European Journal of Neurology 2014, 21: 1249–1250
doi:10.1111/ene.12457
EDITORIAL
Using electrographic sleep elements to determine outcome of critically ill patients with acute encephalopathy
See paper by Sutter et al. on page 1268. Acute encephalopathy represents a major concern for the management of critically ill patients in the intensive care unit (ICU), as associated mortality is as high as 35% [1] and 70% of survivors have cognitive impairment when tested a year later [2]. Sedative medications in mechanically ventilated patients, underlying neurological disease and greater illness severity are risk factors for acute encephalopathy during the ICU stay. The prevalence of acute encephalopathy in ICU patients has been estimated to be 15%–80% [3] and suggests that acute encephalopathy is under-diagnosed. Recognition of acute encephalopathy is based on the use of clinical scales and scoring methods. However, some authors have proposed electroencephalograms (EEGs) as a useful bedside tool offering diagnostic and prognostic value. Electrographic patterns suggestive of acute encephalopathy are characterized by slowing of background frequencies (theta, theta/delta or delta activity), variably associated with triphasic waves or frontal intermittent rhythmic delta activity. Severe sleep disturbances are another important source of concern in the ICU setting. Twenty-fourhour polysomnography demonstrated that only a minority of patients effectively experience normal sleep. Conversely, atypical sleep, defined by the absence of K-complexes and sleep spindles, has been reported in 28%–85% of cases [4,5]. Risk factors for sleep disturbances clearly overlap with those of acute encephalopathy. These include intrinsic factors, such as illness severity, and extrinsic factors directly linked with the ICU environment and the loss of circadian rhythm (noise, light, sedative and opioid medications, nursing interventions). These findings suggest a relationship between sleep disturbances in ICU patients and acute encephalopathy occurrence, but the causal relationship on outcome remains uncertain. In this issue of the journal Sutter et al. [6] report a study of the association of EEG sleep potentials on outcome of encephalopathic ICU patients. The paper has the usual limitations of single-centered, retrospective studies. Their analysis of sleep elements was based on intermittent EEGs whereas polysomnography over 24 h is the gold standard. Thus, we cannot be certain
© 2014 The Author(s) European Journal of Neurology © 2014 EAN
of the absence of sleep elements during the whole 24 h. Furthermore, the diagnosis of acute encephalopathy was retained in the presence of EEG patterns of encephalopathy even though 18% of patients received sedative medications during or 24 h prior to EEG. However, we have to note that adequate statistical efforts were made by the authors to minimize this potential bias. Taking the above into consideration, the prognostic value of the paper by Sutter et al. [6] is confirmatory of other studies that showed a similar improved survival and neurological grade when sleep potentials were present in patients with impaired consciousness from various etiologies [7]. Sutter et al. [6] used logistic regression analysis to determine those sleep potentials that had the strongest statistical association with outcome. Only K-complexes proved to be significantly associated with good outcome in patients without structural brain lesions. If we accept the results of Sutter et al. [6] it seems unlikely that sleep itself conferred the beneficial outcome; it is more probable that K-complexes reflect a higher level of functioning, integrated brain function. K-complexes consist of a brief negative high-voltage peak, the highest potential in normal EEGs, followed by a positive wave and then a final negative peak. They are often, but not always, followed by sleep spindles. Although K-complexes occur spontaneously they can be triggered by various stimuli. Human and animal studies have shown that the K-complex is widespread over the cortex, with frontal predominance, and is generated in its superficial layers. Functional magnetic resonance has shown that K-complexes are part of a physiological ‘sleep network’ including the thalamus, superior temporal lobes, paracentral gyri and medial portions of the occipital, parietal and frontal lobes [8]. Thus, the demonstration of the equivalent of functioning brain networks is a relatively favorable prognostic feature, as is being increasingly recognized.
Disclosure of conflicts of interest The authors declare no financial or other conflicts of interest.
1249
1250
Editorial
S. Legriela and G. B. Youngb a
Intensive Care Unit, Centre Hospitalier de Versailles – Site
Andr e Mignot, Le Chesnay, France; and bDepartment of Clinical Neurological Sciences, Western University, London, ON, Canada
(e-mail: [email protected])
References 1. Ely EW, Shintani A, Truman B, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA 2004; 291: 1753–1762. 2. Girard TD, Jackson JC, Pandharipande PP, et al. Delirium as a predictor of long-term cognitive impairment in survivors of critical illness. Crit Care Med 2010; 38: 1513–1520. 3. Reade MC, Finfer S. Sedation and delirium in the intensive care unit. N Engl J Med 2014; 370: 444–454.
4. Drouot X, Roche-Campo F, Thille AW, et al. A new classification for sleep analysis in critically ill patients. Sleep Med 2012; 13: 7–14. 5. Watson PL, Pandharipande P, Gehlbach BK, et al. Atypical sleep in ventilated patients: empirical electroencephalography findings and the path toward revised ICU sleep scoring criteria. Crit Care Med 2013; 41: 1958–1967. 6. Sutter R, Barnes J, Leyva A, Kaplan PW, Geocadin RG. Electroencephalographic sleep elements and outcome in acute encephalopathic patients: a 4-year cohort study. Eur J Neurol 2014; 21: 1268–1275. 7. Urakami Y. Relationship between sleep spindles and clinical recovery in patients with traumatic brain injury: a simultaneous EEG and MEG study. Clin EEG Neurosci 2012; 43: 39–47. 8. Caporro M, Haneef Z, Yeh HJ, et al. Functional MRI of sleep spindles and K-complexes. Clin Neurophysiol 2012; 123: 303–309.
© 2014 The Author(s) European Journal of Neurology © 2014 EAN
doi:10.1111/ene.12457
EDITORIAL
Using electrographic sleep elements to determine outcome of critically ill patients with acute encephalopathy
See paper by Sutter et al. on page 1268. Acute encephalopathy represents a major concern for the management of critically ill patients in the intensive care unit (ICU), as associated mortality is as high as 35% [1] and 70% of survivors have cognitive impairment when tested a year later [2]. Sedative medications in mechanically ventilated patients, underlying neurological disease and greater illness severity are risk factors for acute encephalopathy during the ICU stay. The prevalence of acute encephalopathy in ICU patients has been estimated to be 15%–80% [3] and suggests that acute encephalopathy is under-diagnosed. Recognition of acute encephalopathy is based on the use of clinical scales and scoring methods. However, some authors have proposed electroencephalograms (EEGs) as a useful bedside tool offering diagnostic and prognostic value. Electrographic patterns suggestive of acute encephalopathy are characterized by slowing of background frequencies (theta, theta/delta or delta activity), variably associated with triphasic waves or frontal intermittent rhythmic delta activity. Severe sleep disturbances are another important source of concern in the ICU setting. Twenty-fourhour polysomnography demonstrated that only a minority of patients effectively experience normal sleep. Conversely, atypical sleep, defined by the absence of K-complexes and sleep spindles, has been reported in 28%–85% of cases [4,5]. Risk factors for sleep disturbances clearly overlap with those of acute encephalopathy. These include intrinsic factors, such as illness severity, and extrinsic factors directly linked with the ICU environment and the loss of circadian rhythm (noise, light, sedative and opioid medications, nursing interventions). These findings suggest a relationship between sleep disturbances in ICU patients and acute encephalopathy occurrence, but the causal relationship on outcome remains uncertain. In this issue of the journal Sutter et al. [6] report a study of the association of EEG sleep potentials on outcome of encephalopathic ICU patients. The paper has the usual limitations of single-centered, retrospective studies. Their analysis of sleep elements was based on intermittent EEGs whereas polysomnography over 24 h is the gold standard. Thus, we cannot be certain
© 2014 The Author(s) European Journal of Neurology © 2014 EAN
of the absence of sleep elements during the whole 24 h. Furthermore, the diagnosis of acute encephalopathy was retained in the presence of EEG patterns of encephalopathy even though 18% of patients received sedative medications during or 24 h prior to EEG. However, we have to note that adequate statistical efforts were made by the authors to minimize this potential bias. Taking the above into consideration, the prognostic value of the paper by Sutter et al. [6] is confirmatory of other studies that showed a similar improved survival and neurological grade when sleep potentials were present in patients with impaired consciousness from various etiologies [7]. Sutter et al. [6] used logistic regression analysis to determine those sleep potentials that had the strongest statistical association with outcome. Only K-complexes proved to be significantly associated with good outcome in patients without structural brain lesions. If we accept the results of Sutter et al. [6] it seems unlikely that sleep itself conferred the beneficial outcome; it is more probable that K-complexes reflect a higher level of functioning, integrated brain function. K-complexes consist of a brief negative high-voltage peak, the highest potential in normal EEGs, followed by a positive wave and then a final negative peak. They are often, but not always, followed by sleep spindles. Although K-complexes occur spontaneously they can be triggered by various stimuli. Human and animal studies have shown that the K-complex is widespread over the cortex, with frontal predominance, and is generated in its superficial layers. Functional magnetic resonance has shown that K-complexes are part of a physiological ‘sleep network’ including the thalamus, superior temporal lobes, paracentral gyri and medial portions of the occipital, parietal and frontal lobes [8]. Thus, the demonstration of the equivalent of functioning brain networks is a relatively favorable prognostic feature, as is being increasingly recognized.
Disclosure of conflicts of interest The authors declare no financial or other conflicts of interest.
1249
1250
Editorial
S. Legriela and G. B. Youngb a
Intensive Care Unit, Centre Hospitalier de Versailles – Site
Andr e Mignot, Le Chesnay, France; and bDepartment of Clinical Neurological Sciences, Western University, London, ON, Canada
(e-mail: [email protected])
References 1. Ely EW, Shintani A, Truman B, et al. Delirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA 2004; 291: 1753–1762. 2. Girard TD, Jackson JC, Pandharipande PP, et al. Delirium as a predictor of long-term cognitive impairment in survivors of critical illness. Crit Care Med 2010; 38: 1513–1520. 3. Reade MC, Finfer S. Sedation and delirium in the intensive care unit. N Engl J Med 2014; 370: 444–454.
4. Drouot X, Roche-Campo F, Thille AW, et al. A new classification for sleep analysis in critically ill patients. Sleep Med 2012; 13: 7–14. 5. Watson PL, Pandharipande P, Gehlbach BK, et al. Atypical sleep in ventilated patients: empirical electroencephalography findings and the path toward revised ICU sleep scoring criteria. Crit Care Med 2013; 41: 1958–1967. 6. Sutter R, Barnes J, Leyva A, Kaplan PW, Geocadin RG. Electroencephalographic sleep elements and outcome in acute encephalopathic patients: a 4-year cohort study. Eur J Neurol 2014; 21: 1268–1275. 7. Urakami Y. Relationship between sleep spindles and clinical recovery in patients with traumatic brain injury: a simultaneous EEG and MEG study. Clin EEG Neurosci 2012; 43: 39–47. 8. Caporro M, Haneef Z, Yeh HJ, et al. Functional MRI of sleep spindles and K-complexes. Clin Neurophysiol 2012; 123: 303–309.
© 2014 The Author(s) European Journal of Neurology © 2014 EAN
