Does Insulin Requirement Post Cardiac Surgery Predicts The Risk Of Developing Diabetes

Overview

The patient outcome in cardiac surgery is substantially linked to the occurrence of hyperglycemia. Qatar ranks 5th in the rate of diabetes globally; Moreover diabetics comprise more than 40% of patients admitted to the cardiac surgery intensive care unit (CTICU) in Qatar heart hospital. This prevalence is higher than the rest of the world. These numbers are projected to increase with accompanied morbidity-mortality hazardous by 2030 if the adequate intervention will not be directed towards better control of blood sugar within ICU and the hospital stay. The overall objective of this project is to explore the immunological profile in patients with poor glycemic control within their intensive care unit stay in Qatar. 'time in range' (TIR) was used for defining glycemic control within the ICU, where patients with time in range more than 80%, (in presence or absence of debates), had better outcomes than those with time in range less than 80% TIR. Notably, regarding wound infection, lengths of ventilation and ICU stay; they were not candidates to recurrent hypoglycemic episodes also. The high HbA1C preoperatively is probably a valid forecaster of indigent glycemic control. Previous studies demonstrated conversion of non-diabetics to diabetics when they face stress of critical illness. No previous studies explored this possible conversion cardiac surgery. Our primary objectives will be to determine whether non-diabetic patients with poor glycemic control in cardiac surgery would develop subsequent diabetes later on. Investigators will follow up non-diabetics patients after 3 months to satisfy this aim. Investigators will include all patients who will undergo cardiac surgery over two years from the time of approval without evidence of diabetes as documented by glycated hemoglobin (HbA1C). Patients will be followed up to one year with laboratory investigations to document whether they will develop diabetes or not. Data will be stored and statistically analyzed. Investigators expect to have details about the possible conversion in this high-risk population.

Critically ill patients frequently suffer from acute hyperglycemia, (a blood glucose level of more than 6.1 mmol/L (110 mg/dL)) and is observed in around 90 percent of ICU patients. Additionally, insulin resistance is expected in more than 80 percent of the critically ill which contributes to the problem. The hypothalamic-pituitary axis, sympathetic adrenergic system, and circulating pro-inflammatory cytokines including tumor necrosis factor alpha (TNF-α) and interleukins modulate hyperglycemia during stress. The seriousness of illness as expressed by the acute physiology and chronic health evaluation score (APACHE II), injury severity, surgery type and the Glasgow Coma Scale correlate with catecholamine and cortisol levels. Catecholamines are released mainly from the adrenal medulla. Multiple effects are assumed to be due to the surge of stress hormones (cardiovascular, immune and metabolic) targeting restoration of homeostasis during stress. Excessive glycogenolysis, gluconeogenesis, and insulin resistance characterize the neuroendocrine stress response. Increased hepatic output of glucose is predominantly the reason of stress hyperglycemia. Mediated through the liver adrenaline and noradrenaline excite gluconeogenesis and glycogenolysis; the latter has additional effects of enhancing glycerol provisions through lipolysis in the liver. Additionally, the emergence of insulin resistance could be due to the release of adipokines from adipose tissue during critical illness. Downgrading of insulin signal transduction is associated with increased TNF-α due to phosphorylation of different molecules straight over the path of insulin-signaling. Glucose redistribution from peripheral tissues towards immune cells during infection could be mediated by variable regulation of glucose transporter-1 and glucose transporter-4. Contributing factors for acute hyperglycemia during critical illness includes the concomitant secretion of additional stress hormones and the use of medications (steroids, lithium, vasopressors, inotropes and β-blockers). Intravenous glucose solutions, overfeeding, parenteral nutrition, and antibiotic and dialysis solutions, also precipitate hyperglycemia. Insulin deficiency or hypovolemia may also lead to hyperglycemia. Peripheral insulin resistance could be promoted with bed rest even without an obvious disease. Bed rest causes reduced skeletal muscle glucose uptake. Hyperglycemia in critically ill diabetics is an integration of pancreatic β-cell secretory disorders and insulin resistance. Consequences of hyperglycemia in the Critically ill patients: in different ICU populations Short-term drawbacks of hyperglycemia include effects on fluid balance through glycosuria and subsequently dehydration. Hyperglycemia associated with white blood cell abnormalities which could impair the complement pathway. Mitochondrial protein could be damaged with hyperglycemia, amplification of inflammatory pathways, altered innate immune system, and downgrading of endothelial functions. The peripheral blood flow could be compromised due to the reduction in endothelial nitric oxide and vascular reactivity with hyperglycemia. Acute hyperglycemia boosts proteolysis and is accompanied by a high risk of cardiac complications, electro-myocardial alteration, hemodynamic compromise, acute kidney injury, and death. Therefore poor clinical outcome and complications are associated with hyperglycemia. The persistence of hyperglycemia for a longer time distinctly associated with pediatric population outcome as expressed by morbidity and mortality. In Individual ICU populations, the risk of hyperglycemia and hypoglycemia increased in patients with sepsis. The Surviving Sepsis Campaign Guidelines recommend keeping the blood sugar below 10mmol/L. In neuro-critical care improved neurological outcome was observed with glucose control in patients, with a less strict glycemic target (7.7-10mmol/L). The impact of hyperglycemia was quantified in a meta-analysis for patients who had acute myocardial infarction. Postoperatively, intensive glucose control was associated with reduced acute heart failure, myocardial infarction, and death in vascular surgeries. Reduced death, infections and post-operative atrial fibrillation were observed after cardiac surgery with moderate blood sugar control. Interestingly, in a recent systemic review and meta-analysis stress hyperglycemia was associated with increased risk of subsequent diabetes in the critically ill. No previous studies went through future development of diabetes or impaired glucose tolerance after cardiac surgeries. 1. Objectives Primary objective : incident of developing diabetes and pre diabetes in patient with post operative stress hyperglycemia 2. Study Methodology * The study will be a prospective cohort study * Investigators will select patient without diabetes who will undergo cardiac surgery, patient will be divided into two groups group 1) Patients with uncontrolled blood sugar in the ICU; and group 2) patient with adequate control of blood sugar in ICU settings * The sample size will be calculated based on previous studies in critically ill patients * Subject inclusion and exclusion criteria Inclusion criteria: 1. Adult males and females above the age of 18 years subjected to cardiac surgery, 2. Acceptance to perform the study protocol and participate throughout the whole trial period (consent approval prior to participation), 3. Understanding the risks and benefits of the study and having signed a written informed consent. Exclusion criteria: Diabetics. Patients who refuse to participate or who /can not sign informed consent. Time in range (TIR), will be used to define the groups within the study, it is a measure of time where the blood glucose stays within the set target range. Our group point that it is it an easy measure that could be encountered without specific demands; therefore, it could be simply utilized in any ICU. Investigators will calculate the whole time of intravenous insulin infusion (A) and the time being within the set goal range (B) during intravenous insulin infusion and expressed TIR as TIR = (B/A) × 100. Our previous study showed that patients with more than 80% time in range, whether or not they had existing diabetes, had better outcomes than those with less than 80% time in range, as expressed by wound infection complication, duration of mechanical ventilation, and ICU length of stay. In addition, they were not candidates for recurrent hypoglycemic attacks. (27) Outcome measures Factors assessed at admission to the ICU will include age, gender, ethnicity, diabetes history, glycated hemoglobin (HbA1C), hypertension history, and surgery type. Investigators will record anesthesia time, cardiopulmonary bypass time (CPP), aortic cross clamp (ACC) time, utilization of inotropes and vasopressors, blood transfusion, Euro SCORE, medications including (statin therapy, steroids, vasopressors, and inotropes) length of mechanical ventilation, length of stay in the ICU and the hospital length of stay. Complications and outcomes, including acute kidney injury (AKI), post-operative atrial fibrillation (POAF), nosocomial infection, stroke, wound infection, and death, will reported for each patient. Data will be retrieved from an established database Dendrite Clinical Systems® (London, UK). Outcomes will be compared in subgroups of diabetics and non-diabetics, and factors associated with poor glycemic control will be analyzed. Outcomes and follow up An outpatient visit will be planned approximately three months after ICU discharge. At the time of this visit, Investigators will obtain age, BMI, waist circumference, diet, exercise, history of hypertension and family and personal history of elevated blood glucose to calculate the Finnish diabetes risk score (FINDRISC) questionnaire. (28) Oral glucose tolerance test (OGTT) will be performed according to the guidelines of the World Health Organization (WHO) with 75-g glucose load. Diabetes will be diagnosed according to the American Diabetes Association guidelines that stat fasting plasma glucose ≥126 mg/dl(7mmol/L) and/or 2-h plasma glucose during the OGTT ≥200 mg/dl (11.1mmol/L) and/or HbA1c ≥6.5 % (48 mmol/L); impaired glucose tolerance is noted when 2-h plasma glucose during the OGTT is between 140-200 mg/dl (7.7-11.1mmol/L). Impaired fasting glucose defined as fasting plasma glucose between 100-126 mg/dl (55.7mmol/L). The primary outcome will be the percentage of development of diabetes in non-diabetics after cardiac surgery The secondary outcome will be to identify whether those patients who are non-diabetics associated with increased morbidity in terms of ICU stay, post-operative atrial fibrillation (POAF), hospital acquired infections, and late wound infections Descriptive statistics will be used to summarize and determine the sample characteristics and distribution of various considered parameters related to demographic, presenting signs and symptoms, clinical features, post-operative outcome measures etc. The normally distributed data and results will be reported with mean and standard deviation (SD) with corresponding 95% confidence interval (CI); the remaining results will be reported with median and inter-quartile range (IQR). Categorical data will be summarized using frequencies and percentages. The focus of the data analysis in this study will be to determine the incident of developing diabetes and pre diabetes in patient with post-operative stress hyperglycemia. Associations between two or more qualitative variables will be assessed using Chi-square (χ2) or Fisher Exact tests as appropriate. Quantitative outcome measures between two independent groups will be analyzed using unpaired t or Mann Whitney U test depending on the normality of the data distribution. Concentration-time profiles for blood glucose, serum insulin and other related quantitative outcome measures will be analyzed as their respective areas under the curve (AUC) from baseline to specific post-baseline time points, with analysis across groups (normal, prediabetes, diabetes) performed by linear regression, with results presented as the marginal group means (95% CI) and associated p value. The impact of different potential covariates and factors will be assessed using multivariate linear regression model. Longitudinal changes in data across time points will be analyzed using a mixed model ANOVA. The relationship between incident of developing diabetes and pre diabetes in patient with post-operative stress hyperglycemia and main intrinsic and extrinsic risk factors (predictor or risk factors) will be estimated by deriving odds ratios (ORs) from logistic regression model and results will be presented and reported in odds ratio (OR) and associated 95% CI. A two-sided P value \<0.05 will be considered to be statistically significant. All statistical analyses will be done using statistical packages SPSS 23.0 (SPSS Inc. Chicago, IL) and Epi Info 2000 (Center for Disease Control and Prevention, Atlanta, Georgia, United States of America