Evidence map›Paper›PMID 27436026›Full record

ArticleEuropean radiology2017

Prediction of presence of kidney disease in patients undergoing intravenous iodinated contrast enhanced computed tomography: a validation study.

Sanne M Schreuder, Jaap Stoker, Shandra Bipat

Abstract readValidation Study
In one paragraph

Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sanne M SchreuderDepartment of Radiology, Academic Medical Centre, G1-212, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands. s.m.schreuder@amc.uva.nl.
Jaap StokerDepartment of Radiology, Academic Medical Centre, G1-212, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
Shandra BipatDepartment of Radiology, Academic Medical Centre, G1-212, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo validate two previously presented models containing risk factors to identify patients with estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m

methodsIn random patients undergoing intravenous contrast-enhanced computed tomography (CECT) the following risk factors were assessed: history of urological/nephrological disease, hypertension, diabetes mellitus, anaemia, congestive heart failure, other cardiovascular disease or multiple myeloma or Waldenström disease. Data on kidney function, age, gender and type and indication of CECT were also registered. We studied two models: model A-diabetes mellitus, history of urological/nephrological disease, cardiovascular disease, hypertension; model B-diabetes mellitus, history of urological/nephrological disease, age >75 years and congestive heart failure. For each model, associations with eGFR <60 ml/min/1.73 m

resultsA total of 1,001 patients, mean age 60.36 years were included. In total, 92 (9.2 %) patients had an eGFR <60 ml/min/1.73 m

conclusionsModel B resulted in the lowest superfluous eGFR measurements while detecting all patients with eGFR <45 ml/min/1.73 m KEY POINTS: • Less than 10% of patients undergoing contrast-enhanced CT have an eGFR of <60ml/min/1.73m

Indexed as

Models, BiologicalAdministration, IntravenousAdultAgedAge FactorsCardiovascular DiseasesContrast MediaDiabetes ComplicationsFemaleGlomerular Filtration RateHumansHypertensionIodineKidneyKidney DiseasesMaleContrast MediaIodineAcute kidney injuryComputed tomographyContrast mediumKidney diseaseRisk factors

Identifiers

PMID27436026
PMCPMC5334394

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Registered trials

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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.