SCr and SCysC Concentrations Before and After Traumatic Amputation in Male Soldiers: A Case-Control Study

Correspondence 4. Lalli PN, Strainic MG, Lin F, Medof ME, Heeger PS. Decay accelerating factor can control T cell differentiation into IFNgamma-producing effector cells via regulating local C5a-induced IL-12 production. J Immunol. 2007;179(9):5793-5802. 5. Peng Q, Li K, Wang N, et al. Dendritic cell function in allostimulation is modulated by C5aR signaling. J Immunol. 2009;183(10):6058-6068. Ó 2013 by the National Kidney Foundation, Inc. http://dx.doi.org/10.1053/j.ajkd.2013.07.029

In Reply to ‘Beneficial Effect of Eculizumab on Thrombotic Microangiopathies: Another Point of View’ In our opinion, the evidence for the hypothesis of Park et al1 in response to our study2 is not clear cut. Kakishita3 reported that an increase in plasma interleukin-12 (IL-12) level might be able to predict thrombotic microangiopathy (TMA), but the report focuses on TMAs that occurred after bone marrow transplantation. We do not know yet whether we can derive the same conclusions for the majority of TMAs, which occur in variable circumstances. Strasly et al4 report in vitro experiments in which the presence of IL-12 in the culture medium decreased heart microvascular endothelial cell proliferation in a dose-dependent manner. However, adding tumor necrosis factor a or vascular endothelial growth factor-A165 either up- or downregulated the proliferation; thus, IL-12 can do both harm and good—it seems to depend on the (in vitro) environment.2 Further complicating the matter is the evidence that C5a also can both up- or downregulate IL-12. Hawlisch et al,5 Reis et al,6 and La Sala et al7 showed in different examples that C5a negatively regulates IL-12(p40) production. However, multiple experimental settings have demonstrated evidence that C5a upregulates IL-12.8,9 How can we explain these apparently conflicting effects of C5a on IL-12? First, C5a may affect IL-12 levels in a dose-dependent manner. Second, IL-12(p70) production is dependent on the ligation of appropriate Toll-like receptors, at least in murine dendritic cells.9 Third, different results could be attributed to significant differences in experimental design.10 Understanding the molecular basis of the different responses to C5a under each condition requires additional studies and probably will shed a different light. What formerly was labeled black or white now has become a shade of grey. Jan Schmidtko, MD Centre Hospitalier Universitaire Vaudois Lausanne, Switzerland Sven Peine, MD Universitätsklinikum Hamburg-Eppendorf Hamburg, Germany

Acknowledgements Financial Disclosure: The authors declare that they have no relevant financial interests.

References 1. Park SJ, Shin JI. Beneficial effect of eculizumab on thrombotic microangiopathies: another point of view. Am J Kidney Dis. 2014;63(1):166-167. 2. Schmidtko J, Peine S, El-Housseini Y, Pascual M, Meier P. Treatment of atypical hemolytic uremic syndrome and thrombotic Am J Kidney Dis. 2014;63(1):164-173

microangiopathies: a focus on eculizumab. Am J Kidney Dis. 2013;61(2):289-299. 3. Kakishita E. Pathophysiology and treatment of thrombotic thrombocytopenic purpura/hemolytic uremic syndrome (TTP/HUS). Int J Hematol. 2000;71(4):320-327. 4. Strasly M, Cavallo F, Geuna M, et al. IL-12 inhibition of endothelial cell functions and angiogenesis depends on lymphocyteendothelial cell cross-talk. J Immunol. 2001;166(6):3890-3899. 5. Hawlisch H, Belkaid Y, Baelder R, Hildeman D, Gerard C, Kohl J. C5a negatively regulates Toll-like receptor 4-induced immune responses. Immunity. 2005;22(4):415-426. 6. Reis ES, Lange T, Kohl G, et al. Sleep and circadian rhythm regulate circulating complement factors and immunoregulatory properties of C5a. Brain Behav Immun. 2011;25(7):14161426. 7. La Sala A, Gadina M, Kelsall BL. G(i)-protein-dependent inhibition of IL-12 production is mediated by activation of the phosphatidylinositol 3-kinase-protein 3 kinase B/Akt pathway and JNK. J Immunol. 2005;175(5):2994-2999. 8. Demangel C, Palendira U, Feng CG, Heath AW, Bean AG, Britton WJ. Stimulation of dendritic cells via CD40 enhances immune responses to Mycobacterium tuberculosis infection. Infect Immun. 2001;69(4):2456-2461. 9. Moulton RA, Mashruwala MA, Smith AK, et al. Complement C5a anaphylatoxin is an innate determinant of dendritic cellinduced Th1 immunity to Mycobacterium bovis BCG infection in mice. J Leukoc Biol. 2007;82(4):956-967. 10. Lalli PN, Strainic MG, Lin F, Medof ME, Heeger PS. Decay accelerating factor can control T cell differentiation into IFN-gamma-producing effector cells via regulating local C5ainduced IL-12 production. J Immunol. 2007;179(9):5793-5802. Ó 2013 by the National Kidney Foundation, Inc. http://dx.doi.org/10.1053/j.ajkd.2013.10.053

RESEARCH LETTERS SCr and SCysC Concentrations Before and After Traumatic Amputation in Male Soldiers: A Case-Control Study To the Editor: Traumatic amputation affects people worldwide, but the impact on renal filtration markers is unknown. Serum creatinine (SCr) and cystatin C (SCysC) levels have been used alone and in combination to estimate glomerular filtration rate (producing eGFRcr, eGFRcys, and eGFRcr-cys, respectively).1-4 A hypothesized reduction in SCr level following amputation could result in overestimation of GFR and underappreciation of CKD. Therefore, we evaluated the effect of amputation on SCr and serum SCysC levels in otherwise healthy soldiers without kidney disease. We conducted a retrospective case-control study of the US Department of Defense Serum Repository (DoDSR) comparing pre- (,24 months) and postamputation (2-24 months; censored for periods of hospital admission or medications known to alter renal filtration marker levels) SCr and SCysC levels for 33 otherwise healthy male soldiers identified in the Armed Forces Amputee Care Program Database. Based on percent estimated body weight loss (%EBWL) determined by Osterkamp5 and Mozumdar and Roy6 estimations from dual-energy x-ray absorptiometry, amputees were divided into 3 groups (3%-5.9%, 6%-13.5%, and .13.5%). Background data were compiled from electronic medical records (Table 1). Exclusion criteria included CKD or AKI from any cause except correctable intravascular volume depletion. 167

Correspondence Table 1. Characteristics of Amputee Study Population and Controls Amputees by Extent of Amputation Variable

Age (y) Race Date of amputation Mechanism

All Amputees

Small

Medium

Large

Controls

24 (20-38)

27 (21-38)

24 (20-33)

23 (20-32)

25 W, 5 O, 3 B

6 W, 2 O, 1 B

7 W, 3 O, 2 B

11 W, 1 O

10 W, 1 O, 1 B

24 (21-32)

9/27/06-9/15/11

10/18/06-4/09/11

9/27/06-2/17/11

6/16/07-9/15/11

NA

25 IED, 1 RPG, 2 MVA, 2 NS

7 IED, 1 RPG, 1 MVA

10 IED, 1 MVA, 1 NS

11 IED, 1 NS

NA

%EBWL

12 (4-24)

5 (4-6)

10 (8-13)

19 (14-24)

NA

Pre BMI

24.9 (20.7-29.4)

24.7 (20.7-28.7)

25.7 (21.8-29.4)

24.3 (22.3-27.5)

NA

Post BMI

22.7 (16.0-29.4)

25.1 (19.7-28.5)

23.7 (16.0-29.4)

19.8 (16.2-25.9)

NA

Post ABMI

25.7 (18.2-32.7)

26.0 (20.5-29.6)

27.2 (22.5-32.7)

23.7 (18.2-28.5)

NA

NSAID use

95%

100%

92%

92%

NA

Received contrast Timing of serum collection Pre (d) Post (d)

45%

22%

50%

58%

NA

247 (70-717) 326 (120-1,106)

284 (125-502) 372 (121-817)

190 (82-317) 302 (124-1,106)

278 (70-717) 316 (120-909)

273 (61-700) 354 (50-1,249)

2.2 (1.4-3.8)

2.7 (1.4-3.8)

2.0 (1.6-2.5)

2.0 (1.5-2.5)

NA

3.9 (2.8-4.8) 5.2 (2.9-7.6)

4.1 (3.0-4.8) 5.0 (2.9-6.3)

3.9 (2.8-4.7) 4.7 (3.6-6.5)

3.7 (2.8-4.4) 5.8 (4.8-7.6)

NA NA

Periamputation albumin (g/dL) Labs .30 d post Albumin (g/dL) WBC count (3103/mL)

Note: Population/controls included no women. Amputees categorized by %EBWL: small, 4%-6%; medium; 6%-13.5%; large, .13.5%. Values in parentheses are ranges. NSAID use is percentage of patients with prescription for NSAID while hospitalized following injury. Received contrast is percentage of patients given iodinated contrast while hospitalized following injury. Timing of collections for controls is referent to date of amputation for each control patient’s 1:1-matched large amputation subgroup case. No intergroup differences in albumin or WBC count were statistically significant. Abbreviations: (A)BMI, (adjusted) body mass index; B, black; IED, improvised explosive device; MVA, motor vehicle accident; NS, not specified; NSAID, nonsteroidal anti-inflammatory drug; O, other; RPG, rocket-propelled grenade; W, white; WBC, white blood cell.

Serum samples were obtained from the previously described DoDSR,7 which also provided a healthy control for each of the 12 amputees with the largest %EBWL, matched on age, sex, race, and timing of serum collection. Standardized SCr and SCysC assays were run by Quest Diagnostics; eGFRs were calculated using CKD-EPI equations. Data were analyzed by paired t test with STATA 12.1 (Stata Corp). SCr level was significantly lower following amputation overall (1.04 6 0.18 vs 0.84 6 0.14 mg/dL; P , 0.001) and in the medium and large amputation subgroups (Table 2). SCysC level was unchanged after amputation both overall (0.80 6 0.09 vs 0.79 6 0.08 mg/L; P 5 0.6) and in all subgroups. SCr and SCysC levels remained unchanged in healthy controls over a similar interval. Overall, there was a statistically significant postamputation increase in eGFRcr (102 6 17 vs 122 6 13 mL/min/1.73 m2; P , 0.001) and eGFRcr-cys (109 6 13 vs 120 6 9 mL/min/1.73 m2; P , 0.001), but not eGFRcys (117 6 12 vs 119 6 11 mL/min/ 1.73 m2; P 5 0.4; Table 2). We report for the first time that traumatic amputation results in a significant reduction in SCr level, but not SCysC level. Thus, there was an average 20-mL/min/1.73 m2 overestimation of GFRcr after amputation, while eGFRcys was unchanged. These estimates assume that our rigorous criteria successfully excluded all amputees with non-prerenal AKI or CKD and that the monthslong interval between injury and follow-up serum analysis ensured recovery to a new physiologic baseline. A missed diagnosis of CKD due to overestimation of GFR could adversely affect clinical care. CKD is associated with significant morbidity and mortality.8 Nephrotoxin avoidance, medication dosing adjustments, and 168

contrast-induced AKI prophylaxis, as well as anemia of CKD and renal osteodystrophy treatment, all become particularly important starting in stage 3 CKD. Later, overestimation of GFR can delay hemodialysis access placement and listing for kidney transplantation. There are multiple potential explanations for unchanged SCysC levels. Due to the appendicular preponderance of skeletal muscle, limb amputation could lead to a disproportionate percent total body loss of cells producing creatine versus those producing SCysC. Our study may have been underpowered to detect small changes in SCysC level following amputation. Beta-trace protein, produced in the choroid plexus, therefore may prove a superior renal filtration marker than even SCysC because traumatic amputation would not be expected to decrease the number of betatrace protein–producing cells.9 A non-GFR determinant specific to SCysC could limit a postamputation reduction. In the absence of new-onset diabetes or smoking, inflammation would be the most likely culprit.10 Normal WBC counts and serum albumin levels following amputation speak against this. However, a comparison of C-reactive protein levels before and after amputation would have better addressed this possibility. Our study has the general limitations associated with retrospective analysis. In addition, a comparison of individual postamputation eGFR to a formal GFR measurement would be useful. However, measuring GFR before and after an unpredictable traumatic amputation is unrealistic. Our study’s small sample size limited our ability to compare %EBWL subgroups. However, our results provide the means and assessment of variation required to determine the sample size for a larger study that Am J Kidney Dis. 2014;63(1):164-173

Correspondence Table 2. SCr and SCysC Concentrations and Associated eGFR Values Before Amputation

All amputees Small amputation Medium amputation Large amputation Controls All amputees Small amputation Medium amputation Large amputation Controls All amputees Small amputation Medium amputation Large amputation Controls All amputees Small amputation Medium amputation Large amputation Controls All amputees Small amputation Medium amputation Large amputation Controls

1.05 1.08 1.10 0.97 1.02

6 6 6 6 6

0.18 0.23 0.17 0.12 0.16

After Amputation

SCr (mg/dL) (0.76-1.53) (0.84-1.53) (0.76-1.26) (0.79-1.19) (0.81-1.31)

eGFRcr (mL/min/1.73 m2) 102 6 17 (64-131) 98 6 19 (64-121) 98 6 19 (78-131) 109 6 13 (86-128) 105 6 17 (77-126) 0.80 0.75 0.81 0.84 0.77

6 6 6 6 6

117 122 117 114 121 109 111 107 111 113

0.10 0.10 0.10 0.08 0.10

SCysC (mg/L) (0.60-1.02) (0.60-0.98) (0.66-1.02) (0.71-0.97) (0.65-0.96) eGFRcys (mL/min/1.73 m2) (89-135) (93-131) (89-135) (95-128) (96-136)

6 6 6 6 6

12 11 12 11 13

6 6 6 6 6

eGFRcr-cys (mL/min/1.73 m2) 13 (76-135) 15 (76-127) 14 (88-135) 10 (97-126) 14 (90-133)

0.84 0.94 0.84 0.76 1.06

6 6 6 6 6

122 110 124 128 101 0.79 0.77 0.80 0.79 0.79

6 6 6 6 6

0.14 0.14 0.12 0.11 0.16 6 6 6 6 6

13 12 12 10 16

0.08 0.07 0.07 0.11 0.09

P Value

(0.65-1.19) (0.79-1.19) (0.65-1.06) (0.65-1.08) (0.84-1.37)

,0.001 0.2 ,0.001 ,0.001 0.6

(89-142) (89-125) (98-142) (98-138) (79-124)

,0.001 0.03 ,0.001 0.001 0.5

(0.62-0.93) (0.67-0.91) (0.71-0.91) (0.62-0.93) (0.63-0.93)

0.6 0.6 0.9 0.2 0.6

119 6 11 (100-138) 120 6 8 (102-130) 118 6 9 (104-130) 119 6 14 (100-138) 119 6 12 (100-138)

0.4 0.8 0.8 0.2 0.4

120 6 9 (101-138) 116 6 10 (101-126) 121 6 9 (105-132) 124 6 9 (112-138) 110 6 12 (91-123)

,0.001 0.3 ,0.001 0.003 0.3

Note: Data are mean 6 standard deviation, with range in parentheses.

may provide a more detailed assessment of the association and correlation between renal filtration markers and the extent of amputation. We conclude that clinicians should interpret SCr and eGFRcr values for amputees with caution. Our data suggest that SCysC level is preferable to SCr level for estimating GFR following amputation. John S. Thurlow, MD,1 Kevin C. Abbott, MD, MPH1 Alison Linberg, DPT,1 Dustin Little, MD1 Joshua Fenderson, MD,2 Stephen W. Olson, MD1 1 Walter Reed National Military Medical Center 2 Uniformed Services University of the Health Sciences Bethesda, Maryland Corresponding author: [email protected]

Acknowledgements We appreciate the assistance of the Amputee Program, under direction of Dr Charles Scoville. We are greatly indebted to the brave wounded service members who made this research possible. The views expressed are those of the authors and do not reflect the official policy of the US government or the departments of the Army, Navy, or Defense. Support: None. Financial Disclosure: The authors declare that they have no relevant financial interests. Am J Kidney Dis. 2014;63(1):164-173

References 1. Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med. 2006;354(23):2473-2483. 2. Inker LA, Schmid CH, Tighiouart H, et al. Estimating glomerular filtration rate from SCr and SCysC. N Engl J Med. 2012;367:20-29. 3. Stevens LA, Coresh J, Schmid CH, et al. Estimating GFR using serum SCysC alone and in combination with SCr: a pooled analysis of 3418 individuals with CKD. Am J Kidney Dis. 2008;51(3):395-406. 4. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from SCr: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461-470. 5. Osterkamp LK. Current perspective on assessment of human body proportions of relevance to amputees. J Am Diet Assoc. 1995;95:215-218. 6. Mozumdar A, Roy SK. Method for estimating body weight in persons with lower-limb amputation and its implication for their nutritional assessment. Am J Clin Nutr. 2004;80: 868-875. 7. Olson SW, Arbogast C, Yuan C, et al. Asymptomatic autoantibodies are associated with future anti-glomerular basement membrane disease. J Am Soc Nephrol. 2011;22:1946-1952. 169

Correspondence 8. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296-1305. 9. Juraschek SP, Coresh J, Inker LA, et al. Comparison of serum concentrations of b-trace protein, b2-microglobulin, SCysC, and creatinine in the US population. Clin J Am Soc Nephrol. 2013;8:584-592. 10. Stevens LA, Schmid CH, Greene T, et al. Factors other than glomerular filtration rate affect serum SCysC levels. Kidney Int. 2009;75(6):652-660. Received December 15, 2012. Accepted in revised form May 15, 2013. Originally published online September 18, 2013. Published by Elsevier Inc. on behalf of the National Kidney Foundation, Inc. This is a US Government Work. There are no restrictions on its use. http://dx.doi.org/10.1053/j.ajkd.2013.07.014

Pharmacokinetics and Pharmacodynamics of Imipenem and Meropenem in Critically Ill Patients Treated With Continuous Venovenous Hemodialysis To the Editor: Imipenem and meropenem are widely used in the treatment of Gram-negative infections in critically ill patients, and dosage adjustments are recommended in the setting of reduced kidney function or continuous renal replacement therapy (CRRT).1 After recent prospective randomized clinical trials failed to show a survival benefit of intensive CRRT, we hypothesized that extracorporeal clearance of antibiotics might lead to antibiotic underdosing and inadequate treatment of infection.2-4 Prior reports of imipenem and meropenem pharmacokinetics (PK) and pharmacodynamics (PD) rarely describe continuous venovenous hemodialysis (CVVHD), and there are no reports regarding meropenem in North American patients receiving CRRT, who may differ from their European counterparts (see first table of Item S1). Here, we report PK and PD measurements from 26 patients at the Cleveland Clinic receiving CVVHD and imipenem (n 5 16) or meropenem (n 5 10) between February 1, 2009, and July 1, 2012. Patients or their surrogates provided informed consent prior to study procedures. Demographic and clinical data were recorded on case report forms. Paired blood and CRRT effluent samples were drawn prior to an antibiotic dose, 30 minutes after the 30minute infusion, and immediately before the following dose. Free imipenem and meropenem concentrations in blood and dialysate were measured by high-performance liquid chromatography and fitted to a single-compartment PK model using nonlinear mixed-effects models. Extracorporeal clearance of carbapenems was calculated from effluent flow rates and drug concentrations. Typical PD parameters for in vivo studies of time-dependent antibiotics such as beta-lactams include time in excess of minimum inhibitory concentration (MIC) or some multiple thereof. We selected time in excess of 8 mg/mL, or 43MIC, as our PD metric for carbapenems active against Pseudomonas species and Enterobacteriaciae5,6 (detailed methods in Item S1). Patients were predominantly male (20/26) and weighed more (92 6 21 kg) than those in other studies (Table 1; Item S1). The intensive care unit mortality rate was very high (61.5%). CRRT dose was 23.4 6 7.4 mL/kg/h. Nonlinear mixed-effects PK modeling yielded a fixed-effect estimate for volume of distribution of 29.6 (95% CI, 26.3-33.1) L and for clearance of 5.34 (95% 170

Table 1. Descriptive Statistics of Patients Variable

Value

Age (y)

64 [49-70]; 58 6 8

M:F

20 (77%): 6 (23%) 96 [76-106]; 92 6 21

Admission weight (kg)

2.45 [2.02-2.90]; 2.48 6 0.57

Albumin (g/dL) Total bilirubin (mg/dL) Dialysate flow rate (mL/h)

1.95 [0.93-6.33]; 6.18 6 9.13 2,500 [2,125-2,688]; 2,387 6 598 34.7 [24.2-40.2]; 32.4 6 9.8

CRRT carbapenem clearance (mL/min) Intensive care unit survival

38.5%

Note: N 5 26, data available for all. Continuous data given as median [interquartile range]; mean 6 standard deviation.

CI, 4.32-6.00) L/h. The corresponding random-effects standard deviation estimates were 6.8 (95% CI, 4.3-10.3) L and 2.4 (95% CI, 1.2-3.0) L/h. Extracorporeal carbapenem clearance was 32.4 6 9.8 mL/min, only slightly lower than the dialysate flow rate (39.6 6 9.9 mL/min). Looking at patient-level covariates (age, sex, current weight, admit weight, weight change, and albumin level), there was a significant effect of current weight on volume of distribution, with a 1-kg increase in current weight corresponding to a 0.17-L increase in volume of distribution on average (P 5 0.02). A significant effect also was observed for drug type: the meropenem group was 6.2 L lower on average (volumes of distribution for imipenem and meropenem of 33.1 and 26.9 L, respectively; P 5 0.01). There was no evidence of an effect of any patient-level covariate on clearance. However, drug type exhibited a significant effect on clearance: the meropenem group was 4.2 L/h lower on average (clearance of 7.2 and 3.0 L/h for imipenem and meropenem, respectively; P , 0.001). Although adding drug type to the model reduced the random-effects variation in clearance from 2.4 to

Figure 1. Distribution of fractional time plasma concentration was .8 mg/mL (43MIC for susceptible bacteria). Drug exposure as estimated by this metric varied widely between individuals. Am J Kidney Dis. 2014;63(1):164-173