Alpha Oscillations Predict Paroxetine Response to Low Sexual Desire in Depression
Background: Decreased sexual desire (libido) is one of the most common sexual complaints in patients with depression. It is known that antidepressants have certain effects on sexual life. Paroxetine is one of those antidepressants. However, the sexual adverse effects of paroxetine are unpredictable. This retrospective study aimed at determining the electrophysiological markers of paroxetine treatment effect on sexual desire in patients with depression (N = 56).
Methods: Quantitative electroencephalography (QEEG) spectral power across all frequency bands were examined in depressed patients with decreased or normal sexual desire. Analysis of covariance was conducted on baseline qEEG, taking attention condition and severity of depression (Hamilton Depression Rating Scale-HDRS) as covariates.
Results: Patients whose sexual desire did not improve had higher frontal alpha power and impaired attention function at baseline examination.
Limitations: The results could be taken as preliminary due to the modest sample size.
Conclusion: Based on the present findings, it can be concluded that frontal alpha power can be a biomarker of lack of libido improvement after treatment with paroxetine.
Mehmet Kemal Arıkan, Reyhan İlhan, Güven Günver, Özden Öksüz, Şenol Turan, Barış Metin. Alpha oscillations predict paroxetine response to low sexual desire in depression. Journal of Affective Disorders Reports 6 (2021) 100222.
Gamma oscillations predict treatment response to aripiprazole in bipolar disorder
Objective: Treatment of Bipolar Disorder (BD) is a challenging issue. Aripiprazole monotherapy is a recommended option for the treatment of mania in BD. The electrophysiological markers of treatment response to aripiprazole could be potentially identified by quantitative Electroencephalography (qEEG).
Methods: Twenty-four patients with BD were analysed retrospectively. Based on the percentage reduction in Young Mania Rating Scale, they were classified as responders (N = 14) and non-responders (N = 10) to aripiprazole monotherapy. Their resting-state qEEG recordings were examined. Spectral power across all frequency bands were calculated. Absolute powers for all frequency bands were compared between these groups.
Results: Independent sample Mann-Whitney U test revealed that patients who did not respond to aripiprazole had greater gamma power than aripiprazole treatment responders.
Conclusions: Based on the present findings, it can be proposed that excess in gamma power could be the electrophysiological biomarkers of unresponsiveness to aripiprazole treatment in BD.
*** Mehmet Kemal Arıkan, Güven Günver, Reyhan İlhan, Özden Öksüz, Baris Metin. Gamma oscillations predict treatment response to aripiprazole in bipolar disorder. Journal of Affective Disorders 294 (2021) 159–162.
A Way to Increase the Sensitivity and Specificity of the Hamilton Depression and Anxiety Scales
Objective: The Hamilton Depression Rating Scale (HDRS-17) and the Hamilton Anxiety Rating Scale (HARS-14) have been acknowledged as gold standards in evaluating the severity of depression and anxiety. The specificity and sensitivity of these scales in predicting somatic complaints of depression and anxiety are issues in both clinical and research areas. The present study proposes a new model to enhance the sensitivity and specificity of HDRS-17 and HARS-14 for predicting symptoms of insomnia, inappetence, and loss of libido in psychiatric patients.
Methods: This study included 1507 patients diagnosed with bipolar disorder, depression, panic disorder, obsessive-compulsive disorder, and generalized anxiety disorder. The HDRS-17 and the HARS-14 were utilized as predictive scales for the prediction of patients’ sleep, appetite, and libido. The sensitivity and specificity were computed using the receiver operating characteristic (ROC). Logistic regression was performed to enhance the predictive values. The predictive value of the logistic regression model was not satisfactory, and a conversion table was therefore designed for each symptom-diagnosis subgroup. The new joint ROC model was then used to recalculate the sensitivity and specificity of the 2 scales for each symptom-diagnosis subgroup. The outcome is a prediction table, presented for use by clinicians.
Results: It was observed that the new statistical model, the joint ROC, increased the sensitivity and specificity of the HDRS-17 and the HARS-14.
Conclusion: Based on the results of the evaluations with the HDRS and the HARS, the joint ROC method was developed to better predict the presence of symptoms.
*** Mehmet Guven Gunver, Mustafa Senocak, Reyhan Ilhan, Hazal Aktas, Sevgi Kilic, Ozden Oksuz, Muhammed Taha Esmeray, Hamide Lacin, Mehmet Kemal Arikan. A Way to Increase the Sensitivity and Specificity of the Hamilton Depression and Anxiety Scales. Psychiatry and Clinical Psychopharmacology 2021. DOI: 10.5152/pcp.2021.21386.
Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus
Objective: Diabetes mellitus (DM) causes structural central nervous system (CNS) impairment, and this situation can be detected by quantitative electroencephalography (QEEG) findings before cognitive impairment is clinically observed. The main aim of this study is to uncover the effect of DM on brain function. Since QEEG reflects the CNS functioning, particularly in cognitive aspects, we expected electrophysiological clues to be found for prevention and follow-up in DM-related cognitive decline. Since a majority of the psychiatric population have cognitive dysfunction, we have given particular attention to those people. It was stated that a decrease was observed in the posterior cortical alpha power due to the hippocampal atrophy by several previous studies and we hypothesize that decreased alpha power will be observed also in DM.
Methods: This study included 2094 psychiatric patients, 207 of whom were diagnosed with DM and 1887 of whom were not diagnosed with DM, and QEEG recordings were performed. Eyes-closed electroencephalography data were segmented into consecutive 2’s epochs. Fourier analysis was performed by averaging across 2 s epochs without artifacts. The absolute alpha power in the occipital regions (O1 and O2) of patients with and without DM was compared.
Results: In the DM group, a decrease in the absolute alpha, alpha 1, and alpha 2 power in O1 and O2 was observed in comparison with the control group. It was determined that the type of psychiatric diagnosis did not affect QEEG findings.
Conclusion: The decrease in absolute alpha power observed in patients diagnosed with DM may be related to the CNS impairment in DM. QEEG findings in DM can be useful while monitoring the CNS impairment, diagnosing DM-related dementia, in the follow-up of the cognitive process, constructing the protocols for electrophysiological interventions like neurofeedback and transcranial magnetic stimulation and monitoring the response to treatment.
*** Özden Öksüz, Mehmet Güven Günver, Mehmet Kemal Arıkan. Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus. Clin EEG Neurosci. 2021 Mar 17;1550059421997657. doi: 10.1177/1550059421997657.
Association of Electroencephalographic Alpha-2 Activity With Fluoxetine Response in Obsessive-Compulsive Disorder
*** Arıkan MK, Günver MG, İlhan R. Association of Electroencephalographic Alpha-2 Activity With Fluoxetine Response in Obsessive-Compulsive Disorder. J Clin Psychopharmacol. 2021 Jan 11. doi: 10.1097/JCP.0000000000001337.
Gamma oscillations predict paroxetine response of patients with Obsessive Compulsive Disorder
Background: Obsessive compulsive disorder is a distressing psychiatric illness with considerable treatment resistance rates. Prediction of treatment response leads to an increase in patient compliance and a decrease in morbidity. To decrease the treatment resistance rates, valid and useful instruments have been searched. Quantitative electroencephalography (QEEG) based markers have been objective predictors of the treatment response in psychiatric disorders.
Aim: This retrospective pilot study aims to explore QEEG as a biomarker to predict early response to paroxetine in OCD patients.
Method: Resting state QEEG and Yale-Brown Obsessive Compulsive Scale (Y-BOCS) were administered to 30 drug-free OCD patients without comorbidity. After maximum 12-week of treatment with paroxetine, patients with and without an early improvement were classified based on at least a 35% reduction in Y-BOCS scores. Pre-treatment QEEG data were compared between the two groups.
Results: Pre-treatment gamma, gamma 1 and gamma 2 oscillations were significantly higher in OCD patients who did not show an early improvement.
Conclusion: These preliminary results indicate that gamma oscillations could be acknowledged as the electrophysiological predictors of early clinical outcomes of OCD patients during paroxetine treatment.
Real-world efficacy of deep TMS for obsessive-compulsive disorder: Post-marketing data collected from twenty-two clinical sites
Background: Deep transcranial magnetic stimulation (dTMS) with the H7-coil was FDA cleared for obsessive-compulsive disorder (OCD) in August 2018 based on multicenter sham-controlled studies. Here we look at the efficacy of dTMS for OCD in real world practices.
Methods: All dTMS clinics were asked to supply their data on treatment details and outcome measures. The primary outcome measure was response, defined by at least a 30% reduction in the Yale Brown Obsessive Compulsive Scale (YBOCS) score from baseline to endpoint. Secondary outcome measures included first response, defined as the first time the YBOCS score has met response criteria, and at least one-month sustained response. Analyses included response rate at the endpoint (after 29 dTMS sessions), number of sessions and days required to reach first response and sustained response.
Results: Twenty-two clinical sites with H7-coils provided data on details of treatment and outcome (YBOCS) measures from a total of 219 patients. One-hundred-sixty-seven patients who had at least one post-baseline YBOCS measure were included in the main analyses. Overall first and sustained response rates were 72.6% and 52.4%, respectively. The response rate was 57.9% in patients who had YBOCS scores after 29 dTMS sessions. First response was achieved in average after 18.5 sessions (SD = 9.4) or 31.6 days (SD = 25.2). Onset of sustained one-month response was achieved in average after 20 sessions (SD = 9.8) or 32.1 days (SD = 20.5). Average YBOCS scores demonstrated continuous reduction with increasing numbers of dTMS sessions.
Conclusions: In real-world clinical practice, the majority of OCD patients benefitted from dTMS, and the onset of improvement usually occurs within 20 sessions. Extending the treatment course beyond 29 sessions results in continued reduction of OCD symptoms, raising the prospect of value for extended treatment protocols in non-responders.
Yiftach Roth, Aron Tendler, Mehmet Kemal Arikan, Ryan Vidrine, David Kent, Owen Muir, Carlene MacMillan, Leah Casuto, Geoffrey Grammer, William Sauve, Kellie Tolin, Steven Harvey, Misty Borst, Robert Rifkin, Manish Sheth, Brandon Cornejo, Raul Rodriguez, Saad Shakir, Taylor Porter, Deborah Kim, Brent Peterson, Julia Swofford, Brendan Roe, Rebecca Sinclair, Tal Harmelech, Abraham Zangen. Journal of Psychiatric Research. November 4, 2020.
Special Report on the Impact of the COVID-19 Pandemic on Clinical EEG and Research and Consensus Recommendations for the Safe Use of EEG
The global COVID-19 pandemic has affected the economy, daily life, and mental/physical health. The latter includes the use of electroencephalography (EEG) in clinical practice and research. We report a survey of the impact of COVID-19 on the use of clinical EEG in practice and research in several countries, and the recommendations of an international panel of experts for the safe application of EEG during and after this pandemic.
Methods: Fifteen clinicians from 8 different countries and 25 researchers from 13 different countries reported the impact of COVID-19 on their EEG activities, the procedures implemented in response to the COVID-19 pandemic, and precautions planned or already implemented during the reopening of EEG activities.
Results: Of the 15 clinical centers responding, 11 reported a total stoppage of all EEG activities, while 4 reduced the number of tests per day. In research settings, all 25 laboratories reported a complete stoppage of activity, with 7 laboratories reopening to some extent since initial closure. In both settings, recommended precautions for restarting or continuing EEG recording included strict hygienic rules, social distance, and assessment for infection symptoms among staff and patients/participants.
Conclusions: The COVID-19 pandemic interfered with the use of EEG recordings in clinical practice and even more in clinical research. We suggest updated best practices to allow safe EEG recordings in both research and clinical settings. The continued use of EEG is important in those with psychiatric diseases, particularly in times of social alarm such as the COVID-19 pandemic.