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Record W3038061401 · doi:10.1177/2329048x20937113

Baclofen Toxicity in Children With Acute Kidney Injury: Case Reports and Review of the Literature

2020· article· en· W3038061401 on OpenAlexaff
Ram A. Mishaal, Nancy Lanphear, Erez Armarnik, Esias R. van Rensburg, Douglas G. Matsell

Bibliographic record

VenueChild Neurology Open · 2020
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsBC Children's HospitalSunny Hill Health Centre for ChildrenUniversity of British Columbia
Fundersnot available
KeywordsBaclofenMedicineSpasticityDiscontinuationSpinal cord injuryAdverse effectAnesthesiaCerebral palsyAcute kidney injuryDystoniaIntensive care medicineInternal medicineSpinal cordPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

Baclofen is a medication used for tone management in cerebral palsy. Although it acts mainly at the spinal cord level, it can cause central nervous system adverse reactions at higher doses. Baclofen is mainly eliminated by renal excretion and there have been reports on adverse events when used in adults with renal impairment; however, there are no consensus guidelines as to the dose adjustments required due to renal impairment. The authors describe 2 children with acute kidney injury (AKI) and systemic side effects with initiation of oral baclofen, which was started for treatment of dystonia/spasticity in the recovery phase of their kidney injury. Following the initiation of the drug, they both had decreased level of consciousness and respiratory difficulties, which warranted discontinuation of the drug. These cases highlight the need for reduced initial dose, slow titration, and close monitoring when initiating baclofen treatment in children with AKI.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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 designCase report
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
Published2020
Admission routes1
Has abstractyes

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