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Record W1408563464 · doi:10.1093/pch/13.6.502

Iatrogenic hyponatremia in hospitalized children: Can it be avoided?

2008· article· en· W1408563464 on OpenAlexaff
Peter Skippen, Robert Adderley, Mary Bennett, Arthur Cogswell, Norbert Froese, David Wensley

Bibliographic record

VenuePaediatrics & Child Health · 2008
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsHyponatremiaMedicineMedical prescriptionFluid restrictionIntensive care medicineElectrolyte DisorderIntravenous fluidFluid intakeTonicityPediatricsAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Iatrogenic hyponatremia in hospitalized children is a common problem. It is usually caused by the administration of free water, either orally or through the prescription of hypotonic intravenous fluids. It can result in cerebral edema and death, and is most commonly reported in healthy children undergoing minor surgery. The current teachings and practical guidelines for maintenance fluid infusions are based on caloric expenditure data in healthy children that were derived and published more than 50 years ago. A re-evaluation of these data and more recent recognition that hospitalized children are vulnerable to hyponatremia, with its resulting morbidity and mortality rates, suggest that changes in paediatricians' approach to fluid administration are necessary. There is no single fluid therapy that is optimal for all hospitalized children. A thorough assessment of the type of fluid, volume of fluid and electrolyte requirements based on individual patient requirements, plus rigorous monitoring, is required in any child receiving intravenous fluids. The present article reviews how hyponatremia occurs and makes recommendations for minimizing the risk of iatrogenic hyponatremia.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.004
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 head0.013
GPT teacher head0.261
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 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

Citations16
Published2008
Admission routes1
Has abstractyes

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