Insulin infusion protocols for critically ill patients: a highlight of differences and similarities

Managing Patients Undergoing Orthopedic Surgery to Improve Glycemic Outcomes

PURPOSE OF REVIEW

Persons with diabetes are more likely to require orthopedic surgery and are at an increased risk of developing postoperative complications. Recognizing the impact of diabetes on musculoskeletal health provides an opportunity to educate healthcare professionals in standardizing the perioperative approach of persons with diabetes.

RECENT FINDINGS

Elevated hemoglobin A1C, fructosamine, and blood glucose levels have been associated with increased risk for complications in the orthopedic population. These risks can be mitigated by the early identification and optimization of these patients in the perioperative period. Intraoperative and postoperative glycemic management should support efforts to maintain glucose at safe levels while avoiding hyperglycemia and hypoglycemia. This paper considers factors surrounding diabetes care in the orthopedic surgical patient. Perioperative care discussed includes optimization, hospitalization to discharge, and special considerations such as steroids and diabetes wearable technology. Hospitals should consider these strategies towards enhancing the care of persons with diabetes requiring musculoskeletal care.

Risk of Hypoglycemia During Insulin Infusion Directed by Paper Protocol Versus Electronic Glycemic Management System in Critically Ill Patients at a Large Academic Medical Center

BACKGROUND

Insulin infusions are commonly utilized to control hyperglycemia in critically ill patients and decrease hyperglycemia associated complications. Safety concerns have been raised in trials evaluating methods of glycemic control regarding the incidence of hypoglycemia and its relationship to increased mortality. Electronic glycemic management systems (eGMS) may result in less variable blood glucose (BG) control and less hypoglycemia. This study aimed to compare BG control, time in target BG range, and the rate of hypoglycemia when critically ill patients were managed with an insulin infusion guided by paper-based protocol (PBP) versus eGMS.

METHODS

This retrospective review compared critically ill patients ≥ 18 years old that received insulin infusion from March to May 2015 (PBP group) and October to January 2017 (eGMS group). The primary outcome was the incidence of hypoglycemia. Secondary outcomes included frequency and severity of hypoglycemia, duration in glycemic target, length of insulin therapy, as well as ICU and hospital length of stay.

RESULTS

Fifty-four patients were evaluated, 27 in each group. Percentage of days with BG <70 mg/dL was significantly reduced after eGMS implementation (21.5% v 1.3%, P < .0001) including the frequency of severe hypoglycemia (BG < 40 mg/dL) (5.4% v 0.01%, P < .0001). Patients in the eGMS group spent a greater amount of time in target BG range (31.5% v 63.7%, P < .0001).

CONCLUSIONS

An eGMS has the potential to address many of the unmet needs of an optimal glycemic control strategy, minimizing hypoglycemia, and glycemic variability in a heterogeneous critically ill population.

Transitioning safely from intravenous to subcutaneous insulin

The transition from intravenous (IV) to subcutaneous (SQ) insulin in the hospitalized patient with diabetes or hyperglycemia is a key step in patient care. This review article suggests a stepwise approach to the transition in order to promote safety and euglycemia. Important components of the transition include evaluating the patient and clinical situation for appropriateness, recognizing factors that influence a safe transition, calculation of proper SQ insulin doses, and deciding the appropriate type of SQ insulin. This article addresses other clinical situations including the management of patients previously on insulin pumps and recommendations for patients requiring glucocorticoids and enteral tube feedings. The use of institutional and computerized protocols is discussed. Further research is needed regarding the transition management of subgroups of patients such as those with type 1 diabetes and end-stage renal disease.

Comparison of the efficacy and safety of two different insulin infusion protocols in the medical intensive care unit

BACKGROUND

New guidelines recommend using less intensive glycemic goals in critically ill patients receiving insulin infusions.

OBJECTIVE

To compare the efficacy and safety of a modified insulin infusion protocol (MIIP) with less stringent blood glucose (BG) goals to an intensive insulin infusion protocol (IIIP) in patients in a medical intensive care unit (MICU).

METHODS

Retrospective review of patients receiving an insulin infusion for at least 24 hours. Patients treated for hyperglycemic emergencies were excluded. The primary endpoint of the study was mean area under the BG curve (BG-AUC) at 24 and 48 hours. Other endpoints included mean BG, hours until BG at goal, rate of BG above goal, frequency of BG measurements, and rate of hypoglycemia.

RESULTS

BG-AUC at 24 hours was similar between the groups (MIIP = 5177.7 ± 1221.3 mg/dL x h vs IIIP = 4850.3 ± 1301.7 mg/dL x h; P = .20). The mean BG level at 24 hours was 225.1 ± 91.1 mg/dL in the MIIP group and 205.7 ± 89.7 mg/dL in the IIIP group (P = .06). In the MIIP group, 61.7% of the BG levels were above goal as compared to 87.5% in the IIIP group (P < .0001). Patients were able to achieve BG goals faster with the MIIP (12.58 ± 10.5 hours vs 29.37 ± 16.8 hours; P < .001). The rate of severe hypoglycemia was lower at 24 hours in the patients following the MIIP (0% vs 0.3%; P = .01).

CONCLUSION

The study showed that by having less intensive glycemic goals, goal BG levels can achieved faster and the rate of severe hypoglycemia can decrease.

Software-guided insulin dosing: tight glycemic control and decreased glycemic derangements in critically ill patients

OBJECTIVE

To determine whether glycemic derangements are more effectively controlled using software-guided insulin dosing compared with paper-based protocols.

PATIENTS AND METHODS

We prospectively evaluated consecutive critically ill patients treated in a tertiary hospital surgical intensive care unit (ICU) between January 1 and June 30, 2008, and between January 1 and September 30, 2009. Paper-based protocol insulin dosing was evaluated as a baseline during the first period, followed by software-guided insulin dosing in the second period. We compared glycemic metrics related to hyperglycemia, hypoglycemia, and glycemic variability during the 2 periods.

RESULTS

We treated 110 patients by the paper-based protocol and 87 by the software-guided protocol during the before and after periods, respectively. The mean ICU admission blood glucose (BG) level was higher in patients receiving software-guided intensive insulin than for those receiving paper-based intensive insulin (181 vs 156 mg/dL; P=.003, mean of the per-patient mean). Patients treated with software-guided intensive insulin had lower mean BG levels (117 vs 135 mg/dL; P=.0008), sustained greater time in the desired BG target range (95-135 mg/dL; 68% vs 52%; P=.0001), had less frequent hypoglycemia (percentage of time BG level was <70 mg/dL: 0.51% vs 1.44%; P=.04), and showed decreased glycemic variability (BG level per-patient standard deviation from the mean: ±29 vs ±42 mg/dL; P=.01).

CONCLUSION

Surgical ICU patients whose intensive insulin infusions were managed using the software-guided program achieved tighter glycemic control and fewer glycemic derangements than those managed with the paper-based insulin dosing regimen.

The future of inpatient diabetes management: glucose as the sixth vital sign

Diabetes is an ever increasing health problem in our society. Due to associated small and large vessel conditions, patients with diabetes are two- to four-fold more likely to require hospitalization than nondiabetic individuals. Furthermore, hyperglycemia in hospitalized patients results in increased susceptibility to wound infections, worse outcomes postcardiac and cerebrovascular events, longer hospital length of stay and increased inpatient mortality. Several studies suggest that tight control of glucose levels yields improvement in these factors. Conversely, other studies have suggested increased mortality after tight glucose management, perhaps as a result of an increased incidence of hypoglycemic events. The most reasonable approach to control of hyperglycemia is to normalize glucose levels as much as possible without triggering hypoglycemia. In the hospital, insulin therapy of hyperglycemia is preferred due to the ability to flexibly manage glucose levels without side effects associated with many alternative antidiabetic agents. Due to the increasing burden of inpatient diabetes, and the detrimental effects of both hyper and hypoglycemia, the authors predict that blood-glucose levels will become the sixth vital sign to be frequently monitored in hospitalized patients and controlled in a narrow range. The future is in the use of insulin pumps controlled by continuous glucose monitors. This technology is complex and has not yet become standard. The development of future inpatient diabetes care will depend on adaptation of hospital systems to advance the new technology.

Improving glycemic control with the adjunct use of a data management software program

BACKGROUND

Published studies have supported the implementation of tight glucose control (TGC) programs to improve patient outcomes and reduce mortality rates. However, measuring a program's efficiency is challenging, because of a lack of systems that capture data, allow access to data, and support analysis and interpretation in a near prospective time frame. We hypothesized that providing clinicians access to real-time blood glucose (BG) results reports could improve the efficacy of our TGC program.

METHODS

We performed a retrospective review of BG data during a 12-month period in a surgical trauma intensive care unit at a level I trauma center. A unit-specific insulin algorithm was used throughout the study. We compared BG values before and after the implementation of a data management software program that allowed clinicians access to real-time BG results reports. Reports were run daily and weekly to monitor the unit's TGC program.

RESULTS

A total of 70 616 BG values from 1044 patients were analyzed. An overall decrease was observed in the BG level mean, from 121 mg/dL to 112 mg/dL (P < .001), as well as a decrease in the aggregated mean across patients, from 132 mg/dL to 119 mg/dL (P < .001), after implementation of the software. The percentage of values within the target range of 80 to 110 mg/dL increased from 38.9% to 50.4% (P < .001). The percentage of BG values less than 70 increased from 2.7% to 3.4% (P < .001). However, the percentage of severe hypoglyce-mic episodes (≤ 40 mg/dL) remained unchanged.

CONCLUSIONS

Access to real-time aggregated BG data reports through the use of a data management software program improved the efficacy of our TGC program.

Glycemic management in the inpatient setting

Hyperglycemia occurs frequently in hospitalized patients and affects patient outcomes, including mortality, inpatient complications, hospital length of stay, and overall hospital costs. Various degrees of glycemic control have been studied and consensus statements from the American Diabetes Association/American Association of Clinical Endocrinologists and The Endocrine Society recommend a target blood glucose range of 140 to 180 mg/dL in most hospitalized patients. Insulin is the preferred modality for treating all hospitalized patients with hyperglycemia, as it is adaptable to changing patient physiology over the course of hospitalization. Critically ill patients should receive intravenous insulin infusion, and all noncritically ill patients with hyperglycemia (individuals with and without diabetes) should be managed using a subcutaneous insulin algorithm with basal, nutritional, and correctional dose components. Hypoglycemia remains a limiting factor to achieving optimal glycemic targets. Similar to hyperglycemia, hypoglycemia is an independent risk factor for poor outcomes in hospitalized patients. Improvement in glycemic control throughout the hospital includes efforts from all health care providers. Institutions can encourage safe insulin use by using insulin algorithms, preprinted order sets, and hypoglycemia protocols, as well as by supporting patient and health care provider education.

Management of hyperglycemia during the perioperative period

Hyperglycemia is frequently encountered in the inpatient setting and is distinctly associated with poor clinical outcomes. Recent literature suggests an association between stringent glycemic control and increased mortality, thus keeping optimal glycemic targets a relevant subject of debate. In the surgical population, hyperglycemia with or without diabetes mellitus may be unrecognized. Factors contributing to hyperglycemia in the hospital include critical illness, use of certain drugs, use of enteral or parenteral nutrition, and variability in oral or nutritional intake as can occur when patients are prepared for procedures or surgery. A sensible approach to managing hyperglycemia in this population includes preoperative recognition of diabetes mellitus and risks for inpatient hyperglycemia. Judicious control of glycemia during the pre-, intra-, and postoperative time periods with avoidance of hypoglycemia mandates the need for a strategy for patient management that extend to time of discharge. We review the consequences of uncontrolled perioperative hyperglycemia, discuss current clinical guidelines and recent controversies, and provide practical tools for glycemic control in the surgical population.

International recommendations for glucose control in adult non diabetic critically ill patients

INTRODUCTION

The purpose of this research is to provide recommendations for the management of glycemic control in critically ill patients.

METHODS

Twenty-one experts issued recommendations related to one of the five pre-defined categories (glucose target, hypoglycemia, carbohydrate intake, monitoring of glycemia, algorithms and protocols), that were scored on a scale to obtain a strong or weak agreement. The GRADE (Grade of Recommendation, Assessment, Development and Evaluation) system was used, with a strong recommendation indicating a clear advantage for an intervention and a weak recommendation indicating that the balance between desirable and undesirable effects of an intervention is not clearly defined.

RESULTS

A glucose target of less than 10 mmol/L is strongly suggested, using intravenous insulin following a standard protocol, when spontaneous food intake is not possible. Definition of the severe hypoglycemia threshold of 2.2 mmol/L is recommended, regardless of the clinical signs. A general, unique amount of glucose (enteral/parenteral) to administer for any patient cannot be suggested. Glucose measurements should be performed on arterial rather than venous or capillary samples, using central lab or blood gas analysers rather than point-of-care glucose readers.

CONCLUSIONS

Thirty recommendations were obtained with a strong (21) and a weak (9) agreement. Among them, only 15 were graded with a high level of quality of evidence, underlying the necessity to continue clinical studies in order to improve the risk-to-benefit ratio of glucose control.

Comparisons of different insulin infusion protocols: a review of recent literature

PURPOSE OF REVIEW

To provide an update on the currently available insulin infusion protocols for treatment of hyperglycemia in critically ill patients and to discuss the major differences and similarities among them.

RECENT FINDINGS

We identified a total of 26 protocols, 20 of which used manual blood-glucose calculations, and six that used computerized algorithms. The major differences and similarities among the insulin infusion protocols were in the following areas: patient characteristics, target glucose level, time to achieve target glucose level, incidence of hypoglycemia, rationale for adjusting the rates of insulin infusion, and methods of blood-glucose measurements. Several computerized protocols hold promise for safer achievement of glycemic targets.

SUMMARY

Insulin infusion is the most effective method for controlling hyperglycemia in critically ill patients. Clinicians should utilize a validated insulin infusion protocol that is well tolerated, and is most appropriate and practical for their institution based on the resources that are available.

Computerized intensive insulin dosing can mitigate hypoglycemia and achieve tight glycemic control when glucose measurement is performed frequently and on time

Introduction

Control of blood glucose (BG) in critically ill patients is considered important, but is difficult to achieve, and often associated with increased risk of hypoglycemia. We examined the use of a computerized insulin dosing algorithm to manage hyperglycemia with particular attention to frequency and conditions surrounding hypoglycemic events.

Methods

This is a retrospective analysis of adult patients with hyperglycemia receiving intravenous (IV) insulin therapy from March 2006 to December 2007 in the intensive care units of 2 tertiary care teaching hospitals. Patients placed on a glycemic control protocol using the Clarian GlucoStabilizer™ IV insulin dosing calculator with a target range of 4.4-6.1 mmol/L were analyzed. Metrics included time to target, time in target, mean blood glucose ± standard deviation, % measures in hypoglycemic ranges <3.9 mmol/L, per-patient hypoglycemia, and BG testing interval.

Results

4,588 ICU patients were treated with the GlucoStabilizer to a BG target range of 4.4-6.1 mmol/L. We observed 254 severe hypoglycemia episodes (BG <2.2 mmol/L) in 195 patients, representing 0.1% of all measurements, and in 4.25% of patients or 0.6 episodes per 1000 hours on insulin infusion. The most common contributing cause for hypoglycemia was measurement delay (n = 170, 66.9%). The median (interquartile range) time to achieve the target range was 5.9 (3.8 - 8.9) hours. Nearly all (97.5%) of patients achieved target and remained in target 73.4% of the time. The mean BG (± SD) after achieving target was 5.4 (± 0.52) mmol/L. Targeted blood glucose levels were achieved at similar rates with low incidence of severe hypoglycemia in patients with and without diabetes, sepsis, renal, and cardiovascular disease.

Conclusions

Glycemic control to a lower glucose target range can be achieved using a computerized insulin dosing protocol. With particular attention to timely measurement and adjustment of insulin doses the risk of hypoglycemia experienced can be minimized.

Tight glycemic control and computerized decision-support systems: a systematic review

Objective

To identify and summarize characteristics of computerized decision-support systems (CDSS) for tight glycemic control (TGC) and to review their effects on the quality of the TGC process in critically ill patients.

Methods

We searched Medline (1950–2008) and included studies on critically ill adult patients that reported original data from a clinical trial or observational study with a main objective of evaluating a given TGC protocol with a CDSS.

Results

Seventeen articles met the inclusion criteria. Eleven out of seventeen studies evaluated the effect of a new TGC protocol that was introduced simultaneously with a CDSS implementation. Most of the reported CDSSs were stand-alone, were not integrated in any other clinical information systems and used the “passive” mode requiring the clinician to ask for advice. Different implementation sites, target users, and time of advice were used, depending on local circumstances. All controlled studies reported on at least one quality indicator of the blood glucose regulatory process that was improved by introducing the CDSS. Nine out of ten controlled studies either did not report on the number of hypoglycemia events (one study), or reported on no change (six studies) or even a reduction in this number (two studies).

Conclusions

While most studies evaluating the effect of CDSS on the quality of the TGC process found improvement when evaluated on the basis of the quality indicators used, it is impossible to define the exact success factors, because of simultaneous implementation of the CDSS with a new or modified TGC protocol and the hybrid solutions used to integrate the CDSS into the clinical workflow.

Hyperglycemia during acute coronary syndrome: a nurse-managed insulin infusion protocol for stricter and safer control

BACKGROUND

Diabetic patients with acute coronary syndromes (ACS) might benefit from tight glycemic control by means of insulin infusion. Nurse-implemented insulin infusion protocols (IIP) are available but none validated in patients with ACS admitted to a coronary care unit (CCU).

AIMS

To assess feasibility, effectiveness and safety of a new nurse-managed IIP (Desio Diabetes Diagram, DDD) for intensive glucose control in patients with suspected ACS and known diabetes or blood glucose (BG) >200 mg/dL.

METHODS AND RESULTS

To reach and maintain a target BG level of 100-139 mg/dL we adopted a nomogram based on the percent changes in the insulin infusion rate according to the current BG value and the percent change from previous BG level. Ninety-one consecutive patients (53 men, mean age 69.7+/-11.2 years) were treated with DDD IIP. Baseline BG was 202.2+/-86.8 mg/dL. The median time to achieve the target was 3 h (Q1-Q3 2-5 h). Afterwards target BG levels were maintained for 70.4+/-15.9% of the time. During 5004 h of insulin infusion BG never fell below 40 mg/dL.

CONCLUSIONS

The nurse-managed DDD IIP was easily implemented in our CCU and permitted strict and safe glycemic control in hyperglycemic patients with ACS.

Perceptions of resident physicians about management of inpatient hyperglycemia in an urban hospital

BACKGROUND

Information regarding practitioner beliefs about inpatient diabetes care is limited.

OBJECTIVE

To assess resident physician attitudes about inpatient hyperglycemia and determine perceived barriers to optimal glycemic control in an urban hospital setting.

DESIGN

A previously developed questionnaire was modified and administered. Residents were asked about the importance of inpatient glucose control, desirable glucose ranges, and problems encountered when managing hyperglycemia.

SETTING

Urban teaching hospital.

RESULTS

Of 85 resident physicians, 66 completed the survey (mean age, 31 years; 47% men; 33% in first residency year). Most respondents categorized glucose control as "very important" in critically-ill and perioperative patients but only "somewhat important" in non-critically-ill patients. Most residents said they would target a therapeutic glucose range within the recommended levels. Most residents (88%) also said they felt "very comfortable" or "somewhat comfortable" using subcutaneous insulin therapy, whereas some were "not at all comfortable" with either subcutaneous (11%) or intravenous (18%) administration. In general, respondents were not very familiar with existing institutional policies and preprinted order sets. The most commonly reported barrier to management of inpatient hyperglycemia was lack of knowledge about appropriate insulin regimens and their use. Anxiety about hypoglycemia was only the third most frequent concern.

CONCLUSION

Most residents acknowledged the importance of good glucose control in hospitalized patients and chose target glucose ranges consistent with existing guidelines. Lack of knowledge about insulin treatment options was the most commonly cited barrier to ideal management. Educational programs should emphasize inpatient treatment strategies for glycemic control.

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.

Designing and implementing insulin infusion protocols and order sets

Influential trials and guidelines supporting the value of glucose control in hospital settings, particularly in the intensive care and postoperative settings, has led to the widespread adoption of intravenous infusions of human regular insulin. As groups have attempted to study the outcomes or to explore improved methods for improved glucose control, a number of insulin infusion protocols (IIPs) have been reported and validated. Now, many institutions are attempting to translate this experience into clinical practice in a systematic manner. The intent of this discussion is to highlight the authors' practical view of best practices in development and use of IIPs. As the implementation of IIPs has progressed, it has become apparent that this is not a simple process. It requires a carefully planned, inclusive, and continuous effort striving to attain effective glucose control while avoiding severe hypoglycemia. Whereas there are limitations in the literature comparing the IIPs, we identify design elements and implementation methods that increase the chances for staff acceptance and safe attainment of glycemic goals. Most importantly, this must be a team effort with attention to the numerous potential pitfalls that can disrupt the process and place patients at risk. In many cases, it is best to start more conservatively and methodically intensify the protocol. Continuous assessment of protocol errors, adverse events, staff satisfaction, and outcomes is vital to overall success.

Computer-assisted glucose control in critically ill patients

Objective

Intensive insulin therapy is associated with the risk of hypoglycemia and increased costs of material and personnel. We therefore evaluated the safety and efficiency of a computer-assisted glucose control protocol in a large population of critically ill patients.

Design and setting

Observational cohort study in three intensive care units (32 beds) in a 1,300-bed university teaching hospital.

Patients

All 2,800 patients admitted to the surgical, neurosurgical, and cardiothoracic units; the study period started at each ICU after implementation of Glucose Regulation for Intensive Care Patients (GRIP), a freely available computer-assisted glucose control protocol.

Measurements and results

We analysed compliance in relation to recommended insulin pump rates and glucose measurement frequency. Patients were on GRIP-ordered pump rates 97% of time. Median measurement time was 5 min late (IQR 20 min early to 34 min late). Hypoglycemia was uncommon (7% of patients for mild hypoglycemia, < 3.5 mmol/l; 0.86% for severe hypoglycemia, < 2.2 mmol/l). Our predefined target range (4.0–7.5 mmol/l) was reached after a median of 5.6 h (IQR 0.2–11.8) and maintained for 89% (70–100%) of the remaining stay at the ICU. The number of measurements needed was 5.9 (4.8–7.3) per patient per day. In-hospital mortality was 10.1%.

Conclusions

Our computer-assisted glucose control protocol provides safe and efficient glucose regulation in routine intensive care practice. A low rate of hypoglycemic episodes was achieved with a considerably lower number of glucose measurements than used in most other schemes.

Electronic supplementary material

The online version of this article (doi:10.1007/s00134-008-1091-y) contains supplementary material, which is available to authorized users.

Treatment with insulin inhibits poly(ADP-ribose)polymerase activation in a rat model of endotoxemia

In critically ill patients various conditions may lead to the activation of poly(ADP-ribose) polymerase (PARP). By promoting cellular energetic dysfunction, and by enhancing pro-inflammatory gene expression, PARP activation significantly contributes to the pathogenesis of shock. PARP activation is usually triggered by DNA strand breakage, which is typically the result of the overproduction of various reactive oxidant species. One of the pathophysiological conditions associated with PARP activation is hyperglycemia, where the reactive species are produced from the mitochondria and other cellular sources. In the present study we tested whether endotoxin-induced PARP activation and pro-inflammatory mediator production can be modified by insulin therapy. Rats subjected to bacterial lipopolysaccharide (LPS) with or without insulin co-treatment were studied. LPS-induced PARP activation in circulating lymphocytes was measured by flow cytometry, tumor necrosis factor alpha (TNF-alpha) production was measured by ELISA. The direct effect of insulin on the PARP activity of mononuclear leukocytes and human umbilical vein endothelial cells (HUVEC) in elevated glucose conditions was tested in vitro. LPS-induced significant hyperglycemic response activated PARP in circulating lymphocytes and induced TNF-alpha production. Insulin treatment prevented LPS-induced hyperglycemic response, blocked PARP activation and blunted LPS-induced TNF-alpha response. Insulin treatment caused a slight reduction in the PARP activity of mononuclear cells and HUVECs in vitro. We demonstrate that insulin treatment blocks LPS-induced PARP activation in vivo. We propose that this effect is mainly indirect, and occurs due to the prevention of stress induced hyperglycemia, with a direct cellular effect of insulin playing a potential minor supplemental role. The current findings may have significant implications in the context of the emerging concept of tight glycemic control and insulin treatment for critically ill patients.