Intensive Insulin Therapy in Mixed Medical/Surgical Intensive Care Units: Benefit Versus Harm
ABSTRACT Intensive insulin therapy (IIT) improves the outcome of prolonged critically ill patients, but concerns remain regarding potential harm and the optimal blood glucose level. These questions were addressed using the pooled dataset of two randomized controlled trials. Independent of parenteral glucose load, IIT reduced mortality from 23.6 to 20.4% in the intention-to-treat group (n = 2,748; P = 0.04) and from 37.9 to 30.1% among long stayers (n = 1,389; P = 0.002), with no difference among short stayers (8.9 vs. 10.4%; n = 1,359; P = 0.4). Compared with blood glucose of 110-150 mg/dl, mortality was higher with blood glucose >150 mg/dl (odds ratio 1.38 [95% CI 1.10-1.75]; P = 0.007) and lower with <110 mg/dl (0.77 [0.61-0.96]; P = 0.02). Only patients with diabetes (n = 407) showed no survival benefit of IIT. Prevention of kidney injury and critical illness polyneuropathy required blood glucose strictly <110 mg/day, but this level carried the highest risk of hypoglycemia. Within 24 h of hypoglycemia, three patients in the conventional and one in the IIT group died (P = 0.0004) without difference in hospital mortality. No new neurological problems occurred in survivors who experienced hypoglycemia in intensive care units (ICUs). We conclude that IIT reduces mortality of all medical/surgical ICU patients, except those with a prior history of diabetes, and does not cause harm. A blood glucose target <110 mg/day was most effective but also carried the highest risk of hypoglycemia.
- SourceAvailable from: Ida Torunn Bjørk
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- "To assess the patient comprehensively, nurses must also identify unpleasant symptoms, such as delirium (Ely et al., 2001; Girard et al., 2010), depression (Idemoto, 2005; Li and Puntillo, 2006) and fatigue (Lerdal et al., 2009; Chen et al., 2010). The syndrome critical illness polyneuropathy/myopathy (CIP/CIM) (Van den Berghe et al., 2006; Hermans et al., 2007) may also influence nurses' assessments. In this study, we refer to CIP/CIM as an unpleasant symptom. "
ABSTRACT: To describe intensive care nurses' perceptions and assessments of unpleasant symptoms and signs in mechanically ventilated and sedated adult intensive care patients. Mechanically ventilated patients are unable to express themselves verbally and depend upon nurses to control their symptoms by understanding their unpleasant experiences, such as pain, anxiety or delirium and interpret the relevant signs. Nurses must have enough knowledge to adjust their analgesics and sedatives appropriately and to avoid under- or oversedation. A cross-sectional survey design. A study with a self-administrated questionnaire was undertaken in October 2007 to February 2008, with a convenience sample of 183 intensive care nurses in Norway. The questionnaire was completed by 86 (47%) nurses. Most perceived that critical illness polyneuropathy/myopathy occurred frequently. Half the nurses underestimated pain, anxiety and delirium. Signs such as a response to contact, cough reflex, wakefulness and muscle tone were considered most important in assessing oversedation. Agitation, facial grimacing, tube intolerance and wakefulness were considered most important in assessing undersedation. The Comfort Scale and Adoption of the Intensive Care Environment corresponded best to the signs identified by the nurses. The nurses underestimated unpleasant symptoms other than critical illness polyneuropathy/myopathy. A further mapping of patients' experiences should be conducted, with an emphasis on the more 'silent' distressing symptoms. Further tools to facilitate the communication of consciousness levels and the intolerance of unpleasant symptoms must be developed and implemented. A deeper understanding of unpleasant symptoms and signs focused in learning activities may help nurses to recognize patients' early problems and allow targeted interventions. A more active stimulus-response assessment of ICU patients is required to detect oversedation, critical illness polyneuropathy/myopathy and hypoactive delirium. Assessment tools should reflect both the patient's tolerance of various unpleasant symptoms and the level of consciousness.Nursing in Critical Care 07/2013; 18(4):176-86. DOI:10.1111/nicc.12012 · 0.87 Impact Factor
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- "These pathophysiologic changes have their impact on the course of anesthesia and surgery specially cardiac surgery and cardiopulmonary bypass . Studies showed that a fraction of nondiabetic patients were found to have glucose intolerance due to the stressful situation of anesthesia and cardiopulmonary bypass  . Recent studies showed that although tight euglycemic control has its beneficial effect on reducing neurological and infectious complications yet this was offset by the possibility of hypoglycemia which is more dangerous in case of general anesthesia in the short term view . "
ABSTRACT: Background Blood glucose control is an important factor in improving outcome of diabetic patients undergoing cardiac surgery.Objective Is to estimate the relation between blood glucose control and perioperative outcomes in these patients.Study designProspective cohort study.Methods One hundred diabetic patients undergoing cardiac surgery, were divided equally into group I (control group) in whom no tight glycemic control was done and group II (study group) in which tight glycemic control was done. Patients in the study group received intra-operatively an infusion of rapidly acting insulin according to a modified protocol to keep blood glucose level between 80 and 110 mg/dl and continued in the ICU until complete recovery from anesthesia. Patients in the control group followed the same protocol of insulin infusion only if their peri-operative blood glucose level exceeded 180 mg/dl.ResultsThere was a rise of blood glucose level in the control group patients till the end of operations (mean level = 227 mg/dl). Mean blood glucose level before CPB was comparable in the two groups, but was significantly different after that until extubation. We reported three cases of delayed recovery in the control group compared to one case in the study group. We also recorded four cases of cardiac problems in group I compared to one case in group II (P = 0.044). There was statistically significant difference between groups regarding renal, neurological and surgical post-operative complications.Conclusion Tight glycemic control is recommended for better patient’s outcome after cardiac anesthesia.01/2013; 29(1):71–76. DOI:10.1016/j.egja.2012.06.002
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- "Hyperglycaemia worsens outcomes, increasing the risk of severe infection , myocardial infarction , and critical illnesses such as polyneuropathy and multiple organ failure . However, repeating these results has been difficult, and thus the role of tight glyceamic control during critical illness and suitable glycaemic ranges have been under scrutiny in recent years        . However, conclusions are varied with both success    , failure,  and, primarily, no clear outcome      . "
ABSTRACT: Intensive insulin therapy (IIT) and tight glycaemic control (TGC), particularly in intensive care unit (ICU), are the subjects of increasing and controversial debate in recent years. Model-based TGC has shown potential in delivering safe and tight glycaemic management, all the while limiting hypoglycaemia. A comprehensive, more physiologically relevant Intensive Control Insulin-Nutrition-Glucose (ICING) model is presented and validated using data from critically ill patients. Two existing glucose-insulin models are reviewed and formed the basis for the ICING model. Model limitations are discussed with respect to relevant physiology, pharmacodynamics and TGC practicality. Model identifiability issues are carefully considered for clinical settings. This article also contains significant reference to relevant physiology and clinical literature, as well as some references to the modeling efforts in this field. Identification of critical constant population parameters was performed in two stages, thus addressing model identifiability issues. Model predictive performance is the primary factor for optimizing population parameter values. The use of population values are necessary due to the limited clinical data available at the bedside in the clinical control scenario. Insulin sensitivity, S(I), the only dynamic, time-varying parameter, is identified hourly for each individual. All population parameters are justified physiologically and with respect to values reported in the clinical literature. A parameter sensitivity study confirms the validity of limiting time-varying parameters to S(I) only, as well as the choices for the population parameters. The ICING model achieves median fitting error of <1% over data from 173 patients (N=42,941 h in total) who received insulin while in the ICU and stayed for ≥ 72 h. Most importantly, the median per-patient 1-h ahead prediction error is a very low 2.80% [IQR 1.18, 6.41%]. It is significant that the 75th percentile prediction error is within the lower bound of typical glucometer measurement errors of 7-12%. These results confirm that the ICING model is suitable for developing model-based insulin therapies, and capable of delivering real-time model-based TGC with a very tight prediction error range. Finally, the detailed examination and discussion of issues surrounding model-based TGC and existing glucose-insulin models render this article a mini-review of the state of model-based TGC in critical care.Computer methods and programs in biomedicine 05/2011; 102(2):192-205. DOI:10.1016/j.cmpb.2010.12.008 · 1.09 Impact Factor