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Record W2024839536 · doi:10.1159/000184947

Nephrotoxicity of High- and Low-Osmolality Contrast Media

2008· article· en· W2024839536 on OpenAlexaff
Anthony M. Jevnikar, K.J.C. Finnie, Bradley M. Dennis, David T. Plummer, A. Avila, A. L. Linton

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsVictoria HospitalWestern University
Fundersnot available
KeywordsNephrotoxicityIohexolMedicineExcretionRenal functionDiatrizoateInternal medicineEndocrinologyUrine osmolalityOsmoleUrinary systemRenal physiologyUrologyKidney

Abstract

fetched live from OpenAlex

Nephrotoxicity of radio-opaque contrast media (CM) is generally believed to involve toxic injury of proximal tubular cells. Measurement of urinary tubular enzyme excretion has been advocated as a sensitive marker of such toxic injury. It has been claimed that the new low-osmolality or nonionic CM reduce the incidence of nephrotoxicity but this remains uncertain. We studied 23 patients with normal renal function undergoing coronary angiography; patients were randomized into three groups receiving either diatrizoate (1,800 mmol/kg H2O), ioxaglate (600 mmol/kg H2O) or iohexol (850 mmol/kg H2O). Urinary excretion of a panel of enzymes increased significantly in all groups by 20 h (p less than 0.05 to less than 0.005). Alanine aminopeptidase excretion at 20 h was greater after the administration of high osmolality ionic CM than with the others but all three CM produced a similar pattern of enzyme excretion. No significant change in glomerular filtration rate was found in any group so the significance of the enzymuria remains uncertain.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.049
GPT teacher head0.328
Teacher spread0.280 · 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

Citations51
Published2008
Admission routes1
Has abstractyes

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