- Open Access
A systematic review on quality indicators for tight glycaemic control in critically ill patients: need for an unambiguous indicator reference subset
Critical Care volume 12, Article number: R139 (2008)
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.
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.
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.
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.
Hyperglycaemia is frequently encountered in critically ill patients [1, 2]. Even critically ill patients without diabetes develop hyperglycaemia. Until recently it was common practice to treat only marked hyperglycaemia in these patients, because hyperglycaemia was considered to be an adaptive response to critical illness . Blood glucose control aiming to achieve normoglycaemia (blood glucose levels of 80 to 110 mg/dl), frequently referred to as 'tight glycaemic control' (TGC), decreases mortality and morbidity in critically ill patients [4, 5]. It is the lowered blood glucose level (BGL) rather than the insulin dose that is related to reduced mortality and morbidity . Attempts at achieving TGC, however, are not perfect and carry a risk for hypoglycaemia [4, 5].
Several observational studies have reported on the quality of the glucose control process itself. The results and conclusions of these studies are contradictory . Some show that the protocol prescribing the control process improves blood glucose control whereas others do not. Apart from differences in case-mix and in the associated therapy (for example, steroid therapy), two important issues hamper comparability between studies. The first impediment is the existing variability in the intervention's evaluation. The following interpretations, based on intention and on process, are both possible: the patient is intended to be treated according to a TGC protocol (for example, when a specific intensive care unit is designated an intervention group), independent of actual adherence to the glucose control protocol; or the characterization of the patient's blood glucose regulation is evaluated according to the actual intensity of blood glucose control. The latter interpretation requires agreement on the level of adherence to the TGC protocol in terms of timing of glucose measurements and insulin provision to qualify a patient as being on TGC. The second impediment concerns the variability in outcome measures; studies may not use a standard list of well defined indicators for evaluating the quality of glucose control. Work presented in this paper concerns this second impediment.
The objective of the present systematic review is to identify and summarize quality indicators for glucose control in published studies of TGC in critically ill patients. It also assesses the applicability of definitions of quality indicators and organizes the indicators into categories. This review may form a basis for future developments of a standard list of well defined indicators that may correlate with clinical outcomes or that reflect clinicians' intuition regarding the quality of a given regulatory process.
Materials and methods
We searched for relevant English language articles based on keywords in title, abstract and MeSH terms, using Ovid MEDLINE® and Ovid MEDLINE® In-Process (1950 to 31 December 2007). The final literature search was performed on 31 December 2007.
The following search strategy was used to identify the relevant articles. In the first stage we searched for 'glucose' and 'insulin'. In the second stage we limited the search using 'critical illness', 'critical care' or 'intensive care'. The results of these two stages were combined using the Boolean operator 'and'. Searching was supplemented by scanning the bibliographies of the identified articles.
Two reviewers independently examined all titles and abstracts. Discrepancies between the two reviewers were resolved by consensus involving a third reviewer. Articles were selected if they reported original data from a clinical trial or observational study conducted in critically ill adult patients, and only if one of their main objectives concerned the evaluation of quality of TGC, with or without implementing an explicitly specified protocol. A study was defined as evaluating a TGC protocol if the (implicit or explicit) protocol implied an upper target range. Adherence to the protocol did not influence whether the study was included. Opinion papers, surveys and letters were excluded. Studies employing glucose-insulin-potassium protocols were excluded because they are not originally designed to achieve TGC.
From the selected papers, the same two reviewers extracted data on TGC quality indicators (their definition and applicability). A quality indicator was defined as a measurable quantity of the TGC process that may, alone or in combination with other quantities, indicate some aspect of its quality. This includes, for example, mean (or median) BGLs as well as interpretations thereof in terms of counts of hyperglycaemic events. Discrepancies between the two reviewers were again resolved by consensus after involving the same third reviewer. We then attempted to categorize the quality indicators into coherent categories that capture their essence.
Searching the online databases yielded 486 articles. Initial screening of titles and abstracts resulted in 50 articles eligible for further full-text review. One additional article was identified by reviewing bibliographies, for a total of 51 articles. Based on the full-text review, two studies were excluded because they turned out not to address original data, leaving 49 articles for detailed analysis. Only five out of 49 studies reported on a target upper limit above 150 mg/dl.
Most papers evaluated multiple quality indicators. The median number of quality indicators was five (range 2 to 10).
By inspecting the quality indicators, we arrived at four indicator categories based on the following: zones (adverse-zone [hypoglycaemia and hyperglycaemia] and in-range zone); BGLs (for example, mean morning BGL); time intervals (for example, time elapsed until an event occurs or time spent in some state); and protocol characteristics (for instance, blood sampling frequency).
The categories are not mutually exclusive. For example, the amount of time during which a patient is regarded to be in a hyperglycaemic state is related to an adverse-zone as well as to time. Below, we list indicators, in decreasing order of reported frequency, and describe our findings about them.
Hypoglycaemia (adverse-zone and time categories)
Almost all studies reported at least one hypoglycaemia-related indicator (43/49 studies). Hypoglycaemia-related indicators address TGC safety. Because of its central position among the TGC quality indicators reported, hypoglycaemia is reported in Table 1 as an overall class of indicators.
Table 3 summarizes the concrete indicators used in this class along with their definitions.
In total, 15 different thresholds of BGL were used to define a hypoglycaemic event, varying from <40 mg/dl to <72 mg/dl. These included four different thresholds to define mild and moderate hypoglycaemia, and three different levels for defining severe or marked hypoglycaemia. Although a BGL <40 mg/dl was reported in eight studies as a hypoglycaemic event, 10 other studies considered this to be severe hypoglycaemia. One study reported severe hypoglycaemia only when a low BGL was accompanied by clinical symptoms such as sweating and decreased level of consciousness .
In some studies the number and/or percentage of BGL measurements below a given threshold and/or the number and percentage of patients with at least one measurement below this threshold were used as safety-related quality indicators. One article considered all measurements below the selected hypoglycaemic threshold value over a period of at least 1 hour to represent a single hypoglycaemic event; hence only when the BGL increased to within the normal range and then dropped below the hypoglycaemic threshold in a subsequent hour was it counted as a second hypoglycaemic event.
In other studies, the definition of hypoglycaemia was not clear, and it appeared that any measurement below the threshold was considered a hypoglycaemic event. Seven studies reported the number and/or percentage of dextrose injections when BGL was under a threshold value (using five different thresholds from 45 to 65 mg/dl) as quality indicators. Seven other indicators in this category were reported in at least one out of nine studies. Except for 'time from starting TGC till first hypoglycaemia', the other six indicators referred to the duration of hypoglycaemia or speed and quality of recovery after a hypoglycaemic event.
BGL summaries over time (BGL category)
BGL summaries were used in 41 out of 49 studies. BGL summaries correspond to the efficiency of TGC. This indicator was calculated in different ways and was represented as mean and/or median. In some studies the BGL itself was the unit of observation. In other studies the mean BGL per patient or per time unit (for example, 1 hour) was the unit of observation. One study reported the mean and median of all BGLs as well as the mean and median of BGL during each intensive insulin therapy run . 'Mean BGL' was also calculated as the area under the glucose/time curve divided by the total time per admission . As long as there is no continuous measurement of BGLs over time (provided at any time point), this measure reflects mean BGL when BGL indeed behaves according to the assumptions underlying the interpolation of consequent BGL measurements.
BGLs are usually summarized as their mean at various points in time or in time intervals, and they are presented in graphs that show mean BGL versus time. Some studies used quality indicators that refer to the mean or median BGL measured at the end of TGC, before and after achieving the target range, or after stopping TGC. Summary of morning BGL was reported in six studies. The time used to define morning BGL varied among the studies. BGL at starting TGC (reported in 14 out of 49 studies) was another frequently used indicator in this group.
Measurements and time in predefined BGL ranges (in-range zone and time categories)
Thirty-eight studies out of 49 examining the number of measurements and/or the time during which BGL was within a predefined range were reported. These indicators are intended to address TGC efficiency. In 31 out of 49 of these studies, the percentage of measurements within the predefined range was considered a proxy for the proportion of time in each predefined BGL range. In 12 out of 49 studies, the percentages of time during which BGL was within the predefined range were calculated, in most of them under the assumption that BGL was linear over time. As shown in Figure 1, under this assumption a straight line is drawn between each two consecutive BGL measurements, and the time to the intersection between the line and a threshold value defining the range was taken as the time spent within the predefined BGL range. Five studies used both the number/percentage of measurements within the predefined range as well as the time during which BGL was within the predefined range. The unit of observation differed also among these studies. Only in one study was the percentage of measurements within the predefined range calculated per patient, and the mean percentage per patient was reported .
Time to capture the defined BGL target (time category)
The time needed to capture the defined BGL target was reported in 25 out of 49 studies and was represented as mean or median.
Similar to the time-related indicators in the predefined BGL range subcategory, in most of these studies it was unclear how this indicator was calculated. Linearity of BGL over time was explicitly mentioned in some studies [12–15] and appeared to have been assumed in other studies. It is possible that some of the studies might have used the time needed to capture the actual first BGL measurement within the target range, instead of the interpolated value shown in Figure 1.
Hyperglycaemic indicators (adverse zone category)
Although the reduction in duration of a hyperglycaemic period forms a major goal of TGC, only 13 out of 49 studies explicitly mentioned how a hyperglycaemic event or indicator were defined. The threshold for considering a BGL measurement to be hyperglycaemic varied among studies from >150 to >250 mg/dl. Four different thresholds for hyperglycaemia and two thresholds for severe hyperglycaemia were reported. Six studies considered a BGL >180 mg/dl to be hyperglycaemic. Among the definitions, hyperglycaemia was identified as the percentage of time or of measurements above the threshold by seven studies [11, 16–21], by one study  as the percentage of patients with at least one measurement above the threshold per day, and by one study  as a BGL above the threshold for at least 2 hours.
The hyperglycaemic index of BGL was defined by determining the area under the curve of BGL over time that is above the hyperglycaemic threshold divided by time per patient [15, 17, 23–25]. The thresholds varied between these studies (from 108 to 207 mg/dl).
Sampling of BGL during the study, BGL at starting TGC and adherence to protocol (protocol category)
Sampling of BGL during the study was represented as mean or median of number of measurements per patient [11, 16, 17, 23–28], per patient treatment day [12, 15, 21, 22, 26, 29, 30] or over 2 days , sampling interval [13, 31–36], frequency per patient hour , percentage of patients with more than one measurement in a predefined time interval (2 hours) , or overall per day [12, 21], and as the percentage of time during which at least one measurement per 2 hours was taken .
Frequent BGL measurement is a key element in TGC, in order to steer the process in a timely manner. However, greater sampling frequency increases nursing and laboratory utilization . In some studies [14, 18, 19] the total number of BGL measurements was reported.
Adherence to protocol (reported in 12/49 studies) is another frequently used indicator. Evaluation of adherence to protocol mainly focused on the difference between the protocol-recommended time of the next BGL test and the actual time of testing.
The remaining indicators (19/30) were mentioned in fewer than six studies, and 12 of them in only one study.
On the whole, the included studies did not comment on why a specific group of indicators was selected, and – after further inspection – we could not find an association between indicator selection and patient population, disease or specification of the designed protocols.
We have identified, listed and categorized TGC quality indicators, as used in 49 studies. In our search for studies pertaining to TGC, we allowed any synonym, without limiting the search a priori. A limitation of our search is that we addressed only studies in which evaluation and quality measurement formed a main objective; we might therefore have missed some studies with a limited evaluation and quality measurement focus. In addition, frequency was used as the ordering principle for presenting and describing indicators. Although this approach provides a good overview of the popular indicators used, it may overlook less frequent but useful indicators. Finally, although indicator categories are useful in terms of managing and understanding indicators, their induction is subjective. One may for example also consider the complexity of calculation of indicators (for instance, calculating mean BGL is simpler and faster than time-weighted mean BGL).
To our knowledge this is the first review dedicated exclusively to quality indicators for TGC in critically ill patients. Existing reviews on TGC have focused on its effects [7, 37]; evidence of its utility and its advantages were reported, and ways to implement TGC protocols successfully discussed.
Indicators and indicator groups have merits and limitations. Measures of mean BGL may mask measurements within adverse zones (for instance, two high BGLs may 'compensate' for one or more BGLs that are too low). Looking at hypoglycaemia and hyperglycaemic events separately would solve this problem, but this requires a way to combine both indicators into one quality indicator of blood glucose management. The Glycaemic Penalty Index, proposed very recently , is an attempt to address each zone and combine the two results. Indicators that neglect measurement timing, including the Glycaemic Penalty Index, may be sensitive to sampling. For example, the mean BGL of two determinations yielding the same BGL value taken at t1 and t2 or at t1 and t3, where say t3 > t2, will provide the same result, although the BGL – behaving as a function of time – may differ markedly. The hyperglycaemia index, which measures the area under the BGL over the time during which it was above a threshold, can mitigate this problem. The use of BGL measurement as the independent unit of observation neglects the within-patient correlation in BGLs. On the other hand, when providing summaries at the patient level, some information is lost. Finally, a statistical point worth noting is that most BGL distributions are log-normal rather than normal , and hence nonparametric measures such as the median and interquartile range are likely to be more appropriate for summarizing the data and inference .
Because hypoglycaemia is the main potential risk from implementation of a TGC protocol, almost all studies reported at least one indicator related to hypoglycaemia. The number of hypoglycaemic events before and after TGC implementation and/or the management of these events form the main TGC safety indicators. However, we found several definitions and ambiguous terminology for defining a blood glucose measurement (or a set of measurements) a hypoglycaemic event. Hypoglycaemic events were usually represented as the percentage or number of measurements below a defined level. Based on most glucose management protocols, the next BGL measurement after a hypoglycaemic event should be taken within 15 to 30 minutes. Only one study clearly stated that all measurements below the hypoglycaemia threshold over 1 hour after the first hypoglycaemic measurement were considered part of a single hypoglycaemic event or episode. In other studies it was not clear how these hypoglycaemic measurements where dealt with within a short interval, and hence whether they were regarded a single or as multiple events. Some studies also reported the number of dextrose injections to address this problem, where each injection corresponds to one hypoglycaemic event regardless of the number of measurements within the short interval. Even in these studies, the criteria and the BGL threshold for dextrose injection were different.
Indicators such as the percentage or number of BGL measurements and the time during which BGL was within predefined ranges were frequently used to represent the time duration in each predefined BGL range. However, the predefined ranges were different in the various studies, once again hampering comparability among them. Summary measures themselves, like mean and median of BGLs, were calculated with different units of analysis. Studies reporting the percentage of measurements tended to base calculations on all BGL measurements, regardless of the number of measurements of per patient.
In contrast, the percentage of time was calculated by taking a summary of each patient as the unit of analysis. These two ways of performing calculations do not necessarily yield the same results, because of within-patient correlations in measurements. It seems prudent to provide both results.
The strong relation between hyperglycaemia and mortality and morbidity is well known from the literature. Hence, hyperglycaemia reduction forms the main goal of TGC. Surprisingly, only nine studies explicitly defined a hyperglycaemic event and employed different definitions of an event in terms of timing and the BGL thresholds (between 150 to 250 mg/dl). Reporting the fraction of time above a threshold instead of the percentage of measurements above a threshold, without time consideration, seems more useful as a proxy for reducing time in a hyperglycaemic state. The hyperglycaemia index – calculated as the area between the curve and the hyperglycaemia threshold divided by time – seems to be a useful time-weighted indicator for hyperglycaemia. In some other studies, the percentage of BGL measurements or time in a predefined BGL range above the defined normoglycaemic threshold was reported but without explicitly labeling them as hyperglycaemia.
The quality of TGC in individual patients was rarely reported. Useful indicators include the percentages of patients with well and poorly controlled BGL, as defined by Carr and coworkers ; patients with at least one BGL outside the blood glucose target range; and patients who were not within the target blood glucose range
On the whole, the authors of studies did not explain their choices of specific subsets of indicators. It is conceivable that an indicator was described by a specific statistic such as a median because of an underlying non-normal distribution, in order to permit sound statistical inference. Although this may explain the specific choice of a statistic, it does not account for the choice for the underlying concept in the first place.
When comparing the results of studies, one must consider differences in case-mix, in insulin therapy, in other associated therapies, in the power of the analysis and in outcome measures. The latter was the focus of this paper. The ambiguity and variability in the definitions of indicators and the threshold values for reporting an event as hypoglycaemia or hyperglycaemia severely hamper comparability among studies. A main problem is the absence of a 'gold standard' against which to compare indicators. Although there are almost no studies comparing different glycaemic metrics with relevant clinical outcomes, such as severity-associated mortality, deciding upon a common glycaemic vocabulary is an essential first step.
One possible useful way to proceed is to investigate further the relationship between indicators and clinical outcomes, for example their prognostic value (for example [24, 41]). A second possible way is to ask a committee of experts to assess, for a wide range of patients, the perceived adequacy of TGC. Ideally, for this sample of patients the BGL would be continuously measured, with insulin provision being based only on protocol-based measurement sampling. Because this is an ethically questionable approach (because not all measured BGLs are acted upon), an alternative is to attempt to achieve very high sampling of BGL measurements. Then, the indicators could be assessed according to their concordance with how well BGL is controlled, as assessed by expert opinion. This approach is subjective but it can provide important insight into the merits of indicators. In the meantime, studies should report on a more comprehensive set of indicators, including at least one pertaining to each of time, hyperglycaemia and hypoglycaemia. One should also report results at the measurement as well as patient level. An important message of this review is that many indicators are not but should be precisely defined, using formulas when necessary, to facilitate their assessment and comparability.
TGC indicators differ widely in their definitions, even when they are meant to measure the same underlying concept.
Many definitions of indicators are not precise, limiting their applicability and hence the reproducibility and comparability of research findings.
An unambiguous indicator reference subset is necessary for evaluating quality of TGC.
The result of this systematic review can be used as a starting point from which to develop a standard list of well defined indicators, which are associated with clinical outcomes or concur with clinicians' subjective views on the quality of the regulatory process.
blood glucose level
tight glycaemic control.
Krinsley JS: Association between hyperglycemia and increased hospital mortality in a heterogeneous population of critically ill patients. Mayo Clin Proc 2003, 78: 1471-1478.
Capes SE, Hunt D, Malmberg K, Gerstein HC: Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview. Lancet 2000, 355: 773-778. 10.1016/S0140-6736(99)08415-9
Schultz MJ, Royakkers AA, Levi M, Moeniralam HS, Spronk PE: Intensive insulin therapy in intensive care: an example of the struggle to implement evidence-based medicine. PLoS Med 2006, 3: e456. 10.1371/journal.pmed.0030456
Berghe G, Wilmer A, Hermans G, Meersseman W, Wouters PJ, Milants I, Van Wijngaerden E, Bobbaers H, Bouillon R: Intensive insulin therapy in the medical ICU. N Engl J Med 2006, 354: 449-461. 10.1056/NEJMoa052521
Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R: Intensive insulin therapy in the critically ill patients. N Engl J Med 2001, 345: 1359-1367. 10.1056/NEJMoa011300
Berghe G, Wouters PJ, Bouillon R, Weekers F, Verwaest C, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P: Outcome benefit of intensive insulin therapy in the critically ill: insulin dose versus glycemic control. Crit Care Med 2003, 31: 359-366. 10.1097/01.CCM.0000045568.12881.10
Meijering S, Corstjens AM, Tulleken JE, Meertens JH, Zijlstra JG, Ligtenberg JJ: Towards a feasible algorithm for tight glycaemic control in critically ill patients: a systematic review of the literature. Crit Care 2006, 10: R19. 10.1186/cc3981
Davidson PC, Steed RD, Bode BW: Glucommander: a computer-directed intravenous insulin system shown to be safe, simple, and effective in 120,618 h of operation. Diabetes Care 2005, 28: 2418-2423. 10.2337/diacare.28.10.2418
Braithwaite SS, Edkins R, Macgregor KL, Sredzienski ES, Houston M, Zarzaur B, Rich PB, Benedetto B, Rutherford EJ: Performance of a dose-defining insulin infusion protocol among trauma service intensive care unit admissions. Diabetes Technol Ther 2006, 8: 476-488. 10.1089/dia.2006.8.476
Laver S, Preston S, Turner D, McKinstry C, Padkin A: Implementing intensive insulin therapy: development and audit of the Bath insulin protocol. Anaesth Intensive Care 2004, 32: 311-316.
Barth MM, Oyen LJ, Warfield KT, Elmer JL, Evenson LK, Tescher AN, Kuper PJ, Bannon MP, Gajic O, Farmer JC: Comparison of a nurse initiated insulin infusion protocol for intensive insulin therapy between adult surgical trauma, medical and coronary care intensive care patients. BMC Emerg Med 2007, 7: 14. 10.1186/1471-227X-7-14
Boord JB, Sharifi M, Greevy RA, Griffin MR, Lee VK, Webb TA, May ME, Waitman LR, May AK, Miller RA: Computer-based insulin infusion protocol improves glycemia control over manual protocol. J Am Med Inform Assoc 2007, 14: 278-287. 10.1197/jamia.M2292
Shulman R, Finney SJ, O'Sullivan C, Glynne PA, Greene R: Tight glycaemic control: a prospective observational study of a computerised decision-supported intensive insulin therapy protocol. Crit Care 2007, 11: R75. 10.1186/cc5964
Rood E, Bosman RJ, Spoel JI, Taylor P, Zandstra DF: Use of a computerized guideline for glucose regulation in the intensive care unit improved both guideline adherence and glucose regulation. J Am Med Inform Assoc 2005, 12: 172-180. 10.1197/jamia.M1598
Vogelzang M, Zijlstra F, Nijsten MW: Design and implementation of GRIP: a computerized glucose control system at a surgical intensive care unit. BMC Med Inform Decis Mak 2005, 5: 38. 10.1186/1472-6947-5-38
Ku SY, Sayre CA, Hirsch IB, Kelly JL: New insulin infusion protocol Improves blood glucose control in hospitalized patients without increasing hypoglycemia. Jt Comm J Qual Patient Saf 2005, 31: 141-147.
Hermayer KL, Neal DE, Hushion TV, Irving MG, Arnold PC, Kozlowski L, Stroud MR, Kerr FB, Kratz JM: Outcomes of a cardiothoracic intensive care web-based online intravenous insulin infusion calculator study at a Medical University Hospital. Diabetes Technol Ther 2007, 9: 523-534. 10.1089/dia.2007.0225
Bone EG, Young D, Chantler J: Target ranges and the apparent compliance with tight glycaemic control. Anaesthesia 2006, 61: 956-958. 10.1111/j.1365-2044.2006.04817.x
Orford N, Stow P, Green D, Corke C: Safety and feasibility of an insulin adjustment protocol to maintain blood glucose concentrations within a narrow range in critically ill patients in an Australian level III adult intensive care unit. Crit Care Resusc 2004, 6: 92-98.
Chant C, Wilson G, Friedrich JO: Validation of an insulin infusion nomogram for intensive glucose control in critically ill patients. Pharmacotherapy 2005, 25: 352-359. 10.1592/phco.25.3.352.61594
Oeyen SG, Hoste EA, Roosens CD, Decruyenaere JM, Blot SI: Adherence to and efficacy and safety of an insulin protocol in the critically ill: a prospective observational study. Am J Crit Care 2007, 16: 599-608.
Markovitz LJ, Wiechmann RJ, Harris N, Hayden V, Cooper J, Johnson G, Harelstad R, Calkins L, Braithwaite SS: Description and evaluation of a glycemic management protocol for patients with diabetes undergoing heart surgery. Endocr Pract 2002, 8: 10-18.
Brown G, Dodek P: Intravenous insulin nomogram improves blood glucose control in the critically ill. Crit Care Med 2001, 29: 1714-1719. 10.1097/00003246-200109000-00010
Vogelzang M, Horst IC, Nijsten MW: Hyperglycaemic index as a tool to assess glucose control: a retrospective study. Crit Care 2004, 8: R122-R127. 10.1186/cc2840
Zimmerman CR, Mlynarek ME, Jordan JA, Rajda CA, Horst HM: An insulin infusion protocol in critically ill cardiothoracic surgery patients. Ann Pharmacother 2004, 38: 1123-1129. 10.1345/aph.1E018
Meynaar IA, Dawson L, Tangkau PL, Salm EF, Rijks L: Introduction and evaluation of a computerised insulin protocol. Intensive Care Med 2007, 33: 591-596. 10.1007/s00134-006-0484-z
Quinn JA, Snyder SL, Berghoff JL, Colombo CS, Jacobi J: A practical approach to hyperglycemia management in the intensive care unit: evaluation of an intensive insulin infusion protocol. Pharmacotherapy 2006, 26: 1410-1420. 10.1592/phco.26.10.1410
Malesker MA, Foral PA, McPhillips AC, Christensen KJ, Chang JA, Hilleman DE: An efficiency evaluation of protocols for tight glycemic control in intensive care units. Am J Crit Care 2007, 16: 589-598.
Kanji S, Singh A, Tierney M, Meggison H, McIntyre L, Hebert PC: Standardization of intravenous insulin therapy improves the efficiency and safety of blood glucose control in critically ill adults. Intensive Care Med 2004, 30: 804-810. 10.1007/s00134-004-2252-2
Mitchell I, Knight E, Gissane J, Tamhane R, Kolli R, Leditschke IA, Bellomo R, Finfer S: A phase II randomised controlled trial of intensive insulin therapy in general intensive care patients. Crit Care Resusc 2006, 8: 289-293.
Carr JM, Sellke FW, Fey M, Doyle MJ, Krempin JA, de la Torre R, Liddicoat JR: Implementing tight glucose control after coronary artery bypass surgery. Ann Thorac Surg 2005, 80: 902-909. 10.1016/j.athoracsur.2005.03.105
Shaw GM, Chase JG, Wong J, Lin J, Lotz T, Le Compte AJ, Lonergan TR, Willacy MB, Hann CE: Rethinking glycaemic control in critical illness: from concept to clinical practice change. Crit Care Resusc 2006, 8: 90-99.
Balkin M, Mascioli C, Smith V, Alnachawati H, Mehrishi S, Saydain G, Slone H, Alessandrini J, Brown L: Achieving durable glucose control in the intensive care unit without hypoglycaemia: a new practical IV insulin protocol. Diabetes Metab Res Rev 2007, 23: 49-55. 10.1002/dmrr.673
Plank J, Blaha J, Cordingley J, Wilinska ME, Chassin LJ, Morgan C, Squire S, Haluzik M, Kremen J, Svacina S, Toller W, Plasnik A, Ellmerer M, Hovorka R, Pieber TR: 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. 10.2337/diacare.29.02.06.dc05-1689
Chase JG, Shaw GM, Lotz T, LeCompte A, Wong J, Lin J, Lonergan T, Willacy M, Hann CE: Model-based insulin and nutrition administration for tight glycaemic control in critical care. Curr Drug Deliv 2007, 4: 283-296. 10.2174/156720107782151223
Lonergan T, Le Compte A, Willacy M, Chase JG, Shaw GM, Wong XW, Lotz T, Lin J, Hann CE: A simple insulin-nutrition protocol for tight glycemic control in critical illness: development and protocol comparison. Diabetes Technol Ther 2006, 8: 191-206. 10.1089/dia.2006.8.191
Nazer LH, Chow SL, Moghissi ES: Insulin infusion protocols for critically ill patients: a highlight of differences and similarities. Endocr Pract 2007, 13: 137-146.
Van Herpe T, De Brabanter J, Beullens M, De Moor B, Berghe G: Glycemic penalty index for adequately assessing and comparing different blood glucose control algorithms. Crit Care 2008, 12: R24. 10.1186/cc6800
Chee F, Fernando T, van Heerden PV: Closed-loop control of blood glucose levels in critically ill patients. Anaesth Intensive Care 2002, 30: 295-307.
Limpert E, Stahel W, Abbt M: Log-normal distributions across the sciences: keys and clues. BioScience 2001, 51: 341-352. 10.1641/0006-3568(2001)051[0341:LNDATS]2.0.CO;2
Vogelzang M, Nijboer JM, Horst IC, Zijlstra F, ten Duis HJ, Nijsten MW: Hyperglycemia has a stronger relation with outcome in trauma patients than in other critically ill patients. J Trauma 2006, 60: 873-879. 10.1097/01.ta.0000195715.63978.80
Krinsley J, Grissler B: Intensive glycemic management in critically ill patients. Jt Comm J Qual Patient Saf 2005, 31: 308-312.
Ball C, de Beer K, Gomm A, Hickman B, Collins P: Achieving tight glycaemic control. Intensive Crit Care Nurs 2007, 23: 137-144. 10.1016/j.iccn.2006.11.007
McMullin J, Brozek J, McDonald E, Clarke F, Jaeschke R, Heels-Ansdell D, Leppert R, Foss A, Cook D: Lowering of glucose in critical care: a randomized pilot trial. J Crit Care 2007, 22: 112-119. 10.1016/j.jcrc.2006.08.002
Goldberg PA, Sakharova OV, Barrett PW, Falko LN, Roussel MG, Bak L, Blake-Holmes D, Marieb NJ, Inzucchi SE: Improving glycemic control in the cardiothoracic intensive care unit: clinical experience in two hospital settings. J Cardiothorac Vasc Anesth 2004, 18: 690-697. 10.1053/j.jvca.2004.08.003
Taylor BE, Schallom ME, Sona CS, Buchman TG, Boyle WA, Mazuski JE, Schuerer DE, Thomas JM, Kaiser C, Huey WY, Ward MR, Zack JE, Coopersmith CM: Efficacy and safety of an insulin infusion protocol in a surgical ICU. J Am Coll Surg 2006, 202: 1-9. 10.1016/j.jamcollsurg.2005.09.015
Lonergan T, Compte AL, Willacy M, Chase JG, Shaw GM, Hann CE, Lotz T, Lin J, Wong XW: A pilot study of the SPRINT protocol for tight glycemic control in critically Ill patients. Diabetes Technol Ther 2006, 8: 449-462. 10.1089/dia.2006.8.449
Wong XW, Singh-Levett I, Hollingsworth LJ, Shaw GM, Hann CE, Lotz T, Lin J, Wong OS, Chase JG: A novel, model-based insulin and nutrition delivery controller for glycemic regulation in critically ill patients. Diabetes Technol Ther 2006, 8: 174-190. 10.1089/dia.2006.8.174
Juneja R, Roudebush C, Kumar N, Macy A, Golas A, Wall D, Wolverton C, Nelson D, Carroll J, Flanders SJ: Utilization of a computerized intravenous insulin infusion program to control blood glucose in the intensive care unit. Diabetes Technol Ther 2007, 9: 232-240. 10.1089/dia.2006.0015
Thomas AN, Marchant AE, Ogden MC, Collin S: Implementation of a tight glycaemic control protocol using a web-based insulin dose calculator. Anaesthesia 2005, 60: 1093-1100. 10.1111/j.1365-2044.2005.04375.x
Bland DK, Fankhanel Y, Langford E, Lee M, Lee SW, Maloney C, Rogers M, Zimmerman G: Intensive versus modified conventional control of blood glucose level in medical intensive care patients: a pilot study. Am J Crit Care 2005, 14: 370-376.
Osburne RC, Cook CB, Stockton L, Baird M, Harmon V, Keddo A, Pounds T, Lowey L, Reid J, McGowan KA, Davidson PC: Improving hyperglycemia management in the intensive care unit: preliminary report of a nurse-driven quality improvement project using a redesigned insulin infusion algorithm. Diabetes Educ 2006, 32: 394-403. 10.1177/0145721706288072
Dilkhush D, Lannigan J, Pedroff T, Riddle A, Tittle M: Insulin infusion protocol for critical care units. Am J Health Syst Pharm 2005, 62: 2260-2264. 10.2146/ajhp040590
Dazzi D, Taddei F, Gavarini A, Uggeri E, Negro R, Pezzarossa A: The control of blood glucose in the critical diabetic patient: a neuro-fuzzy method. J Diabetes Complications 2001, 15: 80-87. 10.1016/S1056-8727(00)00137-9
Goldberg PA, Siegel MD, Sherwin RS, Halickman JI, Lee M, Bailey VA, Lee SL, Dziura JD, Inzucchi SE: Implementation of a safe and effective insulin infusion protocol in a medical intensive care unit. Diabetes Care 2004, 27: 461-467. 10.2337/diacare.27.2.461
Iqbal M, Al-Aithan AM, Rehmani R, Eledrisi M: Initial experience with an intensive care hyperglycemia protocol in a Saudi Arabian intensive care unit. Saudi Med J 2006, 27: 492-496.
Lien LF, Spratt SE, Woods Z, Osborne KK, Feinglos MN: Optimizing hospital use of intravenous insulin therapy: improved management of hyperglycemia and error reduction with a new nomogram. Endocr Pract 2005, 11: 240-253.
De Block C, Manuel YKB, Van Gaal L, Rogiers P: Intensive insulin therapy in the intensive care unit: assessment by continuous glucose monitoring. Diabetes Care 2006, 29: 1750-1756. 10.2337/dc05-2353
Scheuren L, Baetz B, Cawley MJ, Fitzpatrick R, Cachecho R: Pharmacist designed and nursing-driven insulin infusion protocol to achieve and maintain glycemic control in critical care patients. J Trauma Nurs 2006, 13: 140-145.
Roth JM, Bolin B, Baird RW: Evaluation of blood glucose values in critically ill patients before and after implementation of an intensive insulin infusion protocol. Proc (Bayl Univ Med Cent) 2007, 20: 237-239.
The authors declare that they have no competing interests.
All authors made substantial contributions to the study design and methods. SE, AA and NdK performed the literature search, evaluated studies, extracted data, analyzed data and drafted the manuscript. All authors interpreted the results and were involved in revising the final manuscript.
Authors’ original submitted files for images
Below are the links to the authors’ original submitted files for images.
About this article
Cite this article
Eslami, S., de Keizer, N.F., de Jonge, E. et al. A systematic review on quality indicators for tight glycaemic control in critically ill patients: need for an unambiguous indicator reference subset. Crit Care 12, R139 (2008). https://doi.org/10.1186/cc7114
- Blood Glucose Level
- Quality Indicator
- Hypoglycaemic Event
- Tight Glycaemic Control
- Predefined Range