Acute kidney injury (AKI), defined as a rise in serum creatinine of greater than 25% from baseline measured at 48 hours after renal insult, may follow iodinated contrast coronary angiography. Termed contrast-induced nephropathy, it can result in considerable morbidity and mortality. Measurement of serum creatinine as a functional biomarker of glomerular filtration rate is widely used for detection of AKI, but it lacks sensitivity for the early diagnosis of AKI (typically rising 24 hours after functional loss) and, as a solely functional marker of glomerular filtration rate, is unable to differentiate among the various causes of AKI. These intrinsic limitations to creatinine measurement and the recognition that improved clinical outcomes are linked to a more timely diagnosis of AKI, has led investigators to search for novel biomarkers of "early" kidney injury. Several studies have investigated the utility of renal injury biomarkers in a variety of clinical settings including angiography/percutaneous coronary intervention, coronary artery bypass graft surgery, sepsis in intensive care patients, and pediatric cardiac surgery. In this article, we discuss the use of iodinated contrast for coronary procedures and the risk factors for contrast-induced nephropathy, followed by a review the potential diagnostic utility of several novel biomarkers of early AKI in the clinical settings of coronary angiography/percutaneous coronary intervention. In particular, we discuss neutrophil gelatinase associated lipocalin in depth. If validated, such biomarkers would facilitate earlier AKI diagnosis and improve clinical outcomes.

No abstract

First-shock success was significantly higher, particularly in patients with a BMI >25 kg/m(2), when a non-escalating initial 200 J energy was selected. The overall success, duration of procedure and amount of sedation administered, however, did not differ significantly between the two protocols.

No abstract

Abnormal heart rhythms (arrhythmias) are a major cause of cardiovascular disease and death in Europe. Sudden cardiac death accounts for 50% of cardiac mortality in developed countries; ventricular tachycardia or ventricular fibrillation is the most common underlying arrhythmia. In the ambulatory population, atrial fibrillation is the most common arrhythmia and is associated with an increased risk of stroke and heart failure, particularly in an aging population. Early detection of arrhythmias allows appropriate intervention, reducing disability and death. However, in the early stages of disease arrhythmias may be transient, lasting only a few seconds, and are thus difficult to detect. This work addresses the problem of extracting the far-field heart electrogram signal from noise components, as recorded in bipolar leads along the left arm, using a data driven ECG (electrocardiogram) denoising algorithm based on ensemble empirical mode decomposition (EEMD) methods to enable continuous non-invasive monitoring of heart rhythm for long periods of time using a wrist or arm wearable device with advanced biopotential sensors. Performance assessment against a control denoising method of signal averaging (SA) was implemented in a pilot study with 34 clinical cases. EEMD was found to be a reliable, low latency, data-driven denoising technique with respect to the control SA method, achieving signal-to-noise ratio (SNR) enhancement to a standard closer to the SA control method, particularly on the upper arm-ECG bipolar leads. Furthermore, the SNR performance of the EEMD was improved when assisted with an FFT (fast Fourier transform ) thresholding algorithm (EEMD-fft).

This article presents the devising, development, prototyping and assessment of a wearable arm-ECG sensor system (WAMECG1) for long-term non-invasive heart rhythm monitoring, and functionalities for acquiring, storing, visualizing and transmitting high-quality far-field electrocardiographic signals. The system integrates the main building blocks present in a typical ECG monitoring device such as the skin surface electrodes, front-end amplifiers, analog and digital signal conditioning filters, flash memory and wireless communication capability. These are integrated into a comfortable, easy to wear, and ergonomically designed arm-band ECG sensor system which can acquire a bipolar ECG signal from the upper arm of the user over a period of 72 h. The small-amplitude bipolar arm-ECG signal is sensed by a reusable, long-lasting, Ag–AgCl based dry electrode pair, then digitized using a programmable sampling rate in the range of 125 to 500 Hz and transmitted via Wi-Fi. The prototype comparative performance assessment results showed a cross-correlation value of 99.7% and an error of less than 0.75% when compared to a reference high-resolution medical-grade ECG system. Also, the quality of the recorded far-field bipolar arm-ECG signal was validated in a pilot trial with volunteer subjects from within the research team, by wearing the prototype device while: (a) resting in a chair; and (b) doing minor physical activities. The R-peak detection average sensibilities were 99.66% and 94.64%, while the positive predictive values achieved 99.1% and 92.68%, respectively. Without using any additional algorithm for signal enhancement, the average signal-to-noise ratio (SNR) values were 21.71 and 18.25 for physical activity conditions (a) and (b) respectively. Therefore, the performance assessment results suggest that the wearable arm-band prototype device is a suitable, self-contained, unobtrusive platform for comfortable cardiac electrical activity and heart rhythm logging and monitoring.

Mehran risk score, 4 h serum L-FAPB and 6 h plasma NGAL performed best at early CI-AKI prediction. CI-AKI patients were four times more likely to develop MACE and had a trebling of mortality risk at 1 year.

A significant proportion (15%) of patients with a Riata lead had an insulation breach 4 years after implantation. High-resolution fluoroscopic imaging in at least two orthogonal views is required to identify this abnormality.