Julie L V Shaw1, Ashley Cohen2, Danijela Konforte1, Tina Binesh-Marvasti3, David A Colantonio1, Khosrow Adeli4. 1. Clinical Biochemistry Division, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. 2. Clinical Biochemistry Division, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada. 3. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. 4. Clinical Biochemistry Division, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. Electronic address: khosrow.adeli@sickkids.ca.
Abstract
OBJECTIVES: To compare pediatric reference intervals calculated using hospital-based patient data with those calculated using samples collected from healthy children in the community as part of the CALIPER study. METHODS: Hospital-based data for 13 analytes (calcium, phosphate, iron, ALP, cholesterol, triglycerides, creatinine, direct bilirubin, total bilirubin, ALT, AST, albumin and magnesium), measured on the Vitros 5600, collected between 2007 and 2011 were obtained. The data for each analyte were partitioned by age and gender as previously defined by the CALIPER study. Outliers in each partition were removed using the Tukey method. The cumulative distribution function (cdf) was then determined for each analyte value following which, the inverse cdf values of a standard Gaussian distribution were calculated. The analyte values were plotted against the inverse cdf of the standard Gaussian distribution. Piece-wise regression determined the linear portion of the resulting graph using the statistical software R. Linear regression determined an equation for the linear portion in each partition and reference intervals were calculated by extrapolating to identify the 2.5th and 97.5th centiles in each partition based on the inverse cdf values (which would correspond to the values -1.96 and 1.96 of the Gaussian distribution). Using the 90% confidence intervals for the reference intervals defined by CALIPER and the Reference Change Value (RCV) as the criteria, these calculated reference intervals were compared to those reported previously by CALIPER. Reference samples were also measured on the Vitros 5600 analyzer in an attempt to validate the calculated reference intervals. RESULTS: In general, the reference intervals calculated from hospital-based data were generally wider than those calculated by CALIPER. None of the reference intervals calculated using the Hoffmann approach fell completely within the 90% confidence intervals calculated by CALIPER. CONCLUSIONS: These results suggest that calculating pediatric reference intervals from hospital-based data may be useful, as a guide, in some cases but will likely not replace the need to establish reference intervals in healthy pediatric populations.
OBJECTIVES: To compare pediatric reference intervals calculated using hospital-based patient data with those calculated using samples collected from healthy children in the community as part of the CALIPER study. METHODS: Hospital-based data for 13 analytes (calcium, phosphate, iron, ALP, cholesterol, triglycerides, creatinine, direct bilirubin, total bilirubin, ALT, AST, albumin and magnesium), measured on the Vitros 5600, collected between 2007 and 2011 were obtained. The data for each analyte were partitioned by age and gender as previously defined by the CALIPER study. Outliers in each partition were removed using the Tukey method. The cumulative distribution function (cdf) was then determined for each analyte value following which, the inverse cdf values of a standard Gaussian distribution were calculated. The analyte values were plotted against the inverse cdf of the standard Gaussian distribution. Piece-wise regression determined the linear portion of the resulting graph using the statistical software R. Linear regression determined an equation for the linear portion in each partition and reference intervals were calculated by extrapolating to identify the 2.5th and 97.5th centiles in each partition based on the inverse cdf values (which would correspond to the values -1.96 and 1.96 of the Gaussian distribution). Using the 90% confidence intervals for the reference intervals defined by CALIPER and the Reference Change Value (RCV) as the criteria, these calculated reference intervals were compared to those reported previously by CALIPER. Reference samples were also measured on the Vitros 5600 analyzer in an attempt to validate the calculated reference intervals. RESULTS: In general, the reference intervals calculated from hospital-based data were generally wider than those calculated by CALIPER. None of the reference intervals calculated using the Hoffmann approach fell completely within the 90% confidence intervals calculated by CALIPER. CONCLUSIONS: These results suggest that calculating pediatric reference intervals from hospital-based data may be useful, as a guide, in some cases but will likely not replace the need to establish reference intervals in healthy pediatric populations.
Authors: Christina M Parrinello; Morgan E Grams; Yingying Sang; David Couper; Lisa M Wruck; Danni Li; John H Eckfeldt; Elizabeth Selvin; Josef Coresh Journal: Clin Chem Date: 2016-05-19 Impact factor: 8.327
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Authors: Houman Tahmasebi; Victoria Higgins; Angela W S Fung; Dorothy Truong; Nicole M A White-Al Habeeb; Khosrow Adeli Journal: EJIFCC Date: 2017-03-08