Impact of a Paper-Based Dynamic Insulin Infusion Protocol on Glycemic Variability, Time in Target, and Hypoglycemic Risk: A Stepped Wedge Trial in Medical Intensive Care Unit Patients

Assessing glycemic variability in critically ill patients: A prospective cohort study comparing insulin infusion therapy with insulin sliding scale

Glycemic variability (GV) has been associated with an increased mortality rate among critically ill patients. The clinical outcomes of having less GV even with slight hyperglycemia are better than those having tight glycemic control but higher GV. Insulin infusion remains the preferred method to control stress hyperglycemia in critically ill patients. However, its impacts on GV and clinical outcomes in critically ill patients still need further investigation. This study intended to evaluate the impact of insulin infusion therapy (IIT) compared to the insulin sliding scale (ISS) on the extent of GV and explore its impact on the clinical outcomes for critically ill patients. A prospective, single-center observational cohort study was conducted at a tertiary academic hospital in Saudi Arabia between March 2021 and November 2021. The study included adult patients admitted to ICUs who received insulin for stress hyperglycemia management. Patients were categorized into two groups based on the regimen of insulin therapy during ICU stay (IIT versus ISS). The primary outcome was the GV between the two groups. Secondary outcomes were ICU mortality, the incidence of hypoglycemia, and ICU length of stay (LOS). A total of 381 patients were screened; out of them, eighty patients met the eligibility criteria. The distribution of patients having diabetes and a history of insulin use was similar between the two groups. The GV was lower in the IIT group compared to the ISS group using CONGA (- 0.65, 95% CI [- 1.16, - 0.14], p-value = 0.01). Compared with ISS, patients who received IIT had a lower incidence of hypoglycemia that required correction (6.8% vs 2.77%; p-value = 0.38). In contrast, there were no significant differences in ICU LOS and ICU mortality between the two groups. Our study demonstrated that the IIT is associated with decreased GV significantly in critically ill patients without increasing the incidence of severe hypoglycemia. There is no survival benefit with the use of the IIT. Further studies with larger sample size are required to confirm our findings and elaborate on IIT's potential effect in reducing ICU complications in critically ill patients.

An effective insulin infusion protocol for severe traumatic brain injury patients: A retrospective observational study

PURPOSE

Severe traumatic brain injury (sTBI) patients often experience stress hyperglycaemia, which can lead to negative outcomes. This study aims to introduce an effective insulin infusion protocol specifically designed for sTBI patients.

METHODS

Data was collected from all sTBI patients during two periods: 1 October 2019 to 30 April 2020, and 1 June 2020 to 31 December 2020. In May 2020, a new insulin infusion protocol was implemented. Blood glucose management, infection, coagulation, and prognosis were compared in these two periods.

RESULT

195 patients were included, with 106 using the new protocol. The proportion of hyperglycaemia decreased from 40.04% to 26.91% (P<0.05), and the proportion of on-target blood glucose levels increased from 35.69% to 38.98% (P<0.05). Average blood glucose levels decreased from 9.98±2.79mmol/L to 8.96±2.82mmol/L (P<0.05). There was no substantial increase in hypoglycaemia, which remained controlled below 1%. The new protocol positively influenced glucose concentration and dispersion trends. There were no significant differences in catheter-related infections, antibiotic use, mechanical ventilation (MV) duration, length of stay in ICU, Glasgow Outcome Scale (GOS), or mortality. However, the conventional protocol group had a higher coagulation tendency (R-value of thromboelastography 4.80±1.35min vs. 5.52±1.87min, P<0.05), with no difference in deep vein thrombosis (DVT) incidence.

CONCLUSION

Our findings suggest that a customized insulin infusion process for sTBI patients can effectively manage blood glucose. While there is no significant improvement in infection control or prognosis, it may have a positive impact on coagulation without affecting the occurrence of DVT.

Insulin Infusion Protocols for Blood Glucose Management in Critically Ill Patients: A Scoping Review

BACKGROUND

Continuous insulin infusion is a method for maintaining blood glucose stability in critically ill patients with hyperglycemia. Many insulin infusion protocols have been applied in intensive care units. Understanding the content of these protocols can help clinical staff choose the most appropriate and convenient protocol and promote best practices in managing glucose levels in critically ill adult patients.

OBJECTIVE

To examine the types of insulin infusion therapies performed for blood glucose management in critically ill patients.

METHODS

For this scoping review, 3 Chinese-language and 8 English-language databases were searched for articles published from May 25, 2016, to October 25, 2022.

RESULTS

Twenty-one articles met the inclusion criteria. Twenty-one insulin infusion protocols were examined. Most of the insulin infusion protocols were paper protocols. Fourteen glucose management indicators were included in the 21 protocols. The glucose target range for all 21 protocols ranged from 70 to 180 mg/dL (3.9-10.0 mmol/L). Nurses were primarily responsible for protocol implementation in most protocol development processes. The roles of nurses differed in nurse-led insulin infusion protocols and non-nurse-led insulin infusion protocols.

DISCUSSION

This scoping review indicates an urgent need for more comprehensive glycemic control guidelines for patients receiving critical care. Because insulin infusion protocols are core aspects of blood glucose management guidelines, different population subgroups should also be considered.

CONCLUSIONS

Nurse-led guidelines must be based on the best available evidence and should include other variables related to glucose management (eg, patient disease type, medication, and nutrition) in addition to insulin infusion.

Application of the PDCA Cycle for Managing Hyperglycemia in Critically Ill Patients

Introduction

Stress hyperglycemia is a common symptom in critically ill patients, and is not only a marker indicating the severity of illness but is also related to worsening outcomes. Managing stress hyperglycemia without increasing the likelihood of hypoglycemia is one of the most pressing challenges to be urgently addressed in clinics. The Plan-Do-Check-Act (PDCA) cycle management has been put forward in various surgical management scenarios, and has proven to be effective in the diagnosis and treatment of different diseases. It possesses dynamic characteristics and can be updated according to the results of glycemic control and feedback. This study focused on the use of PDCA to manage glucose levels in critically ill patients.

Methods

Based on the glucose level of 1003 critically ill patients admitted to the emergency intensive care unit (EICU) from 1 October 2019 to 31 December 2020, we collected and matched the prevalence of hyperglycemia, hypoglycemia, and glucose variability on a quarterly basis. According to the PDCA management method, we analyzed the possible causes, supervised the implementation of measures, summarized the feedback on improvements, and then proposed new improvement measures for implementation in the next quarter.

Results

Three measures were proposed and applied to enhance the management of hyperglycemia: (I) Updating and formulating three editions of the insulin infusion protocol and increasing the initial and maintenance doses of insulin on a case-by-case basis; (II) reducing the use of parenteral nutrition and ensuring that enteral nutrition is consumed at a uniform and slow rate; and (III) forming a training method during the COVID-19 pandemic and improving implementation of the insulin infusion protocol. Following PDCA management, the prevalence of hyperglycemia fell from 43.18% to 32.61%, the incidence of hypoglycemia was below 1.00%, and there was no significant fluctuation in blood glucose variability.

Conclusion

The PDCA method is helpful in developing a superior insulin infusion protocol for critically ill patients and lowering the prevalence of hyperglycemia in critically ill patients.

Rationale, Methodological Quality, and Reporting of Cluster-Randomized Controlled Trials in Critical Care Medicine: A Systematic Review

OBJECTIVE

Compared with individual-patient randomized controlled trials, cluster randomized controlled trials have unique methodological and ethical considerations. We evaluated the rationale, methodological quality, and reporting of cluster randomized controlled trials in critical care studies.

DATA SOURCES

Systematic searches of Medline, Embase, and Cochrane Central Register were performed.

STUDY SELECTION

We included all cluster randomized controlled trials conducted in adult, pediatric, or neonatal critical care units from January 2005 to September 2019.

DATA EXTRACTION

Two reviewers independently screened citations, reviewed full texts, protocols, and supplements of potentially eligible studies, abstracted data, and assessed methodology of included studies.

DATA SYNTHESIS

From 1,902 citations, 59 cluster randomized controlled trials met criteria. Most focused on quality improvement (24, 41%), antimicrobial therapy (9, 15%), or infection control (9, 15%) interventions. Designs included parallel-group (25, 42%), crossover (21, 36%), and stepped-wedge (13, 22%). Concealment of allocation was reported in 21 studies (36%). Thirteen studies (22%) reported at least one method of blinding. The median total sample size was 1,660 patients (interquartile range, 813-4,295); the median number of clusters was 12 (interquartile range, 5-24); and the median patients per cluster was 141 (interquartile range, 54-452). Sample size calculations were reported in 90% of trials, but only 54% met Consolidated Standards of Reporting Trials guidance for sample size reporting. Twenty-seven of the studies (46%) identified a fixed number of available clusters prior to trial commencement, and only nine (15%) prespecified both the number of clusters and patients required to detect the expected effect size. Overall, 36 trials (68%) achieved the total prespecified sample size. When analyzing data, 44 studies (75%) appropriately adjusted for clustering when analyzing the primary outcome. Only 12 (20%) reported an intracluster coefficient (median 0.047 [interquartile range, 0.01-0.13]).

CONCLUSIONS

Cluster randomized controlled trials in critical care typically involve a small and fixed number of relatively large clusters. The reporting of key methodological aspects of these trials is often inadequate.

EATING AND GLYCEMIC CONTROL AMONG CRITICALLY ILL PATIENTS RECEIVING CONTINUOUS INTRAVENOUS INSULIN

Objective: Consensus guidelines recommend that intensive care unit (ICU) patients with blood glucose (BG) levels >180 mg/dL receive continuous intravenous insulin (CII). The effectiveness of CII at controlling BG levels among patients who are eating relative to those who are eating nothing by mouth (nil per os; NPO) has not been described. Methods: We conducted a retrospective cohort study of 260 adult patients (156 eating, 104 NPO) admitted to an ICU between January 1, 2014, and December 31, 2014, who received CII. Patients were excluded for a diagnosis of diabetic ketoacidosis or hyperglycemic hyperosmolar nonketotic syndrome, admission to an obstetrics service, or receiving continuous enteral or parenteral nutrition. Results: Among 22 baseline characteristics, the proportion of patients receiving glucocorticoid treatment (GCTx) (17.3% eating, 37.5% NPO; P<.001) and APACHE II score (15.0 ± 7.5 eating, 17.9 ± 7.9 NPO; P = .004) were significantly different between eating and NPO patients. There was no significant difference in the primary outcome of patient-day weighted mean BG overall (153 ± 8 mg/dL eating, 156 ± 7 mg/dL NPO; P = .73), or day-by-day BG (P = .37) adjusted for GCTx and APACHE score. Surprisingly, there was a significant difference in the distribution of BG values, with eating patients having a higher percentage of BG readings in the recommended range of 140 to 180 mg/dL. However, eating patients showed greater glucose variability (coefficient of variation 23.1 ± 1.0 eating, 21.2 ± 1.0 NPO; P = .034). Conclusion: Eating may not adversely affect BG levels of ICU patients receiving CII. Whether or not prandial insulin improves glycemic control in this setting should be studied. Abbreviations: BG = blood glucose; CII = continuous insulin infusion; CV = coefficient of variation; HbA1c = hemoglobin A1c; ICU = intensive care unit; NPO = nil per os; PDWMBG = patient day weighted mean blood glucose.

Association of transcription factor 7-like 2 gene (TCF7L2) polymorphisms with stress-related hyperglycaemia (SRH) in intensive care and resulting outcomes: The READIAB study

OBJECTIVE

The study aimed to evaluate the impact of the single nucleotide polymorphism (SNP) rs7903146 on the transcription factor 7-like 2 (TCF7L2) gene in stress-related hyperglycaemia (SRH), defined as blood glucose≥11mmol/L in at least two blood samples during the first 3 days in the intensive care unit (ICU), and on 28-day and 1-year mortality, and incidence of type 2 diabetes (T2D) at 6 months and 1 year in patients hospitalized in the ICU.

METHODS

This prospective observational (non-interventional) multicentre READIAB study, carried out during 2012-2016 in six French ICUs, involved adult patients admitted to ICUs for at least two organ failures; patients admitted for<48h were excluded. During the 3-day ICU observational period, genetic testing, blood glucose values and insulin treatment were recorded.

MAIN RESULTS

The association of rs7903146 with SRH was assessed using logistic regression models. Cox proportional hazards regression models assessed the associations between rs7903146 and mortality and between SRH and mortality, both at 28 days and 1 year. A total of 991 of the 1000 enrolled patients were included in the READIAB-G4 cohort, but 242 (24.4%) had preexisting diabetes and were excluded from the analyses. SRH occurred within the first 3 days in the ICU for one-third of the non-diabetes patients. The association between the rs7903146 polymorphism and SRH did not reach significance (P=0.078): OR_{(peroneTcopy)}: 1.24, 95% CI: 0.98-1.58. A significant association was found between rs7903146 and 28-day mortality after adjusting for severity scores (P=0.026), but was no longer significant at 1 year (P=0.61). At 28 days, mortality was increased in patients with SRH (HR: 2.09, 95% CI: 1.43-3.06; P<0.001), and remained significant at 1 year after adjusting for severity scores (HR: 1.73, 95% CI: 1.32-2.28; P<0.001). On admission, non-diabetes patients with SRH had a higher incidence of T2D at 6 months vs. those without SRH (16.0% vs. 7.6%, RR: 2.11, 95% CI: 1.07-4.20; P=0.030). At 1 year, these figures were 13.4% vs. 9.2%, RR: 1.45, 95% CI: 0.71-2.96; P=0.31). Moreover, the rs7903146 polymorphism was not significantly associated with T2D development at either 6 months (P=0.72) or 1 year (P=0.64).

CONCLUSION

This study failed to demonstrate any significant association between rs7903146 and SRH. Nevertheless, the issue remains an important challenge, as SRH may be associated with increased rates of both mortality and T2D development.

Prospective evaluation of a dynamic insulin infusion algorithm for non critically-ill diabetic patients: A before-after study

INTRODUCTION

Insulin infusion is recommended during management of diabetic patients in critical care units to rapidly achieve glycaemic stability and reduce the mortality. The application of an easy-to-use standardized protocol, compatible with the workload is preferred. Glycaemic target must quickly be reached, therefore static algorithms should be replaced by dynamic ones. The dynamic algorithm seems closer to the physiological situation and appreciates insulin sensitivity. However, the protocol must meet both safety and efficiency requirements. Indeed, apprehension from hypoglycaemia is the main deadlock with the dynamic algorithms, thus their application remains limited. In contrary to the critical care units, to date, no prospective study evaluated a dynamic algorithm of insulin infusion in non-critically ill patients.

AIM

This study primarily aimed to evaluate the efficacy of a dynamic algorithm of intravenous insulin therapy in non-critically-ill patients, and addressed its safety and feasibility in different departments of our university hospital.

METHODS

A "before-after" study was conducted in five hospital departments (endocrinology and four "non-expert" units) comparing a dynamic algorithm (during the "after" period-P2) to the static protocol (the "before" period-P1). Static protocol is based on determining insulin infusion according to an instant blood glycaemia (BG) level at a given time. In the dynamic algorithm, insulin infusion rate is determined according to the rate of change of the BG (the previous and actual BG under a specific insulin infusion rate). Additionally, two distinct glycaemic targets were defined according to the patients' profile: 100-180 mg/dl (5.5-10 mmol/l) for vigorous patients and 140-220 mg/dl (7.8-12.2 mmol/l) for frail ones. Different BG measurements for each patient were collected and recorded in a specific database (e-CRF) in order to analyse the rates of hypo- and hyperglycaemia. A satisfaction survey was also performed. A study approval was obtained from the institutional revision board before starting the study.

RESULTS

Over 8 months, 72 and 66 patients during P1 and P2 were respectively included. The dynamic algorithm was more efficient, with reduced time to control hyperglycaemia (P1 vs P2:8.3 vs 5.3 hours; HR: 2.02 [1.27; 3.21]; p<0.01), increased the number of in-target BG measurements (P1 vs P2: 37.0% vs 41.8%; p<0.05), and reduced the glycaemic variability related to each patient (P1 vs P2, %CV: 40.9 vs 38.2;p<0.05, Index Correlation Class:0.30 vs 0.14; p<0.05). In patients after the first event of hypoglycemia after having started the infusion, new events were lower (P1 vs P2: 19.4 vs 11.4; p<0.001) thanks to an earlier reaction to hypoglycaemia (8.3% during P1 vs 44.3% during P2; p = 0.004). With the dynamic algorithm, the percentage of recurrence of mild hypoglycaemia was significantly lower in frail patients (20.5% vs 10.2%; p<0.001), and in patients managed in the non-expert units (18 vs 7.1%, p<0.001). The %CV was significantly improved in frail patients (36.9%). Mean BG measurements for each patient/day were 5.5±1.1 during P1 and 6.0±1.6 during P2 (p = 0.6). The threat from hypoglycaemia and the difficulty in using dynamic algorithm are barriers for nurses' adherence.

CONCLUSIONS

This dynamic algorithm for non-critically-ill patients is more efficient and safe than the static protocol, and adapted for frail patients and non-expert units.

Hypoglycemia Prevention by Algorithm Design During Intravenous Insulin Infusion

PURPOSE OF REVIEW

This review examines algorithm design features that may reduce risk for hypoglycemia while preserving glycemic control during intravenous insulin infusion. We focus principally upon algorithms in which the assignment of the insulin infusion rate (IR) depends upon maintenance rate of insulin infusion (MR) or a multiplier.

RECENT FINDINGS

Design features that may mitigate risk for hypoglycemia include use of a mid-protocol bolus feature and establishment of a low BG threshold for temporary interruption of infusion. Computer-guided dosing may improve target attainment without exacerbating risk for hypoglycemia. Column assignment (MR) within a tabular user-interpreted algorithm or multiplier may be specified initially according to patient characteristics and medical condition with revision during treatment based on patient response. We hypothesize that a strictly increasing sigmoidal relationship between MR-dependent IR and BG may reduce risk for hypoglycemia, in comparison to a linear relationship between multiplier-dependent IR and BG. Guidelines are needed that curb excessive up-titration of MR and recommend periodic pre-emptive trials of MR reduction. Future research should foster development of recommendations for "protocol maxima" of IR appropriate to patient condition.

Prednosti in slabosti različnih protokolov vodenja vrednosti glukoze v krvi pri kritično bolnih pacientih

Uvod: Medicinske sestre v enotah intenzivne terapije uravnavajo ciljno vrednost glukoze v krvi pri kritično bolnih po sprejetih in veljavnih protokolih. Namen raziskave je bil raziskati prednosti in slabosti različnih protokolov vodenja  vrednosti glukoze v krvi pri kritično bolnih.Metode: Uporabljen je bil sistematični pregled znanstvene in strokovne literature. Iskanje literature je potekalo od 1. 2. 2017 do 8. 8. 2017. V pregled so bile vključene naslednje baze: COBIB.SI, Digitalna knjižnica Slovenije – Dlib.si, CINAHL, ProQuest, PubMed in Google Učenjak. Iskanje je potekalo z različnimi kombinacijami ključnih besed v slovenskem in angleškem jeziku: prednosti, slabosti, medicinske sestre, kritično bolni, glukoza v krvi in protokoli za vodenje vrednosti glukoze v krvi. Uporabljen je bil Boolov operater AND. Iz iskalnega nabora 1064 zadetkov je bilo v končno analizo  vključenih 15 člankov. Za obdelavo podatkov je bil uporabljen model analize konceptov.Rezultati: Identificirana so bila tri tematska področja: (1) primernost različnih protokolov za vodenje vrednosti glukoze v krvi, (2) delovne obremenitve medicinskih sester pri teh protokolih in (3) varnost protokolov. Prednosti računalniško podprtega protokola za vodenje vrednosti glukoze v krvi so v boljšem doseganju ciljne vrednosti koncentracije glukoze v krvi, slabosti pa v pojavu odstopanj v zvezi z načrtovanim časom za merjenje glukoze v krvi.Diskusija in zaključek: Nekatere raziskave ugotavljajo prednosti računalniško podprtih protokolov za vodenje vrednosti glukoze v krvi v smislu tehnoloških izboljšav, zmanjšanja delovnih obremenitev medicinskih sester in izboljšanja varnosti pacientov. Raziskava prispeva k izboljševanju klinične prakse pri delu s kritično bolnimi pacienti.