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Record W2992991283 · doi:10.7759/cureus.6312

Cannabidiol (CBD) for Treatment of Neurofibromatosis-related Pain and Concomitant Mood Disorder: A Case Report

2019· article· en· W2992991283 on OpenAlexaff
Omar Hegazy, Howard Platnick

Bibliographic record

VenueCureus · 2019
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsCollege of Family Physicians of Canada
Fundersnot available
KeywordsCannabidiolMedicineAnxietyMood disordersMoodNeurofibromatosisChronic painPsychiatryCannabisPathology

Abstract

fetched live from OpenAlex

Neurofibromatosis type 1 (NF1) is a common genetic disorder. Pain is a major symptom of this disease which can be secondary to the development of plexiform and subcutaneous neurofibromas, musculoskeletal symptoms (such as scoliosis and pseudoarthrosis), and headaches. Visible neurofibromas add significant psychosocial distress for NF1 patients. Along with the chronic pain, psychosocial distress contributes to associated mood disorders, such as depression and anxiety. Cannabis has been the focus of many studies for treating multiple conditions, including epilepsy, multiple sclerosis, Parkinsonism disease, and many chronic pain conditions. Cannabidiol (CBD) is the major non-psychotropic component of cannabis. CBD has shown anti-inflammatory and analgesic properties, as well as having mood stabilizer and anxiolytic effects. In this report, we present the use of cannabidiol (CBD) for the management of chronic pain and concomitant mood disorder in an NF1 patient.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.290
Teacher spread0.277 · 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 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

Citations16
Published2019
Admission routes1
Has abstractyes

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