Retrospective evaluation of the accuracy of Roche AccuChek Inform and Nova StatStrip glucose meters when used on critically ill patients

Accuracy of the Nova StatStrip® glucometer in patients undergoing major abdominal surgery: an observational study

PURPOSE

While the Nova StatStrip® Glucose Hospital Meter System (Nova Biomedical, Waltham, MA, USA) is approved for point-of-care testing (POCT) in critically ill patients, its use during major abdominal surgery has not been evaluated. The purpose of this study was to assess the accuracy of the Nova StatStrip glucometer in patients undergoing major hepatobiliary procedures using the Parkes error grid (ISO15197:2013) and criteria defined by the Clinical and Laboratory Standards Institute (CLSI) POCT12-A3 guideline.

METHODS

This study was a post hoc exploratory study of patients participating in a prospective randomized controlled trial on the effects of hyperinsulinemic normoglycemia (HNC) on infectious outcomes after hepatobiliary surgery. Arterial blood samples were collected before surgery and one hour, two hours, and three hours after baseline. Blood glucose levels were analyzed by the Nova StatStrip glucometer and the GEM® PremierTM 5000 blood gas analyzer. Accuracy of the StatStrip glucometer was assessed using the Parkes error grid for type 1 diabetes mellitus (when 99% of samples were within zones A and B on the Parkes error grid and clinical accuracy was acceptable) and the CLSI POCT12-A3 criteria.

RESULTS

Blood glucose levels were analyzed in 135 patients, 70 of whom received the HNC. In the Parkes error grid plotted, all samples at all time-points were within zones A and B. The Nova StatStrip glucometer also satisfied CLSI POCT12-A3 criteria at all time-points.

CONCLUSION

The Nova StatStrip glucometer was accurate in patients undergoing major upper abdominal surgery, independent of the administration of high-dose insulin therapy.

STUDY REGISTRATION

ClinicalTrials.gov (NCT01528189); registered 7 February 2012.

Pediatric Reference Intervals for Point-of-Care Random Glucose in Healthy Children and Adolescents

BACKGROUND

Glucose testing at the point-of-care (POC) is routinely used in the diagnosis, prognosis, and monitoring of diabetic states and other clinical conditions. Accurate reference intervals (RIs) are essential in appropriate clinical decision-making. In this study, RIs were established for random glucose (whole blood) in the Canadian Laboratory Initiative on Pediatric Reference (CALIPER) cohort using 2 POC instruments: the Nova Biomedical StatStrip (handheld glucometer) and Radiometer ABL90 FLEX Plus (benchtop instrument). An analytical comparison was also completed between the 2 POC systems and a laboratory-based analyzer (Ortho Vitros 5600).

METHODS

Approximately 400 healthy children and adolescents (birth to 18 years) were recruited with informed consent from community schools or clinics providing care to metabolically stable/healthy children. Random venous samples were collected and run sequentially on the Nova Biomedical StatStrip (whole blood), Radiometer ABL90 FLEX Plus (whole blood), and Ortho Vitros 5600 (serum). RIs and method comparisons between analytical platforms were completed according to CLSI guidelines.

RESULTS

Significantly different glucose concentrations were observed in infancy, requiring age-specific partitioning (0-<1 month, 1-<6 months, 6 months-<19 years) on all platforms. Excellent concordance was observed between POC platforms (Pearson r > 0.90), with a small negative bias. Good comparability was observed between POC and laboratory-based platforms (Pearson r > 0.80).

CONCLUSION

This study established comprehensive pediatric RIs for random glucose (whole blood) on modern POC systems in the CALIPER cohort for the first time. Results demonstrate excellent concordance in glucose values between POC systems and good comparability with a laboratory-based analyzer. These data will assist in more accurate clinical decision-making in pediatric healthcare institutions.

Unintended Consequence of High-Dose Vitamin C Therapy for an Oncology Patient: Evaluation of Ascorbic Acid Interference With Three Hospital-Use Glucose Meters

The use of high-dose vitamin C in cancer care has offered promising results for some patients. However, the intravenous (IV) doses used for these patients can reach concentrations that interfere with some strip-based glucose meters. We characterized the impact of vitamin C interference, from standard to the very high doses used for some cancer protocols, using three different hospital-use glucose meters. For two of the three devices tested, increasing concentrations of ascorbic acid caused false elevations in the glucose measurements. The third glucose meter did not provide inaccurate results, regardless of the vitamin C concentration present. Rather, above a certain threshold, the device generated error messages and no results could be obtained.

Current Status of Clinical Application of Point-of-Care Testing

CONTEXT.—

The clinical applications of point-of-care testing (POCT) are gradually increasing in many health care systems. Recently, POCT devices using molecular genetic method techniques have been developed. We need to examine clinical pathways to see where POCT can be applied to improve them.

OBJECTIVE.—

To introduce up-to-date POCT items and equipment and to provide the content that should be prepared for clinical application of POCT.

DATA SOURCES.—

Literature review based on PubMed searches containing the terms point-of-care testing, clinical chemistry, diagnostic hematology, and clinical microbiology.

CONCLUSIONS.—

If medical resources are limited, POCT can help clinicians make quick medical decisions. As POCT technology improves and menus expand, areas where POCT can be applied will also increase. We need to understand the limitations of POCT so that it can be optimally used to improve patient management.

Comparison of the FreeStyle Libre Pro Flash Continuous Glucose Monitoring (CGM) System and Point-of-Care Capillary Glucose Testing in Hospitalized Patients With Type 2 Diabetes Treated With Basal-Bolus Insulin Regimen

OBJECTIVE

We compared the performance of the FreeStyle Libre Pro continuous glucose monitoring (CGM) and point-of-care capillary glucose testing (POC) among insulin-treated hospitalized patients with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

This was a prospective study in adult patients with T2D admitted to general medicine and surgery wards. Patients were monitored with POC before meals and bedtime and with CGM during the hospital stay. Study end points included differences between POC and CGM in mean daily blood glucose (BG), hypoglycemia <70 and <54 mg/dL, and nocturnal hypoglycemia. We also calculated the mean absolute relative difference (MARD), ±15%/15 mg/dL, ±20%/20 mg/dL, and ±30%/30 mg/dL and error grid analysis between matched glucose pairs.

RESULTS

Mean daily glucose was significantly higher by POC (188.9 ± 37.3 vs. 176.1 ± 46.9 mg/dL) with an estimated mean difference of 12.8 mg/dL (95% CI 8.3-17.2 mg/dL), and proportions of patients with glucose readings <70 mg/dL (14% vs. 56%) and <54 mg/dL (4.1% vs. 36%) detected by POC BG were significantly lower compared with CGM (all P < 0.001). Nocturnal and prolonged CGM hypoglycemia <54 mg/dL were 26% and 12%, respectively. The overall MARD was 14.8%, ranging between 11.4% and 16.7% for glucose values between 70 and 250 mg/dL and higher for 51-69 mg/dL (MARD 28.0%). The percentages of glucose readings within ±15%/15 mg/dL, ±20%/20 mg/dL, and ±30%/30 mg/dL were 62%, 76%, and 91%, respectively. Error grid analysis showed 98.8% of glucose pairs within zones A and B.

CONCLUSIONS

Compared with POC, FreeStyle Libre CGM showed lower mean daily glucose and higher detection of hypoglycemic events, particularly nocturnal and prolonged hypoglycemia in hospitalized patients with T2D. CGM's accuracy was lower in the hypoglycemic range.

Assessment of the performance of blood glucose monitoring systems for monitoring dysglycaemia in neonatal patients

OBJECTIVE

To validate a three-step protocol that assesses the clinical risk associated with using blood glucose monitoring systems (BGMS) in neonates for the management of dysglycaemia.

METHOD

The three-step validation approach included confirmation of the accuracy of the reference method using National Institute of Standards and Technology (NIST) glucose standards, assessment of analytical risk performed on whole blood collected from paediatric patients routinely tested for glucose and a clinical risk assessment performed using heel stick capillary samples collected from 147 new-born babies and neonates admitted to intensive care. BGMS glucose measurements were compared with the NIST aligned laboratory reference method.

RESULTS

The accuracy of the laboratory reference method was confirmed with the NIST standards. Specificity studies demonstrated that the accuracy of one of the BGMS was affected, particularly, in the hypoglycaemic range, by known interference factors including haematocrit, ascorbic acid, lactose, galactose, N-acetylcysteine and glutathione. The accuracy of the other BGMS was unaffected. The clinical performance of this BGMS in neonates met the system accuracy criteria of Clinical and Laboratory Standards Institute (CLSI) POCT 12-A3 standard for evaluating hospital BGMS with 95.1% of glucose measurements within±0.67 mmol/L for samples ≤5.55 mmol/L and 95.6% within±12.5% for samples>5.55 mmol/L.

CONCLUSIONS

This three-step validation protocol provides a challenging approach for determining the accuracy and reliability of BGMS for managing dysglycaemia in neonates. StatStrip BGMS achieved analytical and clinical performance criteria confirming its suitability for use in neonates. We advocate that this validation approach should be considered for performance evaluations of both BGMS and continuous glucose monitoring systems going forward.

Performance of a Modern Glucose Meter in ICU and General Hospital Inpatients: 3 Years of Real-World Paired Meter and Central Laboratory Results

OBJECTIVE

Due to accuracy concerns, the Food and Drug Administration issued guidances to manufacturers that resulted in Center for Medicare and Medicaid Services stating that the use of meters in critically ill patients is "off-label" and constitutes "high complexity" testing. This is causing significant workflow problems in ICUs nationally. We wished to determine whether real-world accuracy of modern glucose meters is worse in ICU patients compared with non-ICU inpatients.

DESIGN

We reviewed glucose results over the preceding 3 years, comparing results from paired glucose meter and central laboratory tests performed within 60 minutes of each other in ICU versus non-ICU settings.

SETTING

Seven ICU and 30 non-ICU wards at a 1,300-bed academic hospital in the United States.

SUBJECTS

A total of 14,763 general medicine/surgery inpatients and 20,970 ICU inpatients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Compared meter results with near simultaneously performed laboratory results from the same patient by applying the 2016 U.S. Food and Drug Administration accuracy criteria, determining mean absolute relative difference and examining where paired results fell within the Parkes consensus error grid zones. A higher percentage of glucose meter results from ICUs than from non-ICUs passed 2016 Food and Drug Administration accuracy criteria (p < 10) when comparing meter results with laboratory results. At 1 minute, no meter result from ICUs posed dangerous or significant risk by error grid analysis, whereas at 10 minutes, less than 0.1% of ICU meter results did, which was not statistically different from non-ICU results.

CONCLUSIONS

Real-world accuracy of modern glucose meters is at least as accurate in the ICU setting as in the non-ICU setting at our institution.

Accuracy of Capillary and Arterial Whole Blood Glucose Measurements Using a Glucose Meter in Patients under General Anesthesia in the Operating Room

BACKGROUND

The aim of this study was to evaluate the use of a glucose meter with surgical patients under general anesthesia in the operating room.

METHODS

Glucose measurements were performed intraoperatively on 368 paired capillary and arterial whole blood samples using a Nova StatStrip (Nova Biomedical, USA) glucose meter and compared with 368 reference arterial whole blood glucose measurements by blood gas analyzer in 196 patients. Primary outcomes were median bias (meter minus reference), percentage of glucose meter samples meeting accuracy criteria for subcutaneous insulin dosing as defined by Parkes error grid analysis for type 1 diabetes mellitus, and accuracy criteria for intravenous insulin infusion as defined by Clinical and Laboratory Standards Institute guidelines. Time under anesthesia, patient position, diabetes status, and other variables were studied to determine whether any affected glucose meter bias.

RESULTS

Median bias (interquartile range) was -4 mg/dl (-9 to 0 mg/dl), which did not differ from median arterial meter bias of -5 mg/dl (-9 to -1 mg/dl; P = 0.32). All of the capillary and arterial glucose meter values met acceptability criteria for subcutaneous insulin dosing, whereas only 89% (327 of 368) of capillary and 93% (344 of 368) arterial glucose meter values met accuracy criteria for intravenous insulin infusion. Time, patient position, and diabetes status were not associated with meter bias.

CONCLUSIONS

Capillary and arterial blood glucose measured using the glucose meter are acceptable for intraoperative subcutaneous insulin dosing. Whole blood glucose on the meter did not meet accuracy guidelines established specifically for more intensive (e.g., intravenous insulin) glycemic control in the acute care environment.

Analytical Performance Evaluation of Infopia Element™ Auto-coding Blood Glucose Monitoring System for Self-Monitoring of Blood Glucose

BACKGROUND

Element™ Auto-coding Blood Glucose Monitoring System (BGMS; Infopia Co., Ltd., Anyang-si, Korea) was developed for self-monitoring of blood glucose (SMBG).

METHODS

Precision, linearity, and interference were tested. Eighty-four capillary blood samples measured by Element™ BGMS were compared with central laboratory method (CLM) results in venous serum. Accuracy was evaluated using ISO 15197:2013 criteria.

RESULTS

Coefficients of variation (CVs; mean) were 2.4% (44.2 mg/dl), 3.7% (100.6 mg/dl), and 2.1% (259.8 mg/dl). Linearity was shown at concentrations 39.25-456.25 mg/l (y = 0.989 + 0.984x, SE = 17.63). Up to 15 mg/dl of galactose, ascorbic acid, and acetaminophen, interference > 10.4% was not observed. Element™ BGMS glucose was higher than CLM levels by 3.2 mg/dl (at 200 mg/dl) to 8.2 mg/dl (at 100 mg/dl). The minimum specification for bias (3.3%) was met at 140 and 200 mg/l glucose. In the Clarke and consensus error grids, 100% of specimens were within zone A and B. For Element™ BGMS values, 92.9% (78/84) to 94.0% (79/84) were within a 15 mg/dl (< 100 mg/dl) or 15% (> 100 mg/dl) of the average CLM value.

CONCLUSION

Element™ BGMS was considered an appropriate SMBG for home use; however, the positive bias at low-to-mid glucose levels requires further improvement.

Clinical Impact of Accurate Point-of-Care Glucose Monitoring for Tight Glycemic Control in Severely Burned Children

OBJECTIVES

The goal of this study was to retrospectively evaluate the clinical impact of an accurate autocorrecting blood glucose monitoring system in children with severe burns. Blood glucose monitoring system accuracy is essential for providing appropriate intensive insulin therapy and achieving tight glycemic control in critically ill patients. Unfortunately, few comparison studies have been performed to evaluate the clinical impact of accurate blood glucose monitoring system monitoring in the high-risk pediatric burn population.

DESIGN

Retrospective analysis of an electronic health record system.

SETTING

Pediatric burn ICU at an academic medical center.

PATIENTS

Children (aged < 18 yr) with severe burns (≥ 20% total body surface area) receiving intensive insulin therapy guided by either a noncorrecting (blood glucose monitoring system-1) or an autocorrecting blood glucose monitoring system (blood glucose monitoring system-2).

MEASUREMENTS AND MAIN RESULTS

Patient demographics, insulin rates, and blood glucose monitoring system measurements were collected. The frequency of hypoglycemia and glycemic variability was compared between the two blood glucose monitoring system groups. A total of 122 patient charts from 2001 to 2014 were reviewed. Sixty-three patients received intensive insulin therapy using blood glucose monitoring system-1 and 59 via blood glucose monitoring system-2. Patient demographics were similar between the two groups. Mean insulin infusion rates (5.1 ± 3.8 U/hr; n = 535 paired measurements vs 2.4 ± 1.3 U/hr; n = 511 paired measurements; p < 0.001), glycemic variability, and frequency of hypoglycemic events (90 vs 12; p < 0.001) were significantly higher in blood glucose monitoring system-1-treated patients. Compared with laboratory measurements, blood glucose monitoring system-2 yielded the most accurate results (mean ± SD bias: -1.7 ± 6.9 mg/dL [-0.09 ± 0.4 mmol/L] vs 7.4 ± 13.5 mg/dL [0.4 ± 0.7 mmol/L]). Blood glucose monitoring system-2 patients achieve glycemic control more quickly (5.7 ± 4.3 vs 13.1 ± 6.9 hr; p< 0.001) and stayed within the target glycemic control range longer compared with blood glucose monitoring system-1 patients (85.2% ± 13.9% vs 57.9% ± 29.1%; p < 0.001).

CONCLUSIONS

Accurate autocorrecting blood glucose monitoring system optimizes intensive insulin therapy, improves tight glycemic control, and reduces the risk of hypoglycemia and glycemic variability. The use of an autocorrecting blood glucose monitoring system for intensive insulin therapy may improve glycemic control in severely burned children.

Glucose Meters: Here Today, Gone Tomorrow?

OBJECTIVE

This special article will review the history of blood glucose meter hospital use and current issues surrounding their use in this patient population.

STUDY SELECTION

Secondary to accuracy concerns that have been known, but likely underappreciated for many years, the U.S. Food and Drug Administration and Centers for Medicare and Medicaid Services are moving toward eliminating current blood glucose meters for use with critically ill patients.

DATA SOURCES

Recent guidance from the U.S. Food and Drug Administration and Centers for Medicare and Medicaid Services along with several recent publications will be used as the primary data sources.

DATA EXTRACTION

U.S. Food and Drug Administration, Centers for Medicare and Medicaid Services communications combined with recent interpretation of this guidance were used to provide this overview.

DATA SYNTHESIS

Centers for Medicare and Medicaid Services have issued a temporary moratorium on the prohibition of the use of blood glucose meters in the critically ill. They have not given a deadline for the moratorium or solicited comments.

CONCLUSIONS

Physicians who care for critically ill patients need to be cognizant of the accuracy and interference limitations of blood glucose meters and aware of the current regulatory situation.

Clinical impact of improved point-of-care glucose monitoring in neonatal intensive care using Nova StatStrip: Evidence for improved accuracy, better sensitivity, and reduced test utilization

OBJECTIVES

Studies have demonstrated improved analytical performance of the Nova StatStrip glucose meter, but limited data is available on its clinical performance in critically ill neonates in the neonatal intensive care unit (NICU).

DESIGN AND METHODS

A retrospective charge review was conducted on 651 neonates admitted to the NICU over 2 years. Demographics, sample collection information, and clinical details were recorded. Glucose measurements were performed at the bedside using either the Nova StraStrip or LifeScan SureStep Flexx meters as well as corresponding measurements of laboratory venous plasma glucose. Performance was analyzed by receiver operator characteristic (ROC) curves for detecting hypoglycemia and critical glucose levels.

RESULTS

Linear regression analysis comparing StatStrip and laboratory venous plasma glucose samples demonstrated significantly tighter agreement (r(2)=0.7994) and accuracy (mean bias=0.13mmol/L) than SureStep (r(2)=0.6845 and mean bias=0.53mmol/L). StatStrip also showed improved sensitivity for detecting critical low glucose values ≤3.0mmol/L (80.9 vs 68.9%, p<0.05). ROC curve analysis further demonstrated excellent performance of StatStrip at this cutoff with an AUC of 0.98. Overall, neonates were also tested significantly less frequently with the StatStrip meter by 24% compared to SureStep.

CONCLUSIONS

Implementation of StatStrip led to better agreement with venous plasma glucose, improved detection of critical low glucose results, and more efficient test utilization. This study demonstrates the importance of accurate and sensitive glucose monitoring in the NICU.

Postmarket Surveillance of Point-of-Care Glucose Meters through Analysis of Electronic Medical Records

BACKGROUND

The electronic medical record (EMR) holds a promising source of data for active postmarket surveillance of diagnostic accuracy, particularly for point-of-care (POC) devices. Through a comparison with prospective bedside and laboratory accuracy studies, we demonstrate the validity of active surveillance via an EMR data mining method [Data Mining EMRs to Evaluate Coincident Testing (DETECT)], comparing POC glucose results to near-in-time central laboratory glucose results.

METHODS

The Roche ACCU-CHEK Inform II® POC glucose meter was evaluated in a laboratory validation study (n = 73), a prospective bedside intensive care unit (ICU) study (n = 124), and with DETECT (n = 852–27 503). For DETECT, the EMR was queried for POC and central laboratory glucose results with filtering based on of bedside collection timestamps, central laboratory time delays, patient location, time period, absence of repeat testing, and presence of peripheral lines.

RESULTS

DETECT and the bedside ICU study produced similar estimates of average bias (4.5 vs 5.0 mg/dL) and relative random error (6.3% vs 5.6%), with overlapping CIs. For glucose &lt;100 mg/dL, the laboratory validation study estimated a lower relative random error of 3.6%. POC average bias correlated with central laboratory turnaround times, consistent with 4.8 mg · dL−1 · h−1 glycolysis. After glycolysis adjustment, average bias was estimated by the bedside ICU study at −0.4 mg/dL (CI, −1.6 to 0.9) and DETECT at −0.7 (CI, −1.3 to 0.2), and percentage POC results occurring outside Clinical Laboratory Standards Institute quality goals were 2.4% and 4.8%, respectively.

CONCLUSIONS

This study validates DETECT for estimating POC glucose meter accuracy compared with a prospective bedside ICU study and establishes it as a reliable postmarket surveillance methodology.

Glucose intolerance associated with hypoxia in people living at high altitudes in the Tibetan highland

OBJECTIVES

To clarify the association between glucose intolerance and high altitudes (2900-4800 m) in a hypoxic environment in Tibetan highlanders and to verify the hypothesis that high altitude dwelling increases vulnerability to diabetes mellitus (DM) accelerated by lifestyle change or ageing.

DESIGN

Cross-sectional epidemiological study on Tibetan highlanders.

PARTICIPANTS

We enrolled 1258 participants aged 40-87 years. The rural population comprised farmers in Domkhar (altitude 2900-3800 m) and nomads in Haiyan (3000-3100 m), Ryuho (4400 m) and Changthang (4300-4800 m). Urban area participants were from Leh (3300 m) and Jiegu (3700 m).

MAIN OUTCOME MEASURE

Participants were classified into six glucose tolerance-based groups: DM, intermediate hyperglycaemia (IHG), normoglycaemia (NG), fasting DM, fasting IHG and fasting NG. Prevalence of glucose intolerance was compared in farmers, nomads and urban dwellers. Effects of dwelling at high altitude or hypoxia on glucose intolerance were analysed with the confounding factors of age, sex, obesity, lipids, haemoglobin, hypertension and lifestyle, using multiple logistic regression.

RESULTS

The prevalence of DM (fasting DM)/IHG (fasting IHG) was 8.9% (6.5%)/25.1% (12.7%), respectively, in all participants. This prevalence was higher in urban dwellers (9.5% (7.1%)/28.5% (11.7%)) and in farmers (8.5% (6.1%)/28.5% (18.3%)) compared with nomads (8.2% (5.7%)/15.7% (9.7%)) (p=0.0140/0.0001). Dwelling at high altitude was significantly associated with fasting IHG+fasting DM/fasting DM (ORs for >4500 and 3500-4499 m were 3.59/4.36 and 2.07/1.76 vs <3500 m, respectively). After adjusting for lifestyle change, hypoxaemia and polycythaemia were closely associated with glucose intolerance.

CONCLUSIONS

Socioeconomic factors, hypoxaemia and the effects of altitudes >3500 m play a major role in the high prevalence of glucose intolerance in highlanders. Tibetan highlanders may be vulnerable to glucose intolerance, with polycythaemia as a sign of poor hypoxic adaptation, accelerated by lifestyle change and ageing.

Impact of Glucose Meter Error on Glycemic Variability and Time in Target Range During Glycemic Control After Cardiovascular Surgery

BACKGROUND

We retrospectively studied the impact of glucose meter error on the efficacy of glycemic control after cardiovascular surgery.

METHOD

Adult patients undergoing intravenous insulin glycemic control therapy after cardiovascular surgery, with 12-24 consecutive glucose meter measurements used to make insulin dosing decisions, had glucose values analyzed to determine glycemic variability by both standard deviation (SD) and continuous overall net glycemic action (CONGA), and percentage glucose values in target glucose range (110-150 mg/dL). Information was recorded for 70 patients during each of 2 periods, with different glucose meters used to measure glucose and dose insulin during each period but no other changes to the glycemic control protocol. Accuracy and precision of each meter were also compared using whole blood specimens from ICU patients.

RESULTS

Glucose meter 1 (GM1) had median bias of 11 mg/dL compared to a laboratory reference method, while glucose meter 2 (GM2) had a median bias of 1 mg/dL. GM1 and GM2 differed little in precision (CV = 2.0% and 2.7%, respectively). Compared to the period when GM1 was used to make insulin dosing decisions, patients whose insulin dose was managed by GM2 demonstrated reduced glycemic variability as measured by both SD (13.7 vs 21.6 mg/dL, P < .0001) and CONGA (13.5 vs 19.4 mg/dL, P < .0001) and increased percentage glucose values in target range (74.5 vs 66.7%, P = .002).

CONCLUSIONS

Decreasing glucose meter error (bias) was associated with decreased glycemic variability and increased percentage of values in target glucose range for patients placed on intravenous insulin therapy following cardiovascular surgery.