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PubMed1988

[Current and future application of the microcomputer in cardiology].

The present and forthcoming applications of micro data processing in cardiology are reviewed. Heart signals benefit from the digital approach which reduces distortions and permits mass storage. Electrocardiography and, notably, Holter systems, as well as ultrasonic or radiological cardiac and vascular imaging begin to profit from these remarkable advances. Data banks will in due course be constituted which, among other things, will provide a better knowledge of the incidence of some diseases or pathological associations and of their natural history and course under treatment. Such banks will also form the basis of an objective evaluation of therapeutic effectiveness.

Angiocardiography↗
PubMed1985

Volumetrical microcomputer-based ultrafiltration monitor for hemodialysis.

Uniform and controlled ultrafiltration during hemodialysis can decrease dialysis side effects. One of the prerequisites for this treatment is accurate measurement of ultrafiltration. The best method currently available for ultrafiltration measurement is based on the volumetrically measured change of dialysate flow over the dialyzer. We have developed an ultrafiltration monitor (UFM) for hemodialysis using two micro-oval flowmeters that measure the flow rate of the dialysate entering and leaving the dialyzer. Correction for intrinsic error was achieved with an Acorn microprocessor, in a calibration run without ultrafiltration and constant, equal flow through both flow transducers. The accuracy of the UFM in vitro was 99.4% of the mean total ultrafiltration, with a correlation coefficient of 0.998 (n = 8) with actual ultrafiltration. In vivo, in which UFM was compared with bed scale body weight monitoring, a correlation coefficient of 0.97 (n = 82) was obtained, and an accuracy of 90% of total ultrafiltration as measured by the change in body weight. Therefore, this UFM provides a cheap and reliable method for ultrafiltration measurement.

Humans↗
PubMed1988

Comparison of a Bayesian program with three microcomputer programs for predicting gentamicin concentrations.

A recently developed Bayesian regression program was compared with three other aminoglycoside pharmacokinetic dosing programs available for clinical use. From 30 adult patients, 152 measured serum gentamicin concentrations (SGC) were evaluated retrospectively (78 peak and 74 trough). Predictive performance was compared for each method by using the first peak and trough SGC pair to predict subsequent serum concentrations, making a total of 92 predictions (48 peak and 44 trough). The two Bayesian programs (Brater and Koup) were further evaluated using only one initial peak or trough SGC to make the same predictions. Mean predicted error (ME), mean absolute error (MAE), and root mean squared error (RMSE) were calculated for each method. Prediction bias and precision were compared statistically, between each method, by calculating the 95% confidence intervals for the delta ME and delta MAE, respectively. No statistically significant differences were found in the MAEs among any of the methods for predicting peak SGCs, with the exception of the Brater program, using a single trough SGC, which was statistically less precise (less than 0.05). There were few statistically significant differences in the MAEs for trough SGCs; however, Koup's Bayesian program using a single trough concentration yielded statistically more precise predictions than the other methods. The ME was found to differ significantly (p less than 0.05) among estimates for peak and trough SGCs provided by some of the predictive methods.(ABSTRACT TRUNCATED AT 250 WORDS)

Adolescent↗