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Record W2095194944 · doi:10.1097/ftd.0b013e318197b7d7

Hypoglycemia in a Healthy Toddler

2009· article· en· W2095194944 on OpenAlexaff
Miguel Glatstein, Dennis Scolnik, Gideon Koren, Yaron Finkelstein

Bibliographic record

VenueTherapeutic Drug Monitoring · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience of respiration and sleep
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsToddlerHypoglycemiaMedicinePediatricsPsychologyEndocrinologyDiabetes mellitusDevelopmental psychology

Abstract

fetched live from OpenAlex

Sulphonylurea ingestion is life-threatening in toddlers due to its strong and prolonged hypoglycemic effect, and is on the toddlers' "one pill can kill" list. Its administration to children may not be accidental. We discuss a case of non-accidental sulphonylurea ingestion by an 18-month-old girl, and the clinical reasoning process leading to identification of the causative agent for the patient's symptoms. A previously healthy 18 month-old girl presented to the Emergency Department with altered mental status and severe hypoglycaemia, which required intravenous hypertonic dextrose solutions to maintain euglycemia. A family history of type II diabetes prompted a search for sulphonylureas in the child's serum, which was positive. Further investigation led to the conclusion that the child's poisoning was the result of the mother's Munchausen-by-proxy syndrome. Sulphonylurea intoxication should be considered in previously healthy children presenting with hypoglycaemia. More than 20% of sulphonylurea poisonings reported in the literature correspond to Munchausen-by-proxy syndrome or homicide attempts. Initial management consists of rapid glucose infusion, but boluses should be avoided whenever possible to prevent rebound hyperinsulinism and worsening hypoglycemia. We stress the need to consider potential child abuse or neglect in a hypoglycaemic patient with sulphonylurea-using caregivers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.064
GPT teacher head0.330
Teacher spread0.267 · 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 designBench or experimental
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

Citations20
Published2009
Admission routes1
Has abstractyes

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