Opioids for breathlessness: Psychological and neural factors influencing response variability

Abstract

Effective management of distressing bodily symptoms (such as pain and breathlessness) is an important clinical goal. However, extensive variability exists in both symptom perception and treatment response. One theory for understanding variability in bodily perception is the ‘Bayesian Brian Hypothesis’, whereby symptoms may result from the combination of sensory inputs and prior expectations. In light of this theory, we explored the relationships between opioid responsiveness, behavioural/physiological symptom modulators and brain activity during anticipation of breathlessness.MethodsWe utilised two existing opioid datasets to investigate the relationship between opioid efficacy and physiological/behavioural qualities, employing hierarchical cluster analyses in: 1) a clinical study in chronic obstructive pulmonary disease, and 2) a functional magnetic resonance brain imaging study of breathlessness in healthy volunteers. We also investigated how opioid efficacy relates to anticipatory brain activity using linear regression in the healthy volunteers.ResultsConsistent across both datasets, diminished opioid efficacy was more closely associated with negative affect than with other physiological and behavioural properties. Furthermore, in healthy individuals, brain activity in the anterior cingulate and ventromedial prefrontal cortices during anticipation of breathlessness were inversely correlated with opioid effectiveness.ConclusionDiminished opioid efficacy for relief of breathlessness may be associated with high negative affective qualities, and was correlated with the magnitude of brain activity during anticipation of breathlessness.Clinical implicationsNegative affect and symptom expectations may influence perceptual systems to become less responsive to opioid therapy.

Baseline psychological traits contribute to Lake Louise Acute Mountain Sickness score at high altitude

“…Hierarchical cluster analysis, similar to the method outlined by Abdallah et al, (2019), was used to assess the relationship between measures of symptoms of AMS on ascent to high altitude and baseline psychological state. Means of the daily measures of Lake Louise AMS score and oxygen saturations from the trek were included to represent AMS symptom burden.…”

Opioids for breathlessness: a narrative review

“…Abdallah et al recently demonstrated that in both people with chronic breathlessness (using morphine) and healthy volunteers (remifentanil), even subtle reductions in measures of mood reduced breathlessness response to opioids: as depression and anxiety increased, so opioid responsiveness decreased. 30 This has important clinical implications. People with significant depression and/or anxiety, should therefore first be managed with non-pharm psycho-educational approaches to modify the impact of emotion on opioid responsiveness before using opioids in order to maximise opioid-response and reduce the risk of adverse effects due to inappropriate dose escalation.…”

A common model for the breathlessness experience

“…Similar approaches have already been used to identify baseline factors, which together predict treatment response in depression [11,12] and pain [13,14]. Our previous work has drawn upon machine learning techniques in order to search for common features both across assessment tools and across the individuals who complete them [15][16][17]. The separable factors revealed by this work centre around mood/affect measures [15][16][17] and symptom All rights reserved.…”

“…Our previous work has drawn upon machine learning techniques in order to search for common features both across assessment tools and across the individuals who complete them [15][16][17]. The separable factors revealed by this work centre around mood/affect measures [15][16][17] and symptom All rights reserved. No reuse allowed without permission.…”

“…Other independent studies using machine learning techniques to identify symptom-based phenotypes in asthma [18] and COPD [19,20] also identified clusters of patients for whom breathlessness was linked with underlying mood/affect. While our previous work has focused on identifying factors underling breathlessness within a single disease [16] or between a patient and a control group [15,17], we have yet to determine whether a common model for the breathlessness experience can be identified across different cardiorespiratory diseases. Also, the stability of such models over time is unknown.…”