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OBJECTIVES: Enhanced recovery after surgery (ERAS) is a multidisciplinary, patient-centred approach aimed at expediting recovery, improving clinical outcomes, and reducing healthcare costs. Initially developed for colorectal surgery, ERAS principles have been successfully applied across various surgical specialties, including cardiac surgery. This study outlines the implementation and certification process of the ERAS program in a tertiary cardiac surgical centre within the Heart-Vessel Department at Lausanne University Hospital. METHODS: The implementation involved forming a multidisciplinary team, including cardiac surgeons, anaesthesiologists, intensivists, a cardiologist, clinical nurse specialists and physiotherapists. The ERAS nurse coordinator played a central role in organizing meetings, promoting the program, developing protocols, and collecting data. The certification process required adherence to ERAS guidelines, structured training and external evaluation. Key phases included pre-ERAS data collection, protocol dissemination, inclusion of the 1st patients, followed by analysis and full implementation. RESULTS: Achieving certification required maintaining a compliance rate of over 70% with established protocols. The process involved overcoming various barriers, such as inconsistent practices and the need for multidisciplinary collaboration. In this paper, we provide some solutions to these challenges, including team education, regular meetings and continuous feedback loops. Preliminary data from the initial cohort showed improvements in early mobilization, opioid use, respiratory complications and shorter hospital stays. CONCLUSIONS: The successful implementation of the ERAS program at our institution demonstrates the feasibility and benefits of a structured, multidisciplinary approach in cardiac surgery. Continuous self-assessment and adherence to guidelines are essential for sustained improvement in patient outcomes and healthcare efficiency.

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BACKGROUND: The sutureless Perceval S bioprosthesis is associated with postoperative thrombocytopenia. Our objectives were to compare the incidence, severity, and clinical implications of thrombocytopenia after aortic valve replacement (AVR) using the Perceval S or the Trifecta bioprosthesis. METHODS: Patients who underwent AVR between March 2016 and August 2019 using the Perceval or Trifecta were retrospectively included. The primary endpoint was the nadir in platelet counts within 15 days after surgery. Secondary endpoints included postoperative hemolysis and inflammatory parameters, as well as clinical and echocardiographic outcomes. RESULTS: Overall, 156 patients were included (Perceval, n = 103; Trifecta, n = 53). Preoperatively, there was no difference in platelet counts between the two groups. Postoperatively, the Perceval S bioprosthesis was associated with a greater decrease in platelet counts. The nadir was reached at Day 3 for both groups, but thrombocytopenia was more severe for the Perceval S (Perceval S vs. Trifecta, 89.2 ± 37.7 × 109/L vs. 106.5 ± 34.1 × 109/L, p = 0.01). No difference regarding lactate dehydrogenase, C-reactive protein, and white blood cells count was found. All-cause 30-day mortality rates (both valves, 2%, p = 0.98), hospital lengths of stay, and re-operation rates were similar. CONCLUSION: The Perceval S bioprosthesis was associated with more severe postoperative thrombocytopenia. This did not translate into higher short-term morbidity or mortality.

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Deploying unmanned aerial vehicles (UAVs) as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using traveling salesman problem with profits (TSPWP) instances executed on various training examples. This dictionary represents the world model and contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP's decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.

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OBJECTIVE: Surgical site infections (SSIs) are a major source of morbidity after cardiac surgery, involving prolonged hospitalisation. Among the numerous techniques of skin closure and dressings available, the optimal method remains undetermined. The DERMABOND-PRINEO (PRINEO) (PRINEO, Ethicon, J&J) is the only skin closure system which combines a topical skin adhesive with a mesh. Other surgical disciplines have highlighted remarkable results with PRINEO. The aim of this study was to evaluate the effects of PRINEO, used as the final layer in sternotomy closure, in the incidence of postoperative SSIs. METHOD: This was a retrospective single-centre cohort study including adult patients who underwent cardiac surgery between January 2015 and December 2018. Patients who had undergone heart transplantation or ventricular assist surgery were excluded. Included patients were divided into two groups depending on the type of post-operative wound care technique used. Group 1 consisted of patients who had their sternotomy closed with a standard dressing and group 2 consisted of patients who were treated with PRINEO. The primary endpoint of our study was the occurrence of SSIs and secondary outcomes were the length of hospitalisation and mortality. RESULTS: A total of 1603 patients were reviewed with the occurrence of 44 SSIs. Both groups were homogeneous in terms of risk factors. The incidence of SSIs was significantly lower in group 2 (PRINEO) than in group 1 (standard dressing) (n=29, 3.8% vs n=15, 1.8%, respectively; p=0.042). However, there was no significant difference in the duration of hospitalisation and mortality. CONCLUSION: In our practice, PRINEO has proven to be a safe wound closure system after sternotomy, with a reduced SSI rate compared to conventional wound care techniques.

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Few patients with coronavirus disease 2019-associated severe acute respiratory distress syndrome (ARDS) require veno-venous extracorporeal membrane oxygenation (VV-ECMO). Prolonged VV-ECMO support necessitates repeated oxygenator replacement, increasing the risk for complications. Transient hypoxemia, induced by VV-ECMO stop needed for this procedure, may induce transient myocardial ischemia and acutely declining cardiac output in critically ill patients without residual pulmonary function. This is amplified by additional activation of the sympathetic nervous system (tachycardia, pulmonary vasoconstriction, and increased systemic vascular resistance). Immediate reinjection of the priming solution of the new circuit and induced acute iatrogenic anemia are other potentially reinforcing factors. The case of a critically ill patient presented here provides an instructive illustration of the hemodynamic relationships occurring during VV-ECMO support membrane oxygenator exchange.

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Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Nevertheless, BESS are usually remotely controlled by SCADA systems, so they are prone to cyberattacks. This paper analyzes the vulnerabilities of BESS and proposes an anomaly detection algorithm that, by observing the physical behavior of the system, aims to promptly detect dangerous working conditions by exploiting the capabilities of a particular neural network architecture called the autoencoder. The results show the performance of the proposed approach with respect to the traditional One Class Support Vector Machine algorithm.

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Critical Infrastructures (CIs) are sensible targets. They could be physically damaged by natural or human actions, causing service disruptions, economic losses, and, in some extreme cases, harm to people. They, therefore, need a high level of protection against possible unintentional and intentional events. In this paper, we show a logical architecture that exploits information from both physical and cybersecurity systems to improve the overall security in a power plant scenario. We propose a Machine Learning (ML)-based anomaly detection approach to detect possible anomaly events by jointly correlating data related to both the physical and cyber domains. The performance evaluation showed encouraging results-obtained by different ML algorithms-which highlights how our proposed approach is able to detect possible abnormal situations that could not have been detected by using only information from either the physical or cyber domain.

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The way of generating and distributing energy throughout the electrical grid to all users is evolving. The concept of Smart Grid (SG) took place to enhance the management of the electrical grid infrastructure and its functionalities from the traditional system to an improved one. To measure the energy consumption of the users is one of these functionalities that, in some countries, has already evolved from a periodical manual consumption reading to a more frequent and automatic one, leading to the concept of Smart Metering (SM). Technology improvement could be applied to the SM systems to allow, on one hand, a more efficient way to collect the energy consumption data of each user, and, on the other hand, a better distribution of the available energy through the infrastructure. Widespread communication solutions based on existing telecommunication infrastructures instead of using ad-hoc ones can be exploited for this purpose. In this paper, we recall the basic elements and the evolution of the SM network architecture focusing on how it could further improve in the near future. We report the main technologies and protocols which can be exploited for the data exchange throughout the infrastructure and the pros and cons of each solution. Finally, we propose an innovative solution as a possible evolution of the SM system. This solution is based on a set of Internet of Things (IoT) communication technologies called Low Power Wide Area Network (LPWAN) which could be employed to improve the performance of the currently used technologies and provide additional functionalities. We also propose the employment of Unmanned Aerial Vehicles (UAVs) to periodically collect energy consumption data, with evident advantages especially if employed in rural and remote areas. We show some preliminary performance results which allow assessing the feasibility of the proposed approach.

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BACKGROUND: Transcatheter aortic valve implantation (TAVI) is the procedure of choice for aortic stenosis in high surgical risk patients, but it is no free from complications. CASE SUMMARY: A 86-year-old patient with severe aortic stenosis underwent TAVI 3 years ago with an Edwards Sapiens valve by femoral access. In the echocardiography follow-up, an aorta-right ventricular (Ao-RV) fistula was noted with restrictive flow and no significant shunt and it was treated conservatively. Three years after TAVI, the patient underwent cardiac surgery because of worsening heart failure due to a severe degenerative mitral regurgitation with tethering of P2 due to left ventricular remodelling, a posterior jet of severe regurgitation, and left ventricular dilatation. Surgical replacement of the TAVI and aortic root with a bioprosthesis (Medtronic Freestyle) and direct closure of the fistula was performed along with the mitral valve replacement. The patient was discharged with a good clinical result and no evidence of remaining Ao-RV fistula at transthoracic echocardiography. DISCUSSION: Aorta-right ventricular fistula is a rare entity. Most reported cases arise after rupture of a congenital coronary sinus aneurism, endocarditis, trauma, and aortic valve or aortic root surgery. This is the 10th reported case after TAVI (9 after an Edwards Sapiens TAVI). Non-significant shunt can be treated conservatively but development of heart failure and death are described in significant shunts. Balloon post-dilatation and the absence of surgical calcium debridement inherent to TAVI may theoretically contribute to the development of the fistula. Surgical replacement and closure of the fistula is a therapeutic option for this entity even in high-risk patients.

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AIMS: Mechanical alterations in patients with electrical conduction abnormalities are reported to have prognostic value in patients with left ventricular asynchrony or long QT syndrome beyond electrocardiogram (ECG) variables. Whether conduction and repolarization patterns derived from ECG are associated with speckle tracking echocardiography parameters in subjects without overt cardiac disease is yet to be investigated. To report ranges of longitudinal deformation according to conduction and repolarization values in a population-based cohort. METHODS AND RESULTS: One thousand, one hundred, and forty subjects (48.6 ± 14.0 years, 47.7% men) enrolled in the fourth visit of the STANISLAS cohort (Lorraine, France) were studied. Echocardiography strain was performed in all subjects. RR, PR, QRS, and QT intervals were retrieved from digitalized 12-lead ECG. Echocardiographic data were stratified according to quartiles of QRS and QTc duration values. Full-wall global longitudinal strain (GLS) was -21.1 ± 2.5% with a mechanical dispersion (MD) value of 34 ± 12 ms. Absolute GLS value was lower in the longest QRS quartile and shortest QTc quartile (both P < 0.001). Time-to-peak of strain was not significantly different according to QRS duration although significantly higher in patients with higher QTc (P < 0.001). MD was significantly greater in patients with longer QTc (32 ± 12 ms for QTc < 396 ms vs. 36 ± 12 ms for QTc > 421 ms; P = 0.002). CONCLUSION: Longer QTc is related to increased MD and better longitudinal strain values. In a population-based setting, QRS is not associated with MD, suggesting that echocardiography-based dyssynchrony does not largely overlap with ECG-based dyssynchrony.

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The Fifth Generation of Mobile Communications (5G) will lead to the growth of use cases demanding higher capacity and a enhanced data rate, a lower latency, and a more flexible and scalable network able to offer better user Quality of Experience (QoE). The Internet of Things (IoT) is one of these use cases. It has been spreading in the recent past few years, and it covers a wider range of possible application scenarios, such as smart city, smart factory, and smart agriculture, among many others. However, the limitations of the terrestrial network hinder the deployment of IoT devices and services. Besides, the existence of a plethora of different solutions (short vs. long range, commercialized vs. standardized, etc.), each of them based on different communication protocols and, in some cases, on different access infrastructures, makes the integration among them and with the upcoming 5G infrastructure more difficult. This paper discusses the huge set of IoT solutions available or still under standardization that will need to be integrated in the 5G framework. UAVs and satellites will be proposed as possible solutions to ease this integration, overcoming the limitations of the terrestrial infrastructure, such as the limited covered areas and the densification of the number of IoT devices per square kilometer.

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Background: Currently there is no medical treatment for X-linked retinoschisis (XLRS). In many retinal dystrophies, carbonic anhydrase inhibitors (CAIs) are effectively used to reduce cystoid macular edema. Prospective studies investigating the effect of CAIs in patients with XLRS are needed for the evaluation of their efficacy in this disease. The purpose of our work is to investigate the effects on macular morphology and function of oral CAIs used for the treatment of foveal lesions in patients with XLRS. Methods: Nineteen patients with a clinical diagnosis of XLRS were enrolled and prescribed oral CAIs for six months. We evaluated the therapeutic effect of CAIs with: best-corrected visual acuity (BCVA), spectral-domain optical coherence tomography, microperimetry (MP) and multifocal electroretinography (mfERG). Results: We observed a significant improvement of BCVA (p-value = 0.013), central retinal thickness (p-value = 0.004) and macular sensitivity (p-value<0.001). Moreover, in regards to mfERG responses, an increase of P1 wave amplitude was observed in three of the six rings. Conclusions: Our data supports the efficacy of oral CAIs for the treatment of macular cyst-like lesions in XLRS patients. The recovery of a normal retinal anatomy by means of oral CAIs could be useful to create the optimal circumstances for gene therapy. The increase in macular sensitivity and in P1 wave amplitude confirmed that MP and mfERG provide with an unbiased and more sensitive understanding of how macular function may respond to the use of CAIs. Therefore, we recommend the use of MP and mfERG to assess the effect of therapy in XLRS.

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Wireless Sensor Networks (WSNs), where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, "real-time" coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure), under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s) and decoder(s) possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions) and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors' own research, and some highlights on the inter-play of the different theories.

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The recently advanced hypothesis that idiopathic intracranial hypertension without papilledema (IIHWOP) is a powerful risk factor for the progression of pain in individuals prone to episodic primary headache implies that IIHWOP is much more prevalent than it is believed to be in the general population and that it can run almost asymptomatic in most of the affected individuals. In this review, we discuss the evidence available supporting that: (a) sinus venous stenosis-associated IIHWOP is much more prevalent than believed in the general population and can run without symptoms or signs of raised intracranial pressure in most of individuals affected, (b) sinus venous stenosis is a very sensitive and specific predictor of intermittent or continuous idiopathic intracranial hypertension with or without papilledema, even in asymptomatic individuals, (c) in primary headache prone individuals, a comorbidity with a hidden stenosis-associated IIHWOP represents a very common, although largely underestimated, modifiable risk factor for the progression and refractoriness of headache.

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Data from two recent studies strongly support the hypothesis that idiopathic intracranial hypertension without papilledema (IIHWOP) could represent a powerful risk factor for the progression of pain in primary headache individuals. The first study highlights that an asymptomatic IIHWOP is much more prevalent than believed in the general population and occurs only in central venous stenosis carriers. In the second study, about one half of a large consecutive series of unresponsive primary chronic headache patients shows significant sinus venous stenosis. A continuous or intermittent IIHWOP was detectable in 91% of this subgroup and in no patient with normal venography. Moreover, after the lumbar puncture, a 2- to 4-week improvement in headache frequency was observed in most of the intracranial hypertensive patients. These findings strongly suggest that patients prone to primary headache who carry central venous outflow abnormalities are at high risk of developing a comorbid IIHWOP, which in turn is responsible for the progression and the unresponsiveness of the pain. Based on the available literature data, we propose that central sinus stenosis-related IIHWOP, although highly prevalent among otherwise healthy people, represents an important modifiable risk factor for the progression and refractoriness of pain in patients predisposed to primary headache. The mechanism could refer to up to one half of the primary chronic headache patients with minimal response to treatments referring to specialized headache clinics. Due to the clinical and taxonomic relevance of this hypothesis further studies are urgently needed.

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A resource allocation problem for a satellite network is considered, where variations of fading conditions are added to those of traffic load. Since the capacity of the system is finite and divided in finite discrete portions, the resource allocation problem reveals to be a discrete stochastic programming one, which is typically NP-Hard. In practice, a good approximation of the optimal solution could be obtained through the adoption of a closed-form expression of the performance measure in steady-state conditions. Once we have summarized the drawbacks of such optimization strategy, we address two novel optimization approaches. The first one derives from Gokbayrak and Cassandras and is based on the minimization over the discrete constraint set using an estimate of the gradient, obtained through a "relaxed continuous extension" of the performance measure. The computation of the gradient estimation is based on infinitesimal perturbation analysis (IPA). Neither closed forms of the performance measures, nor additional feedbacks concerning the state of the system and very mild assumptions about the stochastic environment are requested. The second one is the main contribution of the present work, and is based on an open-loop feedback control (OLFC) strategy, aimed at providing optimal reallocation strategies as functions of the state of the network. The optimization approach leads us to a functional optimization problem, and we investigate the adoption of a neural network-based technique, in order to approximate its solution. As is shown in the simulation results, we obtain near-optimal reallocation strategies with a small real time computational effort and avoid the suboptimal transient periods introduced by the IPA gradient descent algorithm.

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