title: External validation of aminoglycoside models used in web calculators and clinical decision support systems after laboratory conversion to serum creatinine isotope dilution mass spectrometry assay.
abstract: BACKGROUND
  Models to predict gentamicin t(½) from serum creatinine (SCr) estimated creatinine clearance (CrCl) are currently being incorporated into smart-device applications and clinical decision support modules without external validation.
  
  
  OBJECTIVE
  The aim of this study was to determine whether such models remain viable after conversion to isotope dilution mass spectrometry (IDMS) SCr assay.
  
  
  METHODS
  This study analyzed data from retrospective reviews of the medical records of nonobese adults receiving the aminoglycoside gentamicin and having ≥2 evaluable serum gentamicin concentrations after laboratory IDMS SCr conversion, from January 2008 to August 2009, at a tertiary care hospital in Florida. A literature search found a number of cited aminoglycoside models. This group of models was classified as group 1. The World Wide Web was also searched for the term aminoglycoside dosing calculators, with 6 models found and referred to as group 2. Predictive performance measures were used to compare the model results with the t(½) calculated from gentamicin concentrations using the Nelder-Mead algorithm.
  
  
  RESULTS
  The records of 39 patients met the inclusion criteria (23 men, 16 women; age range, 18-86 years; range of estimated CrCl, 55-115 mL/min) and provided the "gold standard" aminoglycoside t(½). A gentamicin t(½) was predicted from several published models (group 1) and from other models used in online smart-device applications (group 2) and clinical decision modules. The median (interquartile range) root mean square errors were 0.48 (0.44 to 0.65) and 0.48 (0.45 to 0.70) hours from group-1 and -2 models, respectively. The median mean relative prediction errors were 9% (-14% to +13%) and 11% (+1% to +21%) from groups 1 and 2. The median mean absolute prediction errors were 21% (19% to 28%) and 21% (20% to 30%) from groups 1 and 2. Adjusting SCr by +20% improved the predictive ability in 3 of 12 cited models and in 5 of 6 models used in applications.
  
  
  CONCLUSIONS
  Models to predict gentamicin t(½) should be externally validated at one's institution before use. The findings from the present study provide a framework for conducting external validation.
authors.affiliation: Department of Pharmacy Practice, College of Pharmacy, Nova Southeastern University, 3200 South University Drive, Ft. Lauderdale, FL 33328, USA. wwolowic@nova.edu
authors.forename: William R
authors.initials: WR
authors.lastname: Wolowich
authors.forename: Jennifer G
authors.initials: JG
authors.lastname: Steinberg
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000900:Anti-Bacterial Agents / Q000493:pharmacokinetics*; D001499:Bayes Theorem; D003404:Creatinine / Q000097:blood*; D020000:Decision Support Systems, Clinical; D005260:Female; D005839:Gentamicins / Q000493:pharmacokinetics*; D006207:Half-Life; D006801:Humans; D020407:Internet; D008297:Male; D013058:Mass Spectrometry / Q000379:methods*; D008875:Middle Aged; D055815:Young Adult
chemical_list: D000900:Anti-Bacterial Agents; D005839:Gentamicins; D003404:Creatinine