Collaborative Antwerp Psychiatric Research Institute

Protect

Prediction Of Treatment response to ECT and Cognitive side effecTs.

Project title

PROTECT: PRediction Of Treatment response to ECT and Cognitive side effecTs.

Project description

The current project is designed to allow better prediction of ECT-response. We base our selection of predictors on clinical impression and previous research results. The predictive capacity of psychomotor functioning, psychotic symptoms and several biomarkers will be investigated.

Project duration

01/02/2014 - 31/12/2019

Promotor

Bernard Sabbe

Didier Schrijvers

PhD Researcher

Linda Van Diermen

Jean-Baptiste Belge

Team

Violette Coppens, Eline Schellens, Ingrid Vanderplas, Sarah Debruyne

Contact

For more information please contact Didier Schrijvers:

Tel. n°: 015304189

E-mail: Didier.schrijvers@uantwerpen.be

Publications

  • Baeten RF, Van Rossum EFC, De Rijke YB, Sabbe BGC, Van Der Mast RC, Belge JB, et al. Hair cortisol in patients with a depressive episode treated with electroconvulsive therapy. J Affect Disord. 2020;274:784-91.
  • Belge JB, van Diermen L, Sabbe B, Parizel P, Morrens M, Coppens V, et al. Inflammation, Hippocampal Volume, and Therapeutic Outcome following Electroconvulsive Therapy in Depressive Patients: A Pilot Study. Neuropsychobiology. 2020;79(3):222-32.
  • Belge JB, Van Diermen L, Schrijvers D, Sabbe B, Constant E, de Timary P, et al. The basal ganglia: A central hub for the psychomotor effects of electroconvulsive therapy. J Affect Disord. 2020;265:239-46.
  • van Diermen L, Hebbrecht K, Schrijvers D, Sabbe BCG, Fransen E, Birkenhäger TK. The Maudsley Staging Method as predictor of electroconvulsive therapy effectiveness in depression. Acta Psychiatr Scand. 2018;138(6):605-14.
  • van Diermen L, van den Ameele S, Kamperman AM, Sabbe BCG, Vermeulen T, Schrijvers D, et al. Prediction of electroconvulsive therapy response and remission in major depression: meta-analysis. Br J Psychiatry. 2018;212(2):71-80.
  • van Diermen L, van den Ameele S, Kamperman AM, Sabbe BCG, Vermeulen T, Schrijvers D, et al. Prediction of Electroconvulsive Therapy Response and Remission in Major Depression: Meta-analysis - CORRIGENDUM. Br J Psychiatry. 2018;212(5):322.
  • van Diermen L, Vanmarcke S, Walther S, Moens H, Veltman E, Fransen E, et al. Can psychomotor disturbance predict ect outcome in depression? J Psychiatr Res. 2019;117:122-8.
  • van Diermen L, Versyck P, van den Ameele S, Madani Y, Vermeulen T, Fransen E, et al. Performance of the Psychotic Depression Assessment Scale as a Predictor of ECT Outcome. J ect. 2019;35(4):238-44.

Summary

It has been convincingly demonstrated that electroconvulsive therapy (ECT) works better and sooner than antidepressants in the treatment of certain subtypes of depression. Given this effectiveness, it would be unfortunate not to give ECT to patients with good response chances as this could substantially shorten the length of a severe depressive episode. Instead of going through all possible psychopharmacological treatment steps, ECT could be proposed much earlier as a treatment option for those patients who might have good response chances. This would be a great advantage for the severely depressed patient, with a decreased disease-burden and hospitalization duration. Moreover, long-term results may improve in these patients.

However, up to now, objective and reliable predictive factors for good ECT response have not yet been established. Clinical characteristics such as psychomotor retardation, psychotic features and age have often been used to predict the outcome of ECT, but there is too little evidence to consider these as strong predictive factors.

The current project is designed to allow better prediction of ECT-response. We base our selection of predictors on clinical impression and previous research results. The predictive capacity of psychomotor functioning, psychotic symptoms and several biomarkers will be investigated. With these clinical and biological patient and depression characteristics, we aim to develop a decision making tool that will allow a more accurate indication of ECT.

We also investigate ways to predict whether or not a patient will have a good response when treatment has already started, based on an early improvement of psychomotor functioning.

Another subject of great importance is predicting and preventing side-effects. When patients at risk for lasting cognitive side-effects can be identified early in the treatment course, treatment can be adjusted to prevent persistence of memory problems. Therefore, the second part of our study focuses on identifying people at risk for cognitive side effects early in the treatment course.