Anaesthetic drugs act at sites within the brain that undergo profound changes during typical ageing. We postulated that anaesthesia-induced brain dynamics observed in the EEG change with age. We analysed the EEG in 155 patients aged 18-90 yr who received propofol (n=60) or sevoflurane (n=95) as the primary anaesthetic. The EEG spectrum and coherence were estimated throughout a 2 min period of stable anaesthetic maintenance. Age-related effects were characterized by analysing power and coherence as a function of age using linear regression and by comparing the power spectrum and coherence in young (18- to 38-yr-old) and elderly (70- to 90-yr-old) patients. Power across all frequency bands decreased significantly with age for both propofol and sevoflurane; elderly patients showed EEG oscillations ∼2- to 3-fold smaller in amplitude than younger adults. The qualitative form of the EEG appeared similar regardless of age, showing prominent alpha (8-12 Hz) and slow (0.1-1 Hz) oscillations. However, alpha band dynamics showed specific age-related changes. In elderly compared with young patients, alpha power decreased more than slow power, and alpha coherence and peak frequency were significantly lower. Older patients were more likely to experience burst suppression. These profound age-related changes in the EEG are consistent with known neurobiological and neuroanatomical changes that occur during typical ageing. Commercial EEG-based depth-of-anaesthesia indices do not account for age and are therefore likely to be inaccurate in elderly patients. In contrast, monitoring the unprocessed EEG and its spectrogram can account for age and individual patient characteristics.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Objectives: Although obesity is associated with risk for chronic kidney disease and improved survival, less is known about the associations of obesity with risk of acute kidney injury and post acute kidney injury mortality. Design: In a single-center inception cohort of almost 15,000 critically ill patients, we evaluated the association of obesity with acute kidney injury and acute kidney injury severity, as well as in-hospital and 1-year survival. Acute kidney injury was defined using the Kidney Disease Outcome Quality Initiative criteria. Measurements and Main Results: The acute kidney injury prevalence rates for normal, overweight, class I, II, and III obesity were 18.6%, 20.6%, 22.5%, 24.3%, and 24.0%, respectively, and the adjusted odds ratios of acute kidney injury were 1.18 (95% CI, 1.06–1.31), 1.35 (1.19–1.53), 1.47 (1.25–1.73), and 1.59 (1.31–1.87) when compared with normal weight, respectively. Each 5-kg/m² increase in body mass index was associated with a 10% risk (95% CI, 1.06–1.24; p < 0.001) of more severe acute kidney injury. Within-hospital and 1-year survival rates associated with the acute kidney injury episodes were similar across body mass index categories. Conclusion: Obesity is a risk factor for acute kidney injury, which is associated with increased short- and long-term mortality.

Objective: Acute kidney injury affects 5% to 7% of all hospitalized patients with a much higher incidence in the critically ill. The Acute Kidney Injury Network proposed a definition in which serum creatinine rises (>0.3 mg/dL) and/or oliguria (<0.5 mL/kg/hr) for a period of 6 hrs are used to detect acute kidney injury. Accurate urine output measurements as well as serum creatinine values from our database were used to detect patients with acute kidney injury and calculate their corresponding mortality risk and length of stay. Design: Retrospective cohort study. Setting: Seven intensive care units at a large, academic, tertiary medical center. Patients: Adult patients without evidence of end-stage renal disease with more than two creatinine measurements and at least a 6-hr urine output recording who were admitted to the intensive care unit between 2001 and 2007. Interventions: Medical records of all the patients were reviewed. Demographic information, laboratory results, charted data, discharge diagnoses, physiological data, and patient outcomes were extracted from the Multiparameter Intelligent Monitoring in Intensive Care II database using a SQL query. Measurements and Main Results: From 19,677 adult patient records, 14,524 patients met the inclusion criteria. Fifty-seven percent developed acute kidney injury during their intensive care unit stay. Inhospital mortality rates were: 13.9%, 16.4%, 33.8% for acute kidney injury 1, 2, and 3, respectively, compared with only 6.2% in patients without acute kidney injury (p < .0001). After adjusting for multiple covariates, acute kidney injury was associated with increased hospital mortality (odds ratio 1.4 and 1.3 for acute kidney injury 1 and acute kidney injury 2 and 2.5 for acute kidney injury 3; p < .0001). Using multivariate logistic regression, we found that in patients who developed acute kidney injury, urine output alone was a better mortality predictor than creatinine alone or the combination of both. Conclusions: More than 50% of our critically ill patients developed some stage of acute kidney injury resulting in a stagewise increased mortality risk. However, the mortality risk associated with acute kidney injury stages 1 and 2 does not differ significantly. In light of these findings, re-evaluation of the Acute Kidney Injury Network staging criteria should be considered.