Achieving durable glucose control in the intensive care unit without hypoglycaemia: A new practical IV insulin protocol

Department of Medicine, Huntington Hospital, Huntington, NY 11743, USA.
Diabetes/Metabolism Research and Reviews (Impact Factor: 3.55). 01/2007; 23(1):49-55. DOI: 10.1002/dmrr.673
Source: PubMed


Hyperglycaemia occurs in a substantial portion of critically ill patients in our intensive care units. Near normalization of elevated blood glucose levels with IV insulin may improve outcome. However, currently published IV insulin protocol are not ideal; most are relatively complex and often result in hypoglycaemia. We designed a protocol that would be practical to use while incorporating the necessary complexities required to achieve good glucose control, coupled with a low incidence hypoglycaemia.
The essential part of the protocol is a matrix specifying the amount by which an insulin flow rate is to be changed. The intersection of the current and the previous blood glucose values on the matrix locates the appropriate cell containing the required change in insulin flow rate. No additional calculations or tables are required.
The initial glucose level obtained by blood glucose meter (BGM) averaged 253.5 +/- 95.6 mg/dL and fell below 140 within 9.3 h on the protocol. The average BGM on the protocol was 133.5 +/- 43.9 mg/dL. Only 0.09% of all glucose values were <40 mg/dL and insulin had to be held only 2.2% of the time on the protocol. Physician input was not required and nursing accuracy in applying the protocol was greater than 94%. This protocol has been adopted as the default IV insulin protocol for the NorthShore-LIJ Health System and several other medical centers.
A practical IV insulin protocol that has been extensively tested is presented. The protocol has been implemented at multiple institutions indicating its ease of use and excellent results.

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    • "Since the introduction of intensive insulin therapy, different algorithms and control systems aiming at effective and safe glucose control have been proposed [19]. These can range from written guidelines [12,13] and protocols [37-40] to elementary [41,42] and advanced computerized algorithms [43-48]. We used an advanced computer algorithm belonging to the family of model predictive control. "
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    ABSTRACT: Closed-loop (CL) systems modulate insulin delivery according to glucose levels without nurse input. In a prospective randomized controlled trial, we evaluated the feasibility of an automated closed-loop approach based on subcutaneous glucose measurements in comparison to a local sliding scale insulin therapy protocol. 24 critically ill adults (predominantly trauma and neuroscience patients) with hyperglycaemia (glucose [greater than or equal to] 10 mmol/l) or already receiving insulin therapy were randomized to receive either fully automated closed-loop therapy (model predictive control algorithm directing insulin and 20% dextrose infusion based on FreeStyle Navigator continuous subcutaneous glucose values, N = 12) or a local protocol (N = 12) with intravenous sliding scale insulin, over 48 hours. The primary endpoint was percentage time when arterial blood glucose was between 6.0 and 8.0 mmol/l. Time when glucose was in target was significantly increased during closed-loop therapy (54.3% [44.1-72.8] vs. 18.5% [0.1-39.9], P=0.001; median [interquartile range]) and so was time in wider targets 5.6-10.0 mmol/l and 4.0-10.0 mmol/l (P[less than or equal to]0.002) reflecting a reduced glucose exposure above 8 and 10 mmol/l (P[less than or equal to]0.002). Mean glucose was significantly lower during CL (7.8 [7.4-8.2] vs. 9.1 [8.3-13.0] mmol/l, P=0.001) without hypoglycaemia (<4 mmol/l) during either therapy. Fully automated closed loop control based on subcutaneous glucose measurements is feasible and may provide efficacious and hypoglycaemia-free glucose control in critically ill adults. Trial Registration: Identifier - NCT01440842.
    Critical care (London, England) 07/2013; 17(4):R159. DOI:10.1186/cc12838 · 4.48 Impact Factor
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    • "These protocols can be generic guidelines on paper, which allow intuitive and anticipative decision making by the nurses (12,13). Alternatively, the protocols can be based on elementary algorithms, either on paper or computerized, which allow less freedom for the nursing staff (14–26). In addition, more complex computer algorithms have been developed to allow effective and safe TGC (27,28). "
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    ABSTRACT: OBJECTIVE Tight blood glucose control (TGC) in critically ill patients is difficult and labor intensive, resulting in poor efficacy of glycemic control and increased hypoglycemia rate. The LOGIC-Insulin computerized algorithm has been developed to assist nurses in titrating insulin to maintain blood glucose levels at 80-110 mg/dL (normoglycemia) and to avoid severe hypoglycemia (<40 mg/dL). The objective was to validate clinically LOGIC-Insulin relative to TGC by experienced nurses.RESEARCH DESIGN AND METHODS The investigator-initiated LOGIC-1 study was a prospective, parallel-group, randomized, controlled clinical trial in a single tertiary referral center. A heterogeneous mix of 300 critically ill patients were randomized, by concealed computer allocation, to either nurse-directed glycemic control (Nurse-C) or algorithm-guided glycemic control (LOGIC-C). Glycemic penalty index (GPI), a measure that penalizes both hypoglycemic and hyperglycemic deviations from normoglycemia, was the efficacy outcome measure, and incidence of severe hypoglycemia (<40 mg/dL) was the safety outcome measure.RESULTSBaseline characteristics of 151 Nurse-C patients and 149 LOGIC-C patients and study times did not differ. The GPI decreased from 12.4 (interquartile range 8.2-18.5) in Nurse-C to 9.8 (6.0-14.5) in LOGIC-C (P < 0.0001). The proportion of study time in target range was 68.6 ± 16.7% for LOGIC-C patients versus 60.1 ± 18.8% for Nurse-C patients (P = 0.00016). The proportion of severe hypoglycemic events was decreased in the LOGIC-C group (Nurse-C 0.13%, LOGIC-C 0%; P = 0.015) but not when considered as a proportion of patients (Nurse-C 3.3%, LOGIC-C 0%; P = 0.060). Sampling interval was 2.2 ± 0.4 h in the LOGIC-C group versus 2.5 ± 0.5 h in the Nurse-C group (P < 0.0001).CONCLUSIONS Compared with expert nurses, LOGIC-Insulin improved efficacy of TGC without increasing rate of hypoglycemia.
    Diabetes care 09/2012; 36(2). DOI:10.2337/dc12-0584 · 8.42 Impact Factor
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    • "Lonergan et al. [18] modeled these dynamics and limited infusion rates accordingly. In contrast, glycaemic control protocols have been published that utilise maximum insulin infusion rates of 10 or 20 units per hour [2] [19] or have no limit [9]. "
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    ABSTRACT: Consistent tight blood sugar control in critically ill patients has proven elusive. Properly accounting for the saturation of insulin action and reducing the need for frequent measurements are important aspects in intensive insulin therapy. This paper presents a composite metabolic model, 'Glucosafe', that integrates models and parameters from normal physiology and accounts for the reduced rate of glucose gut absorption and saturation of insulin action in patients with reduced insulin sensitivity. Particularly, two different sites of reduced insulin sensitivity, before and after the non-linearity of insulin action, are explored with this model. These approaches are assessed based on the model's accuracy in retrospectively predicting blood glucose measurements of 10 randomly chosen, hyperglycemic intensive care patients. For each patient, median absolute percent error is <25% for prediction times < or = 270min and modelling reduced insulin sensitivity after the non-linearity, compared to <29% for modelling reduced insulin sensitivity before the non-linearity. Scaling the insulin effect (after the non-linearity) is a suitable assumption in this model structure. These results are preliminary and subject to further and more extensive validation of the model's capability to predict the longer term (>2h) blood glucose excursion in critically ill patients.
    Computer methods and programs in biomedicine 07/2009; 97(3):211-22. DOI:10.1016/j.cmpb.2009.06.004 · 1.90 Impact Factor
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