Abstract
Background: 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).
Methods: 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.
Results: 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).
Conclusions: 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.
Acknowledgments
The Authors would like to thank Ross Wenzel, Royal North Shore Hospital, for providing their ICP-MS SOP for sweat Cl testing, Jeff Hughes (Program Leader, Chemistry, School of Applied Science, RMIT University) for all his advice and guidance on statistical matters and to PM Separations for their generous provision of the internal quality control materials.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organisation(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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