Pharmacologic management of the critically ill patient in the perioperative period--emphasis on the sepsis syndrome

Reducing the impact of insulin sensitivity variability on glycaemic outcomes using separate stochastic models within the STAR glycaemic protocol

BACKGROUND

The metabolism of critically ill patients evolves dynamically over time. Post critical insult, levels of counter-regulatory hormones are significantly elevated, but decrease rapidly over the first 12-48 hours in the intensive care unit (ICU). These hormones have a direct physiological impact on insulin sensitivity (SI). Understanding the variability of SI is important for safely managing glycaemic levels and understanding the evolution of patient condition. The objective of this study is to assess the evolution of SI over the first two days of ICU stay, and using this data, propose a separate stochastic model to reduce the impact of SI variability during glycaemic control using the STAR glycaemic control protocol.

METHODS

The value of SI was identified hourly for each patient using a validated physiological model. Variability of SI was then calculated as the hour-to-hour percentage change in SI. SI was examined using 6 hour blocks of SI to display trends while mitigating the effects of noise. To reduce the impact of SI variability on achieving glycaemic control a new stochastic model for the most variable period, 0-18 hours, was generated. Virtual simulations were conducted using an existing glycaemic control protocol (STAR) to investigate the clinical impact of using this separate stochastic model during this period of increased metabolic variability.

RESULTS

For the first 18 hours, over 80% of all SI values were less than 0.5 × 10(-3) L/mU x min, compared to 65% for >18 hours. Using the new stochastic model for the first 18 hours of ICU stay reduced the number of hypoglycaemic measurements during virtual trials. For time spent below 4.4, 4.0, and 3.0 mmol/L absolute reductions of 1.1%, 0.8% and 0.1% were achieved, respectively. No severe hypoglycaemic events (BG < 2.2 mmol/L) occurred for either case.

CONCLUSIONS

SI levels increase significantly, while variability decreases during the first 18 hours of a patients stay in ICU. Virtual trials, using a separate stochastic model for this period, demonstrated a reduction in variability and hypoglycaemia during the first 18 hours without adversely affecting the overall level of control. Thus, use of multiple models can reduce the impact of SI variability during model-based glycaemic control.

Modern approaches to the therapy of septic shock

Bacteremia from gram-negative rods is a great cause of concern for hospital physicians today. Shock-complicating gram-negative sepsis has a mortality rate of 60% and above, despite early diagnosis and treatment. Intensive research efforts have shown new pathophysiological mechanisms and mediators involved in septic shock, with changes in recommended treatment protocols. In this report, the authors review the use of corticosteroids, fibronectin, naloxone hydrochloride, and immunotherapy, with emphasis on theoretical considerations and relevant clinical experience. Although these treatment methods may have been promising initially, data from large double-blind human trials are either lacking or unencouraging. While continued research and modern therapeutic approaches should improve future survival rates from septic shock, use of the therapies reviewed should be considered experimental at this time.