Nutrition delivery, workload and performance in a model-based ICU glycaemic control system

Model-based subcutaneous insulin for glycemic control of pre-term infants in the neonatal intensive care unit

Hyperglycaemia is a common problem in neonatal intensive care units (NICUs). Achieving good control can result in better outcomes for patients. However, good control is difficult, where poor control and resulting hypoglycaemia reduces outcomes and confounds results. Clinically validated models can provide good control, and subcutaneous insulin delivery can provide more options for insulin therapy for clinicians. However, this combination has only been significantly utilised in adult outpatient diabetes, but could hold benefit for treating NICU infants. This research combines a well-validated NICU metabolic model with subcutaneous insulin kinetics models to assess the feasibility of a model-based approach. Clinical data from 12 very/extremely pre-mature infants was collected for an average study duration of 10.1 days. Blood glucose, interstitial and plasma insulin, as well as subcutaneous and local insulin were modelled, and patient-specific insulin sensitivity profiles were identified for each patient. Modelling error was low, where the cohort median [IQR] mean percentage error was 0.8 [0.3 3.4] %. For external validation, insulin sensitivity was compared to previous NICU cohorts using the same metabolic model, where overall levels of insulin sensitivity were similar. Overall, the combined system model accurately captured observed glucose and insulin dynamics, showing the potential for a model-based approach to glycaemic control using subcutaneous insulin in this cohort. The results justify further model validation and clinical trial research to explore a model-based protocol.

Estimating Enhanced Endogenous Glucose Production in Intensive Care Unit Patients with Severe Insulin Resistance

BACKGROUND

Critically ill ICU patients frequently experience acute insulin resistance and increased endogenous glucose production, manifesting as stress-induced hyperglycemia and hyperinsulinemia. STAR (Stochastic TARgeted) is a glycemic control protocol, which directly manages inter- and intra- patient variability using model-based insulin sensitivity (SI). The model behind STAR assumes a population constant for endogenous glucose production (EGP), which is not otherwise identifiable.

OBJECTIVE

This study analyses the effect of estimating EGP for ICU patients with very low SI (severe insulin resistance) and its impact on identified, model-based insulin sensitivity identification, modeling accuracy, and model-based glycemic clinical control.

METHODS

Using clinical data from 717 STAR patients in 3 independent cohorts (Hungary, New Zealand, and Malaysia), insulin sensitivity, time of insulin resistance, and EGP values are analyzed. A method is presented to estimate EGP in the presence of non-physiologically low SI. Performance is assessed via model accuracy.

RESULTS

Results show 22%-62% of patients experience 1+ episodes of severe insulin resistance, representing 0.87%-9.00% of hours. Episodes primarily occur in the first 24 h, matching clinical expectations. The Malaysian cohort is most affected. In this subset of hours, constant model-based EGP values can bias identified SI and increase blood glucose (BG) fitting error. Using the EGP estimation method presented in these constrained hours significantly reduced BG fitting errors.

CONCLUSIONS

Patients early in ICU stay may have significantly increased EGP. Increasing modeled EGP in model-based glycemic control can improve control accuracy in these hours. The results provide new insight into the frequency and level of significantly increased EGP in critical illness.

The goldilocks problem: Nutrition and its impact on glycaemic control

BACKGROUND

Glucose intolerance and insulin resistance manifest as hyperglycaemia in intensive care, which is associated with mortality and morbidities. Glycaemic control (GC) may improve outcomes, though safe and effective control has proven elusive. Nutritional glucose intake affects blood glucose (BG) outcomes, but few protocols actively control it. This study aims to examine BG outcomes in the context of nutritional management during GC.

METHODS

Retrospective cohort analysis of 5 glycaemic control cohorts spanning 4 years (n = 273) from Christchurch Hospital Intensive Care Unit (ICU). GC is delivered using a single model-based protocol (STAR), with default 4.4-8.0 mmol/L target range via. modulation of insulin and nutrition. Clinical adaptations/cohorts include variations on upper target (UL-9 with 9.0 mmol/L, reducing workload and nutrition responsiveness), and insulin only (IO) with clinically set nutrition at 3 glucose concentrations (71 g/L vs. 120 and 180 g/L in the TARGET study).

RESULTS

Percent of BG hours in the 4.4-8.0 mmol/L range highest under standard STAR conditions (78%), and was lower at 64% under UL-9, likely due to reduced time-responsiveness of nutrition-insulin changes. By comparison, IO only resulted in 64-69% BG in range across different nutrition types. A subset of patients receiving high glucose nutrition under IO were persistently hyperglycaemic, indicating patient-specific glucose tolerance.

CONCLUSION

STAR GC is most effective when nutrition and insulin are modulated together with timely responsiveness to persistent hyperglycaemia. Results imply modulation of nutrition alongside insulin improves GC, particularly in patients with persistent hyperglycaemia/low glucose tolerance.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

Background

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

Methods

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

Results

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

Conclusion

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

BACKGROUND

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

METHODS

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

RESULTS

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

CONCLUSION

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Assessment of Glycemic Control Protocol (STAR) Through Compliance Analysis Amongst Malaysian ICU Patients

Purpose

This paper presents an assessment of an automated and personalized stochastic targeted (STAR) glycemic control protocol compliance in Malaysian intensive care unit (ICU) patients to ensure an optimized usage.

Patients and Methods

STAR proposes 1–3 hours treatment based on individual insulin sensitivity variation and history of blood glucose, insulin, and nutrition. A total of 136 patients recorded data from STAR pilot trial in Malaysia (2017–quarter of 2019*) were used in the study to identify the gap between chosen administered insulin and nutrition intervention as recommended by STAR, and the real intervention performed.

Results

The results show the percentage of insulin compliance increased from 2017 to first quarter of 2019* and fluctuated in feed administrations. Overall compliance amounted to 98.8% and 97.7% for administered insulin and feed, respectively. There was higher average of 17 blood glucose measurements per day than in other centres that have been using STAR, but longer intervals were selected when recommended. Control safety and performance were similar for all periods showing no obvious correlation to compliance.

Conclusion

The results indicate that STAR, an automated model-based protocol is positively accepted among the Malaysian ICU clinicians to automate glycemic control and the usage can be extended to other hospitals already. Performance could be improved with several propositions.

Usability study of a new tool for nutritional and glycemic management in adult intensive care: Glucosafe 2

The new decision support tool Glucosafe 2 (GS2) is based on a mathematical model of glucose and insulin dynamics, designed to assist caregivers in blood glucose control and nutrition. This study aims to assess end-user acceptance and usability of this bedside decision support tool in an adult intensive care setting. Caregivers were first trained and then invited to trial GS2 prototype on bedside computers. Data for qualitative analysis were collected through semi-structured interviews from twenty users after minimum three trial days. Most caregivers (70%) rated GS2 as convenient and believed it would help improving adherence to current guidelines (85%). Moreover, most nurses (80%) believed that GS2 would be timesaving. Nurses' risk perceptions and manual data entry emerged as central barriers to use GS2 in routine practice. Issues emerged from the caregivers were compiled into a list of 12 modifications of the GS2 prototype to increase end-user acceptance and usability. This usability study showed that GS2 was considered by ICU caregivers as helpful in daily clinical practice, allowing time-saving and better standardization of ICU patient's care. Important issues were raised by the users with implications for the development and deployment of GS2. Integrating the technology into existing IT infrastructure may facilitate caregivers' acceptance. Further clinical studies of the performance and potential health outcomes are warranted.