Mammalian hibernation: a unique model for medical research

Hibernation is an adaptive behavior for some small animals to survive cold winter. Hibernating mammals usually down-regulate their body temperature from ~37°C to only a few degrees. During the evolution, mammalian hibernators have inherited unique strategies to survive extreme conditions that may lead to disease or death in humans and other non-hibernators. Hibernating mammals can not only tolerant deep hypothermia, hypoxia and anoxia, but also protect them against osteoporosis, muscle atrophy, heart arrhythmia and ischemia-reperfusion injury. Finding the molecular and regulatory mechanisms underlying these adaptations will provide novel ideas for treating related human diseases.

On the review of electronic technologies applied to implantable medical devices

The development of electronic implantable medical devices (IMD) has been increasing over the years, targeting very diverse applications and implementing different technologies. The impact of IMDs in the treatment of different ailments like Parkinson’s disease, hearing impairment, heart arrhythmia, and chronic pain, among many others, has been notorious and inspired their exploration to treat other health problems. Even when there is great interest in the scientific community for the exploration and development of IMDs, no standards are ruling its development. This lack of standardization is the reason why the analysis of the tendencies of this area from the technical point of view becomes complex. The analysis of the tendencies in the development of IMD devices required the exploration of diverse sources, which describe heterogeneous systems using very different approaches and methodologies for similar problems. In this paper an open SQL database intended for collecting information from IMD publications is presented; at this point, more than 200 published works are feed in the database covering a period from 1974 to 2018. This database is extensible and enables researchers to find trends and explore the development of IMDs from a broader perspective. We also used this database as a proof of concept to explore some general trends in the design of IMDs based on the included works.

Percolation and tortuosity in heart-like cells

In the last several years, quite a few papers on the joint question of transport, tortuosity and percolation have appeared in the literature, dealing with passage of miscellaneous liquids or electrical currents in different media. However, these methods have not been applied to the passage of action potential in heart fibrosis (HF), which is crucial for problems of heart arrhythmia, especially of atrial tachycardia and fibrillation. In this work we address the HF problem from these aspects. A cellular automaton model is used to analyze percolation and transport of a distributed-fibrosis inflicted heart-like tissue. Although based on a rather simple mathematical model, it leads to several important outcomes: (1) It is shown that, for a single wave front (as the one emanated by the heart's sinus node), the percolation of heart-like matrices is exactly similar to the forest fire case. (2) It is shown that, on the average, the shape of the transport (a question not dealt with in relation to forest fire, and deals with the delay of action potential when passing a fibrotic tissue) behaves like a Gaussian. (3) Moreover, it is shown that close to the percolation threshold the parameters of this Gaussian behave in a critical way. From the physical point of view, these three results are an important contribution to the general percolation investigation. The relevance of our results to cardiological issues, specifically to the question of reentry initiation, are discussed and it is shown that: (A) Without an ectopic source and under a mere sinus node operation, no arrhythmia is generated, and (B) A sufficiently high refractory period could prevent some reentry mechanisms, even in partially fibrotic heart tissue.

A Novel Two-Stage Heart Arrhythmia Ensemble Classifier

Atrial fibrillation (AF) and ventricular arrhythmia (Arr) are among the most common and fatal cardiac arrhythmias in the world. Electrocardiogram (ECG) data, collected as part of the UK Biobank, represents an opportunity for analysis and classification of these two diseases in the UK. The main objective of our study is to investigate a two-stage model for the classification of individuals with AF and Arr in the UK Biobank dataset. The current literature addresses heart arrhythmia classification very extensively. However, the data used by most researchers lack enough instances of these common diseases. Moreover, by proposing the two-stage model and separation of normal and abnormal cases, we have improved the performance of the classifiers in detection of each specific disease. Our approach consists of two stages of classification. In the first stage, features of the ECG input are classified into two main classes: normal and abnormal. At the second stage, the features of the ECG are further categorised as abnormal and further classified into two diseases of AF and Arr. A diverse set of ECG features such as the QRS duration, PR interval and RR interval, as well as covariates such as sex, BMI, age and other factors, are used in the modelling process. For both stages, we use the XGBoost Classifier algorithm. The healthy population present in the data, has been undersampled to tackle the class imbalance present in the data. This technique has been applied and evaluated using an ECG dataset from the UKBioBank ECG taken at rest repository. The main results of our paper are as follows: The classification performance for the proposed approach has been measured using F1 score, Sensitivity (Recall) and Specificity (Precision). The results of the proposed system are 87.22%, 88.55% and 85.95%, for average F1 Score, average sensitivity and average specificity, respectively. Contribution and significance: The performance level indicates that automatic detection of AF and Arr in participants present in the UK Biobank is more precise and efficient if done in a two-stage manner. Automatic detection and classification of AF and Arr individuals this way would mean early diagnosis and prevention of more serious consequences later in their lives.

The Evolution of Digital Technologies in Health Care

Although digital health often is touted as something revolutionary and brand new, the truth is that electronic biomedical equipment has existed for decades and many new digital health tools are simply incremental enhancements. In some cases, a device has been miniaturized for convenience and home use. In other cases, novel algorithms are being placed into clinician workflow as decision aids, not unlike the Physicians’ Desk Reference (PDR) that often was consulted during clinical encounters. The part that is new is Internet connectivity and all the accompanying benefits and risks. In this chapter, the history of biomedical tools and their evolution over the last three decades is reviewed in detail with an eye toward understanding incremental advancements, such as miniaturized heart arrhythmia measurement tools, as well as leaps in progress, such as the widespread adoption of electronic health records.

Failure of non-vitamin K antagonist oral anticoagulants in preventing stroke in elderly patient: a case report of multiple strokes on standard of care treatment for atrial fibrillation

Atrial fibrillation (AF) is the most common type of treated heart arrhythmia. Generally, the treatment goals for atrial fibrillation are to reset the rhythm or control the rate and prevent the development and subsequent embolization of atrial thrombi. These thromboembolic events can occur with any kind of atrial fibrillation that is paroxysmal, persistent or permanent. In patients who are candidate for anticoagulation therapy, major practice guideline provides vitamin K antagonist (VKA) oral anticoagulant and non-VKA oral anticoagulants as treatment options. The risk of AF increases with age and despite treatment on standard of care anticoagulation therapy, recrudescent cardioembolic events may still arise especially in the elderly as we will see in this case.