Intensive insulin therapy in critically ill hospitalized patients: making it safe and effective

Mean Blood Glucose Level During ICU Hospitalization is a Strong Predictor of the Mortality of COVID-19

Objective

To investigate the potential prognostic value of mean blood glucose (MBG) in hospital for prognosis of COVID-19 adult patients in the intensive unit care unit (ICU).

Methods

A single-site and retrospective study enrolled 107 patients diagnosed as COVID-19 from department of critical care medicine in the Second Xiangya Hospital between October 2022 and June 2023. Demographic information including glucose during ICU hospitalization, comorbidity, clinical data, types of medications and treatment, and clinical outcome were collected. The multivariate logistic and cox regression was used to explore the relationship between blood glucose changes and clinical outcomes of COVID-19 during ICU stay.

Results

In total, 107 adult patients confirmed with COVID-19 were included. Multivariate logistic regression results showed an increase in MBG was associated with ICU mortality rate. Compared with normal glucose group (MBG <= 7.8 mmol/L), the risk of ICU mortality, 7-day mortality and 28-day mortality from COVID-19 were significantly increased in high glucose group (MBG >7.8mmol/L).

Conclusion

MBG level during ICU hospitalization was strongly correlated to all-cause mortality and co-infection in COVID-19 patients. These findings further emphasize the importance of overall glucose management in severe cases of COVID-19.

Impact of diabetic versus non-diabetic patients undergoing coronary artery bypass graft surgery on postoperative wound complications: A meta-analysis

The effect of diabetes mellitus (DM) on the incidence of postoperative wound complications in patients with coronary artery bypass grafting (CABG) is still unclear. Thus, we performed a meta-analysis of CABG in DM patients to evaluate existing data from both prospective and historical cohorts. The objective of this trial was to assess the relevance and extent of the effect of diabetes on the outcome of previous CABG procedures. Data sources like Embase and Pubmed were found throughout the research, and the language was limited to English through manual search. The searches were performed up to August 2023. The data were extracted from the study of the inclusion/exclusion criteria, the features of the population, the statistical approach and the clinical results. A qualitative evaluation of the qualifying studies has been carried out. Out of the 1874 studies identified, 21 cohort studies were chosen for analysis. Meta-analyses were performed in 258 454 patients (71 351 diabetic and 187 103 non-diabetic). Twenty-one studies on deep sternal wound infections in CABG patients showed a lower rate of deep sternal wound infections in non-diabetes group compared with those with diabetes (OR, 2.13; 95% CI: 1.97, 2.31, p < 0.00001). And 16 studies of superficial wound infections in patients undergoing CABG were found to be associated with a lower rate of superficial injury (OR, 1.93; 95% CI: 1.53, 2.43, p < 0.00001) compared with those with diabetes; In five trials, perfusion time during CABG (MD, 2.31; 95% CI: -0.16, 4.79, p = 0.07) was observed, and there were no significant differences between diabetes and non-diabetes. Currently, there is a higher risk for CABG in diabetes than in non-diabetes patients with sternal infections and superficial injuries. Future randomized trials will concentrate on the treatment of such perioperatively related complications, which will lower the risk of postoperative wound infection in diabetes.

Practice of hyperglycaemia control in intensive care units of the Military Hospital, Sudan—Needs of a protocol

Hyperglycaemia is a major risk factor in critically ill patients leading to adverse outcomes and mortality in diabetic and non-diabetic patients. The target blood glucose remained controversial; this study aimed to contribute in assessing the practice of hyperglycaemia control in intensive care units of the Military Hospital. Furthermore, the study proposed a protocol for hyperglycaemia control based on findings. A hospital-based cross-sectional study assessed the awareness and practice towards hyperglycaemia management in a sample 83 healthcare staff selected through stratified random sampling technique. In addition, 55 patients were enrolled, through quota sampling, after excluding those with diabetic ketoacidosis, hyperosmolar-hyperglycaemic state and patients < 18 years. A self-administrated questionnaire enabled to collect data from health staff and patient data were extracted from the medical records. SPSS-23 was used to analyze the collected data. Chi-square and ANOVA tests assessed the association among variables, these tests were considered statistically significant when p ≤ 0.05. The training on hyperglycaemia control differed (p = 0.017) between doctors and nurses. The target glycaemic level (140–180 mg/dl) was known by 11.1% of the study participants. Neither the knowledge nor the practice of hyperglycaemia control methods differed among staff (p> 0.05). The use of sliding scale was prevalent (79.3%) across the ICUs (p = 0.002). 31.5% of the patients had received different glycaemic control methods, 11.8% were in the targeted blood glucose level. Sliding scale was the method used by doctors and nurses (71.4% and 81.6% respectively). Lack of awareness about hyperglycaemia management methods was prevalent among ICU healthcare staff. Use of obsolete methods was the common practice in the ICUS of the Military Hospital. Target blood glucose for patients were unmet. Development of a local protocol for glycaemic control in all ICUs is needed along with sustained training programs on hyperglycaemia control for ICU healthcare staff.

Optimal Blood Glucose Monitoring Interval for Insulin Infusion in Critically Ill Non-Cardiothoracic Patients: A Pilot Study

Objective:

The American Diabetes Association and the Society of Critical Care Medicine recommend monitoring blood glucose (BG) every 1-2 hours in patients receiving insulin infusion to guide titration of insulin infusion to maintain serum glucose in the target range; however, this is based on weak evidence. We evaluated the compliance of hourly BG monitoring and relation of less frequent BG monitoring to glycemic status.

Materials and Methods:

Retrospective chart review performed on 56 consecutive adult patients who received intravenous insulin infusion for persistent hyperglycemia in the ICU at Saint Vincent Hospital, a tertiary care community hospital an urban setting in Northeast region of USA. The frequency of fingerstick blood glucose (FSBG) readings was reviewed for compliance with hourly FSBG monitoring per protocol and the impact of FSBG testing at different time intervals on the glycemic status. Depending on time interval of FSBG monitoring, the data was divided into three groups: Group A (<90 min), Group B (91-179 min) and Group C (≥180 min).

Results:

The mean age was 69 years (48% were males), 77% patients had preexisting type 2 diabetes mellitus (T2DM). The mean MPM II score was 41. Of the 1411 readings for BG monitoring on insulin infusion, 467 (33%) were in group A, 806 (57%) in group B and 138 (10%) in group C; hourly BG monitoring compliance was 12.6%. The overall glycemic status was similar among all groups. There were 14 (0.99%) hypoglycemic episodes observed. The rate of hypoglycemic episodes was similar in all three groups (p=0.55).

Conclusion:

In patients requiring insulin infusion for sustained hyperglycemia in ICU, the risk of hypoglycemic episodes was not significantly different with less frequent BG monitoring. The compliance to hourly blood glucose monitoring and ICU was variable, and hypoglycemic episodes were similar across the groups despite the variation in monitoring.

Significance of the Study:

The importance of glycemic control in ICU has been well established and it is a resource intensive venture. However, there are no major studies highlighting the most optimal time interval for blood glucose checks in critically ill patients on insulin infusion. With this study we hypothesize that time duration between blood glucose checks can be increased safely without any untoward effects. Our study provides evidence for effective resource management with reducing the time spent with every glucose check and directly translating into high value care.

Practice of Hyperglycaemia Control in Intensive Care Units of the Military Hospital, Sudan – Needs of a Protocol.. [DOI: 10.1101/2020.08.17.20176453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Hyperglycaemia is a major risk factor in critically ill patients as it leads to adverse outcomes and mortality in diabetic and non-diabetic patients. The target blood glucose remained controversial; this study aimed to contribute in assessing the practice of hyperglycaemia control in intensive care units of Khartoum Military Hospital. Furthermore, it proposed a protocol for hyperglycaemia control based on findings. A hospital-based cross-sectional study assessed the awareness and practice towards hyperglycaemia management in a sample of 83 healthcare staff selected through stratified random sampling technique. In addition, 55 patients were enrolled, through quota sampling, after excluding those with diabetic ketoacidosis, hyperosmolar-hyperglycaemic state and patients < 18 years. A self-administrated questionnaire enabled to collect data from healthcare staff, patients data were extracted from medical records. SPSS 23 was used to analyse the collected data. Chi-square and ANOVA tests assessed the association among variables. All statistical tests were considered statistically significant when p < 0.05. The training on hyperglycaemia control differed statistically (p = 0.017) among healthcare staff. The target glycaemic level (140-180 mg/dl) was knew by 11.1% of the study participants. Neither the knowledge nor the practice of hyperglycaemia control methods differed among staff (p> 0.05). The use of sliding scale was 79.3% across the ICUs with a statistically significant difference (p = 0.002). 31.5% of patients had received glycaemic control based on different methods and 11.8% were in the targeted blood glucose level. Sliding scale was the prevalent method used by doctors (71.4%) and nurses (81.6%). A patient benefited from insulin infusion method, which achieved the NICE-SUGAR target. The poor knowledge and lack of awareness towards hyperglycaemia monitoring led to inappropriate implementation of glycaemia control methods across the Military Hospital ICUs. Sustained training programs on hyperglycaemia control to ICU staff and the availability of a protocol on glycaemia control are highly required.

Issues for the management of people with diabetes and COVID-19 in ICU

In the pandemic “Corona Virus Disease 2019” (COVID-19) people with diabetes have a high risk to require ICU admission. The management of diabetes in Intensive Care Unit is always challenging, however, when diabetes is present in COVID-19 the situation seems even more complicated. An optimal glycemic control, avoiding acute hyperglycemia, hypoglycemia and glycemic variability may significantly improve the outcome. In this case, intravenous insulin infusion with continuous glucose monitoring should be the choice. No evidence suggests stopping angiotensin-converting-enzyme inhibitors, angiotensin-renin-blockers or statins, even it has been suggested that they may increase the expression of Angiotensin-Converting-Enzyme-2 (ACE2) receptor, which is used by “Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to penetrate into the cells. A real issue is the usefulness of several biomarkers, which have been suggested to be measured during the COVID-19. N-Terminal-pro-Brain Natriuretic-Peptide, D-dimer and hs-Troponin are often increased in diabetes. Their meaning in the case of diabetes and COVID-19 should be therefore very carefully evaluated. Even though we understand that in such a critical situation some of these requests are not so easy to implement, we believe that the best possible action to prevent a worse outcome is essential in any medical act.

Issues of Cardiovascular Risk Management in People With Diabetes in the COVID-19 Era

People with diabetes compared with people without exhibit worse prognosis if affected by coronavirus disease 2019 (COVID-19) induced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), particularly when compromising metabolic control and concomitant cardiovascular disorders are present. This Perspective seeks to explore newly occurring cardio-renal-pulmonary organ damage induced or aggravated by the disease process of COVID-19 and its implications for the cardiovascular risk management of people with diabetes, especially taking into account potential interactions with mechanisms of cellular intrusion of SARS-CoV-2. Severe infection with SARS-CoV-2 can precipitate myocardial infarction, myocarditis, heart failure, and arrhythmias as well as an acute respiratory distress syndrome and renal failure. They may evolve along with multiorgan failure directly due to SARS-CoV-2-infected endothelial cells and resulting endotheliitis. This complex pathology may bear challenges for the use of most diabetes medications in terms of emerging contraindications that need close monitoring of all people with diabetes diagnosed with SARS-CoV-2 infection. Whenever possible, continuous glucose monitoring should be implemented to ensure stable metabolic compensation. Patients in the intensive care unit requiring therapy for glycemic control should be handled solely by intravenous insulin using exact dosing with a perfusion device. Although not only ACE inhibitors and angiotensin 2 receptor blockers but also SGLT2 inhibitors, GLP-1 receptor agonists, pioglitazone, and probably insulin seem to increase the number of ACE2 receptors on the cells utilized by SARS-CoV-2 for penetration, no evidence presently exists that shows this might be harmful in terms of acquiring or worsening COVID-19. In conclusion, COVID-19 and related cardio-renal-pulmonary damage can profoundly affect cardiovascular risk management of people with diabetes.

Sliding scale insulin for non-critically ill hospitalised adults with diabetes mellitus

BACKGROUND

Diabetes mellitus is a metabolic disorder resulting from a defect in insulin secretion, function, or both. Hyperglycaemia in non-critically ill hospitalised people is associated with poor clinical outcomes (infections, prolonged hospital stay, poor wound healing, higher morbidity and mortality). In the hospital setting people diagnosed with diabetes receive insulin therapy as part of their treatment in order to achieve metabolic control. However, insulin therapy can be provided by different strategies (sliding scale insulin (SSI), basal-bolus insulin, and other modalities). Sliding scale insulin is currently the most commonly used method, however there is uncertainty about which strategy provides the best patient outcomes.

OBJECTIVES

To assess the effects of SSI for non-critically ill hospitalised adults with diabetes mellitus.

SEARCH METHODS

We identified eligible trials by searching MEDLINE, Embase, LILACS, and the Cochrane Library. We searched the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov trial registers. The date of the last search for all databases was December 2017. We also examined reference lists of identified randomised controlled trials (RCTs) and systematic reviews, and contacted trial authors.

SELECTION CRITERIA

We included RCTs comparing SSI with other strategies for glycaemic control in non-critically ill hospitalised adult participants of any sex with diabetes mellitus.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data, assessed trials for risk of bias, and evaluated the overall certainty of evidence utilising the GRADE instrument. We synthesised data using a random-effects model meta-analysis with 95% prediction intervals, if possible, or descriptive analysis, as appropriate.

MAIN RESULTS

Of 720 records screened, we included eight trials that randomised 1048 participants with type 2 diabetes (387 SSI participants and 615 participants in comparator groups were available for final analysis). We included non-critically ill medical and surgical adults with the diagnosis of diabetes mellitus. The mean follow-up time was measured by the mean length of hospital stay and ranged between five and 24 days. The mean age of participants was 44.5 years to 71 years.Overall, we judged the risk of bias on the trial level as unclear for selection bias, high for outcome-related performance and detection bias with regard to hypoglycaemic episodes, other adverse events, and mean glucose levels, and low for all-cause mortality and length of hospital stay. Attrition bias was low for all outcome measures.Six trials compared SSI with a basal-bolus insulin scheme, three of which investigating 64% of all participants in this category also applying an SSI approach in the bolus comparator part. One trial had a basal insulin-only comparator arm, and the remaining trial used continuous insulin infusion as the comparator. For our main comparison of SSI versus basal-bolus insulin, the results were as follows. Four trials reported mortality data. One out of 268 participants in the SSI group (0.3%) compared with two out of 334 participants in the basal-bolus group (0.6%) died (low-certainty evidence). Severe hypoglycaemic episodes, defined as blood glucose levels below 40 mg/dL (2.2 mmol/L), showed a risk ratio (RR) of 0.22, 95% confidence interval (CI) 0.05 to 1.00; P = 0.05; 5 trials; 667 participants; very low-certainty evidence. The 95% prediction interval ranged between 0.02 and 2.57. All nine severe hypoglycaemic episodes were observed among the 369 participants on basal-bolus insulin (2.4%). The mean length of hospital stay was 0.5 days longer for the SSI group, 95% CI -0.5 to 1.4; P = 0.32; 6 trials; 717 participants; very low-certainty evidence. The 95% prediction interval ranged between -1.7 days and 2.7 days. Adverse events other than hypoglycaemic episodes, such as postoperative infections, showed a RR of 1.16, 95% CI 0.25 to 5.37; P = 0.85; 3 trials; 481 participants; very low-certainty evidence. The mean blood glucose levels ranged across basal-bolus groups from 156 mg/dL (8.7 mmol/L) to 221 mg/dL (12.3 mmol/L). The mean blood glucose level in the SSI groups was 14.8 mg/dL (0.8 mmol/L) higher (95% CI 7.8 (0.4) to 21.8 (1.2); P < 0.001; 6 trials; 717 participants; low-certainty evidence). The 95% prediction interval ranged between -3.6 mg/dL (-0.2 mmol/L) and 33.2 mg/dL (1.8 mmol/L). No trial reported on diabetes-related mortality or socioeconomic effects.

AUTHORS' CONCLUSIONS

We are uncertain which insulin strategy (SSI or basal-bolus insulin) is best for non-critically hospitalised adults with diabetes mellitus. A basal-bolus insulin strategy in these patients might result in better short-term glycaemic control but could increase the risk for severe hypoglycaemic episodes. The certainty of the body of evidence comparing SSI with basal-bolus insulin was low to very low and needs to be improved by adequately performed, well-powered RCTs in different hospital environments with well-educated medical staff using identical short-acting insulins in both intervention and comparator arms to compare the rigid SSI approach with flexible insulin application strategies.

Insulin infusion therapy in critically ill patients

While dysglycemia (hyperglycemia, hypoglycemia and glucose variability) is clearly associated with increased mortality in critically ill patients, target range of blood glucose control remains controversial. Standardized insulin infusion protocols constitute the basis of treatment of these patients. The choice of protocol and its implementation is a great challenge. In this article, we review the published data to help define the essential elements that compose a good protocol and apply the right conditions to make it safe and effective.

Insulin infusion therapy in critical care patients: regular insulin vs short-acting insulin. A prospective, crossover, randomized, multicenter blind study

INTRODUCTION

The aim of this multicenter, prospective, randomized, crossover trial is to compare, in critical care patients receiving insulin infusion therapy (IIT), the pharmacodynamic of Humulin insulin (Hlin), currently used as "standard of care," and Humalog insulin (Hlog), a shorter acting insulin formulation. This was measured as extent and duration of the carryover effect of insulin treatment, with the latter calculated as ratio between blood glucose concentration (BGC) reduction during and after IIT.

MATERIALS AND METHODS

Twenty-eight patients treated in an intensive care unit and receiving full nutritional support were randomly assigned to Hlin or Hlog as first treatment. Insulin was infused at a constant rate in patients presenting with BGC greater than or equal to 180 mg/dL (0.04 U/kg per hour) and was discontinued when BGC was less than or equal to 140 mg/dL (therapeutic BGC drop). Further reductions in BGC after discontinuation of insulin infusion were recorded (postinfusional BGC drop). During the study period, whole blood BGC was measured every 30 minutes. A minimal 6-hour washout interval was maintained between treatments with the 2 types of insulin. The primary end point was the extent (calculated as ratio between the therapeutic BGC drop and the postinfusional BGC drop) and duration of the carryover effect.

RESULTS

Treatment with Hlog, as compared with Hlin, was associated with a less profound carryover effect as well as a briefer duration of carryover (median, 0.40 vs 0.62; P < .001; median, 1 vs 1.5 hours; P < .001).

CONCLUSIONS

The use of constant Hlog infusion for IIT, when compared with Hlin at the same dose, is associated with a less profound carryover effect on BGC after discontinuation of IIT, a briefer duration of carryover, a faster BGC drop during infusion, and a quicker BGC rise after discontinuation. These characteristics suggest that Hlog IIT may be preferable for use in critically ill patients.

Clinical impact of sample interference on intensive insulin therapy in severely burned patients: a pilot study

Severely burned patients benefit from intensive insulin therapy (IIT) for tight glycemic control (TGC). The authors evaluated the clinical impact of automatic correction of hematocrit and ascorbic acid interference for bedside glucose monitoring performance in critically ill burn patients. The performance of two point-of-care glucose monitoring systems (GMSs): 1) GMS1, an autocorrecting device, and 2) GMS2, a noncorrecting device were compared. Sixty remnant arterial blood samples were collected in a prospective observational study to evaluate hematocrit and ascorbic acid effects on GMS1 vs GMS2 accuracy paired against a plasma glucose reference. Next, we enrolled 12 patients in a pilot randomized controlled trial. Patients were randomized 1:1 to receive IIT targeting a TGC interval of 111 to 151 mg/dl and guided by either GMS1 or GMS2. GMS bias, mean insulin rate, and glycemic variability were calculated. In the prospective study, GMS1 results were similar to plasma glucose results (mean bias, -0.75 [4.0] mg/dl; n = 60; P = .214). GMS2 results significantly differed from paired plasma glucose results (mean bias, -5.66 [18.7] mg/dl; n = 60; P = .048). Ascorbic acid therapy elicited significant GMS2 performance bias (29.2 [27.2]; P < .001). Randomized controlled trial results reported lower mean bias (P < .001), glycemic variability (P < .05), mean insulin rate (P < .001), and frequency of hypoglycemia (P < .001) in the GMS1 group than in the GMS2 group. Anemia and high-dose ascorbic acid therapy negatively impact GMS accuracy and TGC in burn patients. Automatic correction of confounding factors improves glycemic control. Further studies are warranted to determine outcomes associated with accurate glucose monitoring during IIT.

Reducing the risk of hypoglycemia associated with intravenous insulin: experience with a computerized insulin infusion program in 4 adult intensive care units

Computerized insulin infusion protocols have facilitated more effective blood glucose (BG) control in intensive care units (ICUs). This is particularly important in light of the risks associated with hypoglycemia. End stage renal disease (ESRD) increases the risk of insulin-induced hypoglycemia. We evaluated BG control in 210 patients in 2 medical ICUs and in 2 surgical ICUs who were treated with a computerized insulin infusion program (CIIP). Our CIIP was programmed for a BG target of 140-180 mg/dL for medical ICU patients or 120-160 mg/dL for surgical ICU patients. In addition, we focused on BG control in the 11% of our patients with ESRD. Mean BG was 147 ± 20 mg/dL for surgical ICU patients and 171 ± 26 mg/dL for medical ICU patients. Of both surgical and medical ICU patients, 17% had 1 or more BG 60-79 mg/dL, while 3% of surgical ICU and 8% of medical ICU patients had 1 or more BG < 60 mg/dL. Mean BG in ESRD patients was 147 ± 16 mg/dL similar to 152 ± 23 mg/dL in patients without ESRD. Of ESRD patients, 41% had 1 or more BG < 79 mg/dL as compared with 17.8% of non-ESRD patients (P < .01). A higher BG target for medical ICU patients as compared with surgical ICU patients yielded comparably low rates of moderate or severe hypoglycemia. However, hypoglycemia among ESRD patients was more common compared to non-ESRD patients, suggesting a need for a higher BG target specific to ESRD patients.

Hyperglycemia in critical illness

Evidence that acute injury and critical illness can result in an elevation of blood glucose levels is not a new concept. However, the last decade has seen a rise in publications describing the potential harm of this unique form of hyperglycemia and the subsequent benefits of glucose control. More recently, the untoward effects of tightly controlling glucose concentrations in this setting have been more thoroughly elucidated. This has lead to a challenging clinical conundrum for practitioners both inside and outside of the intensive care unit. The latest guidelines attempt to shed light on this dilemma and provide guidance for practitioners. This article reviews the progression of the research, the multiple guidelines that have been published, and the clinical implications on the treatment of critical illness hyperglycemia, with particular focus on the emergency department.

Diabetes and hyperglycemia in the critical care setting: has the evidence for glycemic control vanished? (Or … is going away?)

Hyperglycemia is associated with increased mortality and other complications amongst hospitalized patients. However, the studies of tight glycemic control in a range of critical illness settings, including intensive care, acute myocardial infarction, and stroke, have produced inconsistent and divergent results. We examine some of the factors that may have contributed to the differing results, and their implications for targeting tight glucose control in critical illness. With these in mind, most clinical guidelines now recommend moderate glucose control with an upper glucose target of <10 mmol/L (180 mg/dL) in critical illness while avoiding hypoglycemia.

Impact of glucose measurement processing delays on clinical accuracy and relevance

BACKGROUND

In a hospital setting, glucose is often measured from venous blood in the clinical laboratory. However, laboratory glucose measurements are typically not available in real time. In practice, turn-around times for laboratory measurements can be minutes to hours. This analysis assesses the impact of turn-around time on the effective clinical accuracy of laboratory measurements.

METHODS

Data obtained from an earlier study with 58 subjects with type 1 diabetes mellitus (T1DM) were used for this analysis. In the study, glucose measurements using a YSI glucose analyzer were obtained from venous blood samples every 15 min while the subjects were at the health care facility. To simulate delayed laboratory results, each YSI glucose value from a subject was paired with one from a later time point (from the same subject) separated by 15, 30, 45, and 60 min. To assess the clinical accuracy of a delayed YSI result relative to a real-time result, the percentage of YSI pairs that meet the International Organization for Standardization (ISO) 15197:2003(E) standard for glucose measurement accuracy (±15 mg/dl for blood glucose < 75 mg/dl, ±20% for blood glucose ≥ 75 mg/dl) was calculated.

RESULTS

It was observed that delays of 15 min or more reduce clinical accuracy below the ISO 15197:2003(E) recommendation of 95%. The accuracy was less than 65% for delays of 60 min.

CONCLUSION

This analysis suggests that processing delays in glucose measurements reduce the clinical relevance of results in patients with T1DM and may similarly degrade the clinical value of measurements in other patient populations.

Real-time continuous glucose monitoring shows high accuracy within 6 hours after sensor calibration: a prospective study

Accurate and timely glucose monitoring is essential in intensive care units. Real-time continuous glucose monitoring system (CGMS) has been advocated for many years to improve glycemic management in critically ill patients. In order to determine the effect of calibration time on the accuracy of CGMS, real-time subcutaneous CGMS was used in 18 critically ill patients. CGMS sensor was calibrated with blood glucose measurements by blood gas/glucose analyzer every 12 hours. Venous blood was sampled every 2 to 4 hours, and glucose concentration was measured by standard central laboratory device (CLD) and by blood gas/glucose analyzer. With CLD measurement as reference, relative absolute difference (mean±SD) in CGMS and blood gas/glucose analyzer were 14.4%±12.2% and 6.5%±6.2%, respectively. The percentage of matched points in Clarke error grid zone A was 74.8% in CGMS, and 98.4% in blood gas/glucose analyzer. The relative absolute difference of CGMS obtained within 6 hours after sensor calibration (8.8%±7.2%) was significantly less than that between 6 to 12 hours after calibration (20.1%±13.5%, p<0.0001). The percentage of matched points in Clarke error grid zone A was also significantly higher in data sets within 6 hours after calibration (92.4% versus 57.1%, p<0.0001). In conclusion, real-time subcutaneous CGMS is accurate in glucose monitoring in critically ill patients. CGMS sensor should be calibrated less than 6 hours, no matter what time interval recommended by manufacturer.

Blood glucose measurement in the intensive care unit: what is the best method?

Abnormal glucose measurements are common among intensive care unit (ICU) patients for numerous reasons and hypoglycemia is especially dangerous because these patients are often sedated and unable to relate the associated symptoms. Additionally, wide swings in blood glucose have been closely tied to increased mortality. Therefore, accurate and timely glucose measurement in this population is critical. Clinicians have several choices available to assess blood glucose values in the ICU, including central laboratory devices, blood gas analyzers, and point-of-care meters. In this review, the method of glucose measurement will be reviewed for each device, and the important characteristics, including accuracy, cost, speed of result, and sample volume, will be reviewed, specifically as these are used in the ICU environment. Following evaluation of the individual measurement devices and after considering the many features of each, recommendations are made for optimal ICU glucose determination.

Declining in-hospital mortality in patients undergoing coronary bypass surgery in the United States irrespective of presence of type 2 diabetes or congestive heart failure

BACKGROUND

Significant advances in surgical techniques and postsurgical care have been made in the last 10 years. The goal of this study was to evaluate any decline in the age-adjusted in-hospital mortality rate of patients undergoing coronary artery bypass grafting (CABG) using a national database from 1989 to 2004 in the United States.

HYPOTHESIS

Reduction in CABG related mortality in recent years.

METHODS

Using the Nationwide Inpatient Sample (NIS) database, we obtained specific ICD-9-CM codes forCABG to compile the data. To exclude nonatherosclerotic cause of coronary disease, we studied only patients older than 40 years. We calculated total and age-adjusted mortality rate per 100,000 for this period.

RESULTS

The NIS database contained 1 145 285 patients who had CABG performed from 1988 to 2004. The mean age for these patients was 71.05 ± 9.20 years. From 1989, the age-adjusted rate for all CABG-related mortality has been decreasing steadily and reached the lowest level in 2004: 300.3 per 100 000 in 1989, (95%confidence interval [CI], 20.4-575.9) and 104.69 per 100 000 (95% CI, 22.6-186.7) in 2004. Total death also declined from 5.5% to 3.06%. This decline occurred irrespective of comorbidities such as congestive heart failure, diabetes, or acute myocardial infarction, albeit increasing the number of CABG procedures performed in high-risk patients.

CONCLUSIONS

The age-adjusted in-hospital mortality rate from CABG has been declining steadily and reached its lowest level in 2004, irrespective of comorbidities. This decline most likely reflects advances in surgical techniques and the use of evidence-based medicine in patients undergoing CABG.

Glycemia management in critical care patients

Over the last decade, the approach to clinical management of blood glucose concentration (BGC) in critical care patients has dramatically changed. In this editorial, the risks related to hypo, hyperglycemia and high BGC variability, optimal BGC target range and BGC monitoring devices for patients in the intensive care unit (ICU) will be discussed. Hypoglycemia has an increased risk of death, even after the occurrence of a single episode of mild hypoglycemia (BGC < 80 mg/dL), and it is also associated with an increase in the ICU length of stay, the major determinant of ICU costs. Hyperglycemia (with a threshold value of 180 mg/dL) is associated with an increased risk of death, longer length of stay and higher infective morbidity in ICU patients. In ICU patients, insulin infusion aimed at maintaining BGC within a 140-180 mg/dL target range (NICE-SUGAR protocol) is considered to be the state-of-the-art. Recent evidence suggests that a lower BGC target range (129-145 mg/dL) is safe and associated with lower mortality. In trauma patients without traumatic brain injury, tight BGC (target < 110 mg/dL) might be associated with lower mortality. Safe BGC targeting and estimation of optimal insulin dose titration should include an adequate nutrition protocol, the length of insulin infusion and the change in insulin sensitivity over time. Continuous glucose monitoring devices that provide accurate measurement can contribute to minimizing the risk of hypoglycemia and improve insulin titration. In conclusion, in ICU patients, safe and effective glycemia management is based on accurate glycemia monitoring and achievement of the optimal BGC target range by using insulin titration, along with an adequate nutritional protocol.

A novel computerized fading memory algorithm for glycemic control in postoperative surgical patients

BACKGROUND

Hyperglycemia is commonly encountered in critically ill patients and is associated with increased mortality and morbidity. To better control blood glucose levels, we previously developed a new computerized fading memory (FM) algorithm. In this study we evaluated the safety and efficacy of this algorithm in surgical intensive care unit (SICU) patients and compared its performance against the existing insulin-infusion algorithm (named VA algorithm) used in our institution.

METHODS

A computer program was developed to run the FM and VA algorithms. Forty eight patients, who were scheduled to have elective surgery, were randomly assigned to receive insulin infusion on the basis of either the FM or VA algorithm. On SICU admission, an insulin infusion was either continued from the operating room or initiated when the glucose level exceeded the target level of 140 mg/dL. Hourly blood glucose measurements were performed and entered into the computer program, which then prescribed the next insulin dose. The randomly assigned algorithm was applied for the first 8 hours of SICU stay, after which the VA algorithm was used. The number of episodes of hypoglycemia (glucose <60 mg/dL) and excessive hyperglycemia (>300 mg/dL) were noted. Additionally, the time required to bring the glucose level within target range (140 ± 20 mg/dL), the number of glucose measurements within the target range, glycemic variability, and insulin usage were analyzed and compared between the 2 algorithms.

RESULTS

Patient demographics and starting glucose levels were similar between the groups. With the existing VA algorithm, 1 episode of severe hypoglycemia was observed. Three patients did not reach the target range within 8 hours. With the FM algorithm no hypoglycemia occurred, and all patients achieved the target range within 8 hours. Glycemic variability measured by the SD of mean glucose levels was 28% (95% confidence interval, 14% to 39%) lower for the FM algorithm (P < 0.001). The FM algorithm used 1.1 U/h less insulin than did the VA algorithm (P = 0.043).

CONCLUSION

The novel computerized FM algorithm for glycemic control, which emulates physiologic biphasic insulin secretion, managed glucose better than the existing algorithm without any episodes of hypoglycemia. The FM algorithm had less glycemic variability and used less insulin when compared to the conventional clinical algorithm.