Transformation of Sequential Hospital and Outpatient Laboratory Data into Between-Day Reference Change Values.

BACKGROUND: Serial differences between intrapatient consecutive measurements can be transformed into Taylor series of variation vs time with the intersection at time = 0 (y0) equal to the total variation (analytical + biological + preanalytical). With small preanalytical variation, y0, expressed as a percentage of the mean, is equal to the variable component of the reference change value (RCV) calculation: (CVA2 + CVI2)1/2. METHODS: We determined the between-day RCV of patient data for 17 analytes and compared them to healthy participants' RCVs. We analyzed 653 consecutive days of Dartmouth-Hitchcock Roche Modular general chemistry data (4.2 million results: 60% inpatient, 40% outpatient). The serial patient values of 17 analytes were transformed into 95% 2-sided RCV (RCVAlternate), and 3 sets of RCVhealthy were calculated from 3 Roche Modular analyzers' quality control summaries and CVI derived from biological variation (BV) studies using healthy participants. RESULTS: The RCVAlternate values are similar to RCVhealthy derived from known components of variation. For sodium, chloride, bicarbonate calcium, magnesium, phosphate, alanine aminotransferase, albumin, and total protein, the RCVs are equivalent. As expected, increased variation was found for glucose, aspartate aminotransferase, creatinine, and potassium. Direct bilirubin and urea demonstrated lower variation. CONCLUSIONS: Our RCVAlternate values integrate known and unknown components of analytic, biologic, and preanalytic variation, and depict the variations observed by clinical teams that make medical decisions based on the test values. The RCVAlternate values are similar to the RCVhealthy values derived from known components of variation and suggest further studies to better understand the results being generated on actual patients tested in typical laboratory environments.

Average of Patient Deltas: Patient-Based Quality Control Utilizing the Mean Within-Patient Analyte Variation.

BACKGROUND: Because traditional QC is discontinuous, laboratories use additional strategies to detect systematic error. One strategy, the delta check, is best suited to detect large systematic error. The moving average (MA) monitors the mean patient analyte value but cannot equitably detect systematic error in skewed distributions. Our study combines delta check and MA to develop an average of deltas (AoD) strategy that monitors the mean delta of consecutive, intrapatient results. METHODS: Arrays of the differences (delta) between paired patient results collected within 20-28 h of each other were generated from historical data. AoD protocols were developed using a simulated annealing algorithm in MatLab (Mathworks) to select the number of patient delta values to average and truncation limits to eliminate large deltas. We simulated systematic error by adding bias to arrays for plasma albumin, alanine aminotransferase, alkaline phosphatase, amylase, aspartate aminotransferase, bicarbonate, bilirubin (total and direct), calcium, chloride, creatinine, lipase, sodium, phosphorus, potassium, total protein, and magnesium. The average number of deltas to detection (ANDED) was then calculated in response to induced systematic error. RESULTS: ANDED varied by combination of assay and AoD protocol. Errors in albumin, lipase, and total protein were detected with a mean of 6 delta pairs. The highest ANDED was calcium, with a positive 0.6-mg/dL shift detected with an ANDED of 75. However, a negative 0.6-mg/dL calcium shift was detected with an ANDED of 25. CONCLUSIONS: AoD detects systematic error with relatively few paired patient samples and is a patient-based QC technique that will enhance error detection.

Urinary metal concentrations among female welders.

As part of a Canada-wide study of women entering non-traditional trades [Women's Health in Apprenticeship Trades-Metalworkers and Electricians (WHAT-ME)], we examined spot urine samples from women welders in Alberta to determine whether urinary metal concentrations exceeded those of the general population, to compare levels to previously published urinary concentrations in male welders and to examine the relationship with welding tasks. Women mailed-in urine samples collected close to the time of completing a detailed exposure questionnaire, including welding tasks on their most recent day welding at work. Of 53 welders working in their trade, 45 had urinary creatinine >0.3-≤3.0g l(-1) and were included in analyses. Seven metals were examined for which both population and male welder urinary concentrations were available: cadmium, chromium, cobalt, copper, manganese, nickel, and zinc. Principal component analysis was used to extract three components from natural log transformed creatinine-corrected metal concentrations. Of the 45 women, 17 reported more than one main task. Overall two thirds worked in fabrication, a third on pipe welding, and smaller numbers on repair, in construction or other tasks: manual metal arc welding was reported by 62%, semi-automatic arc welding by 47%, and arc welding with a tungsten electrode by 15%. In multiple regression analyses, little relation was found between urinary metals and task or type of welding, except for cadmium where lower levels were seen in those reporting semi-automatic manual welding (after adjustment for age and smoking). The proportion of women welders exceeding the selected general population 95th percentile was high for manganese (96%) and chromium (29%). Urinary metal concentrations were similar to those reported for male welders with only manganese, with a geometric mean in women of 1.91 µg g(-1) creatinine, and perhaps copper (11.8 µg g(-1) creatinine), consistently lower in male welders. Although not evident from the task analysis reported here, differences in exposure by sex may be explained by type of welding or by other work practices. A closely comparable cohort of male welders would be necessary to examine this hypothesis more fully.

Tighter precision target required for lactate testing in patients with lactic acidosis.

BACKGROUND: Allowable analytic errors are generally based on biologic variation in normal, healthy subjects. Some analytes like blood lactate have low concentrations in healthy individuals and resultant allowable variation is large when expressed as a coefficient of variation (CV). In Ricós' compendium of biologic variation, the relative pooled intra-individual lactate variation (si) averages 27% and the desirable imprecision becomes 13.5%. We derived biologic variability (sb) from consecutive patient data and demonstrate that sb of lactate is significantly lower. METHODS: A data repository provided lactate results measured over 18 months in the General Systems intensive care unit (ICU) at the University of Alberta Hospital in Edmonton, Canada. In total 54,000 lactate measurements were made on two point-of-care Radiometer 800 blood gas systems operated by Respiratory Therapy. The standard deviations of duplicates (SDD) were tabulated for the intra-patient lactates that were separated by 0-1, 1-2...up to 16 h. The graphs of SDD vs. time interval were approximately linear; the y-intercept provided by the linear regression represents the sum of sb and short-term analytic variation (sa):y0=(sa²+sb²)½. The short-term sa was determined from imprecisions provided by Radiometer and confirmed with onsite controls. The derivation of sb was performed for multiple patient ranges of lactate. RESULTS: The relative desirable lactate imprecision for patients with lactic acidosis is about half that of normal individuals. CONCLUSIONS: As such, evaluations of lactate measurements must use tighter allowable error limits.

Towards more complete specifications for acceptable analytical performance - a plea for error grid analysis.

Abstract We examine limitations of common analytical performance specifications for quantitative assays. Specifications can be either clinical or regulatory. Problems with current specifications include specifying limits for only 95% of the results, having only one set of limits that demarcate no harm from minor harm, using incomplete models for total error, not accounting for the potential of user error, and not supplying sufficient protocol requirements. Error grids are recommended to address these problems as error grids account for 100% of the data and stratify errors into different severity categories. Total error estimation from a method comparison can be used to estimate the inner region of an error grid, but the outer region needs to be addressed using risk management techniques. The risk management steps, foreign to many in laboratory medicine, are outlined.

The use of serial patient blood gas, electrolyte and glucose results to derive biologic variation: a new tool to assess the acceptability of intensive care unit testing.

BACKGROUND: Most estimates of biologic variation (s(b)) are based on periodically acquiring and storing specimens, followed by analysis within a single analytic run. We demonstrate for many intensive care unit (ICU) tests, only patient results need be statistically analyzed to provide reliable estimates of s(b). METHODS: Over 11 months, approximately 28,000 blood gas measurements (including electrolyte panels and glucose) were performed on one of two Radiometer ABL800 FLEX analyzers (Radiometer, Copenhagen, Denmark) from 1676 ICU patients. We tabulated the measurements of paired intra-patient blood samples drawn within 24 h of each other. After removal of outliers, we calculated the standard deviations of duplicates (SDD) of the intra-patient pairs grouped in 2-h intervals: 0-2 h, 2-4 h, 4-6 h, … 20-22 h and 22-24 h. The SDDs were then regressed against the time intervals of 2-14 h; extrapolation to zero time represents the sum of s(b) and short-term analytic variation (s(a)). RESULTS: Substitution of experimentally derived analytic error permitted the calculation of coefficient of variation (biologic) (CV(b)) (100 s(b)/mean): pH, 0.3%; pCO(2), 5.7%; pO(2), 13%; Na(+), 0.6%; K(+), 4.8%; Cl(-), 0.8%; HCO(3)(-), 3.2%; iCa(++), 2.4%; and glucose, 10.3%. The CV(b) of the electrolytes very closely matches the lowest estimates obtained in the usual manner. CONCLUSIONS: Derivation of the ratio of biologic to analytic variation indicates that the ABL800 is extremely suitable for ICU testing. This analysis should be extended to other point of care instrument systems.

Barricor blood collection tubes are equivalent to PST for a variety of chemistry and immunoassay analytes except for lactate dehydrogenase.

INTRODUCTION: The BD Barricor tube uses a novel mechanical separator designed to eliminate gel artifacts, decrease cellular contamination, and improve stability. Here, we evaluated the Barricor tube as a possible replacement for PST using Beckman Coulter analyzers under both optimal, alternative, and suboptimal centrifugation conditions based on BD recommendations. METHODS: Paired PST and Barricor samples were collected from 4 local hospitals and processed based on site-specific preanalytical systems involving automated or manual centrifugation. Centrifugation conditions ranged from 1912 ×g for 10 min (suboptimal), 2060 g for 10 min (alternative), and 4000 ×g for 3 or 10 min (optimal). Tube volume (4.5 vs. 5.5 ml) was also assessed. Forty-three chemistry and immunochemistry analytes were measured on Beckman Coulter DxC and DxI analyzers. RESULTS: Using an automated preanlaytical system with suboptimal spin conditions, no bias between PST and Barricor was observed for all analytes tested except lactate dehydrogenase (LD). Further investigation revealed significant increase in LD when Barricor was spun for 10 min at 1912, 2060 and 4000 ×g, ranging from +7.4-19.4% vs. PST across the entire measurement interval (87-493 U/l). Smaller tube volume was also associated with higher LD. Differences in LD occurred despite no change in other hemolysis markers such as potassium, phosphate, and AST. CONCLUSIONS: LD is most sensitive to varying centrifugation conditions (time and speed) in Barricor tubes. We recommend that BD centrifugation protocols should be closely evaluated to determine if Barricor is equivalent to PST under local preanalytical configurations.

Accuracy of the CoaguChek XS for point-of-care international normalized ratio (INR) measurement in children requiring warfarin.

Point-of-care INR (POC INR) meters can provide a safe and effective method for monitoring oral vitamin K antagonists (VKAs) in children. Stollery Children's Hospital has a large POC INR meter loan program for children requiring oral VKAs. Our protocol requires that POC INR results be compared to the standard laboratory INR for each child on several consecutive tests to ensure accuracy of CoaguChek XS (Roche Diagnostics, Basel Switzerland) meter. It was the objective of the study to determine the accuracy of the CoaguChek XS by comparing whole blood INR results from the CoaguChek XS to plasma INR results from the standard laboratory in children. POC INR meter validations were performed on plasma samples from two time points from 62 children receiving warfarin by drawing a venous blood sample for laboratory prothrombin (PT)-INR measurements and simultaneous INR determinations using the POC-INR meter. Agreement between CoaguChek XS INR and laboratory INR was assessed using Bland-Altman plots. Bland-Altman's 95% limits of agreement were 0.11 (-0.20; 0.42) and 0.13 (-0.22; 0.48) at the two time points, respectively. In conclusion, the CoaguChek XS meter appraisal generates an accurate and precise INR measure in children when compared to laboratory INR test results.

Application of 3-D Delta check graphs to HbA1c quality control and HbA1c utilization.

Delta checking is a laboratory information system (LIS)-based tool that detects patient and laboratory quality control errors. By using hemoglobin A1c (HbA1c) data, we developed a novel approach to summarizing and presenting patient Delta values to address limitations of current Delta check algorithms. Delta values were calculated from intrapatient pairs of HbA1c (n = 55,327) measured during 2 years in a single referral or a university hospital laboratory. Three-dimensional Delta-time (DeltaT) and percentile limit graphs were constructed. Cumulative distribution function analysis was used to explore clinical utilization. The DeltaT graphs showed that HbA1c Delta values increase asymmetrically over time. Although the 2.5 to 97.5 and 5.0 to 95.0 percentile Delta check limits were similar for both sites, the referral laboratory's 0.5 to 99.5 percentile limits were wider. For acute patient care environments, we recommend limits of -3.5% and 1.8% for measurements between 0 and 60 days and -4.0% and 2.0% for measurements between 60 and 120 days. For the outpatient environment, we recommend limits of -4.2% and 2.1% and 5.0% and 2.5% for measurements between 0 and 60 days and 60 and 120 days, respectively.Delta checking can be significantly improved with customization of limits set by population and interobservation period. Because LIS systems are incapable of these customizations, customers must become advocates for these modifications.