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Record W3112171960 · doi:10.1080/15622975.2020.1851052

A clinical approach to treatment resistance in depressed patients: What to do when the usual treatments don’t work well enough?

2020· article· en· W3112171960 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe World Journal of Biological Psychiatry · 2020
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of British ColumbiaBrain and Cognition Discovery FoundationSt. Michael's HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Health and Medical Research Council
KeywordsResistance (ecology)Work (physics)PsychologyPsychotherapistMedicineEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: Major depressive disorder is a common, recurrent, disabling and costly disorder that is often severe and/or chronic, and for which non-remission on guideline concordant first-line antidepressant treatment is the norm. A sizeable percentage of patients diagnosed with MDD do not achieve full remission after receiving antidepressant treatment. How to understand or approach these 'refractory', 'TRD' or 'difficult to treat' patients need to be revisited. Treatment resistant depression (TRD) has been described elsewhere as failure to respond to adequate treatment by two different antidepressants. This definition is problematic as it suggests that TRD is a subtype of major depressive disorder (MDD), inferring a boundary between TRD and depression that is not treatment resistant. However, there is scant evidence to suggest that a discrete TRD entity exists as a distinct subtype of MDD, which itself is not a discrete or homogeneous entity. Similarly, the boundary between TRD and other forms of depression is predicated at least in part on regulatory and research requirements rather than biological evidence or clinical utility. AIM: This paper aims to investigate the notion of treatment failure in order to understand (i) what is TRD in the context of a broader formulation based on the understanding of depression, (ii) what factors make an individual patient difficult to treat, and (iii) what is the appropriate and individualised treatment strategy, predicated on an individual with refractory forms of depression? METHOD: Expert contributors to this paper were sought internationally by contacting representatives of key professional societies in the treatment of MDD - World Federation of Societies for Biological Psychiatry, Australasian Society for Bipolar and Depressive Disorders, International Society for Affective Disorders, Collegium Internationale Neuro-Psychopharmacologium and the Canadian Network for Mood and Anxiety Treatments. The manuscript was prepared through iterative editing. OUTCOMES: The concept of TRD as a discrete subtype of MDD, defined by failure to respond to pharmacotherapy, is not supported by evidence. Between 15 and 30% of depressive episodes fail to respond to adequate trials of 2 antidepressants, and 68% of individuals do not achieve remission from depression after a first-line course of antidepressant treatment. Failure to respond to antidepressant treatment, somatic therapies or psychotherapies may often reflect other factors including; biological resistance, diagnostic error, limitations of current therapies, psychosocial variables, a past history of exposure to childhood maltreatment or abuse, job satisfaction, personality disorders, co-morbid mental and physical disorders, substance use or non-adherence to treatment. Only a subset of patients not responding to antidepressant treatment can be explained through pharmacokinetic or pharmacodynamics mechanisms. We propose that non remitting MDD should be personalised, and propose a strategy of 'deconstructing depression'. By this approach, the clinician considers which factors contribute to making this individual both depressed and 'resistant' to previous therapeutic approaches. Clinical formulation is required to understand the nature of the depression. Many predictors of response are not biological, and reflect a confluence of biological, psychological, and sociocultural factors, which may influence the illness in a particular individual. After deconstructing depression at a personalised level, a personalised treatment plan can be constructed. The treatment plan needs to address the factors that have contributed to the individual's hard to treat depression. In addition, an individual with a history of illness may have a lot of accumulated life issues due to consequences of their illness, and these should be addressed in a recovery plan. LIMITATIONS: A 'deconstructing depression' qualitative rubric does not easily provide clear inclusion and exclusion criteria for researchers wanting to investigate TRD. CONCLUSIONS: MDD is a polymorphic disorder and many individuals who fail to respond to standard pharmacotherapy and are considered hard to treat. These patients are best served by personalised approaches that deconstruct the factors that have contributed to the patient's depression and implementing a treatment plan that adequately addresses these factors. The existence of TRD as a discrete and distinct subtype of MDD, defined by two treatment failures, is not supported by evidence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.328
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it