Nicklas, Michael

Abstract Background Hemoglobin A1c is used to assess glycemic control to both diagnose and monitor diabetes mellitus. Several different methodologies are available including high performance liquid chromatography (HPLC), capillary electrophoresis (CE), and immunoassay (IA). These methods are standardized and traceable to the Diabetes Control and Complications Trial (DCCT). The aim of this study was to evaluate the difference in HbA1c results between methods and percent of reportable results in variant samples. Methods The HPLC (Bio-Rad Laboratories, Inc; D-100), the CE(Sebia Inc; Capillarys 3), and IA(Roche Diagnostics Inc; Tina-quant Generation 3) were compared using two sets of residual patient samples left after physician ordered testing was complete: 1) samples with an absence of abnormal hemoglobin peaks (i.e. non-variant) detected by HPLC; 2) samples with abnormal hemoglobin peaks (i.e. variant) characterized by hemoglobin electrophoresis performed clinically or lacking an A1c peak by HPLC/CE. The samples were tested within manufacturers stability claims. 317 non-variant samples were compared between the HPLC and CE methods. The absolute difference was calculated for each method using this equation (HbA1c%avg – HbA1c%X) where HbA1c%avg is the average of the methods that produced reportable results and X is the result from each method evaluated. Differences less than or equal to +/-0.3% were considered acceptable. 28 of the 317 non-variant and 47 variant samples were tested by all 3 methodologies. The 47 variant samples grouped into 3 cohorts: common heterozygous variants (HbC, HbD, HbE, HbS and HbF, n=10), uncommon heterozygous variants (n=29) and homozygous variants lacking HbA (n=8). The absolute differences in variant sample results were calculated for samples that did not surpass manufacturer’s claims for producing an accurate result. The frequency of producing a numeric result in variant samples was calculated for each method. Results The HPLC/CE non-variant sample comparison (N=317) had results spanning the measuring range (3.8% - 14.0%) with average(range) of absolute difference=0.1(-0.4to0.6%) with 293/317(92.4%) samples within +/-0.3%. The HPLC/CE/IA non-variant sample comparison (N=28) had a result range=4.0%-9.4%, the average(range) of difference=0.1(-0.2to0.5%) with 25/28 (89.2%) of samples within +/-0.3%. Common heterozygous variant samples gave numeric results with no disqualifying flags in 9 of 10(HPLC), 8 of 10(CE), and 9 of 10(IA) samples tested. The average(range) difference from average=0.0(-0.3,0.5%) for HPLC, 0.0(-0.2,0.3%) for CE, and -0.1(-0.6,0.2%) for IA. Uncommon variant samples gave results in 4 of 29 (HPLC), 20 of 29 (CE), and 26 of 29 (IA) of samples tested. The average(range) difference from average=-0.1(-0.3,0.1%) for HPLC, 0.0(-1.0,1.1%) for CE, and 0.0(-1.1,1.0%) for IA. The homozygous variant (no HbA) samples gave results in 0 of 8 (HPLC), 0 of 8 (CE), and 4 of 8 (IA) of those tested. Conclusion All three methods meet their claims for accurately measuring hemoglobin A1c from non-variant and common hemoglobin variants. The advantage of HPLC and CE is the ability to identify hemoglobin variants that may impact HbA1c quantitation. The IA method provides the most numeric results. IA gave results even when HbA was absent. The lab should understand the capabilities and limitations of their HbA1c method on the population served.

Abstract Background Bicarbonate stability in serum depends on time, exposure to air, temperature, tube size and sample volume. With implementation of Cobas Connection Module (CCM) automation, the workflow for bicarbonate measurement needed to be re-evaluated. The aim of this study was to determine bicarbonate stability in filled 3.5 mL and 5 mL serum-separator tubes (SSTs) and capped and uncapped aliquot tubes on the CCM automation. Methods Bicarbonate was measured on a Cobas c701 (Roche Diagnostics) at various time points. SSTs (n=8) were centrifuged 6 min at 1649g ∼30 min post-collection. Serum was aliquoted (1 mL) into capped or uncapped tubes and kept ambient (15-25°C) on the CCM track for 0, 60, 90, 150, 180, 240 and 300 minutes (n=2 per time point). Primary SSTs (5mL n=4, and 3.5mL n=5) were uncapped on the CCM track and bicarbonate measured at baseline and 30 minute intervals through 6.5 hours. An absolute difference of +/- 4 mmol/L from baseline was considered acceptable. Results Bicarbonate concentrations decrease with time at rates dependent on whether the aliquot tube is capped or uncapped or the SST is 3.5 mL or 5 mL (Figure 1).Figure 1.Average decrease in bicarbonate concentration with time for capped aliquot tubes (black square), uncapped aliquot tubes (red circle), 3.5 mL serum separator tube (blue up triangle), 5 mL serum separator tube (green down triangle). Bars represent +/- 1SD. Conclusions Bicarbonate in serum is stable for testing for 2.5 hours in uncapped 1 mL aliquot tubes, 3.5 hours in capped 1 mL aliquot tubes, 3.5 hours in uncapped full 3.5 mL SST tubes and 6 hours in uncapped full 5 mL SST tubes at ambient temperatures (15-25°C). Bicarbonate testing can be accommodated by total laboratory automation but processes such as add-ons and retesting must be done with caution.

Abstract Background Thoroughly investigating single patient result errors may identify systemic, large-scale testing errors. The laboratory observed an event where a revision to a Total Bile Acid (TBA, Diazyme Laboratories, Inc.) patient result following a 22S quality control (QC) failure displayed a larger than expected difference (52 to 5mcmol/L). TBA is primarily used for diagnosis and monitoring of intrahepatic cholestasis of pregnancy with results >10mcmol/L considered elevated. Retrospective review of result revisions following QC failures (3/15/2017-5/30/2023) revealed that 50%(20/40) yielded result differences of >10mcmol/L(>20SD based on assay imprecision). The aim of this study was to apply a systematic approach to i) estimate the rate of TBA errors, ii) ensure accurate result reporting during investigation period, iii) perform root cause analysis (RCA), and iv) determine corrective and preventative action(s). Methods Residual samples from TBA testing (6/24-7/5/2023) were retested(n=158), differences >+/-3.0mcmol/L or 15% were confirmed on an alternate analyzer, and reports were revised. Automated repeat testing of TBA samples >10mcmol/L was operationalized 7/6/2023. Initial and repeat TBA results were compared(n=448) and results differing by >+/-20% were remeasured on an alternate analyzer. RCA was conducted using a fishbone diagram. NaOH reagent probe washes were implemented for TBA and the error rate was re-assessed. Assays run prior to TBA samples with errors (n=15) were identified. To assess reagent carryover a residual serum pool (TBA ∼5mcmol/L) was aliquoted into 5 tubes in a sample rack. The first sample in the rack was programmed to run an assay suspected of causing carryover followed by 4 TBA measurements. Mean±standard deviation(SD) TBA concentrations were calculated. TBA was also measured in the liquid reagent for amylase, lipase, acetylcholinesterase (ACE) and fructosamine. Results Initial TBA retesting yielded no errors when initial TBA was ≤10mcmol/L(n=51). For samples with TBA >10mcmol/L(n=107), 9(8.4%) had differences exceeding criteria with 8/9 being revised to ≤10mcmol/L. Analysis of automated patient repeat data showed a 3.8%(17/448) error rate when initial TBA >10mcmol/L. After NaOH reagent probe washes were implemented, the error rate decreased to 0.7%(3/448). Assays run directly before an erroneously high TBA result included: lactate, fructosamine, soluble transferrin receptor(STFR), lipase, and ACE. A serum TBA pool(mean±SD=5.1±0.4 mcmol/L,n=15) measured 37.6±1.2mcmol/L(n=3) and 6.7±0.7mcmol/L(n=3) after lipase and fructosamine, respectively. No other assays demonstrated carryover. TBA in lipase reagent compartment B and C was 653 and 649mcmol/L, respectively, and 653mcmol/L in fructosamine reagent compartment B. Conclusions A single patient TBA result revision was investigated and led to identification of reagent carryover causing erroneously high TBA results on the Roche c502 analyzer. Automatic, real-time, repeat testing was implemented to prevent reporting incorrect patient results until RCA could identify the cause. Occurrence rate of erroneous high TBA results decreased from 3.8% to 0.7% after implementation of NaOH washes on the instruments. Carryover experiments confirmed that lipase and fructosamine assays cause carryover when run prior to a TBA sample due to measurable TBA in the reagent. The lab is pursuing moving the fructosamine and lipase reagent to the Roche Cobas c701 to prevent the issue.

Abstract Background Hemolysis is a pre-analytic issue that challenges clinical laboratories. When a specimen with significant hemolysis is obtained in our laboratory, tests where the hemolysis threshold is exceeded are not reported and blood is recollected. Unfortunately, in a subset of patients, the recollected specimen is also hemolyzed (termed “recurrent hemolysis”). In these cases, the second recollection utilizes special collection and handling protocols (i.e., hand-carried to lab, plasma collection, etc.) to mitigate preventable causes of hemolysis. Lipemia is also a known contributor to specimen hemolysis. Mayo Clinic Rochester experienced an increased rate of hemolysis as well as recurrent hemolysis during the height of the COVID-19 pandemic (January 2022). The objective of this study was to investigate the increased rate of recurrent hemolysis and compare to a rate prior to the COVID-19 pandemic (January 2019). Methods Retrospective data analysis was performed for January 2019 (negative control) and January 2022. The number of Mayo Clinic Rochester hospital admissions, admitting diagnosis, medications administered, and number of test collections performed were obtained using reporting functionality in our Electronic Health Record (EHR), Epic. The Laboratory Information System, SoftLab, was utilized to obtain recollection rates due to hemolysis. Data were normalized to total patient admissions for the specified period to account for inter-year variability. R/R Studio was utilized to analyze and visualize the data. Pearson’s Chi-squared test for independence was performed on categorical variables (significance defined as P < 0.05). Results A 28% decrease in hospital admissions (n = 3958:Jan-22 vs n = 5517:Jan-19) and a 23% decrease in total specimens collected on hospitalized patients (n = 40 557:Jan-22 vs n = 52 373:Jan-19) was observed between Jan-19 to Jan-22. However, the laboratory observed a 6% increase in hemolyzed specimens (n = 256:Jan-22 vs n = 241:Jan-19). Recurrent hemolysis occurred in 24% (n = 62/256) of Jan-22 and 17% (n = 43/241) of Jan-19 hemolyzed specimens and required special handling protocols. COVID positive patients comprised 48% (n = 30/62) of those requiring special handling protocols in Jan-22. Further examination revealed 34% (n = 21/62) of Jan-22 and 12% (n = 5/43) of Jan-19 cases of recurrent hemolysis were due to lipemia (P < 0.01). Chart review highlighted a potential source of lipemia from the administration of propofol, a lipophilic sedative emulsion. Of those COVID positive cases with recurrent hemolysis due to lipemia (n = 15/30), 93% (n = 14/15) were receiving propofol at the time of collection (P < 0.001). Conclusion We observed increased rates of specimen hemolysis during the COVID-19 pandemic. While most hemolysis resolves upon specimen recollection, patients with recurrently hemolyzed specimens often require special specimen collection and handling protocols to mitigate hemolysis. Approximately half of the recurrent hemolysis cases in Jan 2022 were COVID-19 positive patients. Lipemia-induced hemolysis was also more frequent in this patient population presumably due to the administration of propofol, a lipophilic emulsion sedative commonly used for COVID positive patients requiring sedation and ICU-level care. It is critical to understand the variety of factors which may contribute to recurrent hemolysis, as intervening with specialized collection and handling protocols to reduce observed pre-analytical hemolysis is required to provide accurate and timely laboratory results.