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Record W4401919153 · doi:10.1192/j.eurpsy.2024.309

Research of cognitive disorders and quality of life in patients, who are receiving methadone replacement maintenance therapy

2024· article· en· W4401919153 on OpenAlexaboutno aff
N. Halytska-Pasichnyk, Вікторія Огоренко

Bibliographic record

VenueEuropean Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMethadoneQuality of life (healthcare)Methadone maintenanceMedicineCognitionMaintenance therapyPsychologyClinical psychologyIntensive care medicinePsychotherapistPsychiatryInternal medicineChemotherapy

Abstract

fetched live from OpenAlex

Introduction Important goals of substitution therapy include: reducing the desire to use opioids - methadone enters the brain with a minimal euphoric effect, reduce the desire to use opioids, allowing to avoid the risk of overdose and control their addiction; prevention of withdrawal syndrome; improving the quality of life - can contribute to the restoration of patients, allowing them to return to a normal life, improve their social, professional and family situation; reducing the risk of transmission of infections HIV and hepatitis; reducing crime - control addiction can reduce related crime and to illicitly obtain opioids; psychosocial support helps patients develop coping strategies and increases their chances of long-term recovery. The goal of substitution therapy is not to completely get rid of addiction, but it can help stabilize the patient’s life and facilitate the recovery process. Objectives Many patients receiving MT also have mental disorders such as cognitive decline, depression, anxiety, PTSD, or even bipolar disorder. These conditions can greatly affect the course and results of treatment.They may also have problems with employment, housing, family conflicts, and legal issues. Methods In the course of the study, 134 patients aged 26 to 64 years (105 men and 29 women) with a diagnosis of opioid addiction and receiving methadone therapy were examined. Of them, 48 patients had a period of stay at MT of up to three years and 86 – more than three years. The Montreal Cognitive Scale (MoCA) was used to assess comorbid cognitive impairments. The WHOQOL-BREF questionnaire was used to assess the quality of life. Results The range of indicators of cognitive functions varied from 21 to 29 points (average - 25.3). 61 patients (46%) showed a result of 26 and above, indicating the absence of cognitive impairment, 51 patients (38%) received from 24 to 21, indicating moderate cognitive impairment. 22 patients (16%) had borderline indicators. When assessing the level of quality of life, indicators of physical and psychological components varied from 12 to 31; self-perception in the range from 10 to 27 points; microsocial support from 3 to 14 points; social well-being from 11 to 36. In general, the level of satisfaction with the quality of life was in the range of 38-83%. Image: Image 2: Conclusions Opioid addiction therapy should be consist of an assessment of physical and psychological status, comorbid disorders, quality of life, etc. We can see, MT does not significantly affect the cognitive functions. The differences in the assessment of the quality of life were noted in the components of microsocial support and social well-being, which indicates the vulnerability of patients in these areas. Duration of opioid dependence, availability of psychosocial support, presence of comorbid conditions affect the quality of life. It is important that treatment is tailored to individual needs of patients. Disclosure of Interest None Declared

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.169
GPT teacher head0.454
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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