- Email: [email protected]
Chronic kidney disease and cognitive impairment in menopausal women
Chronic Kidney Disease and Cognitive Impairment in Menopausal Women Manjula Kurella, MD, Kristine Yaffe, MD, Michael G. Shlipak, MD, Nanette K. Wenger, MD, and Glenn M. Chertow, MD ● Background: Although end-stage renal disease has been associated with cognitive impairment, the relation between lesser degrees of chronic kidney disease (CKD) and cognitive impairment is less well understood. Methods: Data for 1,015 women enrolled at 10 of the 20 Heart Estrogen/Progestin Replacement Study clinical sites were analyzed. All participants were younger than 80 years and had established coronary artery disease at study entry. Participants underwent 6 standard tests of cognitive function evaluating various domains. Unadjusted, residual age- and race-adjusted, and multivariable-adjusted linear and logistic regression models were used. Glomerular filtration rate (GFR) was estimated using the Modification of Diet in Renal Disease regression equation. In addition to analyses across the spectrum of GFRs, CKD was categorized as mild (estimated GFR [eGFR], 45 to 60 mL/min/1.73 m2), moderate (eGFR, 30 to 44 mL/min/1.73 m2), and severe (eGFR, <30 mL/min/1.73 m2) according to a modification of recently established classification guidelines. Results: Mean eGFR was 57 ⴞ 14 mL/min/1.73 m2. In multivariable analyses, eGFR was associated significantly with impairment in global cognition, executive function, language, and memory (⬃15% to 25% increase in risk for dysfunction/10-mL/min/1.73 m2 decrement in eGFR). Associations among eGFR and cognitive function were independent of residual effects of age and race (2 key determinants of GFR) and the contributions of education, lifestyle factors, stroke, diabetes, and other laboratory variables. Conclusion: CKD is associated with cognitive impairment in menopausal women with coronary artery disease. Am J Kidney Dis 45:66 –76. © 2004 by the National Kidney Foundation, Inc. INDEX WORDS: Chronic kidney disease (CKD); cognitive function; quality of life.
C
OGNITIVE IMPAIRMENT IS a wellrecognized manifestation of uremia. A variety of related deficits, including lethargy, reduced attention, memory impairment, concentration difficulty, sleep disturbances, and dementia, have been described in the end-stage renal disease (ESRD) population.1,2 Although the pathogenesis of cognitive impairment in patients with uremia has not been fully elucidated, cognitive function in patients with ESRD has improved with dialysis and renal transplantation.3,4 In addition to the effects of accelerated atherosclerosis, unresolved uremia, ane-
From the Department of Medicine, Divisions of Nephrology, Psychiatry, and Neurology, Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA; and Department of Medicine, Division of Cardiology, Emory University, Atlanta, GA. Received June 8, 2004; accepted in revised form August 2, 2004. Address reprint requests to Glenn M. Chertow, MD, Department of Medicine Research, University of California San Francisco, UCSF Laurel Heights Ste 430, 3333 California St, San Francisco, CA 94118-1211. E-mail: chertowg@ medicine.ucsf.edu © 2004 by the National Kidney Foundation, Inc. 0272-6386/04/4501-0007$30.00/0 doi:10.1053/j.ajkd.2004.08.044 66
mia, hyperparathyroidism, hyperprolactinemia, and other endocrinopathies, the adverse effects of drugs and retained metabolites might also contribute to cognitive impairment in the ESRD population.5,6 It is unknown whether less severe degrees of chronic kidney disease (CKD) also are associated with cognitive impairment. Although generally more subtle, many of the metabolic abnormalities observed in patients with ESRD also are present in patients with CKD.7 CKD is much more common than ESRD. Whereas approximately 300,000 persons in the United States require dialysis therapy, the Third National Health and Nutrition Examination Survey estimated the burden of CKD in the US population to be approximately 8.0 million persons.8 To examine whether CKD is a risk factor for cognitive impairment, we analyzed data collected for 1,015 women who were enrolled at 10 of the 20 Heart Estrogen/Progestin Replacement Study (HERS) clinical sites and underwent cognitive function testing at the end of the study. We hypothesized that cognitive function would vary directly according to glomerular filtration rate (GFR) and that severe CKD (defined as an estimated GFR [eGFR] ⬍30 mL/min/1.73 m2) would
American Journal of Kidney Diseases, Vol 45, No 1 (January), 2005: pp 66 –76
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
be associated with a significant risk for cognitive impairment.
67
tionnaire was used to adjust for symptoms of depression in selected analyses.
Statistical Analysis METHODS
Subjects Study participants, trial design, and primary outcomes of HERS have been described previously.9,10 There were no exclusion criteria based on kidney function. Study subjects were postmenopausal women younger than 80 years with established coronary artery disease who had not undergone hysterectomy. Subjects were randomly assigned to administration of a single tablet containing 0.625 mg of conjugated equine estrogen and 2.5 mg of medroxyprogesterone acetate or matching placebo. Cardiovascular events were the primary outcomes of interest. None of the women enrolled in HERS had a history of dementia or was taking medication for dementia at the time of enrollment.
Subject-Level Data Demographic characteristics, chronic health conditions, medication use, education level, and lifestyle factors were ascertained by means of questionnaire for all HERS participants at enrollment, and some information was updated during the study period. Laboratory values, including serum creatinine, blood urea nitrogen, and albumin, were measured in unfrozen serum at a single central laboratory using standard methods. For the purpose of these analyses, we incorporated laboratory values that coincided with the time cognitive function tests were performed, rather than baseline or other values.
Cognitive Function Tests A battery of 6 cognitive function tests was administered by trained staff at the end of year 4 for participants at 10 of the 20 HERS clinical sites. The Modified Mini-Mental State Examination (3MS) is a global assessment of cognitive function. Scores range from 1 to 100, with higher scores indicating better cognitive performance. A 3MS score less than 80 is used commonly as an indication of impairment.11 The Trail Making Test Part B (Trails B) assesses attention, concentration, psychomotor speed, and executive function (tasks that require organization, assimilation, and execution) by measuring the time required to connect a series of sequential numbered and lettered circles. Better performance is indicated by shorter completion times. The Modified Boston Naming test requires participants to name objects presented on a piece of paper. It assesses language skills, with higher scores denoting better function. For the Verbal Fluency test, subjects are asked to name as many animals as possible in 1 minute. The Verbal Fluency test is a test of working and semantic memory. The Word List Memory and Word List Recall tests evaluate immediate and short-term memory skills, respectively. For the Word List Memory test, participants are queried 3 times on the immediate recall of 10 standardized words (score range, 0 to 30). The Word List Recall test measures recall of the same words after a delay of 20 minutes. In addition, the score on the 15-item Geriatric Depression Scale self-administered ques-
Continuous variables are expressed as mean ⫾ SD or median with 10% and 90% ranges and compared with general linear models. Categorical variables are expressed as proportions and compared using chi-square test. We selected variables for analysis from the larger HERS database that might have confounded the relation between renal function and cognitive function (Table 1). These included demographic variables (eg, age, race), comorbid conditions (eg, diabetes mellitus, hypertension), concurrent laboratory values (eg, serum sodium, cholesterol), and cardiovascular events that were adjudicated during the study (eg, myocardial infarction, stroke). We used number of years of education, exercise patterns, ethanol and tobacco use, and number of teeth as proxies for socioeconomic and lifestyle variables. eGFR was calculated according to the published equation from the Modification of Diet in Renal Disease (MDRD) Study, incorporating age, black versus nonblack race, and serum creatinine, urea nitrogen, and albumin concentrations.12 To examine whether method of CKD classification affected study results, we also calculated estimated creatinine clearance using the Cockcroft-Gault equation.13 Results on all cognitive function tests were qualitatively similar when Cockcroft-Gault estimates were used; therefore, only models using MDRD eGFR are shown. Each of the 6 cognitive function tests was modeled individually. Model building proceeded as follows. First, we conducted unadjusted analyses examining the relation between eGFR and the test of interest. Second, we adjusted for “residual case mix”; age and race in this case. Finally, we adjusted for other confounding variables by using multivariable linear or logistic regression. For cognitive function variables that were normally or near-normally distributed, we used linear regression across the population range of eGFR. For non–normally distributed variables, we a priori dichotomized values for which there were established or otherwise obvious cutoffs. For instance, we used a 3MS score less than 80 and a Trails B score of 300 to dichotomize subjects for these 2 tests. Otherwise, we categorized subjects into quartiles based on data distribution and applied logistic regression to examine predictors of the “abnormal” quartile compared with all other quartiles. We included diabetes in all multivariable models because of the known association between diabetes and cognitive impairment. For other variable selection, we used backward elimination with criteria for acceptance set at P less than 0.05. After the initial multivariable models were fit, we manually added selected variables to evaluate for residual confounding. We predefined residual confounding as a change of 5% or more in the parameter estimate for GFR. We also tested for effect modification by using multiplicative interaction terms for selected variables, and for nonlinearity, by including a quadratic term for GFR. Models comparing cognitive function across the spectrum of eGFRs were primary. We also conducted companion analyses stratifying subjects by defined categories of eGFR. We used a modification of a classification scheme recently published by the National Kidney Foundation–Kidney Disease Outcomes Quality Ini-
68
KURELLA ET AL Table 1. Characteristics of Study Subjects Stratified by CKD Categories GFR (mL/min/1.73 m2)
Age (y) Race (% black) Height (cm) Weight (kg) Quetelet’s index (kg/m2) Diabetes* (%) Hypertension* (%) Tobacco use, current (%) Ethanol use† (%) Education (% graduate) Exercise‡ (%) No. of upper teeth No. of lower teeth Myocardial infarction§ (%) Congestive heart failure§ (%) Stroke§ (%) Stroke or transient ischemic attack§ (%) Coronary artery bypass graft§ (%) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Blood urea nitrogen (mg/dL) Creatinine (mg/dL) Sodium (mEq/L) Potassium (mEq/L) Bicarbonate (mEq/L) Calcium (mg/dL) Phosphorus (mg/dL) Albumin (g/dL) Glucose (mg/dL) Uric acid (mg/dL) Iron (g/dL) Total bilirubin (mg/dL) Cholesterol (mg/dL) Low-density lipoprotein cholesterol (mg/dL) High-density lipoprotein cholesterol (mg/dL) Triglycerides (mg/dL) Lipoprotein (a) (mg/dL)
ⱖ60 (n ⫽ 404)
45-59 (n ⫽ 448)
30-45 (n ⫽ 135)
⬍30 (n ⫽ 28)
P
65.2 ⫾ 6.3 8 159.6 ⫾ 6.1 72.4 ⫾ 15.4 28.3 ⫾ 5.6 15 53 14 11 45 36 7⫾6 8⫾6 7 3 1 2 6 136 ⫾ 18 74 ⫾ 9 13 ⫾ 4 0.9 ⫾ 0.1 140 ⫾ 3 4.3 ⫾ 0.3 24 ⫾ 3 9.2 ⫾ 0.3 3.6 ⫾ 0.5 4.0 ⫾ 0.2 107 ⫾ 33 4.2 ⫾ 1.2 90 ⫾ 34 0.7 ⫾ 0.2 210 ⫾ 39 125 ⫾ 36 53 ⫾ 13 161 ⫾ 76 24 ⫾ 23
67.3 ⫾ 6.1 5 159.2 ⫾ 5.9 70.6 ⫾ 14.2 27.8 ⫾ 5.1 16 56 11 8 39 33 7⫾6 8⫾5 9 7 3 7 7 135 ⫾ 19 72 ⫾ 9 17 ⫾ 4 1.1 ⫾ 0.1 140 ⫾ 2 4.3 ⫾ 0.4 24 ⫾ 2 9.3 ⫾ 0.3 3.6 ⫾ 0.4 3.9 ⫾ 0.2 112 ⫾ 43 4.7 ⫾ 1.2 86 ⫾ 32 0.7 ⫾ 0.2 211 ⫾ 39 125 ⫾ 36 51 ⫾ 13 176 ⫾ 79 22 ⫾ 23
69.5 ⫾ 5.9 4 159.2 ⫾ 6.4 74.1 ⫾ 15.8 29.3 ⫾ 6.0 35 66 10 4 37 26 7⫾6 7⫾6 9 12 5 10 8 137 ⫾ 23 71 ⫾ 9 24 ⫾ 6 1.4 ⫾ 0.1 140 ⫾ 3 4.4 ⫾ 0.4 24 ⫾ 3 9.3 ⫾ 0.3 3.7 ⫾ 0.4 3.9 ⫾ 0.2 122 ⫾ 57 5.5 ⫾ 1.4 82 ⫾ 29 0.7 ⫾ 0.2 216 ⫾ 35 126 ⫾ 40 51 ⫾ 15 181 ⫾ 88 26 ⫾ 25
66.6 ⫾ 6.9 29 161.2 ⫾ 6.9 78.3 ⫾ 20.2 30.1 ⫾ 7.4 57 67 0 0 32 14 5⫾6 7⫾5 11 25 11 18 7 136 ⫾ 19 70 ⫾ 9 48 ⫾ 15 2.9 ⫾ 1.7 140 ⫾ 3 4.4 ⫾ 0.8 23 ⫾ 4 9.1 ⫾ 0.4 4.0 ⫾ 0.6 3.7 ⫾ 0.3 118 ⫾ 48 6.9 ⫾ 1.7 77 ⫾ 33 0.7 ⫾ 0.2 202 ⫾ 46 116 ⫾ 35 50 ⫾ 16 180 ⫾ 97 26 ⫾ 30
⬍0.0001 0.81 0.82 0.61 0.41 ⬍0.0001 0.006 0.02 0.003 0.03 0.006 0.67 0.77 0.17 ⬍0.0001 0.0002 ⬍0.0001 0.47 0.57 0.0008 ⬍0.0001 ⬍0.0001 0.38 ⬍0.0001 0.006 0.26 0.0002 ⬍0.0001 0.002 ⬍0.0001 0.01 0.63 0.51 0.72 0.02 0.005 0.95
NOTE. For continuous variables, P for trend by GFR. To convert blood urea nitrogen in mg/dL to mmol/L, multiply by 0.357; creatinine in mg/dL to mol/L, multiply by 88.4; calcium in mg/dL to mmol/L, multiply by 0.25; phosphorus in mg/dL to mmol/L, multiply by 0.323; albumin in g/dL to g/L, multiply by 10; glucose in mg/dL to mmol/L, multiply by 0.0555; uric acid in mg/dL to mol/L, multiply by 59.48; iron in g/dL to mol/L, multiply by 0.179; bilirubin in mg/dL to mol/L, multiply by 17.1; cholesterol in mg/dL to mmol/L, multiply by 0.0259; low-density lipoprotein cholesterol in mg/dL to mmol/L, multiply by 0.0259; high-density lipoprotein cholesterol in mg/dL to mmol/L, multiply by 0.0259; triglycerides in mg/dL to mmol/L, multiply by 0.0113; lipoprotein (a) in mg/dL to mol/L, multiply by 0.0357. *By history. †Seven or more drinks per week. ‡Three or more times per week. §Adjudicated during study.
tiative.14 Given the relatively large number of subjects with an eGFR between 30 and 59 mL/min/1.73 m2 (stage III CKD) and the relatively small number of subjects with an eGFR less than 30 mL/min/1.73 m2, we split the stage III
CKD category into 2 subcategories (30 to 44 and 45 to 59 mL/min/1.73 m2) to evaluate for threshold effects. In general, the descriptor “CKD” refers to all women with an eGFR less than 60 mL/min/1.73 m2.
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
69
Table 2. Cognitive Function Test Results by CKD Category GFR (mL/min/1.73 m2)
3MS Trails B Boston Naming Verbal Fluency Word List Memory Word List Recall
ⱖ60
45-59
30-44
⬍30
96 (88-99) 130 (59-275) 15 (13-15) 16 (11-23) 21 (14-26) 7 (3-9)
95 (85-99) 131 (60-300) 14 (12-15) 16 (10-23) 20 (14-25) 7 (4-9)
93 (82-99) 157 (13-300) 14 (11-15) 16 (10-22) 19 (11-23) 6 (1-9)
90 (74-98) 183 (14-300) 13 (8-15) 14.5 (10-22) 18.5 (9-24) 6 (0-9)
NOTE. Values expressed as median (10% to 90% range).
For logistic regression models, we used the area under the receiver operating characteristic (ROC) curves to assess model discrimination.15 The Hosmer-Lemeshow goodnessof-fit test was used to assess model calibration.16 We considered the extent of variation explained and Mallow’s Cp in determining optimal linear regression models. For all analyses, 2-tailed P less than 0.05 is considered significant. Analyses were conducted using SAS, version 8.2 (SAS Institute, Cary, NC).
RESULTS
Baseline Characteristics One thousand sixty-three HERS enrollees underwent cognitive function testing. Forty-eight women (4.5%) did not have coincident laboratory test results, and GFR could not be estimated. Mean age was 66.7 ⫾ 6.4 years. Mean eGFR (n ⫽ 1,015) was 57.3 ⫾ 13.9 mL/min/1.73 m2, and mean estimated creatinine clearance was 58.9 ⫾ 19.7 mL/min (42.2 ⫾ 11.1 mL/min incorporating ideal, rather than actual, body weight). Women with no laboratory values were significantly older and had fewer years of education, fewer teeth, and significantly worse scores on all cognitive function tests except the Trails B (data not shown). There were no missing laboratory data elements among the 1,015 subjects with coincident laboratory data. Baseline characteristics of study subjects are listed in Table 1. Compared with women with an eGFR of 60 mL/min/1.73 m2 or greater, women with CKD (eGFR ⬍ 60 mL/min/1.73 m2) were on average older and more likely to have diabetes mellitus, hypertension, congestive heart failure, and stroke. Women with CKD also were less likely to have graduated high school and less likely to exercise. Table 2 lists median and 10% to 90% limits for the 6 tests of cognitive function within each of the CKD categories. Cognitive
function scores generally were higher for HERS participants compared with age- and educationmatched population norms. For example, HERS subjects with an eGFR of 60 mL/min/1.73 m2 or greater had 3MS scores 4 points higher than normative values for women aged between 65 and 69 years with a high school education. Women with an eGFR less than 30 mL/min/1.73 m2 had 3MS scores approximately 2 points lower than published norms.17 Association of Glomerular Filtration Rate With Cognitive Function Test Results Modified Mini-Mental Status Examination. Median score on the 3MS was 95; scores ranged from 53 to 100. In the entire cohort, 5% of women had global cognitive impairment, defined as a 3MS score less than 80. As shown in Table 3, there was a significant association between eGFR and global cognitive impairment with adjustment for the residual effects of age, race, education, adjudicated stroke or transient ischemic attack, tobacco use, and serum cholesterol and sodium concentrations. There was a 27% increase in risk for global cognitive impairment per each 10-mL/min/1.73 m2 decrement in GFR, and persons with severe CKD were 5-fold more likely to have low 3MS scores than those with a normal or near-normal GFR. Because depression may confound global cognitive function and CKD is associated with depression, we conducted an additional analysis in which we also adjusted for the Geriatric Depression Scale. The effect estimates were changed only slightly (25% increase in risk/10-mL/min/ 1.73 m2 decrement in GFR, and 4.5-fold increase for advanced CKD), suggesting that cognitive
70
KURELLA ET AL Table 3. GFR and CKD Categories and Cognitive Impairment by 3MS Score Less Than 80
GFR (per 10 mL/min/1.73 m2) Age (y) Black race Diabetes Education (y) Sodium (mEq/L) Stroke or transient ischemic attack Tobacco use, current Cholesterol (10 mg/dL) CKD GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Sodium (mEq/L) Stroke or transient ischemic attack Tobacco use, current Cholesterol (10 mg/dL)
Unadjusted OR (95% CI)
Residual Age- and RaceAdjusted OR (95% CI)
Full Model OR (95% CI)
1.45 (1.18-1.75) — — — — — — — —
1.32 (1.05-1.61) 1.13 (1.07-1.20) 5.74 (2.64-12.5) — — — — — —
1.27* (1.01-1.59) 1.15* (1.08-1.22) 5.76* (2.46-13.5) 0.69* (0.30-1.60) 0.82* (0.73-0.91) 0.88* (0.79-0.99) 4.10* (1.73-9.74) 2.42* (1.00-5.82) 1.07* (1.00-1.15)
2.41 (1.15-5.06) 3.19 (1.30-7.84) 8.84 (2.78-28.1) — — — — — — — —
2.16 (1.00-4.64) 2.31 (0.90-5.94) 5.58 (1.61-19.4) 1.13 (1.07-1.20) 5.51 (2.48-12.2) — — — — — —
1.91† (0.86-4.23) 1.80† (0.65-4.97) 5.01† (1.27-19.7) 1.15† (1.09-1.23) 5.21† (2.14-12.7) 0.73† (0.31-1.68) 0.82† (0.73-0.91) 0.89† (0.80-0.99) 3.95† (1.66-9.36) 2.46† (1.02-5.93) 1.08† (1.00-1.15)
NOTE. Values expressed as OR (95% CI). OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. To convert cholesterol in mg/dL to mmol/L, multiply by 0.0259. *Area under ROC curve ⫽ 0.84, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.83 †Area under ROC curve ⫽ 0.84, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.50, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 2.69 (1.00 to 7.27), 2.74 (0.95 to 7.88) and 5.57 (1.42 to 27.9).
impairment in patients with CKD was not the result of a depressed affect. Trail Making Test Part B (attention, concentration, psychomotor speed, and executive function). Thirty-three subjects (3%) were recorded as having a zero score (ie, 0 seconds to complete the task) on Trails B and therefore were excluded. Scores on the Trails B ranged from 10 to 300 seconds. One hundred fifteen subjects (12%) had impairment on Trails B (score, 300 seconds). The odds of scoring poorly on Trails B were increased with lower eGFR, even with multivariable adjustment (Table 4). The proportion of subjects with abnormal 3MS (P ⬍ 0.0001) and Trails B scores (P ⫽ 0.001) was associated significantly with CKD category (Fig 1). Modified Boston Naming. Scores on the Boston Naming test ranged from 0 to 15. There were 768 subjects (76%) who achieved scores of 14 or 15. The odds of scoring poorly on the Modified
Boston Naming test also increased significantly with lower eGFR (Table 5). Verbal Fluency. Mean Verbal Fluency score was 16.2 ⫾ 4.9 words (median, 16 words; range, 0 to 37 words), and scores were normally distributed. eGFR was associated significantly with verbal fluency on unadjusted analyses (0.25 words/10 mL/min/1.73 m2; P ⫽ 0.02). However, the GFR–verbal fluency association was no longer statistically significant after adjusting for residual effects of age and race (P ⫽ 0.26) or after multivariable adjustment (P ⫽ 0.96). Word List Memory (immediate) and Word List Recall (delayed). Scores on the Word List Memory test were normally distributed. eGFR was related significantly to the score on Word List Memory (0.54 words/10 mL/min/1.73 m2; P ⬍ 0.0001). Expressed by CKD category, mean numbers of words were 20, 20, 18, and 17 for subjects with eGFRs of 60 or greater, 45
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
71
Table 4. GFR and CKD Categories and Cognitive Impairment by Trails B (score, 300)
GFR (per 10 mL/min/1.73 m2) Age (y) Black race Diabetes Education (y) Weight (kg) Lower teeth (tooth) Upper teeth (tooth) Cholesterol (10 mg/dL) CKD category GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Weight (kg) Lower teeth (tooth) Upper teeth (tooth) Cholesterol (10 mg/dL)
Unadjusted OR (95% CI)
Residual Age- and Race-Adjusted OR (95% CI)
Full Model OR (95% CI)
1.33 (1.16-1.54) — — — — — — — —
1.25 (1.08-1.45) 1.10 (1.06-1.14) 5.78 (3.18-10.5) — — — — — —
1.19* (1.01-1.39) 1.09* (1.05-1.13) 6.14* (3.20-11.8) 1.84* (1.09-3.81) ⫺0.83* (0.77-0.91) 0.98* (0.96-0.99) 0.90* (0.83-0.98) 1.10* (1.02-1.18) 1.06* (1.00-1.11)
1.35 (0.86-2.13) 2.05 (1.16-3.64) 3.52 (1.40-8.85) — — — — — — — —
1.26 (0.79-2.03) 1.70 (0.91-3.09) 2.23 (0.82-6.09) 1.09 (1.05-1.13) 5.96 (3.29-10.8) — — — — — —
1.10† (0.67-1.80) 1.21† (0.63-2.34) 2.24† (0.77-6.51) 1.10† (1.05-1.14) 5.72† (2.96-11.0) 1.92† (1.14-3.26) 0.83† (0.77-0.91) 0.98† (0.97-0.99) 0.90† (0.83-0.97) 1.10† (1.02-1.19) 1.06† (1.01-1.12)
NOTE. To convert cholesterol in mg/dL to mmol/L, multiply by 0.0259. OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. *Area under ROC curve ⫽ 0.79, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.22 †Area under ROC curve ⫽ 0.79, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.22, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 2.02 (1.14 to 3.58), 2.02 (1.07 to 3.82), and 4.08 (1.52 to 10.9).
to 59, 30 to 44, and less than 30 mL/min/1.73 m2. The relation between eGFR and Word List Memory test score remained significant after adjustment for residual effects of age and race and the significant effects of education, to-
Fig 1. Percentage of abnormal study results on the 3MS (score < 80) and Trails B (score, 300) by categories of CKD. Chi-squared test for trend across CKD categories, 3MS (P < 0.0001) and Trails B (P ⴝ 0.01).
bacco use, diabetes, stroke, and systolic and diastolic blood pressure. The multivariable linear effect estimate was 0.25 words/10 mL/min/ 1.73 m2 of eGFR (P ⫽ 0.02). In other words, even after multivariable adjustment, subjects
72
KURELLA ET AL Table 5. GFR and CKD Categories and Cognitive Impairment by Boston Naming (13 or fewer)
GFR (per 10 mL/min/1.73 m2) Age (per year) Black race Diabetes Education (per year) Body weight (per kg) Sodium (per mEq/L) CKD category GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Body weight (kg) Sodium (mEq/L)
Unadjusted OR (95% CI)
Residual Age- and Race-Adjusted OR (95% CI)
Full Model OR (95% CI)
1.23 (1.10-1.37) — — — — — —
1.18 (1.06-1.33) 1.06 (1.03-1.09) 5.42 (3.21-9.18) — — — —
1.16* (1.03-1.31) 1.06* (1.03-1.09) 4.91* (2.78-8.68) 1.18* (0.79-1.79) 0.80* (0.75-0.86) 0.98* (0.97-0.99) 1.07* (1.01-1.14)
1.69 (1.21-2.35) 1.94 (1.24-3.04) 5.32 (2.43-11.7) — — — — — —
1.66 (1.17-2.34) 1.74 (1.08-2.79) 4.03 (1.75-9.28) 1.06 (1.03-1.09) 5.22 (3.06-8.90) — — — —
1.55† (1.09-2.22) 1.43† (0.86-2.37) 4.02† (1.66-9.76) 1.06† (1.03-1.09) 4.68† (2.62-8.34) 1.18† (0.78-1.79) 0.80† (0.75-0.86) 0.98† (0.97-0.99) 1.08† (1.01-1.15)
NOTE. OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. *Area under ROC curve ⫽ 0.72, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.12. †Area under ROC curve ⫽ 0.73, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.52, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 1.43 (0.97 to 2.11), 1.54 (0.98 to 2.42), and 3.11 (1.34 to 7.26). Referent category is estimated GFR of 60 mL/min/1.73 m2.
with a GFR less than 30 mL/min/1.73 m2 were able to recall 2 fewer words than subjects with a normal or near-normal GFR. The odds of achieving a low score (ⱕ4) on the Word List Recall test was significantly related to eGFR (odds ratio [OR], 1.23; 95% confidence interval [CI], 1.11 to 1.37/10 mL/min/1.73 m2). These results were attenuated (OR, 1.12; 95% CI, 1.01 to 1.25) with adjustment for residual effects of age and race, and eGFR was not associated significantly with a low Word List Recall score after multivariable adjustment (P ⫽ 0.23). When expressed by CKD category, there was a marginally significant difference in the multivariable odds of a low Word List Recall score for subjects with an eGFR less than 30 mL/min/1.73 m2 (OR, 2.58; 95% CI, 1.03 to 6.50) compared with subjects with a normal or near-normal GFR. Effect of Group Assignment Group assignment (hormone replacement therapy versus placebo) was not significantly
associated with any of the cognitive function test results. Subjects With and Without Diabetes Given that the MDRD GFR estimating equation was validated in a sample of persons with CKD unrelated to diabetes, we tested whether diabetes influenced the association between CKD and cognitive impairment. Diabetes did not influence the relation between GFR and abnormal results of tests of cognitive function (P ⬎ 0.40 for all interaction terms). Estimated Glomerular Filtration Rate Times Covariate Interactions There were no significant GFR times covariate interactions for the models tested. DISCUSSION
Prior studies of cognitive impairment and kidney disease have been largely limited to persons with advanced kidney failure. Several studies documented abnormalities in electrophysiologi-
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
cal and neurocognitive test results in uremic subjects not yet receiving dialysis and hemodialysis patients compared with medical patients with normal kidney function and healthy controls.18-20 In these early studies, uremic subjects showed up to 50% more impairment in alertness, motor speed, and executive function, although the magnitude of the reported differences depended on the control group. The National Cooperative Dialysis Study examined cognitive function during a clinical trial in which subjects were randomly assigned to hemodialysis with a low versus high blood urea nitrogen level target.3 The National Cooperative Dialysis Study noted electroencephalographic abnormalities, but no significant difference on the Choice Reaction Time test (a measure of psychomotor speed) in subjects assigned to the group with a high blood urea nitrogen level, suggesting a dialyzable substance might be associated with subclinical cognitive impairment in patients with uremia. Although it has been suggested that greater dialysis doses or high-flux dialysis may improve subtle neurocognitive deficits, this has not been shown consistently in small studies. Churchill et al21,22 reported no differences using a battery of cognitive measures in studies comparing patients with stable versus increased hemodialysis dose and comparing highflux versus standard hemodialysis. Aside from uremia, other metabolic abnormalities associated with ESRD and CKD may be responsible for the observed impairment in cognitive function. Anemia is an important risk factor for cognitive impairment in persons with ESRD. Electrophysiological indices and neurocognitive measures have improved after an increase in hemoglobin level with erythropoietin therapy.5,23,24 Marsh et al23 showed a 20% improvement in scores for the Trails B and Symbol Digit Modalities test (a measure of learning and psychomotor speed) after amelioration of anemia with erythropoietin and trends toward improvement in 2 other cognitive measures. There are no published studies of cognitive function in persons with less severe degrees of CKD. A recent study examined the association between acute renal failure after cardiac surgery and cognitive impairment and found no relation between change in serum creatinine or maximum postoperative serum creatinine level and development of cognitive impairment.25
73
In our study, kidney function was an independent predictor of cognitive function across several domains. Risk for global cognitive impairment was increased 5-fold in those with advanced CKD and was independent of age and other vascular disease risk factors, including diabetes and hypercholesterolemia. In addition, these analyses provide evidence that the risk for cognitive impairment associated with CKD is not a threshold phenomenon, but increases incrementally with decreasing kidney function. The risk for cognitive impairment increased approximately 15% to 25% for each 10-mL/min/1.73 m2 decrement in eGFR. One of the strengths of the approach taken in the HERS cohort is the use of multiple measures of cognitive function. We found an association between kidney function and performance on cognitive testing across several spheres of cognitive function, supporting the conclusion that there is a real association between CKD and cognition. Impairment of global function (Mini-Mental State Examination) has been shown previously in patients with ESRD.26 However, most investigators suspect that uremia leads to a specific pattern of cognitive deficits, rather than a global decrease in cognitive function. In this study, executive function, psychomotor skills, language, and attention were all impaired. We also found an association between eGFR and working and semantic memory (by the Verbal Fluency test) and immediate and short-term memory (by the Word List Memory and Recall tests), although these findings were attenuated after adjustment for sociodemographic factors. Whether CKD is causally related to cognitive impairment is uncertain. CKD is associated with other risk factors for cognitive impairment, including advanced age, diabetes, hypertension, and dyslipidemia, although the association between CKD and cognitive impairment remained significant after adjustment for many of these factors. Cognitive impairment in patients with CKD also may be mediated by retention of putative neurotoxins, including byproducts of nitrogen metabolism and parathyroid hormone. Chronic inflammation, detected by using such markers as C-reactive protein and proinflammatory cytokines, has been associated with the development of dementia27 and may be more common in patients with CKD than in the gen-
74
eral population. CKD may be a surrogate for other unmeasured metabolic abnormalities that mediate cognitive function. It is possible that our results may be confounded in part by the increase in depressive symptoms in women with a lower GFR. However, depression is unlikely to entirely explain the results, and adjustment for the presence of depressive symptoms with the Geriatric Depression Scale did not appreciably change the association between GFR and 3MS scores. The results of cognitive function tests were dependent on race. Several studies reported differences in cognitive test scores across ethnic groups, with such minority older adults as African Americans and Latinos scoring lower than whites.28 Some suggested that the validity of tests used to measure cognitive performance and screen for dementia may vary by population subgroup and have low specificity in non–middleclass white elders. Others reported that discrepancies on cognitive test scores may be attributed to early life or life course disadvantages in terms of education quality29 or meaningful differences in the presence and severity of diseases and conditions known to influence cognitive performance (eg, diabetes, vascular disease, and, perhaps, CKD). When we analyzed data from the 946 non–African-American subjects (93%) in HERS, the significant relation between CKD and cognitive impairment remained (eg, ORs of global cognitive impairment [3MS ⬍ 80], 2.3, 3.4, and 5.3 for eGFRs of 45 to 59, 30 to 44, and ⬍ 30 mL/min/1.73 m2, respectively). There are several important limitations to this study. These were cross-sectional analyses; thus, we cannot draw causal inference. A longitudinal study examining changes in cognitive and kidney function would be preferable, although serial evaluations of cognitive function were not performed in HERS. Hemoglobin and hematocrit values were not collected in the HERS cohort. Anemia is a known risk factor for cognitive dysfunction in persons with ESRD.5,23 Although individuals with mild to moderate CKD typically show lower hemoglobin concentrations,7 frank anemia (hemoglobin ⬍ 10 g/dL [100 g/L]) is rare, in contrast to patients with ESRD. Whether these smaller decrements in hemoglobin concentration influence cognitive function or test performance in patients with CKD is unknown. Most other metabolic
KURELLA ET AL
correlates of CKD were adjusted for in the analyses. Elevated parathyroid hormone levels are seen commonly in persons with a GFR less than 60 mL/min/1.73 m2 and were not measured, although the link between parathyroid hormone level and cognitive function is less well described.6 Number of teeth was used previously to adjust for socioeconomic status,30 although adjustment for income might have refined our models further. Although we adjusted for the presence of cardiovascular disease, we could not fully account for its severity. Because cognitive dysfunction may be related to atherosclerosis and patients with CKD may have more extensive atherosclerosis, the effects of CKD per se might be overestimated. Although the cognitive function tests used in this study have been used widely in the elderly, they may not be sufficiently sensitive to detect relatively small differences that may be of clinical significance to the general CKD population. Although we were able to explore 6 domains of cognitive function (global cognition, executive function, language, verbal fluency, and short- and longer-term memory), performing inference tests on 6 domains increases the likelihood of an ␣ (false-positive) error. Because the parameter estimates associated with eGFR had relatively broad CIs, 1 or more of the associations we described may have been spurious. Conversely, in multivariable analyses, we adjusted for several variables potentially “on the causal pathway” between CKD and cognitive impairment, particularly stroke, sodium level, and cholesterol level. In doing so, we may have lessened the significance of the eGFR and CKD category terms (see unadjusted and residual age- and race-adjusted results). The vast majority of the HERS cohort was white; less than 3% were of Asian, Latina, or Native American background. Therefore, we cannot generalize these findings to all ethnic groups. Moreover, the MDRD equation has not been validated in nonwhite non–African-American populations; therefore, eGFR may misclassify true GFR to a greater degree in Asian, Latina, and Native American women. Finally, because HERS enrollees were postmenopausal women with coronary artery disease, we cannot generalize the findings to men, younger women, or women without heart disease, although there is
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
no apparent reason to believe that the association between CKD and cognitive impairment would be dependent on the presence of heart disease. However, it is worth noting that more than 68,000 potential subjects were screened for enrollment in HERS. In summary, menopausal women with CKD have an increased prevalence of impairment in global cognition, executive function, language, and memory, even after adjusting for age, race, and additional confounding variables. Additional studies are required to confirm the associations described here and elucidate the responsible mechanism or mechanisms. This study provides additional evidence that CKD not requiring dialysis therapy may have important clinical consequences. ACKNOWLEDGMENT The authors acknowledge the expert assistance of Christine C. Ireland, MPH, and Feng Lin, PhD.
REFERENCES 1. Teschan PE, Ginn HE, Bourne JR, et al: Quantitative indices of clinical uremia. Kidney Int 15:676-697, 1979 2. English A, Savage RD, Britton PG, Ward MK, Kerr DN: Intellectual impairment in chronic renal failure. Br Med J 1:888-890, 1978 3. Teschan PE, Bourne JR, Reed RB, Ward JW: Electrophysiological and neurobehavioral responses to therapy: The National Cooperative Dialysis Study. Kidney Int Suppl 13:S58-S65, 1983 4. Kramer L, Madl C, Stockenhuber F, et al: Beneficial effect of renal transplantation on cognitive brain function. Kidney Int 49:833-838, 1996 5. Grimm G, Stockenhuber F, Schneeweiss B, Madl C, Zeitlhofer J, Schneider B: Improvement of brain function in hemodialysis patients treated with erythropoietin. Kidney Int 38:480-486, 1990 6. Garcia-Maldonado M, Patterson D, Smith ZM: PTH levels correlate with mental performance in CAPD. Adv Perit Dial 7:234-236, 1991 7. Hsu CY, Bates DW, Kuperman GJ, Curhan GC: Relationship between hematocrit and renal function in men and women. Kidney Int 59:725-731, 2001 8. Jones CA, McQuillan GM, Kusek JW, et al: Serum creatinine levels in the US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 32:992999, 1998 9. Grady D, Applegate W, Bush T, Furberg C, Riggs B, Hulley SB: Heart and Estrogen/progestin Replacement Study (HERS): Design, methods, and baseline characteristics. Control Clin Trials 19:314-335, 1998 10. Hulley S, Grady D, Bush T, et al: Randomized trial of estrogen plus progestin for secondary prevention of coronary heart disease in postmenopausal women. Heart and
75
Estrogen/progestin Replacement Study (HERS) Research Group. JAMA 280:605-613, 1998 11. Ebly EM, Hogan DB, Parhad IM: Cognitive impairment in the nondemented elderly. Results from the Canadian Study of Health and Aging. Arch Neurol 52:612-619, 1995 12. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461-470, 1999 13. Cockcroft DW, Gault MH: Prediction of creatinine clearance from serum creatinine. Nephron 16:31-41, 1976 14. National Kidney Foundation: K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, classification, and stratification. Am J Kidney Dis 39:S1S246, 2002(suppl 1) 15. Hanley JA, McNeil BJ: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29-36, 1982 16. Lemeshow S, Hosmer DW Jr: A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 115:92-106, 1982 17. Bravo G, Hebert R: Age- and education-specific reference values for the Mini-Mental and Modified Mini-Mental State Examinations derived from a non-demented elderly population. Int J Geriatr Psychiatry 12:1008-1018, 1997 18. Teschan PE: Electroencephalographic and other neurophysiological abnormalities in uremia. Kidney Int Suppl 2:S210-S216, 1975 19. Hart RP, Pederson JA, Czerwinski AW, Adams RL: Chronic renal failure, dialysis, and neuropsychological function. J Clin Neuropsychol 5:301-312, 1983 20. Souheaver GT, Ryan JJ, DeWolfe AS: Neuropsychological patterns in uremia. J Clin Psychol 38:490-496, 1982 21. Churchill DN, Wallace JE, Ludwin D, Beecroft ML, Taylor DW: A comparison of evaluative indices of quality of life and cognitive function in hemodialysis patients. Control Clin Trials 12:S159-S167, 1991 (suppl 4) 22. Churchill DN, Bird DR, Taylor DW, Beecroft ML, Gorman J, Wallace JE: Effect of high-flux hemodialysis on quality of life and neuropsychological function in chronic hemodialysis patients. Am J Nephrol 12:412-418, 1992 23. Marsh JT, Brown WS, Wolcott D, et al: rHuEPO treatment improves brain and cognitive function of anemic dialysis patients. Kidney Int 39:155-163, 1991 24. Pickett JL, Theberge DC, Brown WS, Schweitzer SU, Nissenson AR: Normalizing hematocrit in dialysis patients improves brain function. Am J Kidney Dis 33:1122-1130, 1999 25. Swaminathan M, McCreath BJ, Phillips-Bute BG, et al: Serum creatinine patterns in coronary bypass surgery patients with and without postoperative cognitive dysfunction. Anesth Analg 95:1-8, 2002 26. Sehgal AR, Grey SF, DeOreo PB, Whitehouse PJ: Prevalence, recognition, and implications of mental impairment among hemodialysis patients. Am J Kidney Dis 30:4149, 1997 27. Wood JA, Wood PL, Ryan R, et al: Cytokine indices in Alzheimer’s temporal cortex: No changes in mature IL-1 beta or IL-1RA but increases in the associated acute phase
76
proteins IL-6, alpha 2-macroglobulin and C-reactive protein. Brain Res 629:245-252, 1993 28. Manly JJ, Jacobs DM, Sano M, et al: Cognitive test performance among nondemented elderly African Americans and whites. Neurology 50:1238-1245, 1998 29. Albert SM, Teresi JA: Reading ability, education, and
KURELLA ET AL
cognitive status assessment among older adults in Harlem, New York City. Am J Public Health 89:95-97, 1999 30. Perneger TV, Whelton PK, Klag MJ: Race and endstage renal disease. Socioeconomic status and access to health care as mediating factors. Arch Intern Med 155:12011208, 1995
C
OGNITIVE IMPAIRMENT IS a wellrecognized manifestation of uremia. A variety of related deficits, including lethargy, reduced attention, memory impairment, concentration difficulty, sleep disturbances, and dementia, have been described in the end-stage renal disease (ESRD) population.1,2 Although the pathogenesis of cognitive impairment in patients with uremia has not been fully elucidated, cognitive function in patients with ESRD has improved with dialysis and renal transplantation.3,4 In addition to the effects of accelerated atherosclerosis, unresolved uremia, ane-
From the Department of Medicine, Divisions of Nephrology, Psychiatry, and Neurology, Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA; and Department of Medicine, Division of Cardiology, Emory University, Atlanta, GA. Received June 8, 2004; accepted in revised form August 2, 2004. Address reprint requests to Glenn M. Chertow, MD, Department of Medicine Research, University of California San Francisco, UCSF Laurel Heights Ste 430, 3333 California St, San Francisco, CA 94118-1211. E-mail: chertowg@ medicine.ucsf.edu © 2004 by the National Kidney Foundation, Inc. 0272-6386/04/4501-0007$30.00/0 doi:10.1053/j.ajkd.2004.08.044 66
mia, hyperparathyroidism, hyperprolactinemia, and other endocrinopathies, the adverse effects of drugs and retained metabolites might also contribute to cognitive impairment in the ESRD population.5,6 It is unknown whether less severe degrees of chronic kidney disease (CKD) also are associated with cognitive impairment. Although generally more subtle, many of the metabolic abnormalities observed in patients with ESRD also are present in patients with CKD.7 CKD is much more common than ESRD. Whereas approximately 300,000 persons in the United States require dialysis therapy, the Third National Health and Nutrition Examination Survey estimated the burden of CKD in the US population to be approximately 8.0 million persons.8 To examine whether CKD is a risk factor for cognitive impairment, we analyzed data collected for 1,015 women who were enrolled at 10 of the 20 Heart Estrogen/Progestin Replacement Study (HERS) clinical sites and underwent cognitive function testing at the end of the study. We hypothesized that cognitive function would vary directly according to glomerular filtration rate (GFR) and that severe CKD (defined as an estimated GFR [eGFR] ⬍30 mL/min/1.73 m2) would
American Journal of Kidney Diseases, Vol 45, No 1 (January), 2005: pp 66 –76
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
be associated with a significant risk for cognitive impairment.
67
tionnaire was used to adjust for symptoms of depression in selected analyses.
Statistical Analysis METHODS
Subjects Study participants, trial design, and primary outcomes of HERS have been described previously.9,10 There were no exclusion criteria based on kidney function. Study subjects were postmenopausal women younger than 80 years with established coronary artery disease who had not undergone hysterectomy. Subjects were randomly assigned to administration of a single tablet containing 0.625 mg of conjugated equine estrogen and 2.5 mg of medroxyprogesterone acetate or matching placebo. Cardiovascular events were the primary outcomes of interest. None of the women enrolled in HERS had a history of dementia or was taking medication for dementia at the time of enrollment.
Subject-Level Data Demographic characteristics, chronic health conditions, medication use, education level, and lifestyle factors were ascertained by means of questionnaire for all HERS participants at enrollment, and some information was updated during the study period. Laboratory values, including serum creatinine, blood urea nitrogen, and albumin, were measured in unfrozen serum at a single central laboratory using standard methods. For the purpose of these analyses, we incorporated laboratory values that coincided with the time cognitive function tests were performed, rather than baseline or other values.
Cognitive Function Tests A battery of 6 cognitive function tests was administered by trained staff at the end of year 4 for participants at 10 of the 20 HERS clinical sites. The Modified Mini-Mental State Examination (3MS) is a global assessment of cognitive function. Scores range from 1 to 100, with higher scores indicating better cognitive performance. A 3MS score less than 80 is used commonly as an indication of impairment.11 The Trail Making Test Part B (Trails B) assesses attention, concentration, psychomotor speed, and executive function (tasks that require organization, assimilation, and execution) by measuring the time required to connect a series of sequential numbered and lettered circles. Better performance is indicated by shorter completion times. The Modified Boston Naming test requires participants to name objects presented on a piece of paper. It assesses language skills, with higher scores denoting better function. For the Verbal Fluency test, subjects are asked to name as many animals as possible in 1 minute. The Verbal Fluency test is a test of working and semantic memory. The Word List Memory and Word List Recall tests evaluate immediate and short-term memory skills, respectively. For the Word List Memory test, participants are queried 3 times on the immediate recall of 10 standardized words (score range, 0 to 30). The Word List Recall test measures recall of the same words after a delay of 20 minutes. In addition, the score on the 15-item Geriatric Depression Scale self-administered ques-
Continuous variables are expressed as mean ⫾ SD or median with 10% and 90% ranges and compared with general linear models. Categorical variables are expressed as proportions and compared using chi-square test. We selected variables for analysis from the larger HERS database that might have confounded the relation between renal function and cognitive function (Table 1). These included demographic variables (eg, age, race), comorbid conditions (eg, diabetes mellitus, hypertension), concurrent laboratory values (eg, serum sodium, cholesterol), and cardiovascular events that were adjudicated during the study (eg, myocardial infarction, stroke). We used number of years of education, exercise patterns, ethanol and tobacco use, and number of teeth as proxies for socioeconomic and lifestyle variables. eGFR was calculated according to the published equation from the Modification of Diet in Renal Disease (MDRD) Study, incorporating age, black versus nonblack race, and serum creatinine, urea nitrogen, and albumin concentrations.12 To examine whether method of CKD classification affected study results, we also calculated estimated creatinine clearance using the Cockcroft-Gault equation.13 Results on all cognitive function tests were qualitatively similar when Cockcroft-Gault estimates were used; therefore, only models using MDRD eGFR are shown. Each of the 6 cognitive function tests was modeled individually. Model building proceeded as follows. First, we conducted unadjusted analyses examining the relation between eGFR and the test of interest. Second, we adjusted for “residual case mix”; age and race in this case. Finally, we adjusted for other confounding variables by using multivariable linear or logistic regression. For cognitive function variables that were normally or near-normally distributed, we used linear regression across the population range of eGFR. For non–normally distributed variables, we a priori dichotomized values for which there were established or otherwise obvious cutoffs. For instance, we used a 3MS score less than 80 and a Trails B score of 300 to dichotomize subjects for these 2 tests. Otherwise, we categorized subjects into quartiles based on data distribution and applied logistic regression to examine predictors of the “abnormal” quartile compared with all other quartiles. We included diabetes in all multivariable models because of the known association between diabetes and cognitive impairment. For other variable selection, we used backward elimination with criteria for acceptance set at P less than 0.05. After the initial multivariable models were fit, we manually added selected variables to evaluate for residual confounding. We predefined residual confounding as a change of 5% or more in the parameter estimate for GFR. We also tested for effect modification by using multiplicative interaction terms for selected variables, and for nonlinearity, by including a quadratic term for GFR. Models comparing cognitive function across the spectrum of eGFRs were primary. We also conducted companion analyses stratifying subjects by defined categories of eGFR. We used a modification of a classification scheme recently published by the National Kidney Foundation–Kidney Disease Outcomes Quality Ini-
68
KURELLA ET AL Table 1. Characteristics of Study Subjects Stratified by CKD Categories GFR (mL/min/1.73 m2)
Age (y) Race (% black) Height (cm) Weight (kg) Quetelet’s index (kg/m2) Diabetes* (%) Hypertension* (%) Tobacco use, current (%) Ethanol use† (%) Education (% graduate) Exercise‡ (%) No. of upper teeth No. of lower teeth Myocardial infarction§ (%) Congestive heart failure§ (%) Stroke§ (%) Stroke or transient ischemic attack§ (%) Coronary artery bypass graft§ (%) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Blood urea nitrogen (mg/dL) Creatinine (mg/dL) Sodium (mEq/L) Potassium (mEq/L) Bicarbonate (mEq/L) Calcium (mg/dL) Phosphorus (mg/dL) Albumin (g/dL) Glucose (mg/dL) Uric acid (mg/dL) Iron (g/dL) Total bilirubin (mg/dL) Cholesterol (mg/dL) Low-density lipoprotein cholesterol (mg/dL) High-density lipoprotein cholesterol (mg/dL) Triglycerides (mg/dL) Lipoprotein (a) (mg/dL)
ⱖ60 (n ⫽ 404)
45-59 (n ⫽ 448)
30-45 (n ⫽ 135)
⬍30 (n ⫽ 28)
P
65.2 ⫾ 6.3 8 159.6 ⫾ 6.1 72.4 ⫾ 15.4 28.3 ⫾ 5.6 15 53 14 11 45 36 7⫾6 8⫾6 7 3 1 2 6 136 ⫾ 18 74 ⫾ 9 13 ⫾ 4 0.9 ⫾ 0.1 140 ⫾ 3 4.3 ⫾ 0.3 24 ⫾ 3 9.2 ⫾ 0.3 3.6 ⫾ 0.5 4.0 ⫾ 0.2 107 ⫾ 33 4.2 ⫾ 1.2 90 ⫾ 34 0.7 ⫾ 0.2 210 ⫾ 39 125 ⫾ 36 53 ⫾ 13 161 ⫾ 76 24 ⫾ 23
67.3 ⫾ 6.1 5 159.2 ⫾ 5.9 70.6 ⫾ 14.2 27.8 ⫾ 5.1 16 56 11 8 39 33 7⫾6 8⫾5 9 7 3 7 7 135 ⫾ 19 72 ⫾ 9 17 ⫾ 4 1.1 ⫾ 0.1 140 ⫾ 2 4.3 ⫾ 0.4 24 ⫾ 2 9.3 ⫾ 0.3 3.6 ⫾ 0.4 3.9 ⫾ 0.2 112 ⫾ 43 4.7 ⫾ 1.2 86 ⫾ 32 0.7 ⫾ 0.2 211 ⫾ 39 125 ⫾ 36 51 ⫾ 13 176 ⫾ 79 22 ⫾ 23
69.5 ⫾ 5.9 4 159.2 ⫾ 6.4 74.1 ⫾ 15.8 29.3 ⫾ 6.0 35 66 10 4 37 26 7⫾6 7⫾6 9 12 5 10 8 137 ⫾ 23 71 ⫾ 9 24 ⫾ 6 1.4 ⫾ 0.1 140 ⫾ 3 4.4 ⫾ 0.4 24 ⫾ 3 9.3 ⫾ 0.3 3.7 ⫾ 0.4 3.9 ⫾ 0.2 122 ⫾ 57 5.5 ⫾ 1.4 82 ⫾ 29 0.7 ⫾ 0.2 216 ⫾ 35 126 ⫾ 40 51 ⫾ 15 181 ⫾ 88 26 ⫾ 25
66.6 ⫾ 6.9 29 161.2 ⫾ 6.9 78.3 ⫾ 20.2 30.1 ⫾ 7.4 57 67 0 0 32 14 5⫾6 7⫾5 11 25 11 18 7 136 ⫾ 19 70 ⫾ 9 48 ⫾ 15 2.9 ⫾ 1.7 140 ⫾ 3 4.4 ⫾ 0.8 23 ⫾ 4 9.1 ⫾ 0.4 4.0 ⫾ 0.6 3.7 ⫾ 0.3 118 ⫾ 48 6.9 ⫾ 1.7 77 ⫾ 33 0.7 ⫾ 0.2 202 ⫾ 46 116 ⫾ 35 50 ⫾ 16 180 ⫾ 97 26 ⫾ 30
⬍0.0001 0.81 0.82 0.61 0.41 ⬍0.0001 0.006 0.02 0.003 0.03 0.006 0.67 0.77 0.17 ⬍0.0001 0.0002 ⬍0.0001 0.47 0.57 0.0008 ⬍0.0001 ⬍0.0001 0.38 ⬍0.0001 0.006 0.26 0.0002 ⬍0.0001 0.002 ⬍0.0001 0.01 0.63 0.51 0.72 0.02 0.005 0.95
NOTE. For continuous variables, P for trend by GFR. To convert blood urea nitrogen in mg/dL to mmol/L, multiply by 0.357; creatinine in mg/dL to mol/L, multiply by 88.4; calcium in mg/dL to mmol/L, multiply by 0.25; phosphorus in mg/dL to mmol/L, multiply by 0.323; albumin in g/dL to g/L, multiply by 10; glucose in mg/dL to mmol/L, multiply by 0.0555; uric acid in mg/dL to mol/L, multiply by 59.48; iron in g/dL to mol/L, multiply by 0.179; bilirubin in mg/dL to mol/L, multiply by 17.1; cholesterol in mg/dL to mmol/L, multiply by 0.0259; low-density lipoprotein cholesterol in mg/dL to mmol/L, multiply by 0.0259; high-density lipoprotein cholesterol in mg/dL to mmol/L, multiply by 0.0259; triglycerides in mg/dL to mmol/L, multiply by 0.0113; lipoprotein (a) in mg/dL to mol/L, multiply by 0.0357. *By history. †Seven or more drinks per week. ‡Three or more times per week. §Adjudicated during study.
tiative.14 Given the relatively large number of subjects with an eGFR between 30 and 59 mL/min/1.73 m2 (stage III CKD) and the relatively small number of subjects with an eGFR less than 30 mL/min/1.73 m2, we split the stage III
CKD category into 2 subcategories (30 to 44 and 45 to 59 mL/min/1.73 m2) to evaluate for threshold effects. In general, the descriptor “CKD” refers to all women with an eGFR less than 60 mL/min/1.73 m2.
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
69
Table 2. Cognitive Function Test Results by CKD Category GFR (mL/min/1.73 m2)
3MS Trails B Boston Naming Verbal Fluency Word List Memory Word List Recall
ⱖ60
45-59
30-44
⬍30
96 (88-99) 130 (59-275) 15 (13-15) 16 (11-23) 21 (14-26) 7 (3-9)
95 (85-99) 131 (60-300) 14 (12-15) 16 (10-23) 20 (14-25) 7 (4-9)
93 (82-99) 157 (13-300) 14 (11-15) 16 (10-22) 19 (11-23) 6 (1-9)
90 (74-98) 183 (14-300) 13 (8-15) 14.5 (10-22) 18.5 (9-24) 6 (0-9)
NOTE. Values expressed as median (10% to 90% range).
For logistic regression models, we used the area under the receiver operating characteristic (ROC) curves to assess model discrimination.15 The Hosmer-Lemeshow goodnessof-fit test was used to assess model calibration.16 We considered the extent of variation explained and Mallow’s Cp in determining optimal linear regression models. For all analyses, 2-tailed P less than 0.05 is considered significant. Analyses were conducted using SAS, version 8.2 (SAS Institute, Cary, NC).
RESULTS
Baseline Characteristics One thousand sixty-three HERS enrollees underwent cognitive function testing. Forty-eight women (4.5%) did not have coincident laboratory test results, and GFR could not be estimated. Mean age was 66.7 ⫾ 6.4 years. Mean eGFR (n ⫽ 1,015) was 57.3 ⫾ 13.9 mL/min/1.73 m2, and mean estimated creatinine clearance was 58.9 ⫾ 19.7 mL/min (42.2 ⫾ 11.1 mL/min incorporating ideal, rather than actual, body weight). Women with no laboratory values were significantly older and had fewer years of education, fewer teeth, and significantly worse scores on all cognitive function tests except the Trails B (data not shown). There were no missing laboratory data elements among the 1,015 subjects with coincident laboratory data. Baseline characteristics of study subjects are listed in Table 1. Compared with women with an eGFR of 60 mL/min/1.73 m2 or greater, women with CKD (eGFR ⬍ 60 mL/min/1.73 m2) were on average older and more likely to have diabetes mellitus, hypertension, congestive heart failure, and stroke. Women with CKD also were less likely to have graduated high school and less likely to exercise. Table 2 lists median and 10% to 90% limits for the 6 tests of cognitive function within each of the CKD categories. Cognitive
function scores generally were higher for HERS participants compared with age- and educationmatched population norms. For example, HERS subjects with an eGFR of 60 mL/min/1.73 m2 or greater had 3MS scores 4 points higher than normative values for women aged between 65 and 69 years with a high school education. Women with an eGFR less than 30 mL/min/1.73 m2 had 3MS scores approximately 2 points lower than published norms.17 Association of Glomerular Filtration Rate With Cognitive Function Test Results Modified Mini-Mental Status Examination. Median score on the 3MS was 95; scores ranged from 53 to 100. In the entire cohort, 5% of women had global cognitive impairment, defined as a 3MS score less than 80. As shown in Table 3, there was a significant association between eGFR and global cognitive impairment with adjustment for the residual effects of age, race, education, adjudicated stroke or transient ischemic attack, tobacco use, and serum cholesterol and sodium concentrations. There was a 27% increase in risk for global cognitive impairment per each 10-mL/min/1.73 m2 decrement in GFR, and persons with severe CKD were 5-fold more likely to have low 3MS scores than those with a normal or near-normal GFR. Because depression may confound global cognitive function and CKD is associated with depression, we conducted an additional analysis in which we also adjusted for the Geriatric Depression Scale. The effect estimates were changed only slightly (25% increase in risk/10-mL/min/ 1.73 m2 decrement in GFR, and 4.5-fold increase for advanced CKD), suggesting that cognitive
70
KURELLA ET AL Table 3. GFR and CKD Categories and Cognitive Impairment by 3MS Score Less Than 80
GFR (per 10 mL/min/1.73 m2) Age (y) Black race Diabetes Education (y) Sodium (mEq/L) Stroke or transient ischemic attack Tobacco use, current Cholesterol (10 mg/dL) CKD GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Sodium (mEq/L) Stroke or transient ischemic attack Tobacco use, current Cholesterol (10 mg/dL)
Unadjusted OR (95% CI)
Residual Age- and RaceAdjusted OR (95% CI)
Full Model OR (95% CI)
1.45 (1.18-1.75) — — — — — — — —
1.32 (1.05-1.61) 1.13 (1.07-1.20) 5.74 (2.64-12.5) — — — — — —
1.27* (1.01-1.59) 1.15* (1.08-1.22) 5.76* (2.46-13.5) 0.69* (0.30-1.60) 0.82* (0.73-0.91) 0.88* (0.79-0.99) 4.10* (1.73-9.74) 2.42* (1.00-5.82) 1.07* (1.00-1.15)
2.41 (1.15-5.06) 3.19 (1.30-7.84) 8.84 (2.78-28.1) — — — — — — — —
2.16 (1.00-4.64) 2.31 (0.90-5.94) 5.58 (1.61-19.4) 1.13 (1.07-1.20) 5.51 (2.48-12.2) — — — — — —
1.91† (0.86-4.23) 1.80† (0.65-4.97) 5.01† (1.27-19.7) 1.15† (1.09-1.23) 5.21† (2.14-12.7) 0.73† (0.31-1.68) 0.82† (0.73-0.91) 0.89† (0.80-0.99) 3.95† (1.66-9.36) 2.46† (1.02-5.93) 1.08† (1.00-1.15)
NOTE. Values expressed as OR (95% CI). OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. To convert cholesterol in mg/dL to mmol/L, multiply by 0.0259. *Area under ROC curve ⫽ 0.84, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.83 †Area under ROC curve ⫽ 0.84, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.50, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 2.69 (1.00 to 7.27), 2.74 (0.95 to 7.88) and 5.57 (1.42 to 27.9).
impairment in patients with CKD was not the result of a depressed affect. Trail Making Test Part B (attention, concentration, psychomotor speed, and executive function). Thirty-three subjects (3%) were recorded as having a zero score (ie, 0 seconds to complete the task) on Trails B and therefore were excluded. Scores on the Trails B ranged from 10 to 300 seconds. One hundred fifteen subjects (12%) had impairment on Trails B (score, 300 seconds). The odds of scoring poorly on Trails B were increased with lower eGFR, even with multivariable adjustment (Table 4). The proportion of subjects with abnormal 3MS (P ⬍ 0.0001) and Trails B scores (P ⫽ 0.001) was associated significantly with CKD category (Fig 1). Modified Boston Naming. Scores on the Boston Naming test ranged from 0 to 15. There were 768 subjects (76%) who achieved scores of 14 or 15. The odds of scoring poorly on the Modified
Boston Naming test also increased significantly with lower eGFR (Table 5). Verbal Fluency. Mean Verbal Fluency score was 16.2 ⫾ 4.9 words (median, 16 words; range, 0 to 37 words), and scores were normally distributed. eGFR was associated significantly with verbal fluency on unadjusted analyses (0.25 words/10 mL/min/1.73 m2; P ⫽ 0.02). However, the GFR–verbal fluency association was no longer statistically significant after adjusting for residual effects of age and race (P ⫽ 0.26) or after multivariable adjustment (P ⫽ 0.96). Word List Memory (immediate) and Word List Recall (delayed). Scores on the Word List Memory test were normally distributed. eGFR was related significantly to the score on Word List Memory (0.54 words/10 mL/min/1.73 m2; P ⬍ 0.0001). Expressed by CKD category, mean numbers of words were 20, 20, 18, and 17 for subjects with eGFRs of 60 or greater, 45
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
71
Table 4. GFR and CKD Categories and Cognitive Impairment by Trails B (score, 300)
GFR (per 10 mL/min/1.73 m2) Age (y) Black race Diabetes Education (y) Weight (kg) Lower teeth (tooth) Upper teeth (tooth) Cholesterol (10 mg/dL) CKD category GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Weight (kg) Lower teeth (tooth) Upper teeth (tooth) Cholesterol (10 mg/dL)
Unadjusted OR (95% CI)
Residual Age- and Race-Adjusted OR (95% CI)
Full Model OR (95% CI)
1.33 (1.16-1.54) — — — — — — — —
1.25 (1.08-1.45) 1.10 (1.06-1.14) 5.78 (3.18-10.5) — — — — — —
1.19* (1.01-1.39) 1.09* (1.05-1.13) 6.14* (3.20-11.8) 1.84* (1.09-3.81) ⫺0.83* (0.77-0.91) 0.98* (0.96-0.99) 0.90* (0.83-0.98) 1.10* (1.02-1.18) 1.06* (1.00-1.11)
1.35 (0.86-2.13) 2.05 (1.16-3.64) 3.52 (1.40-8.85) — — — — — — — —
1.26 (0.79-2.03) 1.70 (0.91-3.09) 2.23 (0.82-6.09) 1.09 (1.05-1.13) 5.96 (3.29-10.8) — — — — — —
1.10† (0.67-1.80) 1.21† (0.63-2.34) 2.24† (0.77-6.51) 1.10† (1.05-1.14) 5.72† (2.96-11.0) 1.92† (1.14-3.26) 0.83† (0.77-0.91) 0.98† (0.97-0.99) 0.90† (0.83-0.97) 1.10† (1.02-1.19) 1.06† (1.01-1.12)
NOTE. To convert cholesterol in mg/dL to mmol/L, multiply by 0.0259. OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. *Area under ROC curve ⫽ 0.79, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.22 †Area under ROC curve ⫽ 0.79, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.22, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 2.02 (1.14 to 3.58), 2.02 (1.07 to 3.82), and 4.08 (1.52 to 10.9).
to 59, 30 to 44, and less than 30 mL/min/1.73 m2. The relation between eGFR and Word List Memory test score remained significant after adjustment for residual effects of age and race and the significant effects of education, to-
Fig 1. Percentage of abnormal study results on the 3MS (score < 80) and Trails B (score, 300) by categories of CKD. Chi-squared test for trend across CKD categories, 3MS (P < 0.0001) and Trails B (P ⴝ 0.01).
bacco use, diabetes, stroke, and systolic and diastolic blood pressure. The multivariable linear effect estimate was 0.25 words/10 mL/min/ 1.73 m2 of eGFR (P ⫽ 0.02). In other words, even after multivariable adjustment, subjects
72
KURELLA ET AL Table 5. GFR and CKD Categories and Cognitive Impairment by Boston Naming (13 or fewer)
GFR (per 10 mL/min/1.73 m2) Age (per year) Black race Diabetes Education (per year) Body weight (per kg) Sodium (per mEq/L) CKD category GFR (mL/min/1.73 m2) 45-59 30-44 ⬍30 Age (y) Black race Diabetes Education (y) Body weight (kg) Sodium (mEq/L)
Unadjusted OR (95% CI)
Residual Age- and Race-Adjusted OR (95% CI)
Full Model OR (95% CI)
1.23 (1.10-1.37) — — — — — —
1.18 (1.06-1.33) 1.06 (1.03-1.09) 5.42 (3.21-9.18) — — — —
1.16* (1.03-1.31) 1.06* (1.03-1.09) 4.91* (2.78-8.68) 1.18* (0.79-1.79) 0.80* (0.75-0.86) 0.98* (0.97-0.99) 1.07* (1.01-1.14)
1.69 (1.21-2.35) 1.94 (1.24-3.04) 5.32 (2.43-11.7) — — — — — —
1.66 (1.17-2.34) 1.74 (1.08-2.79) 4.03 (1.75-9.28) 1.06 (1.03-1.09) 5.22 (3.06-8.90) — — — —
1.55† (1.09-2.22) 1.43† (0.86-2.37) 4.02† (1.66-9.76) 1.06† (1.03-1.09) 4.68† (2.62-8.34) 1.18† (0.78-1.79) 0.80† (0.75-0.86) 0.98† (0.97-0.99) 1.08† (1.01-1.15)
NOTE. OR and 95% CI estimates for age and race represent residual effect estimates after accounting for the contributions of age and race within the GFR estimate. The OR associated with age and race should not be interpreted as valid effect estimates. There were no significant GFR times covariate interactions. *Area under ROC curve ⫽ 0.72, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.12. †Area under ROC curve ⫽ 0.73, Hosmer-Lemeshow goodness-of-fit chi-squared P ⫽ 0.52, corresponding multivariable OR and 95% CI for Cockcroft-Gault creatinine clearance categories of 45 to 59, 30 to 44, and less than 30 mL/min were 1.43 (0.97 to 2.11), 1.54 (0.98 to 2.42), and 3.11 (1.34 to 7.26). Referent category is estimated GFR of 60 mL/min/1.73 m2.
with a GFR less than 30 mL/min/1.73 m2 were able to recall 2 fewer words than subjects with a normal or near-normal GFR. The odds of achieving a low score (ⱕ4) on the Word List Recall test was significantly related to eGFR (odds ratio [OR], 1.23; 95% confidence interval [CI], 1.11 to 1.37/10 mL/min/1.73 m2). These results were attenuated (OR, 1.12; 95% CI, 1.01 to 1.25) with adjustment for residual effects of age and race, and eGFR was not associated significantly with a low Word List Recall score after multivariable adjustment (P ⫽ 0.23). When expressed by CKD category, there was a marginally significant difference in the multivariable odds of a low Word List Recall score for subjects with an eGFR less than 30 mL/min/1.73 m2 (OR, 2.58; 95% CI, 1.03 to 6.50) compared with subjects with a normal or near-normal GFR. Effect of Group Assignment Group assignment (hormone replacement therapy versus placebo) was not significantly
associated with any of the cognitive function test results. Subjects With and Without Diabetes Given that the MDRD GFR estimating equation was validated in a sample of persons with CKD unrelated to diabetes, we tested whether diabetes influenced the association between CKD and cognitive impairment. Diabetes did not influence the relation between GFR and abnormal results of tests of cognitive function (P ⬎ 0.40 for all interaction terms). Estimated Glomerular Filtration Rate Times Covariate Interactions There were no significant GFR times covariate interactions for the models tested. DISCUSSION
Prior studies of cognitive impairment and kidney disease have been largely limited to persons with advanced kidney failure. Several studies documented abnormalities in electrophysiologi-
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
cal and neurocognitive test results in uremic subjects not yet receiving dialysis and hemodialysis patients compared with medical patients with normal kidney function and healthy controls.18-20 In these early studies, uremic subjects showed up to 50% more impairment in alertness, motor speed, and executive function, although the magnitude of the reported differences depended on the control group. The National Cooperative Dialysis Study examined cognitive function during a clinical trial in which subjects were randomly assigned to hemodialysis with a low versus high blood urea nitrogen level target.3 The National Cooperative Dialysis Study noted electroencephalographic abnormalities, but no significant difference on the Choice Reaction Time test (a measure of psychomotor speed) in subjects assigned to the group with a high blood urea nitrogen level, suggesting a dialyzable substance might be associated with subclinical cognitive impairment in patients with uremia. Although it has been suggested that greater dialysis doses or high-flux dialysis may improve subtle neurocognitive deficits, this has not been shown consistently in small studies. Churchill et al21,22 reported no differences using a battery of cognitive measures in studies comparing patients with stable versus increased hemodialysis dose and comparing highflux versus standard hemodialysis. Aside from uremia, other metabolic abnormalities associated with ESRD and CKD may be responsible for the observed impairment in cognitive function. Anemia is an important risk factor for cognitive impairment in persons with ESRD. Electrophysiological indices and neurocognitive measures have improved after an increase in hemoglobin level with erythropoietin therapy.5,23,24 Marsh et al23 showed a 20% improvement in scores for the Trails B and Symbol Digit Modalities test (a measure of learning and psychomotor speed) after amelioration of anemia with erythropoietin and trends toward improvement in 2 other cognitive measures. There are no published studies of cognitive function in persons with less severe degrees of CKD. A recent study examined the association between acute renal failure after cardiac surgery and cognitive impairment and found no relation between change in serum creatinine or maximum postoperative serum creatinine level and development of cognitive impairment.25
73
In our study, kidney function was an independent predictor of cognitive function across several domains. Risk for global cognitive impairment was increased 5-fold in those with advanced CKD and was independent of age and other vascular disease risk factors, including diabetes and hypercholesterolemia. In addition, these analyses provide evidence that the risk for cognitive impairment associated with CKD is not a threshold phenomenon, but increases incrementally with decreasing kidney function. The risk for cognitive impairment increased approximately 15% to 25% for each 10-mL/min/1.73 m2 decrement in eGFR. One of the strengths of the approach taken in the HERS cohort is the use of multiple measures of cognitive function. We found an association between kidney function and performance on cognitive testing across several spheres of cognitive function, supporting the conclusion that there is a real association between CKD and cognition. Impairment of global function (Mini-Mental State Examination) has been shown previously in patients with ESRD.26 However, most investigators suspect that uremia leads to a specific pattern of cognitive deficits, rather than a global decrease in cognitive function. In this study, executive function, psychomotor skills, language, and attention were all impaired. We also found an association between eGFR and working and semantic memory (by the Verbal Fluency test) and immediate and short-term memory (by the Word List Memory and Recall tests), although these findings were attenuated after adjustment for sociodemographic factors. Whether CKD is causally related to cognitive impairment is uncertain. CKD is associated with other risk factors for cognitive impairment, including advanced age, diabetes, hypertension, and dyslipidemia, although the association between CKD and cognitive impairment remained significant after adjustment for many of these factors. Cognitive impairment in patients with CKD also may be mediated by retention of putative neurotoxins, including byproducts of nitrogen metabolism and parathyroid hormone. Chronic inflammation, detected by using such markers as C-reactive protein and proinflammatory cytokines, has been associated with the development of dementia27 and may be more common in patients with CKD than in the gen-
74
eral population. CKD may be a surrogate for other unmeasured metabolic abnormalities that mediate cognitive function. It is possible that our results may be confounded in part by the increase in depressive symptoms in women with a lower GFR. However, depression is unlikely to entirely explain the results, and adjustment for the presence of depressive symptoms with the Geriatric Depression Scale did not appreciably change the association between GFR and 3MS scores. The results of cognitive function tests were dependent on race. Several studies reported differences in cognitive test scores across ethnic groups, with such minority older adults as African Americans and Latinos scoring lower than whites.28 Some suggested that the validity of tests used to measure cognitive performance and screen for dementia may vary by population subgroup and have low specificity in non–middleclass white elders. Others reported that discrepancies on cognitive test scores may be attributed to early life or life course disadvantages in terms of education quality29 or meaningful differences in the presence and severity of diseases and conditions known to influence cognitive performance (eg, diabetes, vascular disease, and, perhaps, CKD). When we analyzed data from the 946 non–African-American subjects (93%) in HERS, the significant relation between CKD and cognitive impairment remained (eg, ORs of global cognitive impairment [3MS ⬍ 80], 2.3, 3.4, and 5.3 for eGFRs of 45 to 59, 30 to 44, and ⬍ 30 mL/min/1.73 m2, respectively). There are several important limitations to this study. These were cross-sectional analyses; thus, we cannot draw causal inference. A longitudinal study examining changes in cognitive and kidney function would be preferable, although serial evaluations of cognitive function were not performed in HERS. Hemoglobin and hematocrit values were not collected in the HERS cohort. Anemia is a known risk factor for cognitive dysfunction in persons with ESRD.5,23 Although individuals with mild to moderate CKD typically show lower hemoglobin concentrations,7 frank anemia (hemoglobin ⬍ 10 g/dL [100 g/L]) is rare, in contrast to patients with ESRD. Whether these smaller decrements in hemoglobin concentration influence cognitive function or test performance in patients with CKD is unknown. Most other metabolic
KURELLA ET AL
correlates of CKD were adjusted for in the analyses. Elevated parathyroid hormone levels are seen commonly in persons with a GFR less than 60 mL/min/1.73 m2 and were not measured, although the link between parathyroid hormone level and cognitive function is less well described.6 Number of teeth was used previously to adjust for socioeconomic status,30 although adjustment for income might have refined our models further. Although we adjusted for the presence of cardiovascular disease, we could not fully account for its severity. Because cognitive dysfunction may be related to atherosclerosis and patients with CKD may have more extensive atherosclerosis, the effects of CKD per se might be overestimated. Although the cognitive function tests used in this study have been used widely in the elderly, they may not be sufficiently sensitive to detect relatively small differences that may be of clinical significance to the general CKD population. Although we were able to explore 6 domains of cognitive function (global cognition, executive function, language, verbal fluency, and short- and longer-term memory), performing inference tests on 6 domains increases the likelihood of an ␣ (false-positive) error. Because the parameter estimates associated with eGFR had relatively broad CIs, 1 or more of the associations we described may have been spurious. Conversely, in multivariable analyses, we adjusted for several variables potentially “on the causal pathway” between CKD and cognitive impairment, particularly stroke, sodium level, and cholesterol level. In doing so, we may have lessened the significance of the eGFR and CKD category terms (see unadjusted and residual age- and race-adjusted results). The vast majority of the HERS cohort was white; less than 3% were of Asian, Latina, or Native American background. Therefore, we cannot generalize these findings to all ethnic groups. Moreover, the MDRD equation has not been validated in nonwhite non–African-American populations; therefore, eGFR may misclassify true GFR to a greater degree in Asian, Latina, and Native American women. Finally, because HERS enrollees were postmenopausal women with coronary artery disease, we cannot generalize the findings to men, younger women, or women without heart disease, although there is
CKD AND COGNITIVE IMPAIRMENT IN WOMEN
no apparent reason to believe that the association between CKD and cognitive impairment would be dependent on the presence of heart disease. However, it is worth noting that more than 68,000 potential subjects were screened for enrollment in HERS. In summary, menopausal women with CKD have an increased prevalence of impairment in global cognition, executive function, language, and memory, even after adjusting for age, race, and additional confounding variables. Additional studies are required to confirm the associations described here and elucidate the responsible mechanism or mechanisms. This study provides additional evidence that CKD not requiring dialysis therapy may have important clinical consequences. ACKNOWLEDGMENT The authors acknowledge the expert assistance of Christine C. Ireland, MPH, and Feng Lin, PhD.
REFERENCES 1. Teschan PE, Ginn HE, Bourne JR, et al: Quantitative indices of clinical uremia. Kidney Int 15:676-697, 1979 2. English A, Savage RD, Britton PG, Ward MK, Kerr DN: Intellectual impairment in chronic renal failure. Br Med J 1:888-890, 1978 3. Teschan PE, Bourne JR, Reed RB, Ward JW: Electrophysiological and neurobehavioral responses to therapy: The National Cooperative Dialysis Study. Kidney Int Suppl 13:S58-S65, 1983 4. Kramer L, Madl C, Stockenhuber F, et al: Beneficial effect of renal transplantation on cognitive brain function. Kidney Int 49:833-838, 1996 5. Grimm G, Stockenhuber F, Schneeweiss B, Madl C, Zeitlhofer J, Schneider B: Improvement of brain function in hemodialysis patients treated with erythropoietin. Kidney Int 38:480-486, 1990 6. Garcia-Maldonado M, Patterson D, Smith ZM: PTH levels correlate with mental performance in CAPD. Adv Perit Dial 7:234-236, 1991 7. Hsu CY, Bates DW, Kuperman GJ, Curhan GC: Relationship between hematocrit and renal function in men and women. Kidney Int 59:725-731, 2001 8. Jones CA, McQuillan GM, Kusek JW, et al: Serum creatinine levels in the US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis 32:992999, 1998 9. Grady D, Applegate W, Bush T, Furberg C, Riggs B, Hulley SB: Heart and Estrogen/progestin Replacement Study (HERS): Design, methods, and baseline characteristics. Control Clin Trials 19:314-335, 1998 10. Hulley S, Grady D, Bush T, et al: Randomized trial of estrogen plus progestin for secondary prevention of coronary heart disease in postmenopausal women. Heart and
75
Estrogen/progestin Replacement Study (HERS) Research Group. JAMA 280:605-613, 1998 11. Ebly EM, Hogan DB, Parhad IM: Cognitive impairment in the nondemented elderly. Results from the Canadian Study of Health and Aging. Arch Neurol 52:612-619, 1995 12. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 130:461-470, 1999 13. Cockcroft DW, Gault MH: Prediction of creatinine clearance from serum creatinine. Nephron 16:31-41, 1976 14. National Kidney Foundation: K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, classification, and stratification. Am J Kidney Dis 39:S1S246, 2002(suppl 1) 15. Hanley JA, McNeil BJ: The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29-36, 1982 16. Lemeshow S, Hosmer DW Jr: A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 115:92-106, 1982 17. Bravo G, Hebert R: Age- and education-specific reference values for the Mini-Mental and Modified Mini-Mental State Examinations derived from a non-demented elderly population. Int J Geriatr Psychiatry 12:1008-1018, 1997 18. Teschan PE: Electroencephalographic and other neurophysiological abnormalities in uremia. Kidney Int Suppl 2:S210-S216, 1975 19. Hart RP, Pederson JA, Czerwinski AW, Adams RL: Chronic renal failure, dialysis, and neuropsychological function. J Clin Neuropsychol 5:301-312, 1983 20. Souheaver GT, Ryan JJ, DeWolfe AS: Neuropsychological patterns in uremia. J Clin Psychol 38:490-496, 1982 21. Churchill DN, Wallace JE, Ludwin D, Beecroft ML, Taylor DW: A comparison of evaluative indices of quality of life and cognitive function in hemodialysis patients. Control Clin Trials 12:S159-S167, 1991 (suppl 4) 22. Churchill DN, Bird DR, Taylor DW, Beecroft ML, Gorman J, Wallace JE: Effect of high-flux hemodialysis on quality of life and neuropsychological function in chronic hemodialysis patients. Am J Nephrol 12:412-418, 1992 23. Marsh JT, Brown WS, Wolcott D, et al: rHuEPO treatment improves brain and cognitive function of anemic dialysis patients. Kidney Int 39:155-163, 1991 24. Pickett JL, Theberge DC, Brown WS, Schweitzer SU, Nissenson AR: Normalizing hematocrit in dialysis patients improves brain function. Am J Kidney Dis 33:1122-1130, 1999 25. Swaminathan M, McCreath BJ, Phillips-Bute BG, et al: Serum creatinine patterns in coronary bypass surgery patients with and without postoperative cognitive dysfunction. Anesth Analg 95:1-8, 2002 26. Sehgal AR, Grey SF, DeOreo PB, Whitehouse PJ: Prevalence, recognition, and implications of mental impairment among hemodialysis patients. Am J Kidney Dis 30:4149, 1997 27. Wood JA, Wood PL, Ryan R, et al: Cytokine indices in Alzheimer’s temporal cortex: No changes in mature IL-1 beta or IL-1RA but increases in the associated acute phase
76
proteins IL-6, alpha 2-macroglobulin and C-reactive protein. Brain Res 629:245-252, 1993 28. Manly JJ, Jacobs DM, Sano M, et al: Cognitive test performance among nondemented elderly African Americans and whites. Neurology 50:1238-1245, 1998 29. Albert SM, Teresi JA: Reading ability, education, and
KURELLA ET AL
cognitive status assessment among older adults in Harlem, New York City. Am J Public Health 89:95-97, 1999 30. Perneger TV, Whelton PK, Klag MJ: Race and endstage renal disease. Socioeconomic status and access to health care as mediating factors. Arch Intern Med 155:12011208, 1995