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Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

In patients with cirrhosis, hyperammonemia and hepatic encephalopathy are common after gastrointestinal bleeding and can be simulated by an amino acid challenge (AAC), or the administration of a mixture of amino acids mimicking the composition of hemoglobin. The aim of this study was to investigate the clinical, psychometric, and wake-/sleep-electroencephalogram (EEG) correlates of induced hyperammonemia. Ten patients with cirrhosis and 10 matched healthy volunteers underwent: (1) 8-day sleep quality/timing monitoring; (2) neuropsychiatric assessment at baseline/after AAC; (3) hourly ammonia/subjective sleepiness assessment for 8 hours after AAC; (4) sleep EEG recordings (nap opportunity: 17:00-19:00) at baseline/after AAC. Neuropsychiatric performance was scored according to age-/education-adjusted Italian norms. Sleep stages were scored visually for 20-second epochs; power density spectra were calculated for consecutive 20-second epochs and average spectra determined for consolidated episodes of non-rapid eye movement (non-REM) sleep of minimal common length. The AAC resulted in: (i) an increase in ammonia concentrations/subjective sleepiness in both patients and healthy volunteers; (ii) a worsening of neuropsychiatric performance (wake EEG slowing) in two (20%) patients and none of the healthy volunteers; (iii) an increase in the length of non-REM sleep in healthy volunteers [49.3 (26.6) versus 30.4 (15.6) min; P = 0.08]; (iv) a decrease in the sleep EEG beta power (fast activity) in the healthy volunteers; (v) a decrease in the sleep EEG delta power in patients. Conclusion: AAC led to a significant increase in daytime subjective sleepiness and changes in the EEG architecture of a subsequent sleep episode in patients with cirrhosis, pointing to a reduced ability to produce restorative sleep. (HEPATOLOGY 2012)

Hepatic encephalopathy (HE) is the term used to describe the neuropsychiatric abnormalities that can be observed in patients with acute or chronic hepatic failure.1 These abnormalities can be clinically obvious (overt HE) or detected by psychometric/electrophysiological testing (minimal HE).2 They are thought to be due to neurotoxic substances of intestinal origin, which escape hepatic detoxification and reach the systemic circulation and the brain, impinging on neurotransmission.3 In patients with cirrhosis, overt HE is common after a gastrointestinal bleed, which can be simulated by the oral administration of a mixture of amino acids mimicking the composition of hemoglobin.4 Such a test, termed amino acid challenge (AAC), has been used to assess the risk of developing HE.5

Sleep-wake disturbances are common in patients with cirrhosis and have been traditionally associated with HE.1 More recent data seem to indicate that daytime sleepiness is part of the HE spectrum, whereas night sleep disturbances may have a different pathophysiology.6, 7 Abnormalities in the circadian rhythm of melatonin of both central (reduced cerebral sensitivity to dark/light cues) and peripheral origin (reduced melatonin clearance) have been described in this patient population but they do not offer a comprehensive explanation for the observed sleep-wake abnormalities.8, 9 Limited information is available on the sleep electroencephalogram (EEG) features of patients with cirrhosis.10, 11 The largest studies date back to the 1970s and were conducted in decompensated patients with severe, overt HE.10 Correlations were observed between the clinical severity of encephalopathy and the degree of disruption of sleep architecture.10

The transition between wake and sleep, as well as the transitions between non-rapid eye movement (non-REM) and REM sleep, are characterized by well-defined EEG characteristics. Non-REM sleep is divided into stages 1 to 4, with stages 3 and 4 representing deep sleep. Non-REM stage 1 is considered a transitional state between waking and sleep. Non-REM stage 2 is characterized by K-complexes and sleep spindles, whereas stages 3 and 4 (or slow wave sleep) are dominated by high-amplitude, low frequency (delta) waves.12 Delta activity (power in the 0.75-4.5 Hz range of the EEG spectrum) in non-REM sleep is a reliable indicator of sleep homeostasis, which reflects the effect of sleep/wake history on sleep propensity: delta activity increases as a function of the duration of prior wakefulness and dissipates with progression of sleep.13

Brief sleep EEG recordings of 90-120 minutes, or “nap” studies, are easier to perform than all-night polysomnography, especially in a clinical setting. Naps have been shown to accurately reflect the current level of homeostatic sleep pressure, which accumulates during the wake period.14 Furthermore, naps taken later in the day are characterized by a higher level of sleep pressure, and thus a higher amount of slow wave sleep.15 Protocols with repeated naps require patients to maintain regular sleep-wake schedules prior to/during the study, thus only medically stable subjects can be included.

The aims of the present study were: (1) to test the hypothesis that an ammonia load increases subjective daytime sleepiness in patients with cirrhosis; (2) to establish whether induced hyperammonemia/increased daytime sleepiness impinge on sleep EEG, particularly the amount of slow-wave sleep, in the subsequent sleep episode.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Study Subjects

The patient population comprised 10 consecutive, right-handed, out-patient attendees [9 men; mean (standard deviation, SD) age: 54 (14) years] with cirrhosis. The functional severity of liver disease was assessed using Pugh's modification of the Child's grading system16 and the Model for Endstage Liver Disease (MELD).17 Patients were excluded if they were <20/>80 years of age, could not comply with the study procedures, had misused alcohol in the preceding 6 months, had had episodes of hepatic decompensation/in-patient admissions during the previous month, had a history/clinical signs of overt HE or severe sleep-wake disturbances, were on anti-HE treatment, had a history of significant head injury, cardio-/cerebrovascular disease, neurological/psychiatric comorbidity, were taking neuroactive medication/medication known to affect sleep, had traveled across more than two time zones in the preceding 3 months, or undertaken shift work in the preceding 5 years.

The protocol required patients to maintain regular sleep-wake schedules during the weeks prior to/during the study period. These requirements were not met in the Child C patients screened, who were prone to episodes of decompensation/inpatient admissions.

The reference population comprised 10 right-handed healthy volunteers [5 men; 49 (13) years]. None drank alcohol in excess of 20 g/day, were taking prescription medication, or had traveled/undertaken shift work as defined above.

One patient (A, 55-year-old male, Child B) underwent wake/nap EEG recordings (see below) prior to/after the insertion of a trans-jugular portal-systemic shunt (TIPS). One patient (B, 68-year-old male, Child C) underwent wake/nap EEG recordings prior to/after treatment of severe, overt HE.

Study Design

Individual studies were conducted over an 8-day period (Fig. 1), in two separate locations: Padova University Hospital (study day 1: informed consent; protocol instructions; quality of life/sleep questionnaires, sleep diaries and actigraphy; nutritional evaluation) and the patients' homes (study days 2-3, 5-7: sleep quality and timing monitoring by diaries/actigraphy). On study days 4 and 8 (Padova University Hospital), subjects underwent a neuropsychiatric evaluation in the morning and a nap study in the early evening; subjective sleepiness was monitored hourly. Subjects were randomized to receive the AAC (see below) or regular breakfast on study days 4 or 8; on the day they received the AAC capillary ammonia was monitored hourly.

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Figure 1. Study design, locations, and timing. *Hourly ammonia assessment was performed only after the AAC. AAC, amino acid challenge; EEG: electroencephalogram.

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Subjects were asked to refrain from daytime napping and from applying significant changes to their sleep-wake habits and their intake of caffeinated/alcoholic beverages over the whole study period. Adherence was confirmed by sleep diaries and by caffeine/alcohol intake records.

Nutritional Evaluation

This included measurement of weight/height, calculation of the body mass index (BMI), and evaluation of body composition by the mid-arm circumference and the triceps skinfold thickness. The mid-arm muscular area was then calculated and the results scored according to reference percentiles.18

Quality of Life

Subjects completed the 36-item Short Form Health Profile (SF36) questionnaire.19 SF36 summary measures (SF36-Physical/Mental) were calculated using Italian scoring coefficients.

Habitual Sleep Timing and Sleep Quality

Pittsburgh Sleep Quality Index (PSQI) Questionnaire

This is used to assess sleep quality over the preceding month.20

Epworth Sleepiness Scale (ESS)

Subjects are asked to rate their likelihood of “dozing off” in eight situations and responses are summed to provide a total score.21

Horne-Östberg (HÖ) Questionnaire

This is used to define diurnal preference as evening, intermediate, or morning.22

Sleep Diaries

Subjects kept individual daily sleep diaries for the whole study period, recording their bedtime, the time they started trying to sleep, their sleep onset, and wake-up and get-up times.

Actigraphy

An actigraph is a device that records movement by means of an accelerometer; its use is based on the assumption that a lack of movement indicates rest. In this study, an Armband Sensewear (Sensormedics Italia, Milan, Italy) was worn on the nondominant wrist throughout the study period, except when showering/bathing. Sleep efficiency (100*time of estimated sleep/time spent in bed) was used as a summary indicator of sleep quality.23

Neuropsychological Assessment

Psychometric Hepatic Encephalopathy Score (PHES) Battery

This paper-and-pencil psychometric test battery is used for the diagnosis/quantification of HE.24 Individual test results were scored in relation to age-/education-adjusted Italian norms and performance classified as impaired if the sum of the standard deviations from the norms (PHES score) was ≤−4.25

Scan Test

This computerized working memory test, based on the Sternberg task,26 is used for the diagnosis/quantification of HE.27 Two random series (memory and test sets) of 2, 3, or 4 digits are consecutively presented on a computer screen. The subject is asked to press number 1 on the keyboard if there are common digits between the memory and the test sets (i.e., 2861, 83), and number 3 if there are not (i.e., 2861, 73). Accuracy and reaction times were scored in relation to age-/education-adjusted Italian norms.

Electrophysiological Assessment

Wake EEG

The EEG was recorded for 10 minutes, eyes closed, in a condition of relaxed wakefulness, using a 21-electrode EEG cap (SEI emg s.r.l., Cittadella, Italy). Electrodes were placed according to the International 10-20 system; ground: Fpz; reference: Oz. Each channel had its own analog-to-digital converter, was bandpass-filtered between 0.33 and 120 Hz, the resolution was 0.19 μV/bit and the sampling frequency was 256 Hz (Brainquick 3200, Micromed, Italy). The EEG was visually inspected to exclude focal activity and to select one, continuous 80-second, artifact-free section for subsequent spectral analysis by Fast Fourier Transform (average of 40 2-second epochs, Hanning window, frequency resolution 0.5 Hz; MatLab, MathWorks, Natick, MA). Spectral analysis was performed for the P3-P4 derivation and the EEG classified based on the mean dominant frequency (MDF) and the relative power of the delta and theta bands.28 Where obvious on visual inspection of the power spectrum, the frequency of the dominant peak was also obtained.

Nap EEG

Between 17:00 and 19:00 hours, subjects were placed in a quiet, dark, and shielded hospital room and given the opportunity to nap. The EEG was recorded as described above. In addition, the mastoids, submental electromyogram and ocular movements were also recorded.

Sleep stages were scored visually for 20-second epochs (C3-A2 derivation) according to standard criteria12 (Rembrandt Analysis Manager, v. 8; Embla Systems, Broomfield, CO) by one of the authors (A.B.), who had no information on either the subject or the experimental condition. Blocks of consolidated non-REM sleep (sleep stages 2-4, without intervening epochs of wake or stage 1 sleep) of equal length in the two experimental conditions (minimal length: 8 minutes) were selected for subsequent spectral analysis. Power spectra were computed by Fast Fourier Transform (2-second epochs, Hanning window, frequency resolution 0.5 Hz).

Artifacts were identified by visual inspection or whenever delta power exceeded a subject-specific threshold.

Amino Acid Challenge

The AAC was administered at 07:00 hours on study days 4 or 8. It consisted of a flavored, 54 g amino acid mixture, mimicking the composition of the hemoglobin contained in 400 mL of blood.4 The mixture was dispersed in 50-100 mL of water and ingested over a period of 10-15 minutes.

Capillary ammonia concentrations were measured prior to and at hourly intervals for 8 hours after the AAC using the Ammonia Checker (Menarini Diagnostics, Firenze, Italy).

Subjective sleepiness was also monitored on an hourly basis using the Karolinska Sleepiness Scale (KSS)29 on both study days 4 and 8.

Ethics

The study protocol was approved by the Hospital of Padua Ethics Committee. All participants provided written, informed consent. The study was conducted according to the Declaration of Helsinki (Hong Kong Amendment) and Good Clinical Practice (European) guidelines.

Statistical Analysis

Data are presented as mean (SD) unless otherwise specified. The distribution of variables was assessed by the Shapiro-Wilks' test and between group comparisons performed using Student's t or Mann-Whitney U tests, as appropriate. Comparisons between pre- and post-AAC variables were performed by repeated measures analysis of variance (ANOVA) using the variable healthy volunteers versus patients as a “group” factor. Log-transformed average sleep EEG power spectra were analyzed with linear mixed model ANOVA. The factors group (patients versus healthy volunteers) and condition (AAC versus baseline), as well as their interaction, were tested. Whenever the factor condition or the interaction were significant, post-hoc paired t tests were performed. Statistical analyses were performed with SAS 9.1.3 (SAS Institute, Cary, NC) and Statistica 7.1 (StatSoft, Tulsa, OK).

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

Baseline Evaluation

Age and level of education were comparable in patients and healthy volunteers; the number of males was higher in the patients group (90 versus 50%; χ2 3.8, P = 0.05). Six patients were classed as Child A and 4 as Child B; average MELD was 9.1 (2.2). None of the patients or the healthy volunteers had abnormal BMI. Four (40%) patients and two (20%) healthy volunteers had initial muscle mass depletion.

Quality of life was impaired in patients compared to healthy volunteers [SF36-Physical: 41.1 (9.6) versus 50.4 (7.7), P = 0.02; Table 1]. No significant differences were observed in diurnal preference/daytime sleepiness between the two study groups. As expected based on patients selection, subjective sleep quality (PSQI questionnaire) was also comparable, whereas actigraphy documented significantly lower sleep efficiency in the patients [68.5 (15.9) versus 81.0 (9.0)%, P = 0.05; Table 1]. On average, habitual sleep timing was delayed in patients compared to healthy volunteers, although the differences were not significant (Table 1). Both groups exhibited fluctuations in subjective sleepiness in the course of the day, with a peak in the early afternoon (Fig. 2).

Table 1. Quality of Life and Sleep-Wake Data in Healthy Volunteers and Patients With Cirrhosis
 VariableHealthy VolunteersPatients with Cirrhosis
  • *

    P < 0.05 significant difference between healthy volunteers and patients with cirrhosis.

Quality of lifeSF36 Summary physical50.4 (7.7)41.1 (9.6)*
SF36 Summary mental50.9 (7.8)51.1 (4.8)
Day-time sleepinessEpworth Sleepiness Scale5.2 (1.9)4.4 (3.1)
Night sleep qualityPittsburgh Sleep Quality Index6.3 (3.8)5.3 (2.7)
Diurnal preferenceHorne-Östberg questionnaire57.9 (11.6)58.1 (8.1)
Habitual sleep timing (Sleep diaries)Bed-time (clock time)23:30 (01:06)24:06 (01:30)
Try to sleep time (clock time)23:42 (01:06)24:30 (01:18)
Sleep onset (clock time)24:00 (01:06)24:42 (01:24)
Wake-up time (clock time)07:00 (00:54)07:15 (01:18)
Get-up time (clock time)07:24 (00:54)07:24 (01:24)
Number of awakenings1.2 (1.2)1.1 (0.7)
ActigraphySleep efficiency (%)81.0 (9.0)68.5 (15.9)*
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Figure 2. Hourly capillary ammonia levels (A) in healthy volunteers (black line, white squares) and patients with cirrhosis (black line, black circles). Hourly subjective sleepiness ratings in healthy volunteers (B) and patients with cirrhosis (C), at baseline (gray lines) and after the AAC (black lines). The ACC resulted in an increase in ammonia levels, which reached their maximum at 4 hours from administration in both groups. In addition, the AAC resulted in the appearance of a morning, subjective sleepiness peak, which was not present at baseline, and coincided with the ammonia peak (gray vertical bar across panels). KSS: Karolinska Sleepiness Scale; AAC: amino acid challenge.

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Baseline Psychometric Performance

All healthy volunteers and patients had normal PHES and Scan test performances at baseline. However, patients scored worse on both measures (Table 2).

Table 2. Psychometric, Wake and Sleep EEG Variables in Healthy Volunteers and Patients With Cirrhosis at Baseline and After AAC
  Healthy VolunteersPatients with Cirrhosis
 VariableBaselineAACBaselineAAC
  • *

    P < 0.05 significant difference between healthy volunteers and patients with cirrhosis at baseline.

  • P = 0.08 trend for a significant difference between baseline and AAC in healthy volunteers.

  • Sleep stages 3 and 4 were reached by three healthy volunteers and four patients at baseline and five healthy volunteers and three patients after AAC.

PsychometryPHES score (z points)4.2 (1.2)3.4 (1.8)1.6 (2.7)*2.0 (2.7)
Sternberg score (z points)0.2 (0.9)0.4 (1.3)-1.0 (1.3)*-0.8 (0.9)
Wake EEGMDF (Hz)11.3 (1.7)11.3 (1.2)10.4 (2.0)10.4 (1.6)
Dominant peak (Hz)9.9 (0.2)9.3 (1.5)9.0 (0.9)*8.9 (0.8)
Relative theta power (%)11 (3)11 (3)20 (1)*23 (1)
Sleep EEGNon-REM sleep duration (min)30.4 (15.6)49.3 (26.6)51.0 (14.5)*51.8 (34.9)
Stage 1 (min)8.9 (6.8)13.5 (11.8)9.7 (4.2)13.1 (10.8)
Stage 2 (min)19.7 (10.0)30.5 (17.3)33.2 (13.1)*30.8 (22.9)
Stages 3-4 (min)4.7 (3.8)10.6 (8.3)12.9 (7.7)20.7 (19.6)
Baseline Wake EEG

All healthy volunteers and nine patients had a normal wake EEG; one patient had grade I EEG slowing according to Amodio et al.28 On average, patients had a significantly slower EEG than healthy volunteers (Table 2).

Baseline Nap EEG

Eight healthy volunteers and eight patients reached consolidated non-REM sleep during the nap opportunity in both experimental conditions, thus nap EEG analysis was limited to these subjects.

Patients slept significantly longer than healthy volunteers [51.0 (14.5) versus 30.4 (15.6) minutes; P = 0.02; Table 2]. However, the length of the solid blocks of non-REM sleep selected for spectral analysis was comparable in the two groups (Table 2).

Power spectra (1.5-25 Hz) of the baseline nap EEG were comparable in patients and healthy volunteers [factor group (patients versus healthy volunteers) not significant; Fig. 3].

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Figure 3. (A,B) Power spectra of the nap EEG in healthy volunteers (A) and patients with cirrhosis (B) at baseline (gray lines) and after AAC (black lines). (C,D) Relative power spectra, where the nap EEG power after AAC (black line) is expressed as a percentage of the baseline value (gray line) in healthy volunteers (C) and patients with cirrhosis (D). The middle panels indicate statistical significance: black circles indicate a significant condition factor (AAC versus baseline), whereas gray circles indicate a significant interaction between the group (healthy volunteers versus patients) and condition (AAC versus baseline) factors. In healthy volunteers (A-C), the challenge resulted in a decrease in power between 16 and 25 (fast activity range; black triangles: significant post-hoc t tests). In patients with cirrhosis (B-D), the challenge resulted in a decrease in power between 2 and 6.5 Hz (within the delta range; black triangles: significant post-hoc t tests). AAC: amino acid challenge.

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Amino Acid Challenge.

Six (60%) patients and five (50%) healthy volunteers were randomized to receive AAC on study day 4, whereas the remainder received it on study day 8. The AAC was well tolerated, although three healthy volunteers and two patients complained of nausea.

Post-AAC Ammonemia

Patients had significantly higher baseline ammonia levels compared to healthy volunteers [202 (61) versus 147 (45) μg/dL, P = 0.03]. The AAC resulted in a significant increase in ammonia levels in both groups, with highest values at approximately 4 hours after the AAC (Fig. 2). Ammonia concentrations in the two groups showed a similar time course up to the peak; the decrease in ammonia concentrations thereafter was steeper in the healthy volunteers, although the interaction effect was not significant [time course: F = 2.1, P = 0.05; group (patients versus healthy volunteers): F = 15.3, P = 0.00; time course*group: F = 0.7, P = 0.66; Fig. 2A].

Post-AAC Subjective Sleepiness

The AAC resulted in an increase in subjective sleepiness in both healthy volunteers and patients with cirrhosis (Fig. 2). In both groups, a small morning (11:00 hours) peak in sleepiness appeared, which was not present at baseline; the sleepiness peak coincided with the time when ammonia reached maximal concentrations (Fig. 2, gray bar). The increase in subjective sleepiness after AAC was prominent in the morning hours in patients and throughout the recording in healthy volunteers [time course: F = 6.0, P = 0.00; group (patients versus healthy volunteers): F = 8.7, P = 0.00; condition (AAC versus baseline): F = 36, P = 0.00; group*condition: F = 5.9, P = 0.02; Fig. 2B,C].

Post-AAC Psychometric Performance

The AAC did not induce significant changes in PHES or Scan test performance in any of the study subjects (Table 2).

Post-AAC Wake EEG

The AAC did not result in significant changes in the wake EEG of any of the healthy volunteers. Two patients whose EEGs were normal at baseline developed grade I EEG slowing; the EEG of the patient who had grade I EEG alterations at baseline did not change significantly. Average, spectral EEG parameters did not change significantly (Table 2).

Post-AAC Nap EEG

Healthy volunteers showed a trend for longer non-REM sleep after AAC compared to baseline [49.3 (26.6) versus 30.4 (15.6) minutes; P = 0.08; Table 2]. Patients had comparable amounts of non-REM sleep in the two experimental conditions [51.8 (34.9) versus 51.0 (14.5) minutes; Table 2].

In healthy volunteers, the AAC resulted in a significant decrease of the EEG activity between 15 and 23 Hz (fast frequency range). In contrast, in patients the AAC induced a significant reduction in the EEG activity between 2 and 6.5 Hz (delta, or slow wave sleep range) (Fig. 3).

Case Reports

At baseline, the wake EEG of patient A was within the normal range (MDF 11.2 Hz, peak frequency 10.0 Hz). TIPS insertion resulted in slowing of the wake EEG (MDF 9.3 Hz, peak frequency 8.5 Hz; Fig. 4). At baseline, the spectrum of the nap EEG had normal features, with a spindle peak at 15 Hz. TIPS insertion resulted in the disappearance of the spindle peak and the appearance of a peak at 6.5 Hz (Fig. 4).

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Figure 4. Wake and nap EEG spectra in the two case reports. Patient A wake. The wake EEG of patient A prior to TIPS insertion (gray line) was normal, with a peak within the alpha range at 10 Hz (gray arrow). TIPS (black line) resulted in a slowing of the peak to 8.5 Hz (black arrow). Patient A nap. The nap power spectrum was substantially normal prior to TIPS insertion (gray line), with a peak in the sleep spindle frequency range at 15 Hz (gray arrow). After TIPS (black line), the spindle peak disappeared, whereas a peak appeared at 6.5 Hz (theta activity, mostly in the frontal derivations; data not shown). Patient B wake. The wake EEG of patient B prior to treatment for HE was disorganized (gray line), with no obvious peak. Treatment (black line) resulted in the appearance of a dominant alpha peak at 9 Hz, and a second, smaller beta peak at 16.5 Hz (black arrows). Patient B nap. The main difference between the spectra prior to and after treatment was visible within the spindle frequency range: the sleep spindle peak was broad (gray arrow) prior to treatment, whereas two sleep spindle peaks at 13 and 15 Hz (black arrows) appeared after treatment. HE, hepatic encephalopathy; TIPS: trans-jugular portal-systemic shunt.

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At baseline, the wake EEG of patient B was slowed (MDF 4.7 Hz, dominant peak not present). Treatment with nonabsorbable disaccharides and antibiotics plus rehydration resulted in a normalization of the EEG (MDF 10.5 Hz, peak at 9 Hz). Prior to treatment, the spectrum of the nap EEG had “near-normal” features, with a sleep spindle peak at 14 Hz. Treatment resulted in the appearance of two sleep spindle peaks (14 and 16 Hz; Fig. 4) with higher spectral power compared to nap prior to treatment.

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

The AAC resulted in the expected increase in capillary ammonia concentrations, together with an increase in subjective sleepiness and changes in both wake and nap EEG characteristics in patients with cirrhosis. Conversely, no significant changes were observed in psychometric performance. In healthy volunteers the AAC was also associated with increased ammonia levels and subjective sleepiness, and with changes in the nap EEG. AAC-related sleep and nap EEG changes had opposite direction in healthy volunteers and patients. The amount of non-REM sleep displayed a trend toward an increase in healthy volunteers but not in patients. In addition, healthy volunteers showed a decrease in fast sleep EEG activity, whereas patients showed a reduction in delta activity, and thus more superficial sleep.

Baseline Profiles

The quality of life, sleep-wake rhythms, and neuropsychiatric performance of the patient population were those expected based on previous studies, and the fact that only relatively well-compensated individuals with no HE and no significant sleep-wake abnormalities were recruited.6, 7, 30 These restrictive selection criteria were aimed at: (1) limiting confounders on sleep-wake variables; (2) avoiding episodes of precipitated, overt HE after the AAC; (3) maximizing the differences between the AAC and the baseline conditions. Nonetheless, the patients' quality of life was impaired, their sleep less efficient, and, albeit only as a trend, delayed compared to healthy volunteers. Neuropsychiatric performance was well preserved but still significantly worse than that of healthy volunteers, with slower reaction times on psychometry and slower wake EEG. The diurnal time-course of subjective sleepiness had not been previously investigated in this patient population and exhibited the expected increase in the early afternoon. Such an increase is known to occur also in healthy subjects,31 and relates to the interaction of the circadian and homeostatic components of sleep regulation.32

The nap EEG characteristics of well-compensated patients with cirrhosis are largely unknown. In this small population they were comparable to those of healthy volunteers, although the patients tended to sleep longer during the nap opportunity. This may relate to the observed, higher baseline ammonia levels and/or increased levels of daytime sleepiness, which have been described in these individuals,6, 7 also in association with blunted melatonin rhythms.33

Post-AAC Profiles

The AAC led to the expected increase in ammonia levels, with a peak at approximately four hours after administration. Douglass et al.4 reported an earlier peak, at ≈2 hours from the administration of the same mixture. The differences may be due to differences in the patients enrolled, the ones in this study being better compensated, and/or to the fact that hourly ammonia measurements may be insufficient for accurate definition of the peak time. In our study, baseline ammonia concentrations were higher in the patients than healthy volunteers, but showed a similar time course up to the peak. The decrease in ammonia levels after the peak was steeper in the healthy volunteers. This is in agreement with the notions that: (1) hyperammonemia after AAC is largely due to the absorption/oxidation of amino acids; (2) ammonia is a high extraction molecule, which is removed by the liver in a flow-dependent manner,34 thus explaining the reduced clearance in patients.

The observation that the ammonia peak was associated with a quantifiable, transient increase in subjective sleepiness is a completely novel finding. There is some evidence that overt HE is associated with excessive daytime sleepiness,6, 7 and some of the wake EEG features of HE, particularly the anteriorization of the background rhythm, are reminiscent of those observed during the wake-sleep transition.35 The findings in the present study suggest that subjective sleepiness may be increased even for levels of ammonia that do not result in neuropsychiatric alterations. This has relevant clinical implications: (1) measures of sleepiness may be useful as surrogate measures of HE; (2) the relationship between HE and difficulties in complex task execution (i.e., driving) may not lay in specific cognitive deficits36 but in a reduction in vigilance.

The AAC had virtually no effect on paper-and-pencil or computerized psychometric performance, whereas it caused some slowing of the wake EEG in two patients. This is in line with a previous study on AAC4 and with a recent, small series suggesting that a sleep deprivation protocol does not affect cognition in these patients.11 In addition, the tight but necessary exclusion criteria may have led to the selection of a group of subjects who were not particularly prone to develop neuropsychiatric abnormalities, and indeed had excellent baseline psychometric performance despite slightly raised ammonia levels. Finally, it has recently been suggested that the EEG and psychometric alterations associated with HE may have different biochemical correlates, the former being more related to increased concentrations of neurotoxins of intestinal origin, the latter to the activated inflammatory cascade.37

Healthy volunteers and patients had similar nap EEG features at baseline, with comparable ability to generate delta activity, and they both reported subjective sleepiness after the AAC. However, the effect of the AAC on sleep structure and nap EEG was different in the two groups, with non-REM sleep prolongation and fast EEG activity suppression in the healthy volunteers and reduction in delta activity, thus more superficial sleep, in the patients.

Sleep and wakefulness are homeostatically regulated, and the ability to generate restful sleep depends, to some extent, on the quality of the previous waking period.13 Thus, the power of the waking EEG theta band increases as a function of the duration of wakefulness,38 and increased sleep pressure is reflected in an increase in non-REM sleep delta activity in the sleep EEG.13, 39 It is possible that in hyperammonemic/encephalopathic patients with cirrhosis, who show excessive daytime sleepiness and a chronic increase in the waking EEG theta activity,7 wakefulness might be somewhat “inefficient,” thus compromising the build-up of the homoeostatic response, and resulting in an inability to generate deep, restful sleep. Therefore, it can be hypothesized that treatment strategies aimed at reducing daytime sleepiness may also lead to an improvement in night sleep architecture in these patients.

The two case reports confirmed that HE is associated with prominent, reversible changes of both wake and nap EEG structure. Interestingly, in these two cases the HE-related sleep EEG changes were particularly prominent within the sleep spindle range, an area of the spectrum that was only moderately affected by the AAC. Similar findings have been reported once before in a group of patients with overt HE.10 Clearly, differences are to be expected between the electrophysiological profile of full-blown, spontaneous or TIPS-related overt HE and AAC-related hyperammonemia because the latter is only a model of the former, it is not meant to induce severe neuropsychiatric dysfunction and it is not necessarily accompanied by the degree of hepatic failure and/or the precipitants which are associated with spontaneous HE.

In conclusion, profound changes were observed in response to the AAC in clinical (subjective sleepiness), wake and nap EEG indices, suggesting that such techniques are exquisitely sensitive to ammonia levels, which have limited neuropsychiatric/neuropsychological correlates. These findings have important clinical implications: (1) subjective sleepiness may be a useful surrogate marker of HE; (2) correction of excessive daytime sleepiness, either by pharmacological or chronotherapeutic strategies, may also result in improved night sleep.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References

We thank all study participants for their patient and cheerful cooperation. We thank Professor Carlo Merkel, University of Padua, for helpful discussions on the article and constant support.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  • 1
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