A systematic review on quality indicators for tight glycaemic control in critically ill patients: need for an unambiguous indicator reference subset

Risk and reward: extending stochastic glycaemic control intervals to reduce workload

Background

STAR is a model-based, personalised, risk-based dosing approach for glycaemic control (GC) in critically ill patients. STAR provides safe, effective control to nearly all patients, using 1–3 hourly measurement and intervention intervals. However, the average 11–12 measurements per day required can be a clinical burden in many intensive care units. This study aims to significantly reduce workload by extending STAR 1–3 hourly intervals to 1 to 4-, 5-, and 6-hourly intervals, and evaluate the impact of these longer intervals on GC safety and efficacy, using validated in silico virtual patients and trials methods. A Standard STAR approach was used which allowed more hyperglycaemia over extended intervals, and a STAR Upper Limit Controlled approach limited nutrition to mitigate hyperglycaemia over longer intervention intervals.

Results

Extending STAR from 1–3 hourly to 1–6 hourly provided high safety and efficacy for nearly all patients in both approaches. For STAR Standard, virtual trial results showed lower % blood glucose (BG) in the safe 4.4–8.0 mmol/L target band (from 83 to 80%) as treatment intervals increased. Longer intervals resulted in increased risks of hyper- (15% to 18% BG > 8.0 mmol/L) and hypo- (2.1% to 2.8% of patients with min. BG < 2.2 mmol/L) glycaemia. These results were achieved with slightly reduced insulin (3.2 [2.0 5.0] to 2.5 [1.5 3.0] U/h) and nutrition (100 [85 100] to 90 [75 100] % goal feed) rates, but most importantly, with significantly reduced workload (12 to 8 measurements per day). The STAR Upper Limit Controlled approach mitigated hyperglycaemia and had lower insulin and significantly lower nutrition administration rates.

Conclusions

The modest increased risk of hyper- and hypo-glycaemia, and the reduction in nutrition delivery associated with longer treatment intervals represent a significant risk and reward trade-off in GC. However, STAR still provided highly safe, effective control for nearly all patients regardless of treatment intervals and approach, showing this unique risk-based dosing approach, modulating both insulin and nutrition, to be robust in its design. Clinical pilot trials using STAR with different measurement timeframes should be undertaken to confirm these results clinically.

The association between long-term glycaemic control, glycaemic gap and neurological outcome of in-hospital cardiac arrest in diabetics: A retrospective cohort study

AIM

Resuscitation guidelines do not recommend a target blood glucose (BG) level specifically tailored for diabetics experiencing an in-hospital cardiac arrest (IHCA). The glycosylated haemoglobin (HbA1c) level may be associated with neurological prognosis and used to identify the optimal BG level for diabetic IHCA patients.

METHODS

This study was a retrospective study in a single medical centre. Patients with an IHCA between 2006 and 2015 were screened. The estimated average glucose (eAG) level was converted from the HbA1c level measured within three months prior to the IHCA. The minimum glycaemic gap was calculated from the post-resuscitation minimum BG level minus the eAG level.

RESULTS

A total of 141 patients were included in this study. The mean HbA1c was 7.2% (corresponding eAG: 160.2 mg/dL [8.9 mmol/L]). Multivariable logistic regression analysis indicated an eAG level of less than 196 mg/dL (10.9 mmol/L; corresponding HbA1c: 8.5%) was positively associated with a favourable neurological outcome at hospital discharge (odds ratio [OR]: 5.12, 95% confidence interval [CI]: 1.11-23.70; p-value = 0.04). An absolute minimum glycaemic gap of less than 70 mg/dL (3.9 mmol/L) was also positively associated with a favourable neurological outcome (OR: 5.41, 95% CI: 1.41-20.78; p-value = 0.01).

CONCLUSION

For diabetic patients, poor long-term glycaemic control correlated with worse neurological recovery following an IHCA. The HbA1c-derived average BG level could be used as a reference point for glycaemic management during the early stage of post-cardiac arrest syndrome. The glycaemic gap could be used to identify the optimal glycaemic range around the reference point.

Improving glycemic control in critically ill patients: personalized care to mimic the endocrine pancreas

There is considerable physiological and clinical evidence of harm and increased risk of death associated with dysglycemia in critical care. However, glycemic control (GC) currently leads to increased hypoglycemia, independently associated with a greater risk of death. Indeed, recent evidence suggests GC is difficult to safely and effectively achieve for all patients. In this review, leading experts in the field discuss this evidence and relevant data in diabetology, including the artificial pancreas, and suggest how safe, effective GC can be achieved in critically ill patients in ways seeking to mimic normal islet cell function. The review is structured around the specific clinical hurdles of: understanding the patient’s metabolic state; designing GC to fit clinical practice, safety, efficacy, and workload; and the need for standardized metrics. These aspects are addressed by reviewing relevant recent advances in science and technology. Finally, we provide a set of concise recommendations to advance the safety, quality, consistency, and clinical uptake of GC in critical care. This review thus presents a roadmap toward better, more personalized metabolic care and improved patient outcomes.

A systematic scoping review on the consequences of stress-related hyperglycaemia

Background

Stress-related hyperglycaemia (SHG) is commonly seen in acutely ill patients and has been associated with poor outcomes in many studies performed in different acute care settings. We aimed to review the available evidence describing the associations between SHG and different outcomes in acutely ill patients admitted to an ICU. Study designs, populations, and outcome measures used in observational studies were analysed.

Methods

We conducted a systematic scoping review of observational studies following the Joanna Briggs methodology. Medline, Embase, and the Cochrane Library were searched for publications between January 2000 and December 2015 that reported on SHG and mortality, infection rate, length of stay, time on ventilation, blood transfusions, renal replacement therapy, or acquired weakness.

Results

The search yielded 3,063 articles, of which 43 articles were included (totalling 536,476 patients). Overall, the identified studies were heterogeneous in study conduct, SHG definition, blood glucose measurements and monitoring, treatment protocol, and outcome reporting. The most frequently reported outcomes were mortality (38 studies), ICU and hospital length of stay (23 and 18 studies, respectively), and duration of mechanical ventilation (13 studies). The majority of these studies (40 studies) compared the reported outcomes in patients who experienced SHG with those who did not. Fourteen studies (35.9%) identified an association between hyperglycaemia and increased mortality (odds ratios ranging from 1.13 to 2.76). Five studies identified hyperglycaemia as an independent risk factor for increased infection rates, and one identified it as an independent predictor of increased ICU length of stay.

Discussion

SHG was consistently associated with poor outcomes. However, the wide divergences in the literature mandate standardisation of measuring and monitoring SHG and the creation of a consensus on SHG definition. A better comparability between practices will improve our knowledge on SHG consequences and management.

[Metabolic control in the critically ill patient an update: hyperglycemia, glucose variability hypoglycemia and relative hypoglycemia]

BACKGROUND

Metabolic changes of glucose in critically ill patients increase morbidity and mortality. The appropriate level of blood glucose has not been established so far and should be adjusted for different populations. However concepts such as glucose variability and relative hypoglycemia of critically ill patients are concepts that are changing management methods and achieving closer monitoring.

OBJECTIVES

The purpose of this review is to present new data about the management and metabolic control of patients in critical areas.

CONCLUSIONS

Currently glucose can no longer be regarded as an innocent element in critical patients; both hyperglycemia and hypoglycemia increase morbidity and mortality of patients. Protocols and better instruments for continuous measurement are necessary to achieve the metabolic control of our patients.

Glucose Control in the ICU: A Continuing Story

In the present era of near-continuous glucose monitoring (CGM) and automated therapeutic closed-loop systems, measures of accuracy and of quality of glucose control need to be standardized for licensing authorities and to enable comparisons across studies and devices. Adequately powered, good quality, randomized, controlled studies are needed to assess the impact of different CGM devices on the quality of glucose control, workload, and costs. The additional effects of continuing glucose control on the general floor after the ICU stay also need to be investigated. Current algorithms need to be adapted and validated for CGM, including effects on glucose variability and workload. Improved collaboration within the industry needs to be encouraged because no single company produces all the necessary components for an automated closed-loop system. Combining glucose measurement with measurement of other variables in 1 sensor may help make this approach more financially viable.

Associations between blood glucose level and outcomes of adult in-hospital cardiac arrest: a retrospective cohort study

BACKGROUND

We intended to analyse the associations between blood glucose (BG) level and clinical outcomes of in-hospital cardiac arrest (IHCA).

METHODS

We conducted a retrospective observational study in a single medical centre and evaluated patients who experienced IHCA between 2006 and 2014. We used multivariable logistic regression analysis to study associations between independent variables and outcomes. We calculated the mean BG level for each patient by averaging the maximum and minimum BG levels in the first 24 h after arrest, and we used mean BG level for our final analysis.

RESULTS

We included a total of 402 patients. Of these, 157 patients (39.1 %) had diabetes mellitus (DM). The average mean BG level was 209.9 mg/dL (11.7 mmol/L). For DM patients, a mean BG level between 183 and 307 mg/dL (10.2-17.1 mmol/L) was significantly associated with favourable neurological outcome (odds ratio [OR] 2.71, 95 % confidence interval [CI] 1.18-6.20; p value = 0.02); a mean BG level between 147 and 317 mg/dL (8.2-17.6 mmol/L) was significantly associated with survival to hospital discharge (OR 2.38, 95 % CI 1.26-4.53; p value = 0.008). For non-DM patients, a mean BG level between 143 and 268 mg/dL (7.9-14.9 mmol/L) was significantly associated with survival to hospital discharge (OR 2.93, 95 % CI 1.62-5.40; p value < 0.001).

CONCLUSIONS

Mean BG level in the first 24 h after cardiac arrest was associated with neurological outcome for IHCA patients with DM. For neurological and survival outcomes, the optimal BG range may be higher for patients with DM than for patients without DM.

Study of a structured action pathway and persistent monitoring tool among nurses to achieve cent percent management of hypoglycaemia in in-patients: A measure of quality of healthcare

BACKGROUND

Reporting and management of hypoglycaemia is a reflection of quality of healthcare delivery. The study evaluates success of a structured plan implemented in a tertiary care hospital in terms of an evidence-based hypoglycaemia management protocol, training and awareness among all nurses in the organisation to achieve 100% reporting of hypoglycaemia.

METHODS

A prospective study was conducted over a 3-year period. An in-house hypoglycaemia management protocol was designed, included in the induction training programme of nurses and implemented in wards under the guidance of master trainers. Each episode of hypoglycaemia was reported, managed and logged into centralised database, Quality Flash Matrix (QF). The QF was analysed at end of each 24 h cycle to carry out a root cause analyses and appropriate correction in training modules. Data were extracted from hospital records, patient case records and QF in terms of total number of cases receiving insulin and total number of episodes of hypoglycaemia documented and reported.

RESULTS

Incidence of hypoglycaemia recorded was 6.4, 5.3 and 4.7 per 1000 patient hours for the years 2011, 2012 and 2013, respectively. The percentage of episodes of hypoglycaemia reported improved from 78% (1st quarter 2011) to 100% (4th quarter 2012). Root cause analysis showed change in diet of patient with no corresponding change in insulin and vice versa being the commonest cause for hypoglycaemia consistent over the study period.

CONCLUSION

Constant structured training of nurses, constant surveillance and appropriate feedback analysis result in decreased incidence of hypoglycaemia and increased reporting of episodes of hypoglycaemia.

Reporting on Glucose Control Metrics in the Intensive Care Unit

The 'diabetes of injury' typically associated with critical illness has recently been thoroughly revisited and much better characterised following major therapeutic advances. The occurrence of severe hyperglycaemia, moderate hypoglycaemia or high glycaemic variability has been associated with an increased mortality and rate of complications in large independent cohorts of acutely ill patients. Hence, current guidelines advocate the prevention and avoidance of each of these three dysglycaemic domains, and the use of a common metrics for a quantitative description of dysglycaemic events, such as the proportion of time spent in the target glycaemic range as a unifying variable. Using a common language will help to face the future challenges, including the definition of the most appropriate blood glucose (BG) target according to the category of admission, the time interval from the initial injury and the medical history. The clinical testing of technological improvements in the monitoring systems and the therapeutic algorithms should be assessed using the same metrics.

Glucose control positively influences patient outcome: A retrospective study

OBJECTIVE

The goal of this research is to demonstrate that well-regulated glycemia is beneficial to patient outcome, regardless of how it is achieved.

METHODS

This analysis used data from 1701 patients from 2, independent studies. Glycemic outcome was measured using cumulative time in band (cTIB), calculated for 3 glycemic bands and for threshold values of t = 0.5, 0.6, 0.7, and 0.8. For each day of intensive care unit stay, patients were classified by cTIB, threshold, and hospital mortality, and odds of living (OL) and odds ratio were calculated.

RESULTS

The OL given cTIB ≥ t is higher than the OL given cTIB <t for all values of t, every day, for all 3 glycemic bands studied. The difference between the odds clearly increased over intensive care unit stay for t>0.6. Higher cTIB thresholds resulted in larger increases to odds ratio over time and were particularly significant for the 4.0 to 7.0 mmol/L glycemic band.

CONCLUSION

Increased cTIB was associated with higher OL. These results suggest that effective glycemic control positively influences patient outcome, regardless of how the glycemic regulation is achieved. Blood glucose < 7.0 mmol/L is associated with a measurable increase in the odds of survival, if hypoglycemia is avoided.

Designing effective visualizations of habits data to aid clinical decision making

Background

Changes in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data.

Methods

Our approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times.

Results

The User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients.

Conclusions

We observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.

Electronic supplementary material

The online version of this article (doi:10.1186/s12911-014-0102-x) contains supplementary material, which is available to authorized users.

Monitoring activities of daily living of the elderly and the potential for its use in telecare and telehealth: a review

OBJECTIVE

This review was designed to determine whether telemonitoring activities of daily living (ADL) of elderly people can improve quality of life and be beneficial to their healthcare.

MATERIALS AND METHODS

Electronic databases were searched for studies that monitored ADL of elderly people and preferably measured some clinical outcomes such as ability to predict key events that require intervention and for studies that assessed perception of elderly people of such telemonitoring systems. The articles were reviewed and assessed independently by two reviewers.

RESULTS

One hundred seventy-five unique studies were found. Sixty-seven of these were identified for potential inclusion, and 25 studies were finally included. Study characteristics, parameters monitored, outcomes, and problems encountered were summarized and discussed. The main focus was on the potential benefits of ADL monitoring on the care of elderly people.

CONCLUSIONS

Although most studies reported on technical improvements in methods for detecting changes in ADL, few, if any, determined the benefits to the patient of telemonitoring for changes in ADL or correlation with any physiological changes. We propose sensor and system characteristics for improved user acceptance and deployment in a large-scale care plan. We present areas requiring further investigation.

Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients

OBJECTIVE

To evaluate the literature and identify important aspects of insulin therapy that facilitate safe and effective infusion therapy for a defined glycemic end point.

METHODS

Where available, the literature was evaluated using Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology to assess the impact of insulin infusions on outcome for general intensive care unit patients and those in specific subsets of neurologic injury, traumatic injury, and cardiovascular surgery. Elements that contribute to safe and effective insulin infusion therapy were determined through literature review and expert opinion. The majority of the literature supporting the use of insulin infusion therapy for critically ill patients lacks adequate strength to support more than weak recommendations, termed suggestions, such that the difference between desirable and undesirable effect of a given intervention is not always clear.

RECOMMENDATIONS

The article is focused on a suggested glycemic control end point such that a blood glucose ≥ 150 mg/dL triggers interventions to maintain blood glucose below that level and absolutely <180 mg/dL. There is a slight reduction in mortality with this treatment end point for general intensive care unit patients and reductions in morbidity for perioperative patients, postoperative cardiac surgery patients, post-traumatic injury patients, and neurologic injury patients. We suggest that the insulin regimen and monitoring system be designed to avoid and detect hypoglycemia (blood glucose ≤ 70 mg/dL) and to minimize glycemic variability.Important processes of care for insulin therapy include use of a reliable insulin infusion protocol, frequent blood glucose monitoring, and avoidance of finger-stick glucose testing through the use of arterial or venous glucose samples. The essential components of an insulin infusion system include use of a validated insulin titration program, availability of appropriate staffing resources, accurate monitoring technology, and standardized approaches to infusion preparation, provision of consistent carbohydrate calories and nutritional support, and dextrose replacement for hypoglycemia prevention and treatment. Quality improvement of glycemic management programs should include analysis of hypoglycemia rates, run charts of glucose values <150 and 180 mg/dL. The literature is inadequate to support recommendations regarding glycemic control in pediatric patients.

CONCLUSIONS

While the benefits of tight glycemic control have not been definitive, there are patients who will receive insulin infusion therapy, and the suggestions in this article provide the structure for safe and effective use of this therapy.

A review of hospital characteristics associated with improved performance

PURPOSE

The objective of this review was to critically appraise the literature relating to associations between high-level structural and operational hospital characteristics and improved performance.

DATA SOURCES

The Cochrane Library, MEDLINE (Ovid), CINAHL, proQuest and PsychINFO were searched for articles published between January 1996 and May 2010. Reference lists of included articles were reviewed and key journals were hand searched for relevant articles.

STUDY SELECTION

and data extraction Studies were included if they were systematic reviews or meta-analyses, randomized controlled trials, controlled before and after studies or observational studies (cohort and cross-sectional) that were multicentre, comparative performance studies. Two reviewers independently extracted data, assigned grades of evidence according to the Australian National Health and Medical Research Council guidelines and critically appraised the included articles. Data synthesis Fifty-seven studies were reported within 12 systematic reviews and 47 observational articles. There was heterogeneity in use and definition of performance outcomes. Hospital characteristics investigated were environment (incentives, market characteristics), structure (network membership, ownership, teaching status, geographical setting, service size) and operational design (innovativeness, leadership, organizational culture, public reporting and patient safety practices, information technology systems and decision support, service activity and planning, workforce design, staff training and education). The strongest evidence for an association with overall performance was identified for computerized physician order entry systems. Some evidence supported the associations with workforce design, use of financial incentives, nursing leadership and hospital volume.

CONCLUSION

There is limited, mainly low-quality evidence, supporting the associations between hospital characteristics and healthcare performance. Further characteristic-specific systematic reviews are indicated.

Systolic blood pressure reduction and risk of acute renal injury in patients with intracerebral hemorrhage

BACKGROUND

Aggressive systolic blood pressure reduction may precipitate acute renal injury because of underlying hypertensive nephropathy in patients with intracerebral hemorrhage. The study's objective was to determine the rate and determinants of acute renal injury during acute hospitalization among subjects with intracerebral hemorrhage using a post hoc analysis of a multicenter prospective study.

METHODS

Subjects with intracerebral hemorrhage and elevated systolic blood pressure of 170 mm Hg or greater who presented within 6 hours of symptom onset and underwent treatment of acute hypertensive response and fluid management as per study and local protocols, respectively. Acute renal injury was defined post hoc using the criteria used in Acute Kidney Injury Network classifications within 72 hours of admission. Descriptive statistics and standard statistical tests were used to characterize and evaluate the effect of systolic blood pressure reduction parameters (relative to initial systolic blood pressure) and average maximum hourly dose of nicardipine on the occurrence of acute renal injury.

RESULTS

A total of 60 subjects were recruited (57% were men; mean age of 62.0 ± 15.1 years). Five subjects (9%) had stage I acute renal injury according to the Acute Kidney Injury Network criteria. None of the subjects had stage II or III acute renal injury. The serum creatinine course for the first 3 days suggested that the peak elevation of creatinine was seen at 18, 30, 57, 58, and 71 hours after baseline measurements in these 5 subjects, all of which except for the first one were beyond the protocol-specified treatment period. The incidences of neurologic deterioration and symptomatic hematoma expansion were significantly greater in the subjects with stage I renal impairment. The systolic blood pressure reduction parameters (in particular, the area under the curve depicting the 24-hour systolic blood pressure summary statistic) and the higher average maximum hourly nicardipine dose were strongly associated with stage I renal impairment.

CONCLUSIONS

Although acute renal injury is infrequent and mild among subjects with intracerebral hemorrhage undergoing systolic blood pressure reduction, a trend in association between systolic blood pressure reduction and renal impairment was observed in this small study. Therefore, it is important to carefully monitor the renal function when administering treatment to reduce systolic blood pressure in patients with intracerebral hemorrhage.

Association of serum glucose concentrations during acute hospitalization with hematoma expansion, perihematomal edema, and three month outcome among patients with intracerebral hemorrhage

BACKGROUND

There is some evidence that hyperglycemia increases the rate of poor outcomes in patients with intracerebral hemorrhage (ICH). We explored the relationship between various parameters of serum glucose concentrations measured during acute hospitalization and hematoma expansion, perihematomal edema, and three month outcome among subjects with ICH.

METHODS

A post-hoc analysis of a multicenter prospective study recruiting subjects with ICH and elevated systolic blood pressure (SBP) ≥170 mmHg who presented within 6 h of symptom onset was performed. The serum glucose concentration was measured repeatedly up to 5 times over 3 days after admission and change over time was characterized using a summary statistic by fitting the linear regression model for each subject. The admission glucose, glucose change between admission and 24 hour glucose concentration, and estimated parameters (slope and intercept) were entered in the logistic regression model separately to predict the functional outcome as measured by modified Rankin scale (mRS) at 90 days (0-3 vs. 4-6); hematoma expansion at 24 h (≤33 vs. >33%); and relative perihematomal edema expansion at 24 h (≤40 vs. >40%).

RESULTS

A total of 60 subjects were recruited (aged 62.0 ±15.1 years; 56.7% men). The mean of initial glucose concentration (±standard deviation) was 136.7 mg/dl (±58.1). Thirty-five out of 60 (58%) subjects had a declining glucose over time (negative slope). The risk of poor outcome (mRS 4-6) in those with increasing serum glucose levels was over two-fold relative to those who had declining serum glucose levels (RR = 2.64, 95% confidence interval [CI]: 1.03, 6.75). The RRs were 2.59 (95% CI: 1.27, 5.30) for hematoma expansion >33%; and 1.25 (95% CI: 0.73, 2.13) for relative edema expansion >40%.

CONCLUSIONS

Decline in serum glucose concentration correlated with reduction in proportion of subjects with hematoma expansion and poor clinical outcome. These results provide a justification for a randomized controlled clinical trial to evaluate the efficacy of aggressive serum glucose reduction in reducing death and disability among patients with ICH.

Carbohydrate provision in the era of tight glucose control

Glycemic control in the critically ill patient has remained a controversial issue over the last decade. Several large trials, with widely varying results, have generated significant interest in defining the optimal target for blood-glucose control necessary for improving care while minimizing morbidity. Nutritional support has evolved into an additional area of critical care where appropriate practices have been associated with improved patient outcomes. Carbohydrate provision can impact blood-glucose levels, and the relationship between nutrition and glucose levels has become more complex in the era of improved glycemic control. This review discusses the controversy surrounding intensive-insulin therapy in the intensive care unit and explores the relationship with nutritional support, both in the enteral and parenteral form. Achieving realistic goals in both carbohydrate provision and glycemic control may improve patient outcome, and are not mutually exclusive practices.

Phase II study of tight glycaemic control in COPD patients with exacerbations admitted to the acute medical unit

BACKGROUND

Hyperglycaemia is associated with poor outcomes from exacerbations of chronic obstructive pulmonary disease (COPD). Glycaemic control could improve outcomes by reducing infection, inflammation and myopathy. Most patients with COPD are managed on the acute medical unit (AMU) outside intensive care (ICU).

OBJECTIVE

To determine the feasibility, safety and efficacy of tight glycaemic control in patients on an AMU.

DESIGN

Prospective, non-randomised, phase II, single-arm study of tight glycaemic control in COPD patients with acute exacerbations and hyperglycaemia admitted to the AMU. Participants received intravenous, then subcutaneous, insulin to control blood glucose to 4.4-6.5 mmol/l. Tight glycaemic control was evaluated: feasibility, protocol adherence; acceptability, patient questionnaire; safety, frequency of hypoglycaemia (capillary blood glucose (CBG) <2.2 mmol/l and 2.2-3.3 mmol/l); efficacy, median CBG, fasting CBG, proportion of measurements/time in target range, glycaemic variability.

RESULTS

were compared with 25 published ICU studies. Results 20 patients (10 females, age 71 ± 9 years; forced expiratory volume in 1 s: 41 ± 16% predicted) were recruited. Tight glycaemic control was feasible (78% CBG measurements and 89% of insulin-dose adjustments were adherent to protocol) and acceptable to patients. 0.2% CBG measurements were <2.2 mmol/l and 4.1% measurements 2.2-3.3 mmol/l. The study CBG and proportion of measurements/time in target range were similar to that of ICU studies, whereas the fasting CBG was lower, and the glycaemic variability was greater.

CONCLUSIONS

Tight glycaemic control is feasible and has similar safety and efficacy on AMU to ICU. However, as more recent ICU studies have shown no benefit and possible harm from tight glycaemic control, alternative strategies for blood glucose control in COPD exacerbations should now be explored. Trial registration number ISRCTN: 42412334. http://Clinical.Trials.gov NCT00764556.

Management of tight intraoperative glycemic control during off-pump coronary artery bypass surgery in diabetic and nondiabetic patients

OBJECTIVES

To optimize intra- and postoperative insulin management in cardiac surgical patients.

DESIGN

A prospective, randomized, open-label, single-center study.

SETTING

A large nonuniversity hospital.

PARTICIPANTS

Sixty diabetics and 60 nondiabetics undergoing off-pump cardiac bypass surgery.

INTERVENTIONS

Intra- and postoperative tight glycemic control were achieved using different approaches with a modified insulin protocol.

MEASUREMENTS AND MAIN RESULTS

Nondiabetics were divided randomly: in the ND-ind group (n = 30), insulin was started at induction according to preinduction blood glucose (BG) concentrations. In group ND >110 (n = 30), insulin was started when BG concentrations exceeded 110 mg/dL during surgery. Up to 85% of the ND >110 group started on insulin intraoperatively. Intraoperatively, the ND-ind group had more BG within target (80-110 mg/dL) (p = 0.002), less BG >130 mg/dL (p = 0.015), and more BG between 70 and 79 mg/dL (p = 0.002). In diabetics, BG concentration was checked every 30 (DM-30), n = 30) versus 60 minutes (DM-60, n = 30) to improve the protocol's performance. Intraoperatively, there were more BG concentrations within target (80-110 mg/dL) (p = 0.02) and less >130 mg/dL (p = 0.0002) in the DM-30 group. During surgery, the hyperglycemic index and the glycemic penalty index were lower in the ND-ind group (p < 0.05). Postoperatively, the mean BG concentrations, hyperglycemic index, and glycemic penalty index in diabetics and nondiabetics were comparable between groups (p < 0.05). In the overall 2,641 BG samples, the lowest BG concentration in the operating room was 71 and in the intensive care unit (ICU) it was 61 mg/dL.

CONCLUSIONS

In diabetics and nondiabetics undergoing off-pump coronary artery bypass surgery, tight perioperative glycemic control is feasible and efficient, with minimal risks for hypo- and hyperglycemia. In nondiabetics, starting insulin therapy from induction onwards results in more measurements within target, without affecting the mean BG. In diabetics, decreasing the sampling interval from 60 to 30 minutes results in more measurements within target and in a mean blood glucose within target at ICU arrival.

Characteristics and effects of nurse dosing over-rides on computer-based intensive insulin therapy protocol performance

OBJECTIVE

To determine characteristics and effects of nurse dosing over-rides of a clinical decision support system (CDSS) for intensive insulin therapy (IIT) in critical care units.

DESIGN

Retrospective analysis of patient database records and ethnographic study of nurses using IIT CDSS.

MEASUREMENTS

The authors determined the frequency, direction-greater than recommended (GTR) and less than recommended (LTR)- and magnitude of over-rides, and then compared recommended and over-ride doses' blood glucose (BG) variability and insulin resistance, two measures of IIT CDSS associated with mortality. The authors hypothesized that rates of hypoglycemia and hyperglycemia would be greater for recommended than over-ride doses. Finally, the authors observed and interviewed nurse users.

RESULTS

5.1% (9075) of 179,452 IIT CDSS doses were over-rides. 83.4% of over-ride doses were LTR, and 45.5% of these were ≥ 50% lower than recommended. In contrast, 78.9% of GTR doses were ≤ 25% higher than recommended. When recommended doses were administered, the rate of hypoglycemia was higher than the rate for GTR (p = 0.257) and LTR (p = 0.033) doses. When recommended doses were administered, the rate of hyperglycemia was lower than the rate for GTR (p = 0.003) and LTR (p < 0.001) doses. Estimates of patients' insulin requirements were higher for LTR doses than recommended and GTR doses. Nurses reported trusting IIT CDSS overall but appeared concerned about recommendations when administering LTR doses.

CONCLUSION

When over-riding IIT CDSS recommendations, nurses overwhelmingly administered LTR doses, which emphasized prevention of hypoglycemia but interfered with hyperglycemia control, especially when BG was >150 mg/dl. Nurses appeared to consider the amount of a recommended insulin dose, not a patient's trend of insulin resistance, when administering LTR doses overall. Over-rides affected IIT CDSS protocol performance.

Glucose variability measures and their effect on mortality: a systematic review

Objective

To systematically review the medical literature on the association between glucose variability measures and mortality in critically ill patients.

Methods

Studies assessing the association between a measure of glucose variability and mortality that reported original data from a clinical trial or observational study on critically ill adult patients were searched in Ovid MEDLINE^® and Ovid EMBASE^®. Data on patient populations, study designs, glucose regulations, statistical approaches, outcome measures, and glucose variability indicators (their definition and applicability) were extracted.

Result

Twelve studies met the inclusion criteria; 13 different indicators were used to measure glucose variability. Standard deviation and the presence of both hypo- and hyperglycemia were the most common indicators. All studies reported a statistically significant association between mortality and at least one glucose variability indicator. In four studies both blood glucose levels and severity of illness were considered as confounders, but only one of them checked model assumptions to assert inference validity.

Conclusions

Glucose variability has been quantified in many different ways, and in each study at least one of them appeared to be associated with mortality. Because of methodological limitations and the possibility of reporting bias, it is still unsettled whether and in which quantification this association is independent of other confounders. Future research will benefit from using an indicator reference subset for glucose variability, metrics that are linked more directly to negative physiological effects, more methodological rigor, and/or better reporting.

Glucose and insulin administration while maintaining normoglycemia during cardiac surgery using a computer-assisted algorithm

BACKGROUND

applying the principles of the hyperinsulinemic-normoglycemic clamp technique we have introduced glucose and insulin administration while maintaining normoglycemia (GIN therapy) to surgical patients. The objective of this study was to evaluate a novel computer software (GIN Computer Software [GINCS]) program using an algorithm based on the original clamp equation and modified for its use during cardiac surgery.

METHODS

thirty-six patients without diabetes undergoing elective cardiac surgery were randomly assigned to manually controlled or computer-guided GIN therapy. In both groups insulin was administered at 5 mU/kg/min during surgery. Simultaneously, 20% dextrose was infused at a rate adjusted to maintain blood glucose (BG) between 4.0 and 6.0 mmol/L. The adjustments were made either following an algorithm based on our previous GIN experience or suggestions made by the software program. The primary outcome was the achievement of target glycemia.

RESULTS

normoglycemia was achieved in both groups as reflected by mean BG concentrations of 5.0 ± 0.5 mmol/L and 5.1 ± 0.2 mmol/L. Mean sampling intervals were longer in the GINCS group than in the manual group (21.5  ± 1.9 vs. 14.2 ± 2.2 min, P < 0.001). The GINCS therapy was associated with a greater percentage of BG measurements within target (manual group, before cardiopulmonary bypass [CPB] 79.7%, during CPB 68.1%, and after CPB 69.1%; GINCS group, before CPB 94.1%, during CPB 92.4%, and after CPB 97.7%; P < 0.001). No hypoglycemia was observed.

CONCLUSIONS

the use of a computer-guided GIN protocol in patients without diabetes undergoing open heart surgery provided excellent and safe glycemic control.

Comparison of the effectiveness and safety of two insulin infusion protocols in the management of hyperglycemia in critically ill children

OBJECTIVES

To compare the effectiveness and safety of a paper-based and a computerized algorithm used for tight glycemic control.

SETTING

Academic pediatric intensive care unit.

DESIGN

Retrospective cohort study.

PATIENTS

Two groups of nondiabetic critically ill children with persistent hyperglycemia (blood glucose ≥140 mg/dL [ ≥7.8 mmol/L] for at least 2 hrs) were included.

INTERVENTION

One group of patients' blood glucose was controlled at 90-119 mg/dL (5.0-6.6 mmol/L) using the Yale Insulin Infusion Protocol (YIIP), a paper-based protocol. Another group of patients' blood glucose was controlled at 80-110 mg/dL (4.4-6.1 mmol/L) with eProtocol insulin (ePi), a computerized decision support tool.

MEASUREMENTS AND MAIN RESULTS

The effectiveness of the protocols was compared using percentages of blood glucose values within target range and glucose variability index. A safety comparison was made using hypoglycemia rates at ≤40 mg/dL (≤2.2 mmol/L), ≤50 mg/dL (≤2.8 mmol/L), and ≤60 mg/dL (≤3.3 mmol/L). Forty-two patients and 12 patients were included in the YIIP and ePi groups, respectively. The percent of values in range was lower in the YIIP group (33%) compared with the ePi group (41%) (p < .001). Mean glucose variability index was comparable in the two groups (18.7 ± 8.9 mg/dL/hr [1.0 ± 0.5 mmol/L/hr] for the YIIP group and 14.4 ± 7.6 mg/dL/hr [0.8 ± 0.4 mmol/L/hr] for the ePi group; p = .111). Hypoglycemia rates were statistically similar in both groups. In the YIIP group, 10% of patients and in the ePi group, 25% of patients had blood glucose ≤40 mg/dL (≤2.2 mmol/L) (p = .168).

CONCLUSION

YIIP is less effective but is as safe as ePi in achieving tight glycemic control. We are awaiting the results of two multicenter trials designed to determine the survival benefit of tight glycemic control in children. Further studies are needed to determine the clinical significance of the different glucose metrics in critically ill patients.

Randomized clinical trial of a customized electronic alert requiring an affirmative response compared to a control group receiving a commercial passive CPOE alert: NSAID--warfarin co-prescribing as a test case

BACKGROUND

Studies that have looked at the effectiveness of computerized decision support systems to prevent drug-drug interactions have reported modest results because of low response by the providers to the automated alerts.

OBJECTIVE

To evaluate, within an inpatient computerized physician order entry (CPOE) system, the incremental effectiveness of an alert that required a response from the provider, intended as a stronger intervention to prevent concurrent orders of warfarin and non-steroidal anti-inflammatory drugs (NSAIDs).

DESIGN

Randomized clinical trial of 1963 clinicians assigned to either an intervention group receiving a customized electronic alert requiring affirmative response or a control group receiving a commercially available passive alert as part of the CPOE. The study duration was 2 August 2006 to 15 December 2007.

MEASUREMENTS

Alert adherence was compared between study groups.

RESULTS

The proportion of desired ordering responses (ie, not reordering the alert-triggering drug after firing) was lower in the intervention group (114/464 (25%) customized alerts issued) than in the control group (154/560 (28%) passive alerts firing). The adjusted OR of inappropriate ordering was 1.22 (95% CI 0.69 to 2.16).

CONCLUSION

A customized CPOE alert that required a provider response had no effect in reducing concomitant prescribing of NSAIDs and warfarin beyond that of the commercially available passive alert received by the control group. New CPOE alerts cannot be assumed to be effective in improving prescribing, and need evaluation.

International recommendations for glucose control in adult non diabetic critically ill patients

INTRODUCTION

The purpose of this research is to provide recommendations for the management of glycemic control in critically ill patients.

METHODS

Twenty-one experts issued recommendations related to one of the five pre-defined categories (glucose target, hypoglycemia, carbohydrate intake, monitoring of glycemia, algorithms and protocols), that were scored on a scale to obtain a strong or weak agreement. The GRADE (Grade of Recommendation, Assessment, Development and Evaluation) system was used, with a strong recommendation indicating a clear advantage for an intervention and a weak recommendation indicating that the balance between desirable and undesirable effects of an intervention is not clearly defined.

RESULTS

A glucose target of less than 10 mmol/L is strongly suggested, using intravenous insulin following a standard protocol, when spontaneous food intake is not possible. Definition of the severe hypoglycemia threshold of 2.2 mmol/L is recommended, regardless of the clinical signs. A general, unique amount of glucose (enteral/parenteral) to administer for any patient cannot be suggested. Glucose measurements should be performed on arterial rather than venous or capillary samples, using central lab or blood gas analysers rather than point-of-care glucose readers.

CONCLUSIONS

Thirty recommendations were obtained with a strong (21) and a weak (9) agreement. Among them, only 15 were graded with a high level of quality of evidence, underlying the necessity to continue clinical studies in order to improve the risk-to-benefit ratio of glucose control.

Implementing glucose control in intensive care: a multicenter trial using statistical process control

Background

Glucose control (GC) with insulin decreases morbidity and mortality of critically ill patients. In this study we investigated GC performance over time during implementation of GC strategies within three intensive care units (ICUs) and in routine clinical practice.

Methods

All adult critically ill patients who stayed for >24 h between 1999 and 2007 were included. Effects of implementing local GC guidelines and guideline revisions on effectiveness/efficiency-related indicators, safety-related indicators, and protocol-related indicators were measured.

Results

Data of 17,111 patient admissions were evaluated, with 714,141 available blood glucose levels (BGL) measurements. Mean BGL, time to reach target, hyperglycemia index, sampling frequency, percentage of hyperglycemia events, and in-range measurements statistically changed after introducing GC in all ICUs. The introduction of simple rules on GC had the largest effect. Subsequent changes in the protocol had a smaller effect than the introduction of the protocol itself. As soon as the protocol was introduced, in all ICUs the percentage of hypoglycemia events increased. Various revisions were implemented to reduce hypoglycemia events, but levels never returned to those from pre-implementation. More intensive implementation strategies including the use of a decision support system resulted in better control of the process.

Conclusion

There are various strategies to achieve GC in routine clinical practice but with variable success. All of them were associated with an increase in hypoglycemia events, but GC was never stopped. Instead, these events have been accepted and managed. Statistical process control is a useful tool for monitoring phenomena over time and captures within-institution changes.

Electronic supplementary material

The online version of this article (doi:10.1007/s00134-010-1924-3) contains supplementary material, which is available to authorized users.

Clinical review: Strict or loose glycemic control in critically ill patients--implementing best available evidence from randomized controlled trials

Glycemic control aiming at normoglycemia, frequently referred to as 'strict glycemic control' (SGC), decreased mortality and morbidity of adult critically ill patients in two randomized controlled trials (RCTs). Five successive RCTs, however, failed to show benefit of SGC with one trial even reporting an unexpected higher mortality. Consequently, enthusiasm for the implementation of SGC has declined, hampering translation of SGC into daily ICU practice. In this manuscript we attempt to explain the variances in outcomes of the RCTs of SGC, and point out other limitations of the current literature on glycemic control in ICU patients. There are several alternative explanations for why the five negative RCTs showed no beneficial effects of SGC, apart from the possibility that SGC may indeed not benefit ICU patients. These include, but are not restricted to, variability in the performance of SGC, differences among trial designs, changes in standard of care, differences in timing (that is, initiation) of SGC, and the convergence between the intervention groups and control groups with respect to achieved blood glucose levels in the successive RCTs. Additional factors that may hamper translation of SGC into daily ICU practice include the feared risk of severe hypoglycemia, additional labor associated with SGC, and uncertainties about who the primarily responsible caregiver should be for the implementation of SGC.

Which factors influence glycemic control in the intensive care unit?

PURPOSE OF REVIEW

Intensive insulin therapy titrated to restore and maintain blood glucose between 80 and 110 mg/dl (4.4-6.1 mmol/l) was found to improve survival of critically ill patients in one pioneering proof-of-concept study performed in a surgical intensive care unit. The external validity of these findings was investigated.

RECENT FINDINGS

Six independent prospective randomized controlled trials, involving 9877 patients in total, were unable to confirm the survival benefit reported in the pioneering trial. Several hypotheses were proposed to explain this discrepancy, including the case-mix, the features of the usual care, the quality of glucose control and the risks associated with hypoglycemia.

SUMMARY

Before a better understanding and delineation of the conditions associated with and improved outcome by tight glycemic control, the choice of an intermediate glycemic target appears as a safe and effective solution.

How to weigh the current evidence for clinical practice

This article presents a template for judging trials of tight glucose control in critically ill patients. It reviews threats to both internal validity and generalisability using examples from the current literature. When judging internal validity, it is important to consider factors specific to trials of glucose control (particularly the methods of glucose control, measurement and reporting) in addition to factors common to all randomised controlled trials (such as treatment allocation, losses to follow-up and protocol violations). Judging generalisability requires the identification of differences between the trial population and the population for whom the intervention is being considered. These may relate to the setting, the patients or the practical delivery of tight glucose control or other interventions. Once identified, a judgement must be made for each difference of whether it is likely to modify the effect of tight glucose control.

Is hypoglycaemia dangerous?

Tight glycaemic control (TGC) for patients treated in an intensive care unit ICU is associated with an increased risk for hypoglycaemia. Since hypoglycaemia mainly occurs in the sickest patients, no matter whether TGC is applied or not, it might be a marker for severity of illness or a harmful event in itself. Furthermore, it remains a matter of debate whether harmful effects of hypoglycaemia outbalance the clinical benefits of TGC. This review focusses on the clinical manifestations of hypoglycaemia in the critically ill and highlights its potential short- and long-term consequences specifically concerning neurocognitive function.

An overview of hypoglycemia in the critically ill

Hypoglycemia is a common and serious problem among patients with diabetes mellitus. It is also perceived as the most important obstacle to tight glucose control using intensive insulin therapy in critically ill patients. Because glucose is an obligatory metabolic fuel for the brain, hypoglycemia always represents an emergency that signals the inability of the brain to meet its energy needs. When left untreated, hypoglycemia can result in permanent brain damage and ultimately, death. In the context of critical illness that limits endogenous glucose production and increases glucose utilization, inadequate nutrition, or insufficient provision of glucose, intensive insulin therapy is the most frequent cause of hypoglycemia. Neurogenic and neuroglycopenic symptoms of hypoglycemia can remain unknown because of the underlying critical illness and sedation. Thus, close and reliable monitoring of the glycemic level is crucial in detecting hypoglycemia. In prospective randomized controlled studies comparing the effects of two glucose regimens, intensive insulin therapy aimed to reach strict glucose control (<110 mg/dl) but increased the incidence of severe hypoglycemia (<40 mg/dl) by four- to sixfold. Severe hypoglycemia is statistically associated with adverse outcomes in intensive care unit patients, although a direct causal relationship has not been demonstrated.

Year in review 2008: Critical Care--metabolism

In 2008, the interest in metabolic and endocrine issues and their consequences in critically ill patients was high. A large proportion of the research papers related to these issues was related to the metabolism of glucose and its control and to the changes in body composition, including muscular weakness. In Critical Care, original reports from investigations of glucose physiology and clinical data from observational and interventional studies were published. Important reports of the effects of hormone analogues, such as vasopressin and hydrocortisone, and early antioxidants in selected subpopulations were also available in 2008.

Computerized intensive insulin dosing can mitigate hypoglycemia and achieve tight glycemic control when glucose measurement is performed frequently and on time

Introduction

Control of blood glucose (BG) in critically ill patients is considered important, but is difficult to achieve, and often associated with increased risk of hypoglycemia. We examined the use of a computerized insulin dosing algorithm to manage hyperglycemia with particular attention to frequency and conditions surrounding hypoglycemic events.

Methods

This is a retrospective analysis of adult patients with hyperglycemia receiving intravenous (IV) insulin therapy from March 2006 to December 2007 in the intensive care units of 2 tertiary care teaching hospitals. Patients placed on a glycemic control protocol using the Clarian GlucoStabilizer™ IV insulin dosing calculator with a target range of 4.4-6.1 mmol/L were analyzed. Metrics included time to target, time in target, mean blood glucose ± standard deviation, % measures in hypoglycemic ranges <3.9 mmol/L, per-patient hypoglycemia, and BG testing interval.

Results

4,588 ICU patients were treated with the GlucoStabilizer to a BG target range of 4.4-6.1 mmol/L. We observed 254 severe hypoglycemia episodes (BG <2.2 mmol/L) in 195 patients, representing 0.1% of all measurements, and in 4.25% of patients or 0.6 episodes per 1000 hours on insulin infusion. The most common contributing cause for hypoglycemia was measurement delay (n = 170, 66.9%). The median (interquartile range) time to achieve the target range was 5.9 (3.8 - 8.9) hours. Nearly all (97.5%) of patients achieved target and remained in target 73.4% of the time. The mean BG (± SD) after achieving target was 5.4 (± 0.52) mmol/L. Targeted blood glucose levels were achieved at similar rates with low incidence of severe hypoglycemia in patients with and without diabetes, sepsis, renal, and cardiovascular disease.

Conclusions

Glycemic control to a lower glucose target range can be achieved using a computerized insulin dosing protocol. With particular attention to timely measurement and adjustment of insulin doses the risk of hypoglycemia experienced can be minimized.

Tight glycemic control and computerized decision-support systems: a systematic review

Objective

To identify and summarize characteristics of computerized decision-support systems (CDSS) for tight glycemic control (TGC) and to review their effects on the quality of the TGC process in critically ill patients.

Methods

We searched Medline (1950–2008) and included studies on critically ill adult patients that reported original data from a clinical trial or observational study with a main objective of evaluating a given TGC protocol with a CDSS.

Results

Seventeen articles met the inclusion criteria. Eleven out of seventeen studies evaluated the effect of a new TGC protocol that was introduced simultaneously with a CDSS implementation. Most of the reported CDSSs were stand-alone, were not integrated in any other clinical information systems and used the “passive” mode requiring the clinician to ask for advice. Different implementation sites, target users, and time of advice were used, depending on local circumstances. All controlled studies reported on at least one quality indicator of the blood glucose regulatory process that was improved by introducing the CDSS. Nine out of ten controlled studies either did not report on the number of hypoglycemia events (one study), or reported on no change (six studies) or even a reduction in this number (two studies).

Conclusions

While most studies evaluating the effect of CDSS on the quality of the TGC process found improvement when evaluated on the basis of the quality indicators used, it is impossible to define the exact success factors, because of simultaneous implementation of the CDSS with a new or modified TGC protocol and the hybrid solutions used to integrate the CDSS into the clinical workflow.

Data mining technologies for blood glucose and diabetes management

Data mining is the process of selecting, exploring, and modeling large amounts of data to discover unknown patterns or relationships useful to the data analyst. This article describes applications of data mining for the analysis of blood glucose and diabetes mellitus data. The diabetes management context is particularly well suited to a data mining approach. The availability of electronic health records and monitoring facilities, including telemedicine programs, is leading to accumulating huge data sets that are accessible to physicians, practitioners, and health care decision makers. Moreover, because diabetes is a lifelong disease, even data available for an individual patient may be massive and difficult to interpret. Finally, the capability of interpreting blood glucose readings is important not only in diabetes monitoring but also when monitoring patients in intensive care units. This article describes and illustrates work that has been carried out in our institutions in two areas in which data mining has a significant potential utility to researchers and clinical practitioners: analysis of (i) blood glucose home monitoring data of diabetes mellitus patients and (ii) blood glucose monitoring data from hospitalized intensive care unit patients.

Ingredients for adequate evaluation of blood glucose algorithms as applied to the critically ill

The article by Eslami and colleagues provides an overview of the indicators used to measure the quality of blood glucose control in patients admitted to the intensive care unit. Each indicator can be related to one or more of the following categories: blood glucose zones, blood glucose levels, time intervals, and features of the insulin titration algorithm. Some important issues (for instance those concerning the clarity of definitions used for glycaemic thresholds) are raised. This systematic review calls for a practical guide to advise the clinician how different blood glucose signals should (ideally) be evaluated and which steps should to be undertaken.