Inaccurate Self-Monitoring of Blood Glucose Readings in Patients on Chronic Ambulatory Peritoneal Dialysis with Icodextrin

Disturbances in Insulin-Glucose Metabolism in Patients With Advanced Renal Disease With and Without Diabetes

CONTEXT

Use of insulin in patients with diabetes and advanced chronic kidney disease (CKD; stages 4 to 5) is challenging and shows great variability among individuals. We explored the mechanisms underlying this variability.

EVIDENCE ACQUISITION

PubMed was searched for articles in English from 1960 to 2018 for advanced CKD and diabetes, glucose and insulin metabolism, insulin clearance, secretion and resistance, plasma insulin concentration, glycemic control, hypoglycemia, insulin dosage, and continuous glucose monitoring (CGM) in CKD.

EVIDENCE SYNTHESIS

The evidence shows that in most patients the daily dose of insulin needs to be significantly reduced with a high degree of variability; in some the dose remains unchanged, and rarely it is increased. The premise that the marked reduction in insulin requirement is essentially attributable to decreased insulin clearance by kidneys leading to prolongation of its plasma half-life, elevated blood insulin concentration, and hypoglycemia is not entirely correct. Other factors including decreases in food intake, insulin secretion, insulin clearance by peripheral tissues, and renal gluconeogenesis play important roles. There is also heightened resistance to insulin due to metabolic acidosis, uremic toxins, inflammatory state, and vitamin D deficiency. Importantly, the magnitude of changes in each of these factors varies between individuals with the same degree of CKD.

CONCLUSIONS

In the presence of diabetes with advanced CKD, the insulin regimen should be individualized based on knowledge of the daily glucose patterns. The use of CGM is promising for safer glycemic control in patients with advanced CKD and diabetes and helps prevent extremes of hypoglycemia and hyperglycemia.

Evaluation of hematocrit interference with MyStar extra and seven competitive devices

In previous studies, meters employing dynamic electrochemistry (DE), have been shown to correct for hematocrit (HCT) interference. This laboratory investigation assessed the HCT stability of MyStar Extra (Sanofi) in comparison to 7 competitive devices (Accu-Chek Aviva Nano & Accu-Chek Performa, Roche Diagnostics; Contour XT and Contour Link, Bayer; FreeStyle Freedom Lite, Abbott; MyLife Pura, Ypsomed; OneTouch Verio Pro, LifeScan). Venous heparinized blood was freshly drawn, immediately aliquoted, and manipulated to contain 3 different blood glucose concentrations (50-80 mg/dL, 150-180 mg/dL, and 350-400 mg/dL) and 5 different HCT levels (20-25%, 30-35%, 40-45%, 50-55%, and 60-65%). After careful oxygenation to normal blood oxygen pressure, each of the 15 different samples was measured 8 times with 2 devices and 2 strip lots of each meter (32 measurements/meter/sample). YSI Stat 2300 served as laboratory reference method. Next to determination of the mean absolute relative deviation (MARD), stability to HCT influence was assumed, when less than 10% difference occurred between the highest and lowest mean glucose deviations in relation to HCT over all tested glucose ranges (HIF: hematocrit interference factor). Four of the devices showed stable performance: Contour XT (MARD: 1.3%/HIF: 6.1%), MyStar Extra (4.7%/7.1%), OneTouch Verio Pro (4.5%/7.3%), and Contour Link (6.3%/9.3%). The 4 other meters were influenced by HCT (Accu-Chek Performa: 4.7%/20.9%, Accu-Chek Aviva Nano: 4.5%/22.4%, FreeStyle Freedom Lite: 4.8%/24.5%; MyLife Pura: 6.4%/28.7%). In this study, all meters showed a good accuracy, but only 50% of them, including MyStar Extra, were shown to reliably correct for potential hematocrit influence on the meter results.

Blood glucose meters employing dynamic electrochemistry are stable against hematocrit interference in a laboratory setting

BACKGROUND

Hematocrit (HCT) is known to be a confounding factor that interferes with many blood glucose (BG) measurement technologies, resulting in wrong readings. Dynamic electrochemistry has been identified as one possible way to correct for these potential deviations. The purpose of this laboratory investigation was to assess the HCT stability of four BG meters known to employ dynamic electrochemistry (BGStar and iBGStar, Sanofi; Wavesense Jazz, AgaMatrix; Wellion Linus, MedTrust) in comparison with three other devices (GlucoDock, Medisana; OneTouch Verio Pro, LifeScan; FreeStyle Freedom InsuLinx, Abbott-Medisense).

METHODS

Venous heparinized blood was immediately aliquoted after draw and manipulated to contain three different BG concentrations (60-90, 130-160, and 280-320 mg/dl) and five different HCT levels (25%, 35%, 45%, 55%, and 60%). After careful oxygenation to normal blood oxygen pressure, each of the resulting 15 different samples was measured six times with three devices and three strip lots of each meter. The YSI Stat 2300 served as laboratory reference method. Stability to HCT influence was assumed when less than 10% difference occurred between the highest and lowest mean glucose deviations in relation to HCT concentrations [hematocrit interference factor (HIF)].

RESULTS

Five of the investigated self-test meters showed a stable performance with the different HCT levels tested in this investigation: BGStar (HIF 4.6%), iBGStar (6.6%), Wavesense Jazz (4.1%), Wellion Linus (8.5%), and OneTouch Verio Pro (6.2%). The two other meters were influenced by HCT (FreeStyle InsuLinx 17.8%; GlucoDock 46.5%).

CONCLUSIONS

In this study, meters employing dynamic electrochemistry, as used in the BGStar and iBGStar devices, were shown to correct for potential HCT influence on the meter results. Dynamic electrochemistry appears to be an effective way to handle this interfering condition.

Hematocrit interference of blood glucose meters for patient self-measurement

BACKGROUND

Abnormal hematocrit levels may interfere with glucose readings of patient self-assessment blood glucose (BG) meters. The aim of this laboratory investigation was to assess the potential influence of hematocrit variations on a variety of BG meters applying different measurement technologies.

METHODS

Venous heparinized blood was manipulated to contain three different BG concentrations (50-90, 120-180, and 280-350 mg/dl) and five different hematocrit levels (25%, 35%, 45%, 55%, and 65%). After careful oxygenation to normal blood oxygen pressure (65-100 mmHg), each sample was measured (eight times) with the following devices: Accu-Chek® Aviva Nano and Active, Breeze®2 and Contour®, FreeStyle Freedom Lite®, GlucoDr. auto™, Glucofix® mio Plus, GlucoLab™, GlucoMen® LX Plus, Nova Max® Link, Nova Max® Plus, OneTouch® Ultra®2 and Verio®, On Call® Plus and Platinum, Optium Xceed®, Precision Xceed®, and TaiDoc Fora TD-4227. A YSI 2300 STAT Plus™ glucose analyzer served as reference method. Stability to hematocrit influence was assumed, with <10% mean glucose result bias between the highest and lowest hematocrit levels.

RESULTS

Six of the investigated meters showed a stable performance in this investigation: Accu-Chek Active (7%), Glucofix mio Plus (5%), GlucoMen LX Plus (4%), Nova Max Plus (4%), Nova Max Link (7%), and OneTouch Verio (3%). All other meters failed this hematocrit interference test, with FreeStyle Freedom Lite (11%), and On Call Platinum (12%) being the better devices and On Call Plus (68%), GlucoLab (51%), TaiDoc Fora TD-4227 (39%), and Breeze 2 (38%) showing the worst performance.

CONCLUSIONS

Hematocrit may affect BG meter performance in daily routine. In case of interference, low hematocrit values (<35%) result in too high readings. Our results encourage use of meters that are not affected by hematocrit interference.

Determination of hematocrit interference in blood samples derived from patients with different blood glucose concentrations

BACKGROUND

We performed a blood glucose meter hematocrit (HCT) interference test with lower sample manipulation requirements by using blood samples from patients with different blood glucose (BG) levels.

METHODS

Blood from five patients with different BG levels (2.8, 5.6, 8.3, 13.9, 19.4 mmol/liter) was manipulated to contain five different HCT concentrations (35/40/45/50/55%). Each sample was measured three times in parallel with 14 BG testing devices (reference method: YSI 2300 STAT Plus™ Glucose Analyzer). The largest mean deviations in both directions from the reference method (normalized to 100% at 45% HCT) were added as a measure for hematocrit interference factor (HIF). A HIF >10% was considered to represent clinically relevant HCT interference.

RESULTS

Few devices showed no clinically relevant HCT interference at high/low BG levels: BGStar® (7.2%, 7.3%), iBGStar® (9.0%, 8.6%), Contour® (10.0%, 4.6%), OneTouch® Verio™ 2 (10.0%, 5.2%), and GlucoMen® LX (7.2%, 5.1%). Other devices showed interference at one or both glucose ranges: ACCU-CHEK® Aviva (12.6%, 10.7%), Aviva Nano (7.2%, 10.5%), Breeze2 (3.6%, 30.2%), GlucoCard G+ (12.6%, 7.0%), OneTouch® Ultra®2 (12.6%, 25.6%), FreeStyle Freedom Lite® (9.0%, 11.0%), Precision Xceed (16.2%, 15.3%), and MediTouch® (19.8%, 28.0%). The deviations in all devices were less pronounced in the HCT range of 35-50%.

CONCLUSIONS

The results of this trial with less sample manipulation (HCT only) confirmed previous examinations with HCT and glucose manipulation. The same devices showed HCT stability as previously observed. Artificial sample manipulation may be less crucial than expected when evaluating HCT interference.

Clinical assessment of the accuracy of blood glucose measurement devices

OBJECTIVES

Blood glucose meters for patient self-measurement need to comply with the accuracy standards of the ISO 15197 guideline. We investigated the accuracy of the two new blood glucose meters BG*Star and iBG*Star (Sanofi-Aventis) in comparison to four other competitive devices (Accu-Chek Aviva, Roche Diagnostics; FreeStyle Freedom Lite, Abbott Medisense; Contour, Bayer; OneTouch Ultra 2, Lifescan) at different blood glucose ranges in a clinical setting with healthy subjects and patients with type 1 and type 2 diabetes. BGStar and iBGStar are employ dynamic electrochemistry, which is supposed to result in highly accurate results.

METHODS

The study was performed on 106 participants (53 female, 53 male, age (mean ± SD): 46 ± 16 years, type 1: 32 patients, type 2: 34 patients, and 40 healthy subjects). Two devices from each type and strips from two different production lots were used for glucose assessment (∼200 readings/meter). Spontaneous glucose assessments and glucose or insulin interventions under medical supervision were applied to perform measurements in the different glucose ranges in accordance with the ISO 15197 requirements. Sample values <50 mg/dL and >400 mg/dL were prepared by laboratory manipulations. The YSI glucose analyzer (glucose oxidase method) served as the standard reference method which may be considered to be a limitation in light of glucose hexokinase-based meters.

RESULTS

For all devices, there was a very close correlation between the glucose results compared to the YSI reference method results. The correlation coefficients were r = 0.995 for BGStar and r = 0.992 for iBGStar (Aviva: 0.995, Freedom Lite: 0.990, Contour: 0.993, Ultra 2: 0.990). Error-grid analysis according to Parkes and Clarke revealed both 100% of the readings to be within the clinically acceptable areas (Clarke: A + B with BG*Star (100 + 0), Aviva (97 + 3), and Contour (97 + 3); and 99.5% with iBG*Star (97.5 + 2), Freedom Lite (98 + 1.5), and Ultra 2 (97.5 + 2)).

CONCLUSIONS

This study demonstrated the very high accuracy of BG*Star, iBG*Star, and the competitive blood glucose meters in a clinical setting.

Dynamic electrochemistry corrects for hematocrit interference on blood glucose determinations with patient self-measurement devices

BACKGROUND

It has been demonstrated that dynamic electrochemistry can be used to correct blood glucose measurement results for potentially interfering conditions, such as humidity, hematocrit (HCT) variations, and ascorbic acid. The purpose of this laboratory investigation was to assess the potential influence of hematocrit variations on a variety of blood glucose meters applying different measurement technologies.

METHODS

Venous heparinized whole blood was drawn, immediately aliquoted, and manipulated to contain three different blood glucose concentrations (80, 155, and 310 mg/dl) and five different hematocrit levels (25%, 37%, 45%, 52%, and 60%). After careful oxygenation to normal blood oxygen pressure, each of the resulting 15 different samples was measured 8 times with the following devices: BGStar, Contour, Accu-Chek Aviva, Accu-Chek Aviva Nano, Breeze 2, Precision Xceed, OneTouch Ultra 2, OneTouch Verio, FreeStyle Freedom Lite, Glucocard G+, GlucoMen LX, GlucoMen GM, and StatStrip [point-of-care (POC) device]. Cobas (Roche Diagnostics, glucose hexokinase method) served as laboratory plasma reference method. Stability to hematocrit influence was assumed when less than 10% bias occurred between the highest and lowest hematocrit levels when analyzing mean deviations for all three glucose concentrations.

RESULTS

Besides the POC StatStrip device, which is known to measure and correct for hematocrit (resulting in <2% bias), four self-test meters also showed a stable performance in this investigation: dynamic electrochemistry, BGStar (8%), and static electrochemistry, Contour (6%), Glucocard G+ (2%), and OneTouch Verio (6%). The other meters failed this test: colorimetry, FreeStyle Freedom Lite (16%), and static electrochemistry, Accu-Chek Aviva (23%), Accu-Chek Aviva Nano (18%), Breeze 2 (36%), OneTouch Ultra 2 (34%), Precision Xceed (34%), GlucoMen LX (24%), and GlucoMen GM (31%).

CONCLUSIONS

As hematocrit variations occur in daily routine (e.g., because of smoking, exercise, hypermenorrhea, pregnancy, stay in mountains, and hemodialysis), our results may encourage use of meters with stable performance under these conditions. Dynamic electrochemistry as used in the BGStar device (sanofi-aventis) appears to be an effective technology to correct for potential hematocrit influence on the meter results.

Self-monitoring of blood glucose in diabetes: is it worth it?

Self-monitoring of blood glucose (SMBG) is advocated as a valuable aid in the management of diabetes. The volume and cost of monitoring continues to increase. SMBG has a number of theoretical advantages/disadvantages which might impact on treatment, outcome and wellbeing. Investigating and quantifying the effect of self-monitoring in a condition where self-management plays a central role poses major methodological difficulties because of the need to minimize confounding factors. Despite the absence of definitive evidence, some situations where monitoring is generally accepted to be beneficial include patients on insulin, during pregnancy, in patients with hypoglycaemia unawareness and while driving. An area of controversy is the role of monitoring in non-insulin-requiring type-2 diabetes where observational and controlled studies give conflicting results. The available evidence does not support the general use of monitoring by all patients with type-2 diabetes, although further research is needed to identify specific subgroups of patients or specific situations where monitoring might be useful. The best use of SMBG in patients with type-2 diabetes might be for those receiving insulin and those on sulphonylurea drugs. The impact of monitoring on patient wellbeing must also be considered, with some studies suggesting adverse psychological effects. Given the large increase in the prevalence of type-2 diabetes, it will be important to define the role of SMBG so that resources can be used appropriately. Presently, the widespread use of SMBG (particularly in type-2 diabetes patients) is a good example of self-monitoring that was adopted in advance of robust evidence of its clinical efficacy.

Severe unrecognised hypoglycaemia presenting as pseudonormoglycaemia and unexplained coma in two patients with renal failure

We describe the occurrence of pseudonormoglycaemia and the consequences of severe prolonged hypoglycaemia observed in two patients with renal failure requiring renal replacement therapy. There was a persistent discrepancy, in both cases, between glucose levels measured by the hospital laboratory and those measured by the bedside glucometer, resulting in a significantly false high glucose measurement (pseudonormoglycaemia). This inaccurate glucose determination led to a delayed diagnosis of their truly severe and prolonged hypoglycaemia ultimately leading to prolonged coma and death. Icodextrin, a polysaccharide commonly used in continuous ambulatory peritoneal dialysis solutes, and maltose-containing solutions such as immunoglobulins for intravenous administration, can cause a dangerous overestimation of glucose levels determined by capillary blood glucose analysers utilising glucose dehydrogenase. A high level of awareness is required in order to avoid incidents related to misinterpretation of glucose levels.

Assessing the Quality of Glucose Monitor Studies: A Critical Evaluation of Published Reports

Background: In recent years, a large number of studies have been published on the performance of glucose monitors. The quality of these reports is not known.

Methods: We searched the PubMed database for performance evaluations of handheld glucose monitors published from August 2002 to November 2006. Relevant articles were compared to 20 recommendations from the Standards for Reporting Diagnostic Accuracy (STARD) and 18 recommendations from the Clinical and Laboratory Standards Institute (CLSI).

Results: A total of 52 reports met our inclusion criteria and were reviewed. None (0%) of the reports conformed to all 38 STARD and CLSI recommendations. The range of compliance to these recommendations varied widely (median 53%; range 21%–84%). Only 1 study of the 52 reported following a CLSI recommendation for checking reference test results. Fewer than half (42%) of the reports contained STARD-recommended statements regarding how and when comparative measurements were performed.

Conclusions: None of the glucose monitor reports from our review conformed to all STARD and CLSI recommendations. Our finding that the average rate of compliance to recommendations was low suggests that many of the researchers did not follow published recommendations for study design, methodology, and reporting and that study quality and conclusions may have been affected. Future studies evaluating the performance of glucose monitoring systems should be carefully designed and follow published recommendations for methodological and reporting quality.