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Refractometric total plasma protein measurement as a cage‐side indicator of hypoalbuminemia and hypoproteinemia in hospitalized dogs

2011· article· en· W2154658971 on OpenAlexaff
Galina M. Hayes, Karol A. Mathews, A Floras, Cate Dewey

Bibliographic record

VenueJournal of Veterinary Emergency and Critical Care · 2011
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHypoalbuminemiaHypoproteinemiaMedicineAlbuminInternal medicineGastroenterologySerum albuminEndocrinology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the relationship between total plasma protein (TPP) as measured by refractometry and serum hypoalbuminemia and hypoproteinemia in hospitalized dogs. DESIGN: Retrospective, observational study conducted over 6-month period between March and August 2008. SETTING: University teaching hospital. ANIMALS: Four hundred and three hospitalized dogs in an ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: TPP, serum albumin, total protein, glucose, urea, cholesterol was measured from dogs enrolled in study. TPP was evaluated as a predictor for hypoalbuminemia defined both as albumin <25 g/L (<2.5 g/dL) and albumin <20 g/L (<2.0 g/dL), and serum hypoproteinemia, defined as serum total protein <40 g/L (<4.0 g/dL), using logistic regression. Impact of glucose, urea, cholesterol, and total bilirubin on refractometric readings were also assessed. TPP predicted hypoalbuminemia at albumin concentrations of <25 g/L (<2.5 g/dL) and <20 g/L (<2.0 g/dL) (P<0.001). A TPP<60 g/L (<6.0 g/dL) predicted albumin <25 g/L (<2.5 g/dL) with 73% sensitivity and 86% specificity. A TPP<58 g/L (<5.8 g/dL) predicted a serum albumin <20 g/L (<2.0 g/dL) with 70% sensitivity and 80% specificity. For dogs with known risk factors where specificity optimization may be appropriate, refractometer TPP<50 g/L (<5.0 g/dL) and <48 g/L (<4.8 g/dL) predicted hypoalbuminemia at each level with >95% specificity, although sensitivity was poor. Refractometer TPP<58 g/L (<5.8 g/dL) predicted serum total protein of <40 g/L (<40 g/dL) with sensitivity of 82% and specificity of 84%. Hypercholesterolemia and hyperglycemia significantly affected TPP readings; an increase in serum glucose by 10 mmol/L (180 mg/dL) was associated with an average independent increase in refractometer TPP of 2.27 g/L (0.23 g/dL) (P<0.001, 95% confidence interval=1.08-3.47) and an increase in serum cholesterol of 1 mmol/L (38.6 mg/dL) was associated with an average independent increase in refractometer TPP of 1.36 g/L (0.14 g/dL) (P<0.001, 95% confidence interval=1.12-1.59). CONCLUSION: Suboptimal sensitivity limits the use of refractometric TPP for prediction of hypoalbuminemia in the context of patient screening; a high proportion of false negatives may result. However, identification of a refractometric TPP<58 g/L is strongly indicative of both serum hypoalbuminemia and hypoproteinemia, with high specificity, and warrants further investigation. Refractometric readings may be falsely increased in patients with hyperglycemia or hypercholesterolemia.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.323
Teacher spread0.261 · 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".

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Citations19
Published2011
Admission routes1
Has abstractyes

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