George S Cembrowski1, Qian Xu2, Adam R Cembrowski3, Junyi Mei4, Hossein Sadrzadeh5. 1. Department of Laboratory Medicine and Pathology, University of Alberta Hospital, 4B1.24 Walter C. Mackenzie Centre, 8440 - 112 Street, Edmonton, Alberta T6G 2B7, Canada; University of Alberta, 4B1.24 Walter C. Mackenzie Centre, 8440 - 112 Street, Edmonton, Alberta T6G 2B7, Canada; Alberta Health Services, 4B1.24 Walter C. Mackenzie Centre, 8440 - 112 Street, Edmonton, Alberta T6G 2B7, Canada. Electronic address: George.Cembrowski@albertahealthservices.ca. 2. University of Manitoba, 66 Chancellors Cir, Winnipeg, MB R3T 2N2, Canada. 3. University of Alberta, 116 St & 85 Ave, Edmonton, AB T6G 2R3, Canada. 4. University of Toronto, 27 King's College Cir, Toronto, ON M5S, Canada. 5. Department of Pathology and Laboratory Medicine, University of Calgary, Calgary, AB, Canada; Calgary Laboratory Services, Calgary, AB, Canada.
Abstract
BACKGROUND: Within- and/or between-instrument variation may falsely indicate patient trends or obscure real trends. We employ a methodology that transforms sequential intra-patient results into estimates of biologic and analytic variation. We previously derived realistic biologic variation (sb) of blood gas (BG) and hematology analytes. We extend this methodology to derive the imprecision of two GEM 4000 BG analyzers. METHODS: A laboratory data repository provided arterial BG, electrolyte and metabolite results generated by two GEM 4000s on ICU patients in 2012-2013. We tabulated consecutive pairs of intra-patient results separated by increasing time interval between consecutive tests. The average between pair variations were regressed against time with the y-intercept representing the sum of the biologic variation and short term analytic variation: yo2=sb2+sa2. Using an equivalent equation for the Radiometer ABL, the imprecision of the two GEMs was calculated: saGEM=(yoGEM2-yoABL2+saABL2)1/2. This analysis was performed for nearly all measurements, regardless of time as well for values obtained over two 12h mutually exclusive periods, starting either at 2am or 2pm. RESULTS: Regression graphs were derived from 1800 patients' blood gas results with least 10,000 data pairs grouped into 2h intervals. The calculated saGEM exceed the directly measured saABL with many GEM sigma ratios of biologic variation/analytic variation being close to unity. All of the afternoon saGEM exceeded their morning counterparts with pH, pCO2, K and bicarbonate being statistically significant. CONCLUSION: For many analytes, the average analytical variation of tandem GEMs approximates the biologic variation, indicating impaired clinical usefulness of tandem sequential measurements. A significant component of this variation is due to increased variation of the GEMs between 2pm and 2am.
BACKGROUND: Within- and/or between-instrument variation may falsely indicate patient trends or obscure real trends. We employ a methodology that transforms sequential intra-patient results into estimates of biologic and analytic variation. We previously derived realistic biologic variation (sb) of blood gas (BG) and hematology analytes. We extend this methodology to derive the imprecision of two GEM 4000 BG analyzers. METHODS: A laboratory data repository provided arterial BG, electrolyte and metabolite results generated by two GEM 4000s on ICU patients in 2012-2013. We tabulated consecutive pairs of intra-patient results separated by increasing time interval between consecutive tests. The average between pair variations were regressed against time with the y-intercept representing the sum of the biologic variation and short term analytic variation: yo2=sb2+sa2. Using an equivalent equation for the Radiometer ABL, the imprecision of the two GEMs was calculated: saGEM=(yoGEM2-yoABL2+saABL2)1/2. This analysis was performed for nearly all measurements, regardless of time as well for values obtained over two 12h mutually exclusive periods, starting either at 2am or 2pm. RESULTS: Regression graphs were derived from 1800 patients' blood gas results with least 10,000 data pairs grouped into 2h intervals. The calculated saGEM exceed the directly measured saABL with many GEM sigma ratios of biologic variation/analytic variation being close to unity. All of the afternoon saGEM exceeded their morning counterparts with pH, pCO2, K and bicarbonate being statistically significant. CONCLUSION: For many analytes, the average analytical variation of tandem GEMs approximates the biologic variation, indicating impaired clinical usefulness of tandem sequential measurements. A significant component of this variation is due to increased variation of the GEMs between 2pm and 2am.