ReviewEuropean radiology2016
Estimating GFR prior to contrast medium examinations--what the radiologist needs to know!
Review in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.
- Preventing contrast medium-induced acute kidney injury : Side-by-side comparison of Swedish-ESUR guidelines.European radiology · 2018Pooled it
- First-in-Human Phase 1 Study to Evaluate the Clinical Pharmacology Properties of RBN-3143, a Novel Inhibitor of Mono-Adenosine Diphosphate Ribosyltransferase-PARP14.Clinical pharmacology in drug development · 2025Trial
- Urinary NGAL, IGFBP-7, and TIMP-2: novel biomarkers to predict contrast medium-induced acute kidney injury in children.Renal failure · 2022Trial
- Absolute and relative GFR and contrast medium dose/GFR ratio: cornerstones when predicting the risk of acute kidney injury.European radiology · 2024Article
- A unique case of nephrogenic systemic fibrosis from gadolinium exposure in a patient with normal eGFR.BMJ case reports · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
unlabelledCreatinine-based equations to estimate glomerular filtration rate (GFR) are increasingly used in radiological practice and in studies on contrast medium-induced acute kidney injury (CIAKI). Their use is recommended in guidelines and contrast medium textbooks to identify patients at risk of CIAKI or nephrogenic systemic fibrosis. There is also an increased interest in cystatin C-based equations. Adopting GFR equations requires local creatinine and cystatin C assay calibrations to equal those used in developing the equations to avoid overestimation or underestimation of renal function. Methods should preferably be traceable to international standards, and assay traceability should be defined in CIAKI studies. Absolute GFR (mL/min) should be used when dosing contrast media and relating the dose to CIAKI instead of commonly used relative GFR (mL/min/1.73 m(2)) estimates. Accuracy of creatinine and cystatin C equations (percentage of GFR estimates within 30% of measured GFR) ranges between 75% and 85%. Equations combining creatinine and cystatin C may reach 90%, an accuracy similar to clearance methods (used as a reference test when developing and validating equations) when compared to the gold standard, renal clearance of inulin. The local laboratory or nephrology experts should be consulted in matters of method calibration and choice of GFR equation. KEY POINTS: • Traceability of creatinine/cystatin C assays used in GFR equations must be defined. • Absolute, not relative, GFR should be used when dosing contrast media. • Consult the local laboratory or nephrologist to choose the proper GFR equation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.