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Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice

Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice

Ronald J. Swatzyna, Ph.D. – BCN (Associate Fellow), Director of Electrophysiological Research, The Tarnow Center for Self-Management, Houston, TX

Jay D. Tarnow, M.D. – Director for The Tarnow Center for Self-Management, Houston, TX

Jonika D. Tannous, B.S. – Statistical Research Intern, Rice University, The Tarnow Center for Self-Management, Houston, TX

Vijayan Pillai, Ph.D. – Professor, The University of Texas at Arlington Graduate School of Social Work, Arlington, TX

Christina Schieszler, B.S. – Research Intern, The University of Houston Graduate College of Social Work, The Tarnow Center for Self-Management, Houston, TX

Gerald P. Kozlowski, Ph.D. – BCN (Certified Senior Fellow), Faculty Member Department of Clinical Psychology, Saybrook University, San Francisco, CA

Abstract

Pharmaco-EEG studies using clinical electroencephalograms (EEG) and quantitative EEG (qEEG) technologies have existed for over four decades. This is a promising area which could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect electroencephalography (EEG) and quantitative EEG (qEEG) data. In the past five years, we have identified a subset of refractory cases (n=386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders. Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher’s Exact Test and Binary Logistics Regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection.

Psychiatry does well in many instances: however there are perplexing cases that do not respond to traditional psychotropic intervention. Many abnormalities seen in the EEG are considered normal variants in the general population; however, minor abnormalities are important when clinical correlation exists. The utilization of EEG and qEEG, together with clinical presentation to identify neurobiomarkers has the potential to link neuronal irregularities with presenting symptom separately for each age group.

Results

  • N = 386 clinical cases: Ages 5-11 (n = 119), 12 – 17 (n = 105), and 18 – 69 (n = 162).
  • All cases were refractory, failing on at least two attempts of psychotropicintervention.

There were four emerging neurobiomarkers in these cases:

  • Encephalopathy (EN) can be defined as an organic diffuse disturbance in brain function producing neurological and psychological manifestations.
  • Focal Slowing (FS) is characterized by a predominance of slower electrical activity in a particular area of the brain.
  • Beta Spindles (BS) are identified as synchronous activity in the beta range around  a specific frequency and are indicative of hyper-arousal and most often seen fronto-centrally.
  • Transient Discharges (TD) are defined as EEG cerebral dysrhythmias identified by isolated episodic paroxysmal bursts of slow activity, controversial/anomalous spikey waveforms and/or true non-controversial epileptiform discharges.

There were two diagnoses and two diagnostic categories analyzed in this study:

  • Attention Deficit Hyperactivity Disorder (ADD)
  • Autistic Spectrum Disorder (ASD)
  • Depressive Disorders (DEP)
  • Anxiety Disorders (ANX)

The relationship between the diagnoses and the neurobiomarkers identified was examined separately for each age group.

Findings: Equally across all three age groups, there is very poor association (6.25%) between the patient’s diagnosis and the neurobiomarker responsible for their symptoms.

Table 1: Fisher’s Exact Test Signifigant P Values **

ADD ASD DEP ANX
Children

5 – 11

N=119

EN

FS

BS

TD

.209

.811

.093

1.00

.325

.538

.203

1.00

.788

.724

.588

.819

.003**

.620

.619

.836

Adolescents

12-17

N=105

EN

FS

BS

TD

.612

.757

.619

1.00

.070

.470

.560

.789

.732

.384

.019**

.067

.262

.619

.420

.207

Adults

18-69

N=162

EN

FS

BS

TD

.371

.621

.480

.108

.788

.436

.209

.536

.341

.384

.008**

.610

.063

.865

.865

.618

Table 2: Binary Logistics Regression Signifigant P Values **

ADD ASD DEP ANX
Children

5 – 11

N=119

EN

FS

BS

TD

.138

.457

.050

.984

.370

.741

.224

.860

.778

.131

.483

.550

.019**

.654

.826

.909

Adolescents

12-17

N=105

EN

FS

BS

TD

.445

.752

.521

.988

.036

.279

.486

.460

.282

.709

.010**

.062

.210

.420

.374

.123

Adults

18-69

N=162

EN

FS

BS

TD

.394

.298

.273

.080

.740

.201

.110

.339

.159

.765

.006**

.394

.067

.916

.892

.708

Discussion

  • The Fisher’s Exact Test showed only 3 significant findings out of 48 possible combinations.
  • The same three combinations identified by Fisher’s Exact Test were found to be significant using binary regression analysis. Children with EN were 11 times less likely to have ANX. In adolescents, those with BS were over five times more likely to be diagnosed with MDD. Likewise, adults with BS were three times more likely to be diagnosed with MDD. No other significant relationships were identified.

Conclusions

  • When used separately, an EEG, a qEEG, and clinical presentation lacks synergy.
  • However, when all three are combined in the hands of an experienced psychiatrist, the shortcomings of each are minimized.
  • Therefore, EEG and qEEG technologies can identify and quantify neuronal irregularities that reflect brain dysfunction causing clinically correlated psychiatric pathologies.
  • Using this neurobiomarker model across all age groups, we found evidence explaining why the medications tried previously had failed.
  • If left unidentified, any substantial improvement in psychiatric medication management and efficacious treatment planning would be thwarted.
  • Experienced psychiatrists who use this technology to assist in medication  selection have a great advantage.

Prior Meeting Presentations

  • International Society for Neurofeedback & Research 21st Annual Conference, September 2013, Dallas, Texas, USA
  • Biofeedback Federation of Europe 17th Annual Meeting, February, 2014, Venice, Italy
  • Joint Meeting of the EEG & Clinical Neuroscience Society (ECNS), the Society for Neuroimaging in Psychiatry (ISNIP), and the International Society for Brain Electromagnetic Topography (ISBET) September, 2014, Halifax, Nova Scotia, Canada
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Techniques Effecting the LORETA Source Solution

LORETA can be done in a few ways… as a source analysis for the entire EEG or segment being analyzed… or after a decomposition into the ICA components… The later will provide a better estimate of generators of the
individual components which are all blended for the overall LORETA, distorting the sources with other sources. Continue reading →

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Prof. Juri D. Kropotov Interview 2013

Juri speaks about the recent ERP meeting in St Petersburg Russia, held during the summer’s “white nights” when the night sky does not darken fully and the night is very short. Juri is interviewed in his offices, only 200 meters from Pavlov’s famous laboratory.

The discussion of the new methodology of ICA decomposition of the ERP, as well as the benefit of ERP added to the EEG/qEEG is discussed. There is discussion of the diagnostic specificity of the ERP methods, and the concept of biomarkers.

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Medication Failure: EEG/qEEG Findings Provide Evidence

This is the PowerPoint “Medication Failure: EEG/qEEG Findings Provide Evidence” as presented at ISNR Conference Workshop 20 September 21, 2013

Presented by:
Ronald J. Swatzyna, Ph.D., L.C.S.W.
The Tarnow Center for Self-Management
drron@tarnowcenter.com

Vijayan K. Pillai, Ph.D.
The University of Texas at Arlington
pillai@uta.edu

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FDA Approval of EEG Aid for ADHD

There has been a lot of discussion since the FDA announced approving a new medical device just approved to assist in the diagnosis of ADHD in children and adolescents. “The device, the Neuropsychiatric EEG-Based Assessment Aid (NEBA) System, is based on electroencephalogram technology, which records different kinds of electrical impulses given off by neurons in the brain and the number of times the impulses are given off each second. The NEBA System is a 15- to 20-minute noninvasive test that calculates the ratio of two standard brain-wave frequencies, known as theta and beta waves; the ratio has been shown to be higher in children and adolescents with ADHD than in those without it, according to FDA” (http://alert.psychiatricnews.org/2013/07/ fda-approves-device-to-help-diagnose.html). However, the use of this technology to assist in the diagnosis of ADHD is not new.

David Rabiner, Ph.D. (Senior Research Scientist, Duke University) published a report (Attention Research Update April 2001) titled “New Support for the Use of qEEG scanning in Diagnosing ADHD” (http://www.helpforadd.com/2001/april.htm). This report acknowledged utilizing the measure of the ratio of theta to beta waves in the prefrontal cortex as a marker for ADHD (ages 6-20). Therefore the technology is not new, and although the NEBA System is helping to bring scientific evidence into the realm of psychiatric diagnosis, there is more to it then has been discussed thus far. Continue reading →

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Technology Helps Explain Medication Failure

In almost every area of medicine, doctors can order tests to provide objective physical data to guide their medication selection. However, the practice of psychiatry is most often based on observation, self-report and psychological testing. It appears that we are better at measuring impairment than we are at identifying the source and prescribing an effective medication. Is there a way we can do better?

The director of the National Institute of Mental Health, Tomas Insel, suggests there are many medicines, but they are not working adequately. This is because the symptoms of mental illness are too illusive and are shared by many diagnoses. Insel (2012) says, “It’s much harder to fix something if you don’t know what is going wrong.” Medications are being prescribed to treat a set of symptoms suggestive of a specific disorder without any objective evidence of the cause. Additionally, the practice of polypharmacy has become way too common in children and adolescents.

Pharmaceutical industry advertising promotes adding a medication when the first medication fails to produce the desired results (i.e., adding Abilify to your antidepressant). The message is that when one medication fails, keep adding more in an effort to address the additional symptoms. Each additional medication increases the risk of side effects. It is not uncommon for children to come to us with several medications prescribed. Last month, for example, we saw a 9-year-old female with prescriptions for Olanzapine three times a day, Lithium Carbonate daily and Amphetamine Salts three times a day. Also, a 10-year-old male came to us on Focolin three times a day, Seroquel twice a day, Lexipro daily and Zyprexa daily. If there was a way to determine why a medication failed, would it not be prudent to investigate why? If current technology could help? Continue reading →

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Electroencephalography (EEG) Underused Investigative Tool in Hospitals, Study Finds

child eeg Electroencephalography (EEG) Underused Investigative Tool in Hospitals, Study Finds

A retrospective study of patients who had in-hospital electroencephalography (EEG) has established that EEG is a valuable tool that could be deployed more widely to identify treatable causes of impaired consciousness in the hospital setting.

The study is published in the April issue of the Mayo Clinic Proceedings.

Altered mental status (AMS) and paroxysmal spells of uncertain origin are common among hospitalized patients. Impaired consciousness can sometimes be linked to metabolic or cardiac causes, but some of these spells may represent seizures or non-convulsive epilepsy, which can be detected only by electroencephalography (EEG). Although EEG is the key test in making these diagnoses, it is relatively underused in the inpatient setting owing to lack of availability and neurologic consultation at many hospitals in the United States. Continue reading →

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Association between ADHD and intensity of sunlight: Can ADHD be prevented?

kids in sun Association between ADHD and intensity of sunlight: Can ADHD be prevented?

Nijmegen, March 26th, 2013 – A study published today in Biological Psychiatry sheds new light on the increasing rates (prevalence) of attention-deficit/hyperactivity disorder, known as ADHD. Children with ADHD have problems with inattention, distractibility, disorganization, impulsiveness, and overactivity. This study found that “sunny” regions with high solar intensity, such as the US states of California, Arizona, and Colorado, and countries like Spain and Mexico have lower prevalence of ADHD. An apparent protective effect of sunlight accounted for 34-57% of the variance in ADHD prevalence. The authors speculate that this may be related to sunlight’s effects on preventing circadian rhythm (“biological clock”) disturbances. These results suggest ways to prevent or treat ADHD for a substantial sub-group of patients…

Read the article here.

Read the full PDF paper “Geographic Variation in the Prevalence of Attention-Deficit/Hyperactivity Disorder: The Sunny Perspective” by Martijn Arns, Kristiaan B. van der Heijden, L. Eugene Arnold, and J. Leon Kenemans.

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National Institute for Health and Clinical Excellence (NHS NICE) has published final guidance recommending the use of brain monitoring technology

The healthcare guidance body NICE (National Institute for Health and Clinical Excellence (NHS NICE) has published final guidance recommending the use of brain monitoring technology such as the Bispectral Index (BIS, Covidien), E-Entropy (GE Healthcare) and Narcotrend-Compact M (MT MonitorTechnik GmbH & Co).  These EEG-based depth of anaesthesia monitors should be considered as positive options in patients receiving total intravenous anaesthesia (TIVA) and in patients who are considered at higher risk of adverse outcomes during any type of general anaesthesia, such as seniors, those with high body mass index, and those with cardiovascular and liver disease.

EEG based Brain Monitoring Systems helps clinicians assess patient consciousness levels through measuring the electrical activity in the brain. This includes patients who are at higher risk of unintended awareness (anesthesia too light) and also those patients who are at higher risk from excessively deep anaesthesia.

Superior surgical outcomes, the low cost of the testing and the ease of use of these technologies all contribute to the recommendations.

You can access these documents through ASET (www.ASET.org)

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Move up to modern de-artifacting

There is an on-going dispute regarding de-artifacting methods used in qEEG.  Though there are vested interests counseling against the use of modern techniques to remove artifact while leaving the underlying EEG intact, there are also those who have specialized in the area that can provide a detailed reply to the vested interests.  Just such a reply was posted recently in a commercial list server, and we got the author’s permission to re-post the discussion on the qEEGSupport.com website in a non-commercial publicly accessible form for all to see.

It specifically points to the fact that the phase changes seen are due to removal of artifact, not the distortion of the underlying EEG, which has residual subtle artifacts remaining if processed with classical approaches.

If you cut time segments out of the EEG to remove artifacts, you also remove the underlying connectivity information, splicing discontinuous microstates together destroys the underlying time series.

In the give and take of the real world of neuroscience, the need to provide a valid time-series showing the connectivity of the neural networks, yet free of artifact, is driving the need to switch to more modern techniques than snipping out segments of time.  If you want to distort the timeline of the EEG (phase) just cut and paste lots of EEG together in one second chunks.

The neuroscience community will undoubtedly continue to discuss these issues, but the need for clean valid EEG is driving the field to these newer techniques, and they are performing well under the scrutiny.

Jay Gunkelman Continue reading →

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