PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of diacareAmerican Diabetes AssociationSubscribeSearchDiabetes Care Journal
 
Diabetes Care. 2009 May; 32(5): 757–761.
Published online 2009 February 5. doi:  10.2337/dc08-1851
PMCID: PMC2671097

Comparison of Three Protocols for Tight Glycemic Control in Cardiac Surgery Patients

Jan Blaha, MD,1 Petr Kopecky, MD,1 Michal Matias, MD,1 Roman Hovorka, PHD,2 Jan Kunstyr, MD, PHD,1 Tomas Kotulak, MD,3 Michal Lips, MD,1 David Rubes, MD,1 Martin Stritesky, MD, PHD,1 Jaroslav Lindner, MD, PHD,4 Michal Semrad, MD, PHD,4 and Martin Haluzik, MD, DSC5

Abstract

OBJECTIVE

We performed a randomized trial to compare three insulin-titration protocols for tight glycemic control (TGC) in a surgical intensive care unit: an absolute glucose (Matias) protocol, a relative glucose change (Bath) protocol, and an enhanced model predictive control (eMPC) algorithm.

RESEARCH DESIGN AND METHODS

A total of 120 consecutive patients after cardiac surgery were randomly assigned to the three protocols with a target glycemia range from 4.4 to 6.1 mmol/l. Intravenous insulin was administered continuously or in combination with insulin boluses (Matias protocol). Blood glucose was measured in 1- to 4-h intervals as requested by the protocols.

RESULTS

The eMPC algorithm gave the best performance as assessed by time to target (8.8 ± 2.2 vs. 10.9 ± 1.0 vs. 12.3 ± 1.9 h; eMPC vs. Matias vs. Bath, respectively; P < 0.05), average blood glucose after reaching the target (5.2 ± 0.1 vs. 6.2 ± 0.1 vs. 5.8 ± 0.1 mmol/l; P < 0.01), time in target (62.8 ± 4.4 vs. 48.4 ± 3.28 vs. 55.5 ± 3.2%; P < 0.05), time in hyperglycemia >8.3 mmol/l (1.3 ± 1.2 vs. 12.8 ± 2.2 vs. 6.5 ± 2.0%; P < 0.05), and sampling interval (2.3 ± 0.1 vs. 2.1 ± 0.1 vs. 1.8 ± 0.1 h; P < 0.05). However, time in hypoglycemia risk range (2.9–4.3 mmol/l) in the eMPC group was the longest (22.2 ± 1.9 vs. 10.9 ± 1.5 vs. 13.1 ± 1.6; P < 0.05). No severe hypoglycemic episode (<2.3 mmol/l) occurred in the eMPC group compared with one in the Matias group and two in the Bath group.

CONCLUSIONS

The eMPC algorithm provided the best TGC without increasing the risk of severe hypoglycemia while requiring the fewest glucose measurements. Overall, all protocols were safe and effective in the maintenance of TGC in cardiac surgery patients.

The landmark Leuven Study (1) demonstrated that intensive insulin therapy targeted to maintain normoglycemia between 4.4 and 6.1 mmol/l reduced mortality in the surgical intensive care unit (ICU) and markedly decreased the frequency of organ complications associated with critical illness. Other studies confirmed these findings, particularly in cardiac surgery patients (25), whereas others still questioned the safety and universality of the beneficial effect of tight glycemic control (TGC) in different subgroups of critically ill patients (69).

In principle, the need to maintain euglycemia in the ICU has been widely accepted. Numerous insulin protocols of variable effectiveness have been developed (5,1012). Most of these protocols require considerable ICU staff training and experience, and some call for intuitive decisions. In consequence, some protocols may lead to inconsistent application, mistakes, or misinterpretation. Furthermore, frequent glucose measurements, essential for TGC, may markedly increase the workload of ICU nursing staff (13,14).

Most newly developed glucose management protocols are compared against the so-called standard protocols with which adequate glucose control is not usually achieved. Head-to-head comparison of specifically designed TGC protocols (1518) is not available, although such information is of the highest importance from the practical point of view.

We carried out such a direct comparison of three different, effective, and published TGC management protocols with a major focus on TGC effectiveness and safety. We performed a monocenter randomized trial and compared a protocol based on the absolute glucose value, the Matias protocol (15,17); a protocol based on the relative glucose change, the Bath protocol (19); and a computer-based model predictive control algorithm with variable sampling rate (eMPC) (16) developed within the 6th Framework Programme e-Health Project “Closed Loop Insulin Infusion for Critically Ill Patients.”

RESEARCH DESIGN AND METHODS

Patients, aged 18–90 years, admitted to the postoperative ICU after elective cardiac surgery, were included. Written informed consent was obtained from all participants before being enrolled in the study. The study was approved by the Human Ethical Review Committee, 1st Faculty of Medicine and General University Hospital, Prague, Czech Republic, and was performed in accordance with the guidelines proposed in the Declaration of Helsinki. Exclusion criteria were insulin allergy, mental incapacity, and language barrier.

We enrolled 120 consecutive patients; 40 patients were randomly assigned into the Matias, Bath, and eMPC protocol treatment groups regardless of their preoperative or admission glycemia levels. The TGC protocols were started after patients' admission to the ICU after arrival from the operating theater and lasted until the end of the ICU stay. Because the duration of the ICU stay and the total monitoring time differed among patients, only data for up to 48 h were used for the comparison of the protocols. Forty-eight hours of ICU stay were accomplished in 109 of 120 patients included in the study. The mean follow-up time was 46.7 ± 0.5 h for the Matias, 45.7 ± 0.7 h for the Bath, and 47.2 ± 0.3 h for the eMPC protocols, respectively.

Target glucose range

The target glucose range was 4.4–6.1 mmol/l, which has been demonstrated to reduce mortality and morbidity (1). No routine protocol was used for perioperative glycemia control.

Blood glucose monitoring, insulin treatment regimens, and nutrition

Blood glucose was monitored, and insulin was administered according to the rules/suggestions of each protocol. Undiluted arterial blood for measurement of blood glucose was drawn from an arterial line, inserted for routine monitoring procedures. Whole blood glucose was analyzed by a standard point-of-care testing device (ABL 700; Radiometer Medical, Copenhagen, Denmark).

Insulin (Actrapid HM; Novo Nordisk, Baegsvard, Denmark) was given in a central venous line as a continuous infusion (Bath and eMPC protocols) or as a combination of a continuous infusion and boluses (Matias protocol). A standard concentration of 50 IU of insulin in 50 ml 0.9% NaCl was used. In all patients, infusion of a 10% glucose solution was initiated upon admission to ICU with a glucose dose of 2.5 g/kg ideal body weight (height in centimeters minus 100) per hour and lasted for 18 h, when normal oral food intake was started. In patients receiving mechanical ventilation, the glucose infusion lasted for 48 h, and then standard enteral nutrition was initiated.

Clinical parameters and patients' clinical history data including age, sex, race, height, weight, BMI, EuroSCORE (the European System for Cardiac Operative Risk Evaluation that identifies a number of risk factors, which help to predict mortality from cardiac surgery), history of diabetes, and type of surgery were collected prospectively. Adverse events, medication, and nutrition were continuously monitored and documented.

Outcome measures

Parameters for the assessment of the effectiveness of different TGC management protocols were as follows: entire study average glycemia level; time to the target range of 4.4–6.1 mmol/l (80–110 mg/dl); average glucose level after the target range was reached; number of hypoglycemic episodes (blood glucose <2.9 mmol/l); time within the target range; time between 2.9 and 4.3 mmol/l (54–70 mg/dl) with no clinical manifestations of hypoglycemia but indicating risk for hypoglycemia; time between 6.2 and 8.3 mmol/l (110–150 mg/dl) indicating risk of hyperglycemia; time in >8.3 mmol/l (150 mg/dl) indicating hyperglycemia; and sampling interval indicating workload. The percentage of time in the target range was calculated as number of values in the target range in each patient/number of measurements × 100.

The three TGC management protocols were implemented by the ICU nursing staff with supervision by ICU doctors as required. Protocol training was performed by the ICU physician and a departmental nurse, usually individually, at bedside. A 3-month period was devoted to the implementation of the Bath insulin protocol, whereas the Matias and eMPC protocols have been used in the ICU previously.

Statistical analysis

Statistical analysis was performed using STATISTICA software (StatSoft, Tulsa, OK). The protocols were compared using ANOVA followed by a Holm-Sidak test, Student's t test, or Mann-Whitney U test as appropriate. The significance level was set at P = 0.05.

Description of TGC glucose management protocols

The TGC glucose management protocols are described in online appendices 1–3, available at http://care.diabetesjournals.org/cgi/content/full/dc08-1851/DC1.

RESULTS

The baseline characteristics of the study patients at the time of admission to the ICU are listed in Table 1. The study groups did not differ with respect to age, BMI, EuroSCORE, type of surgery, baseline blood glucose level, or occurrence of diabetes. Blood glucose control characteristics are shown in Table 2 and Figs. 1 and and2,2, respectively.

Table 1
Baseline characteristics of patients after cardiac surgery at the time of admission to the ICU
Table 2
Study blood glucose control data
Figure 1
Blood glucose concentrations and time to target range, expressed as means ± SEM, in patients after cardiac surgery controlled by the Matias, Bath, and eMPC protocols.
Figure 2
Blood glucose concentrations, expressed as means ± SEM, in patients after cardiac surgery, controlled by the Matias, Bath, and eMPC protocols during the entire 48-h postoperative period. Average time within the target range was 38.2 ± ...

Table 2 demonstrates significantly better blood glucose control was achieved in the eMPC group compared with the Matias and the Bath groups: entire study average glucose (5.9 ± 0.2 vs. 6.7 ± 0.1 vs. 6.5 ± 0.2 mmol/l; P < 0.05) and percentage of time within the target range (46.6 ± 3.0 vs. 38.2 ± 2.9 vs. 39.7 ± 3.1%, P < 0.05). To better describe and compare TGC associated with each protocol, we divided glucose profiles into the period before reaching the target range (Table 2 and Fig. 1) and the period after reaching the target range (Table 2). With respect to the time to target range, the eMPC protocol performed significantly better than the Matias and Bath protocols (Table 2; Fig. 2). In the period after reaching the target range, the eMPC algorithm showed superior performance relative to the Matias and Bath protocols with respect to average glycemia (5.2 ± 0.1 vs. 6.2 ± 0.1 vs. 5.8 ± 0.1 mmol/l; P < 0.05), time in target range (62.8 ± 4.4 vs. 48.4 ± 3.2 vs. 55.5 ± 3.2% of time; respectively, P < 0.05), time in risk of hyperglycemia (13.7 ± 2.6 vs. 27.5 ± 2.2 vs. 24.5 ± 2.4% of time; P < 0.05), and time in hyperglycemia (1.3 ± 1.2 vs. 12.8 ± 2.2 vs. 6.5 ± 2.0% of time; P < 0.05) (Table 2).

The average insulin infusion rate and the total insulin dose throughout the entire study were significantly higher in the eMPC compared with the Matias and Bath protocols (mean insulin rate 5.1 ± 1.0 vs. 3.7 ± 0.4 vs. 4.1 ± 0.5 IU/h; P < 0.05). The average sampling interval, as an indicator of workload, was significantly shorter in the Bath versus both the Matias and eMPC groups (Table 2). Two episodes of severe hypoglycemia defined as glycemia <2.3 mmol/l were observed during the study in the Bath group and one episode in the Matias group, whereas no such episode occurred in the eMPC group. All three hypoglycemic episodes were classified as “asymptomatic” and were not related to established major risk factors of ICU hypoglycemia such as nutritional interruption, delayed glucose measurement, or drug administration.

CONCLUSIONS

In the present study we compared the performance and safety of three insulin-titration protocols for TGC in the postoperative period in cardiac surgery patients. We showed that the most satisfactory glucose control was achieved with a computer-based eMPC algorithm, whereas the use of the relative glucose value–based Bath protocol resulted in less satisfactory glucose control. The absolute glucose value–based algorithm, the Matias protocol, showed the least satisfactory performance. Importantly, all three protocols were reasonably safe. Only three severe hypoglycemic episodes (blood glucose <2.3 mmol/l) occurred throughout the entire study. Strikingly, no such episode was noted in the eMPC group that achieved the best glucose control among the three protocols.

The results of our study further underscore the fact that the ability to correctly implement a glucose management protocol is the key prerequisite to successful and safe glucose control in critically ill patients. Our ICU has >6 years experience with the use of the Matias protocol and 4 years' experience with testing the eMPC algorithm, whereas the Bath protocol has not been used in our center before. However, after a 3-month implementation period, our ICU staff was able to successfully use all three protocols without any major problems or safety concerns. This experience differs markedly from the two large multicenter studies with TGC, the Glucontrol Study and the Volume Substitution and Insulin Therapy in Severe Sepsis (VISEP) Study, that were discontinued because of excessive risk of hypoglycemia. It is possible that insufficient time for insulin protocol implementation and the lack of previous experiences with TGC markedly influenced the outcomes of both studies (7,9,20,21).

To our knowledge, our study is the first to compare head-to-head three well-documented and widely used TGC protocols. We used the simplest and possibly the most straightforward way to analyze the data and calculated the average blood glucose and the percentage of time within the target range. For the sake of clarity and transparency, we did not use any data interpolation and/or other more sophisticated data analysis tools.

Each protocol tested in our study represented a principally different approach to glucose control. The Matias algorithm differs from the other two protocols by combining continuous intravenous insulin infusion with intravenous insulin boluses. This approach might have a possible advantage in the ability to quickly achieve the target range. Interestingly, although the Matias protocol achieved the target range ~1.5 h earlier than the Bath protocol, it was still significantly worse than the computer-based eMPC algorithm that achieved the target range 2 h earlier than the Matias protocol without using intravenous insulin boluses. The superior performance of the eMPC algorithm was not accompanied by a higher risk of hypoglycemia. In fact, the opposite was true because no severe hypoglycemia was detected in the eMPC algorithm group (Table 2).

The principal difference between the Bath protocol and the Matias protocol is that the insulin dose is based on the relative change of the blood glucose between the two measurements rather than on the absolute glucose concentration itself. A major advantage of the Bath protocol may be that relative blood glucose change may give a better indication of the high variability of patients' insulin resistance and the nature and severity of their illness especially in comparison with the Matias protocol. A direct comparison of the Bath algorithm with absolute glucose value–based Matias protocol showed slightly better performance of the former with significantly lower mean blood glucose and time in hyperglycemia after reaching the target range. Conversely, the time to reach the target range was longer and the sampling interval was shorter with the Bath protocol than with the Matias protocol.

The eMPC protocol also uses the rate of change in blood glucose, although this is not carried out in an explicit manner as with the Bath protocol. Instead, the eMPC algorithm derives insulin sensitivity and other physiologically relevant parameters from up to a 10-h blood glucose profile. The eMPC algorithm achieved significantly better results compared with the other two protocols in the majority of the most important parameters (Table 2): in effectiveness (time to target range), in efficiency of glycemia management after reaching the target range (mean glycemia, time in target range, time in risk of hyperglycemia, and time in hyperglycemia), and in sampling interval. Improved glucose control with the use of the eMPC algorithm was accompanied by a longer time within the range at higher risk of hypoglycemia, but the occurrence of moderate or severe hypoglycemia was zero in the eMPC group, suggesting the high level of safety of this protocol.

Overall, compared with some of the previously published studies, all three protocols were able to achieve reasonably tight glucose control without an excessive risk of hypoglycemia and/or other complications (21). The low rate of hypoglycemic events and the overall results in our study could have been partially due to a relatively high constant rate of glucose infusion administered throughout the study. A constant high-rate glucose infusion is expected to accelerate glucose turnover and the overall system response. In consequence, this feature of the protocol should improve the stability of glucose control, especially under the routine protocol, whereas the eMPC protocol should be less affected. It is thus possible that the overall outcome of the three protocols tested would differ under the conditions of a lower parenteral glucose administration, and the results thus cannot be directly applicable to other patient populations.

From the user point of view, the major difference between the eMPC and other protocols is the nonfixed sampling interval of the eMPC algorithm. In typical ICU settings, there is usually a time window within which any therapeutic and/or other procedure including TGC should occur. In reality, such a standard “fixed” interval then may vary considerably. The eMPC algorithm, with its bedside screen interface continuously showing time to next measurement, emphasizes the importance of on-time sampling. The nurses then tend to adapt their activities so that they can fulfill eMPC instructions within the required time frame. For the sake of our comparative study, we asked our nurses to be as accurate as possible in fulfilling all requirements of the algorithms, especially with respect to timing of blood glucose measurements. Thus, the study conditions for both the Matias and Bath algorithms could have been somehow better compared with a “real-life” situation.

Because two of the three protocols tested were partially implemented in our ICU previously, our study does not answer the question of how difficult it is to implement the protocols from the very beginning. The 3-month implementation period was long enough to safely use the Bath protocol under our ICU settings. We suggest that an appropriate implementation period and previous experience of our ICU staff with TGC may be the reasons that the quality and safety of glucose control in our study were significantly better than the results of most of the previously published studies (2225).

In summary, we demonstrate that the computer-based eMPC algorithm with a variable sampling interval is more effective in achieving and maintaining TGC in patients after cardiac surgery than both the relative glucose levels change–based Bath protocol and the absolute glucose value–based Matias protocol. Overall, all three protocols were able to achieve reasonable blood glucose control without any major side effects.

Supplementary Material

Online-Only Appendix:

Acknowledgments

This work was supported by Charles University in Prague (Grant 44407); by research project MSM0021620814 from the Czech Ministry of Education, Youth, and Sports; and by the National Institute for Health Research Cambridge Biomedical Research Centre.

R.H. has received consultancy fees from BBraun. No other potential conflicts of interest relevant to this article were reported.

We thank all intensive care unit personnel for extending their workload during the implementation and study period.

Preliminary data were presented at the Annual Meeting of the European Association of Cardiothoracic Anesthesiologists, Antalya, Turkey, 11–14 June 2008.

Footnotes

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

References

1. van den Berghe G, Wouters P, Weekers F, et al. : Intensive insulin therapy in the critically ill patients. N Engl J Med 2001; 345: 1359– 1367 [PubMed]
2. Finney SJ, Zekveld C, Elia A, et al. : Glucose control and mortality in critically ill patients. JAMA 2003; 290: 2041– 2047 [PubMed]
3. Furnary AP, Gao G, Grunkemeier GL, et al. : Continuous insulin infusion reduces mortality in patients with diabetes undergoing coronary artery bypass grafting. J Thorac Cardiovasc Surg 2003; 125: 1007– 1021 [PubMed]
4. Gale SC, Sicoutris C, Reilly PM, et al. : Poor glycemic control is associated with increased mortality in critically ill trauma patients. Am Surg 2007; 73: 454– 460 [PubMed]
5. Krinsley JS.: Effect of an intensive glucose management protocol on the mortality of critically ill adult patients. Mayo Clin Proc 2004; 79: 992– 1000 [PubMed]
6. Gandhi GY, Nuttall GA, Abel MD, et al. : Intensive intraoperative insulin therapy versus conventional glucose management during cardiac surgery: a randomized trial. Ann Intern Med 2007; 146: 233– 243 [PubMed]
7. Devos P.: Glucontrol study: Comparing the effects of two glucose control regimens by insulin in intensive care unit patients [article online], 2005. Available at http://clinicaltrials.gov/ct2/show/NCT00107601 Accessed 24 September 2008
8. Treggiari MM, Karir V, Yanez ND, et al. : Intensive insulin therapy and mortality in critically ill patients. Crit Care 2008; 12: R29. [PMC free article] [PubMed]
9. Reinhart K, Deufel T, Löffler M.: Efficacy of volume substitution and insulin therapy in severe sepsis (VISEP trial) [article online], 2005. Available at http://clinicaltrials.gov/ct2/show/NCT00135473 Accessed 24 September 2008
10. Zimmerman CR, Mlynarek ME, Jordan JA, et al. : An insulin infusion protocol in critically ill cardiothoracic surgery patients. Ann Pharmacother 2004; 38: 1123– 1129 [PubMed]
11. Goldberg PA, Siegel MD, Sherwin RS, et al. : Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit. Diabetes Care 2004; 27: 461– 467 [PubMed]
12. Kanji S, Singh A, Tierney M, et al. : Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults. Intens Care Med 2004; 30: 804– 810 [PubMed]
13. Aragon D.: Evaluation of nursing work effort and perceptions about blood glucose testing in tight glycemic control. Am J Crit Care 2006; 15: 370– 377 [PubMed]
14. Malesker MA, Foral PA, McPhillips AC, et al. : An efficiency evaluation of protocols for tight glycemic control in intensive care units. Am J Crit Care 2007; 16: 589– 598 [PubMed]
15. Hovorka R, Kremen J, Blaha J, et al. : Blood glucose control by a model predictive control algorithm with variable sampling rate versus a routine glucose management protocol in cardiac surgery patients: a randomized controlled trial. J Clin Endocrinol Metab 2007; 92: 2960– 2964 [PubMed]
16. Pachler C, Plank J, Weinhandl H, et al. : Tight glycaemic control by an automated algorithm with time-variant sampling in medical ICU patients. Intensive Care Med 2008; 34: 1224– 1230 [PubMed]
17. Plank J, Blaha J, Cordingley J, et al. : Multicentric, randomized, controlled trial to evaluate blood glucose control by the model predictive control algorithm versus routine glucose management protocols in intensive care unit patients. Diabetes Care 2006; 29: 271– 276 [PubMed]
18. Blaha J, Kopecky P, Kotulak T, et al. : Blood glucose control in cardiac surgery patients: a comparative study of different insulin protocols. J Cardiothorac Vasc Anesth 2008; 22( Suppl. 3): S23
19. Laver S, Preston S, Turner D, et al. : Implementing intensive insulin therapy: development and audit of the Bath insulin protocol. Anaesth Intensive Care 2004; 32: 311– 316 [PubMed]
20. Lacherade J-C, Outin H, De Jonghe B, et al. : Insulin and pentastarch for severe sepsis. N Engl J Med 2008; 358: 2071– 2075 [PubMed]
21. Brunkhorst FM, Engel C, Bloos F, et al. : Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med 2008; 358: 125– 139 [PubMed]
22. Chase JG, Shaw G, Le Compte A, et al. : Implementation and evaluation of the SPRINT protocol for tight glycaemic control in critically ill patients: a clinical practice change. Crit Care 2008; 12: R49. [PMC free article] [PubMed]
23. Lecomte P, Foubert L, Nobels F, et al. : Dynamic tight glycemic control during and after cardiac surgery is effective, feasible, and safe. Anesth Analg 2008; 107: 51– 58 [PubMed]
24. Saager L, Collins GL, Burnside B, et al. : A randomized study in diabetic patients undergoing cardiac surgery comparing computer-guided glucose management with a standard sliding scale protocol. J Cardiothorac Vasc Anesth 2008; 22: 377– 382 [PubMed]
25. Shulman R, Finney SJ, O'Sullivan C, et al. : Tight glycaemic control: a prospective observational study of a computerised decision-supported intensive insulin therapy protocol. Crit Care 2007; 11: R75. [PMC free article] [PubMed]

Articles from Diabetes Care are provided here courtesy of American Diabetes Association