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J A Farringer

Publications and source records attributed to J A Farringer.

7 recordsLinked to original sources
PubMed1989

Bayesian forecasting of aminoglycoside dosing requirements in obese patients: influence of subpopulation versus general population pharmacokinetic parameters as the internal estimates.

An aminoglycoside Bayesian forecaster was evaluated in obese patients. This study assessed the influence of replacing the program-supplied general population parameters (GPP) with obese population parameters (OPP) determined from the study population (n = 26). After entering the required patient information and the first peak and trough levels, patient-specific pharmacokinetic parameters were generated by the Bayesian program based on GPP. These parameters were used to predict peak and trough levels for a second dosage regimen. Next, average OPP determined from a study population were substituted for the GPP, and the peak and trough levels were predicted again. Finally, Bayesian predictions of peak and trough levels were made in a validation population (n = 10), first with GPP, then with OPP. The accuracy of the predictions were evaluated through a prediction error analysis in which mean error indicates bias and mean absolute error and root mean-squared error indicate precision. Means were statistically compared through a Student's t test, with the significance level set at p less than 0.05. For the study and validation populations, peak level predictions based on the OPP had less bias and greater precision than those predicted with GPP. Peaks predicted with GPP were statistically different from the observed peaks as well as the peaks predicted using the OPP. There was no statistical difference between the observed peaks and the predicted peaks using the OPP. The trough level predictions using GPP in the study population had less bias than those predicted using OPP; however, the OPP predictions had less bias in the validation population.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗
PubMed1988

Predicting need for pharmacokinetic consultation follow-up using discriminant analysis.

A discriminant function that predicts whether a patient will require more than one intervention by the pharmacokinetic consultation service (PCS) was derived and evaluated prospectively. In phase 1, peak and trough serum aminoglycoside concentrations were evaluated for each of the 150 patients. The patients were then classified into either group 1 or group 2. Group 1 patients required a change in regimen after the initial recommended regimen was begun, while patients in group 2 did not require a change in regimen. Forty-seven variables of group 1 and group 2 were compared by univariate analysis. Stepwise discriminant analysis was then used to develop a model for classifying patients into either group 1 or group 2. In phase 2, the discriminant function derived in phase 1 was applied to a new group of 47 patients. In phase 1, significant variables of the derived discriminant function, in decreasing order of significance, were leukemia, serum creatinine concentration, location in an intensive-care unit (ICU), male sex, actual volume of distribution, therapeutic trough concentration, and number of days in the ICU before consultation. In phase 2, 6 (23%) of the 26 patients who actually required a change were classified into group 2, and 8 (38%) of the 21 patients who were assigned to group 1 for continuous monitoring did not actually require a regimen change. Although the results of the derived discriminant function were significant, the function's clinical utility in predicting the need for a second dosing intervention was poor.

Adult↗
PubMed1988

Clinical assessment of a two-compartment Bayesian forecasting method for lidocaine.

The predictive performance of a two-compartment Bayesian forecasting method for lidocaine (L) was evaluated concurrently with lidocaine therapy in 46 hospitalized patients; 14 of these patients presented with congestive heart failure (CHF). Using an HP-85 microcomputer, demographic and dose-concentration information obtained during continuous lidocaine therapy was used to forecast subsequent lidocaine concentrations. One lidocaine concentration was obtained within each of the three intervals following initiation of lidocaine infusions: I1 (1-6 h), I2 (6-12 h), and I3 (greater than 12 h). Patients were categorized into 4 groups: (a) short-term infusions (less than 24 h) without CHF, (b) short-term infusions with CHF, (c) long-term infusions (greater than 24 h) without CHF, and (d) long-term infusions with CHF. The mean prediction errors (range -0.60-0.27) included zero (95% confidence limits) in all groups and suggested no bias. Forecasts of the I3 lidocaine concentrations were consistently more precise [lower mean absolute errors (MAE) and root mean squared errors] using the lidocaine concentration obtained during the 6-12-h interval (I2) than when the lidocaine concentration obtained at the earlier interval (I1) was used. The MAE was reduced by 20-40% when a single lidocaine concentration obtained during I2 was used as compared to I1. Precision was only slightly improved with the use of two lidocaine concentrations. We conclude that this Bayesian algorithm is unbiased and delivers acceptable precision in forecasting lidocaine concentrations.

Adult↗
PubMed1987

Accuracy of three methods for predicting concentrations of free phenytoin.

Predictions of free (unbound) serum phenytoin concentration by three methods were compared with results obtained by the Abbott TDx Free Phenytoin ultrafiltration and fluorescence-polarization immunoassay technique. Data were obtained for hospitalized adults who had been receiving phenytoin for at least five days and were free of renal or hepatic disease. Total phenytoin concentration was determined, and free phenytoin concentration was measured in ultrafiltrate at 25 degrees C. For each patient, measured concentrations of total phenytoin and albumin were used to predict free phenytoin concentrations by the Gugler method, the Sheiner-Tozer nomogram, and the Sheiner-Tozer equation. Mean measured percentages of free phenytoin were 17.79%, 12.13%, and 8.73%, respectively, for patients with albumin concentrations of less than 2 g/dL (n = 5), 2-3 g/dL (n = 18), and greater than 3 g/dL (n = 26). There was a strong correlation between actual and predicted free phenytoin concentrations for each of the methods, but all methods were found to lack precision. All methods also exhibited bias, as demonstrated by overprediction of the free concentration; however, none of the methods exhibited bias when the difference between the in vitro temperature of 25 degrees C and the in vivo temperature of 37 degrees C was considered. Because of their poor precision, the three methods evaluated in this study are not recommended for predicting free phenytoin concentration.

Adult↗
PubMed1986

Experience with intrainstitutional clinical evaluations of newly marketed preparations as a basis for drug-product selection to hospital formularies.

The decision to admit a new drug-product formulation (NDPF) to a hospital pharmacy formulary is a difficult task, particularly when minimal pharmacokinetic or clinical efficacy data are available. To provide objective information to the Pharmacy and Therapeutics (P&T) Committee, we implemented a procedure to evaluate these NDPFs at our institution. This procedure, termed clinical evaluation, was initiated at our institution in 1981. The clinical evaluations of two NDPFs were performed. The two NDPFs studied were a transdermal nitroglycerin preparation and a sustained-release procainamide preparation. The clinical assessment of the therapeutic and the pharmacokinetic performance of each preparation was made by clinical pharmacists. Following completion of the clinical evaluation, the data were presented at a regular meeting of the P&T committee. The presentation of clinical data derived from our patient population facilitated objective assessment by the P&T committee regarding formulary status. We conclude that the clinical evaluation represents a novel approach to acquire data necessary for objective decisions on NDPFs by the P&T committee.

Administration, Topical↗