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Record W2026993888 · doi:10.4021//jmc.v4i3.939

Cannabinoid Hyperemesis Syndrome Presenting With Recurrent Acute Renal Failure

2012· article· en· W2026993888 on OpenAlexvenueno aff
Oladapo A. Abodunde, Joseph Nakda, Nneka Nweke, Raghava Levaka Veera

Bibliographic record

VenueJournal of Medical Cases · 2012
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineVomitingNauseaMetabolic acidosisHypokalemiaHyponatremiaCannabisMetabolic alkalosisPediatricsAnion gapInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Cannabinoid hyperemesis syndrome is a recently recognized clinical syndrome characterized by chronic cannabis use, profound vomiting and compulsive bathing among other features. Despite the degree of vomiting associated with this disorder, renal impairment and electrolyte disturbances are not commonly reported findings. We report the case of a 36-year-old male with a history of chronic daily cannabis use, who presented to our hospital with acute renal impairment five times in 4 years, with nearly identical clinical picture in each presentation. His symptom complex in each admission consisted of severe nausea and vomiting, compulsive hot showers, and resolution of symptoms within days of abstaining from cannabis. His clinical course included significantly abnormal basic metabolic panels at the time of each admission, with return to normal baseline values 96 hours following hydration in every case. The other consistent findings on admission were hypochloremic, hyponatremic dehydration with mixed metabolic alkalosis and high anion gap metabolic acidosis. He also had proteinuria and microscopic hematuria.This case highlights a serious and potentially life-threatening complication of the disorder. The consistency of the findings suggests a pattern that is associated with this disorder. It is unclear whether the course of renal involvement is benign in the long term. doi: http://dx.doi.org/10.4021/jmc939w

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.411
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.323
Teacher spread0.297 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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