 33,335.0 baht respectively p < 0.0001. Early invasive groups in NSTEMI/UA had much higher median costs 145,794.0 baht when compared to those of the conservative group, 47,908 baht, p < 0.0001. Two multiple linear regression models according to the diagnostic group identified the independent factors for predicting cost. PCI, LOS, CABG, admission in a private hospital, Death, GPIIb/IlIa inhibitors use, major bleeding, coronary angiogram, thrombolytics use, age and diabetes were independent predictors for the cost in STEMI patients, R2 = 0.58. For those of NSTEMI/UA, the independent predictors for the cost were PCI, LOS, CABG, admission in a private hospital, death, GP IIb/IIIa inhibitors use, major bleeding, coronary angiogram, age, ventricular arrhythmia, CHF and referred patients, R2 =0.62. CONCLUSION: Costs in ACS patients were markedly different among diagnostic groups. The clinical risk factors were hospital type, type of payers, referred system, treatment procedures, drugs used and complications including outcome. Some of these factors could independently predict the costs.

Prevalence of cardiovascular risk factors in a rural area in Southern Thailand: potential ethnic differences.

In Thepa district, Songkhla province, Southern Thailand, parents of children being followed long term from conception for their development (N 1325), as well as health workers of the same district (N 150) were surveyed with regards to anthropometry, occupation, family size, food and leisure habits, and blood levels of lipids, sugar, creatinine and hematocrit. Differences among those of Thai or Chinese extracts (Thai-Buddhists) and those of Malay extracts (Thai-Muslims) were separately evaluated for males and females. The mean age for the group (N 1475, including 636 couples) was 31.5 +/- 7.3 (SD) and ranged from 15-66 years. There were 794 females (485 Muslims) ages 29.6 +/- 6.6 (SD). The Muslim families were larger in size averaging 2.8 +/- 1.6 children while the Buddhist's averaged 1.9 +/- 0.9. Fifty four percent of the group were engaged in rubber tapping and this often included both members of the family. Sixty eight percent of the males currently smoked Differences in measured variables between Muslims and Buddhists were minimal. The most striking however was the high density lipoprotein cholesterol (HDL-C) among the males where the age-adjusted average was 51.3 +/- 0.72 (SE) among the Buddhists and 42.2 +/- 0.59 (SE) in the Muslims. This difference was significant even when adjusted for other related variables. Differences in the ethnic groups were also examined in terms of prevalence of risks (hypertension, BMI > or = 25%, waist-hip-ratio, fasting plasma glucose > or = 110 mg%, total cholesterol > or = 200 mg%, triglyceride > or = 150 mg% and low HDL-C). For hypertension (systolic > or = 140 or diastolic > or = 90 mmHg), female Muslims showed higher prevalence (4.5% vs 1.6%; OR 2.82 CI 1.04-7.64). For low HDL-C, male Muslim showed higher prevalence 23.6 vs 8.8%, OR 2.31 CI 1.27-4.22). Other risks showed no differences among the ethnic groups. The differences in parameters or in prevalence of risk between these two ethnic groups (minimal intermarriage) are distinct from differences among Malays and Chinese in Singapore where such differences were subsequently reflected in the differences in incidence and out-come of ischemic heart diseases.