Cardiovascular Effects of Non-Selective Monoamine Oxidase Inhibitors and Intranasal Esketamine Combination in Depression – A Quasi-Experimental Design with Bayesian Analyses

Abstract

Introduction

Ketamine and esketamine (ESK) offer new treatment options for resistant depression. Unlike traditional antidepressants, they can be used in combination with non-selective monoamine oxidase inhibitors (NS-MAOI) without the risk of serotonergic syndrome. However, potential sympathomimetic synergy may lead to elevated blood pressure (BP). This series investigates whether cardiovascular parameters (heart rate, systolic [SP], and diastolic [DP] pressures) increase during ESK sessions and whether the ESK+NS-MAOI combination is associated with BP elevations.

Methods

We collected cardiovascular parameters for ESK sessions conducted between 2018 and 2022. These parameters were measured at baseline and every 30 min for 2 h. Patients were categorized into two non-equivalent groups: those receiving ESK alone and those receiving ESK+NS-MAOI. A Bayesian random model was used to estimate the evolution of these parameters, while a Bayesian hierarchical model assessed factors contributing to BP elevation.

Results

ESK sessions (n=193), of which 116 involved NS-MAOI, were performed in 13 patients. SP, DP, and heart rate showed peak increases during sessions, but these changes were not clinically significant (SP+8.68 mmHg, DP+6.57 mmHg, and heart rate+3.5 bpm). No significant differences were found between the ESK-alone and ESK+NS-MAOI groups. The combination was not identified as a factor linked to BP elevations.

Discussion

These findings align with previous research on ketamine derivatives and suggest minimal peripheric sympathomimetic synergy with NS-MAOI. Bayesian models were used to account for biases intrinsically related to these ecological data and provide a foundation for future open adversarial collaborations.
Registration NCT05530668

Keywords

treatment-resistant depression - esketamine - monoamine oxidase inhibitors - markov chains monte-marlo models - bayesian analysis.

Publication History

Received: 04 December 2024

Accepted: 08 February 2025

Article published online:
02 June 2025

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