Cooperative scheduling and load balancing techniques in fog and edge computing

Fog and Edge Computing are two models that reached maturity in the last decade. Today, they are two solid concepts and plenty of literature tried to develop them. Also corroborated by the development of technologies, like for example 5G, they can now be considered de facto standards when building low and ultra-low latency applications, privacy-oriented solutions, industry 4.0 and smart city infrastructures. The common trait of Fog and Edge computing environments regards their inherent distributed and heterogeneous nature where the multiple (Fog or Edge) nodes are able to interact with each other with the essential purpose of pre-processing data gathered by the uncountable number of sensors to which they are connected to, even by running significant ML models and relying upon specific processors (TPU). However, nodes are often placed in a geographic domain, like a smart city, and the dynamic of the traffic during the day may cause some nodes to be overwhelmed by requests while others instead may become completely idle. To achieve the optimal usage of the system and also to guarantee the best possible QoS across all the users connected to the Fog or Edge nodes, the need to design load balancing and scheduling algorithms arises. In particular, a reasonable solution is to enable nodes to cooperate. This capability represents the main objective of this thesis, which is the design of fully distributed algorithms and solutions whose purpose is the one of balancing the load across all the nodes, also by following, if possible, QoS requirements in terms of latency or imposing constraints in terms of power consumption when the nodes are powered by green energy sources. Unfortunately, when a central orchestrator is missing, a crucial element which makes the design of such algorithms difficult is that nodes need to know the state of the others in order to make the best possible scheduling decision. However, it is not possible to retrieve the state without introducing further latency during the service of the request. Furthermore, the retrieved information about the state is always old, and as a consequence, the decision is always relying on imprecise data. In this thesis, the problem is circumvented in two main ways. The first one considers randomised algorithms which avoid probing all of the neighbour nodes in favour of at maximum two nodes picked at random. This is proven to bring an exponential improvement in performance with respect to the probe of a single node. The second approach, instead, considers Reinforcement Learning as a technique for inferring the state of the other nodes thanks to the reward received by the agents when requests are forwarded. Moreover, the thesis will also focus on the energy aspect of the Edge devices. In particular, will be analysed a scenario of Green Edge Computing, where devices are powered only by Photovoltaic Panels and a scenario of mobile offloading targeting ML image inference applications. Lastly, a final glance will be given at a series of infrastructural studies, which will give the foundations for implementing the proposed algorithms on real devices, in particular, Single Board Computers (SBCs). There will be presented a structural scheme of a testbed of Raspberry Pi boards, and a fully-fledged framework called ``P2PFaaS'' which allows the implementation of load balancing and scheduling algorithms based on the Function-as-a-Service (FaaS) paradigm

Smartphone-based colorimetric sensor application for measuring biochemical material concentration

In this paper, colorimetric analysis for biochemical samples has been realized, by developing an easy-to-use smartphone colorimetric sensing android application that can measure the molar concentration of the biochemical liquid analyte. The designed application can be used for on-site testing and measurement. We examined three different biochemical materials with the application after preparation with five different concentrations and testing in laboratory settings, namely glucose, triglycerides, and urea. Our results showed that for glucose triglycerides, and urea the absorbance and transmittance regression coefficient (R2) for the colorimetric sensing application were 0.9825, and 0.9899; 0.9405 and 0.9502; 0.9431 and 0.8597, respectively. While for the spectrophotometer measurement the (R2) values were 0.9973 @560 nm and 0.9793 @600 nm; 0.952 @620 nm and 0.9364 @410 nm; 0.9948 @570 nm and 0.9827 @530 nm, respectively. The novelty of our study lies in the accurate prediction of multiple biochemical materials concentrations in various lightning effects, reducing the measurement time in an easy-to-use portable environment without the need for internet access, also tackling various issues that arise in the traditional measurements like power consumption, heating, and calibration. The ability to convey multiple tasks, prediction of concentration, measurement of both absorbance and transmittance, with error estimation charts and (R2) values reporting within the colorimetric sensing application as far as our knowledge there has not been any application that can provide all the capabilities of our application

On real-time scheduling in Fog computing: A Reinforcement Learning algorithm with application to smart cities

Fog Computing is today a wide used paradigm that allows to distribute the computation in a geographic area. This not only makes possible to implement time-critical applications but opens the study to a series of solutions which permit to smartly organise the traffic among a set of Fog nodes, which constitute the core of the Fog Computing paradigm. A typical smart city setting is subject to a continuous change of traffic conditions, a node that was saturated can become almost completely unloaded and this creates the need of designing an algorithm which allows to meet the strict deadlines of the tasks but at the same time it can choose the best scheduling policy according to the current load situation that can vary at any time. In this paper, we use a Reinforcement Learning approach to design such an algorithm starting from the power-of-random choice paradigm, used as a baseline. By showing results from our delay-based simulator, we demonstrate how such distributed reinforcement learning approach is able to maximise the rate of the tasks executed within the deadline in a way that is equal to every node, both in a fixed load condition and in a real geographic scenario

Leveraging Reinforcement Learning for online scheduling of real-time tasks in the Edge/Fog-to-Cloud computing continuum

The computing continuum model is a widely ac-cepted and used approach that make possible the existence of applications that are very demanding in terms of low latency and high computing power. In this three-layered model, the Fog or Edge layer can be considered as the weak link in the chain, indeed the computing nodes whose compose it are generally heterogeneous and their uptime cannot be compared with the one offered by the Cloud. Taking into account these inexorable characteristics of the continuum, in this paper, we propose a Reinforcement Learning based scheduling algorithm that makes per-job request decisions (online scheduling) and that is able to maintain an acceptable performance specifically targeting real-time applications. Through a series of simulations and comparisons with other fixed scheduling strategies, we demonstrate how the algorithm is capable of deriving the best possible scheduling policy when Fog or Edge nodes have different speeds and can unpredictably fail

A study on real-time image processing applications with edge computing support for mobile devices

Different libraries allow performing computer vision tasks, e.g., object recognition, in almost every mobile device that has a computing capability. In modern smartphones, such tasks are compute-intensive, energy hungry computation running on the GPU or the particular Machine Learning (ML) processor embedded in the device. Task offloading is a strategy adopted to move compute-intensive tasks and hence their energy consumption to external computers, in the edge network or in the cloud. In this paper, we report an experimental study that measure under different mobile computer vision set-ups the energy reduction when the inference of an image processing is moved to an edge node, and the capability to still meet real-time requirements. In particular, our experiments show that offloading the task - in our case real-time object recognition - to a possible next-to-the-user node allows saving about the 70% of battery consumption while maintaining the same frame rate (fps) that local processing can achieve

Towards Testbed as-a-Service: design and implementation of an unattended SoC cluster

The current computing power of single-board computers (SBCs) is relevant, and if this factor is associated with the very low cost of installing and operating such devices, building a cluster is a natural consequence. Very often in fog computing, researchers need to run and test their distributed solutions and algorithms in real hardware and software, rather than by simulations and doing this in a cluster of SBCs is feasible and inexpensive. This paper addresses most of the problems and issues that arise when building a self-contained, remote controllable and unattended cluster of Raspberry Pi that minimizes the physical intervention of a human operator, which enables the notion of Testbed as-a-Service. The solution envisioned here is to set up the cluster in a desktop computer case, which needs addressing power management and to allow remote configuration of experiments. Moreover, the paper proposes several guidelines for installing a suitable operating system and software for running any kind of distributed application

Antithrombotic strategies in the catheterization laboratory for patients with acute coronary syndromes undergoing percutaneous coronary interventions: Insights from the EmploYEd antithrombotic therapies in patients with acute coronary Syndromes HOspitalized in Italian cardiac care units Registry

Aims: In the last decades, several new therapies have emerged for the treatment of acute coronary syndromes (ACS). We sought to describe real-world patterns of use of antithrombotic treatments in the catheterization laboratory for ACS patients undergoing percutaneous coronary interventions (PCI). Methods: EmploYEd antithrombotic therapies in patients with acute coronary Syndromes HOspitalized in Italian cardiac care units was a nationwide, prospective registry aimed to evaluate antithrombotic strategies employed in ACS patients in Italy. Results: Over a 3-week period, a total of 2585 consecutive ACS patients have been enrolled in 203 cardiac care units across Italy. Among these patients, 1755 underwent PCI (923 with ST-elevation myocardial infarction and 832 with non-ST-elevation ACS). In the catheterization laboratory, unfractioned heparin was the most used antithrombotic drug in both ST-elevation myocardial infarction (64.7%) and non-ST-elevation ACS (77.5%) undergoing PCI and, as aspirin, bivalirudin and glycoprotein IIb/IIIa inhibitors (GPIs) more frequently employed before or during PCI compared with the postprocedural period. Any crossover of heparin therapy occurred in 36.0% of cases, whereas switching from one P2Y12 inhibitor to another occurred in 3.7% of patients. Multivariable analysis yielded several independent predictors of GPIs and of bivalirudin use in the catheterization laboratory, mainly related to clinical presentation, PCI complexity and presence of complications during the procedure. Conclusion: In our contemporary, nationwide, all-comers cohort of ACS patients undergoing PCI, antithrombotic therapies were commonly initiated before the catheterization laboratory. In the periprocedural period, the most frequently employed drugs were unfractioned heparin, leading to a high rate of crossover, followed by GPIs and bivalirudin, mainly used during complex PCI

Hospital Care of Older Patients With COPD: Adherence to International Guidelines for Use of Inhaled Bronchodilators and Corticosteroids

313noObjectives: We aimed to analyze the prevalence and impact of COPD in older patients hospitalized in internal medicine or geriatric wards, and to investigate adherence to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines, associated clinical factors, and outcomes. Design: Data were obtained from REgistro POliterapie SIMI (REPOSI), a prospective multicenter observational registry that enrolls inpatients aged 65 years. Setting and Participants: Older hospitalized patients enrolled from 2008 to 2016 with a diagnosis of COPD. Measures: We evaluated adherence to the 2018 GOLD guidelines at admission and discharge, by examining the prescription of inhaled bronchodilators and corticosteroids in COPD patients. We also evaluated the occurrence of outcomes and its association with COPD and guideline adherence. Results: At hospital admission, COPD was diagnosed in 1302 (21.5%) of 6046 registered patients. COPD patients were older, with more impaired clinical and functional status and multiple comorbidities. Overall, 34.3% of COPD patients at admission and 35.6% at discharge were adherent to the GOLD guidelines. Polypharmacy (5 drugs) at admission [odds ratio (OR): 3.28, 95% confidence interval (CI): 2.24-4.81], a history of acute COPD exacerbation (OR: 2.65, 95% CI: 1.44-4.88) at admission, smoking habit (OR: 1.45, 95% CI: 1.08-1.94), and polypharmacy at discharge (OR: 6.76, 95% CI: 4.15-11.0) were associated with adherence to guidelines. COPD was independently associated with the risk of cardiovascular and respiratory death and rehospitalization occurrence compared to patients without COPD during follow-up. Adherence to guidelines was inversely associated with the occurrence of death from all causes (OR: 0.12, 95% CI: 0.02-0.90). Conclusions/Implications: COPD was common in older patients acutely hospitalized, showing an impaired functional and clinical status. Prescriptions for older COPD patients were often not adherent to GOLD guidelines. Poor adherence to guidelines was associated with a worse clinical status. There is a need to improve adherence to guidelines in treating COPD patients, with the ultimate goal of reducing clinical events.reservedmixedProietti, Marco; Agosti, Pasquale; Lonati, Chiara; Corrao, Salvatore; Perticone, Francesco; Mannucci, Pier Mannuccio; Nobili, Alessandro; Harari, Sergio; Tettamanti, Mauro; Pasina, Luca; Franchi, Carlotta; Marengoni, Alessandra; Salerno, Francesco; Cesari, Matteo; Licata, Giuseppe; Violi, Francesco; Corazza, Gino Roberto; Cortesi, Laura; Ardoino, Ilaria; Prisco, Domenico; Silvestri, Elena; Cenci, Caterina; Emmi, Giacomo; Biolo, Gianni; Zanetti, Michela; Guadagni, Martina; Zaccari, Michele; Vanoli, Massimo; Grignani, Giulia; Pulixi, Edoardo Alessandro; Bernardi, Mauro; Bassi, Silvia Li; Santi, Luca; Zaccherini, Giacomo; Mannarino, Elmo; Lupattelli, Graziana; Bianconi, Vanessa; Paciullo, Francesco; Nuti, Ranuccio; Valenti, Roberto; Ruvio, Martina; Cappelli, Silvia; Palazzuoli, Alberto; Olivieri, Oliviero; Girelli, Domenico; Matteazzi, Thomas; Barbagallo, Mario; Dominguez, Ligia; Cocita, Floriana; Beneduce, Vincenza; Plances, Lidia; Zoli, Marco; Lazzari, Ilaria; Brunori, Mattia; Pasini, Franco Laghi; Capecchi, Pier Leopoldo; Palasciano, Giuseppe; Modeo, Maria Ester; Di Gennaro, Carla; Cappellini, Maria Domenica; Maira, Diletta; Di Stefano, Valeria; Fabio, Giovanna; Seghezzi, Sonia; Mancarella, Marta; Rossi, Paolo Dionigi; Damanti, Sarah; Clerici, Marta; Conti, Federica; Miceli, Emanuela; Lenti, Marco Vincenzo; Pisati, Martina; Dominioni, Costanza Caccia; Murialdo, Giovanni; Marra, Alessio; Cattaneo, Federico; Pontremoli, Roberto; Secchi, Maria Beatrice; Ghelfi, Davide; Anastasio, Luigi; Sofia, Lucia; Carbone, Maria; Cipollone, Francesco; Guagnano, Maria Teresa; Angelucci, Ermanno; Valeriani, Emanuele; Mancuso, Gerardo; Calipari, Daniela; Bartone, Mosè; Delitala, Giuseppe; Berria, Maria; Muscaritoli, Maurizio; Molfino, Alessio; Petrillo, Enrico; Zuccalà, Giuseppe; D'Aurizio, Gabriella; Romanelli, Giuseppe; Zucchelli, Alberto; Picardi, Antonio; Gentilucci, Umberto Vespasiani; Gallo, Paolo; Dell'Unto, Chiara; Annoni, Giorgio; Corsi, Maurizio; Bellelli, Giuseppe; Zazzetta, Sara; Mazzola, Paolo; Szabo, Hajnalka; Bonfanti, Alessandra; Arturi, Franco; Succurro, Elena; Rubino, Mariangela; Serra, Maria Grazia; Bleve, Maria Antonietta; Gasbarrone, Laura; Sajeva, Maria Rosaria; Brucato, Antonio; Ghidoni, Silvia; Fabris, Fabrizio; Bertozzi, Irene; Bogoni, Giulia; Rabuini, Maria Victoria; Cosi, Elisabetta; Manfredini, Roberto; Fabbian, Fabio; Boari, Benedetta; De Giorgi, Alfredo; Tiseo, Ruana; Paolisso, Giuseppe; Rizzo, Maria Rosaria; Borghi, Claudio; Strocchi, Enrico; De Sando, Valeria; Pareo, Ilenia; Sabbà, Carlo; Vella, Francesco Saverio; Suppressa, Patrizia; Schilardi, Andrea; Loparco, Francesca; Fenoglio, Luigi; Bracco, Christian; Giraudo, Alessia Valentina; Fargion, Silvia; Periti, Giulia; Porzio, Marianna; Tiraboschi, Slivia; Peyvandi, Flora; Rossio, Raffaella; Ferrari, Barbara; Colombo, Giulia; Monzani, Valter; Savojardo, Valeria; Folli, Christian; Ceriani, Giuliana; Pallini, Giada; Dallegri, Franco; Ottonello, Luciano; Liberale, Luca; Caserza, Lara; Salam, Kassem; Liberato, Nicola Lucio; Tognin, Tiziana; Bianchi, Giovanni Battista; Giaquinto, Sabrina; Purrello, Francesco; Di Pino, Antonino; Piro, Salvatore; Rozzini, Renzo; Falanga, Lina; Spazzini, Elena; Ferrandina, Camillo; Montrucchio, Giuseppe; Petitti, Paolo; Salmi, Raffaella; Gaudenzi, Piergiorgio; Perri, Ludovica; Landolfi, Raffaele; Montalto, Massimo; Mirijello, Antonio; Guasti, Luigina; Castiglioni, Luana; Maresca, Andrea; Squizzato, Alessandro; Molaro, Marta; Grossi, Alessandra; Bertolotti, Marco; Mussi, Chiara; Libbra, Maria Vittoria; Dondi, Giulia; Pellegrini, Elisa; Carulli, Lucia; Colangelo, Lidia; Falbo, Tania; Stanghellini, Vincenzo; De Giorgio, Roberto; Ruggeri, Eugenio; Vecchio, Sara del; Salvi, Andrea; Leonardi, Roberto; Damiani, Giampaolo; Gabrielli, Armando; Capeci, William; Mattioli, Massimo; Martino, Giuseppe Pio; Biondi, Lorenzo; Pettinari, Pietro; Ghio, Riccardo; Col, Anna Dal; Minisola, Salvatore; Colangelo, Luciano; Afeltra, Antonella; Marigliano, Benedetta; Pipita, Maria Elena; Castellino, Pietro; Blanco, Julien; Zanoli, Luca; Pignataro, Samuele; Saracco, Valter; Fogliati, Marisa; Bussolino, Carlo; Mete, Francesca; Gino, Miriam; Cittadini, Antonio; Vigorito, Carlo; Arcopinto, Michele; Salzano, Andrea; Bobbio, Emanuele; Marra, Alberto Maria; Sirico, Domenico; Moreo, Guido; Gasparini, Francesca; Prolo, Silvia; Pina, Gloria; Ballestrero, Alberto; Ferrando, Fabio; Berra, Sergio; Dassi, Simonetta; Nava, Maria Cristina; Graziella, Bruno; Baldassarre, Stefano; Fragapani, Salvatore; Gruden, Gabriella; Galanti, Giorgio; Mascherini, Gabriele; Petri, Cristian; Stefani, Laura; Girino, Margherita; Piccinelli, Valeria; Nasso, Francesco; Gioffrè, Vincenza; Pasquale, Maria; Scattolin, Giuseppe; Martinelli, Sergio; Turrin, Mauro; Sechi, Leonardo; Catena, Cristina; Colussi, Gianluca; Passariello, Nicola; Rinaldi, Luca; Berti, Franco; Famularo, Giuseppe; Patrizia, Tarsitani; Castello, Roberto; Pasino, Michela; Ceda, Gian Paolo; Maggio, Marcello Giuseppe; Morganti, Simonetta; Artoni, Andrea; Del Giacco, Stefano; Firinu, Davide; Losa, Francesca; Paoletti, Giovanni; Montalto, Giuseppe; Licata, Anna; Malerba, Valentina; Antonino, Lasco; Basile, Giorgio; Antonino, Catalano; Malatino, Lorenzo; Stancanelli, Benedetta; Terranova, Valentina; Di Marca, Salvatore; Mecocci, Patrizia; Ruggiero, Carmelinda; Boccardi, Virginia; Meschi, Tiziana; Lauretani, Fulvio; Ticinesi, Andrea; Minuz, Pietro; Fondrieschi, Luigi; Pirisi, Mario; Fra, Gian Paolo; Sola, Daniele; Porta, Massimo; Riva, Piero; Quadri, Roberto; Scanzi, Giorgio; Mengoli, Caterina; Provini, Stella; Ricevuti, Laura; Simeone, Emilio; Scurti, Rosa; Tolloso, Fabio; Tarquini, Roberto; Valoriani, Alice; Dolenti, Silvia; Vannini, Giulia; Tedeschi, Alberto; Trotta, Lucia; Volpi, Riccardo; Bocchi, Pietro; Vignali, Alessandro; Cattaneo, MaraProietti, Marco; Agosti, Pasquale; Lonati, Chiara; Corrao, Salvatore; Perticone, Francesco; Mannucci, Pier Mannuccio; Nobili, Alessandro; Harari, Sergio; Tettamanti, Mauro; Pasina, Luca; Franchi, Carlotta; Marengoni, Alessandra; Salerno, Francesco; Cesari, Matteo; Licata, Giuseppe; Violi, Francesco; Corazza, Gino Roberto; Cortesi, Laura; Ardoino, Ilaria; Prisco, Domenico; Silvestri, Elena; Cenci, Caterina; Emmi, Giacomo; Biolo, Gianni; Zanetti, Michela; Guadagni, Martina; Zaccari, Michele; Vanoli, Massimo; Grignani, Giulia; Pulixi, Edoardo Alessandro; Bernardi, Mauro; Bassi, Silvia Li; Santi, Luca; Zaccherini, Giacomo; Mannarino, Elmo; Lupattelli, Graziana; Bianconi, Vanessa; Paciullo, Francesco; Nuti, Ranuccio; Valenti, Roberto; Ruvio, Martina; Cappelli, Silvia; Palazzuoli, Alberto; Olivieri, Oliviero; Girelli, Domenico; Matteazzi, Thomas; Barbagallo, Mario; Dominguez, Ligia; Cocita, Floriana; Beneduce, Vincenza; Plances, Lidia; Zoli, Marco; Lazzari, Ilaria; Brunori, Mattia; Pasini, Franco Laghi; Capecchi, Pier Leopoldo; Palasciano, Giuseppe; Modeo, Maria Ester; Di Gennaro, Carla; Cappellini, Maria Domenica; Maira, Diletta; Di Stefano, Valeria; Fabio, Giovanna; Seghezzi, Sonia; Mancarella, Marta; Rossi, Paolo Dionigi; Damanti, Sarah; Clerici, Marta; Conti, Federica; Miceli, Emanuela; Lenti, Marco Vincenzo; Pisati, Martina; Dominioni, Costanza Caccia; Murialdo, Giovanni; Marra, Alessio; Cattaneo, Federico; Pontremoli, Roberto; Secchi, Maria Beatrice; Ghelfi, Davide; Anastasio, Luigi; Sofia, Lucia; Carbone, Maria; Cipollone, Francesco; Guagnano, Maria Teresa; Angelucci, Ermanno; Valeriani, Emanuele; Mancuso, Gerardo; Calipari, Daniela; Bartone, Mosè; Delitala, Giuseppe; Berria, Maria; Muscaritoli, Maurizio; Molfino, Alessio; Petrillo, Enrico; Zuccalà, Giuseppe; D'Aurizio, Gabriella; Romanelli, Giuseppe; Zucchelli, Alberto; Picardi, Antonio; Gentilucci, Umberto Vespasiani; Gallo, Paolo; Dell'Unto, Chiara; Annoni, Giorgio; Corsi, Maurizio; Bellelli, Giuseppe; Zazzetta, Sara; Mazzola, Paolo; Szabo, Hajnalka; Bonfanti, Alessandra; Arturi, Franco; Succurro, Elena; Rubino, Mariangela; Serra, Maria Grazia; Bleve, Maria Antonietta; Gasbarrone, Laura; Sajeva, Maria Rosaria; Brucato, Antonio; Ghidoni, Silvia; Fabris, Fabrizio; Bertozzi, Irene; Bogoni, Giulia; Rabuini, Maria Victoria; Cosi, Elisabetta; Manfredini, Roberto; Fabbian, Fabio; Boari, Benedetta; De Giorgi, Alfredo; Tiseo, Ruana; Paolisso, Giuseppe; Rizzo, Maria Rosaria; Borghi, Claudio; Strocchi, Enrico; De Sando, Valeria; Pareo, Ilenia; Sabbà, Carlo; Vella, Francesco Saverio; Suppressa, Patrizia; Schilardi, Andrea; Loparco, Francesca; Fenoglio, Luigi; Bracco, Christian; Giraudo, Alessia Valentina; Fargion, Silvia; Periti, Giulia; Porzio, Marianna; Tiraboschi, Slivia; Peyvandi, Flora; Rossio, Raffaella; Ferrari, Barbara; Colombo, Giulia; Monzani, Valter; Savojardo, Valeria; Folli, Christian; Ceriani, Giuliana; Pallini, Giada; Dallegri, Franco; Ottonello, Luciano; Liberale, Luca; Caserza, Lara; Salam, Kassem; Liberato, Nicola Lucio; Tognin, Tiziana; Bianchi, Giovanni Battista; Giaquinto, Sabrina; Purrello, Francesco; Di Pino, Antonino; Piro, Salvatore; Rozzini, Renzo; Falanga, Lina; Spazzini, Elena; Ferrandina, Camillo; Montrucchio, Giuseppe; Petitti, Paolo; Salmi, Raffaella; Gaudenzi, Piergiorgio; Perri, Ludovica; Landolfi, Raffaele; Montalto, Massimo; Mirijello, Antonio; Guasti, Luigina; Castiglioni, Luana; Maresca, Andrea; Squizzato, Alessandro; Molaro, Marta; Grossi, Alessandra; Bertolotti, Marco; Mussi, Chiara; Libbra, Maria Vittoria; Dondi, Giulia; Pellegrini, Elisa; Carulli, Lucia; Colangelo, Lidia; Falbo, Tania; Stanghellini, Vincenzo; De Giorgio, Roberto; Ruggeri, Eugenio; Vecchio, Sara del; Salvi, Andrea; Leonardi, Roberto; Damiani, Giampaolo; Gabrielli, Armando; Capeci, William; Mattioli, Massimo; Martino, Giuseppe Pio; Biondi, Lorenzo; Pettinari, Pietro; Ghio, Riccardo; Col, Anna Dal; Minisola, Salvatore; Colangelo, Luciano; Afeltra, Antonella; Marigliano, Benedetta; Pipita, Maria Elena; Castellino, Pietro; Blanco, Julien; Zanoli, Luca; Pignataro, Samuele; Saracco, Valter; Fogliati, Marisa; Bussolino, Carlo; Mete, Francesca; Gino, Miriam; Cittadini, Antonio; Vigorito, Carlo; Arcopinto, Michele; Salzano, Andrea; Bobbio, Emanuele; Marra, Alberto Maria; Sirico, Domenico; Moreo, Guido; Gasparini, Francesca; Prolo, Silvia; Pina, Gloria; Ballestrero, Alberto; Ferrando, Fabio; Berra, Sergio; Dassi, Simonetta; Nava, Maria Cristina; Graziella, Bruno; Baldassarre, Stefano; Fragapani, Salvatore; Gruden, Gabriella; Galanti, Giorgio; Mascherini, Gabriele; Petri, Cristian; Stefani, Laura; Girino, Margherita; Piccinelli, Valeria; Nasso, Francesco; Gioffrè, Vincenza; Pasquale, Maria; Scattolin, Giuseppe; Martinelli, Sergio; Turrin, Mauro; Sechi, Leonardo; Catena, Cristina; Colussi, Gianluca; Passariello, Nicola; Rinaldi, Luca; Berti, Franco; Famularo, Giuseppe; Patrizia, Tarsitani; Castello, Roberto; Pasino, Michela; Ceda, Gian Paolo; Maggio, Marcello Giuseppe; Morganti, Simonetta; Artoni, Andrea; Del Giacco, Stefano; Firinu, Davide; Losa, Francesca; Paoletti, Giovanni; Montalto, Giuseppe; Licata, Anna; Malerba, Valentina; Antonino, Lasco; Basile, Giorgio; Antonino, Catalano; Malatino, Lorenzo; Stancanelli, Benedetta; Terranova, Valentina; Di Marca, Salvatore; Mecocci, Patrizia; Ruggiero, Carmelinda; Boccardi, Virginia; Meschi, Tiziana; Lauretani, Fulvio; Ticinesi, Andrea; Minuz, Pietro; Fondrieschi, Luigi; Pirisi, Mario; Fra, Gian Paolo; Sola, Daniele; Porta, Massimo; Riva, Piero; Quadri, Roberto; Scanzi, Giorgio; Mengoli, Caterina; Provini, Stella; Ricevuti, Laura; Simeone, Emilio; Scurti, Rosa; Tolloso, Fabio; Tarquini, Roberto; Valoriani, Alice; Dolenti, Silvia; Vannini, Giulia; Tedeschi, Alberto; Trotta, Lucia; Volpi, Riccardo; Bocchi, Pietro; Vignali, Alessandro; Cattaneo, Mar

Antihypertensive treatment changes and related clinical outcomes in older hospitalized patients

Background: Hypertension management in older patients represents a challenge, particularly when hospitalized. Objective: The objective of this study is to investigate the determinants and related outcomes of antihypertensive drug prescription in a cohort of older hospitalized patients. Methods: A total of 5671 patients from REPOSI (a prospective multicentre observational register of older Italian in-patients from internal medicine or geriatric wards) were considered; 4377 (77.2%) were hypertensive. Minimum treatment (MT) for hypertension was defined according to the 2018 ESC guidelines [an angiotensin-converting-enzyme-inhibitor (ACE-I) or an angiotensin-receptor-blocker (ARB) with a calcium-channel-blocker (CCB) and/or a thiazide diuretic; if >80 years old, an ACE-I or ARB or CCB or thiazide diuretic]. Determinants of MT discontinuation at discharge were assessed. Study outcomes were any cause rehospitalization/all cause death, all-cause death, cardiovascular (CV) hospitalization/death, CV death, non-CV death, evaluated according to the presence of MT at discharge. Results: Hypertensive patients were older than normotensives, with a more impaired functional status, higher burden of comorbidity and polypharmacy. A total of 2233 patients were on MT at admission, 1766 were on MT at discharge. Discontinuation of MT was associated with the presence of comorbidities (lower odds for diabetes, higher odds for chronic kidney disease and dementia). An adjusted multivariable logistic regression analysis showed that MT for hypertension at discharge was associated with lower risk of all-cause death, all-cause death/hospitalization, CV death, CV death/hospitalization and non-CV death. Conclusions: Guidelines-suggested MT for hypertension at discharge is associated with a lower risk of adverse clinical outcomes. Nevertheless, changes in antihypertensive treatment still occur in a significant proportion of older hospitalized patients