Intensive insulin therapy in intensive care: an example of the struggle to implement evidence-based medicine

"One more thing to think about…" Cognitive burden experienced by intensive care unit nurses when implementing a tight glucose control protocol

Critically ill patients require intensive nursing care. Intensive care unit (ICU) nurses, who care for these physiologically unstable patients, are continuously occupied with the integration of assessments, monitoring, and interventions that are responsive to a patient's evolving state. Since 2005, numerous evidenced-based clinical protocols have been implemented in the critical care unit. Individually, each may not appear to be burdensome but, collectively, these clinical protocols add to the cognitive work of ICU nurses. While nurses are central to the successful implementation of these protocols, little is written about the cognitive burden imposed on them by the addition of these clinical protocols. This article explores the impact of clinical protocols on the cognitive burden of ICU nurses, using a tight glucose control (TGC) protocol as an exemplar case. Research from management, ergonomics, systems engineering, and nursing is used to build the concept of cognitive burden. Future research can build upon this understanding to facilitate successful implementation of clinical protocols.

Insulin therapy in critically ill patients

Hyperglycemia frequently occurs with acute medical illness, especially among patients with cardiovascular disease, and has been linked to increased morbidity and mortality in critically ill patients. Even patients who are normoglycemic can develop hyperglycemia in response to acute metabolic stress. An expanding body of literature describes the benefits of normalizing hyperglycemia with insulin therapy in hospitalized patients. As a result, both the American Diabetes Association and the American College of Endocrinology have developed guidelines for optimal control of hyperglycemia, specifically targeting critically ill, hospitalized patients. Conventional blood glucose values of 140–180 mg/dL are considered desirable and safely achievable in most patients. More aggressive control to <110 mg/dL remains controversial, but has shown benefits in certain patients, such as those in surgical intensive care. Intravenous infusion is often used for initial insulin administration, which can then be transitioned to subcutaneous insulin therapy in those patients who require continued insulin maintenance. This article reviews the data establishing the link between hyperglycemia and its risks of morbidity and mortality, and describes strategies that have proven effective in maintaining glycemic control in high-risk hospitalized patients.

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.

Has mortality from sepsis improved and what to expect from new treatment modalities: review of current insights

BACKGROUND

The incidence of sepsis is increasing continuously, making mortality rate reduction through improved intensive care unit (ICU) care and new treatment modalities a pressing issue. This study aimed to provide insight into the effects of modern ICU care on mortality trends from severe sepsis and to provide a quantitative review of the relative effectiveness of new treatment modalities in reducing deaths.

METHODS

Mortality data from severe sepsis were extracted from the control arms of several large randomized trials of sepsis treatment published within the last two decades. The effectiveness of recent treatment strategies was expressed as the number of patients it is necessary to treat by that method to save one life (number needed to treat: NNT).

RESULTS

Death from severe sepsis showed a decline from 44% to 35% between 1990 and 2000. The two most effective strategies in critically ill patients are early appropriate antibiotics (NNT 3; 95% confidence interval [CI] 2, 4) and early goal-directed therapy (NNT 6; 95% CI 4, 24). Infusion of recombinant human activated protein C is the most effective anticoagulant therapy (NNT 15; 95% CI 10, 27). Intensive insulin therapy is only moderately effective (NNT 27; 95% CI 15, 124).

CONCLUSIONS

The mortality rate from severe sepsis has decreased significantly with modernization of ICU care. New therapeutic strategies may reduce further the mortality rate. However, focused implementation of these new strategies in accordance with their relative effectiveness is needed before we can expect to see their true effect on mortality rates.

Towards closed-loop glycaemic control

Blood glucose control performed by intensive care unit (ICU) nurses is becoming standard practice for critically ill patients. New algorithms, ranging from basic protocols to elementary computerized protocols to advanced computerized protocols, have been presented during the last years aiming to reduce the workload of the medical team. This paper gives an overview of the different types of algorithms and their features. Performance comparisons between different algorithms are avoided as blood glucose sampling frequencies and protocol durations were not similar among different studies and even within studies. Particularly advanced computerized protocols can potentially be introduced as fully-automated blood glucose algorithms when accurate and reliable near-continuous glucose sensor devices are available. Furthermore, it is surprising to consider in some of the described protocols that the original blood glucose target ranges (80-110 mg/dl) were increased (due to fear of hypoglycaemia) and/or that glycaemia levels were determined in capillary blood samples.

The impact of early hypoglycemia and blood glucose variability on outcome in critical illness

Introduction

In critical illness, the association of hypoglycemia, blood glucose (BG) variability and outcome are not well understood. We describe the incidence, clinical factors and outcomes associated with an early hypoglycemia and BG variability in critically ill patients.

Methods

Retrospective interrogation of prospectively collected data from the Australia New Zealand Intensive Care Society Adult Patient Database on 66184 adult admissions to 24 intensive care units (ICUs) from 1 January 2000 to 31 December 2005. Primary exposure was hypoglycemia (BG < 4.5 mmol/L) and BG variability (BG < 4.5 and ≥ 12.0 mmol/L) within 24 hours of admission. Primary outcome was all-cause mortality.

Results

The cumulative incidence of hypoglycemia and BG variability were 13.8% (95% confidence interval (CI) = 13.5 to 14.0; n = 9122) and 2.9% (95%CI = 2.8 to 3.0, n = 1913), respectively. Several clinical factors were associated with both hypoglycemia and BG variability including: co-morbid disease (P < 0.001), non-elective admissions (P < 0.001), higher illness severity (P < 0.001), and primary septic diagnosis (P < 0.001). Hypoglycemia was associated with greater odds of adjusted ICU (odds ratio (OR) = 1.41, 95% CI = 1.31 to 1.54) and hospital death (OR = 1.36, 95% CI = 1.27 to 1.46). Hypoglycemia severity was associated with 'dose-response' increases in mortality. BG variability was associated with greater odds of adjusted ICU (1.5, 95% CI = 1.4 to 1.6) and hospital (1.4, 95% CI = 1.3 to 1.5) mortality, when compared with either hypoglycemia only or neither.

Conclusions

In critically ill patients, both early hypoglycemia and early variability in BG are relatively common, and independently portend an increased risk for mortality.

Early blood glucose control and mortality in critically ill patients in Australia

OBJECTIVE

To measure temporal trends in blood glucose (BG) control and describe their association with hospital mortality in a cohort of critically ill patients from Australia.

DESIGN

Interrogation of prospectively collected data from the Australia New Zealand Intensive Care Society Adult Patient Database.

SETTING

Twenty-four intensive care units (ICU) across Australia.

PATIENTS AND PARTICIPANTS

A cohort of 66,184 adult ICU admissions for >or=24 hours from January 1, 2000, to December 31, 2005.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Highest and lowest BG values within 24 hours of ICU admission, standard demographic, clinical, and physiologic data, and hospital mortality. Medical, mechanically ventilated surgical, cardiac surgical, and septic subgroups were evaluated. Average BG was evaluated as a continuous variable and by quartiles (low [<5.6 mmol/L], near normal [5.6-8.69 mmol/L], high [8.69-11.79 mmol/L], and highest [>11.79 mmol/L]). There were 132,368 BG values, with a mean (95% confidence intervals) value 8.69 mmol/L (8.66-8.73). There was no trend in BG for the entire cohort (p = 0.66) over the study period; yet, BG increased after 2002 (0.17 mmol/L, p < 0.0001). The mechanically ventilated surgical and cardiac surgical subgroups had decreasing trends in BG (p < 0.001), whereas the septic subgroup had an increasing BG trend (p < 0.001). BG in the low, high, and highest quartiles, compared with the near-normal quartile, were consistently associated with higher hospital mortality in crude (odds ratio 1.31, 1.58, and 2.00) and multivariable analysis (odds ratio 1.29, 1.07, and 1.10), respectively. This association was similarly shown for the mechanically ventilated surgical and cardiac surgical subgroups.

CONCLUSIONS

In a large cohort of ICU patients from Australia, there was no significant change in early glycemic control from 2000 to 2005. There were differences in selected subgroups. Average BG decreased in surgical subgroups, whereas it increased in septic patients. Both high and early low BG values were independently associated with hospital mortality.

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

Introduction

The objectives of this study were to systematically identify and summarize quality indicators of tight glycaemic control in critically ill patients, and to inspect the applicability of their definitions.

Methods

We searched in MEDLINE^® for all studies evaluating a tight glycaemic control protocol and/or quality of glucose control that reported original data from a clinical trial or observational study on critically ill adult patients.

Results

Forty-nine studies met the inclusion criteria; 30 different indicators were extracted and categorized into four nonorthogonal categories: blood glucose zones (for example, 'hypoglycaemia'); blood glucose levels (for example, 'mean blood glucose level'); time intervals (for example, 'time to occurrence of an event'); and protocol characteristics (for example, 'blood glucose sampling frequency'). Hypoglycaemia-related indicators were used in 43 out of 49 studies, acting as a proxy for safety, but they employed many different definitions. Blood glucose level summaries were used in 41 out of 49 studies, reported as means and/or medians during the study period or at a certain time point (for example, the morning blood glucose level or blood glucose level upon starting insulin therapy). Time spent in the predefined blood glucose level range, time needed to reach the defined blood glucose level target, hyperglycaemia-related indicators and protocol-related indicators were other frequently used indicators. Most indicators differ in their definitions even when they are meant to measure the same underlying concept. More importantly, many definitions are not precise, prohibiting their applicability and hence the reproducibility and comparability of research results.

Conclusions

An unambiguous indicator reference subset is necessary. The result of this systematic review can be used as a starting point from which to develop a standard list of well defined indicators that are associated with clinical outcomes or that concur with clinicians' subjective views on the quality of the regulatory process.

Treating hyperglycemia and diabetes with insulin therapy: transition from inpatient to outpatient care

CONTEXT

Intensive insulin therapy is recommended to control glucose elevations in the critically ill and has been shown to significantly improve outcomes among hospital inpatients with acute hyperglycemia or newly diagnosed diabetes. Once discharged, the hyperglycemic patient may require ongoing outpatient care, most often under the attention of a primary care physician.

EVIDENCE ACQUISITION

The purpose of this review is to provide a background of in-hospital hyperglycemia management and discharge planning in preparation for continued outpatient care. Primary data sources were identified through a PubMed search (1990-2007) using keywords, such as diabetes, hyperglycemia, in-hospital, discharge, and insulin.

EVIDENCE SYNTHESIS

Hyperglycemia protocols with strict glycemic goals have been shown to improve morbidity and mortality among critically ill inpatients. Discharge planning should prepare patients for self-care and give them the survival skills necessary to maintain glycemic control. In preparation for discharge, patients are usually transitioned from insulin infusions to subcutaneous insulin administered through an appropriate basal-prandial regimen.

CONCLUSION

A thorough understanding of hyperglycemia history and treatment will allow the primary care physician to deliver optimal diabetes care and thereby improve both short-term and long-term outcomes for those patients with critical illnesses and hyperglycemia or diabetes.

Why are clinicians not embracing the results from pivotal clinical trials in severe sepsis? A bayesian analysis

BACKGROUND

Five pivotal clinical trials (Intensive Insulin Therapy; Recombinant Human Activated Protein C [rhAPC]; Low-Tidal Volume; Low-Dose Steroid; Early Goal-Directed Therapy [EGDT]) demonstrated mortality reduction in patients with severe sepsis and expert guidelines have recommended them to clinical practice. Yet, the adoption of these therapies remains low among clinicians.

OBJECTIVES

We selected these five trials and asked: Question 1--What is the current probability that the new therapy is not better than the standard of care in my patient with severe sepsis? Question 2--What is the current probability of reducing the relative risk of death (RRR) of my patient with severe sepsis by meaningful clinical thresholds (RRR >15%; >20%; >25%)?

METHODS

Bayesian methodologies were applied to this study. Odds ratio (OR) was considered for Question 1, and RRR was used for Question 2. We constructed prior distributions (enthusiastic; mild, moderate, and severe skeptic) based on various effective sample sizes of other relevant clinical trials (unfavorable evidence). Posterior distributions were calculated by combining the prior distributions and the data from pivotal trials (favorable evidence).

MAIN FINDINGS

Answer 1--The analysis based on mild skeptic prior shows beneficial results with the Intensive Insulin, rhAPC, and Low-Tidal Volume trials, but not with the Low-Dose Steroid and EGDT trials. All trials' results become unacceptable by the analyses using moderate or severe skeptic priors. Answer 2--If we aim for a RRR>15%, the mild skeptic analysis shows that the current probability of reducing death by this clinical threshold is 88% for the Intensive Insulin, 62-65% for the Low-Tidal Volume, rhAPC, EGDT trials, and 17% for the Low-Dose Steroid trial. The moderate and severe skeptic analyses show no clinically meaningful reduction in the risk of death for all trials. If we aim for a RRR >20% or >25%, all probabilities of benefits become lower independent of the degree of skepticism.

CONCLUSIONS

Our clinical threshold analysis offers a new bedside tool to be directly applied to the care of patients with severe sepsis. Our results demonstrate that the strength of evidence (statistical and clinical) is weak for all trials, particularly for the Low-Dose Steroid and EGDT trials. It is essential to replicate the results of each of these five clinical trials in confirmatory studies if we want to provide patient care based on scientifically sound evidence.

Is there more to glycaemic control than meets the eye?

Tight glycaemic control has emerged as a major focus in critical care. However, the struggle to repeat, improve and standardize the results of the initial landmark studies is ongoing. The prospective computerized glycaemic control study by Shulman et al. highlights two emerging and often overlooked aspects of intensive insulin therapy protocols beyond simple glycaemic performance. First, the clinical ergonomics and ability to integrate into the critical care unit workflow must be considered as they may impact results and definitely affect uptake. Second, the real lessons of any protocol's performance are likely to be best realized by comparison with other results, a task that is very difficult without a consensus method of reporting that allows such comparisons across studies. Embracing these issues will take the field closer to accepted, repeatable approaches to tight glycaemic control.

Nurse-led implementation of an insulin-infusion protocol in a general intensive care unit: improved glycaemic control with increased costs and risk of hypoglycaemia signals need for algorithm revision

Background

Strict glycaemic control (SGC) has become a contentious issue in modern intensive care. Physicians and nurses are concerned about the increased workload due to SGC as well as causing harm through hypoglycaemia. The objective of our study was to evaluate our existing degree of glycaemic control, and to implement SGC safely in our ICU through a nurse-led implementation of an algorithm for intensive insulin-therapy.

Methods

The study took place in the adult general intensive care unit (11 beds) of a 44-bed department of intensive care at a tertiary care university hospital. All patients admitted during the 32 months of the study were enrolled. We retrospectively analysed all arterial blood glucose (BG) results from samples that were obtained over a period of 20 months prior to the implementation of SGC. We then introduced an algorithm for intensive insulin therapy; aiming for arterial blood-glucose at 4.4 – 6.1 mmol/L. Doctors and nurses were trained in the principles and potential benefits and risks of SGC. Consecutive statistical analyses of blood samples over a period of 12 months were used to assess performance, provide feedback and uncover incidences of hypoglycaemia.

Results

Median BG level was 6.6 mmol/L (interquartile range 5.6 to 7.7 mmol/L) during the period prior to implementation of SGC (494 patients), and fell to 5.9 (IQR 5.1 to 7.0) mmol/L following introduction of the new algorithm (448 patients). The percentage of BG samples > 8 mmol/L was reduced from 19.2 % to 13.1 %. Before implementation of SGC, 33 % of samples were between 4.4 to 6.1 mmol/L and 12 patients (2.4 %) had one or more episodes of severe hypoglycaemia (< 2.2 mmol/L). Following implementation of SGC, 45.8 % of samples were between 4.4 to 6.1 mmol/L and 40 patients (8.9 %) had one or more episodes of severe hypoglycaemia. Of theses, ten patients died while still hospitalised (all causes).

Conclusion

The retrospective part of the study indicated ample room for improvement. Through the implementation of SGC the fraction of samples within the new target range increased from 33% to 45.8%. There was also a significant increase in severe hypoglycaemic episodes. There continues to be potential for improved glycaemic control within our ICU. This might be achieved through an improved algorithm and continued efforts to increase nurses' confidence and skills in achieving SGC.