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Frusemide results in an extracellular to intracellular fluid shift in horses

2006· article· en· W2047649712 on OpenAlexaff
Mariann Forro, Michael I. Lindinger

Bibliographic record

VenueEquine Veterinary Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsExtracellular fluidIntracellular FluidBody waterFurosemideHorseExtracellularIntracellularDiureticFluid compartmentsBody fluidChemistryMedicinePharmacologyEndocrinologyInternal medicineBody weightBiologyBiochemistry

Abstract

fetched live from OpenAlex

REASONS FOR PERFORMING STUDY: Frusemide (Lasix) is commonly used diuretic in horse racing and equine clinical practice. While pharmacology, pharmacodynamics, renal and haematological effects of frusemide have been studied in horses, its effects on the distribution of fluid within the horse remain unknown. OBJECTIVE: To quantify the effects of frusemide on extracellular and intracellular fluid shifts. METHODS: Horses were infused with 1 mg/kg body mass (n = 7) or 2 mg/kg (n = 9) i.v. frusemide. Total body water (TBW), extracellular fluid volume (ECFV) and plasma volume (PV) were measured using D2O, NaSCN and Evans blue dilution. Change in ECFV was assessed from the change in plasma [protein] and from repeated infusion/dilution of NaSCN. RESULTS: Frusemide resulted in a 0.020 +/- 0.002 l/kg decrease in TBW within 120 min. At 120 min after frusemide infusion the ECFV losses were nearly double the TBW losses, therefore ECFV loss in excess of TBW loss is seen as an increase in ICFV. CONCLUSIONS: Frusemide resulted in a net shift of fluid (electrolytes and water) from the extracellular to intracellular fluid compartment. POTENTIAL RELEVANCE: The fluid shifts that occur within horses administered frusemide has not previously been characterised. The intracellular shift of fluid is of performance and clinical significance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.044
GPT teacher head0.326
Teacher spread0.282 · 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

Citations12
Published2006
Admission routes1
Has abstractyes

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