Kelley, Barbara R

Abstract Background Rapid testing for Neisseria gonorrhoeae, Chlamydia trachomatis, and Trichomonas vaginalis may be useful for antibiotic stewardship initiatives. Our institution recently implemented the second-generation Visby Medical Sexual Health Test (Visby Gen2) for rapid diagnosis of STIs in our emergency department. Here we (1) compared result concordance of the (Visby Gen2) to the first-generation Visby Medical Sexual Health Click Test (Visby Gen1), (2) compared assay failure rates of the Visby Gen1 to Gen2 tests, and (3) compared result turnaround time (TAT) for clinically ordered rapid STI tests to central laboratory STI results. Methods Accuracy was assessed using residual clinical samples in Aptima buffer submitted for routine molecular STI testing (C. trachomatis, N. gonorrhoeae, and T. vaginalis) in the central laboratory on the Panther platform (Hologic). Aptima samples were diluted 1:33 in Visby collection buffer prior to testing on the Visby cartridge. Clinically reported results were used as reference results. Diluted samples with discordant results were re-tested on the reference method and the result from the dilution was used in calculations. Assay failure rates were calculated as the number of failed assays compared to the total assays performed. TAT for rapid and central lab testing was calculated as time of sample received in laboratory to time verified in laboratory information system. Results For Visby Gen1 we observed negative concordance of 100% (41/41) for C. trachomatis, 97.5% (39/40) for N. gonorrhoeae, and 97.1% (34/35) for T. vaginalis. Positive concordance was 91.7% (11/12) for C. trachomatis, 100% (11/11) for N. gonorrhoeae, and 100% (17/17) for T. vaginalis. For Visby Gen1 we observed a 10.5% (12/114) cartridge failure rate. For Visby Gen2, we observed negative concordance of 100% (59/59) for C. trachomatis, 100% (63/63) for N. gonorrhoeae, and 100% (55/55) for T. vaginalis while positive concordance was 100% (10/10) for C. trachomatis, 100% (6/6) for N. gonorrhoeae, and 90.9% (10/11) for T. vaginalis. The Visby Gen2 assay displayed a 4.9% (4/81) cartridge failure rate. Six weeks after implementing the Visby Gen2 assay in our ED, rapid STI panel TAT was 0.48 hours on average (n=20). In the central laboratory the average TAT was 22.31 hours (n=7892). Conclusions Assay concordance to reference method was similar for Visby Gen1 and Gen2 assays. The cartridge failure rate improved by 46.7% with the Gen2 assay which should decrease the need to repeat testing due to assay failure. Result TAT decreased by 97.8% when comparing rapid Visby results to central laboratory. Therefore, Visby STI testing using the Gen2 assay can provide accuracy and rapid results likely to facilitate more rapid patient management.

Abstract Background Managing preanalytical variables is critical to providing quality laboratory test results. However, this can be a challenge for laboratory staff, particularly with manual detection of interfering substances and complicated workflows. For coagulation testing, we assess specimen integrity and acceptability by visual checks and quantification of interfering substance on a chemistry analyzer. To improve this subjective process, we evaluated the technical performance of a new model of coagulation analyzer with automated preanalytical specimen integrity detection. Our objective was to determine if we could reduce the number of specimens requiring visual inspection/off-analyzer interference testing in order to simplify our testing workflow. Methods Citrated plasma specimens received in the Hospital Clinical Laboratory at Mayo Clinic (Rochester, MN) were tested on the TOP ACL 500 or TOP ACL 550 Series Coagulation analyzers (Werfen, Boston, MA) according to manufacturer’s instruction. Specimens tested on the TOP 500 were visually inspected for hemolysis, icterus, and lipemia (HIL). If the technologist detected a possible interferent, an aliquot of plasma was analyzed on our cobas c501 chemistry analyzer (c501) (Roche Diagnostics, Indianapolis, IN) to obtain HIL values. Laboratory-established or manufacturer-defined interference thresholds were applied in determining specimen acceptability. For samples tested on the TOP 550, specimen integrity was assessed by the instrument’s automated interference detection module. The analyzer reported HIL as an “interference cloud” or estimated range, rather than a single value like the c501. HIL values were estimated by visual assessment of the low end of the “interference cloud”. Values were confirmed on the c501 only for specimens with an “interference cloud” at/exceeding the test-specific interference thresholds. We analyzed data from a 2-month period pre- (TOP 500) and post-implementation (TOP 550). The percent of specimens requiring quantitation/confirmation on the c501 was calculated. Statistical significance was calculated using the Chi-squared test where significance was defined as p<0.01. Correlation between c501 and TOP 550 estimated HIL values was evaluated. Results A total of 2.2% (171/7605) and 1.3% (113/8983) of specimens tested on the TOP 500 and TOP 550, respectively, required HIL measurements on the c501 (p<0.001). Of those samples, 8.2% (14/171) and 14.2% (16/113) from the TOP 500 and TOP 550, respectively, had HIL values above the interference thresholds and were rejected by the laboratory. Comparison of the estimated HIL values from the “interference cloud” and from the c501 resulted in slopes (Pearson correlation coefficients) of: H 1.56 (0.77), I 0.67 (0.97), and L 1.35 (0.99). Conclusions In comparison to our workflow with visual assessment of interference, use of the automated interference detection functionality on the TOP 550 instrument resulted in a lower percentage of specimens requiring HIL measurements on the chemistry analyzer. Agreement between interference measurements obtained on the c501 and the TOP 550 was moderate where TOP 550 overestimated the degree of hemolysis and lipemia and underestimated icterus. Implementation of automated interference detection on the TOP 550 analyzer improved our workflow by eliminating the need for tedious and subjective visual checks and reducing the percentage of specimens requiring additional HIL measurements.

Abstract Background Turnaround time (TAT), defined as time of collection to time of result verification, is monitored monthly for cardiac Troponin (cTnT). Within our STAT laboratory, our TAT goal is 85% of cTnT results verified within 45 min. In October 2021, our lab began observing an increase in TAT. A quality improvement project was launched to identify a root cause and possible solutions. Methods cTnT TAT data from the Hospital Clinical Laboratory (STAT lab) at Mayo Clinic, Rochester, MN was extracted from our Laboratory Information System (LIS) using Tableau (Salesforce Inc., Seattle, WA). The data were categorized into three components: collection time, in lab processing and testing time, and time to result verification. Goal metrics for each component are: collection <10 min, in lab processing and testing <25 min, and result verification to LIS <5 min. The average time for each component and percentage not meeting TAT goals were calculated in Microsoft Excel. TAT while performing manual verification of results (January 2022) and after autoverification was implemented (December 2022) were compared. Results Prior to implementation of cTnT autoverification, total orders for January 2022 were 1408 with 82.0% meeting TAT of 45 min. Of the 18.0% not meeting TAT, 207 (14.7%) orders exceeded goals for one or more components (percentages do not total 100%): collection delays 131 (63.0%), in lab processing and testing delay 175 (85.0%), and delay in result verification to LIS 80 (39.0%). For those orders not meeting the 45 min TAT goal, mean times were 17.6, 40.3, and 8 min for collection time, in lab processing and testing, and result verification to LIS, respectively. Post implementation of autoverification, total orders for December 2022 were 1444 with 88.6% meeting TAT of 45 min. Of the 11.4% not meeting TAT, 93 (6.4%) orders were outside goals for multiple components: collection delays 51 (55.0%), in lab processing and testing delay 67 (72.0%), and result verification to LIS 0 (0.0%) orders. For those orders not meeting the 45 min TAT goal, mean times 16.6, 39.7, and 0 min for collection time, in lab processing and testing, and result verification to LIS, respectively. Conclusion Achieving TAT goals agreed upon by the laboratory and clinical practice is critical to quality patient care. An investigation into our delayed TAT for cTnT highlighted several opportunities for intervention within the control of the lab. We chose to implement autoverification of results to easily and consistently eliminate the time required for manual result verification. TAT was improved by 6.6% (82.0% to 88.6%) through autoverification of results, allowing technologists to focus on other clinical work.

Abstract Background Analytical outliers (fliers) occur with most troponin methods and can adversely affect patient management. We compared the analytical outlier rates for the Roche 5th generation Troponin T STAT (cTnT) reformulated (biotin-insensitive) reagent using a Cobas e601 analyzer (Indianapolis, IN) to rates observed in a previous study using the biotin-sensitive reagent on a Cobas e411 analyzer. Methods Plasma separator tubes (PST) were collected from hospital patients with orders for clinical cTnT testing. PST samples were centrifuged for 3 min at 4000g and analyzed using the biotin-insensitive cTnT Gen 5 assay on a Roche Cobas e601 immunoassay system. If samples displayed measurable cTnT Gen 5 (≥6 ng/L), samples were stored at 2–8 °C within 2 h of initial measurement (N = 2555). Within 24 h of initial analysis, samples were warmed to room temperature, aliquoted, re-centrifuged at 4000g for 3 min, and cTNT was re-measured on the same analyzer. Outlier rates were compared to a previous study (N = 1997) using nearly identical study design but using biotin-sensitive Roche 5th Gen cTnT reagent on an e411 analyzer. We defined analytical outliers by three methods: Repeat value (after aliquoting and re-centrifugation) that differed from the initial value for all samples with measurable cTnT by a critical difference (CD): where CD = z × √2 × SDanalytical, with a z-value of 3.719 and using SD from best fit line of precision vs cTnT concentration. Precision experiments were performed using four plasma pools in 5 × 5 precision experiment on the e411 analyzer. Using the same CD but considering only initial cTnT values <100 ng/L, those are most likely to be clinically significant or lead to misinterpretation. Using CD for initial values <100 ng/L, and a fixed 10% difference between replicates for initial values ≥100 ng/L, accounting for our practice of reporting the cTnT “delta” in percent (rather than absolute) for values ≥100 ng/L. Comparisons of outlier rates between the biotin-sensitive and biotin-insensitive reagents were performed using Pearson’s chi-squared test. Results Using the CD the total number of outliers that were observed for the biotin-insensitive reagent on the e601 was 208/2555 (8.1%), compared to 68/1997 (3.4%) on the biotin-sensitive reagent measured on the e411 (P < 0.0001). Outliers were observed in 138 (6.4%) of samples with initial values < 100 ng/L using the biotin-insensitive reagent on the e601 compared to 45 (2.6%) of such samples on the e411 (P < 0.0001). Using the Z score method to define outliers for initial values <100 ng/L and a fixed 10% to define outliers for initial values ≥100 ng/L, the outlier rate was 151 (5.9%) for the biotin-insensitive reagent on the e601 compared to 53 (2.7%) on the e411 (P < 0.0001). Conclusions Analytical outliers occurred more frequently using the reformulated (biotin-insensitive) reagent on the Roche Cobas e601 analyzer, compared to outlier rates observed for biotin-sensitive reagent on the Cobas e411.