Evidence map›Paper›PMID 28321322›Full record

ArticleCanadian journal of kidney health and disease2017

Creatinine Assay Attainment of Analytical Performance Goals Following Implementation of IDMS Standardization: Further Improvements Required.

Elizabeth Sunmin Lee, Christine P Collier, Christine A White

Open access · goldAbstract read
In one paragraph

Article in Canadian journal of kidney health and disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 10 citations in OpenAlex.

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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 at 1 institution in 1 country.

Elizabeth Sunmin LeeDivision of Nephrology, Department of Medicine, Queen's University, Kingston, Ontario, Canada.
Christine P CollierDepartment of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada.
Christine A WhiteDivision of Nephrology, Department of Medicine, Queen's University, Kingston, Ontario, Canada.
Queen's University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe international initiative to standardize creatinine (Cr) assays by tracing reference materials to Isotope Dilution Mass Spectrometry (IDMS) assigned values was implemented to reduce interlaboratory variability and improve assay accuracy.

objectiveThe aims of this study were to examine whether IDMS standardization has improved Cr assay accuracy (bias), interlaboratory variability (precision), total error (TE), and attainment of recommended analytical performance goals.

methodsExternal Quality Assessment (EQA) data (n = 66 challenge vials) from Ontario, Canada, were analyzed. The bias, precision, TE, and the number of EQA challenge vials meeting performance goals were determined by assay manufacturer before (n = 32) and after (n = 34) IDMS implementation.

resultsThe challenge vials with the worst bias and precision were spiked with known common interfering substances (glucose and bilirubin). IDMS standardization improved assay bias (10.4%-1.6%,

conclusionsWhile IDMS standardization has improved Cr assay accuracy and thus reduced TE, significant interlaboratory variability remains. Contemporary Cr assays do not currently meet the standards required to allow for accurate and consistent estimated glomerular filtration rate assessment and chronic kidney disease diagnosis across laboratories. Further improvements in Cr assay performance are needed.

Indexed as

chronic kidney diseasecreatinineExternal Quality AssessmentIDMS traceable

Identifiers

PMID28321322
PMCPMC5347424
OpenAlexW2589810629

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.