Increased prognostic accuracy of TBI when a brain electrical activity biomarker is added to loss of consciousness (LOC).

BACKGROUND: Extremely high accuracy for predicting CT+ traumatic brain injury (TBI) using a quantitative EEG (QEEG) based multivariate classification algorithm was demonstrated in an independent validation trial, in Emergency Department (ED) patients, using an easy to use handheld device. This study compares the predictive power using that algorithm (which includes LOC and amnesia), to the predictive power of LOC alone or LOC plus traumatic amnesia. PARTICIPANTS: ED patients 18-85years presenting within 72h of closed head injury, with GSC 12-15, were study candidates. 680 patients with known absence or presence of LOC were enrolled (145 CT+ and 535 CT- patients). METHODS: 5-10min of eyes closed EEG was acquired using the Ahead 300 handheld device, from frontal and frontotemporal regions. The same classification algorithm methodology was used for both the EEG based and the LOC based algorithms. Predictive power was evaluated using area under the ROC curve (AUC) and odds ratios. RESULTS: The QEEG based classification algorithm demonstrated significant improvement in predictive power compared with LOC alone, both in improved AUC (83% improvement) and odds ratio (increase from 4.65 to 16.22). Adding RGA and/or PTA to LOC was not improved over LOC alone. CONCLUSIONS: Rapid triage of TBI relies on strong initial predictors. Addition of an electrophysiological based marker was shown to outperform report of LOC alone or LOC plus amnesia, in determining risk of an intracranial bleed. In addition, ease of use at point-of-care, non-invasive, and rapid result using such technology suggests significant value added to standard clinical prediction.

Hypokalemia in diabetic ketoacidosis is less common than previously reported.

[K+] < 3.5 mmol/L is reported to occur in approximately 4 % of patients with diabetic ketoacidosis (DKA.) Therefore, the American Diabetes Association (ADA) and Joint British Diabetes Societies (JBDS) recommend the assessment of [K+] before the initiation of insulin treatment to avoid the precipitation of morbid hypokalemia. The purpose of this study was to assess the incidence of hypokalemia in patients presenting to the emergency department (ED) with DKA. This was a multicenter retrospective, cross-sectional study at EDs with a combined annual adult census of 155,000. Adult patients diagnosed with DKA in the ED, or who were admitted from the ED and subsequently diagnosed with DKA as determined from the hospital electronic database between January 2008 and December 2008, were included for analysis if they had the following initial laboratory values: (1) serum glucose >13.9 mmol/L (250 mg/dL), (2) serum bicarbonate <18 mmol/L (18 mEq/L) or anion gap >15, and (3) evidence of ketonaemia or ketonuria. 537 patients were diagnosed with DKA in the ED at the participating institutions during the reference period. The median [K+] was 4.9 mmol/L (IQR 4.3, 5.5). There were a total of seven patients with an initial 3.3 < [K+] < 3.5 mmol/L, but none with a [K+] < 3.3 mmol/L. Thus, no patients in our study sample required potassium supplementation before the initiation of insulin treatment. The incidence of hypokalemia in our sample of patients with DKA was much less than previously reported, with no cases requiring potassium supplementation before insulin administration.

Quantitative brain electrical activity in the initial screening of mild traumatic brain injuries.

INTRODUCTION: The incidence of emergency department (ED) visits for Traumatic Brain Injury (TBI) in the United States exceeds 1,000,000 cases/year with the vast majority classified as mild (mTBI). Using existing computed tomography (CT) decision rules for selecting patients to be referred for CT, such as the New Orleans Criteria (NOC), approximately 70% of those scanned are found to have a negative CT. This study investigates the use of quantified brain electrical activity to assess its possible role in the initial screening of ED mTBI patients as compared to NOC. METHODS: We studied 119 patients who reported to the ED with mTBI and received a CT. Using a hand-held electroencephalogram (EEG) acquisition device, we collected data from frontal leads to determine the likelihood of a positive CT. The brain electrical activity was processed off-line to generate an index (TBI-Index, biomarker). This index was previously derived using an independent population, and the value found to be sensitive for significant brain dysfunction in TBI patients. We compared this performance of the TBI-Index to the NOC for accuracy in prediction of positive CT findings. RESULTS: Both the brain electrical activity TBI-Index and the NOC had sensitivities, at 94.7% and 92.1% respectively. The specificity of the TBI-Index was more than twice that of NOC, 49.4% and 23.5% respectively. The positive predictive value, negative predictive value and the positive likelihood ratio were better with the TBI-Index. When either the TBI-Index or the NOC are positive (combining both indices) the sensitivity to detect a positive CT increases to 97%. CONCLUSION: The hand-held EEG device with a limited frontal montage is applicable to the ED environment and its performance was superior to that obtained using the New Orleans criteria. This study suggests a possible role for an index of brain function based on EEG to aid in the acute assessment of mTBI patients.