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Record W3003414336 · doi:10.14740/jocmr4066

The Opioid System and Food Intake: Use of Opiate Antagonists in Treatment of Binge Eating Disorder and Abnormal Eating Behavior

2020· review· en· W3003414336 on OpenAlexvenueno aff
Leon Valbrun, Valeriy Zvonarev

Bibliographic record

VenueJournal of Clinical Medicine Research · 2020
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsNaltrexoneEating disordersBulimia nervosaMedicineBinge eatingAnorexia nervosaBinge-eating disorderPsychiatryBupropionPsycINFOOpioid use disorderClinical psychologyPsychotherapistOpioidPsychologyMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

Eating disorders (EDs) and substance use disorders (SUDs) commonly co-occur, especially in conjunction with affective syndromes, yet little is known about opiate abuse and ED symptoms in patients on naltrexone-bupropion therapy. Moreover, evidence suggests that the opioid system can also be regarded as one of the major systems regulating the anticipatory processes preceding binge eating episodes. The lack of evidence in the effectiveness of psychotherapy treatment in addition to psychotropic mediations compounds the difficulties in stabilizing individuals with EDs. This article aims to exhaustively review literature relating to the use of opioid antagonists in the management of binge eating disorder (BED) and other abnormal eating habits and how this can be augmented by the use of psychological approaches to come up with the most effective therapy or combination of therapies to manage these conditions. Although this approach is promising, it has not been evaluated. A review of the literature pertaining to the use of naltrexone in patients with EDs was performed through PubMed, PsycINFO and MEDLINE. We selected 63 relevant articles published between 1981 and 2018 and those written in English. Search terms included "Opioid antagonists", "naltrexone", "bupropion" and "Psychotherapy" each combined with "Binge Eating Disorder", "Bulimia Nervosa", "Anorexia Nervosa", "Eating Disorder", "EDNOS" and "Obesity". While working with these articles, we also identified several problems related to use of these methods in real clinical practice. Seventy-seven articles were reviewed, and 63 were selected for inclusion. Data obtained from these sources confirmed that the blockade of opioid receptors diminishes food intake. More recent findings also indicate that the combination of bupropion and naltrexone can induce weight loss. Augmentation of this by introducing psychotherapy may lead to better outcomes. Cognitive behavioral therapy (CBT) was the most frequently recommended psychotherapy intervention, showing efficacy for EDs and chemical addictions as documented by most of the studies, but with uncertain efficacy when utilized as augmentation strategy. There are limited data supporting the use of psychotherapy in augmentation of standard therapy in ED; however, there is evidence to support that psychotherapy is safe in this population and has been effective in cases of patients with opiate addiction with and without psychiatric comorbidities as well as BED. More research is needed to establish treatment guidelines. Combining pharmacotherapeutic and psychotherapeutic interventions leads to the achievement of a better outcome in managing patients with EDs. Involving families or the use of support groups increases chances of adherence to the prescribed interventions resulting in higher rates of remission. However, it is clear that all of these interventions must occur in the context of a comprehensive treatment program. We believe that patient-specific psychotherapy may not only facilitate the treatment process, but also cause significant alterations in eating pattern. This approach for BED may lead to more significant treatment outcomes, but this possibility must be tested in larger samples.

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.

How this classification was reachedexpand

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.799
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.398
GPT teacher head0.568
Teacher spread0.171 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations43
Published2020
Admission routes1
Has abstractyes

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