» Articles » PMID: 17623086

Tight Glycaemic Control: a Prospective Observational Study of a Computerised Decision-supported Intensive Insulin Therapy Protocol

Overview
Journal Crit Care
Specialty Critical Care
Date 2007 Jul 12
PMID 17623086
Citations 23
Authors
Affiliations
Soon will be listed here.
Abstract

Introduction: A single centre has reported that implementation of an intensive insulin protocol, aiming for tight glycaemic control (blood glucose 4.4 to 6.1 mmol/l), resulted in significant reduction in mortality in longer stay medical and surgical critically ill patients. Our aim was to determine the degree to which tight glycaemic control can be maintained using an intensive insulin therapy protocol with computerized decision support and to identify factors that may be associated with the degree of control.

Methods: At a general adult 22-bed intensive care unit, we implemented an intensive insulin therapy protocol in mechanically ventilated patients, aiming for a target glucose range of 4.4 to 6.1 mmol/l. The protocol was integrated into the computerized information management system by way of a decision support program. The time spent in each predefined blood glucose band was estimated, assuming a linear trend between measurements.

Results: Fifty consecutive patients were investigated, involving analysis of 7,209 blood glucose samples, over 9,214 hours. The target tight glycaemic control band (4.4 to 6.1 mmol/l) was achieved for a median of 23.1% of the time that patients were receiving intensive insulin therapy. Nearly half of the time (median 48.5%), blood glucose was within the band 6.2 to 7.99 mmol/l. Univariate analysis revealed that body mass index (BMI), Acute Physiology and Chronic Health Evaluation (APACHE) II score and previous diabetes each explained approximately 10% of the variability in tight glycaemic control. BMI and APACHE II score explained most (27%) of the variability in tight glycaemic control in the multivariate analysis, after adjusting for age and previous diabetes.

Conclusion: Use of the computerized decision supported intensive insulin therapy protocol did result in achievement of tight glycaemic control for a substantial percentage of each patient's stay, although it did deliver 'normoglycaemia' (4.4 to about 8 mmol/l) for nearly 75% of the time. Tight glycaemic control was difficult to achieve in critically ill patients using this protocol. More sophisticated methods such as continuous blood glucose monitoring with automated insulin and glucose infusion adjustment may be a more effective way to achieve tight glycaemic control. Glycaemia in patients with high BMI and APACHE II scores may be more difficult to control using intensive insulin therapy protocols. Trial registration number 05/Q0505/1.

Citing Articles

Monitoring the Impact of Aggressive Glycemic Intervention during Critical Care after Cardiac Surgery with a Glycemic Expert System for Nurse-Implemented Euglycemia: The MAGIC GENIE Project.

Rao R, Perreiah P, Cunningham C J Diabetes Sci Technol. 2021; 15(2):251-264.

PMID: 33650454 PMC: 8256075. DOI: 10.1177/1932296821995568.


An in silico method to identify computer-based protocols worthy of clinical study: An insulin infusion protocol use case.

Wong A, Pielmeier U, Haug P, Andreassen S, Morris A J Am Med Inform Assoc. 2015; 23(2):283-8.

PMID: 26228765 PMC: 5009926. DOI: 10.1093/jamia/ocv067.


International multidisciplinary consensus conference on multimodality monitoring: ICU processes of care.

McNett M, Horowitz D Neurocrit Care. 2014; 21 Suppl 2:S215-28.

PMID: 25208666 DOI: 10.1007/s12028-014-0020-x.


Computerization of the Yale insulin infusion protocol and potential insights into causes of hypoglycemia with intravenous insulin.

Marvin M, Inzucchi S, Besterman B Diabetes Technol Ther. 2013; 15(3):246-52.

PMID: 23289409 PMC: 3696925. DOI: 10.1089/dia.2012.0277.


On the management of hyperglycaemia in critically ill patients undergoing surgery.

Nomikos I, Kyriazi M, Vamvakopoulou D, Sidiropoulos A, Apostolou A, Kyritsaka A J Clin Med Res. 2012; 4(4):237-41.

PMID: 22870170 PMC: 3409618. DOI: 10.4021/jocmr604w.


References
1.
Plank J, Blaha J, Cordingley J, Wilinska M, Chassin L, Morgan C . 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(2):271-6. DOI: 10.2337/diacare.29.02.06.dc05-1689. View

2.
Vogelzang M, Zijlstra F, Nijsten M . Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit. BMC Med Inform Decis Mak. 2005; 5:38. PMC: 1334184. DOI: 10.1186/1472-6947-5-38. View

3.
Malhotra A . Intensive insulin in intensive care. N Engl J Med. 2006; 354(5):516-8. PMC: 2287193. DOI: 10.1056/NEJMe058304. View

4.
Shaw G, Chase J, Wong J, Lin J, Lotz T, Le Compte A . Rethinking glycaemic control in critical illness--from concept to clinical practice change. Crit Care Resusc. 2006; 8(2):90-9. View

5.
Turina M, Christ-Crain M, Polk Jr H . Diabetes and hyperglycemia: strict glycemic control. Crit Care Med. 2006; 34(9 Suppl):S291-300. DOI: 10.1097/01.CCM.0000231887.84751.04. View