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Record W2100288509 · doi:10.1503/cmaj.1040847

Nephropathy induced by contrast media: pathogenesis, risk factors and preventive strategies

2005· review· en· W2100288509 on OpenAlexvenueno aff
Ilan Goldenberg

Bibliographic record

VenueCanadian Medical Association Journal · 2005
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePathogenesisNephropathyIntensive care medicineDiabetes mellitusHeart failureDiabetic nephropathyClinical trialContrast-induced nephropathyKidneyInternal medicineBioinformaticsPathologyEndocrinology

Abstract

fetched live from OpenAlex

With the increasing use of contrast media in diagnostic and interventional procedures, nephropathy induced by contrast media has become the third leading cause of hospital-acquired acute renal failure. It is also associated with a significant risk of morbidity and death. The current understanding of the pathogenesis indicates that contrast-medium nephropathy is caused by a combination of renal ischemia and direct toxic effects on renal tubular cells. Patients with pre-existing renal insufficiency, diabetes mellitus and congestive heart failure are at highest risk. Risk factors also include the type and amount of contrast medium administered. Therapeutic prevention strategies are being extensively investigated, but there is still no definitive answer. In this article, we review the current evidence on the causes, pathogenesis and clinical course of contrast-medium nephropathy as well as therapeutic approaches to its prevention evaluated in clinical trials.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.328
Teacher spread0.303 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations378
Published2005
Admission routes1
Has abstractyes

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