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Nocturia, Sleep and Daytime Function in Stable Heart Failure
Journal of Cardiac Failure, Volume 18, Issue 7, 2012, pages 569 - 575
The aim of this study was to evaluate nocturia severity and nocturia-related differences in sleep, daytime symptoms and functional performance among patients with stable heart failure (HF).
Methods and Results
In this cross-sectional observational study, we recruited 173 patients [mean age 60.3 ± 16.8 years; female n = 60 (35%); mean left ventricular ejection fraction 32 ± 14.6%] with stable chronic HF from HF disease management programs in the northeastern United States. Participants reported nocturia and completed a 6-minute walk test (6MWT), 1 night of ambulatory polysomnography, and the SF-36 Medical Outcomes Study, Epworth Sleepiness, Pittsburgh Sleep Quality Index, Multidimensional Assessment of Fatigue, and Centers for the Epidemiological Studies of Depression scales. Participants reported 0 (n = 30; 17.3%), 1–2 (n = 87; 50.2%), and ≥3 (n = 56; 32.4%) nightly episodes of nocturia. There were decreases in sleep duration and efficiency, REM and stage 3–4 sleep, physical function, and 6MWT distance and increases in the percentage of wake time after sleep onset, insomnia symptoms, fatigue, and sleepiness across levels of nocturia severity.
Nocturia is common, severe, and closely associated with decrements in sleep and functional performance and increases in fatigue and sleepiness in patients with stable HF.
Key Words: Heart failure, insomnia, nocturia, sleep, fatigue, physical function, quality of life.
Nocturia is common among patients with heart failure (HF) and is often a reported cause of poor sleep.1, 2, and 3 In the general population, nocturia was closely associated with poor sleep quality,4, 5, 6, and 7 a 75% increased risk of insomnia, and a 71% increased risk of poor sleep in men and women between the ages of 55 and 84 years. 8
Although it is often presumed that nocturia leads to disturbed sleep, it is also plausible that awakening results in the perception of the need to void. 8 Awakenings may result from a host of environmental, social, psychologic, and health-related reasons, including sleep-disordered breathing (SDB), that are closely associated with poor sleep architecture and decrements in sleep continuity. 9 Resulting decreases in slow-wave sleep may lead to decreased secretion of renin and aldosterone, 10 and decreased REM sleep may lead to increased urine flow and decreased osmolality. 11 These factors may lead to nocturia.
SDB, including Cheyne Stokes breathing/central sleep apnea and obstructive sleep apnea, is common in patients with HF. 12 Obstructive sleep apnea is associated with elevated intrathoracic pressure which leads to increased atrial natrurietric peptide, and central sleep apnea is usually associated with decompensated HF 13 ; both may lead to nocturia. Although studies have shown that obstructive sleep apnea is associated with nocturia in the general population,13, 14, and 15 a recent study demonstrated that nocturia and SDB were not related in HF patients. 16
Numerous studies have demonstrated that nocturia is associated with daytime symptoms (fatigue, depression, sleepiness) and poor daytime function and quality of life in middle-aged and older adults.4, 5, 7, 17, and 18 Although these daytime problems, as well as nocturia and poor self-reported sleep and insomnia are common in patients with HF, there have been few attempts to quantify nocturia severity or the differences in sleep, daytime symptoms (eg, depression, fatigue, sleepiness), or functional performance across levels of nocturia severity in these patients. Given the high burden of symptoms and poor functional performance among HF patients, it is important to understand and address possible contributing factors, such as nocturia. Therefore, the purposes of this study were to evaluate: 1) the extent to which HF patients reported nocturia and nocturia severity; 2) clinical and demographic differences across levels of nocturia severity; 3) differences in self-reported and objective characteristics of sleep across levels of nocturia severity; and 4) differences in daytime symptoms (depression, fatigue, sleepiness) and self-reported and objective functional performance across levels of nocturia severity in community-residing patients with stable HF.
We conducted a cross-sectional study to evaluate the study aims. This report was part of a larger study that had the overall purpose of evaluating the extent to which sleep and SDB explained daytime symptoms and functional performance. Full details of the study design and methods have been previously published9 and 19 but are summarized here as relevant to the present report.
The sample included patients with stable HF recruited from 5 specialized HF disease management programs in the northeastern United States. Participants had stable New York Heart Association (NYHA) functional class II–IV HF. Stability was defined as the absence of hospital admissions, emergency department visits, or titration of vasoactive medications within a month before the sleep evaluation. We excluded patients who had cognitive impairment, end-stage renal failure, neurologic or musculoskeletal conditions affecting mobility of the nondominant arm (due to the use of wrist actigraphy), or previously identified SDB.
Human subjects approval was obtained, and each of the patients provided written informed consent. Participants were recruited during routine visits to the HF programs. Medical records were reviewed, and participants completed the 6-minute walk test (6MWT) in the clinic setting. Participants underwent a 1-night unattended ambulatory polysomnographic (PSG) study at home and completed sleep/symptom diaries and a packet of questionnaires to evaluate self-reported habitual sleep characteristics, nocturnal symptoms (nocturia, pain, and dyspnea), daytime symptoms (sleepiness, depression, fatigue), and self-reported functional performance. Each participant was paid $50 at the conclusion of data collection.
Variables and Measures
Nocturia was elicited in 2 ways to capture its frequency at a time proximal to the PSG and its “habitual” (over the past month) nature. 1) Participants were asked to record the number of times that they awoke each night to void in a daily sleep/symptom diary. We used the data from the night of the PSG as the proximal measure of nocturia severity and classified it as follows: 0 voids/night (group I); 1–2 voids/night (group II); ≥3 or more voids (group III). 2) Habitual nocturia was elicited through the Sleep Habits Questionnaire 20 and defined as a response of “often or almost always” to the item eliciting the frequency of awakening at night to use the bathroom over the past month.
Sleep and Sleep Disorders
We used self-report (questionnaires), and physiologic (PSG) measures of sleep to obtain information on patient perceptions as well as its objective characteristics.
We recorded unattended nocturnal PSG for 1 night in the participants' homes with the Safiro (Compumedics) sleep recorder. We obtained electroencephalograms (C3/A2 and C4/A1), electro-oculograms, and bipolar submental electromyograms, respiratory effort, nasal flow via a pressure transducer, oxygen saturation, electrocardiogram, body position, and leg movements.
PSG studies were uploaded to a personal computer. They were scored manually on a high-resolution monitor using 30-second epochs and standardized scoring methods. 21 Sleep duration, wake time, sleep latency (time from lights out until the first epoch of stage 1 sleep), and the percentages of wake time after sleep onset and sleep stages were calculated. Sleep stages were calculated in minutes and expressed as the percentage of the total sleep period.
Self-Reported Sleep Characteristics
The Pittsburgh Sleep Quality Index (PSQI), a widely used and reliable and valid measure of sleep quality, 22 was used to obtain participants' perception of habitual sleep duration and latency (time to lights out until the beginning of sleep). Sleep efficiency was calculated as: (sleep duration/time in bed) × 100.
Insomnia symptoms were evaluated with questions from the Sleep Habits Questionnaire (SHQ). 20 The presence of insomnia symptoms was determined by a response of “often” or “almost always” to ≥1 insomnia symptoms (difficulty initiating sleep, difficulty maintaining sleep, and awakening too early in the morning). 20 Coefficient alpha as calculated from the present data was 0.83. 19
We evaluated sleepiness, fatigue, and depressive symptoms, which are common and disabling daytime symptoms of HF and sleep disorders. The Epworth Sleepiness Scale (ESS), a reliable and valid measure of sleepiness occurring in everyday life,23, 24, and 25 was used to measure sleepiness. Coefficient alpha on the data obtained in the present study was 0.77. 9 A score of >10 is indicative of clinically significant excessive daytime sleepiness.
The Center for Epidemiological Studies Depression scale (CESD)28 and 29 was used to measure depressive symptoms. It is reliable, valid, sensitive, and specific in a variety of populations.30 and 31 The total scale score and the dichotomized scale score (CESD <16 or ≥16), indicating likelihood of clinically relevant depression, were used.
Functional performance is the “day-to-day corporeal activities people do in the normal course of their lives to meet basic needs, fulfill usual roles, and maintain health and wellbeing.” 32 The 6MWT and the SF-36 Medical Outcomes Study (version 2) physical function (PF) subscale were used to evaluate objective and subjective attributes of functional performance, respectively.
The 6MWT 33 is a reliable and valid objective measure of the distance walked under controlled conditions.33, 34, and 35 A distance of <1,000 feet predicted mortality. 36 We reported 6MWT as both a continuous and dichotomous (<1,000 or ≥1,000 feet) variable.
The SF-36 PF subscale37 and 38 was used to elicit self-reported physical function. The SF-36 has well documented reliability and validity in healthy and chronically ill populations.39, 40, 41, 42, 43, and 44 The Charlson comorbidity index was used as an indicator of comorbidity. 45
Data obtained from the questionnaires, diaries, and PSG data were double-entered into a database and analyzed with SPSS (version 18) software. Data were cleaned and evaluated for missing values and corrected for skewness. We computed descriptive statistics (means, standard deviations, frequencies, and percentages) to describe the primary study variables. Analysis of variance was used to compare the nocturia severity groups on the continuous sleep, symptom, and functional performance variables, and chi-square was used to evaluate the associations between nocturia severity categories and the categoric clinical, demographic, sleep, symptom, and functional performance variables. Analysis of covariance was used to evaluate the extent to which the effects of nocturia severity on the dependent continuous variables were independent of the effects of covariates, including clinical and demographic characteristics and percentage of time awake at night. Logistic regression analysis was used to evaluate the odds ratios for the associations between nocturia severity and insomnia, 6MWT, and excessive daytime sleepiness dichotomized at levels that had clinical meaning while controlling for the effects of clinical and demographic covariates and the percentage of time awake at night.
The sample consisted of 173 patients who had stable HF (mean left ventricular ejection fraction [LVEF] 32.6 ± 15.2%; mean age 60.35 ± 16.07 years; women n = 60 [35%]). The sample included 110 (63.6%) European, 50 (29%) African, 7 (4%) Asian, and 10 (6%) Latino participants. The majority of participants used diuretics, including loop (n = 139; 80.3%), thiazides (n = 29; 16.7%), and potassium-sparing (n = 50; 28.9%) drugs. Detailed information on the clinical comorbidity and additional medications used by the participants was previously reported.9 and 19
Habitual Nocturia and Nocturia Severity
Habitual nocturia was reported by 109 participants (63.0%). Participants reported voiding 0–8 times per night (mean 1.87 ± 1.45). We classified nocturia severity as follows: 0 voids/night (group I: n = 30; 17.3%); 1–2 voids/night (group II: n = 87; 50.2%); ≥3 voids (group III: n = 56; 32.4%; Table 1 ).
|Group I (No Nocturia) (n = 30; 17.3%)||Group II (Nocturia 1–2/Night) (n = 87; 50.2%)||Group III (Nocturia ≥3/Night) (n = 56; 32.4%)|
|Age (y)∗||53.70 ± 16.04||63.38 ± 14.89||59.20 ± 16.88|
|Female||13 (43.3%)||31 (35.6%)||16 (28.6%)|
|Male||17 (56.7%)||56 (64.4%)||40 (71.4%)|
|White||21 (70.0%)||59 (67.8%)||30 (53.6%)|
|Minority||9 (30.0%)||28 (32.2%)||26 (46.4%)|
|LVEF <45%||26 (86.7%)||64 (73.6%)||41 (75.9%)|
|NYHA functional class||2.37 ± 0.72||2.51 ± 0.63||2.45 ± 0.71|
|II||21 (70.0%)||47 (54.1%)||32 (57.6%)|
|III||6 (20.0%)||35 (40.2%)||20 (35.7%)|
|IV||3 (10.0%)||5 (5.7%)||4 (7.1%)|
|Body mass index (kg/m2)||29.68 ± 6.45||30.90 ± 8.32||31.01 ± 8.42|
|Comorbidity||2.27 ± 1.79||2.54 ± 1.61||2.39 ± 1.20|
|Use diuretics||22 (81.5%)||75 (86.2%)||48 (85.7%)|
|Self-Reported Habitual Sleep Characteristics|
|Sleep latency (min)||21.70 ± 15.14||27.80 ± 28.08||35.51 ± 38.48|
|Sleep duration (min)∗||421.20 ± 80.4||393.60 ± 99.6||358.80 ± 106.20|
|Sleep efficiency (%)∗∗||87.72 ± 14.05||81.38 ± 15.93||73.76 ± 20.22|
|Insomnia symptoms∗∗||10 (33.3%)||37 (43.0%)||40 (72.2%)|
|Sleep duration (min)∗||335.72 ± 99.04||336.12 ± 84.98||297.83 ± 108.34|
|Sleep latency (min)||36.57 ± 53.89||26.45 ± 29.00||32.50 ± 31.58|
|Wake time (min)∗∗||59.5 ± 45.08||105.59 ± 69.4||117.56 ± 78.39|
|% wake time after sleep onset∗∗||15.11 ± 10.99||13.99 ± 5.92||28.65 ± 17.99|
|% stage 1 sleep||19.23 ± 7.21||21.09 ± 8.89||19.28 ± 7.69|
|% stage 2 sleep||43.38 ± 11.81||39.34 ± 11.24||37.83 ± 12.92|
|% stage 3–4 sleep∗∗||8.83 ± 7.62||4.97 ± 5.78||4.15 ± 5.20|
|% REM sleep∗||13.40 ± 6.46||11.05 ± 5.18||10.08 ± 6.75|
|Daytime Symptoms and Functional Performance|
|SF-36 physical function subcale||23.33 ± 2.39||22.73 ± 2.13||22.29 ± 2.07|
|6-minute walk (ft)∗||1,162.46 ± 476.70||985.13 ± 435.16||905.03 ± 411.50)|
|Walk <1,000 feet∗||7 (23.3%)||35 (40.2%)||29 (51.8%)|
|Depressive symptoms||17.57 ± 10.60||16.22 ± 11.12||17.84 ± 11.17|
|Depressed (CESD >16)||14 (46.2%)||38 (43.2%)||27 (48.2%)|
|Global fatigue∗∗||28.51 ± 14.89||26.83 ± 13.98||35.08 ± 14.27|
|Daytime sleepiness∗||6.37 ± 2.89||8.32 ± 3.94||9.32 ± 5.20|
|Sleepy (ESS >10)∗||3 (12.5%)||21 (26.2%)||19 (40.4%)|
∗P < .05; ∗∗P < .01; based on analysis of variance [continuous variables] or chi-square [categoric variables].
Clinical and Demographic Characteristics and Nocturia
Habitual nocturia was not associated with age, sex, race, comorbidity, LVEF, NYHA functional classification, or use of diuretics. There was a significant overall difference between nocturia severity groups based on age (P < .05), but there were no other clinical or demographic differences between these groups ( Table 1 ). There were no differences in nocturia severity based on diuretic use, frequency of dosing, or types of diuretics (data not shown).
Nocturia Severity and Sleep Characteristics
There were statistically significant overall differences between nocturia severity groups on self-reported sleep duration (P < .05) and sleep efficiency (P < .01), but no difference in sleep latency. Participants with ≥3 episodes of nocturia (group III) had an hour less self-reported sleep than those in group I ( Table 1 ).
There was also a significant difference in the proportion of patients reporting insomnia symptoms across levels of nocturia severity in the bivariate analyses ( Table 1 ). Logistic regression analysis was used to calculate the odds ratios of the effects of nocturia severity on insomnia while controlling for covariates (age, sex, and comorbidity). Patients in group III had a nearly 7-fold increase in the odds of reporting insomnia symptoms, but participants in group II had no increased odds of having insomnia compared with those who had no nocturia (group I; Table 2 ).
|OR||95% CI||P Value|
|Insomnia Symptoms ∗|
|Group II (1–2 voids/night)||1.76||0.70–4.42||.230|
|Group III (3 or more voids/night)||6.52||2.35–18.09||<.001|
|Excessive daytime sleepiness (ESS >10) †|
|Group II (1–2 voids/night)||4.63||1.14–16.37||.031|
|Group III (≥3 voids/night)||8.61||1.99–30.09||.003|
|6-minute walk <1,000 feet †|
|Group II (1–2 voids/night)||2.22||.70–6.99||.175|
|Group III (3 or more voids/night)||5.99||1.69–21.54||.006|
∗ Covariates: age, sex, comorbidity (Charlson comorbidity index).
† Covariates: age, sex, comorbidity (Charlson comorbidity index), WASO%).
WASO%, percentage of wake time after sleep onset. Reference group: no nocturia (group I).
There were statistically significant differences across levels of nocturia severity in PSG-measured sleep duration, wake time, percentage of wake time after sleep onset, and the percentages of stage 3–4 and REM sleep, but not sleep latency. Nocturnal wake time measured with PSG was almost 2 hours in group III, about twice the duration of that of participants in group I.
Nocturia Severity, Daytime Symptoms, and Functional Performance
Mean levels of fatigue and sleepiness were higher and 6MWT distance shorter across levels of nocturia severity, but there were no overall differences in depression or self-reported physical function ( Table 1 ). There was also an overall increase in the proportion of patients who had a 6MWT distance <1,000 feet and those who reported excessive daytime sleepiness (ESS >10) across levels of nocturia severity, with 51% of the sample in group III walking <1,000 feet.
To evaluate the differences in fatigue, depression, sleepiness, physical function and 6 MWT distance across levels of nocturia severity, independent of the effects of age, gender, comorbidity, and the percentage of time awake after sleep onset, we conducted separate analyses of covariance with nocturia severity as the independent variable and these clinical and demographic variables and percent wake after sleep onset as covariates. There were statistically significant nocturia severity–related differences in sleepiness (P = .009), fatigue (P = .001), self-reported physical function (P = .040), and 6MWT (P = .047), but not depression (P = .740).
We used logistic regression to evaluate the odds ratios of the associations between nocturia severity and the dichotomized dependent variables (ESS >10), and 6MWT distance <1,000 feet ( Table 2 ). As in the analysis of covariance described above, we included age, sex, comorbidity, and percentage of wake time after sleep onset as covariates. Nocturia severity (group II) was associated with a >4-fold increase in the odds of excessive daytime sleepiness, and the most severe nocturia (group III) was associated with an almost 8-fold increase in the odds of excessive daytime sleepiness, compared with those with no nocturia (group I). Patients with the highest nocturia severity (group III) had a >5-fold increase in the odds of walking <1,000 feet on the 6MWT compared with those who had no nocturia ( Table 2 ).
Nocturia is common and often severe in patients with stable HF. A full one-third of patients awakened ≥3 times per night to void. The prevalence of nocturia concurrent with the PSG recording is consistent with the report of another study of HF patients, 1 but the rate of habitual nocturia is lower, and there are no comparative data on the nocturia severity as indicated by voiding frequency (such as measured in the present study) in patients with HF. Prevalence rates are higher than rates reported in older adults with mixed cardiovascular disorders (55%) 46 and a population-based sample of older adults. 8 The reasons for the discrepancies between the reports of habitual nocturia and nocturia severity within our study compared with other studies are not known, but they may result from differences in measurement methods as well as patient recall. The lower rate of habitual nocturia compared with the previously reported rate 1 may also be related to the younger age of the participants in the present study compared with other samples recruited from the population of elderly patients with HF.
We quantified large nocturia severity–related differences in sleep duration and time awake during the night by both self-report and polysomnographic measures, extending earlier studies that evaluated only self-reports.1 and 2 Although there is some debate about normative values for sleep duration, typical adults obtain ∼7 hours of sleep per night. Based on this norm, the patients with nocturia demonstrated deprivation in the overall quantity of sleep, as indicated by sleep duration, as well as deprivation of specific sleep stages [REM and slow-wave (stages 3–4) sleep] in excess of the levels found in those without nocturia. The high proportion of patients with insomnia at all levels of nocturia severity exceeds the 10% prevalence in the U.S. population, 47 but the percentage (71.4%) is particularly striking in those with the highest nocturia severity. These findings underscore the important intersection of nocturia severity and sleep among HF patients.
Although causality can not be determined in this cross-sectional study, decreases in slow-wave sleep may lead to decreased secretion of renin and aldosterone, 10 and decreased REM sleep may lead to increased urine flow and decreased osmolality, 11 both of which may lead to nocturia. On the other hand, frequent nocturia and difficulty returning to sleep after awakening to void may also lead to sleep deprivation and further limit REM and stage 3–4 sleep. Further study is needed to evaluate the temporal relationships among these phenomena.
The importance of nocturia to HF patients is underscored by its robust independent associations with fatigue, sleepiness, and self-reported and objective measures of functional performance. As few as 1–2 episodes of nocturia increased the odds of excessive daytime sleepiness, whereas ≥3 episodes of nocturia increased the odds of both excessive daytime sleepiness and decrements in 6MWT distance. In contrast with past studies that found associations between nocturia and poor mental health,4 and 8 we found no differences in depression across levels of nocturia severity.
Although numerous population-based studies have found associations between nocturia and quality of life,4, 5, and 18 differences between the methods used in those studies and the present project preclude direct comparison of the results. It is possible that our findings are not unique to HF but reflect relationships found in the general population. However, the high burden of daytime symptoms and functional performance among HF patients suggests that any additional factors that increase this burden, such as nocturia, are meaningful in this vulnerable group of patients and should be a focus of assessment and treatment.
Although there were differences in sleep duration, sleep efficiency, and percentage of wake time after sleep onset based on nocturia severity, decrements in sleep did not explain the differences in fatigue, sleepiness, or functional performance found across levels of nocturia severity. Although one explanation might be that nocturia severity and the symptom and functional decrements are a consequence of underlying HF-related pathophysiology, the absence of differences in LVEF, comorbidity, or NYHA functional classification across levels of nocturia severity do not support this explanation. Further study is needed to evaluate the reasons for the high symptom and functional burden associated with nocturia severity.
Strengths of this study were inclusion of a clinically stable, demographically heterogeneous group of HF patients and the use ambulatory PSG sleep measurement that enabled quantification of sleep characteristics, including sleep stages, in the participants' home environments. Although self-report does not always accurately reflect objective findings, owing to the limitation of patient recall, patient perceptions are important to symptom interpretation and clinical assessment and therefore provide an important perspective. The overall shorter sleep duration elicited with PSG compared with self-report may reflect to some extent the intrusive effects of the sleep recording.
Although comorbidity was not associated with nocturia severity, it is possible that chronic conditions that were not included in the Charlson comorbidity index (eg, prostatic hypertrophy) and developmental changes (eg, menopause) may contribute to nocturia and poor sleep. Although the use of specific diuretics or the frequency of dosing was not associated with nocturia, we did not have complete information on dosage or precise timing, both of which may contribute to nocturia.
Future longitudinal experimental studies are needed to explain the causal directions and mechanisms underlying the findings of this study. Use of voiding diaries, assessment of fluid intake, and detailed information on medication usage is likely to be useful in understanding the nature of nocturia and related differences in sleep, fatigue, sleepiness, depression, and daytime function.
It is possible that behavioral or pharmacologic interventions that improve sleep may also improve nocturia. Manipulation of diuretic dosage and timing to reduce nocturia severity may improve sleep, as well as fluid overload among HF patients, but the effects of this treatment on nocturia and sleep have been understudied. From a clinical perspective, the findings of the present study suggest the importance of eliciting nocturia severity among HF patients, because it is readily elicited and may be a clue to the presence of poor sleep, fatigue, sleepiness, and poor functional performance.
Future research is needed to better understand the likely complex and multivariate factors that contribute to nocturia severity in HF patients, the direction of the relationship between nocturia severity, sleep, daytime functional performance, and daytime symptoms, including fatigue and sleepiness, and the effects of treatment.
The authors acknowledge the assistance of Laura Andrews, Nancy Bonnet, Della Campbell, George Evans, Marybeth Gregory, Rakiel Kanayefska, Agha Khan, Syed Naqvi, Eileen Oates, Rubab Qureshi, Leonie Rose, Alison Rosen, Leslie Faith Morritt-Taub, and Teresa Williams.
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1 Yale University School of Nursing, New Haven, Connecticut
2 Newark Beth Israel Medical Center, Newark, New Jersey
3 Hackensack University Medical Center, Hackensack, New Jersey
4 St Jude Medical, Sylmar, California
5 Lehigh Valley Health System, Allentown, Pennsylvania
6 Bon Secours Charity Health System, Suffern, New York
7 New York University Medical School, New York, New York
∗ Reprint requests: Nancy S. Redeker, PhD, RN, FAHA, FAAN, Professor and Associate Dean of Scholarly Affairs, Yale University School of Nursing, 100 Church Street, South, PO Box 9740, New Haven, CT 06536-07040. Tel: 203-737-242; Fax: 203-737-4480.
Funding: National Institutes of Health R01NR008022.
See page 574 for disclosure information.
© 2012 Elsevier Inc., All rights reserved.