Drug dependence and prescribing ketamine for treatment-resistant depression in Australia and New Zealand.

Ketamine is a restricted and regulated medication in Australia and New Zealand, which has implications when considering treatment for patients with treatment-resistant depression and a history of illicit drug use, abuse or dependence. Regulations governing prescription of ketamine for treatment-resistant depression vary between jurisdictions in Australia and New Zealand, though most restrict use in those with drug dependence. There is substantial variation in definitions of drug dependence used in each jurisdiction, and between the legal and clinical definitions, with the latter specified in the current International Classification of Diseases, Eleventh Revision and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. This paper reviews the literature assessing the risk of ketamine misuse and dependence in patients with a history of illicit drug use, abuse or dependence and presents recommendations for psychiatrists who prescribe ketamine in such patients with treatment-resistant depression.

Who are you after psychedelics? A systematic review and a meta-analysis of the magnitude of long-term effects of serotonergic psychedelics on cognition/creativity, emotional processing and personality.

This systematic review and a meta-analysis synthesised the results from contemporary, randomized and non-randomized controlled studies to assess lasting (one week minimum) changes on cognition/creativity, emotional processing and personality from serotonergic psychedelics. PubMed, Embase and PsycInfo were searched in July 2022. Risk of bias was assessed using Rob 2.0 and ROBINS-I. Ten studies met the eligibility criteria which involved 304 participants. No statistically significant effects were found for the majority outcome measures across the three constructs. A meta-analysis of emotional recognition outcomes found an overall significant effect for faster reaction times in the active treatment groups for disgust (SMD=-0.63, 95% CI=[-1.01 to -0.25], I2 = 65%) and sadness (SMD=-0.45, 95% CI=[-0.85 to -0.06], I2 = 60%). Future research should include larger samples, better control conditions, standardized doses and longer follow-up periods to confirm these preliminary findings.

A naturalistic effectiveness study of maintenance therapies for the bipolar disorders.

BACKGROUND: Treatment decision-making for individuals with bipolar disorder can be difficult. Recommendations from clinical practice guidelines can be affected by multiple methodological limitations, while pharmaco-epidemiological data suggest great variety in prescription practices across regions. Given these inconsistencies, this study aimed to provide an alternative perspective on the effectiveness of common bipolar disorder maintenance treatments through considering naturalistic data. METHODS: A total of 246 individuals with bipolar disorder (84 bipolar I [BP-I], 162 bipolar II [BP-II]) were recruited through clinics and/or websites. All were euthymic and had trialled at least one mood stabiliser. They completed an online survey containing questions on demographics, clinical variables, symptomatology, and the effectiveness/side effect profiles of any mood stabilisers (MSTs) or atypical antipsychotics (AAPs) that they have taken. RESULTS: Lithium and lamotrigine were the most commonly prescribed MSTs and the most effective at mood stabilisation. Lithium and lamotrigine appeared marginally more effective for BP-I and BP-II respectively, however, only the latter difference was statistically significant. Furthermore, lamotrigine had the more favourable side effect profile. Amongst the AAPs, quetiapine and olanzapine were the most commonly prescribed, but they were negligibly superior to other AAPs. CONCLUSION: This study clearly established a preference for lamotrigine in the maintenance treatment of BP-II. While the literature consistently emphasises the primacy of lithium in bipolar disorder treatment, its side effect profile as observed in this study remains a concern. Future research considering moderators of treatment response and concomitant medications could help to identify further nuances to consider for treatment decision-making.

Subcutaneous ketamine infusion in palliative patients for major depressive disorder (SKIPMDD)-Phase II single-arm open-label feasibility study.

BACKGROUND: Ketamine at subanaesthetic dosages (≤0.5mg/kg) exhibits rapid onset (over hours to days) antidepressant effects against major depressive disorder in people who are otherwise well. However, its safety, tolerability and efficacy are not known for major depressive disorder in people with advanced life-limiting illnesses. OBJECTIVE: To determine the feasibility, safety, tolerability, acceptability and any antidepressant signal/activity to justify and inform a fully powered study of subcutaneous ketamine infusions for major depressive disorder in the palliative setting. METHODS: This was a single arm, open-label, phase II feasibility study (Australian New Zealand Clinical Trial Registry Number-ACTRN12618001586202). We recruited adults (≥ 18-years-old) with advanced life-limiting illnesses referred to four palliative care services in Sydney, Australia, diagnosed with major depressive disorder from any care setting. Participants received weekly subcutaneous ketamine infusion (0.1-0.4mg/kg) over two hours using individual dose-titration design. Outcomes assessed were feasibility, safety, tolerability and antidepressant activity. RESULTS: Out of ninety-nine referrals, ten participants received ketamine and were analysed for responses. Accrual rate was 0.54 participants/month across sites with 50% of treated participants achieving ≥ 50% reduction in baseline Montgomery-Åsberg Depression Rating Scale, meeting feasibility criteria set a priori. There were no clinically relevant harms encountered. CONCLUSIONS: A future definitive trial exploring the effectiveness of subcutaneous infusion of ketamine for major depressive disorder in the palliative care setting may be feasible by addressing identified study barriers. Individual dose-titration of subcutaneous ketamine infusions over two hours from 0.1mg/kg can be well-tolerated and appears to produce transient antidepressant signals over hours to days.

Burnout and depression: Points of convergence and divergence.

BACKGROUND: Debate is ongoing as to whether burnout can be differentiated from depression. This study evaluated whether burnout and depression could be distinguished using a new burnout measure and other variables. METHODS: Scores on the Sydney Burnout Measure (SBM) were compared between participants with self-diagnosed burnout (BO-all group; n = 622) and clinically-diagnosed depression (DEP-all group; n = 90). The latter group was split into melancholic (DEP-mel; n = 56) and non-melancholic (DEP-nonmel; n = 34) depression subgroups for subsequent analyses. Differences in reporting of depressive symptoms and causal attributions were also evaluated. RESULTS: While total SBM scores showed poor differentiation, the BO-all group had lower social withdrawal and higher empathy loss subscale scores than the depression groups. Odds ratios were significant for several of the depressive symptoms and causal attribution items when comparing the BO-all group to the DEP-all and DEP-mel groups, while only a few items were significant when comparing the BO-all and DEP-nonmel groups. LIMITATIONS: Participants in the depression group were assigned by clinician-based depression diagnoses, rather than by a standardised diagnostic interview, and the group had a relatively small sample size. Participants in the burnout group were self-diagnosed and not assessed for comorbid psychiatric diagnoses. CONCLUSIONS: There were some nuanced symptoms differences between burnout and depression, but many of the SBM symptoms were not specific to burnout. Results also suggested that burnout overlaps more with non-melancholic than melancholic depression, and that differentiation of burnout and depression may rely more on weighting causal factors over symptoms.

Modelling self-diagnosed burnout as a categorical syndrome.

OBJECTIVE: There is currently little consensus as to how burnout is best defined and measured, and whether the syndrome should be afforded clinical status. The latter issue would be advanced by determining whether burnout is a singular dimensional construct varying only by severity (and with some level of severity perhaps indicating clinical status), or whether a categorical model is superior, presumably reflecting differing 'sub-clinical' versus 'clinical' or 'burning out' vs 'burnt out' sub-groups. This study sought to determine whether self-diagnosed burnout was best modelled dimensionally or categorically. METHODS: We recently developed a new measure of burnout which includes symptoms of exhaustion, cognitive impairment, social withdrawal, insularity, and other psychological symptoms. Mixture modelling was utilised to determine if scores from 622 participants on the measure were best modelled dimensionally or categorically. RESULTS: A categorical model was supported, with the suggestion of a sub-syndromal class and, after excluding such putative members of that class, two other classes. Analyses indicated that the latter bimodal pattern was not likely related to current working status or differences in depression symptomatology between participants, but reflected subsets of participants with and without a previous diagnosis of a mental health condition. CONCLUSION: Findings indicated that sub-categories of self-identified burnout experienced by the lay population may exist. A previous diagnosis of a mental illness from a mental health professional, and therefore potentially a psychological vulnerability factor, was the most likely determinant of the bimodal data, a finding which has theoretical implications relating to how best to model burnout.

Comorbid bipolar disorder and borderline personality disorder: Diagnosis using machine learning.

Comorbid bipolar disorder (BP) and borderline personality disorder (BPD) presents a diagnostic challenge in its differentiation from each condition individually. We aimed to use a machine learning (ML) approach to differentiate comorbid BP/BPD from both BP and BPD. Participants were assigned DSM diagnoses and compared on self-report measures examining personality, emotion regulation strategies and perceived parental experiences during childhood. 82 participants were assigned as BP, 52 as BPD and 53 as comorbid BP/BPD. ML-derived diagnoses had an accuracy of 79.6% in classifying BP/BPD vs. BP, and 61.7% in classifying BP/BPD vs. BPD. Stress-related paranoid ideation and other core borderline personality items were important in distinguishing BP/BPD vs. BP, whereas deficits in emotion regulation strategies were important in distinguishing BP/BPD vs. BPD. Impulsivity and anger were important across both analyses. We identified clinical variables more distinctive in comorbid BP/BPD, with superior accuracy in distinguishing from BP, and with lower accuracy compared to BPD alone. Such an additive model should assist in sharpening clinical decision making, with future machine learning examination of larger datasets likely to further improve diagnostic accuracy.

The Ketamine Side Effect Tool (KSET): A comprehensive measurement-based safety tool for ketamine treatment in psychiatry.

OBJECTIVES: On a background of the rapidly expanding clinical use of ketamine and esketamine for treatment of depression and other conditions, we examined safety monitoring, seeking to identify knowledge gaps relevant to clinical practice. METHODS: An international group of psychiatrists discussed the issue of safety of ketamine and esketamine and came to a consensus on key safety gaps. RESULTS: There is no standard safety monitoring for off-label generic ketamine. For intranasal esketamine, each jurisdiction providing regulatory approval may specify monitoring. Treatment is often provided beyond the period for which safety has been demonstrated, with no agreed framework for monitoring of longer term side effects for either generic ketamine or intranasal esketamine. LIMITATIONS: The KSET has established face and content validity, however it has not been validated against other measures of safety. CONCLUSIONS: We recommend the Ketamine Side Effect Tool (KSET) as a comprehensive safety monitoring tool for acute and longer term side effects.

Why might bipolar disorder and borderline personality disorder be bonded?

The prevalence of comorbid bipolar disorder (BD) and borderline personality disorder (BPD) is distinctly higher in community samples than would be expected if the two conditions are independent. While there have been multiple explanations suggested for their interdependence, no clear model has been established. This paper reviews a broader set of explanations than considered previously, where relevant prevalence studies of the conditions are reported, previous explanations overviewed, and additional potential linkage causes are considered. It was found that there is unlikely to be any single determinant of the comorbid presence of BD and BPD. The most likely candidates are the artefactual impact of transdiagnostic features, with true comorbid status reflecting both pleiotropic genetic influences and environmental factors. Measurement errors in diagnostic assignment emerging from transdiagnostic features are likely to have clouded previous studies and therefore the interpretations. Comorbid BD/BPD is likely to be distinctly more common than estimated by clinicians, and clarification of the reasons why this is may well assist clinical management.

A new machine learning-derived screening measure for differentiating bipolar from unipolar mood disorders.

BACKGROUND: While there are several accepted screening measures for identifying those with a bipolar disorder, variations in overall classification rates argue for the pursuit of a more discriminating measure. Extant measures, as well as the DSM-5, rate each diagnostic criterion as having equivalent weighting values; an approach which may compromise diagnostic assignment if symptoms vary considerably in their diagnostic sensitivity. We therefore sought to develop a new measure and examine whether a weighted rating scale was superior to one assigning equivalent weightings to each item. METHODS: An international sample of 165 bipolar patients and a comparison sample of 29 unipolar patients completed a measure assessing 96 putative manic/hypomanic symptoms. A previous machine learning analysis had identified the twenty most discriminating items. In this study, analysis was undertaken involving only the ten most discriminating items. RESULTS: Whether items were scored as each having equivalent value or as weighted by their machine learning-generated values, classificatory accuracy was extremely high (in the order of 96%). Analyses also identified optimal cut-off scores. High classificatory accuracy was also obtained when scores for separate bipolar I and bipolar II groups were compared with scores from the unipolar group. LIMITATIONS: The sample consisted of comparatively few unipolar patients. CONCLUSIONS: The ten-item set allows a new measure for researchers to evaluate, while the items should assist clinician assessment as to whether a patient has a bipolar or unipolar mood disorder.

Ketamine treatment for depression: A model of care.

OBJECTIVE: Ketamine and related compounds are emerging as rapidly acting therapies for treatment-resistant depression. Ketamine differs from standard antidepressants in its speed of action, specific acute and cumulative side effects, risk of dependence and regulatory requirements. However, there is currently little guidance offering translation from research studies into clinical practice. We therefore detail a comprehensive model of care for ketamine treatment of depression. METHOD: We formulated a set of policies and procedures for a 'compassionate use' ketamine programme that developed out of our clinical research in ketamine. These policies and procedures were formulated into a detailed model of care. RESULTS: The current Australian and New Zealand regulatory frameworks and professional bodies' recommendations regarding ketamine are detailed along with clinical governance and infrastructure considerations. We next describe a four-step model comprising initial assessment, pre-treatment, treatment and post-treatment phases. The model comprises thorough psychiatric and medical assessments examining patient suitability, a rigorous consenting process and structured safety monitoring across an acute treatment course or maintenance therapy. Our ketamine dose-titration method is detailed allowing flexible dosing of patients across a treatment course enabling individualised treatment. CONCLUSION: The model of care aims to bridge the gap between efficacy studies and clinical care outside of research settings as ketamine and related compounds become increasingly important therapies for treatment-resistant depression.

Differentiation of bipolar disorder versus borderline personality disorder: A machine learning approach.

BACKGROUND: Differentiation of bipolar disorder (BP) from borderline personality disorder (BPD) is a common diagnostic dilemma. We undertook a machine learning (ML) approach to distinguish the conditions. METHODS: Participants meeting DSM criteria for BP or BPD were compared on measures examining cognitive and behavioral BPD constructs, emotion regulation strategies, and parental behaviors during childhood. Two analyses used continuous and dichotomised data, with ML-allocated diagnoses compared to DSM. RESULTS: 82 participants met DSM criteria for BP and 52 for BPD. Accuracy of ML classification was 84.1% - 87.8% for BP, 50% - 57.7% for BPD, with overall accuracy of 73.1% - 73.9%. Importance of items differed between the analyses with the overall most important items including identity difficulties, relationship problems, female gender, feeling suicidal after a relationship breakdown and age. LIMITATIONS: Participants were volunteers, preponderance of bipolar II (BP II) participants, comorbidity of BP and BPD not examined, and small BPD sample contributed to the relatively low classification accuracies for this group CONCLUSIONS: Study findings may assist distinguishing BP and BPD based on differences in cognitive and behavioral domains, emotion regulation strategies and parental behaviors. Future studies using larger datasets could further improve predictive accuracy and assist in differential diagnosis.

The biology of burnout: Causes and consequences.

OBJECTIVES: Burnout is a state of exhaustion resulting from prolonged and excessive workplace stress. We sought to examine biological underpinnings of burnout, focussing on mechanisms and physical consequences. METHODS: We searched the literature on burnout and evaluated studies examining biological parameters in patient populations (i.e. 'clinical' burnout) as well as in individuals from the general population judged as having some degree of burnout evaluated using a dimensional approach. RESULTS: Findings suggest that burnout is associated with sustained activation of the autonomic nervous system and dysfunction of the sympathetic adrenal medullary axis, with alterations in cortisol levels. Limited studies have also shown altered immune function and changes in other endocrine systems. Consequences of burnout include increased allostatic load, structural and functional brain changes, excito-toxicity, systemic inflammation, immunosuppression, metabolic syndrome, cardiovascular disease and premature death. Limitations of studies include variability in study populations, low specificity of burnout measures, and mostly cross-sectional studies precluding examination of changes across the course of burnout. CONCLUSIONS: Further examination of biological mechanisms of burnout would benefit from more homogeneous clinical samples, challenge tests and prospective studies. This would assist in differentiation from conditions such as depression and aid with development of specific treatment targets for burnout.

Categorical differentiation of the unipolar and bipolar disorders.

There has been a longstanding debate as to whether the bipolar disorders differ categorically or dimensionally, with some dimensional or spectrum models including unipolar depressive disorders within a bipolar spectrum model. We analysed manic/hypomanic symptom data in samples of clinically diagnosed bipolar I, bipolar II and unipolar patients, employing latent class analyses to determine if separate classes could be identified. Mixture analyses were also undertaken to determine if a unimodal, bimodal or a trimodal pattern was present. For both a refined 15-item set and an extended 30-item set of manic/hypomanic symptoms, our latent class analyses favoured three-class solutions, while mixture analyses identified trimodal distributions of scores. Findings argue for a categorical distinction between unipolar and bipolar disorders, as well as between bipolar I and bipolar II disorders. Future research should aim to consolidate these results in larger samples, particularly given that the size of the unipolar group in this study was a salient limitation.

Differentiating mania/hypomania from happiness using a machine learning analytic approach.

BACKGROUND: This study aimed to improve the accuracy of bipolar disorder diagnoses by identifying symptoms that help to distinguish mania/hypomania in bipolar disorders from general 'happiness' in those with unipolar depression. METHODS: An international sample of 165 bipolar and 29 unipolar depression patients (as diagnosed by their clinician) were recruited. All participants were required to rate a set of 96 symptoms with regards to whether they typified their experiences of manic/hypomanic states (for bipolar patients) or when they were 'happy' (unipolar patients). A machine learning paradigm (prediction rule ensembles; PREs) was used to derive rule ensembles that identified which of the 94 non-psychotic symptoms and their combinations best predicted clinically-allocated diagnoses. RESULTS: The PREs were highly accurate at predicting clinician bipolar and unipolar diagnoses (92% and 91% respectively). A total of 20 items were identified from the analyses, which were all highly discriminating across the two conditions. When compared to a classificatory approach insensitive to the weightings of the items, the ensembles were of comparable accuracy in their discriminatory capacity despite the unbalanced sample. This illustrates the potential for PREs to supersede traditional classificatory approaches. LIMITATIONS: There were considerably less unipolar than bipolar patients in the sample, which limited the overall accuracy of the PREs. CONCLUSIONS: The consideration of symptoms outlined in this study should assist clinicians in distinguishing between bipolar and unipolar disorders. Future research will seek to further refine and validate these symptoms in a larger and more balanced sample.

The bipolar disorders: A case for their categorically distinct status based on symptom profiles.

BACKGROUND: It is unclear whether the bipolar disorders (i.e. BP-I/BP-II) differ dimensionally or categorically. This study sought to clarify this issue. METHODS: We recruited 165 patients, of which 69 and 96 had clinician-assigned diagnoses of BP-I and BP-II respectively. Their psychiatrists completed a data sheet seeking information on clinical variables about each patient, while the patients completed a different data sheet and scored a questionnaire assessing the prevalence and severity of 96 candidate manic/hypomanic symptoms. RESULTS: We conducted a series of analyses examining a set (and two sub-sets) of fifteen symptoms that were significantly more likely to be reported by the clinically diagnosed BP-I patients. Latent class analyses favoured two-class solutions, while mixture analyses demonstrated bimodality, thus arguing for a BP-I/BP-II categorical distinction. Statistically defined BP-I class members were more likely when manic to have experienced psychotic features and over-valued ideas. They were also more likely to have been hospitalised, and to have been younger when they received their bipolar diagnosis and first experienced a depressive or manic episode. LIMITATIONS: The lack of agreement between some patients and managing clinicians in judging the presence of psychotic features could have compromised some analyses. It is also unclear whether some symptoms (e.g. grandiosity, noting mystical events) were capturing formal psychotic features or not. CONCLUSIONS: Findings replicate our earlier study in providing evidence to support the modelling of BP-I and BP-II as categorically discrete conditions. This should advance research into aetiological factors and determining optimal (presumably differing) treatments for the two conditions.

A Review of Antidepressant-Associated Hypomania in Those Diagnosed with Unipolar Depression-Risk Factors, Conceptual Models, and Management.

PURPOSE OF REVIEW: The nosology and management of antidepressant-associated hypomania (AAH) in the treatment of unipolar depression requires clarification. We sought to review recent studies examining AAH, focusing on risk factors, differing explanatory models, and management strategies. RECENT FINDINGS: AAH occurs more frequently in those of female gender, younger age, and with a bipolar disorder (BP) family history. Depressive features (e.g., suicidal ideation, psychotic symptoms) in those with AAH were similar to those with established BPs. Explanatory models for AAH describe it as (i) a transient iatrogenic event, (ii) a specific "bipolar III" disorder, (iii) indicative of "conversion" to BP, (iv) acceleration of BP, and (v) coincidental and unrelated to antidepressant medication. Management recommendations include antidepressant cessation, atypical antipsychotic medications, or switching to a mood stabilizer. Determinants and management of AAH in the treatment of unipolar depression requires considerable clarification, likely to be achieved by close clinical review and refined research studies.

Development of the Ketamine Side Effect Tool (KSET).

BACKGROUND: Currently, no specific, systematic assessment tool for the monitoring and reporting of ketamine-related side effects exists. Our aim was to develop a comprehensive Ketamine Side Effect Tool (KSET) to capture acute and longer-term side effects associated with repeated ketamine treatments. METHODS: Informed by systematic review data and clinical research, we drafted a list of the most commonly reported side effects. Face and content validation were obtained via feedback from collaborators with expertise in psychiatry and anaesthetics, clinical trial piloting and a modified Delphi Technique involving ten international experts. RESULTS: The final version consisted of four forms that collect information at time points: screening, baseline, immediately after a single treatment, and longer-term follow-up. Instructions were developed to guide users and promote consistent utilisation. LIMITATIONS: Further evaluation of feasibility, construct validity and reliability is required, and is planned across multiple international sites. CONCLUSIONS: The structured Ketamine Side Effect Tool (KSET) was developed, with confirmation of content and face validity via a Delphi consensus process. This tool is timely, given the paucity of data regarding ketamine's safety, tolerability and abuse potential over the longer term, and its recent adoption internationally as a clinical treatment for depression. Although based on data from depression studies, the KSET has potential applicability for ketamine (or derivatives) used in other medical disorders, including chronic pain. We recommend its utilisation for both research and clinical scenarios, including data registries.

Differential Diagnosis of Bipolar II Disorder and Borderline Personality Disorder.

PURPOSE OF REVIEW: Differentiating bipolar (BP) disorders (in particular BP II) from borderline personality disorder (BPD) is a common diagnostic dilemma. We sought to critically examine recent studies that considered clinical differences between BP II and BPD, which might advance their delineation. RECENT FINDINGS: Recent studies focused on differentiating biological parameters-genetics, epigenetics, diurnal rhythms, structural and functional neuroimaging-with indicative differences not yet sufficient to guide diagnosis. Key differentiating factors include family history, developmental antecedents, illness course, phenomenological differences in mood states, personality style and relationship factors. Less differentiating factors include impulsivity, neuropsychological profiles, gender distribution, comorbidity and treatment response. This review details parameters offering differentiation of BP II from BPD and should assist in resolving a frequent diagnostic dilemma. Future studies should specifically examine the BP II subtype directly with BPD, which would aid in sharpening the distinction between the disorders.