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EN
Accurate early prediction of heart failure and identification of heart failure sub-phenotypes can enable in-time interventions and treatments, assist with policy decisions, and lead to a better understanding of disease pathophysiology in groups of patients. However, decision making more challenging for clinicians since the available data is complex, heterogeneous, temporal, and different in granularity. Even with much data, it is difficult for a cardiologist to pre-judge a patient’s heart condition at the next visit by relying on data from only one visit. Moreover, complicated and overloaded information bewilders clinicians, bringing obstacles to the stratification of patients and the mining of disease typical patterns in subgroups. To overcome these issues, this study proposes a novel Patient Representation model based on a temporal Bidirectional neural network with an Attention mechanism deep learning model called tBNA-PR. tBNA-PR effectively models heterogeneous and temporal Electronic Health Records (tEHRs) data from past and future directions to obtain informative patient representation to realize accurate heart failure prediction and reasonable patient stratification. Additionally, this study extracts typical diagnosis and prescriptions for disease patterns exploration and identifies significant features of sub-phenotypes for subgroup explanation in the context of complex clinical settings to provide better quality healthcare services and clinical decision support. This study leverages a real-world dataset MIMIC-III database. We carried out experiments on the prediction of heart failure to investigate tBNA-PR, which obtains prediction accuracy of 0.78, F1-Score of 0.7671, and AUC of 0.7198, showing a certain superiority compared with several state-of-the-art benchmarks. Moreover, we identified three distinct sub-phenotypes in all heart failure patients in the dataset with the clustering method and subgroup analysis. Sub-phenotype I has characteristics of more long-term anticoagulants. This sub-group has more patients who have the thrombotic disease. Sub-phenotype II has features of more patients having kidney disease, pneumonia, urinary tract infection, and coronary heart disease surgery history. Subphenotype III has characteristics of more patients having acidosis, depressive disorder, esophageal reflux, obstructive sleep apnea, and acquired hypothyroidism. Statistical tests show that the features, including age, creatinine, hemoglobin, urea nitrogen, and blood potassium, are significantly different among the three sub-phenotypes and have particular high importance. The resultant findings from this work have practical implications for clinical decision support.
EN
Cardiac Resynchronization Therapy Defibrillator (CRT-D) is a method to improve heart rate variability and arrhythmia-related symptoms in heart failure patients. According to clinical reports, CRT is not entirely safe and risk-free like other surgery. It can reduce heart failure risks, shorten hospital stays, and enhance the patients’ quality of life. The present study aims to perform the proper selection of patients before surgery to avoid potential costs. This article focuses on the data collection of heart failure patients’ activities, the process of features effective extraction, and identifying an optimal pattern using a Deep Learning (DL) algorithm. Also, the main tasks of the proposed methods include the use of qualitative indicators for initial feature extraction, oversampling from minority class, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) hierarchical clustering, selecting features from Low error clusters, selecting samples from high error clusters, and classification using customized DL configuration. The research data collection consisted of 209 patients with 60 demographic, clinical, laboratory, ECG, and echo features. In addition, features were analyzed based on their significance in predicting CRT response status. The DL algorithm, which used dense layers and convolution for its architecture, was employed to heart failure patients optimally identify the treatment status. The proposed method predicted the response to cardiac resynchronization therapy with an error rate of 91.85% and an Area Under Curve (AUC) of 0.957 and a sensitivity of 94.22%.
3
Content available remote Mechaniczne wspomaganie rzutu serca. Przegląd metod i urządzeń
PL
Niewydolność serca dotyka około 700 000 osób w Polsce, a na świecie około 2-3% populacji i jest obecnie jednym z największych wyzwań kardiologii. Najczęściej jest chorobą przewlekle postępującą. W zaawansowanych przypadkach, gdy leczenie farmakologiczne okazuje się nieskuteczne, istnieje potrzeba zastosowania urządzeń, które odciążają pracę serca i wspomagają jego rzut. W bardzo zaawansowanych przypadkach należy rozważyć przeszczep serca, lecz jest to metoda ograniczona dostępnością dawców, przez co jedynie niewielka część pacjentów ma wykonywany ten zabieg. Obecnie dostępne urządzenia są w stanie wspomagać lub częściowo zastąpić pracę serca. W zależności od wskazań i potrzeb urządzenia te mogą być stosowane: krótkotrwale w związku z zabiegami rewaskularyzacyjnymi tętnic wieńcowych, jako leczenie pomostowe do chwili przeszczepu serca oraz jako terapia zastępcza wobec przeszczepu. Urządzenia te możemy podzielić na: krótkoterminowe urządzenia zakładane do układu naczyniowego – kontrapulsacja wewnątrzaortalna, systemy Impella i Tandem Heart, systemy pozaustrojowego wspomagania krążenia – ECMO, wszczepialne urządzenia wspomagające pracę lewej komory lub obu komór serca oraz sztuczne serce TAH (Total Artificial Heart). Wśród wskazań do stosowania mechanicznego wspomagania rzutu serca można wymienić krańcową niewydolność serca, wstrząs kardiogenny, mechaniczne powikłania zawału, pooperacyjny zespół małego rzutu lub niewydolność przeszczepionego serca. Wybierając metodę, należy uwzględnić istotne przeciwwskazania, do których w zależności od wybranego urządzenia, możemy zaliczyć: wady zastawki aortalnej (zarówno zwężenie, jak i niedomykalność), obecność mechanicznej zastawki aortalnej, rozwarstwiający tętniak aorty, choroby naczyń uniemożliwiające dostęp naczyniowy. W ostatnich latach rozwijanych jest wiele urządzeń, które mają za zadanie wspomagać pracę serca, choć obecnie ich dostępność ograniczają wysokie koszty, w przyszłości urządzenia te staną się bardziej dostępne.
EN
Heart failure affects 700 000 people in Poland and about 2-3% of the population all over the world and currently is one of the most challenging problems in cardiology. In most cases heart failure is chronic and progressive disease. In severe cases, when pharmacological treatment is not sufficient, ventricular assist devices (VAD) - electromechanical devices for assisting cardiac circulation should be considered. In cases of advanced congestive heart failure heart transplantation can be considered, although this method is restricted by the number of donors therefore only small percentage of patient can undergo the surgery. Currently available devices are able to assist or partially substitute heart function. Depending on indications and needs these devices can be used: in the short-term in coronary artery revascularization procedures, as a bridge to heart transplantation and sometimes as a destination therapy instead of transplantation. Ventricular assist devices can be divided into: intra-aortic balloon pumps, Impella and Tandem Heart systems, Extracorporeal membrane oxygenation (ECMO), left ventricular assist device (LVAD) or total artificial heart (TAH). Indication for ventricular assist devices are advanced congestive heart failure, cardiogenic shock, recovering from myocardial infarction or cardiac surgery, postoperative low cardiac output syndrome, insufficiency of transplanted heart. Before deciding on use of VAD contraindications specific for each of those devices should be taken into consideration including aortic regurgitation, aortic valve stenosis, presence of artificial aortic valve, vascular diseases limiting vascular access. In recent years number of ventricular assist devices have been developed, although their use is currently limited by high costs, in the nearest future they will become more available.
EN
Objectives: Our goal is to develop a double lumen cannula (DLC) for a percutaneous right ventricular assist device (pRVAD) in order to eliminate two open chest surgeries for RVAD installation and removal. The objective of this study was to evaluate the performance, flow pattern, blood hemolysis, and thrombosis potential of the pRVAD DLC. Methods: Computational fluid dynamics (CFD), using the finite volume method, was performed on the pRVAD DLC. For Reynolds numbers <4000, the laminar model was used to describe the blood flow behavior, while shear-stress transport k-ω model was used for Reynolds numbers >4000. Bench testing with a 27 Fr prototype was performed to validate the CFD calculations. Results: There was <1.3% difference between the CFD and experimental pressure drop results. The Lagrangian approach revealed a low index of hemolysis (0.012% in drainage lumen and 0.0073% in infusion lumen) at 5 l/min flow rate. Blood stagnancy and recirculation regions were found in the CFD analysis, indicating a potential risk for thrombosis. Conclusions: The pRVAD DLC can handle up to 5 l/min flow with limited potential hemolysis. Further modification of the pRVAD DLC is needed to address blood stagnancy and recirculation.
EN
End stage heart failure patients could benefit from left ventricular assist device (LVAD) implantation as bridge to heart transplantation or as destination therapy. However, LVAD suffers from several limitations, including the presence of a battery as power supply, the need for cabled connection from inside to outside the patient, and the lack of autonomous adaptation to the patient metabolic demand during daily activity. The authors, in this wide scenario, aim to contribute to advancement of the LVAD therapy by developing the hardware and the firmware of a portable autoregulation unit (ARU), able to fulfill the needs of sensorized VAD in terms of physic/physiological data storing, continuous monitoring, wireless control from the external environment and automatic adaptation to patient activities trough the implementation of autoregulation algorithms. Moreover, in order to answer the rules and safety requirements for implantable biomedical devices, a user control interface (UCI), was developed and associated to the ARU for an external manual safe control. The ARU and UCI functionalities and autoregulation algorithms have been successfully tested on bench and on animal, with a response time of 1 s for activating autoregulation algorithms. Animal experiments showed as the presence of the ARU do not affect the animal cardiovascular system, giving a proof of concept of its applicability in vivo.
EN
Recently, the ventricular assist devices are widely applied for a surgical treatment of the final stage of severe heart failure as the bridge to heart transplantation or the destination therapy. However, it was anticipated that the artificial components in the ventricular assist devices might cause the problems concerning thrombosis and infection. As heart failure involves the decrease in myocardial contractile function, the mechanical assistance by using an artificial myocardium might be effective. In this study, the authors developed a mechano-electric artificial myocardial assist system (artificial myocardium), which is capable of supporting natural contractile function from the outside of the ventricle.
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