This Month in AJKD

Article Outline

• Drug Dosing Recommendations Based on Kidney Function Estimating Equations
• Teaching Catheter Insertion Through Simulation Technology
• Influenza Vaccination in Patients With CKD
• CKD and Risk of Hospitalization and Death With Pneumonia

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Drug Dosing Recommendations Based on Kidney Function Estimating Equations 

See Stevens et al, pages 33-42.

The Food and Drug Administration recommends that pharmaceutical companies use the Cockcroft-Gault (CG) equation to estimate kidney function in pharmacokinetic studies and the development of drug dosing guidelines; however, the Modification of Diet in Renal Disease (MDRD) Study equation is more accurate and more often reported by clinical laboratories than the CG equation. In this issue, Stevens et al compared recommended dosing of 15 medications that are cleared by the kidneys using kidney function estimates based on the MDRD Study equation and CG equation using actual and ideal body weight (CG_IBW) with measured GFR. The study population consisted of 5,504 patients from 6 research and 4 clinical populations with diverse clinical characteristics. Concordance with measured GFR was 88% for MDRD Study equation compared with 85% for the CG equation (P < 0.001) and 82% for the CG_IBW equation (P < 0.001), with lower concordance when dosing recommendations for drugs included narrow GFR ranges. These authors suggest that the MDRD Study equation can be used for drug dosage adjustments.

Table 4. Concordance Between Drug Dosing Recommendations Using Measured Versus Estimated Kidney Function

Drug	MDRD Study			CG			CGIBW
	Concordant	Discordant		Concordant	Discordant		Concordant	Discordant
		< mGFR	> mGFR		< mGFR	> mGFR		< mGFR	> mGFR
2 Dosing levels
Enoxaparin	95	2	3	93	1	5	93	4	3
Eptifibatide	93	4	3	90	4	7	87	11	2
Ranitidine	93	4	3	90	4	7	87	11	2
Average	94	3	3	91	3	6	89	9	2
3 Dosing levels
Acylovir	95	2	3	93	1	6	94	3	3
Atenolol	91	4	6	88	2	10	85	12	3
Cefazolin	92	3	5	90	2	8	90	6	4
Digoxin	91	5	4	88	4	8	85	12	3
Levofloxacin	88	5	7	84	4	12	82	12	6
Tenofovir	86	5	9	82	4	14	79	14	8
Tramadol	93	2	4	92	2	7	92	4	4
Average	91	4	5	88	3	9	87	9	4
4 Dosing levels
Allopurinol	79	14	6	77	11	12	69	27	4
Gabapentin	84	9	8	79	7	14	74	19	6
Sotolol	85	8	7	81	7	12	77	18	5
Average	83	10	7	79	8	13	73	21	5
5 Dosing levels
Disopyramide	75	15	10	72	11	17	65	27	8
Lamivudine	85	7	8	80	5	15	77	16	7
Average	80	11	9	76	8	16	71	22	8
Overall average	88	6	6	85	5	10	82	13	4

Note: Units are mL/min; conversion factor from mL/min to mL/s, ×0.0167.

Abbreviations: CG, Cockcroft-Gault equation using actual body weight; CG_IBW, Cockcroft-Gault equation using ideal body weight; MDRD, Modification of Diet in Renal Disease Study equation; mGFR, measured glomerular filtration rate.

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Teaching Catheter Insertion Through Simulation Technology 

See Barsuk et al, pages 70-76; and O'Neill, pages 4-5.

Temporary hemodialysis catheter (THDC) insertion is a required skill for nephrology fellows; however, traditional fellowship training may provide inadequate preparation to perform this procedure. In this issue, Barsuk et al use a central venous catheter (CVC) simulator to assess nephrology fellows' THDC insertion skills and evaluate the impact of an educational intervention on skill development to mastery standards. Of the 18 participating nephrology fellows from 3 academic centers in Chicago from May to August 2008, 6 graduating fellows (traditionally trained) underwent assessment of internal jugular THDC insertion skill using a CVC simulator and 12 first-year fellows (simulator trained) underwent baseline testing and received a 2-hour education session featuring deliberate practice with the CVC simulator. After the skills examination was scored on a 27-item checklist, performance of traditionally trained graduating fellows in THDC insertion was shown to be poor (mean, 53.1%), and only 17% met the minimum passing score of 79% as determined by 10 clinical experts using the Angoff (item-based) and Hofstee (group-based) standard setting methods. Performance of simulator-trained first-year fellows improved from a mean of 29.5% to a mean of 88.6% after simulator training (P = 0.002). Simulator-trained fellows showed significantly higher THDC insertion performance than traditionally trained graduating fellows (P = 0.001). In an editorial, Dr O'Neill hopes that the performance of the graduating nephrologists in this study is not representative, but believes that, at a minimum, fellows should undergo some formal training (with simulation if available) and undergo documented evaluation with a checklist as used here by Barsuk et al.

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Influenza Vaccination in Patients With CKD 

See Scharpé et al, pages 77-85; Bond et al, pages 86-94; Birdwell et al, pages 112-121; and Kallen and Fiore, pages 6-9.

In this issue, 2 clinical trials provide updated information regarding immunogenicity of inactivated influenza vaccine among different groups of patients with CKD. Scharpé et al found a high percentage of hemodialysis patients developed seroprotective levels of antibodies (defined as antibody titers ≥ 1:40 using the hemagglutinin inhibition [HI] test) to the influenza A (H1N1) virus (81.1%), influenza A (H3N2) virus (87.1%), and the influenza B virus (86.4%) components of the vaccine, which is a rate comparable to that seen in healthy controls. In a second article, Bond et al found that the percentage of kidney transplant recipients developing an HI titer greater than 1:32 or having a four-fold rise in HI titer following influenza vaccination was lower than that seen in healthy adults, particularly in those within 6 months of transplantation. An editorial by Drs Kallen and Fiore explains that there is inconsistent data about influenza vaccine immunogenicity among patients on hemodialysis and lower antibody responses among patients who have recently received a kidney transplant. The editorialists also suggest that clinicians caring for these patients must consider the possibility of influenza among both vaccinated and unvaccinated CKD patients with respiratory illness during influenza season.

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CKD and Risk of Hospitalization and Death With Pneumonia 

See James et al, pages 24-32; and Coresh, pages 1-3.

The effects of kidney disease on the risk of hospitalization or death from specific noncardiovascular causes like pneumonia are unclear. In this issue, James et al conduct a retrospective community-based cohort study from a Canadian health region of 252,516 participants with 1 or more outpatient serum creatinine measurements from July 1, 2003 to June 30, 2004 who were not receiving dialysis or kidney transplantation to determine the associations between estimated GFR and hospitalization or death with pneumonia. After adjustment for age, sex, socioeconomic status, and comorbidities, they found that lower estimated GFR was associated with increased risk of hospitalization with pneumonia, although the magnitude of effect varied with age. An editorial by Dr Coresh reviews the importance of “nonkidney” outcomes of CKD other than cardiovascular disease, especially common and preventable outcomes such as pneumonia. He also emphasizes the importance of small increases in relative risk due to decreased estimated GFR in high-risk populations, such as the elderly, and appropriate research methods to determine the estimated GFR threshold below which risk increases.

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