Distribution and correlates of creatinine clearance in children and adolescents with blood pressure elevation

Distribution and correlates of creatinine clearance in children and adolescents with blood pressure elevation stephen R. Daniels, MD, PhD, C. Frederic Strife, MD, Lawrence M. Dolan, and Jennifer M. H. Loggie, MD

MD,

From the Divisions of Cardiology, Clinical Pharmacology, Endocrinology and Nephrology, the Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio

The kidney has been implicated as both an etiologic factor and as a target organ in patients with essential hypertension. Renal function has not been studied extensively in children and adolescents with essential hypertension. Eightyeight subjects. aged 6 to 23 years, with blood pressure persistently above the 90th percentile for age were studied. Creatinine clearance was determined from a single 24-hour urine collection. The mean creatinine clearance was 129.3 ± 55.3 ml/rntn per 1.73 m2 . Multiple regression analysis was used to investigate potential correlates of creatinine clearance. Because creatinine clearance was not normally distributed, the logarithm of creatinine clearance was used as the dependent variable. Body mass index, resting heart rate, and basal supine plasma renin cetlvltv were significant direct independent correlates. Peripheral vascular resistance at maximal exercise was an inverse correlate of the logarithm of creatinine clearance. These findings are consistent with previous studies of adults and may provide the basis for strategies to identify young patients with essential hypertension who are at risk for the development of renal dysfunction. (J PEDIATR 1993;122:568-73)

Elevated blood pressure may initiate nephrosclerosis and accelerate loss of renal function in adults with essential hypertension.' In fact, hypertension is one of the most common causes of progressive renal insufficiency in adults in the United States, and subtle renal damage is common in patients with hypertension.? However, the mechanisms by which blood pressure elevation damages the kidney are not well understood, and it is difficult to identify adults with hypertension who are destined for eventual renal failure. Supported in part by grants K08-HL01380, ROl-HL36498 and RR-00123 from the National Institutes of Health, Bethesda, Maryland. Dr. Daniels is an Established Investigator of the American Heart Association. Presented in part at the meeting of the American Society of Hypertension, New York, New York, May 19, 1990. Reprint requests: Stephen R. Daniels, MD, PhD, Division of Cardiology, Children's Hospital Medical Center, Eiland and Bethesda Avenues, Cincinnati, OH 45229. Copyright @ 1993 by Mosby-Year Book, Inc. 0022-3476/93/$1.00 + .10 9/0/45141

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Changes in glomerular filtration rate have been implicated as an etiologic factor in essential hypertension! and as an indicator of target-organ damage." In clinical studies of adults with essential hypertension, several markers have been associated with incipient hypertensive nephropathy. These markers include hemodynamic factors, plasma norepinephrine concentration, plasma renin activity, plasma lipid levels, fasting blood sugar, and serum uric acid level." There have been few studies of the effects of elevated blood pressure on the kidneys in children and adolescents with essential hypertension. The purpose of this study was to describe the distribution of creatinine clearance in young patients with essential hypertension and to investigate potential correlates of creatinine clearance in this population.

METHODS Subjects. The study population consisted of patients with essential hypertension between the ages of 6 and 23 years followed in the hypertension clinic of the Children's Hospital Medical Center (CHMC). Blood pressure elevation was

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defined as systolic or diastolic blood pressure greater than the 90th percentile for age and sex 6 on at least three occasions during a 3-month period. Secondary causes of hypertension were excluded by clinical findings, routine laboratory examinations, and imaging techniques. Ninety-seven subjects met the entrance criteria. After informed consent was obtained from adolescent and-their parents, the subjects were admitted to the <:;HMC Clinical Research Center for a 36-hour period. This study was approved by the CHMC Institutional Review Board. Dependent variable. Creatinine clearance was calculated from a single 24-hour urine collection obtained under close supervision in the clinical research center. Urine and serum creatinine concentrations were measured by colorimetry in the CHMC Clinical Chemistry Laboratory. Creatinine clearance was calculated and adjusted to 1.73 m 2 body surface area. The completeness of the urine collection was determined by the subject's medical record and by questioning the subjects in the clinical research center. Urinary creatinine excretion (measured in milligrams per kilogram per day) was also used to verify completeness of urine collections. Subjects with irregularities in the urine collection or with creatinine excretion less than 8.0 or more than 32.0 mg/kg per day were excluded from the analysis." Independent variables. Nine categories of potential correlates of glomerular filtration rate were studied: (1) demography, (2) body size, (3) blood pressure and heart rate, (4) family history of cardiovascular disease, (5) treatment with antihypertensive medication, (6) dietary sodium intake and use of tobacco and alcohol, (7) laboratory tests , (8) cardiovascular reactivity to playing a video game under challenging conditions, and (9) cardiovascular reactivity to maximal exercise. Several variables in each of these categories wereinvestigated as potential independent correlates of creatinine clearance. The demographic variables. included age, race, sex, and socioeconomic status, measured by family income and maternal education. Body size variables included height, weight•. and body mass index, calculated as follows: Body mass index = Weight [in kilograms'[/Height [in centimeters]2. The mean systolic and diastolic blood pressure during follow-up in the hypertension clinic, the age at diagnosis of hypertension, and the known duration of the disease course were obtained from the medical records. Heart rate and blood pressure were measured by following the guidelines recommended by the Second Task Force on Btood Pressure Control in Children (National Heart, Lung , and Blood Institute)." Information concerning a family history of hypertension, dyslipoproteinemia, and early (before age 65 years) cardiovascular morbidity and death in first-degree relatives of the subject was obtained. Subjects were characterized with re-

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spect to treatment with antihypertensive medication , the number of medications used, and the duration of treatment. They were also questioned, without the paren ts present, about tobacco and alcohol.use. Dietary sodium intake was estimated in two ways. First, sodium excretion in the urine during a 24~hour period was taken as an indexof dietary salt intake. Second, subjects were allowed to select their diet while in the clinical research center. The type and amount of foods consumed were observed by a trained dietician, and the intake of sodium during a 24-hour period was calculated from the known sodium composition of each food. Venipuncture was performed at 8 AM on subjects who had been supine and fasting overnight. Several laboratory analyses were performed on the blood samples, including a lipid profile and determinations of fasting plasma glucose, hemoglobin (a measure of blood viscosity), plasma renin activity, serum aldosterone , and plasma catecholamine values . Basal plasma renin activity (Du Pont Co., Wilmington, Del.) and serum aldosterone concentration (Biotecx Laboratories, Inc., Friendswood, Tex.) were measured by radioimmunoassay in the endocrinology laboratory of the University of Cincinnati Hospital. Plasma catecholamine concentrations (dopamine, epinephrine, and norepinephrine) were measured by high-pressure liquid chromatography with electrochemical detection at the SmithKline Clinical Laboratories (St. Louis; Mo.). Measurements of total cholesterol, high-density lipoprotein-cholesterol, and triglyceride concentrations were conducted in a laboratory standardized by the Centers for Disease Control and Prevention, Atlanta, Ga. The low-density lipoprotein-cholesterol concentration was then calculated from those measurements. Two methods were used to investigate hemodynamic responses, First, a video game (PAC -Man) with an adjustable skill level was used to measure cardiovascular reactivity to a task requiring sustained concentration under challenging conditions. Previous studies have demonstrated that this stressor elicits cardiovascular changes comparable to those observed during mental arithmetic.? The instructions for the game emphasized that the game is a measure of handeye coordination and skill and that the subject is to attempt to achieve as high a score as possible. With the subject sitting quietly, baseline blood pressure and hear t rate were measured at 2-minute intervals for 10 minutes before the game . Measurements were then taken at I-minute intervals for 5 minutes during the game. The mean systolic and diastolic blood pressures, pulse pressure, and heart rate during mental stress, and the mean change in blood pressure and heart rate from resting to playing the video game, were used in the analysis . Second, a graded bicycle ergometer exercise protocol was used in the investigation; the subject's blood pressure, heart rate, and cardiac output were measured at rest and at 50%,

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TobIe I. Descriptive statistics for study population VarIable

Age at study (yr) Height (em)

Weight (kg) Bodymass index (weight/height/) Age at diagnosis (yr) Duration of hypertension (mo) SystolicBP at diagnosis (mm Hg) Diastolic BP at diagnosis (mm Hg) Resting heart rate (beats/min) Supine basal plasma renin activity (ng/dl/hr) Peripheral vascular resistance at maximum exercise (dynesec em-i)

Mean

Range

14.8 165.5 69.7 25.1 12.5 30.2 127.5 82.3 82.4 1.14

6-23 129.7-191.4 26.4-123.0 14.8-42.4 4-23 3-144 100-186 56-128 52-115 0.01-3.81

511.5

268-944

BP, Blood pressure.

75%, and lOO% of predicted maximal work load. The predicted maximal work load was calculated from a regression equation based on age, sex, and body size and previously derived in this laboratory from studies of the effects of exercise in normal children.l'' If the subject was able to perform at greater than 100% of the predicted work load, additional measurements were taken at increasing work loads until exhaustion. The amount of exercise performed by each subject was recorded. The working capacity and the heart rate, blood pressure, and cardiac output (CO) were measured as described previously.l? Peripheral vascular resistance (PVR) was calculated (in dyne per second per centimeter- S) from the variables described above by using the following equation!': MAP-RAP CO

X 80 = PVR

where MAP is the mean arterial pressure and the right atrial pressure (RAP) is assumed to be 5 rnm Hg. The values for heart rate, systolic blood pressure, diastolic blood pressure, cardiac output, and peripheral vascular resistance at maximal exercise, and the change in these measurements from rest to maximal exercise and the amount of exercise performed, were used as independent variables in the analysis. Data analysis. All data are expressed as the mean ± SD or range. The distribution of all variables was examined. When a variable was not normally distributed, transformations were employed to conform to the assumptions for statistical analysis. Because of the possibility that antihypertensivemedication may alter glomerular filtration rate, data were analyzed with those patients receiving medication both included and excluded. Because creatinine clearance was not normally distributed, a logarithmic transformation was used in the multi-

variable analysis. The correlations between the logarithm of creatinine clearance and the individual independent variables were determined by using the Pearson correlation coefficient. Multiple linear regression was used to examine the relationship between the independent variables and the logarithm of creatinine clearance to determine which variables were significant independent determinants of creatinine clearance. An all-possible-regressions multiple regression procedure was used. The regression model selected as the "best" model was the one that produced the highest multiple R2 and also contained only independent variables with regression coefficients that were statistically significantly different from zero. An all-possible-regressions analysis considers all combinations of independent variables and their ability to explain the variance of the dependent variable. This involves both a qualitative and a statistical evaluation of the multiple correlation coefficient (R 2) . The increase in R2 for the addition of an independent variable to a regression model was evaluated by comparing the regression model without that variable. An increase in R2 of 10% or more was considered important. A statistical test that the R2 was significantly different from zero was also performed for models that were judged to be candidates for the "best" regression model for explaining the variance of the logarithm of creatinine clearance. For candidate models, t tests for each of the regression coefficients were performed to test the null hypothesis that the regression coefficients were significantly different from zero. Only models in which all of the regression coefficients were significantly different from zero were considered. A p value <0.05 was used to indicate statistical significance. RESULTS Ninety-seven subjects had 24-hour urine collections. Nine were excluded because of incomplete urine collection. Of the remaining 88 subjects, 45 (51%) were white and 67 (76%) were male; 25 (28%) were receiving antihypertensive medication. Descriptive statistics for the study population are presented in Table I. The mean glomerular filtration rate was 129.3 ± 55.3 mljmin per 1.73 m 2 , the median was 119.7 mljmin per 1.73 m 2, and the range was from 55.1 to 338.7 ml/rnin per 1.73 m 2(Figure). The significant correlates of the logarithm of creatinine clearance are presented in Table II. The strongest direct correlate was body mass index (r = 0.33). The only inverse correlate was peripheral vascular resistance at maximum exercise tr = -0.18). The summary of the multiple regression analysis for the logarithm of creatinine clearance is presented in Table III. In this multivariable analysis a positive regression coefficient indicates a direct association between the independent

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FREQUENCY 14 13 12

10 9 8 7 6 5

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7 0

e a

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1

1 2

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1 4

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1 5 0

1 6 0

1 7 0

1 1 8 9 0 .0

2

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2 9 0

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CREATININE CLEARANCE Figure. Distribution of creatinine clear ance (in milliliters per minu te per 1.73 m2) in children and adolescents with essent ia l hypertens ion.

variab les and the logarithm of creatinine clearance, and a negative regression coefficient denotes an inverse relationship between the two. The multiple R 2 for the regression model is 0.35, which means that the regr ession equation including those variables accounts for 35% of the variance of the glomerular filtration rate. This suggests that other variables, not investigated in our study, are important determinants of glomerular filtration rate in young patients with hypertension. That the regression coefficients ar e significantly different from zero is an indication that the variables included in the model make a significant independe nt contr ibution to the explanation of the variance of the depende nt va riab le (logarithm of creatinine clearance) . D I S C U SSIO N Increased glomerular filtration rate has been reported to be one indicator of early nephrosclerosis in patients with diabetes mellitusl'' and hypertension.f In the study of Schmieder et al.," the patients with glomerular hyperfiltrat ion also had normal renal blood flow; this association implies increased filtra tion fraction and transcapillary hydraulic pressure. Studies of the spontaneously hypertensive rat

hav e demonstrated that glomerular damage occurs when increased hy draulic pressure is transmitted to the glomerular capillary.P Brenner' suggested that glomerularhyperfiltration caused by a reduction of glomerular surface area may be an etiologic factor in the genesis of essential hypertension. This may be especially important in the subset of patients with salt sensitivity . Creatinine clearance can be used to estimate glomerular filtration rate; however, the estimation may be higher tha n the true value.!" Studies of creatinine cleara nce in normal adults have demonstrated that the intraindividual variability is approximately 18% to 21 % in individuals studied once a year. 15 Multiple urine collections may improve reproducibility. However, the variability probably also reflects differe nces in muscle mass, dietary protein intake, and daily activity, as well as changes in renal function . The distribution and variability of creatinine clearance have not been extensively studied in children . These factors may limit the utility of a single measurement of creatinine clearance for determi ning renal function. In our study, neither dietary protein intake nor daily activity was controlled. Despit e the se limitation s, creati nine cleara nce has often been used

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Table II. Significant correlates of the logarithm of creatinine clearance Correlation coefflcienf

Table III. Multiple regression model for log creatinine clearance p

Demographic"

Body size Weight Body mass indext Triceps skin-fold thickness Blood pressure - heart rate Restingheart rate at time of study] Coefficient of variation of SBP Family history" Treatment" Diet* Laboratorystudy Supine Plasma Renin Activity]

0.23 0.33 0.31

<0.05 <0.01 <0.01

0.19 0.21

0.05 0.05

Intercept Body mass index (kg/m 2) Resting heart rate (beats/min) Supine plasma renin activity (ng/dl/hr) Peripheralvascular resistance at maximum exercise (dyne sec cm- S)

Coefficient 3.916 0.024 0.009 0.071 -0.001

Standard error

p

0.318 0.007 0.003 0.029

<0,001 <0.001 <0.01 <0.02

0.0003

<0.001

N '" 74. MuitipleR2 = 0.35,

0.26

<0.05

0.19 -0.18

0.05 <0.01

Stress"

Cardiovascular reactivity to exercise Heart rate at maximum exercise Peripheralvascular resistance at maximum exercise'[

Variable

SBP, Systolic blood pressure.

"Demcgraphic, family history, treatment, diet and life-style, and mental stress variables were not significantly correlated with log creatinine clearance. tVariable was significant in multiple regression.

clinically as a noninvasive indicator of renal function in children. The correlates of creatinine clearance have been studied in normal adults. James etal. 15 reported that black subjects had higher creatinine clearance than white subjects. Men also had higher creatinine clearance than women, even after the values were adjusted for differences in weight. Molina et al.16 studied creatinine clearance in school age-children in Venezuela and found no relationship to age, but they did find that creatinine clearance, unstimulated by dietary protein intake, was higher in male than in female subjects. Berenson etal.? investigated the relationship ofblood pressure to creatinine clearance in the Bogalusa, La., population.They found that black children in the higher blood pressure strata had creatinine clearance that was not significantly lower than that in black children in the lower blood pressure strata," The correlates of creatinine clearance have not previously been studied in children and adolescents with essential hypertension. We did not find an association between any of the demographic variables and the logarithm of creatinine clearance. Furthermore, the levels of blood pressure at the time of study and during outpatient visits were not associated with the logarithm of creatinine clearance. We did find that the variability of blood pressure during visits to the hypertension clinic was of borderline significance in the univariable analysis, but this was not a significant correlate in the multivariable analysis.

In studies of adults, plasma catecholamine levels, plasma lipid concentrations, and plasma renin activity have all been related to incipient hypertensive nephropathy.' In our study, plasma renin activity was directly associated with the logarithm of creatinine clearance. The other independent laboratory variables were not significantly associated with glomerular filtration rate. Previous studies of adults have shown a direct relationship between plasma renin activity and vascular injury to the heart, brain, and kidneys.!? This finding led to the suggestion that a high-renin phenotype in hypertensive adults is an independent risk factor for vascular injury. Because of the cross-sectional design of our study, it is impossible to determine a cause-and-effect temporal relationship between plasma renin activity and glomerular filtration rate. Further longitudinal studies are in progress and may better define the relationship between the two variables. Body mass index, which is a measure of ponderosity, and resting heart rate were direct independent correlates of the logarithm of creatinine clearance. These findings indicate that heavier subjects and those subjects with higher heart rates are more likely to have an elevated creatinine clear .. ance. The relationship between serum creatinine values and increased muscle mass is wellknown.l'' Further study will be needed for better definition of the relationship of body composition to creatinine clearance in children with essential hypertension. The mechanisms by which heart rate influences renal function are not clear; however, increased heart rate is associated with increased cardiac output. Messerli et aL19 previously demonstrated a direct correlation between cardiac output and renal and hepatic blood flow in adult patients with borderline hypertension. In our study, peripheral vascular resistance at maximum exercise was inversely correlated with the logarithm of creatinine clearance. Thus lower peripheral resistance during exercise may be associated with a higher glomerular filtration rate. It is possihle thatthese results demonstrate a more widespread alteration of vascular autoregulation; Thus an increase in cardiac output may be accompanied bya

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decrease in peripheral and renal vascular resistance. This finding is consistent with observations, in both animals and human beings, that indicate that failure of adequate renal afferent arteriolar constriction exposes the glomeruli to elevated blood pressure and flow. Under these circumstances, hyperperfusion induces hypertensive glomerular lesions.I" In summary, independent correlates of creatinine clearance have been identified in children and adolescents with essential hypertension. If these findings are confirmed in future longitudinal studies using more precise measures of renal function, they may ultimately provide the basis for strategies to identify subsets of pediatric patients with essential hypertension who are at risk for the development of renal dysfunction. This might lead to improvement in the clinical management of essential hypertension and ultimately to prevention of renal failure. REFERENCES 1. Baldwin DS, Neugarten J. Blood pressure control and progression of renal insufficiency. In: Mitch WE, Brenner BM, Stein JB, eds. The progressive nature of renal disease. New York: Churchill Livingstone, 1988:81-110. 2. Kaplan NM. Systemic hypertension: mechanisms and diagnosis. In: Braunwald E, ed. Heart disease: a textbook of cardiovascular medicine. 2nd ed. Philadelphia: WB Saunders, 1984: 849-901. 3. Brenner BM. Glomeruli and blood pressure: less of one, more of the other. Am J Hypertens 1988;1:335-47. 4. Schmieder RE, Messerli FH, Garavaglia GE, Nunez BD. Glomerular hyperfiltration indicates target organ disease in essential hypertension. Circulation 1987;76:IV-273. 5. Frohlich ED An epilogue: target-organ involvement in essential hypertension based on presented concepts and discussions. Am J Cardiol 1987;60:127I-321. 6. Task Force on Blood Pressure Control in Children [National Heart, Lung and Blood Institute]. Report of the Task Force on Blood Pressure Control in Children. Pediatrics 1977;59:797820. 7. Berenson GS, Voors AW, Dalferes ER, Webber LS, Shuler SE. Creatinine clearance, electrolytes and plasma renin activ-

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ity related to blood pressure of white and black children: the Bogalusa Heart Study. J Lab Clin Med 1979;93:535-48. 8. Second Task Force on Blood Pressure Control in Children [National Heart, Lung, and Blood Institute]. Report of the Second Task Force on Blood Pressure Control in Children1987. Pediatrics 1987;79:1-25. 9. Dembroski TM, MacDougall JM, Shields JL, Petitio J, Lushene R. Components of type A coronary prone behavior pattern and cardiovascular responses to psychomotor performance challenge. J Behav Med 1978;1:159-76. 10. James FW, Kaplan S, Glueck CJ, Tsay J, Knight MJ, Sarwar CJ. Responses of normal children and young adults to controlled bicycle exercise. Circulation 1980;61:902-12. 11. Sokolow M, Mcllroy MD, eds, Clinical cardiology. 3rd ed. Los Altos, California: Lange, 1981:79. 12. Mogensen CE, Christensen CK. Predicting diabetic nephropathy in insulin-dependent patients. N Engl J Med 1984;311:8993. 13. Martinez-Maldonado M, Rodridquez-Sargent C, Cangiano JL, Dworkin LD. Pathogenesis of systemic hypertension and glomerular injury in the spontaneously hypertensive rat. Am J Cardiol 1987;60:47I-52I. 14. Levey AS. Use of glomerular filtration rate measurements to assess the progression of renal disease. Semin N ephrol 1989; 9:370-9. 15. James GD, Sealey JE, Alderman M, et al. A longitudinal study of urinary creatinine and creatinine clearance in normal subj ec ts: race, sex and age differences. Am J B ypertens1988; I :12431. 16. Molina E, Herrera J, Rodriquez-Iturbe B. The renal functional reserve in health and renal disease in school age children. Kidney Int 1988;34:809-16. 17. Brunner HR, Laragh JH, Baer L, et al. Essential hypertension: renin and aldosterone, heart attack and stroke. N Engl J Med 1972;286:441-5. 18. Edwards KDG, Whyte HM. Creatinine excretion and body composition. Clin Sci 1959;18:361-6. 19. Messerli FH, DeCarvalho JGR, Christie B, Frohlich ED. Systemic and regional hemodynamics in low, normal and high cardiac output borderline hypertension. Circulation 1978;58: 441-8. 20. Schwartz GL, Strong CG. Renal parenchymal involvement in essential hypertension. Med Clin North Am 1987;71:843-58.