1. Characterization of Complex Fractionated Atrial Electrograms by Sample
Entropy: An International Multi–Center Study
Atrial fibrillation (AF) is the most commonly clinically-encountered arrhythmia.
Catheter ablation of AF is mainly based on trigger elimination and modification
of the AF substrate. Substrate mapping ablation of complex fractionated atrial
electrograms (CFAEs) has emerged to be a promising technique. To improve
substrate mapping based on CFAE analysis, automatic detection algorithms need to
be developed in order to simplify and accelerate the ablation procedures.
According to the latest studies, the level of fractionation has been shown to be
promisingly well estimated from CFAE measured during radio frequency (RF)
ablation of AF. The nature of CFAE is generally nonlinear and nonstationary, so
the use of complexity measures is considered to be the appropriate technique for
the analysis of AF records. This work proposes the use of sample entropy
(SampEn), not only as a way to discern between non-fractionated and fractionated
atrial electrograms (A-EGM), but also as a tool for characterizing the degree of
A-EGM regularity, which is linked to changes in the AF substrate and to heart
2. Metabolomic profiling of urinary changes in mice with monosodium
Obesity with related complications represents a widespread health problem. The
etiopathogenesis of obesity is often studied using numerous rodent models. The
mouse model of monosodium glutamate (MSG)-induced obesity was exploited as a
model of obesity combined with insulin resistance. The aim of this work was to
characterize the metabolic status of MSG mice by NMR-based metabolomics in
combination with relevant biochemical and hormonal parameters. NMR analysis of
urine at 2, 6, and 9 months revealed altered metabolism of nicotinamide and
polyamines, attenuated excretion of major urinary proteins, increased levels of
phenylacetylglycine and allantoin, and decreased concentrations of methylamine
in urine of MSG-treated mice. Altered levels of creatine, citrate, succinate,
and acetate were observed at 2 months of age and approached the values of
control mice with aging. The development of obesity and insulin resistance in
6-month-old MSG mice was also accompanied by decreased mRNA expressions of
adiponectin, lipogenetic and lipolytic enzymes and peroxisome
proliferator-activated receptor-gamma in fat while mRNA expressions of
lipogenetic enzymes in the liver were enhanced. At the age of 9 months,
biochemical parameters of MSG mice were normalized to the values of the
controls. This fact pointed to a limited predictive value of biochemical data up
to age of 6 months as NMR metabolomics confirmed altered urine metabolic
composition even at 9 months.
3. Discrimination of Complex Fractionated Atrial Electrograms Using Multifractal
Complex fractionated atrial electrograms provide an important tool for
identifying arrhythmogenic substrates that can be used to guide catheter
ablation for atrial fibrillation (AF). However, fractionation is a phenomenon
that remains unclear. This paper aims to evaluate the multifractal properties of
electrograms in AF in order to propose a method based on multifractal analysis
able to discriminate between different levels of fractionation. We introduce a
new method, the h-fluctuation index (hFI), where h is the generalised Hurst
exponent, to extract information from the shape of the multifractal spectrum.
Two multifractal frameworks are evaluated: multifractal detrended fluctuation
analysis and wavelet transform modulus maxima. hFI is exemplified through its
application in synthetic signals, and it is evaluated in a database of
electrograms labeled on the basis of four degrees of fractionation. We compare
the performance of hFI with other indexes, and find that hFI outperforms them.
The results of the study provide evidence that multifractal analysis is useful
for studying fractionation phenomena in AF electrograms, and indicate that hFI
can be proposed as a tool for grade fractionation associated with the detection
of target sites for ablation in AF.
4. Strategy for NMR metabolomic analysis of urine in obesity mouse models –
from sample collection to interpretation of acquired data
The mouse model of monosodium glutamate induced obesity was used to examine and
consequently optimize the strategy for analysis of urine samples by NMR
spectroscopy. A set of nineteen easily detectable metabolites typical in
obesity-related studies was selected. The impact of urine collection protocol,
choice of (1)H NMR pulse sequence, and finally the impact of the normalization
method on the detected concentration of selected metabolites were investigated.
We demonstrated the crucial effect of food intake and diurnal rhythms resulting
in the choice of a 24-hour fasting collection protocol as the most convenient
for tracking obesity-induced increased sensitivity to fasting. It was shown that
the Carr-Purcell-Meiboom-Gill (CPMG) experiment is a better alternative to
one-dimensional nuclear Overhauser enhancement spectroscopy (1D-NOESY) for NMR
analysis of mouse urine due to its ability to filter undesirable signals of
proteins naturally present in rodent urine. Normalization to total spectral area
provided comparable outcomes as did normalization to creatinine or probabilistic
quotient normalization in the CPMG-based model. The optimized approach was found
to be beneficial mainly for low abundant metabolites rarely monitored due to
their overlap by strong protein signals.
5. Perioperative tight glucose control reduces postoperative adverse events in
non-diabetic cardiac surgery patients
Context: Tight glucose control (TGC) reduces morbidity and mortality in patients
undergoing elective cardiac surgery, but only limited data about its optimal
timing are available to date.
Objective: The purpose of this article was to compare the effects of
perioperative vs postoperative initiation of TGC on postoperative adverse events
in cardiac surgery patients.
Design: This was a single center, single-blind, parallel-group, randomized
Settings: The setting was an academic tertiary hospital.
Participants: Participants were 2383 hemodynamically stable patients undergoing
major cardiac surgery with expected postoperative intensive care unit treatment
for at least 2 consecutive days.
Intervention: Intensive insulin therapy was initiated perioperatively or
postoperatively with a target glucose range of 4.4 to 6.1 mmol/L.
Main Outcome Measures: Adverse events from any cause during postoperative
hospital stay were compared.
6. Dynamic approximate entropy electroanatomic maps detect rotors in a simulated
atrial fibrillation model
There is evidence that rotors could be drivers that maintain atrial
fibrillation. Complex fractionated atrial electrograms have been located in
rotor tip areas. However, the concept of electrogram fractionation, defined
using time intervals, is still controversial as a tool for locating target sites
for ablation. We hypothesize that the fractionation phenomenon is better
described using non-linear dynamic measures, such as approximate entropy, and
that this tool could be used for locating the rotor tip. The aim of this work
has been to determine the relationship between approximate entropy and
fractionated electrograms, and to develop a new tool for rotor mapping based on
fractionation levels. Two episodes of chronic atrial fibrillation were simulated
in a 3D human atrial model, in which rotors were observed. Dynamic approximate
entropy maps were calculated using unipolar electrogram signals generated over
the whole surface of the 3D atrial model. In addition, we optimized the
approximate entropy calculation using two real multi-center databases of
fractionated electrogram signals, labeled in 4 levels of fractionation. We found
that the values of approximate entropy and the levels of fractionation are
positively correlated. This allows the dynamic approximate entropy maps to
localize the tips from stable and meandering rotors. Furthermore, we assessed
the optimized approximate entropy using bipolar electrograms generated over a
vicinity enclosing a rotor, achieving rotor detection. Our results suggest that
high approximate entropy values are able to detect a high level of fractionation
and to locate rotor tips in simulated atrial fibrillation episodes. We suggest
that dynamic approximate entropy maps could become a tool for atrial
fibrillation rotor mapping.