Differential influence of arterial blood glucose on cerebral metabolism following severe traumatic brain injury

INTRODUCTION: Maintaining arterial blood glucose within tight limits is beneficial in critically ill patients. Upper and lower limits of detrimental blood glucose levels must be determined. METHODS: In 69 patients with severe traumatic brain injury (TBI), cerebral metabolism was monitored by assessing changes in arterial and jugular venous blood at normocarbia (partial arterial pressure of carbon dioxide (paCO2) 4.4 to 5.6 kPa), normoxia (partial arterial pressure of oxygen (paO2) 9 to 20 kPa), stable haematocrit (27 to 36%), brain temperature 35 to 38 degrees C, and cerebral perfusion pressure (CPP) 70 to 90 mmHg. This resulted in a total of 43,896 values for glucose uptake, lactate release, oxygen extraction ratio (OER), carbon dioxide (CO2) and bicarbonate (HCO3) production, jugular venous oxygen saturation (SjvO2), oxygen-glucose index (OGI), lactate-glucose index (LGI) and lactate-oxygen index (LOI). Arterial blood glucose concentration-dependent influence was determined retrospectively by assessing changes in these parameters within pre-defined blood glucose clusters, ranging from less than 4 to more than 9 mmol/l. RESULTS: Arterial blood glucose significantly influenced signs of cerebral metabolism reflected by increased cerebral glucose uptake, decreased cerebral lactate production, reduced oxygen consumption, negative LGI and decreased cerebral CO2/HCO3 production at arterial blood glucose levels above 6 to 7 mmol/l compared with lower arterial blood glucose concentrations. At blood glucose levels more than 8 mmol/l signs of increased anaerobic glycolysis (OGI less than 6) supervened. CONCLUSIONS: Maintaining arterial blood glucose levels between 6 and 8 mmol/l appears superior compared with lower and higher blood glucose concentrations in terms of stabilised cerebral metabolism. It appears that arterial blood glucose values below 6 and above 8 mmol/l should be avoided. Prospective analysis is required to determine the optimal arterial blood glucose target in patients suffering from severe TBI.

The role of admission blood glucose in outcome prediction of surviving patients with multiple injuries

BACKGROUND: Recent literature demonstrates hyperglycemia to be common in patients with trauma and associated with poor outcome in patients with traumatic brain injury and critically ill patients. The goal of this study was to analyze the impact of admission blood glucose on the outcome of surviving patients with multiple injuries. METHODS: Patients' charts (age >16) admitted to the emergency room of the University Hospital of Berne, Switzerland, between January 1, 2002, and December 31, 2004, with an Injury Severity Score >or=17 and more than one severely injured organ system were reviewed retrospectively. Outcome measurements included morbidity, intensive care unit, and hospital length of stay. RESULTS: The inclusion criteria were met by 555 patients, of which 108 (19.5%) patients died. After multiple regression analysis, admission blood glucose proved to be an independent predictor of posttraumatic morbidity (p < 0.0001), intensive care unit, and hospital length of stay (p < 0.0001), despite intensified insulin therapy on the intensive care unit. CONCLUSIONS: In this population of patients with multiple injuries, hyperglycemia on admission was strongly associated with increased morbidity, especially infections, prolonged intensive care unit, and hospital length of stay independent of injury severity, gender, age, and various biochemical parameters.

Admission blood glucose is an independent predictive factor for hospital mortality in polytraumatised patients

PURPOSE: The goal of this study was to analyse a possible association of admission blood glucose with hospital mortality of polytraumatised patients and to develop an outcome prediction model for this patient group. METHODS: The outcome of adult polytraumatised patients admitted to the University Hospital of Berne, Switzerland, between 2002 and 2004 with an ISS > or = 17, and more than one severely injured organ system was retrospectively analysed. RESULTS: The inclusion criteria were met by 555 patients, of which 108 (19.5%) died. Hyperglycaemia proved to be an independent predictor for hospital mortality (P < 0.0001), following multiple regression analysis. After inclusion of admission blood glucose, the calculated mortality prediction model performed better than currently described models (P < 0.0001, AUC 0.924). CONCLUSION: In this retrospective, single-centre study in polytraumatised patients, admission blood glucose proved to be an independent predictor of hospital mortality following regression analysis controlling for age, gender, injury severity and other laboratory parameters. A reliable admission blood glucose-based mortality prediction model for polytraumatised patients could be established. This observation may be helpful in improving the precision of future outcome prediction models for polytraumatised patients. These observations warrant further prospective evaluation.

Predictive value of cerebrospinal fluid (CSF) lactate level versus CSF/blood glucose ratio for the diagnosis of bacterial meningitis following neurosurgery.

The value of cerebrospinal fluid (CSF) lactate level and CSF/blood glucose ratio for the identification of bacterial meningitis following neurosurgery was assessed in a retrospective study. During a 3-year period, 73 patients fulfilled the inclusion criteria and could be grouped by preset criteria in one of three categories: proven bacterial meningitis (n = 12), presumed bacterial meningitis (n = 14), and nonbacterial meningeal syndrome (n = 47). Of 73 patients analyzed, 45% were treated with antibiotics and 33% with steroids at the time of first lumbar puncture. CSF lactate values (cutoff, 4 mmol/L), in comparison with CSF/blood glucose ratios (cutoff, 0.4), were associated with higher sensitivity (0.88 vs. 0.77), specificity (0.98 vs. 0.87), and positive (0.96 vs. 0.77) and negative (0.94 vs. 0.87) predictive values. In conclusion, determination of the CSF lactate value is a quick, sensitive, and specific test to identify patients with bacterial meningitis after neurosurgery.

Fasting blood glucose and 8-year mortality in the hypertension detection follow-up program population

This study analyzed the relationship between fasting blood glucose (FBG) and 8-year mortality in the Hypertension Detection Follow-up Program (HDFP) population. Fasting blood glucose (FBG) was examined both as a continuous variable and by specified FBG strata: Normal (FBG 60–100 mg/dL), Impaired (FBG ≥100 and ≤125 mg/dL), and Diabetic (FBG>125 mg/dL or pre-existing diabetes) subgroups. The relationship between type 2 diabetes was examined with all-cause mortality. This thesis described and compared the characteristics of fasting blood glucose strata by recognized glucose cut-points; described the mortality rates in the various fasting blood glucose strata using Kaplan-Meier mortality curves, and compared the mortality risk of various strata using Cox Regression analysis. Overall, mortality was significantly greater among Referred Care (RC) participants compared to Stepped Care (SC) {HR = 1.17; 95% CI (1.052,1.309); p-value = 0.004}, as reported by the HDFP investigators in 1979. Compared with SC participants, the RC mortality rate was significantly higher for the Normal FBG group {HR = 1.18; 95% CI (1.029,1.363); p-value = 0.019} and the Impaired FBG group, {HR = 1.34; 95% CI (1.036,1.734); p-value = 0.026,}. However, for the diabetic group, 8-year mortality did not differ significantly between the RC and SC groups after adjusting for race, gender, age, smoking status among Diabetic individuals {HR = 1.03; 95% CI (0.816,1.303); p-value = 0.798}. This latter finding is possibly due to a lack of a treatment difference of hypertension among Diabetic participants in both RC and SC groups. The largest difference in mortality between RC and SC was in the Impaired subgroup, suggesting that hypertensive patients with FBG between 100 and 125 mg/dL would benefit from aggressive antihypertensive therapy.^

Sources of familial aggregation and co-aggregation of fasting blood glucose and nutritional factors among Mexican -Americans in Starr County, Texas

The purpose of this study was to determine the effects of nutrient intake, genetic factors and common household environmental factors on the aggregation of fasting blood glucose among Mexican-Americans in Starr County, Texas. This study was designed to determine: (a) the proportion of variation of fasting blood glucose concentration explained by unmeasured genetic and common household environmental effects; (b) the degree of familial aggregation of measures of nutrient intake; and (c) the extent to which the familial aggregation of fasting blood glucose is explained by nutrient intake and its aggregation. The method of path analysis was employed to determine these various effects.^ Genes play an important role in fasting blood glucose: Genetic variation was found to explain about 40% of the total variation in fasting blood glucose. Common household environmental effects, on the other hand, explained less than 3% of the variation in fasting blood glucose levels among individuals. Common household effects, however, did have significant effects on measures of nutrient intake, though it explained only about 10% of the total variance in nutrient intake. Finally, there was significant familial aggregation of nutrient intake measures, but their aggregation did not contribute significantly to the familial aggregation of fasting blood glucose. These results imply that similarities among relatives for fasting blood glucose are not due to similarities in nutrient intake among relatives. ^

Automatic blood glucose classification for gestational diabetes with feature selection: decision trees vs neural networks

Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that compares 6 different feature selection methods for two machine learning algorithms: neural networks and decision trees. Three searching algorithms, Greedy, Best First and Genetic, were combined with two different evaluators, CSF and Wrapper, for the feature selection. The study has been made with 6080 blood glucose measurements from 25 patients. Decision trees with a feature set selected with the Wrapper evaluator and the Best first search algorithm obtained the best accuracy: 95.92%.

Carotid body chemoreceptor regulation of blood glucose during aerobic exercise

Regulación carótida en ejercicio aeróbico