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Record W3024373957 · doi:10.26355/eurrev_201808_15738

Delirium tremens in an AUD patient after an intrathecal baclofen pump induced total alcohol abstinence.

2018· article· en· W3024373957 on OpenAlexaff
M E Calvo, Þorsteinn Gunnarsson, Lloyd R. Smith, M Hao

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicAlcoholism and Thiamine Deficiency
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBaclofenDelirium tremensMedicineSpasticityAnesthesiaAbstinenceAlcohol withdrawal syndromeAlcohol dependenceDiazepamAlcoholPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Delirium Tremens (DT) is the most severe complication of alcohol withdrawal syndrome (AWS), and has a mortality rate of 1-5%. Baclofen is recommended for spasticity treatment, but it has recently been used for alcohol withdrawal symptoms reduction and alcohol abstinence. CASE REPORT: A cervical spinal cord injury patient was treated for two years with oral baclofen 80 mg/day for spasticity. He is alcohol-dependent and a cannabis user and required an intrathecal baclofen (ITB) pump implant. A week after the implant, he stopped drinking, as "he didn't felt the urge anymore". The AWS appeared five days after the last alcohol intake and DT at 7 days. Diazepam 20 mg was used up to three times per day, but didn't seem to improve or reduce the anxiety, agitation, visual or auditory hallucinations. Two years later the patient remains alcohol abstinent and still on intrathecal baclofen. CONCLUSIONS: Alcohol-dependent patients can abruptly stop their alcohol intake, while in continuous infusion of intrathecal baclofen. Baclofen can be useful in the acute treatment of AWS as it seems to reduce diazepam requirements and in long-term alcohol abstinence. In the presence of AWS, while on chronic baclofen, no dose reduction should be attempted, as it can worsen the AWS or trigger baclofen withdrawal.

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 score0.567
Threshold uncertainty score0.785

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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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

Citations4
Published2018
Admission routes1
Has abstractyes

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