Clinical characteristics associated with relapse 2 years after electroconvulsive therapy for major depression

Objective: High relapse rates are observed after electroconvulsive therapy (ECT) for major depression. Identifying patients who are at increased risk for relapse to intensify their treatment regimen post-ECT might reduce relapse rates. We aimed to determine clinical characteristics that are associated with relapse within 2 years after successful ECT. Methods: Patients who remitted to ECT in a randomised controlled trial comparing adjuvant nortriptyline and placebo during a course of bilateral ECT were followed-up prospectively for 1 year with open-label nortriptyline (Dutch Trial Register NTR5579). Second-year follow-up data were collected retrospectively. Thirty-four patients were included in this follow-up cohort. To examine the association between clinical characteristics and the risk of relapse, unadjusted hazard ratios (HRs) were calculated. Results: At 2 years post-ECT, the overall relapse rate was 50%, and the HRs for relapse in patients with psychotic features, a higher severity of depression, and medication resistance prior to ECT were 0.33 (CI 0.12–0.89; p = 0.029), 0.88 (CI 0.80–0.98; p = 0.014), and 4.48 (CI 1.28–15.73, p = 0.019), respectively. No effect was found for age, sex or episode duration on the relapse rate. Conclusions: Depressed patients with psychotic features, with higher symptom severity and without medication resistance prior to ECT have a significantly decreased risk of relapse after successful ECT. A sustained remission rate of 50% over 2 years in patients with severe major depression who were treated with nortriptyline monotherapy after successful ECT is encouraging.</p

Influence of an adjuvant antidepressant on the efficacy of electroconvulsive therapy: A systematic review and meta-analysis

Objective: The primary indication for electroconvulsive therapy is medication-resistant major depression. There is some evidence that combining electroconvulsive therapy with an antidepressant, instead of electroconvulsive therapy monotherapy, might improve remission rates. However, data on this topic have not been systematically studied. We undertook a systematic review and meta-analysis to determine the effectiveness of an adjuvant antidepressant during electroconvulsive therapy for major depression. Methods: Embase, Medline Ovid, Web of Science, Cochrane Central, PsychINFO Ovid and Google Scholar were searched up to January 2019. Randomized controlled trials and cohort studies reporting on the influence of an adjuvant antidepressant on the efficacy of electroconvulsive therapy for major depression were included. Authors independently screened records, extracted data and assessed study quality. We reported this systematic review and meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results: Nine studies were included in the meta-analysis. The meta-analysis revealed a significant advantage of adjuvant antidepressants versus placebo. The overall effect size per category of antidepressant was as follows: tricyclic antidepressants: Hedges’ g 0.32 (95% confidence interval: [0.14, 0.51]) (k = 6) with low heterogeneity (I2: 4%, p = 0.39); selective serotonin reuptake inhibitors/serotonin noradrenaline reuptake inhibitors: Hedges’ g 0.27 (95% confidence interval: [0.03, 0.52]) (k = 2) with a lack of heterogeneity (I2: 0%, p = 0.89); and monoamine oxidase inhibitors: Hedges’ g 0.35 (95% confidence interval: [−0.07, 0.77]) with moderate heterogeneity (I2: 43%, p = 0.17) (k = 3). Conclusion: An adjuvant antidepressant enhances the efficacy of electroconvulsive therapy for major depression. Tricyclic antidepressants, selective serotonin reuptake inhibitors/serotonin noradrenaline reuptake inhibitors and monoamine oxidase inhibitors showed the same effect size. However, the effect sizes of tricyclic antidepressants and monoamine oxidase inhibitors are most likely underestimated, due to insufficient doses in most of the included studies. We recommend the routine use of an adequately dosed antidepressant during electroconvulsive therapy for major depression

Prediction of electroconvulsive therapy response and remission in major depression: Meta-analysis

Electroconvulsive therapy (ECT) is considered to be the most effective treatment in severe major depression. The identification of reliable predictors of ECT response could contribute to a more targeted patient selection and consequently increased ECT response rates. Aims To investigate the predictive value of age, depression severity, psychotic and melancholic features for ECT response and remission in major depression. Method A meta-analysis was conducted according to the PRISMA statement. A literature search identified recent studies that reported on at least one of the potential predictors. Results Of the 2193 articles screened, 34 have been included for metaanalysis. Presence of psychotic features is a predictor of ECT remission (odds ratio (OR) = 1.47, P = 0.001) and response (OR = 1.69, P < 0.001), as is older age (standardised mean difference (SMD) = 0.26 for remission and 0.35 for response (P < 0.001)). The severity of depression predicts response (SMD = 0.19, P = 0.001), but not remission. Data on melancholic symptoms were inconclusive. Conclusions ECT is particularly effective in patients with depression with psychotic features and in elderly people with depression. More research on both biological and clinical predictors is needed to further evaluate the position of ECT in treatment protocols for major depression

Prediction of electroconvulsive therapy response and remission in major depression: meta-analysis

Abstract: Background Electroconvulsive therapy (ECT) is considered to be the most effective treatment in severe major depression. The identification of reliable predictors of ECT response could contribute to a more targeted patient selection and consequently increased ECT response rates. Aims To investigate the predictive value of age, depression severity, psychotic and melancholic features for ECT response and remission in major depression. Method A meta-analysis was conducted according to the PRISMA statement. A literature search identified recent studies that reported on at least one of the potential predictors. Results Of the 2193 articles screened, 34 have been included for metaanalysis. Presence of psychotic features is a predictor of ECT remission (odds ratio (OR) = 1.47, P = 0.001) and response (OR = 1.69, P < 0.001), as is older age (standardised mean difference (SMD) = 0.26 for remission and 0.35 for response (P < 0.001)). The severity of depression predicts response (SMD = 0.19, P = 0.001), but not remission. Data on melancholic symptoms were inconclusive. Conclusions ECT is particularly effective in patients with depression with psychotic features and in elderly people with depression. More research on both biological and clinical predictors is needed to further evaluate the position of ECT in treatment protocols for major depression

Tethering Cells via Enzymatic Oxidative Crosslinking Enables Mechanotransduction in Non-Cell-Adhesive Materials

Cell–matrix interactions govern cell behavior and tissue function by facilitating transduction of biomechanical cues. Engineered tissues often incorporate these interactions by employing cell-adhesive materials. However, using constitutively active cell-adhesive materials impedes control over cell fate and elicits inflammatory responses upon implantation. Here, an alternative cell–material interaction strategy that provides mechanotransducive properties via discrete inducible on-cell crosslinking (DOCKING) of materials, including those that are inherently non-cell-adhesive, is introduced. Specifically, tyramine-functionalized materials are tethered to tyrosines that are naturally present in extracellular protein domains via enzyme-mediated oxidative crosslinking. Temporal control over the stiffness of on-cell tethered 3D microniches reveals that DOCKING uniquely enables lineage programming of stem cells by targeting adhesome-related mechanotransduction pathways acting independently of cell volume changes and spreading. In short, DOCKING represents a bioinspired and cytocompatible cell-tethering strategy that offers new routes to study and engineer cell–material interactions, thereby advancing applications ranging from drug delivery, to cell-based therapy, and cultured meat

Microgel Technology to Advance Modular Tissue Engineering

The field of tissue engineering aims to restore the function of damaged or missing tissues by combining cells and/or a supportive biomaterial scaffold into an engineered tissue construct. The construct’s design requirements are typically set by native tissues – the gold standard for tissue engineers. Closely observing native tissues from an engineering perspective reveals a complex multiscale modular design. This natural architecture is essential for proper tissue functioning, but not trivial to manufacture. Recapitulating the complexity of native tissues requires high-resolution manufacturing technologies such as microfluidics. However, increasing resolution is typically at the cost of production throughput and vice versa, which hampers the clinical translation of complex tissue engineering strategies. New advanced concepts that integrate both high-resolution and rapid additive manufacturing techniques are thus prerequisite to upgrade the field of modular tissue engineering. This thesis describes: i) the development of various innovative biomaterials and microfluidic platforms for the production of (cell-laden) hydrogel microparticles (i.e. microgels) that act as tissue engineering building blocks; ii) the modification of microgels with in situ tunable biomechanical and biochemical properties to enable specific tailoring of the cellular microenvironment; iii) their incorporation into modular bio-inks, which is a novel concept to enable the facile engineering of complex tissues using standard biofabrication methods; and iv) the invention of a platform technology called ‘in-air microfluidics’ (IAMF), which uniquely enables the chip-free micromanufacturing of droplets, particles, and 3D modular biomaterials at rates that are readily compatible with clinical applications. Together, this thesis introduces a number of innovative biomaterial modifications and microfluidics-based manufacturing concepts that facilitate the development and clinical translation of modular tissue engineering applications