Walter ckenzie Center

Edmonton, Canada

Walter ckenzie Center

Edmonton, Canada
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Krouwer J.S.,Krouwer Consulting | Cembrowski G.S.,Walter ckenzie Center
Journal of Diabetes Science and Technology | Year: 2010

Glucose performance is reviewed in the context of total error, which includes error from all sources, not just analytical. Many standards require less than 100% of results to be within specific tolerance limits. Analytical error represents the difference between tested glucose and reference method glucose. Medical errors include analytical errors whose magnitude is great enough to likely result in patient harm. The 95% requirements of International Organization for Standardization 15197 and others make little sense, as up to 5% of results can be medically unacceptable. The current American Diabetes Association standard lacks a specification for user error. Error grids can meaningfully specify allowable glucose error. Infrequently, glucose meters do not provide a glucose result; such an occurrence can be devastating when associated with a life-threatening event. Nonreporting failures are ignored by standards. Estimates of analytical error can be classified into the four following categories: imprecision, random patient interferences, protocol-independent bias, and protocol-dependent bias. Methods to estimate total error are parametric, nonparametric, modeling, or direct. The Westgard method underestimates total error by failing to account for random patient interferences. Lawton's method is a more complete model. Bland-Altman, mountain plots, and error grids are direct methods and are easier to use as they do not require modeling. Three types of protocols can be used to estimate glucose errors: method comparison, special studies and risk management, and monitoring performance of meters in the field. Current standards for glucose meter performance are inadequate. The level of performance required in regulatory standards should be based on clinical needs but can only deal with currently achievable performance. Clinical standards state what is needed, whether it can be achieved or not. Rational regulatory decisions about glucose monitors should be based on robust statistical analyses of performance. © Diabetes Technology Society.


Krouwer J.S.,Krouwer Consulting | Cembrowski G.S.,Walter ckenzie Center
Journal of Diabetes Science and Technology | Year: 2015

Traditional glucose error grids provide error limits for glucose meters. These criteria help to assess the meter's suitability to prevent acute injury. We present a rationale for an error grid that provides a different set of error limits to help prevent chronic injury in diabetes. For example, glucose values in the no treatment zone of a traditional error grid could be harmful in diabetic retinopathy. The same method comparison data informs both the acute and chronic injury error grids. All of the data are used in an acute injury error grid, whereas only long-term biases populate a chronic injury error grid. These biases can be due to reagent lots and patient specific interferences. An example of a chronic injury glucose error grid is provided using simulated data. © 2015 Diabetes Technology Society.


Abuetabh Y.,University of Alberta | Persad S.,University of Alberta | Nagamori S.,Japan National Institute of Infectious Diseases | Huggins J.,Walter ckenzie Center | And 3 more authors.
Annals of Clinical and Laboratory Science | Year: 2011

Background: Cholangiocarcinoma (CC) is the most frequent malignant epithelial tumor of the biliary system. CC has received increasing interest due to its different etiologic factors, invasiveness, and the difficulty of diagnosis at an early stage. The pathogenesis of CC has not been clearly defined, but cohesiveness of tumor cells seems to be a critical factor. Calcium-dependent adherence proteins or cadherins are a family of proteins essential for connecting the plasma membrane of adjacent cells. Linkage of cadherins with the cytoskeleton occurs through another class of proteins, called catenins. E-cadherin forms a mutually exclusive complex or unit with β-catenin. Loss of E-cadherin - β-catenin adhesion represents an important step in the progression of many epithelial malignancies. Cell lines arising from CC are not often investigated and may show a differential expression of cell adhesion molecules, particularly E-cadherin - β-catenin. We hypothesized that a moderately invasive cell line of CC may co-localize both molecules in cytoplasm and cytoplasmic membrane, indicating a greater "tightness" of the tumor cells, while a metastasizing cell line may show isolated cytoplasmic membrane localization, indicating tumor cells probably more keen to reach the blood stream and give metastases. Thus, our aim was to investigate the expression and localization of E-cadherin and β-catenin in two CC cell lines, including a rapidly metastasizing cell line and a moderately invasive cell line, correlating to a different degree of invasiveness of the primary tumor. Materials and Methods: OZ and HuCCT1 cells represent homogeneous, functional human biliary epithelial tumor cell lines that were originally isolated in Japan. Following cell line growth we extracted total proteins. Western blot analysis, immunofluorescence and confocal laser microscopy were used to identify the protein expression and their cyto-localization and co-localization. Results: Both CC cell lines expressed E-cadherin and β-catenin, but they showed remarkably different localization patterns. In HuCCT1, both E-cadherin and β-catenin were localized in the cytoplasm, while in OZ these proteins were localized in the cytoplasmic membrane only. This was attributed to a different degree of invasiveness of the primitive CC from which the cell lines were characterized, OZ being a metastasizing cell line, HuCCT1 being a moderately invasive cell line. Conclusion: To the best of our knowledge, this is the first time that E-cadherin and β-catenin have been studied in detail in these two cell lines. These data seem to be very promising in terms of adding insight into the cell biology of CC and initiating investigations that aim to identify cytoskeletal dynamics and ultimately provide guidelines for developing new therapeutic strategies. © 2011 by the Association of Clinical Scientists, Inc.


Krouwer J.S.,Krouwer Consulting | Cembrowski G.S.,Walter ckenzie Center
Clinical Chemistry and Laboratory Medicine | Year: 2011

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. © 2011 by Walter de Gruyter Berlin Boston.


PubMed | Walter ckenzie Center and Krouwer Consulting
Type: Journal Article | Journal: Journal of diabetes science and technology | Year: 2014

Traditional glucose error grids provide error limits for glucose meters. These criteria help to assess the meters suitability to prevent acute injury. We present a rationale for an error grid that provides a different set of error limits to help prevent chronic injury in diabetes. For example, glucose values in the no treatment zone of a traditional error grid could be harmful in diabetic retinopathy. The same method comparison data informs both the acute and chronic injury error grids. All of the data are used in an acute injury error grid, whereas only long-term biases populate a chronic injury error grid. These biases can be due to reagent lots and patient specific interferences. An example of a chronic injury glucose error grid is provided using simulated data.

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