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A candidate reference method using ICP-MS for sweat chloride quantification

Overview of attention for article published in Clinical Chemistry and Laboratory Medicine, October 2015
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Title
A candidate reference method using ICP-MS for sweat chloride quantification
Published in
Clinical Chemistry and Laboratory Medicine, October 2015
DOI 10.1515/cclm-2015-0506
Pubmed ID
Authors

Jake T. Collie, R. John Massie, Oliver A.H. Jones, Paul D. Morrison, Ronda F. Greaves

Abstract

The aim of the study was to develop a method for sweat chloride (Cl) quantification using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to present to the Joint Committee for Traceability in Laboratory Medicine (JCTLM) as a candidate reference method for the diagnosis of cystic fibrosis (CF). Calibration standards were prepared from sodium chloride (NaCl) to cover the expected range of sweat Cl values. Germanium (Ge) and scandium (Sc) were selected as on-line (instrument based) internal standards (IS) and gallium (Ga) as the off-line (sample based) IS. The method was validated through linearity, accuracy and imprecision studies as well as enrolment into the Royal College of Pathologists of Australasia Quality Assurance Program (RCPAQAP) for sweat electrolyte testing. Two variations of the ICP-MS method were developed, an on-line and off-line IS, and compared. Linearity was determined up to 225 mmol/L with a limit of quantitation of 7.4 mmol/L. The off-line IS demonstrated increased accuracy through the RCPAQAP performance assessment (CV of 1.9%, bias of 1.5 mmol/L) in comparison to the on-line IS (CV of 8.0%, bias of 3.8 mmol/L). Paired t-tests confirmed no significant differences between sample means of the two IS methods (p=0.53) or from each method against the RCPAQAP target values (p=0.08 and p=0.29). Both on and off-line IS methods generated highly reproducible results and excellent linear comparison to the RCPAQAP target results. ICP-MS is a highly accurate method with a low limit of quantitation for sweat Cl analysis and should be recognised as a candidate reference method for the monitoring and diagnosis of CF. Laboratories that currently practice sweat Cl analysis using ICP-MS should include an off-line IS to help negate any pre-analytical errors.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 11%
Student > Postgraduate 2 11%
Professor > Associate Professor 2 11%
Lecturer 1 5%
Student > Bachelor 1 5%
Other 4 21%
Unknown 7 37%
Readers by discipline Count As %
Chemistry 3 16%
Medicine and Dentistry 3 16%
Biochemistry, Genetics and Molecular Biology 1 5%
Engineering 1 5%
Unknown 11 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 October 2015.
All research outputs
#16,721,717
of 25,374,647 outputs
Outputs from Clinical Chemistry and Laboratory Medicine
#1,203
of 2,902 outputs
Outputs of similar age
#164,708
of 290,681 outputs
Outputs of similar age from Clinical Chemistry and Laboratory Medicine
#19
of 76 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,902 research outputs from this source. They receive a mean Attention Score of 3.8. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 290,681 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.