CSCC 2020 VIRTUAL CONFERENCE PROGRAM
“This event is an Accredited Group Learning Activity as defined by the CSCC/CACB Professional Development Program.”
« Cette activité est une activité de formation collective agréée selon la définition établie par le Programme de perfectionnement professionnel de la SCCC et l’ACBC. »
Thank you to our generous sponsors
|PLATINUM SPONSOR||GOLD SPONSOR|
| Thursday August 27, 2020
Top Abstract Presentations
|Chair:||Mohamed Abouelhassan, Clinical Biochemist, Lifelabs, Toronto ON|
|1205||Preliminary consensus of core laboratory quality indicators among academic teaching hospitals of the University of Toronto|
|Presenter:||Paul Yip, Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, ON|
Objectives: The ISO 15189 standard requires laboratories to implement quality indicators (QI) to monitor and evaluate performance. Individual organizations define their own indicators and methodology, which limits the ability to compare metrics across laboratories. We sought to identify common QIs and potential gaps that could aid to improve performance and patient safety more broadly.
Design and Methods: The study was initiated within the LMP Quality Council and focused on QIs associated with biochemistry and hematology. Information on QIs was obtained through review of operating procedures, process charts, and performance scorecards. The IFCC Model of Quality Indicators framework was used to organize QIs from six academically affiliated hospital laboratories. Individual QIs from participating institutions were given a point based on similarity to each IFCC recommendation. QIs with the most points were selected to establish a preliminary consensus.
Results: The initial list identified 10 potential QIs which spanned the entire testing process. Only misidentification errors was common across all 6 laboratories. Inappropriate turnaround times (TATs), hemolyzed samples, unacceptable performances in EQA-PT schemes, and critical results notification, were the next most common QIs that were used in 5 laboratories. TAT monitoring included STAT analysis for potassium, troponin, and WBC count. The remaining QIs that were used in 4 laboratories were STAT INR TAT, incorrect fill level, and clotted samples.
Conclusions: The selected QIs are considered high priority for their impact on patient safety. Current efforts aim to adopt harmonized data collection and reporting systems throughout the Toronto region and share the LMP experience with other centers across Canada.
|1225||CLSI-based verification of CALIPER pediatric reference intervals for endocrine and fertility hormones on the Abbott Alinity platform|
|Speaker:||Mary Kathryn Bohn, CALIPER Project, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto ON|
Background: Reference intervals (RIs) are essential for accurate test result interpretation. The Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) has developed age- and sex-specific RIs for over 180 biomarkers on several analytical platforms. In the current study, published CALIPER RIs for nine immunoassays on the Abbott ARCHITECT platform were assessed for verification on the new Abbott Alinity platform using healthy pediatric serum samples.
Methods:Based on CLSI guidelines, 100 CALIPER serum samples were analyzed for nine immunoassays (free thyroxine, free triiodothyronine, total thyroxine, total triiodothyronine, thyroid stimulating hormone, follicle stimulating hormone, luteinizing hormone, progesterone, and 25-hydroxy Vitamin D) on the Abbott Alinity. The percentage of test results falling within published ARCHITECT confidence and reference limits was determined for each analyte. If ≥ 90% of test results fell within the confidence limits of published CALIPER RIs, they were considered verified.
Results: Of the nine immunoassays assessed, eight met the criteria for RI verification with results from ≥ 90% of results falling within ARCHITECT confidence limits. CALIPER RIs previously published for free thyroxine on the ARCHITECT platform did not verify on the Alinity platform, with 67% of samples falling within confidence limits.
Conclusion: Our data demonstrate excellent concordance between the Abbott ARCHITECT and Alinity immunoassays, as well as the robustness of previously established CALIPER RIs for nine endocrine and fertility hormones, eliminating the need for de novo RI studies for most parameters. These results can be expected to facilitate pediatric test result interpretation in institutions using the new Alinity platform.
|1245||CALIPER pediatric reference value distributions for plasma cytokines and chemokines and establishment of age-stratified reference intervals on the ProteinSimple Ella platform|
|Speaker:||Lusia Sepiashvilli, Clinical Biochemist, The Hospital for Sick Children, Toronto, ON|
Background: The objective of this study was to establish pediatric reference values and cut-offs for 8 plasma cytokines and chemokines in the CALIPER cohort to support their interpretation.
Methods:Healthy children and adolescents (n=311), aged 1-19 were recruited as part of CALIPER with informed consent. Analytes were measured in EDTA plasma using multiplex immunoassays (Panel 1: CD163, CXCL-9/MIG, IFN-& gamma;, TNF-α; Panel 2: IL-1β, IL-6, IL-10, IL-18, ProteinSimple® Ella™, Bio-Techne). Age and sex partitions were statistically evaluated using the Harris and Boyd method. After outlier removal, reference intervals were calculated using the non-parametric rank (n>120) and robust (n≤120) method, following CSLI C28-A3 guidelines. Additionally, 75th and 95th percentile cut-offs were determined.
Results: Three types of reference value distributions were observed: (a) consistent concentrations throughout age and sex: IL-6, and IFN-γ (b) gradual concentration decrease with age: CD163, TNF-α, CXCL-9/MIG, and IL-10 (c) sharp rise in concentrations from 4-<14y with significantly lower concentrations at earlier and later ages: IL-1β and IL-18. Many analytes showed dynamic concentration changes requiring age partitioning. Unique intervals were required from 1-<8y for CXCL-9/MIG, IL-10, and TNF-α. CD163, IL-18 and IL-1β required 3 age partitions; IL-6, and IFN-γ required one. CD163 demonstrated sex-differences in ages 8-<13y. IL-6, IL-1β, and IFN-γ were undetectable in 12%, 18%, and 49% of subjects, respectively.
Conclusions: Robust reference values and cut-offs for 8 cytokines and chemokines in a healthy pediatric population described herein are expected to support laboratory assessment of pediatric patients and underscore the importance of age stratification for these novel parameters.
|1305||Evidence-based harmonization of reference intervals for thyroid markers across Canada: Harnessing the power of large inter-provincial outpatient datasets and direct reference data from healthy Canadians|
|Speaker:||Zahraa Mohammed-Ali, University of Toronto, Toronto ON|
Objective: There is an evident need for reference interval (RI) harmonization across Canada for common laboratory tests, including immunoassays. The Canadian Society of Clinical Chemists (CSCC) Harmonized Reference Interval (hRI) Working Group aims to establish evidence-based hRIs and support their implementation across Canada. Here, we report recommended hRIs for endocrine markers.
Methods:Data for thyroid stimulating hormone (TSH), free T4 (FT4), and free T3 (FT3) were extracted for outpatients (19-<80 years, n=603504-8642574) from four centers, DynaLIFE Alberta (Siemens ADVIA), Dynacare Ontario (Roche cobas), LifeLabs British Columbia and Ontario (Abbott ARCHITECT) from 01/01/2017-12/31/2018. For each analyte, center-, age- and sex-specific differences were determined using the Harris & Boyd method. Outliers were then removed. Finally, center-specific and Canada-wide RIs were derived using the Arzideh method and compared to direct data from the Canadian Health Measures Survey (CHMS) and other harmonization initiatives to propose hRIs.
Results: No endocrine markers showed statistical sex- and/or age-specific differences. Thus, one harmonized partition (19-<80 years) is recommended for TSH (0.60-4.55 mIU/L), FT4 (9.5-15.5 pmol/L) and FT3 (3.0-5.7 pmol/L). There were no center-specific differences for TSH. However, FT3 and FT4 data from LifeLabs (British Columbia and Ontario) was significantly lower compared to Dynacare (Ontario) and DynaLIFE (Alberta).
Conclusion: The reported evidence-based recommendations are supported by robust analysis of large inter-provincial datasets and hRI group discussions that included comparisons to direct and indirect data from other initiatives. Next steps include investigating the discrepancies between LifeLabs and other centres, validating recommended hRIs, and developing Canada-wide implementation strategies.