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Record W1969213806 · doi:10.1111/sdi.12235

Variability in the Management of Lithium Poisoning

2014· review· en· W1969213806 on OpenAlexaff
Darren M. Roberts, Sophie Gosselin

Bibliographic record

VenueSeminars in Dialysis · 2014
Typereview
Languageen
FieldMedicine
TopicPoisoning and overdose treatments
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineObservational studyIntensive care medicineExtracorporealLithium (medication)Randomized controlled trialTreatment modalityHemodialysisModalitiesMultidisciplinary approachInternal medicine

Abstract

fetched live from OpenAlex

Three patterns of lithium poisoning are recognized: acute, acute-on-chronic, and chronic. Intravenous fluids with or without an extracorporeal treatment are the mainstay of treatment; their respective roles may differ depending on the mode of poisoning being treated. Recommendations for treatment selection are available but these are based on a small number of observational studies and their uptake by clinicians is not known. Clinician decision-making in the treatment of four cases of lithium poisoning was assessed at a recent clinical toxicology meeting using an audience response system. Variability in treatment decisions was evident in addition to discordance with published recommendations. Participants did not consistently indicate that hemodialysis was the first-line treatment, instead opting for a conservative approach, and continuous modalities were viewed favorably; this is in contrast to recommendations in some references. The development of multidisciplinary consensus guidelines may improve the management of patients with lithium poisoning but prospective randomized controlled trials are required to more clearly define the role of extracorporeal treatments.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.345
Teacher spread0.319 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2014
Admission routes1
Has abstractyes

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