Clinica Chimica Acta 438 (2015) 252–254
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Evaluation of the performance of a new OptiScanner™ 5000 system for an intermittent glucose monitoring Alessandra Barassi a,⁎, Michele Umbrello b, Francesca Ghilardi a, Clara Anna Linda Damele a, Luca Massaccesi c, Gaetano Iapichino b,d, Gian Vico Melzi d’Eril a a
Laboratorio di Analisi, Ospedale San Paolo, Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milano, Italy UO Anestesia e Rianimazione, Polo Universitario San Paolo, Milano, Italy Dipartimento di Scienze Biomediche, Chirurgiche e Odontoiatriche, Università di Milano, Milano, Italy d Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Milano, Italy b c
a r t i c l e
i n f o
Article history: Received 16 January 2014 Received in revised form 5 September 2014 Accepted 5 September 2014 Available online 11 September 2014 Keywords: Intermittent glucose monitoring mid-IR fixed-wavelength system new OptiScanner™ 5000 system
a b s t r a c t Background: Mid-infrared spectral technology has shown a high degree of promise in detecting glucose in plasma. OptiScan Biomedical has developed a glucose monitor based on mid-infrared spectroscopy that withdraws blood samples and measures plasma glucose. The objective of this study was to evaluate the accuracy and performance of the OptiScanner™ 5000 system on different pools of blood. Methods: This study was performed to validate the blood glucose measurements obtained with the OptiScanner™ 5000 by comparing them to Central Laboratory glucose measurements (VITROS® 5600 Integrated System) as a comparative method across a broad range of glucose values over a three day period to obtain 80–90 paired measurements. Results: A total of 81 paired measurements, distributed between 33 and 320 mg/100 mL of glucose, were performed. The aggregate data points were within International Organization for Standardization standards, with 100% of the glucose values within ±15%. Conclusions: The current study suggests that a mid-IR fixed-wavelength system (OptiScanner) can measure glucose accurately across a wide range of glucose values in plasma of ICU patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Glucose meters play a central role in the modern management of diabetes. The American Diabetes Association recommends the use of handheld and portable glucose monitoring devices for self-monitoring at home and for point-of-care testing in hospital settings to reduce complications arising from poor glycemic control [1,2]. Although glucose meters provide quick measurements, there is controversy concerning their use with critically ill patients in emergency rooms, intensive care units and operating rooms. Acute hyperglycemia is common in critically ill patients. Approximately 90% of all patients develop blood glucose concentrations N 110 mg/dL (6.1 mmol/L) during critical illness [3]. The traditional view of glycemic control in these patients was that acute hyperglycemia represented a normal, and perhaps beneficial, adaptive response that promoted cellular glucose uptake [2]. More recently, recognition that hyperglycemia is independently associated with increased ICU mortality [4–9] and evidence that better control of blood glucose illness can be beneficial [9] has led to the study of tighter ⁎ Corresponding author at: Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via di Rudinì 8, 20142 Milano, Italy. Tel.: +39 3355444121; fax: +39 81844027. E-mail address: [email protected] (A. Barassi).
http://dx.doi.org/10.1016/j.cca.2014.09.008 0009-8981/© 2014 Elsevier B.V. All rights reserved.
blood glucose control in critical care. Hypoglycemia is dangerous, particularly so in critical care settings where it may have gone undetected, and the optimal blood glucose concentration should be b 200 to 215 mg/dL (11.1–12.0 mmol/L) to avoid the adverse effect of hyperglycemia and increased osmolarity on granulocyte function [10–12]. Although no casual link has yet been demonstrated between hypoglycemia and increased mortality, recent data provide a greater understanding of the strong association between hypoglycemia and death. As a consequence, all critically ill patients treated with insulin should be considered at risk of hypoglycemia and monitored accordingly. Few methods exist for accurate, regular, point-of-care measurement of blood glucose in ICUs. The use of handheld meters has been shown to be prone to error [13,14] and require hospital staff to operate them and thus may reduce sampling frequency due to time constraints. Furthermore, most point-of-care glucose measuring systems were not developed to guide the administration of insulin in critically ill patients, and it has become clear that they are not accurate enough to guide therapy aimed at keeping blood glucose concentration within a 30 mg/dL (1.7 mmol/L) range [15–17]. Mid-infrared spectral technology has shown a high degree of promise in detecting analytes in plasma [18]. With mid-IR spectroscopy, a reagentless method of measurement, not only can glucose in plasma be identified, but quantified as well.
A. Barassi et al. / Clinica Chimica Acta 438 (2015) 252–254
The objective of this study was to evaluate the accuracy and performance of the OptiScanner™ 5000 system on different pools of blood. 2. Material and methods Mid-infrared (mid-IR) spectral technology has shown a high degree of promise in detecting analytes in plasma [18]. OptiScan Biomedical has developed a reagentless method that uses mid-IR spectroscopy to accurately measure glucose concentrations in human blood samples. The method consists of a cuvette and an onboard spectrometer that uses 25 wavelengths to estimate glucose. Specifically, 11 of the filters are between 7 and 8 μm, 6 of the filters are between 8 and 9 μm and 8 of the filters are between 9 and 10 μm. The device is intended to connect to an existing blood access port of the patient, requiring no additional cannula insertion. A small sample of venous blood is withdrawn, the plasma is separated using a centrifuge within the system, and a glucose reading is produced every 15 min. In the Central Laboratory of San Paolo University Hospital (Milan, Italy) glucose levels were analyzed on a VITROS® 5000 Integrated System (Ortho Clinical Diagnostics) using the VITROS GLUSlide method, a multilayered, analytical element coated on a polyester support. The chemical determination involves enzymatic glucose oxidation followed by development of color linked to oxidation of a dye, which is measured by reflected light. The dye system is closely related to that first reported by Trinder [19]. The use of glucose slides has been described by Curme et al. [20]. The specimens were analyzed using the same lot of reagent, eliminating any lot-to-lot variability in the results. The VITROS GLUSlide method is traceable to a primary standard method. This study was performed to validate the blood glucose measurements obtained with the OptiScanner™ 5000 by comparing them to Central Laboratory glucose measurements as a comparative method across a broad range of glucose values over a three day period to obtain 80–90 paired measurements. The aim was to verify that OptiScanner™ 5000 is suitable for bedside, real-time glucose measurement in the ICU and determine its equivalency to the central lab glucose analyzer. Each day a 200 mL blood sample (Li+ Heparin), pooled from the patients that accessed the emergency department the night before, was obtained. During the experiment, the blood stored in a flask was either spiked with glucose or diluted with saline in order to adjust glucose concentrations to obtain samples ranging from hypoglycemia to hyperglycemia. For every 15-minute OptiScanner™ 5000 measurement cycle, a Central Laboratory measurement of glucose was performed. The OptiScanner™ 5000 system does not need calibration because there is no blood contact with the measurement technology and elements of measurement are stable over years. In this study, pseudo samples, obtained from specimen manipulation, were analyzed using the same lot of VITROS reagents and the results were compared to those of OptiScanner also using the same lot of reagents. This procedure is not reflective of real-world performance which would incorporate multiple lots of reagents and actual patient samples. However, in this first estimate of the device's performance we liked to obtain “clean” results with as least variables as possible for a preliminary comparative approach to the new technology. This investigation conforms to the principles outlined in the Declaration of Helsinki.
253
value. Zone A values are said to be clinically accurate with no risk. Zone B is considered generally accurate with slight risk. Finally, zone D is classified as potential failure to detect hypo- or hyperglycemia. For every analysis, p b 0.05 was considered statistically significant. Analysis was performed with Stata 12 (Stata Corp., College Station, TX, USA) for Windows.
3. Results During the study, a total of 81 paired measurements were performed. Glucose values were distributed between 33 and 320 mg/100 mL. Fig. 1 shows the agreement between the OptiScanner™ 5000 and the Central Laboratory. The slope of the regression line was 1.02 [95% CI: 1.01–1.04] mg/100 mL (p b 0.001), with R-squared of 0.996. Bland–Altman analysis shows a mean difference between the two devices of −1.5 [95% CI: (−2.7)–(−0.2)] mg/100 mL, with limits of agreement ranging from −12.9 to 9.8 mg/100 mL. Fig. 2 shows the results of the Clarke Error Grid analysis. All the determinations (100%) fall within region A, i.e. lie within 15% of the comparative sensor. The Fig. 1 demonstrates the majority of samples above the mean up to a level of about 100 mg/dL, values closer to the mean between 100 and 200 mg/dL, and values well below the mean with values above 200 mg/dL. This negative trend could be apparent only because of the small number of measurements. Only further study with a larger number of measurements would need to demonstrate the presence of a negative bias.
2.1. Statistical analysis Data are presented as mean ± standard deviation if normally distributed, or median [interquartile range] if not. The comparison between Central Laboratory glucose determinations was performed with simple linear regression and Bland–Altman analysis [16]. A Clarke Error Grid (CEG) [21] was built to quantify the clinical accuracy of blood glucose determinations generated by the OptiScanner™ 5000 as compared to Central Laboratory measurements, used as a comparative
Fig. 1. The agreement between the OptiScanner™ 5000 and the Central Laboratory. OS: OptiScanner; Central: Central Laboratory.
254
A. Barassi et al. / Clinica Chimica Acta 438 (2015) 252–254
In conclusion, the current study suggests that a mid-IR fixedwavelength system can measure glucose accurately across a wide range of glucose values.
References
Fig. 2. Clarke error grid analysis of 81 paired glucose samples (OptiScanner vs Central Laboratory). OS: OptiScanner.
4. Discussion The study demonstrates the feasibility of using fixed-wavelength mid-IR measurement technology to provide accurate measurements of blood glucose. The high correlation suggests that this technology compares favorably to a comparative method such as VITROS. The measurement technology used an algorithm with an expanding library of verified and validated interferences to become insensitive to the variety of plasma expanders, medications, and the numerous injuries, illnesses, and complications present in the critically injured and ill patients. The high accuracy was kept across a wide range of glucose levels at least against a standard laboratory procedure. The analysis of the paired readings showed that the device provided an accurate response in 100% of all measurements. Our results strongly confirm and further validate data in previous preclinical studies using the OptiScanner device [22,23]. Our validation study is only a first estimate of the device's performance since actual patient samples were not utilized in the studies. The results obtained with our pseudosamples would not necessarily be reflective of performance on live patients. Further studies employing real blood samples obtained from critically ill patients are needed to confirm the good accuracy found here using pseudosamples. In particular, blood samples can be selected from anemic patients that are reported to give false high blood glucose concentrations [24,25] when measured with POC devices that apply a corrective formula to refer to plasma the glucose concentration measured in whole blood. One limitation of the study is that the generation of plasma was done manually. This has been separately addressed and studied in a system that uses a reagentless cuvette and onboard spectrometer with storage of spectral data on interferents [26].
[1] American Diabetes Association. Consensus statement on self-monitoring of blood glucose. Diabetes Care 1987;10:95–9. [2] American Diabetes Association. Diabetes Care 1996;19:S62–6. [3] van den Berghe G, Wouters P, Weekers F, et al. Intensive insulin therapy in critically ill patients. N Engl J Med 2001;345:1359–67. [4] Robinson LE, van Soeren MH. Insulin resistance and hyperglycemia in critical illness: role of insulin in glycemic control. AACN Clin Issues 2004;15:45–62. [5] Burkett E, Keijzers G, Lind J. The relationship between blood glucose level and QTc duration in the critically ill. Crit Care Resusc 2009;11:8–13. [6] Mitchell I, Knight E, Gissane J, et al. A phase II randomised controlled trial of intensive insulin therapy in general intensive care patients. Crit Care Resusc 2006;8: 289–93. [7] Coursin DB, Connery LE, Ketzler JT. Perioperative diabetic and hyperglycemic management issues. Crit Care Med 2004;32:S116–25. [8] Malmberg K, Rydén L, Efendic S, et al. Randomized trial of insulin–glucose infusion followed by subcutaneous insulin treatment in diabetic patients with acute myocardial infarction (DIGAMI study): effects on mortality at 1 year. J Am Coll Cardiol 1995; 26:57–65. [9] Malmberg K. Prospective randomised study of intensive insulin treatment on long term survival after acute myocardial infarction in patients with diabetes mellitus. DIGAMI (Diabetes Mellitus, Insulin Glucose Infusion in Acute Myocardial Infarction) Study Group. BMJ 1997;314:1512–5. [10] Bagdade J, Stewart M, Walters E. Impaired granulocyte adherence. A reversible defect in host defense in patients with poorly controlled diabetes. Diabetes 1978;27: 677–81. [11] Mowat A, Baum J. Chemotaxis of polymorphonuclear leukocytes from patients with diabetes mellitus. N Engl J Med 1971;284:621–7. [12] Latham R, Lancaster AD, Covington JF, Pirolo JS, Thomas Jr CS. The association of diabetes and glucose control with surgical-site infections among cardiothoracic surgery patients. Infect Control Hosp Epidemiol 2001;22:607–12. [13] Boyd JC, Bruns DE. Quality specifications for glucose meters: assessment by simulation modeling of errors in insulin dose. Clin Chem 2001;47:209–14. [14] Kanji S, Buffie J, Hutton B, et al. Reliability of point-of-care testing for glucose measurement in critically ill adults. Crit Care Med 2005;33:2778–85. [15] Scott MG, Bruns DE, Boyd JC, Sacks DB. Tight glucose control in the intensive care unit: are glucose meters up to the task? Clin Chem 2009;55:18–20. [16] Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10. [17] Finkielman JD, Oyen LJ, Afessa B. Agreement between bedside blood and plasma glucose measurement in the ICU setting. Chest 2005;127:1749–51. [18] Heise HM, Marbach R, Koschinsky TH, Gries FA. Multicomponent assay for blood substrates in human plasma by mid-infrared spectroscopy and its evaluation for clinical analysis. Appl Spectrosc 1994;48:85–95. [19] Trinder P. Determination of glucose in blood using glucose oxidase with an alternative oxygen acceptor. Ann Clin Biochem 1969;6:24–7. [20] Curme HG, Columbus RL, Dappen GM, et al. Multilayer film elements for clinical analysis: general concepts. Clin Chem 1978;24:1335–42. [21] Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care 1987;10:622–8. [22] Krinsley J, Zheng P, Hall D, Magarian P. ICU validation of the OptiScanner, a continuous glucose monitoring device. Crit Care Med 2006;34:A67. [23] Magarian P, Sterling B. Plasma-generating glucose monitor accuracy demonstrated in an animal model. J Diabetes Sci Technol 2009;3:1411–8. [24] Dellinger RP, Levy MM, Carlet JM, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008;36:296–327. [25] Hoedemaekers CW, Klein Gunnewiek JM, Prinsen MA, Willems JL, Van der Hoeven JG. Accuracy of bedside glucose measurement from three glucometers in critically ill patients. Crit Care Med 2008;36:3062–6. [26] Krinsley J, Bochicchio K, Calentine C, Bochicchio G. Glucose measurement of intensive care unit patient plasma samples using a fixed-wavelength mid-infrared spectroscopy system. J Diabetes Sci Technol 2012;6:294–301.
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Evaluation of the performance of a new OptiScanner™ 5000 system for an intermittent glucose monitoring Alessandra Barassi a,⁎, Michele Umbrello b, Francesca Ghilardi a, Clara Anna Linda Damele a, Luca Massaccesi c, Gaetano Iapichino b,d, Gian Vico Melzi d’Eril a a
Laboratorio di Analisi, Ospedale San Paolo, Dipartimento di Scienze della Salute, Università degli Studi di Milano, Milano, Italy UO Anestesia e Rianimazione, Polo Universitario San Paolo, Milano, Italy Dipartimento di Scienze Biomediche, Chirurgiche e Odontoiatriche, Università di Milano, Milano, Italy d Dipartimento di Fisiopatologia Medico-Chirurgica e dei Trapianti, Università degli Studi di Milano, Milano, Italy b c
a r t i c l e
i n f o
Article history: Received 16 January 2014 Received in revised form 5 September 2014 Accepted 5 September 2014 Available online 11 September 2014 Keywords: Intermittent glucose monitoring mid-IR fixed-wavelength system new OptiScanner™ 5000 system
a b s t r a c t Background: Mid-infrared spectral technology has shown a high degree of promise in detecting glucose in plasma. OptiScan Biomedical has developed a glucose monitor based on mid-infrared spectroscopy that withdraws blood samples and measures plasma glucose. The objective of this study was to evaluate the accuracy and performance of the OptiScanner™ 5000 system on different pools of blood. Methods: This study was performed to validate the blood glucose measurements obtained with the OptiScanner™ 5000 by comparing them to Central Laboratory glucose measurements (VITROS® 5600 Integrated System) as a comparative method across a broad range of glucose values over a three day period to obtain 80–90 paired measurements. Results: A total of 81 paired measurements, distributed between 33 and 320 mg/100 mL of glucose, were performed. The aggregate data points were within International Organization for Standardization standards, with 100% of the glucose values within ±15%. Conclusions: The current study suggests that a mid-IR fixed-wavelength system (OptiScanner) can measure glucose accurately across a wide range of glucose values in plasma of ICU patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Glucose meters play a central role in the modern management of diabetes. The American Diabetes Association recommends the use of handheld and portable glucose monitoring devices for self-monitoring at home and for point-of-care testing in hospital settings to reduce complications arising from poor glycemic control [1,2]. Although glucose meters provide quick measurements, there is controversy concerning their use with critically ill patients in emergency rooms, intensive care units and operating rooms. Acute hyperglycemia is common in critically ill patients. Approximately 90% of all patients develop blood glucose concentrations N 110 mg/dL (6.1 mmol/L) during critical illness [3]. The traditional view of glycemic control in these patients was that acute hyperglycemia represented a normal, and perhaps beneficial, adaptive response that promoted cellular glucose uptake [2]. More recently, recognition that hyperglycemia is independently associated with increased ICU mortality [4–9] and evidence that better control of blood glucose illness can be beneficial [9] has led to the study of tighter ⁎ Corresponding author at: Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via di Rudinì 8, 20142 Milano, Italy. Tel.: +39 3355444121; fax: +39 81844027. E-mail address: [email protected] (A. Barassi).
http://dx.doi.org/10.1016/j.cca.2014.09.008 0009-8981/© 2014 Elsevier B.V. All rights reserved.
blood glucose control in critical care. Hypoglycemia is dangerous, particularly so in critical care settings where it may have gone undetected, and the optimal blood glucose concentration should be b 200 to 215 mg/dL (11.1–12.0 mmol/L) to avoid the adverse effect of hyperglycemia and increased osmolarity on granulocyte function [10–12]. Although no casual link has yet been demonstrated between hypoglycemia and increased mortality, recent data provide a greater understanding of the strong association between hypoglycemia and death. As a consequence, all critically ill patients treated with insulin should be considered at risk of hypoglycemia and monitored accordingly. Few methods exist for accurate, regular, point-of-care measurement of blood glucose in ICUs. The use of handheld meters has been shown to be prone to error [13,14] and require hospital staff to operate them and thus may reduce sampling frequency due to time constraints. Furthermore, most point-of-care glucose measuring systems were not developed to guide the administration of insulin in critically ill patients, and it has become clear that they are not accurate enough to guide therapy aimed at keeping blood glucose concentration within a 30 mg/dL (1.7 mmol/L) range [15–17]. Mid-infrared spectral technology has shown a high degree of promise in detecting analytes in plasma [18]. With mid-IR spectroscopy, a reagentless method of measurement, not only can glucose in plasma be identified, but quantified as well.
A. Barassi et al. / Clinica Chimica Acta 438 (2015) 252–254
The objective of this study was to evaluate the accuracy and performance of the OptiScanner™ 5000 system on different pools of blood. 2. Material and methods Mid-infrared (mid-IR) spectral technology has shown a high degree of promise in detecting analytes in plasma [18]. OptiScan Biomedical has developed a reagentless method that uses mid-IR spectroscopy to accurately measure glucose concentrations in human blood samples. The method consists of a cuvette and an onboard spectrometer that uses 25 wavelengths to estimate glucose. Specifically, 11 of the filters are between 7 and 8 μm, 6 of the filters are between 8 and 9 μm and 8 of the filters are between 9 and 10 μm. The device is intended to connect to an existing blood access port of the patient, requiring no additional cannula insertion. A small sample of venous blood is withdrawn, the plasma is separated using a centrifuge within the system, and a glucose reading is produced every 15 min. In the Central Laboratory of San Paolo University Hospital (Milan, Italy) glucose levels were analyzed on a VITROS® 5000 Integrated System (Ortho Clinical Diagnostics) using the VITROS GLUSlide method, a multilayered, analytical element coated on a polyester support. The chemical determination involves enzymatic glucose oxidation followed by development of color linked to oxidation of a dye, which is measured by reflected light. The dye system is closely related to that first reported by Trinder [19]. The use of glucose slides has been described by Curme et al. [20]. The specimens were analyzed using the same lot of reagent, eliminating any lot-to-lot variability in the results. The VITROS GLUSlide method is traceable to a primary standard method. This study was performed to validate the blood glucose measurements obtained with the OptiScanner™ 5000 by comparing them to Central Laboratory glucose measurements as a comparative method across a broad range of glucose values over a three day period to obtain 80–90 paired measurements. The aim was to verify that OptiScanner™ 5000 is suitable for bedside, real-time glucose measurement in the ICU and determine its equivalency to the central lab glucose analyzer. Each day a 200 mL blood sample (Li+ Heparin), pooled from the patients that accessed the emergency department the night before, was obtained. During the experiment, the blood stored in a flask was either spiked with glucose or diluted with saline in order to adjust glucose concentrations to obtain samples ranging from hypoglycemia to hyperglycemia. For every 15-minute OptiScanner™ 5000 measurement cycle, a Central Laboratory measurement of glucose was performed. The OptiScanner™ 5000 system does not need calibration because there is no blood contact with the measurement technology and elements of measurement are stable over years. In this study, pseudo samples, obtained from specimen manipulation, were analyzed using the same lot of VITROS reagents and the results were compared to those of OptiScanner also using the same lot of reagents. This procedure is not reflective of real-world performance which would incorporate multiple lots of reagents and actual patient samples. However, in this first estimate of the device's performance we liked to obtain “clean” results with as least variables as possible for a preliminary comparative approach to the new technology. This investigation conforms to the principles outlined in the Declaration of Helsinki.
253
value. Zone A values are said to be clinically accurate with no risk. Zone B is considered generally accurate with slight risk. Finally, zone D is classified as potential failure to detect hypo- or hyperglycemia. For every analysis, p b 0.05 was considered statistically significant. Analysis was performed with Stata 12 (Stata Corp., College Station, TX, USA) for Windows.
3. Results During the study, a total of 81 paired measurements were performed. Glucose values were distributed between 33 and 320 mg/100 mL. Fig. 1 shows the agreement between the OptiScanner™ 5000 and the Central Laboratory. The slope of the regression line was 1.02 [95% CI: 1.01–1.04] mg/100 mL (p b 0.001), with R-squared of 0.996. Bland–Altman analysis shows a mean difference between the two devices of −1.5 [95% CI: (−2.7)–(−0.2)] mg/100 mL, with limits of agreement ranging from −12.9 to 9.8 mg/100 mL. Fig. 2 shows the results of the Clarke Error Grid analysis. All the determinations (100%) fall within region A, i.e. lie within 15% of the comparative sensor. The Fig. 1 demonstrates the majority of samples above the mean up to a level of about 100 mg/dL, values closer to the mean between 100 and 200 mg/dL, and values well below the mean with values above 200 mg/dL. This negative trend could be apparent only because of the small number of measurements. Only further study with a larger number of measurements would need to demonstrate the presence of a negative bias.
2.1. Statistical analysis Data are presented as mean ± standard deviation if normally distributed, or median [interquartile range] if not. The comparison between Central Laboratory glucose determinations was performed with simple linear regression and Bland–Altman analysis [16]. A Clarke Error Grid (CEG) [21] was built to quantify the clinical accuracy of blood glucose determinations generated by the OptiScanner™ 5000 as compared to Central Laboratory measurements, used as a comparative
Fig. 1. The agreement between the OptiScanner™ 5000 and the Central Laboratory. OS: OptiScanner; Central: Central Laboratory.
254
A. Barassi et al. / Clinica Chimica Acta 438 (2015) 252–254
In conclusion, the current study suggests that a mid-IR fixedwavelength system can measure glucose accurately across a wide range of glucose values.
References
Fig. 2. Clarke error grid analysis of 81 paired glucose samples (OptiScanner vs Central Laboratory). OS: OptiScanner.
4. Discussion The study demonstrates the feasibility of using fixed-wavelength mid-IR measurement technology to provide accurate measurements of blood glucose. The high correlation suggests that this technology compares favorably to a comparative method such as VITROS. The measurement technology used an algorithm with an expanding library of verified and validated interferences to become insensitive to the variety of plasma expanders, medications, and the numerous injuries, illnesses, and complications present in the critically injured and ill patients. The high accuracy was kept across a wide range of glucose levels at least against a standard laboratory procedure. The analysis of the paired readings showed that the device provided an accurate response in 100% of all measurements. Our results strongly confirm and further validate data in previous preclinical studies using the OptiScanner device [22,23]. Our validation study is only a first estimate of the device's performance since actual patient samples were not utilized in the studies. The results obtained with our pseudosamples would not necessarily be reflective of performance on live patients. Further studies employing real blood samples obtained from critically ill patients are needed to confirm the good accuracy found here using pseudosamples. In particular, blood samples can be selected from anemic patients that are reported to give false high blood glucose concentrations [24,25] when measured with POC devices that apply a corrective formula to refer to plasma the glucose concentration measured in whole blood. One limitation of the study is that the generation of plasma was done manually. This has been separately addressed and studied in a system that uses a reagentless cuvette and onboard spectrometer with storage of spectral data on interferents [26].
[1] American Diabetes Association. Consensus statement on self-monitoring of blood glucose. Diabetes Care 1987;10:95–9. [2] American Diabetes Association. Diabetes Care 1996;19:S62–6. [3] van den Berghe G, Wouters P, Weekers F, et al. Intensive insulin therapy in critically ill patients. N Engl J Med 2001;345:1359–67. [4] Robinson LE, van Soeren MH. Insulin resistance and hyperglycemia in critical illness: role of insulin in glycemic control. AACN Clin Issues 2004;15:45–62. [5] Burkett E, Keijzers G, Lind J. The relationship between blood glucose level and QTc duration in the critically ill. Crit Care Resusc 2009;11:8–13. [6] Mitchell I, Knight E, Gissane J, et al. A phase II randomised controlled trial of intensive insulin therapy in general intensive care patients. Crit Care Resusc 2006;8: 289–93. [7] Coursin DB, Connery LE, Ketzler JT. Perioperative diabetic and hyperglycemic management issues. Crit Care Med 2004;32:S116–25. [8] Malmberg K, Rydén L, Efendic S, et al. Randomized trial of insulin–glucose infusion followed by subcutaneous insulin treatment in diabetic patients with acute myocardial infarction (DIGAMI study): effects on mortality at 1 year. J Am Coll Cardiol 1995; 26:57–65. [9] Malmberg K. Prospective randomised study of intensive insulin treatment on long term survival after acute myocardial infarction in patients with diabetes mellitus. DIGAMI (Diabetes Mellitus, Insulin Glucose Infusion in Acute Myocardial Infarction) Study Group. BMJ 1997;314:1512–5. [10] Bagdade J, Stewart M, Walters E. Impaired granulocyte adherence. A reversible defect in host defense in patients with poorly controlled diabetes. Diabetes 1978;27: 677–81. [11] Mowat A, Baum J. Chemotaxis of polymorphonuclear leukocytes from patients with diabetes mellitus. N Engl J Med 1971;284:621–7. [12] Latham R, Lancaster AD, Covington JF, Pirolo JS, Thomas Jr CS. The association of diabetes and glucose control with surgical-site infections among cardiothoracic surgery patients. Infect Control Hosp Epidemiol 2001;22:607–12. [13] Boyd JC, Bruns DE. Quality specifications for glucose meters: assessment by simulation modeling of errors in insulin dose. Clin Chem 2001;47:209–14. [14] Kanji S, Buffie J, Hutton B, et al. Reliability of point-of-care testing for glucose measurement in critically ill adults. Crit Care Med 2005;33:2778–85. [15] Scott MG, Bruns DE, Boyd JC, Sacks DB. Tight glucose control in the intensive care unit: are glucose meters up to the task? Clin Chem 2009;55:18–20. [16] Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10. [17] Finkielman JD, Oyen LJ, Afessa B. Agreement between bedside blood and plasma glucose measurement in the ICU setting. Chest 2005;127:1749–51. [18] Heise HM, Marbach R, Koschinsky TH, Gries FA. Multicomponent assay for blood substrates in human plasma by mid-infrared spectroscopy and its evaluation for clinical analysis. Appl Spectrosc 1994;48:85–95. [19] Trinder P. Determination of glucose in blood using glucose oxidase with an alternative oxygen acceptor. Ann Clin Biochem 1969;6:24–7. [20] Curme HG, Columbus RL, Dappen GM, et al. Multilayer film elements for clinical analysis: general concepts. Clin Chem 1978;24:1335–42. [21] Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care 1987;10:622–8. [22] Krinsley J, Zheng P, Hall D, Magarian P. ICU validation of the OptiScanner, a continuous glucose monitoring device. Crit Care Med 2006;34:A67. [23] Magarian P, Sterling B. Plasma-generating glucose monitor accuracy demonstrated in an animal model. J Diabetes Sci Technol 2009;3:1411–8. [24] Dellinger RP, Levy MM, Carlet JM, et al. Surviving Sepsis Campaign: international guidelines for management of severe sepsis and septic shock: 2008. Crit Care Med 2008;36:296–327. [25] Hoedemaekers CW, Klein Gunnewiek JM, Prinsen MA, Willems JL, Van der Hoeven JG. Accuracy of bedside glucose measurement from three glucometers in critically ill patients. Crit Care Med 2008;36:3062–6. [26] Krinsley J, Bochicchio K, Calentine C, Bochicchio G. Glucose measurement of intensive care unit patient plasma samples using a fixed-wavelength mid-infrared spectroscopy system. J Diabetes Sci Technol 2012;6:294–301.
