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.
Beck
D E
DE
School of Pharmacy, Auburn University, AL.
Bradley
E L
EL
Farringer
J A
JA
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000617:Aminoglycosides; D000900:Anti-Bacterial Agents / Q000493:pharmacokinetics*; D004341:Drug Evaluation; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012017:Referral and Consultation; D013223:Statistics as Topic
D000617:Aminoglycosides; D000900:Anti-Bacterial Agents