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Record W4391881226 · doi:10.1017/cjn.2024.27

Hyponatremia in Guillain-Barre Syndrome: A Review of Its Pathophysiology and Management

2024· review· en· W4391881226 on OpenAlexvenueno aff
Archana B Netto, Niveditha Chandrahasa, Sheril S Koshy, Arun B. Taly

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2024
Typereview
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsnot available
FundersUniversity of Cambridge
KeywordsHyponatremiaMedicineGuillain-Barre syndromePathophysiologyIncidence (geometry)Intensive care medicineDiseasePediatricsPolyradiculoneuropathyInternal medicine

Abstract

fetched live from OpenAlex

Guillain-Barre syndrome (GBS) is the commonest cause of acute polyradiculoneuropathy that requires hospitalization. Many of these patients experience systemic and disease-related complications during its course. Notable among them is hyponatremia. Though recognized for decades, the precise incidence, prevalence, and mechanism of hyponatremia in GBS are not well known. Hyponatremia in GBS patients is associated with more severe in-hospital disease course, prolonged hospitalization, higher mortality, increased costs, and a greater number of other complications in the hospital and worse functional status at 6 months and at 1 year. Though there are several reports of low sodium associated with GBS, many have not included the exact temporal relationship of sodium or its serial values during GBS thereby underestimating the exact incidence, prevalence, and magnitude of the problem. Early detection, close monitoring, and better understanding of the pathophysiology of hyponatremia have therapeutic implications. We review the complexities of the relationship between hyponatremia and GBS with regard to its pathophysiology and treatment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.318
Teacher spread0.279 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicElectrolyte and hormonal disordersFrench-language works237,207