Detection Of Pathophysiological Changes Research Articles

Sugihara causality analysis of scalp EEG for detection of early Alzheimer's disease.

Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI) and early Alzheimer's disease (AD). The hypothesis of this work is that scalp EEG based causality measurements have different distributions for different cognitive groups and hence the causality measurements can be used to distinguish between NC, MCI, and AD participants. The current results are based on 30-channel resting EEG records from 48 age-matched participants (mean age 75.7 years) — 15 normal controls (NCs), 16 MCI, and 17 early-stage AD. First, a reconstruction model is developed for each EEG channel, which predicts the signal in the current channel using data of the other 29 channels. The reconstruction model of the target channel is trained using NC, MCI, or AD records to generate an NC-, MCI-, or AD-specific model, respectively. To avoid over fitting, the training is based on the leave-one-out principle. Sugihara causality between the channels is described by a quality score based on comparison between the reconstructed signal and the original signal. The quality scores are studied for their potential as biomarkers to distinguish between the different cognitive groups. First, the dimension of the quality scores is reduced to two principal components. Then, a three-way classification based on the principal components is conducted. Accuracies of 95.8%, 95.8%, and 97.9% are achieved for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. This work presents a novel application of Sugihara causality analysis to capture characteristic changes in EEG activity due to cognitive deficits. The developed method has excellent potential as individualized biomarkers in the detection of pathophysiological changes in early-stage AD.

Goal-Directed Therapy: New Trends and Horizons

In traumatized or critically ill patients suffering from a variety of severe illnesses, survival often depends on the successful handling of a chain of time-critical events with the ultimate goal to provide sufficient tissue oxygenation. Timely initiated goal-directed therapy (GDT) is a cornerstone in the care and treatment of these patients. Based on adequate monitoring techniques, goal-directed algorithms can facilitate the early detection of pathophysiological changes and influence therapies that may improve the clinical outcomes [1]. However, there are still many controversies regarding the application of GDT in different categories of patients [2]. Thus, a search for critical illnesses and conditions that might potentially profit from GDT may be of significant importance. In this special issue we have invited authors to submit original research and review articles elucidating the front of research and defining the optimal targets for the management and treatment of various perioperative and critically ill conditions, subsequently describing goal-oriented therapeutical interventions. The papers represent a wide spectrum of topics including early hemodynamic therapy in sepsis, perioperative monitoring, goal-directed hemodynamic optimization in cardiothoracic surgery, goal-oriented management of mechanical ventilation in respiratory failure, and important aspects of novel therapies in acute lung injury and acute respiratory distress syndrome. The publications reflect new therapeutic approaches for many critically ill patients. New targets for GDT and treatment algorithms are elucidated, such as static and dynamic preload parameters, weaning and derecruitment tests during ventilation, esophageal pressure, and other respiratory variables. The papers also reflect the limitations of current monitoring tools and therapeutic strategies and discuss the optimal indications of their use. We hope that the articles in this special issue will create new ideas of goal-directed therapies that can be evaluated for future clinical implementation. Mikhail Kirov Lars Bjertnaes Zsolt Molnar Samir Sakka

Perioperative haemodynamic therapy

To discuss the perioperative monitoring tools and targets for haemodynamic optimization and to assess the influence of goal-directed therapy (GDT) on organ function, complications and outcome in different categories of surgical patients. The choice of perioperative haemodynamic monitoring for GDT depends on the surgery-related and the patient-related risk. Conventional monitoring and minimally invasive approaches can be used for perioperative optimization of low-risk to moderate-risk patients. Thermodilution methods and continuous cardiac output/oxygen transport monitoring are the most reliable techniques for major surgery and high-risk/unstable patients. An important goal of perioperative haemodynamic therapy is to maintain cardiac function and organ perfusion, optimizing the balance between oxygen delivery and consumption. Several studies, using different monitoring tools and end-points, have shown that GDT provides optimal haemodynamic performance, improves organ function, reduces the number of complications and time to ICU and hospital discharge and decreases the mortality rate in high-risk surgical patients. GDT provides a number of benefits in major surgery. Based on adequate monitoring, the goal-directed algorithms facilitate early detection of pathophysiological changes and influence the perioperative haemodynamic therapy that can improve the clinical outcome. The perioperative GDT should be early, adequate and individualized for every patient.

Lactate Dehydrogenase Isoenzyme Pattern in Tissues and Serum of the Calf

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