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Record W4285027620 · doi:10.64719/pb.4442

Sleep Deprivation & Amphetamine Induced Psychosis

2025· article· en· W4285027620 on OpenAlexaff
Amr Said Shalaby, Abdullah Osama Bahanan, Mishal Hasan Alshehri, Khaled Ahmed Elag

Bibliographic record

VenuePsychopharmacology Bulletin · 2025
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsAmphetamineSleep deprivationPsychosisMedicinePsychiatrySleep (system call)PsychologyAnesthesiaInternal medicineCognition

Abstract

fetched live from OpenAlex

Objectives: To explore the relationship between sleep deprivation and amphetamine-induced psychosis. Methods: The patient group included 78 patients with a diagnosis of amphetamine (Captagon)-induced psychosis. The control group included 49 patients with no current or past history of amphetamine (Captagon)-induced psychosis. All study subjects underwent the following: a demographic sheet, a structured clinical interview for SM-IV (SCID 1), a drug use questionnaire, a questionnaire to explore any relationship between sleep deprivation and Captagon-induced psychosis, routine medical investigation, and urine screening for detection of drugs. Results: The patient group showed significantly higher both regular and maximum daily doses of Captagon. Patients showed more periods of sleep deprivation with the use of Captagon in comparison to controls, especially with the increase of the Captagon dose. Patients believed that the occurrence and termination of sleep deprivation were the cause of the start and end of psychotic experiences (more so than the increase and decrease or stoppage of Captagon doses). Conclusion: sleep deprivation plays an essential role in the development of psychotic symptoms in patients who are using Captagon.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.371
Teacher spread0.324 · 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".

Quick stats

Citations9
Published2025
Admission routes1
Has abstractyes

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