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Strategies to reduce the risk of contrast nephropathy: an evidence-based approach

2006· review· en· W2334669479 on OpenAlexaff
Neesh Pannu, Marcello Tonelli

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2006
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsInstitute of Health EconomicsUniversity of Alberta
Fundersnot available
KeywordsMedicineNephropathyIntensive care medicineContrast-induced nephropathyClinical trialContext (archaeology)Internal medicineEndocrinology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Contrast nephropathy is a common complication associated with angiographic procedures that carries significant morbidity and mortality. Recent clinical trials of prophylactic strategies have reported contradictory results. This review presents recent insights into the pathophysiology of contrast nephropathy and reviews trial results in this context. RECENT FINDINGS: A prediction rule has been developed to better identify patients at risk of developing contrast nephropathy. Factors other than osmolality play a significant role in the pathogenesis of contrast nephropathy, at least for agents with osmolalities of 800 mOsm/kg or less. New randomized trial data do not support a role for N-acetylcysteine in contrast nephropathy prophylaxis and there is additional evidence that fenoldopam is ineffective. Pooled analyses of theophylline prophylaxis trials are inconclusive. Theoretical and clinical data suggest that ascorbic acid may be renoprotective, but this requires further study. SUMMARY: The overall incidence of contrast nephropathy remains low. Available evidence supports the use of hydration and low volumes of iso-osmolar or low-osmolar contrast in patients at risk of developing contrast nephropathy. Heterogeneity has affected interpretability of interventional trials of N-acetylcysteine or theophylline prophylaxis strategies. Future clinical trials must identify and target moderate-risk to high-risk patients and ensure that proven therapies are included in trial protocols.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0060.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.223
GPT teacher head0.435
Teacher spread0.212 · 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 designSystematic review
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

Citations17
Published2006
Admission routes1
Has abstractyes

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