Assessment of the DIXTAL DX-2710 Automated Oscillometric Device for Blood Pressure Measurement with the Validation Protocols of the British Hypertension Society (BHS) and the Association for the Advancement of Medical Instrumentation (AAMI)

OBJECTIVE: To assess the Dixtal DX2710 automated oscillometric device used for blood pressure measurement according to the protocols of the BHS and the AAMI. METHODS: Three blood pressure measurements were taken in 94 patients (53 females 15 to 80 years). The measurements were taken randomly by 2 observers trained to measure blood pressure with a mercury column device connected with an automated device. The device was classified according to the protocols of the BHS and AAMI. RESULT: The mean of blood pressure levels obtained by the observers was 148±38/93±25 mmHg and that obtained with the device was 148±37/89±26 mmHg. Considering the differences between the measurements obtained by the observer and those obtained with the automated device according to the criteria of the BHS, the following classification was adopted: "A" for systolic pressure (69% of the differences < 5; 90% < 10; and 97% < 15 mmHg); and "B" for diastolic pressure (63% of the differences < 5; 83% < 10; and 93% < 15 mmHg). The mean and standard deviation of the differences were 0±6.27 mmHg for systolic pressure and 3.82±6.21 mmHg for diastolic pressure. CONCLUSION: The Dixtal DX2710 device was approved according to the international recommendations.

Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.