Removal of body surface area normalisation improves raw-measured glomerular filtration rate estimation by the Chronic Kidney Disease Epidemiology Collaboration equation and drug dosing in the obese.

BACKGROUND/AIM: We aimed to compared estimated glomerular filtration rate (eGFR) according to the Chronic Kidney Disease Epidemiology Collaboration equation (CKD-EPI), with (mL/min/1.73 m(2) ) and without body surface area (BSA) normalisation (CKD-EPI_noBSA, mL/min) against measured (99m) Technetium - diethylenepentaacetic acid (Tc-DTPA GFR) (mL/min) in 222 individuals, including 80 with malignancy. METHODS: BSA was calculated for each individual using the Du Bois equation. The CKD-EPI and CKD-EPI_noBSA equations were compared with measured Tc-DTPA GFR with respect to bias, proportion within 30% of GFR (P30) and root mean square error for predicting levels of GFR, and concordance in relation to carboplatin dosing. RESULTS: The mean (SD) for BSA and measured GFR for the entire group was 1.99 (0.25) m(2) and 127 (41) mL/min respectively. The P30 for Tc-DTPA GFR was significantly higher with the CKD-EPI_noBSA (80%) than with the CKD-EPI equation (63%, P = 0.0001). In those with body mass index (BMI) > 30 kg/m(2) , the P30 values for the CKD-EPI_noBSA and CKD-EPI were 74% and 42% respectively (P < 0.0001). Carboplatin dosing concordance for the cancer patients using the CKD-EPI and CKD-EPI_noBSA equation was 71% and 56% respectively (P = 0.07). In 78 individuals with BMI > 30 kg/m(2) , concordance in relation to carboplatin dosing using CKD-EPI_noBSA was 65% compared with 26% with the CKD-EPI (P < 0.0001). CONCLUSION: The CKD-EPI without normalisation (CKD-EPI_noBSA) equation was superior to the CKD-EPI equation in estimating raw-measured Tc-DTPA GFR (mL/min).

The performances of the Cockcroft-Gault, modification of diet in renal disease study and chronic kidney disease epidemiology collaboration equations in predicting gentamicin clearance.

BACKGROUND: It is unclear which renal function equation, employing an isotope dilution mass spectrometry (IDMS)-aligned creatinine assay, best predicts gentamicin clearance. METHODS: The performances of the Cockcroft-Gault, Modification of Diet in Renal Disease (MDRD) Study and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations for predicting gentamicin clearances were assessed retrospectively in 240 patients treated with gentamicin during 2011-2012, when the local creatinine assay was IDMS-aligned. Comparisons were based on the percentage within 30% of gentamicin clearance (P 30) and the root-mean-square error (RMSE) of each equation. Gentamicin clearance was calculated from plasma concentrations using a one-compartment model. RESULTS: The Cockcroft-Gault equation and the CKD-EPI equation corrected for individual body surface area (BSA) were associated with the highest P 30 (69% and 67%, respectively) and lowest RMSE (39 and 36 mL/min, respectively) in the 240 patients. Correction for individual BSA improved the performances of the MDRD Study and CKD-EPI equations in patients with body mass indices <18.5 or ≥30 kg/m(2). The equations systematically underestimated gentamicin clearance as gentamicin clearance increased, with performance being inferior with gentamicin clearance ≥90 versus <90 mL/min. CONCLUSIONS: The CKD-EPI equation corrected for individual BSA, and the Cockcroft-Gault equation, provided the best estimates of gentamicin clearance. The CKD-EPI and MDRD Study equations should be corrected for individual BSA at the extremes of body size, if used for guiding gentamicin therapy. The performances of the equations were inferior in patients with higher values of gentamicin clearance.

Dosing of dabigatran etexilate in relation to renal function and drug interactions at a tertiary hospital.

BACKGROUND: Plasma concentrations of the anticoagulant dabigatran are correlated with clinical outcomes, and are affected by renal function, intestinal P-glycoprotein (P-gp) activity and stomach acidity. AIMS: To determine the adherence to dabigatran etexilate renal dosing guidelines, the frequency of co-prescription of potentially interacting drugs in patients on dabigatran, and how these related to dabigatran dosing. METHODS: A retrospective chart review of 204 patients discharged from a tertiary hospital on dabigatran etexilate over a 12-month period. Creatinine clearance, using the Cockcroft-Gault equation, was used as the surrogate of renal function in the 86 patients where this was calculable. RESULTS: Prescribed dabigatran etexilate dose rates in relation to creatinine clearance and the manufacturer's guidelines were classified as 'standard', 'low' and 'high' in 47% (40/86), 49% (42/86) and 5% (4/86) of patients respectively. Co-prescribed drugs that potentially interact with dabigatran etexilate were present in 75% (154/204) of patients and included strong P-gp inhibitors (16%, 32/204), proton-pump inhibitors (46%, 94/204) and anti-platelet drugs (47%, 95/204). Co-prescription of strong P-gp inhibitors was associated with the prescription of 'low' dose rates relative to renal function (P = 0.025). CONCLUSIONS: Few patients were dosed excessively in relation to creatinine clearance. Around 50% was prescribed with 'low' dose rates in relation to creatinine clearance, which because of the association with co-prescription of strong P-gp inhibitors may be clinically appropriate. Most patients were co-prescribed with drugs that potentially interact with dabigatran etexilate.

Comparing dose prediction software used to manage gentamicin dosing.

BACKGROUND: Current Australian guidelines recommend initiating directed therapy of gentamicin if administration exceeds 48 h. Directed doses of gentamicin require the monitoring of plasma concentrations of gentamicin to determine the 24-h area under the time course of plasma gentamicin concentrations (AUC) and a dosage prediction program, for example TCIWorks or Aladdin. However, doses calculated by such programs have not been compared with an established program. AIM: To compare the directed dosage of gentamicin calculated by TCIWorks, Aladdin and an Excel-based program, with an established program, Abbottbase. METHODS: Peak and trough plasma concentrations after the first and second administered doses of gentamicin were available from three patient groups (n = 20-23) with varying creatinine clearances (<40, 40-80, >80 mL/min). The directed dose needed to produce 24-h AUC values of 80 mg.h/L was calculated using each program. RESULTS: There was a strong correlation between the directed doses predicted by each of the three programs compared with Abbottbase, following the first administered dose (r(2) > 0.97, P < 0.0001). The mean ratio (90% confidence intervals) of these directed doses of the gentamicin were: TCIWorks/Abbottbase 106% (105-107%), Aladdin/Abbottbase 102% (101-103%) and Excel/Abbottbase 108% (106-109%). The correlations and dose ratios were also similar when comparisons were made following the second administered dose. For each of the three renal function groups, all programs yielded similar directed doses. CONCLUSIONS: The four programs used in the calculation of directed doses of gentamicin yielded similar results. Any would be suitable for use in clinical practice.

Audit of anticoagulant thromboprophylaxis in hospitalized oncology patients.

BACKGROUND: Venous thromboembolism (VTE) is a significant problem in oncology patients. VTE prophylaxis is underutilized in hospitalized medical patients, but there are few data for the appropriateness and frequency of its use in the oncology subgroup. We aimed to document local practice. METHODS: A cross-sectional chart review of all hospitalized patients cared for by the Christchurch Hospital Oncology Service was carried out during two defined 4-week periods. Assessment for indications and contraindications to prophylactic anticoagulation was based on the 2004 American College of Chest Physicians evidence-based consensus guidelines. RESULTS: Of 113 admissions to the oncology service, 38 (33.6%) had indications for prophylactic anticoagulation. However, 23 of these also had contraindications, leaving only 15 (13%) admissions where prophylactic anticoagulation was deemed appropriate. Only one was appropriately given prophylactic anticoagulation. CONCLUSION: Only a minority of hospitalized oncology patients are appropriate for prophylactic anticoagulation. Where it is suitable, however, it is poorly utilized locally. Local promotion of VTE prophylaxis and further study of this subgroup of hospitalized medical patients may improve uptake of this practice and attenuate morbidity from VTE.