Prediction of the Cognitive Effects of Electroconvulsive Therapy Via Machine Learning and Neuroimaging

Depression Clinical Trial

— CoEffECT  

Official title:

Prediction of the Cognitive Effects of Electroconvulsive Therapy Via Machine Learning and Neuroimaging

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT03490149
• Other study ID #: CoEffECT - Study
• Status: Recruiting
• Start date: January 2, 2018
• Est. completion date: December 1, 2022

Study information

• Verified date: May 2022
• Source: University Hospital, Bonn
• Contact: Maximilian Kiebs, M.Sc.
• Phone: 0049228287
• Email: m.kiebs[@]ukbonn.de
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The study aims to use machine learning to predict the occurrence of episodic and autobiographical memory deficits as well as treatment response following a course of electroconvulsive therapy. Additionally, the neurophysiological correlates of the cognitive effects after a course of ECT will be investigated. Therefore, structural, resting-state and diffusion tensor images will be collected within one week before the first and after the last ECT treatment from severely depressed patients. Standard measures of cognitive function and specifically episodic as well as autobiographical memory will also be collected longitudinally and used for prediction. The study consists of 60 ECT receiving inpatients suffering from major unipolar or bipolar depression, 60 medication-only controls and 60 healthy controls.

Description:

Due to the immense disease burden of major depression and unsatisfactory response to standard pharmacological and psychological treatments, the need for treatment alternatives is evident. Electroconvulsive therapy (ECT) remains to be the most efficacious treatment known for treatment-resistant depression. However, although many studies show response rates above 70%, ECT can be considered vastly underused. Reasons contributing to this phenomenon may include stigma, regulatory restrictions, limited medical training, safety and side-effect concerns, or reluctance among professionals to recommend ECT. Most of these reasons have already been refuted or put into perspective by psychological and neuroscientific studies (e.g. ECT causes brain lesions) and most cognitive deficits related to the ECT course seem to fade after several weeks of discontinuation. Still, in terms of the tolerability, memory disturbances remain the most problematic effect of ECT. Besides subjective reports from patients after a course of ECT, experimental studies have also found evidence of episodic and autobiographical memory impiarment attributable to ECT. The origins of these effects are still largely unknown and remain a goal for further research. It has now been shown that structural T1 weighted MR-images can be used to predict the response to a course of ECT via machine learning. Therefore, this study aims to use machine learning to predict the occurrence of episodic and specifically autobiographical memory deficits arising within a course of electroconvulsive therapy based on MR-images collected within one week before the first ECT treatment from severely depressed patients. Additionally, the neurophysiological correlates of the cognitive effects modulated by a course of ECT will be investigated longitudinally through the use of structural, resting-state and diffusion tensor images. The study consists of 60 ECT receiving inpatients suffering from major unipolar or bipolar depression. If successful, this line of research should lead to a better tolerability of ECT by aiding in the complex decision making process involved in prescribing ECT as well as the parameter setting within a treatment course (e.g. uni- vs. bilateral).

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 180
• Est. completion date: December 1, 2022
• Est. primary completion date: December 1, 2021
• Gender: All
• Age group: 18 Years to 85 Years

Eligibility

Inclusion Criteria:

• The duration of the current depressive episode is at least four weeks
• The duration of the current depressive episode is less than five years
• Inpatients of the psychiatric clinic of the University Hospital Bonn and eligible for ECT because of major depressive disorder or major depressive episode in bipolar disorder (according to DSM-5 criteria)
• Score on HDRS 28 = 20
• Ability to understand the purpose of and procedures required for the study and willingness to consent to participation
• Meeting of standard medical prerequisites for ECT (judged by staff psychiatrist)
• Ability to speak and understand the german language

Exclusion Criteria:

• No lifetime occurence of a personality disorder
• Current (or within the last year) posttraumatic stress disorder
• Schizophrenia or any other psychotic disorder except for psychotic depression
• Severe somatic or neurological condition (e.g. stroke)
• Head trauma resulting in unconsciousness for more than 5 minutes
• Pregnancy
• Maintenance ECT or ECT received during the last 6 month
• Subjects who do not consent to be informed of incidental findings that could have healthcare implications
• Drug or alcohol dependence (<6 month before ECT)
• Is currently enrolled in a study with an investigational study drug
• Has any condition that, in the opinion of the investigator, would compromise the wellbeing of the subject or the study or prevent the subject from meeting or performing study requirements

Related Conditions & MeSH terms

• Cognitive Impairment
• Depression
• ECT
• Memory Impairment

Intervention

Device:
• Electroconvulsive Therapy
Series of electroconvulsive therapy for major depressive disorder

Drug:
• Medication - Treatment as usual
Medication only sample - Treatment as usual

Locations

Country	Name	City	State
Germany	Klinik und Poliklinik für Psychiatrie und Psychotherapie	Bonn	Nordrhein-Westfalen

Sponsors (2)

Lead Sponsor	Collaborator
University Hospital, Bonn	Maximilian Kiebs, M.Sc. - University Hospital Bonn (Department of Medical Psychology)

Country where clinical trial is conducted

Germany, 

References & Publications (19)

Aoki Y, Yamaguchi S, Ando S, Sasaki N, Bernick PJ, Akiyama T. The experience of electroconvulsive therapy and its impact on associated stigma: A meta-analysis. Int J Soc Psychiatry. 2016 Dec;62(8):708-718. Epub 2016 Oct 26. Review. — View Citation

Bailine S. Reimbursement and documentation issues in an ambulatory ECT program. J ECT. 1998 Dec;14(4):255-8. — View Citation

Case BG, Bertollo DN, Laska EM, Price LH, Siegel CE, Olfson M, Marcus SC. Declining use of electroconvulsive therapy in United States general hospitals. Biol Psychiatry. 2013 Jan 15;73(2):119-26. doi: 10.1016/j.biopsych.2012.09.005. Epub 2012 Oct 8. — View Citation

Dwork AJ, Arango V, Underwood M, Ilievski B, Rosoklija G, Sackeim HA, Lisanby SH. Absence of histological lesions in primate models of ECT and magnetic seizure therapy. Am J Psychiatry. 2004 Mar;161(3):576-8. — View Citation

Haq AU, Sitzmann AF, Goldman ML, Maixner DF, Mickey BJ. Response of depression to electroconvulsive therapy: a meta-analysis of clinical predictors. J Clin Psychiatry. 2015 Oct;76(10):1374-84. doi: 10.4088/JCP.14r09528. — View Citation

Lisanby SH, Maddox JH, Prudic J, Devanand DP, Sackeim HA. The effects of electroconvulsive therapy on memory of autobiographical and public events. Arch Gen Psychiatry. 2000 Jun;57(6):581-90. — View Citation

Payne NA, Prudic J. Electroconvulsive therapy: Part I. A perspective on the evolution and current practice of ECT. J Psychiatr Pract. 2009 Sep;15(5):346-68. doi: 10.1097/01.pra.0000361277.65468.ef. Review. — View Citation

Prudic J, Peyser S, Sackeim HA. Subjective memory complaints: a review of patient self-assessment of memory after electroconvulsive therapy. J ECT. 2000 Jun;16(2):121-32. Review. — View Citation

Redlich R, Opel N, Grotegerd D, Dohm K, Zaremba D, Bürger C, Münker S, Mühlmann L, Wahl P, Heindel W, Arolt V, Alferink J, Zwanzger P, Zavorotnyy M, Kugel H, Dannlowski U. Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data. JAMA Psychiatry. 2016 Jun 1;73(6):557-64. doi: 10.1001/jamapsychiatry.2016.0316. — View Citation

Sackeim HA. Autobiographical memory and electroconvulsive therapy: do not throw out the baby. J ECT. 2014 Sep;30(3):177-86. doi: 10.1097/YCT.0000000000000117. — View Citation

Sackeim HA. Memory and ECT: from polarization to reconciliation. J ECT. 2000 Jun;16(2):87-96. Review. — View Citation

Sackeim HA. Modern Electroconvulsive Therapy: Vastly Improved yet Greatly Underused. JAMA Psychiatry. 2017 Aug 1;74(8):779-780. doi: 10.1001/jamapsychiatry.2017.1670. — View Citation

Semkovska M, McLoughlin DM. Objective cognitive performance associated with electroconvulsive therapy for depression: a systematic review and meta-analysis. Biol Psychiatry. 2010 Sep 15;68(6):568-77. doi: 10.1016/j.biopsych.2010.06.009. Epub 2010 Jul 31. Review. — View Citation

Sinyor M, Schaffer A, Levitt A. The sequenced treatment alternatives to relieve depression (STAR*D) trial: a review. Can J Psychiatry. 2010 Mar;55(3):126-35. Review. — View Citation

Slade EP, Jahn DR, Regenold WT, Case BG. Association of Electroconvulsive Therapy With Psychiatric Readmissions in US Hospitals. JAMA Psychiatry. 2017 Aug 1;74(8):798-804. doi: 10.1001/jamapsychiatry.2017.1378. — View Citation

UK ECT Review Group. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet. 2003 Mar 8;361(9360):799-808. Review. — View Citation

Whiteford HA, Degenhardt L, Rehm J, Baxter AJ, Ferrari AJ, Erskine HE, Charlson FJ, Norman RE, Flaxman AD, Johns N, Burstein R, Murray CJ, Vos T. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet. 2013 Nov 9;382(9904):1575-86. doi: 10.1016/S0140-6736(13)61611-6. Epub 2013 Aug 29. Review. — View Citation

Wilhelmy S, Rolfes V, Grözinger M, Chikere Y, Schöttle S, Groß D. Knowledge and attitudes on electroconvulsive therapy in Germany: A web based survey. Psychiatry Res. 2018 Apr;262:407-412. doi: 10.1016/j.psychres.2017.09.015. Epub 2017 Sep 11. — View Citation

Wilkinson D, Daoud J. The stigma and the enigma of ECT. Int J Geriatr Psychiatry. 1998 Dec;13(12):833-5. — View Citation

* Note: There are 19 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in auditory verbal learning performance	Auditory Verbal Learning Test (AVLT)	Within one week before first and one week after last ECT
Primary	Change in autobiographical memory performance	Autobiographical Memory Interview (AMI-SF)	Within one week before first and one week after last ECT
Primary	Change in subjective memory impairment	Qualitative Interview	Within one week before first and one week after last ECT
Primary	Occurence of retrograde amnesia		Within the first week after last ECT
Secondary	Change in depression severity as measured by the Hamilton Depression Rating Scale (HDRS 28).	Hamilton Depression Rating Scale (HDRS 28). Remission defined as Hamilton Depression Rating Scale-28 score of less than or equal to 9 after the ECT course. Response defined as min. -50% change in Hamilton Depression Rating Scale-28 score after ECT.	One week before first and one week after last ECT
Secondary	Change in depression severity as measured by the Montgomery-Åsberg Depression Rating Scale (MADRS)	Montgomery-Åsberg Depression Rating Scale (MADRS). Remission defined as Montgomery-Åsberg Depression Rating Scale score of less than or equal to 7 after the ECT course. Response defined as min. -50% change in Montgomery-Åsberg Depression Rating Scale score after ECT.	One week before first and one week after last ECT