Point of Care Testing (POCT) refers to clinical laboratory testing performed outside the central laboratory, nearer to the patient and sometimes at the patient bedside. The testing is usually performed by clinical staff, such as physicians or nurses, who are not laboratory trained. This document was developed by the POCT Interest group of the Canadian Society of Clinical Chemists (CSCC) as practical guidance for quality assurance practices related to POCT performed in hospital and outside hospital environments. The aspects of quality assurance addressed in this document include: (1) device selection, (2) initial device verification, (3) ongoing device verification, (4) ongoing quality assurance including reagent and quality control (QC) lot changes, and (5) quality management including operator and document management.

Point of care testing (POCT) is one of the fastest growing disciplines in clinical laboratory medicine. POCT devices are widely used in both acute and chronic patient management in the hospital and primary physician office settings. As demands for POCT in various healthcare settings increase, managing the quality and regulatory compliance are continually challenging. Despite technological advances in applying automatic system checks and built-in quality control to prevent analytical and operator errors, poor planning for POCT connectivity and informatics can limit data accessibility and management efficiency which impedes the utilization of POCT to its full potential. This article will summarize how connectivity and data management system can improve timely access to POCT results, effective management of POCT programs, and ensure regulatory compliance.

Background: The StatSensor is a point-of-care device which measures creatinine in capillary whole blood. Previous studies reported an underestimation of the creatinine measurements at high creatinine concentrations and were performed in the prestandardization era for creatinine. Objective: This accuracy-based study evaluates the use of this device in kidney-transplanted patients and those with chronic kidney disease (CKD). Design: Cross-sectional diagnostic accuracy study. Setting: Nephrology outpatient clinic in an urban tertiary center. Participants: Adults with CKD or a functioning kidney transplant. Measurements: Duplicate StatSensor creatinine measurements were performed on capillary whole blood samples collected by direct fingerstick and SAFE-T-FILL collection device. Results were compared with simultaneous venous blood sampling for serum and plasma creatinine measured by an enzymatic method on the Roche Integra 400 mainframe analyzer with traceability to the ID-GC-MS (isotope dilution gas chromatography mass spectrometry) reference method. Methods: Deming regression, Pearson correlation coefficient, and Bland-Altman analysis were used to assess accuracy and comparability between capillary whole blood measured by StatSensor and plasma creatinine measured by routine analyzer with traceability to the reference method. Estimated glomerular filtration (eGFR) rates were calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and concordance with Kidney Disease Improving Global Outcomes (KDIGO) CKD stage classification was evaluated. Results: There were 60 participants (mean age = 61.9 ± 15.0 years, 55% men, 33% transplant, mean plasma creatinine = 137 ± 59 µmol/L). Bland-Altman analysis indicated a positive mean bias of 12.7 µmol/L between StatSensor fingerstick creatinine measurement and plasma creatinine. Comparison of eGFR (CKD-EPI) calculated from the StatSensor fingerstick creatinine versus plasma creatinine showed misclassification across all KDIGO CKD stages. Postanalytical correction of the bias did not improve misclassifications. The use of mean of duplicate StatSensor creatinine results did not improve performance compared with the use of singlet results. Limitations: Single center, limited participant numbers. Conclusions: The results of our study suggest that the limiting characteristics of the StatSensor device are not only bias, but also imprecision. The level of imprecision observed may influence clinical decision-making and limit the usefulness of StatSensor as a CKD screening tool. If choosing to utilize it for either screening for or monitoring CKD, it is essential that clinicians understand the limitations of point-of-care devices and apply this knowledge to test interpretation.

Background: Therapeutic drug monitoring of immunosuppressant drugs are used to monitor drug efficacy and toxicity and to prevent organ transplant rejection. This study evaluates the analytical performance of semi-automated electrochemiluminescence immunoassays (ECLIA) for cyclosporine (CSA), tacrolimus (TAC) and sirolimus (SRL) on the Roche cobas e 411 analyzer at a major transplant hospital to assess method suitability and limitations. Methods: Residual whole blood samples from patients undergoing immunosuppressant therapy were used for evaluation. Imprecision, linearity, functional sensitivity, method comparisons and lot-to-lot comparisons were assessed. Results: Total imprecision ranged from 3.3 to 7.1% for CSA, 3.9 to 9.4% for TAC, and 4.6 to 8.2% for SRL. Linearity was verified from 30.0 to 960.9 μg/L for CSA, from 1.1 to 27.1 μg/L for TAC, and from 0.5 to 32.3 µg/L for SRL. The functional sensitivity met the manufacturer’s claims and was determined to be <6.5 μg/L for CSA, 1.1 μg/L for TAC, and <0.1 µg/L for SRL (CV≤20%). Deming regression analysis of method comparisons with the ARCHITECT immunoassay yielded slopes of 0.917 (95%CI: 0.885-0.949) and r of 0.985 for CSA, 0.938 (95%CI: 0.895-0.981) and r of 0.974 for TAC, and 0.842 (0.810-1.110) and r of 0.982 for SRL. Deming regression analysis of comparisons with the LC–MS/MS method yielded slopes of 1.331 (95%CI: 1.167-1.496) and r of 0.969 for CSA, 0.924 (95%CI: 0.843-1.005) and r of 0.984 for TAC, and 0.971 (95%CI: 0.913-1.030) and r of 0.993 for SRL. Conclusions: The cobas e 411 ECLIA for CSA, TAC, and SRL have acceptable precision, linearity, and functional sensitivity. The method comparisons correlated well with the ARCHITECT immunoassay and LC–MS/MS and is fit for therapeutic drug monitoring

Background: Serum IgG4 is typically measured to investigate for Immunoglobulin G4-related Disease (IgG4-RD), a fibroinflammatory condition associated with polyclonal increase in serum IgG4. However, increased IgG4 can also be monoclonal, and little is known about IgG4 myeloma. Methods: We describe two cases of IgG4 myeloma without clinical, radiologic, or laboratory features of IgG4-related disease. Results: An 84 year old man presented with anemia and compression fractures and a 77 year old man presented with anemia, hypercalcemia and renal failure. Both had markedly elevated monoclonal serum IgG4, 34 g/L and 48 g/L in the beta region, and increased IgG positive bone marrow plasma cells, 50% and 80%, respectively. Neither had clinical or radiological manifestations of IgG4-related disease (IgG4-RD) such as salivary or lacrimal gland swelling, autoimmune pancreatitis , or retroperitoneal fibrosis. Both cases responded well to standard myeloma therapy. The IgG4 paraprotein caused spuriously elevated beta-2 microglobulin of 45.2 mg/L in case two due to interference with the assay. Conclusion: These cases illustrate the importance of performing serum protein electrophoresis in tandem with IgG subclasses to distinguish between polyclonal and monoclonal increases in serum IgG4. The lack of typical IgG4-RD features in these two patients suggests that monoclonal elevation in serum IgG4 alone is insufficient to cause the organ damage characteristic of IgG4-RD. Larger studies of IgG myeloma subtypes are warranted to explore whether IgG1, IgG2, IgG3 and IgG4 myeloma differ in natural history and whether the interference with beta-2 microglobulin is specific to IgG4 monoclonal proteins.