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Drug-induced syndrome of inappropriate antidiuretic hormone

2007· article· en· W1992224494 on OpenAlexvenueno aff
E. Idris Jones

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2007
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAntidiureticDrugMedicineHormonePharmacologyInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

HYPONATREMIA, OFTEN DEFINED AS SERUM SODIUM LESS THAN 130 mmol/L, is the most common electrolyte disturbance among hospitalized patients. A complication of a variety of diseases, surgical treatments, or drugs, it may be hypertonic, hypotonic, or isotonic in nature. Antidiuretic hormone (ADH) is also known as arginine vasopressin (AVP). Produced in the posterior pituitary gland in response to an increased plasma sodium concentration, it induces water retention. It increases cellular permeability to water in the distal tubule and collecting duct of the nephron, leading to increased water resorption by the kidney. The syndrome of inappropriate antidiuretic hormone secretion (SIADH) is characterized by either the sustained release of ADH in the absence of stimuli, or by the enhanced action of ADH on the kidneys. Increased ADH activity impairs the kidney’s ability to dilute urine, resulting in decreased excretion of ingested water and a highly concentrated and decreased volume of urine. If fluid intake is not sufficiently reduced in the setting of increased ADH activity, serum hypotonicity and hyponatremia will occur. Patients with SIADH will present with normal volume status (euvolemic) because the excess water distributes evenly throughout the body’s fluid compartments. Causes of SIADH include malignant diseases (e.g., carcinoma, lymphomas, sarcomas), pulmonary disorders (e.g., pneumonia, asthma), central nervous system disorders (e.g., meningitis, stroke, head trauma), and a number of medications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.263
Teacher spread0.242 · 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.

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

Citations9
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Pharmacists Journal / Revue des Pharmaciens du CanadaSame topicElectrolyte and hormonal disordersFrench-language works237,207