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Comparative study between effect of Cannabis and Synthetic Cannabinoids on cognitive functions

2022· article· en· W4283768888 on OpenAlexaboutno aff
Mohammed Abdel-Ghany, Mohammed Hamouda, Mohammed Fahmi

Bibliographic record

VenueAl-Azhar International Medical Journal /Al-Azhar International Medical Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsnot available
Fundersnot available
KeywordsSynthetic cannabinoidsCannabisEffects of cannabisCannabinoidPharmacologyCognitionMedicineNeurosciencePsychologyCannabidiolPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Background: Synthetic cannabinoid usage is on the rise around the world, and it has become a huge global health issue. Previous studies showed a relationship between synthetic cannabinoids and cognitive function decline either after acute or chronic usage. Aim of the study: The present study aims at comparing between natural and synthetic cannabinoids effect on cognitive functions in a sample of Egyptian patients. Subjects and methods: Thirty patients using synthetic cannabinoids with or without cannabis and 30 patients using cannabis were included in the study. Montreal Cognitive Assessment was used to test cognitive functions. Results: Impairments in attention, language, orientation, abstract thinking, visuospatial and executive functions were observed in patients using synthetic cannabinoids with or without cannabis and were significantly higher than in patients using cannabis alone. Conclusion: Synthetic cannabinoids and cannabis both cause cognitive dysfunction and when cannabis abusers add synthetic cannabinoids to cannabis, it causes more cognitive dysfunction. According to the findings of this study, future research should focus on evaluating each cognitive domain with more extensive test batteries and supporting these assessments with brain imaging studies.

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)0.007
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.008
Insufficient payload (model declined to judge)0.0210.000

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 head0.019
GPT teacher head0.363
Teacher spread0.344 · 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.

Study designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueAl-Azhar International Medical Journal /Al-Azhar International Medical JournalSame topicBiochemical effects in animalsFrench-language works237,207