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555 results on '"Barbati G"'

1. Identification of hemodynamically stable patients with acute pulmonary embolism at high risk for death: external validation of different models

Author

Becattini, Cecilia, Gulizia, Michele M., Agnelli, Giancarlo, Dentali, Francesco, Di Lenarda, Andrea, Enea, Iolanda, Fabbri, Andrea, Maggioni, Aldo P., Pomero, Fulvio, Ruggeri, Maria Pia, Lucci, Donata, Vedovati, Maria Cristina, Duranti, Michele, Guercini, Francesco, Groff, Paolo, Verso, Melina, Fabbri, Gianna, Savoia, Martina, Baldini, Ester, Mecatti, Barbara Bartolomei, Bianchini, Francesca, Ceseri, Martina, Gonzini, Lucio, Gorini, Marco, Lorimer, Andrea, Orsini, Giampietro, Tricoli, Martina, Cimini, L.A., Becattini, C., Agnelli, G., Cesarini, V., Sanna, M., Pepe, G., Marchetti, C., Roldan, M. Olivan, Lenzi, L., Cozzio, S., Tomio, P., Diamanti, M., Beltrame, A., Glinski, L., Treleani, M., Coppa, A., Vanni, S., Bartalucci, P., Taccone, A., Costacurta, C., Bortolotti, P., Bortolussi, M., De Vecchi, M., Zanardi, F., Greco, I., Cosentini, R., Gerloni, R., Artusi, N., Cominotto, F., Sisto, U.G., Picariello, C., Roncon, L., Maddalozzo, A., Nitti, C., Riccomi, F., Buzzo, M., Bassanelli, G., Savonitto, S., Bianchi, A., Bilato, C., Lobascio, I., Dalla Valle, C., Pomata, D.P., Giostra, F., Tinuper, A.L., Zalunardo, B., Visonà, A., Panzavolta, C., Novelli, A., Bertini, A., Granai, C., Colombo, S., Periti, E., Bonacchini, L., Abrignani, M.G., Casciolo, M.F., D'Amato, A., Scardovi, A.B., Ricci, R., Iosi, S., Fontana, M.C., Marrazzo, A., Borselli, M., Di Fusco, S.A., Colivicchi, F., Enea, I., Triggiani, M., Papa, I., Pasini, G.F., Fioravanti, C., Panarello, S., Raggi, F., Marzolo, M., Cuppini, S., Milan, M., Barchetti, M., De Laura, D., Caldarola, P., Fiorini, R., Rastelli, G., Ameri, P., La Malfa, G., Cinelli, F., Sganzerla, P.C., Ubaldi, S., Sanchez, F.A., Forgione, C., Cuccia, C., Predieri, S., Fusco, S., Mumoli, N., Porta, C., Romei, M., Lucidi, M., Romaniello, A., Volpe, M., Mogni, P., Pizzolato, E., Martino, G.P., Bitti, G., Righini, G., Bandiera, G., Pennacchio, E., Limauro, S., Dachille, A., Ignone, G., Fuscaldo, G.F., De Rosa, F.M., Vazzana, N., Chesi, G., Di Filippo, F., Pierpaoli, L., Corapi, A., Vatrano, M., Angotti, C., Baccetti, F., Harari, S.A., Luisi, F., Daghini, E., De Curtis, E., Lucà, F., Ciancia, F., Blandizzi, S., Lettica, G.V., D'Orazio, S., Cosmi, F., Zaccaroni, S., Silingardi, M., Valeriano, V., Pugliese, F.R., Murgia, A.P., Parpaglia, P. Pinna, Martinelli, L., Caponi, C., Clemente, M.A., Ciccarone, A., Bongarzoni, A., Garagiola, M., Leone, M.C., Veropalumbo, M.R., Sacco, M., Morella, P., Dorigoni, S., Peterlana, D., Di Paola, R., Felis, S., Correale, M., Brunetti, N.D., Petrelli, G., Feliziani, F.T., Mastroiacovo, D., Romualdi, R., Pasin, F., Bonardi, S., Delfino, P., Scifo, C., Savioli, G., Ceresa, I.F., Galeotalanza, M., Benazzi, B., Porzio, M., Rosini, F., Ancona, C., Verrelli, C., Pasini, A. Fratta, Dalle Carbonare, L., Bozza, N., Nacci, F., Scarabelli, M.A., Amico, F., Marchesi, C., Mazzone, A., Di Tommaso, R., Cocco, F., Pezzuto, G., Luciani, A., Zamboni, P., Muriago, M., Del Pesce, L., Lucarini, A.R., Guglielmelli, E., Vannucchi, V., Moroni, F., Fichera, D., Malatino, L., Sgroi, C., Morana, I.M., Cicero, S., La Rosa, D., Mete, F., Gino, M., De Palma, A., Alessandri, M., Maestripieri, V., Battocchio, M., De Santis, M.T., Saladini, F., Corsi, D.C., Macarone Palmieri, N., Pierfranceschi, M. Giorgi, Palmonari, V., Fontanella, L., Airoldi, L., Bonocore, M., Paliani, U., Prat, L. Iogna, Chiecchi, L., Cuonzo, M., Paludo, A., Padula, D., Antonelli, A., Bicchi, M., Tota, G., Ariello, M., Sai, R., Civita, M., Tucci, M., Barbati, G., Conti, M., Cettina, R., Magnani, O., Levato, M., Gessi, V., De Rui, M., Bellizzi, A., Farneti, L., Salomone, P., Mannarini, A., Grifoni, E., Del Ghianda, S., Campodonico, J., De Cesare, N., Mutone, D., Pasoli, P., Meloni, S., Frenda, A., Viola, G., Torromeo, C., Campana, C., Pistone, M.C., Caravita, S., La Creta, C.P., Miscio, F., Loreno, M., Fenu, P., Mazzetti, M., Rossini, D., Brunacci, M., Capuano, A., Tagliamonte, G., Pinelli, M., Ballocca, F., Parca, G., Pasini, S.M., Maragno, M.G., Vecchi, F., Mancinelli, L., Cavalli, A., Di Mare, F., Conficoni, E., Miceli, R., Pecoraro, R., Fonti, C., Pegoraro, S., Piccinni, G.C., Caruso, G., Boriani, G., Lanzillotta, P., Piccolo, P., Calò, L., Stolfo, D., Mangiacapra, S., Marziali, A., Volponi, M.C., Querci, G., Terribile, R., Menabue, M., Fiorentini, A., Musci, R.L., Uras, S., Cicini, M.P., Manetti, S., Francese, G.M., Melchio, R., Scorpiglione, N., Carrara, D., Pani, A., Morisco, C., Rodolico, M., Colombo, Silvia, Vanni, Simone, Abrignani, Maurizio Giuseppe, Scardovi, Angela Beatrice, Marrazzo, Alessandra, Borselli, Matteo, Barchetti, Marco, and Maggioni, Aldo Pietro

Published
2024
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2. Deep artificial neural network for prediction of atrial fibrillation through the analysis of 12-leads standard ECG

Author

Scagnetto, A., Barbati, G., Gandin, I., Cappelletto, C., Baj, G., Cazzaniga, A., Cuturello, F., Ansuini, A., Bortolussi, L., and Di Lenarda, A.

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning
Abstract

Atrial Fibrillation (AF) is a heart's arrhythmia which, despite being often asymptomatic, represents an important risk factor for stroke, therefore being able to predict AF at the electrocardiogram exam, would be of great impact on actively targeting patients at high risk. In the present work we use Convolution Neural Networks to analyze ECG and predict Atrial Fibrillation starting from realistic datasets, i.e. considering fewer ECG than other studies and extending the maximal distance between ECG and AF diagnosis. We achieved 75.5% (0.75) AUC firstly increasing our dataset size by a shifting technique and secondarily using the dilation parameter of the convolution neural network. In addition we find that, contrarily to what is commonly used by clinicians reporting AF at the exam, the most informative leads for the task of predicting AF are D1 and avR. Similarly, we find that the most important frequencies to check are in the range of 5-20 Hz. Finally, we develop a net able to manage at the same time the electrocardiographic signal together with the electronic health record, showing that integration between different sources of data is a profitable path. In fact, the 2.8% gain of such net brings us to a 78.6% (std 0.77) AUC. In future works we will deepen both the integration of sources and the reason why we claim avR is the most informative lead., Comment: 10 pages, 2 figures, 5 tables

Published
2022

8. Flexible Approaches Based on Multistate Models and Microsimulation to Perform Real-World Cost-Effectiveness Analyses: An Application to Proprotein Convertase Subtilisin-Kexin Type 9 Inhibitors

Author

Gregorio, C, Rea, F, Ieva, F, Scagnetto, A, Indennidate, C, Cappelletto, C, Di Lenarda, A, Barbati, G, Gregorio, C, Rea, F, Ieva, F, Scagnetto, A, Indennidate, C, Cappelletto, C, Di Lenarda, A, and Barbati, G

Abstract

Objectives: This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia. Methods: The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models. Results: In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained. Conclusions: The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights.

Published
2024

10. Organization and Activity of Italian Echocardiographic Laboratories: A Survey of the Italian Society of Echocardiography and Cardiovascular Imaging

Author

Ciampi, Q, Pepi, M, Antonini-Canterin, F, Barbieri, A, Barchitta, A, Faganello, G, Miceli, S, Parato, V, Tota, A, Trocino, G, Abbate, M, Accadia, M, Alemanni, R, Angelini, A, Anglano, F, Anselmi, M, Aquila, I, Aramu, S, Avogadri, E, Azzaro, G, Badano, L, Balducci, A, Ballocca, F, Barbarossa, A, Barbati, G, Barletta, V, Barone, D, Becherini, F, Benfari, G, Beraldi, M, Bergandi, G, Bilardo, G, Binno, S, Bolognesi, M, Bongiovi, S, Bragato, R, Braggion, G, Brancaleoni, R, Bursi, F, Dessalvi, C, Cameli, M, Canu, A, Capitelli, M, Capra, A, Carbonara, R, Carbone, M, Carbonella, M, Carrabba, N, Casavecchia, G, Casula, M, Chesi, E, Cicco, S, Citro, R, Cocchia, R, Colombo, B, Colonna, P, Conte, M, Corrado, G, Cortesi, P, Cortigiani, L, Costantino, M, Cozza, F, Cucchini, U, D'Angelo, M, Ros, S, D'Andrea, F, D'Andrea, A, D'Auria, F, De Caridi, G, De Feo, S, De Matteis, G, De Vecchi, S, Del Giudice, C, Dell'Angela, L, Delli Paoli, L, Dentamaro, I, Destefanis, P, Di Fulvio, M, Di Gaetano, R, Di Giannuario, G, Di Gioia, A, Di Martino, L, Di Muro, C, Di Nora, C, Di Salvo, G, Dodi, C, Dogliani, S, Donati, F, Dottori, M, Epifani, G, Fabiani, I, Ferrara, F, Ferrara, L, Ferrua, S, Filice, G, Fiorino, M, Forno, D, Garini, A, Giarratana, G, Gigantino, G, Giorgi, M, Giubertoni, E, Greco, C, Grigolato, M, Marra, W, Holzl, A, Iaiza, A, Iannaccone, A, Ilardi, F, Imbalzano, E, Inciardi, R, Inserra, C, Iori, E, Izzo, A, La Rosa, G, Labanti, G, Lanzone, A, Lanzoni, L, Lapetina, O, Leiballi, E, Librera, M, Lo Conte, C, Lo Monaco, M, Lombardo, A, Luciani, M, Lusardi, P, Magnante, A, Malagoli, A, Malatesta, G, Mancusi, C, Manes, M, Manganelli, F, Mantovani, F, Manuppelli, V, Marchese, V, Marinacci, L, Mattioli, R, Maurizio, C, Mazza, G, Mazza, S, Melis, M, Meloni, G, Merli, E, Milan, A, Minardi, G, Monaco, A, Monte, I, Montresor, G, Moreo, A, Mori, F, Morini, S, Moro, C, Morrone, D, Negri, F, Nipote, C, Nisi, F, Nocco, S, Novello, L, Nunziata, L, Perini, A, Parodi, A, Pasanisi, E, Pastorini, G, Pavasini, R, Pavoni, D, Pedone, C, Pelliccia, F, Pelliciari, G, Pelloni, E, Pergola, V, Perillo, G, Petruccelli, E, Pezzullo, C, Piacentini, G, Picardi, E, Pinna, G, Pizzarelli, M, Pizzuti, A, Poggi, M, Posteraro, A, Privitera, C, Rampazzo, D, Ratti, C, Rettegno, S, Ricci, F, Ricci, C, Rolando, C, Rossi, S, Rovera, C, Ruggieri, R, Russo, M, Sacchi, N, Saladino, A, Sani, F, Sartori, C, Scarabeo, V, Sciacqua, A, Scillone, A, Scopelliti, P, Scorza, A, Scozzafava, A, Serafini, F, Serra, W, Severino, S, Simeone, B, Sirico, D, Solari, M, Spadaro, G, Stefani, L, Strangio, A, Surace, F, Tamborini, G, Tarquinio, N, Tassone, E, Tavarozzi, I, Tchana, B, Tedesco, G, Tinto, M, Torzillo, D, Totaro, A, Triolo, O, Troisi, F, Tusa, M, Vancheri, F, Varasano, V, Venezia, A, Vermi, A, Villari, B, Zampi, G, Zannoni, J, Zito, C, Zugaro, A, Di Bella, G, Carerj, S, Ciampi Q., Pepi M., Antonini-Canterin F., Barbieri A., Barchitta A., Faganello G., Miceli S., Parato V. M., Tota A., Trocino G., Abbate M., Accadia M., Alemanni R., Angelini A., Anglano F., Anselmi M., Aquila I., Aramu S., Avogadri E., Azzaro G., Badano L., Balducci A., Ballocca F., Barbarossa A., Barbati G., Barletta V., Barone D., Becherini F., Benfari G., Beraldi M., Bergandi G., Bilardo G., Binno S. M., Bolognesi M., Bongiovi S., Bragato R. M., Braggion G., Brancaleoni R., Bursi F., Dessalvi C. C., Cameli M., Canu A., Capitelli M., Capra A. C. M., Carbonara R., Carbone M., Carbonella M., Carrabba N., Casavecchia G., Casula M., Chesi E., Cicco S., Citro R., Cocchia R., Colombo B. M., Colonna P., Conte M., Corrado G., Cortesi P., Cortigiani L., Costantino M. F., Cozza F., Cucchini U., D'Angelo M., Ros S. D., D'Andrea F., D'Andrea A., D'Auria F., De Caridi G., De Feo S., De Matteis G. M., De Vecchi S., Del Giudice C., Dell'Angela L., Delli Paoli L., Dentamaro I., Destefanis P., Di Fulvio M., Di Gaetano R., Di Giannuario G., Di Gioia A., Di Martino L. F. M., Di Muro C., Di Nora C., Di Salvo G., Dodi C., Dogliani S., Donati F., Dottori M., Epifani G., Fabiani I., Ferrara F., Ferrara L., Ferrua S., Filice G., Fiorino M., Forno D., Garini A., Giarratana G. A., Gigantino G., Giorgi M., Giubertoni E., Greco C. A., Grigolato M., Marra W. G., Holzl A., Iaiza A., Iannaccone A., Ilardi F., Imbalzano E., Inciardi R., Inserra C. A., Iori E., Izzo A., La Rosa G., Labanti G., Lanzone A. M., Lanzoni L., Lapetina O., Leiballi E., Librera M., Lo Conte C., Lo Monaco M., Lombardo A., Luciani M., Lusardi P., Magnante A., Malagoli A., Malatesta G., Mancusi C., Manes M. T., Manganelli F., Mantovani F., Manuppelli V., Marchese V., Marinacci L., Mattioli R., Maurizio C., Mazza G. A., Mazza S., Melis M., Meloni G., Merli E., Milan A., Minardi G., Monaco A., Monte I., Montresor G., Moreo A., Mori F., Morini S., Moro C., Morrone D., Negri F., Nipote C., Nisi F., Nocco S., Novello L., Nunziata L., Perini A. P., Parodi A., Pasanisi E. M., Pastorini G., Pavasini R., Pavoni D., Pedone C., Pelliccia F., Pelliciari G., Pelloni E., Pergola V., Perillo G., Petruccelli E., Pezzullo C., Piacentini G., Picardi E., Pinna G., Pizzarelli M., Pizzuti A., Poggi M. M., Posteraro A., Privitera C., Rampazzo D., Ratti C., Rettegno S., Ricci F., Ricci C., Rolando C., Rossi S., Rovera C., Ruggieri R., Russo M. G., Sacchi N., Saladino A., Sani F., Sartori C., Scarabeo V., Sciacqua A., Scillone A., Scopelliti P. A., Scorza A., Scozzafava A., Serafini F., Serra W., Severino S., Simeone B., Sirico D., Solari M., Spadaro G. L., Stefani L., Strangio A., Surace F. C., Tamborini G., Tarquinio N., Tassone E. J., Tavarozzi I., Tchana B., Tedesco G., Tinto M., Torzillo D., Totaro A., Triolo O. F., Troisi F., Tusa M., Vancheri F., Varasano V., Venezia A., Vermi A. C., Villari B., Zampi G., Zannoni J., Zito C., Zugaro A., Di Bella G., Carerj S., Ciampi, Q, Pepi, M, Antonini-Canterin, F, Barbieri, A, Barchitta, A, Faganello, G, Miceli, S, Parato, V, Tota, A, Trocino, G, Abbate, M, Accadia, M, Alemanni, R, Angelini, A, Anglano, F, Anselmi, M, Aquila, I, Aramu, S, Avogadri, E, Azzaro, G, Badano, L, Balducci, A, Ballocca, F, Barbarossa, A, Barbati, G, Barletta, V, Barone, D, Becherini, F, Benfari, G, Beraldi, M, Bergandi, G, Bilardo, G, Binno, S, Bolognesi, M, Bongiovi, S, Bragato, R, Braggion, G, Brancaleoni, R, Bursi, F, Dessalvi, C, Cameli, M, Canu, A, Capitelli, M, Capra, A, Carbonara, R, Carbone, M, Carbonella, M, Carrabba, N, Casavecchia, G, Casula, M, Chesi, E, Cicco, S, Citro, R, Cocchia, R, Colombo, B, Colonna, P, Conte, M, Corrado, G, Cortesi, P, Cortigiani, L, Costantino, M, Cozza, F, Cucchini, U, D'Angelo, M, Ros, S, D'Andrea, F, D'Andrea, A, D'Auria, F, De Caridi, G, De Feo, S, De Matteis, G, De Vecchi, S, Del Giudice, C, Dell'Angela, L, Delli Paoli, L, Dentamaro, I, Destefanis, P, Di Fulvio, M, Di Gaetano, R, Di Giannuario, G, Di Gioia, A, Di Martino, L, Di Muro, C, Di Nora, C, Di Salvo, G, Dodi, C, Dogliani, S, Donati, F, Dottori, M, Epifani, G, Fabiani, I, Ferrara, F, Ferrara, L, Ferrua, S, Filice, G, Fiorino, M, Forno, D, Garini, A, Giarratana, G, Gigantino, G, Giorgi, M, Giubertoni, E, Greco, C, Grigolato, M, Marra, W, Holzl, A, Iaiza, A, Iannaccone, A, Ilardi, F, Imbalzano, E, Inciardi, R, Inserra, C, Iori, E, Izzo, A, La Rosa, G, Labanti, G, Lanzone, A, Lanzoni, L, Lapetina, O, Leiballi, E, Librera, M, Lo Conte, C, Lo Monaco, M, Lombardo, A, Luciani, M, Lusardi, P, Magnante, A, Malagoli, A, Malatesta, G, Mancusi, C, Manes, M, Manganelli, F, Mantovani, F, Manuppelli, V, Marchese, V, Marinacci, L, Mattioli, R, Maurizio, C, Mazza, G, Mazza, S, Melis, M, Meloni, G, Merli, E, Milan, A, Minardi, G, Monaco, A, Monte, I, Montresor, G, Moreo, A, Mori, F, Morini, S, Moro, C, Morrone, D, Negri, F, Nipote, C, Nisi, F, Nocco, S, Novello, L, Nunziata, L, Perini, A, Parodi, A, Pasanisi, E, Pastorini, G, Pavasini, R, Pavoni, D, Pedone, C, Pelliccia, F, Pelliciari, G, Pelloni, E, Pergola, V, Perillo, G, Petruccelli, E, Pezzullo, C, Piacentini, G, Picardi, E, Pinna, G, Pizzarelli, M, Pizzuti, A, Poggi, M, Posteraro, A, Privitera, C, Rampazzo, D, Ratti, C, Rettegno, S, Ricci, F, Ricci, C, Rolando, C, Rossi, S, Rovera, C, Ruggieri, R, Russo, M, Sacchi, N, Saladino, A, Sani, F, Sartori, C, Scarabeo, V, Sciacqua, A, Scillone, A, Scopelliti, P, Scorza, A, Scozzafava, A, Serafini, F, Serra, W, Severino, S, Simeone, B, Sirico, D, Solari, M, Spadaro, G, Stefani, L, Strangio, A, Surace, F, Tamborini, G, Tarquinio, N, Tassone, E, Tavarozzi, I, Tchana, B, Tedesco, G, Tinto, M, Torzillo, D, Totaro, A, Triolo, O, Troisi, F, Tusa, M, Vancheri, F, Varasano, V, Venezia, A, Vermi, A, Villari, B, Zampi, G, Zannoni, J, Zito, C, Zugaro, A, Di Bella, G, Carerj, S, Ciampi Q., Pepi M., Antonini-Canterin F., Barbieri A., Barchitta A., Faganello G., Miceli S., Parato V. M., Tota A., Trocino G., Abbate M., Accadia M., Alemanni R., Angelini A., Anglano F., Anselmi M., Aquila I., Aramu S., Avogadri E., Azzaro G., Badano L., Balducci A., Ballocca F., Barbarossa A., Barbati G., Barletta V., Barone D., Becherini F., Benfari G., Beraldi M., Bergandi G., Bilardo G., Binno S. M., Bolognesi M., Bongiovi S., Bragato R. M., Braggion G., Brancaleoni R., Bursi F., Dessalvi C. C., Cameli M., Canu A., Capitelli M., Capra A. C. M., Carbonara R., Carbone M., Carbonella M., Carrabba N., Casavecchia G., Casula M., Chesi E., Cicco S., Citro R., Cocchia R., Colombo B. M., Colonna P., Conte M., Corrado G., Cortesi P., Cortigiani L., Costantino M. F., Cozza F., Cucchini U., D'Angelo M., Ros S. D., D'Andrea F., D'Andrea A., D'Auria F., De Caridi G., De Feo S., De Matteis G. M., De Vecchi S., Del Giudice C., Dell'Angela L., Delli Paoli L., Dentamaro I., Destefanis P., Di Fulvio M., Di Gaetano R., Di Giannuario G., Di Gioia A., Di Martino L. F. M., Di Muro C., Di Nora C., Di Salvo G., Dodi C., Dogliani S., Donati F., Dottori M., Epifani G., Fabiani I., Ferrara F., Ferrara L., Ferrua S., Filice G., Fiorino M., Forno D., Garini A., Giarratana G. A., Gigantino G., Giorgi M., Giubertoni E., Greco C. A., Grigolato M., Marra W. G., Holzl A., Iaiza A., Iannaccone A., Ilardi F., Imbalzano E., Inciardi R., Inserra C. A., Iori E., Izzo A., La Rosa G., Labanti G., Lanzone A. M., Lanzoni L., Lapetina O., Leiballi E., Librera M., Lo Conte C., Lo Monaco M., Lombardo A., Luciani M., Lusardi P., Magnante A., Malagoli A., Malatesta G., Mancusi C., Manes M. T., Manganelli F., Mantovani F., Manuppelli V., Marchese V., Marinacci L., Mattioli R., Maurizio C., Mazza G. A., Mazza S., Melis M., Meloni G., Merli E., Milan A., Minardi G., Monaco A., Monte I., Montresor G., Moreo A., Mori F., Morini S., Moro C., Morrone D., Negri F., Nipote C., Nisi F., Nocco S., Novello L., Nunziata L., Perini A. P., Parodi A., Pasanisi E. M., Pastorini G., Pavasini R., Pavoni D., Pedone C., Pelliccia F., Pelliciari G., Pelloni E., Pergola V., Perillo G., Petruccelli E., Pezzullo C., Piacentini G., Picardi E., Pinna G., Pizzarelli M., Pizzuti A., Poggi M. M., Posteraro A., Privitera C., Rampazzo D., Ratti C., Rettegno S., Ricci F., Ricci C., Rolando C., Rossi S., Rovera C., Ruggieri R., Russo M. G., Sacchi N., Saladino A., Sani F., Sartori C., Scarabeo V., Sciacqua A., Scillone A., Scopelliti P. A., Scorza A., Scozzafava A., Serafini F., Serra W., Severino S., Simeone B., Sirico D., Solari M., Spadaro G. L., Stefani L., Strangio A., Surace F. C., Tamborini G., Tarquinio N., Tassone E. J., Tavarozzi I., Tchana B., Tedesco G., Tinto M., Torzillo D., Totaro A., Triolo O. F., Troisi F., Tusa M., Vancheri F., Varasano V., Venezia A., Vermi A. C., Villari B., Zampi G., Zannoni J., Zito C., Zugaro A., Di Bella G., and Carerj S.

Abstract

Background: The Italian Society of Echocardiography and Cardiovascular Imaging (SIECVI) conducted a national survey to understand better how different echocardiographic modalities are used and accessed in Italy. Methods: We analyzed echocardiography laboratory activities over a month (November 2022). Data were retrieved via an electronic survey based on a structured questionnaire, uploaded on the SIECVI website. Results: Data were obtained from 228 echocardiographic laboratories: 112 centers (49%) in the northern, 43 centers (19%) in the central, and 73 (32%) in the southern regions. During the month of observation, we collected 101,050 transthoracic echocardiography (TTE) examinations performed in all centers. As concern other modalities there were performed 5497 transesophageal echocardiography (TEE) examinations in 161/228 centers (71%); 4057 stress echocardiography (SE) examinations in 179/228 centers (79%); and examinations with ultrasound contrast agents (UCAs) in 151/228 centers (66%). We did not find significant regional variations between the different modalities. The usage of picture archiving and communication system (PACS) was significantly higher in the northern (84%) versus central (49%) and southern (45%) centers (P < 0.001). Lung ultrasound (LUS) was performed in 154 centers (66%), without difference between cardiology and noncardiology centers. The evaluation of left ventricular (LV) ejection fraction was evaluated mainly using the qualitative method in 223 centers (94%), occasionally with the Simpson method in 193 centers (85%), and with selective use of the three-dimensional (3D) method in only 23 centers (10%). 3D TTE was present in 137 centers (70%), and 3D TEE in all centers where TEE was done (71%). The assessment of LV diastolic function was done routinely in 80% of the centers. Right ventricular function was evaluated using tricuspid annular plane systolic excursion in all centers, using tricuspid valve annular systolic velocity by tissue

Published
2023

14. Patient adherence to drug treatment in a community based-sample of patients with chronic heart failure

Author

Rea, F, Iorio, A, Barbati, G, Bessi, R, Castrichini, M, Nuzzi, V, Scagnetto, A, Senni, M, Corrao, G, Sinagra, G, Di Lenarda, A, Rea F., Iorio A., Barbati G., Bessi R., Castrichini M., Nuzzi V., Scagnetto A., Senni M., Corrao G., Sinagra G., Di Lenarda A., Rea, F, Iorio, A, Barbati, G, Bessi, R, Castrichini, M, Nuzzi, V, Scagnetto, A, Senni, M, Corrao, G, Sinagra, G, Di Lenarda, A, Rea F., Iorio A., Barbati G., Bessi R., Castrichini M., Nuzzi V., Scagnetto A., Senni M., Corrao G., Sinagra G., and Di Lenarda A.

Published
2022

15. P123 TRANSCATHETER ABLATION OF SUPRAVENTRICULAR ARRHYTHMIAS IN PATIENTS SUFFERING FROM HYPERTROPHIC CARDIOMYOPATHY: A PROPENSITY SCORE–BASED ANALYSIS

Author

Pierri, A, primary, Albani, S, additional, Buongiorno, A, additional, Ricotti, A, additional, Grossi, S, additional, De Rosa, C, additional, Mabritto, B, additional, Bongioanni, S, additional, Luceri, S, additional, Negri, F, additional, Grilli, G, additional, Barbisan, D, additional, Burelli, M, additional, Biondi, F, additional, Cireddu, M, additional, Berg, J, additional, Musumeci, M, additional, Di Donna, P, additional, Vianello, P, additional, Del Franco, A, additional, Scaglione, M, additional, Barbati, G, additional, Berchialla, P, additional, Russo, V, additional, Imazio, M, additional, Porto, I, additional, Canepa, M, additional, Peretto, G, additional, Francia, P, additional, Autore, C, additional, Castagno, D, additional, Gaita, F, additional, Olivotto, I, additional, Merlo, M, additional, Sinagra, G, additional, and Musumeci, G, additional

Published
2023
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17. Predictive value of valgus head-shaft angle in identifying Neer 4-part proximal humerus fractures. A radiographic and CT-scan analysis of 120 cases

Author

Murena, L., Ratti, C., Maritan, G., Rasio, N., Grandesso, M., Barbati, G., Cusitore, M., Canton, G., Murena, L., Ratti, C., Maritan, G., Rasio, N., Grandesso, M., Barbati, G., Cusitore, M., and Canton, G.

Subjects
Male, 4-part fracture, Humeral head-shaft angle, Predictive value, Proximal humerus fractures, Valgus displacement, predictive value, humeral head-shaft angle, Proximal humerus fracture, valgus displacement, Middle Aged, Radiography, proximal humerus fractures, Injury Severity Score, Predictive Value of Tests, Shoulder Fractures, Humans, Original Article, Female, Tomography, X-Ray Computed, Aged
Abstract

Background and aim of the work: Understanding the fracture morphology and its relation to the expected outcome and risk of complications is fundamental for proximal humerus fractures (PHFs) management. Most Neer 3- and 4-part fractures may deserve surgical treatment. Unfortunately, plain x-rays may not be able to differentiate between a 3- or 4-part fractures unless an axillary or analogue projection is carried out. Aim of the present study is to evaluate whether a high valgus head-shaft angle degree is predictive of a Neer 4-part rather than a 3-part fracture. Methods: The study included 120 3-(75 cases) and 4-(45 cases) part PHFs (valgus displaced in 98 cases), M:F ratio = 1:2.6, mean age 65.7 years, classified on CT scan images. The humeral head shaft angle was calculated on AP x-rays and statistically correlated with 3 and 4-part fractures to identify values predictive of 4-part fracture. Results: Valgus head/shaft angle was significantly higher in 4-part fractures, especially in the valgus displaced group (p < 0.001). A cutoff value of 168.5° was identified as predictive of a 4-part fracture with a sensibility of 74% and specificity of 78%. Increasing by 1 degree the humeral head-shaft angle, the chance to have a 4-part fracture increases of 3% in the whole population and of 11% in the valgus sub-group. Conclusion: The severity of PHF can be predicted analysing valgus head shaft angle on AP x-rays with a sensibility of 74% and specificity of 78% in identifying a 4-part fracture with a cutoff value of 168.5°.

Published
2020

22. C65 POST–DISCHARGE ARRHYTHMIC RISK STRATIFICATION OF PATIENTS WITH ACUTE MYOCARDITIS AND LIFE–THREATENING VENTRICULAR TACHYARRHYTHMIAS

Author

Gentile, P, primary, Merlo, M, additional, Peretto, G, additional, Ammirati, E, additional, Sala, S, additional, Della Bella, P, additional, Aquaro, G, additional, Imazio, M, additional, Potena, L, additional, Campodonico, J, additional, Foà, A, additional, Raafs, A, additional, Hazebroek, M, additional, Brambatti, M, additional, Cercek, A, additional, Nucifora, G, additional, Shrivastava, S, additional, Huang, F, additional, Schmidt, M, additional, Muser, D, additional, Van De Heyning, C, additional, Van Craenenbroeck, E, additional, Aoki, T, additional, Sugimura, K, additional, Shimokawa, H, additional, Cannatà, A, additional, Artico, J, additional, Porcari, A, additional, Colopi, M, additional, Bussani, R, additional, Barbati, G, additional, Garascia, A, additional, Cipriani, M, additional, Agostoni, P, additional, Pereira, N, additional, Heymans, S, additional, Adler, E, additional, Camici, P, additional, Frigerio, M, additional, and Sinagra, G, additional

Published
2022
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28. Persistent left ventricular dysfunction after acute lymphocytic myocarditis: Frequency and predictors

Author

Merlo, M, Ammirati, E, Gentile, P, Artico, J, Cannata, A, Finocchiaro, G, Barbati, G, Sormani, P, Varrenti, M, Perkan, A, Fabris, E, Aleksova, A, Bussani, R, Petrella, D, Cipriani, M, Raineri, C, Frigerio, M, Sinagra, G, Merlo M., Ammirati E., Gentile P., Artico J., CANNATA, ADALGISA, Finocchiaro G., Barbati G., Sormani P., Varrenti M., Perkan A., Fabris E., Aleksova A., Bussani R., Petrella D., Cipriani M., Raineri C., Frigerio M., Sinagra G., Merlo, M, Ammirati, E, Gentile, P, Artico, J, Cannata, A, Finocchiaro, G, Barbati, G, Sormani, P, Varrenti, M, Perkan, A, Fabris, E, Aleksova, A, Bussani, R, Petrella, D, Cipriani, M, Raineri, C, Frigerio, M, Sinagra, G, Merlo M., Ammirati E., Gentile P., Artico J., CANNATA, ADALGISA, Finocchiaro G., Barbati G., Sormani P., Varrenti M., Perkan A., Fabris E., Aleksova A., Bussani R., Petrella D., Cipriani M., Raineri C., Frigerio M., and Sinagra G.

Abstract

Background Persistent left ventricular (LV) systolic dysfunction in patients with acute lymphocytic myocarditis (LM) is widely unexplored. Objectives To assess the frequency and predictors of persistent LV dysfunction in patients with LM and reduced LVEF at admission. Methods and results We retrospectively evaluated 89 consecutive patients with histologically-proven acute myocarditis enrolled at three Italian referral hospitals. A subgroup of 48 patients with LM, baseline systolic impairment and an available echocardiographic assessment at 12 months (6–18) from discharge constituted the study population. The primary study end-point was persistent LV dysfunction, defined as LVEF <50% at 1-year, and was observed in 27/48 patients (56.3%). Higher LV end-diastolic diameter at admission (odds ratio [OR] 1.22, 95% confidence interval [CI] 1.04–1.43, p = 0.002), non-fulminant presentation (OR 8.46, 95% CI 1.28–55.75, p = 0.013) and presence of a poor lymphocytic infiltrate (OR 12.40, 95% CI 1.23–124.97, p = 0.010) emerged as independent predictors of persistent LV dysfunction at multivariate analysis (area under the curve 0.91, 95% CI 0.82–0.99). Pre-discharge LVEF was lower in patients with persistent LV dysfunction compared to the others (32%±8 vs. 53%±8, p <0.001), and this single variable showed the best accuracy in predicting the study end-point (area under the curve 0.95, 95% CI 0.89–1.00). Conclusions More than half of patients presenting with acute LM and LVEF <50% who survive the acute phase show persistent LV dysfunction after 1-year from hospital discharge. Features of sub-acute inflammatory process and of established myocardial damage at initial hospitalization emerged as predictors of this end-point

Published
2019

30. Sex-related differences in chronic heart failure: a community-based study

Author

Russo, G, Rea, F, Barbati, G, Cherubini, A, Stellato, K, Scagnetto, A, Iorio, A, Corrao, G, Di Lenarda, A, Russo, Giulia, Rea, Federico, Barbati, Giulia, Cherubini, Antonella, Stellato, Kira, Scagnetto, Arjuna, Iorio, Annamaria, Corrao, Giovanni, Di Lenarda, Andrea, Russo, G, Rea, F, Barbati, G, Cherubini, A, Stellato, K, Scagnetto, A, Iorio, A, Corrao, G, Di Lenarda, A, Russo, Giulia, Rea, Federico, Barbati, Giulia, Cherubini, Antonella, Stellato, Kira, Scagnetto, Arjuna, Iorio, Annamaria, Corrao, Giovanni, and Di Lenarda, Andrea

Abstract

AIMS: To evaluate sex-related differences among real-life outpatients with chronic heart failure across the ejection fraction spectrum and to evaluate whether these differences might impact therapy and outcomes. METHODS: A total of 2528 heart failure patients were examined between 2009 and 2015 [mean age 76, 42% females; 59% with heart failure with preserved ejection fraction (HFpEF), 17% with heart failure with mid-range ejection fraction (HFmrEF) and 24% with heart failure with reduced ejection fraction (HFrEF)]. Females showed a higher prevalence of HFpEF than males. RESULTS: Females were older, less obese and with less ischaemic heart disease. They have renal failure and anaemia more frequently than males. There were no differences in terms of heart failure therapy in the HFrEF group, but a lower prescription rate of angiotensin-converting enzyme-I/AT1 blockers in HFmrEF and HFpEF and a higher prescription of mineralocorticoid receptor antagonists in the female group with HFpEF were observed. Crude rate mortality and composite outcome (death/heart failure progression) run similarly across sexes regardless of the ejection fraction categories. After adjustment, risk of mortality was significantly lower in females than males in the HFmrEF and HFpEF groups, whereas similar risk was confirmed across sexes in the HFrEF group. Considering prognostic risk factors, noncardiac comorbidities emerged in the HFpEF group. CONCLUSION: In a community-based heart failure cohort, females were differently distributed within heart failure phenotypes and they presented some different characteristics across ejection fraction categories. Although in an unadjusted model there was no significant difference for adverse outcomes, in an adjusted model females showed a lower risk of mortality in HFpEF and HFmrEF. Concerning sex-related prognostic risk factors, noncardiac comorbidities significantly affected adverse prognosis in females with HFpEF.

Published
2021

39. Prevalence and prognostic impact of non-cardiac co-morbidities in heart failure outpatients with preserved and reduced ejection fraction: a community-based study

Author

Iorio, A, Senni, M, Barbati, G, Greene, S, Poli, S, Zambon, E, Di Nora, C, Cioffi, G, Tarantini, L, Gavazzi, A, Sinagra, G, Di Lenarda, A, Iorio A, Senni M, Barbati G, Greene SJ, Poli S, Zambon E, Di Nora C, Cioffi G, Tarantini L, Gavazzi A, Sinagra G, Di Lenarda A, Iorio, A, Senni, M, Barbati, G, Greene, S, Poli, S, Zambon, E, Di Nora, C, Cioffi, G, Tarantini, L, Gavazzi, A, Sinagra, G, Di Lenarda, A, Iorio A, Senni M, Barbati G, Greene SJ, Poli S, Zambon E, Di Nora C, Cioffi G, Tarantini L, Gavazzi A, Sinagra G, and Di Lenarda A

Abstract

Aim: To assess adverse outcomes attributable to non-cardiac co-morbidities and to compare their effects by left ventricular ejection fraction (LVEF) group [LVEF <50% (heart failure with reduced ejection fraction, HFrEF), LVEF ≥50% (heart failure with preserved ejection fraction, HFpEF)] in a contemporary, unselected chronic heart failure population. Methods and results: This community-based cohort enrolled patients from October 2009 to December 2013. Adjusted hazard ratio (HR) and the population attributable fraction (PAF) were used to compare the contribution of 15 non-cardiac co-morbidities to adverse outcome. Overall, 2314 patients (mean age 77 ±10 years, 57% men) were recruited [n = 941 (41%) HFrEF, n = 1373 (59%) HFpEF]. Non-cardiac co-morbidity rates were similarly high, except for obesity and hypertension which were more prevalent in HFpEF. At a median follow-up of 31 (interquartile range 16–41) months, 472 (20%) patients died. Adjusted mortality rates were not significantly different between the HFrEF and HFpEF groups. After adjustment, an increasing number of non-cardiac co-morbidities was associated with a higher risk for all-cause mortality [HR 1.25; 95% confidence interval (CI) 1.10–1.26; P < 0.001], all-cause hospitalization (HR 1.17; 95% CI 1.12–1.23; P < 0.001), heart failure hospitalization (HR 1.28; 95% CI 1.19–1.38; P < 0.001), non-cardiovascular hospitalization (HR 1.16; 95% CI 1.11–1.22; P < 0.001). The co-morbidities contributing to high PAF were: anaemia, chronic kidney disease, chronic obstructive pulmonary disease, diabetes mellitus, and peripheral artery disease. These findings were similar for HFrEF and HFpEF. Interaction analysis yielded similar results. Conclusions: In a contemporary community population with chronic heart failure, non-cardiac co-morbidities confer a similar contribution to outcomes in HFrEF and HFpEF. These observations suggest that quality improvement initiatives aimed at optimizing co-morbidities may be

Published
2018

42. Impact on clinical outcomes of right ventricular response to percutaneous correction of secondary mitral regurgitation

Author

Caiffa, T, primary, Castrichini, M, additional, Biagini, E, additional, De Luca, A, additional, Compagnone, M, additional, Berardini, A, additional, Merlo, M, additional, Fabris, E, additional, Vitrella, G, additional, Pinamonti, B, additional, Korcova, R, additional, Barbati, G, additional, Saia, F, additional, Stolfo, D, additional, and Sinagra, G, additional

Published
2021
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