Cardioprotective effects of insulin: how intensive insulin therapy may benefit cardiac surgery patients

Interest in the effects of insulin on the heart came with the recognition that hyperglycemia in the context of myocardial infarction is associated with increased risks of mortality, congestive heart failure, or cardiogenic shock. More recently, instigated by research findings on stress hyperglycemia in critical illness, this interest has been extended to the influence of insulin on clinical outcome after cardiac surgery. Even in nondiabetic individuals, stress hyperglycemia commonly occurs as a key metabolic response to critical illness, eg, after surgical trauma. It is recognized as a major pathophysiological feature of organ dysfunction in the critically ill. The condition stems from insulin resistance brought about by dysregulation of key homeostatic processes, which implicates immune/inflammatory, endocrine, and metabolic pathways. It has been associated with adverse clinical outcomes, including increased mortality, increased duration of mechanical ventilation, increased intensive care unit (ICU) and hospital stay, and increased risk of infection. Hyperglycemia in critical illness is managed with exogenous insulin as standard treatment; however, there is considerable disagreement among experts in the field as to what target blood glucose level is optimal for the critically ill patient. Conventionally, the aim of insulin therapy has been to maintain blood glucose levels below the renal threshold, typically 220 mg/dL (12.2 mmol/L). In recent years, some have advocated tight glycemic control (TGC) with intensive insulin therapy (IIT) to normalize blood glucose levels to within the euglycemic range, typically 80 to 110 mg/dL (4.4–6.1 mmol/L).

Understanding post-operative temperature drop in cardiac surgery: a mathematical model

A mathematical model is presented to understand heat transfer processes during the cooling and re-warming of patients during cardiac surgery. Our compartmental model is able to account for many of the qualitative features observed in the cooling of various regions of the body including the central core containing the majority of organs, the rectal region containing the intestines and the outer peripheral region of skin and muscle. In particular, we focus on the issue of afterdrop: a drop in core temperature following patient re-warming, which can lead to serious post-operative complications. Model results for a typical cooling and re-warming procedure during surgery are in qualitative agreement with experimental data in producing the afterdrop effect and the observed dynamical variation in temperature between the core, rectal and peripheral regions. The influence of heat transfer processes and the volume of each compartmental region on the afterdrop effect is discussed. We find that excess fat on the peripheral and rectal regions leads to an increase in the afterdrop effect. Our model predicts that, by allowing constant re-warming after the core temperature has been raised, the afterdrop effect will be reduced.

Comparison of two methods of presenting risk information to patients about the side effects of medicines

Objective: To determine whether the use of verbal descriptors suggested by the European Union (EU) such as "common" (1-10% frequency) and "rare" (0.01-0.1%) effectively conveys the level of risk of side effects to people taking a medicine. Design: Randomised controlled study with unconcealed allocation. Participants: 120 adults taking simvastatin or atorvastatin after cardiac surgery or myocardial infarction. Setting: Cardiac rehabilitation clinics at two hospitals in Leeds, UK. Intervention: A written statement about one of the side effects of the medicine (either constipation or pancreatitis). Within each side effect condition half the patients were given the information in verbal form and half in numerical form (for constipation, "common" or 2.5%; for pancreatitis, "rare" or 0.04%). Main outcome measure: The estimated likelihood of the side effect occurring. Other outcome measures related to the perceived severity of the side effect, its risk to health, and its effect on decisions about whether to take the medicine. Results: The mean likelihood estimate given for the constipation side effect was 34.2% in the verbal group and 8.1% in the numerical group; for pancreatitis it was 18% in the verbal group and 2.1% in the numerical group. The verbal descriptors were associated with more negative perceptions of the medicine than their equivalent numerical descriptors. Conclusions: Patients want and need understandable information about medicines and their risks and benefits. This is essential if they are to become partners in medicine taking. The use of verbal descriptors to improve the level of information about side effect risk leads to overestimation of the level of harm and may lead patients to make inappropriate decisions about whether or not they take the medicine.