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Record W4413051975 · doi:10.2196/64101

Use of Naltrexone for Patients With Stimulant Use Disorder in Malaysia: Protocol for a Retrospective Cohort Study

2025· article· en· W4413051975 on OpenAlexvenueno aff
Nor Asiah Muhamad, Nur Hasnah Maamor, Muhammad Arif Muhamad Rasat, Tengku Puteri Nadiah Tengku Baharudin Shah, Izzah Athirah Rosli, Fatin Norhasny Leman, Nurul Hidayah Jamalluddin, Nurul Syazwani Misnan, Norliza Chemi, Norni Abdullah, Nurashikin Ibrahim

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsNaltrexoneAbstinenceMedicineOpioid use disorderHeroinBuprenorphineOpioidOpioid antagonistStimulantPsychiatryAnesthesiaInternal medicine(+)-NaloxoneDrug

Abstract

fetched live from OpenAlex

BACKGROUND: Naltrexone is an opioid receptor antagonist. Naltrexone is used to block the euphoric and sedative effects of drugs such as heroin, codeine, and morphine. The medication helps to bind and block opioid receptors to decrease opioid cravings. In Malaysia, naltrexone has been used for maintenance treatments for heroin and alcohol since 1996. However, since 2011, naltrexone has been used as an off-label stimulant use disorder (StUD) treatment to achieve abstinence. OBJECTIVE: This study aims to determine the abstinence among StUD and non-StUD patients treated and without naltrexone. METHODS: We will conduct a retrospective cohort study on the effect of naltrexone or treatment as usual (TAU) by examining the data for both StUD and non-StUD patients. We will use patients' clinical records from the hospital registry. All adult patients (aged 18-65 years) diagnosed with StUD or other substance use disorders who were treated with naltrexone and standard care from January 1, 2011, to December 31, 2023, will be screened. All StUD and non-StUD patients who were offered the naltrexone treatment or TAU at the beginning of treatment will be recruited. All data will be extracted using a standardized data extraction form. Descriptive analysis will be performed to describe the distribution of patient characteristics, sociodemographic profiles, and percentages of abstinence and treatment retention. We will conduct univariable analysis to determine the association of stimulant abstinence and treatment retention between naltrexone and TAU among both StUD and non-StUD patients. All significant independent variables will be further analyzed using a cross-sectional time series method for categorical variables. RESULTS: Recruitment began in July 2025. Data analysis will begin after completing data collection, planned for January 2026. CONCLUSIONS: The expected main outcome of this study is to observe the significant associations of stimulant use abstinence and treatment retention between TAU and naltrexone among StUD and non-StUD patients. The findings from this study may provide preliminary evidence regarding the use of naltrexone in treating StUD. Currently, there is no specific medication to treat amphetamine or methamphetamine use disorder. The effect of naltrexone with psychosocial interventions for StUD is unclear. Public health approaches recognize the multifaceted nature of substance misuse and focus on addressing the myriad individual, environmental, and social factors that contribute to StUD. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/64101.

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)0.012
metaresearch head score (Gemma)0.009
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.009
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0210.004

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 head0.189
GPT teacher head0.521
Teacher spread0.332 · 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
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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