Refined Multiscale Entropy Predicts Early Failure in Electrical Cardioversion of Atrial Fibrillation

[EN] Electrical cardioversion (ECV) is a well-established strategy for atrial fibrillation (AF) management. Despite its high initial effectiveness, a high relapsing rate is also found. Hence, identification of patients at high risk of early AF recurrence is crucial for a rationale therapeutic strategy. For that purpose, a set of indices characterizing fibrillatory (f-) waves have been proposed, but they have not considered nonlinear dynamics present at different timescales within the cardiovascular system. This work thus explores whether a multiscale entropy (MSE) analysis of the f-waves can improve preoperative predictions of ECV outcome. Thus, two MSE approaches were considered, i.e., traditional MSE and a refined version (RMSE). Both algorithms were applied to the main f-waves component extracted from lead V1 and entropy values were computed for the first 20 time-scales. As a reference, dominant frequency (DF) and f-wave amplitude (FWA) were also computed. A total of 70 patients were analyzed, and all parameters but FWA showed statistically significant differences between those relapsing to AF and maintaining sinus rhythm during a follow-up of 4 weeks. RMSE reported the best results for the scale 19, improving predictive ability up to an 8% with respect to DAF and FWA. Consequently, investigation of nonlinear dynamics at large time-scales can provide useful insights able to improve predictions of ECV failureThis research was funded by the projects DPI2017-83952-C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501/000411 from "Junta de Castilla La Mancha" and AICO/2019/036 from "Generalitat Valenciana".Cirugeda, EM.; Calero, S.; Hidalgo, VM.; Enero, J.; Rieta, JJ.; Alcaraz, R. (2020). Refined Multiscale Entropy Predicts Early Failure in Electrical Cardioversion of Atrial Fibrillation. IEEE. 1-4. https://doi.org/10.22489/CinC.2020.369S1

Multidimensional Characterization of the Atrial Activity to Predict Electrical Cardioversion Outcome of Persistent Atrial Fibrillation

[EN] European Society of Cardiology guidelines recommend electrical cardioversion (ECV) as a rhythm control strategy in persistent atrial fibrillation (AF). Although ECV initially restores sinus rhythm (SR) in almost every patient, mid- and long-term AF recurrence rates are high, so that additional research is needed to anticipate ECV outcome and rationalize the management of AF patients. Although indices characterizing fibrillatory (f -) waves from surface lead V1, such as dominant frequency (DF), amplitude (FWA), and entropy, have reported good results, they discard the spatial information from the remaining leads. Hence, this work explores whether a multidimensional characterization approach of these parameters can improve ECV outcome prediction. The obtained results have shown that multidimensional FWA reported more balanced values of sensitivity and specificity, although the discriminant ability was similar in both cases. For DF, a similar outcome was also obtained. In contrast, multivariate entropy overcome discriminant ability of its univariate version by 5%, rightly anticipating result in more than 80% of ECV cases. Therefore, multidimensional entropy analysis seems to be able to quantify novel dynamics in the f-waves, which lead to a better ECV outcome predictionThis research was funded by the projects DPI2017-83952C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501/000411 from "Junta de Castilla La Mancha" and AICO/2019/036 from "Generalitat Valenciana"Cirugeda, EM.; Calero, S.; Plancha, E.; Enero, J.; Rieta, JJ.; Alcaraz, R. (2020). Multidimensional Characterization of the Atrial Activity to Predict Electrical Cardioversion Outcome of Persistent Atrial Fibrillation. IEEE. 1-4. https://doi.org/10.22489/CinC.2020.377S1

Adherence to the neonatal resuscitation algorithm for preterm infants in a tertiary hospital in Spain.

BACKGROUND: There is evidence that delivery room resuscitation of very preterm infants often deviates from internationally recommended guidelines. There were no published data in Spain regarding the quality of neonatal resuscitation. Therefore, we decided to evaluate resuscitation team adherence to neonatal resuscitation guidelines after birth in very preterm infants. METHODS: We conducted an observational study. We video recorded resuscitations of preterm infants < 32 weeks' gestational age and evaluated every step during resuscitation according to a score-sheet specifically designed for this purpose, following Carbine's method, where higher scores indicated that more intense resuscitation maneuvers were required. We divided the score achieved by the total possible points per patient to obtain the percentage of adherence to the algorithm. We also compared resuscitations performed by staff neonatologists to those performed by pediatricians on-call. We compared percentages of adherence to the algorithm with the Chi-square test for large groups and Fisher's exact test for smaller groups. We compared assigned Apgar scores with those given after analyzing the recordings and described them by their median and interquartile range. We measured the interrater agreement between Apgar scores with Cohen's kappa coefficient. Linear and logarithmic regressions were drawn to characterize the pattern of algorithm adherence. Statistical analysis was performed using SPSS V.20. A p-value < 0.05 was considered significant. Our Hospital Ethics Committee approved this project, and we obtained parental written consent beforehand. RESULTS: Sixteen percent of our resuscitations followed the algorithm. The number of mistakes per resuscitation was low. Global adherence to the algorithm was 80.9%. Ventilation and surfactant administration were performed best, whereas preparation and initial steps were done with worse adherence to the algorithm. Intubation required, on average, 2.2 attempts; success on the first attempt happened in 33.3% of cases. Only 12.5% of intubations were achieved within the allotted 30 s. Many errors were attributable to timing. Resuscitations led by pediatricians on-call were performed as correctly as those by staff neonatologists. CONCLUSIONS: Resuscitation often deviates from the internationally recognized algorithm. Perfectly performed resuscitations are infrequent, although global adherence to the algorithm is high. Neonatologists and pediatricians need intubation training

Further evidence of interaction between vasodilator β\u3csub\u3e2\u3c/sub\u3e- and vasoconstrictor α\u3csub\u3e2\u3c/sub\u3e-adrenoceptor-mediated responses in maintaining vascular tone in anesthetized rats

The importance of the interaction of α- and β-adrenoceptors in maintaining vascular tone in rats was studied. This interaction after clenbuterol (CLEN) treatment indicates an important contribution of the circulating epinephrine (EPI) levels. In urethane-anesthetized rats, the β2-adrenoceptor antagonist (CI 118.551 was more effective in antagonizing isoproterenol-induced hypotension (mainly β2-mediated) than tachycardia (mainly β1-mediated). Intravenous (i.v.) administration of the α2-adrenoceptor agonist clonidine (CLO) induced an initial pressor response followed by a more prolonged hypotension and bradycardia. The initial hypertensive effect was potentiated by previous acute administration of ICI 118.551 as well as by the nonselective β-adrenoceptor antagonist propranolol, but not by metoprolol, a more selective β1-blocker. Fourteen days of administration of the β2-adrenoceptor agonist CLEN [0.3 mg/kg, subcutaneously (s.c.) twice daily], a treatment that induces desensitization of β2-mediated vasodilation, increased the pressor response induced by CLO, an effect that was not observed in pentobarbital-anesthetized rats. In any case, neither β-blockers nor CLEN treatment affects the hypotension and bradycardia induced by CLO. Mean blood pressure (BP) of CLEN-treated rats was increased under urethane anesthesia but not under pentobarbital anesthesia. Catecholamine levels (principally EPI) were higher in urethane-anesthetized rats. These results provide further evidence of a functional interaction between α2- and β2-adrenoceptor-mediated responses in rat vasculature and suggest that vasodilator β2-adrenoceptors might contribute to the determination of peripheral vascular tone when circulating EPI is substantially elevated

Pressor response induced by clenbuterol treatment in immobilized normotensive rats

Short-term treatment with clenbuterol [0.6 mg/kg-1 subcutaneously (s.c.) daily] produces a pressor effect in stressed rats after a period of immobilization (40 min). The stress applied markedly increases the plasma concentrations of norepinephrine (NE) and epinephrine. After bilateral adrenal demedullation, the increased levels of catecholamines and the hypertensive response obtained after clenbuterol treatment in the stressed animals were reduced to the values of the control rats. Clenbuterol treatment produced desensitization of the β2-adrenoceptor-mediated effect and thus reduced the vasodilator response induced by isoproterenol and increased the vasoconstriction produced by epinephrine but not that caused by NE. This desensitization may be responsible for the hypertensive response after clenbuterol treatment in stressed animals which is attenuated after adrenal demedullation. In conclusion, our results provide evidence that clenbuterol treatment induces pressor effect in normotensive animals under stress

The optimization of thermoelectric generator array for harnessing electrical power from air conditioning unit

We live in a world where innovations and development are in process and a significant amount of energy is in demand with the consumption of energy, it is also wasted and should be kept minimized by any means. Wasted energy such as heat is found to be a good source of alternative energy. Heat is abundant and oftentimes generated by electrical equipment. The energy harnessed can be stored and utilized using proper power management, thus minimizing waste and conserving energy. The project not only aims on the utilization of harnessed energy for power but also to establish a system that will not depend mainly on electrical energy provided by an electrical source but rather use electrical energy converted from wasted heat energy and save electrical cost. TEG or Thermoelectric is a unique type of transducer that is capable of converting any heat source directly into electrical energy by using the concept of Seebeck Effect. The configuration created for harnessing the waste heat from the air conditioning unit focuses on utilizing the Seebeck Effect by means of installing a cooling system to the cold side of the TEG array, and a copper plate on the hot side of the TEG array to spread the heat evenly on the hot side of the TEG array to attain the highest voltage possible. The electrical output attained will be fed to a DC-DC boost converter boost the voltage to power up certain devices or charge a battery

Vision System for Hand Gesture Recognition (VISOR)

Vision system for Hand Gesture Recognition (VISOR) is a software application that recognizes a set of dynamic continuous gestures (using only a single hand) from a predefined vocabulary using computer vision algorithms. The system is user-independent and able to contend with different backgrounds and does not require the user to wear a long-sleeved garment (a limitation commonly found in similar systems). A standard USB web camera, placed near the workstation that contains the application, is used to capture gesture sequences. In every frame captured, the hand is detected and afterwards tracked. The hand is detected using a combination of skin-color segmentation and shape analysis based on the concept of convexity defects and several heuristics regarding the human hand shape, established empirically. Upon the hand detection, the user is given a time limit, in which the gesture sequence must be performed. The gesture is recognized by means of extracting temporal and structural information such as motion, hand shape and orientation from the image sequence. In order to recognize the sequence as one of the valid gestures, scoreboarding with respect to the features mentioned is applied after feature extraction. The system\u27s performance is evaluated in an indoor environment. The prototype was able to detect a user\u27s bare hand and track it throughout the duration of gesture performance. A hand detection rate of 77.65% was achieved with 6.47% false positives, during testing. The system was able to recognize gestures with a success rate of 70% for the old approach and 80% for the new approach, while being able to operate in real-time

Prediction of Early Failure in Electrical Cardioversion of Atrial Fibrillation Using Refined Multiscale Entropy

[EN] In the management of atrial fibrillation (AF), electrical cardioversion (ECV) is a common treatment. Although its initial success rate is high, many patients present AF recurrence after some weeks or months. Hence, being able to identify patients at low chance of mid-term sinus rhythm maintenance is important for a rationale therapeutic strategy. To this end, several parameters assessing fibrillatory (f-) waves have been introduced, however, with limited predictive ability. Moreover, the cardiovascular system exhibits nonlinear dynamics at different time-scales that these indices do not account for. Hence, the present work evaluates the ability of the multiscale entropy (MSE) analysis of the f-waves to improve preoperative forecasts of ECV outcome. Both traditional MSE and a refined version (RMSE) were applied to the main f waves component obtained for standard lead V1. As a reference, previously proposed predictors were also computed. Results revealed that RMSE was able to anticipate AF recurrence after 1 month of ECV with an accuracy around 78%. Moreover, a Naive Bayes model combining previous parameters and RMSE indices reported a discriminant ability 10% higher than single metrics. It could then be concluded that analysis of nonlinear dynamics at large time-scales can enhance ECV outcome predictions.This research was funded by projects: DPI2017-83952-C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501000411 from Junta de Castilla la Mancha and AICO/2019/036 from Generalitat Valenciana.Cirugeda, EM.; Calero, S.; Hidalgo, VM.; Enero, J.; Rieta, JJ.; Alcaraz, R. (2020). Prediction of Early Failure in Electrical Cardioversion of Atrial Fibrillation Using Refined Multiscale Entropy. IEEE. 1-4. https://doi.org/10.1109/EHB50910.2020.9280294S1