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5. Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

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Judge, PK, Staplin, N, Mayne, KJ, Wanner, C, Green, JB, Hauske, SJ, Emberson, JR, Preiss, D, Ng, SYA, Roddick, AJ, Sammons, E, Zhu, D, Hill, M, Stevens, W, Wallendszus, K, Brenner, S, Cheung, AK, Liu, ZH, Li, J, Hooi, LS, Liu, WJ, Kadowaki, T, Nangaku, M, Levin, A, Cherney, D, Maggioni, AP, Pontremoli, R, Deo, R, Goto, S, Rossello, X, Tuttle, KR, Steubl, D, Massey, D, Landray, MJ, Baigent, C, Haynes, R, Herrington, WG, Abat, S, Abd Rahman, R, Abdul Cader, R, Abdul Hafidz, MI, Abdul Wahab, MZ, Abdullah, NK, Abdul-Samad, T, Abe, M, Abraham, N, Acheampong, S, Achiri, P, Acosta, JA, Adeleke, A, Adell, V, Adewuyi-Dalton, R, Adnan, N, Africano, A, Agharazii, M, Aguilar, F, Aguilera, A, Ahmad, M, Ahmad, MK, Ahmad, NA, Ahmad, NH, Ahmad, NI, Ahmad Miswan, N, Ahmad Rosdi, H, Ahmed, I, Ahmed, S, Aiello, J, Aitken, A, AitSadi, R, Aker, S, Akimoto, S, Akinfolarin, A, Akram, S, Alberici, F, Albert, C, Aldrich, L, Alegata, M, Alexander, L, Alfaress, S, Alhadj Ali, M, Ali, A, Alicic, R, Aliu, A, Almaraz, R, Almasarwah, R, Almeida, J, Aloisi, A, Al-Rabadi, L, Alscher, D, Alvarez, P, Al-Zeer, B, Amat, M, Ambrose, C, Ammar, H, An, Y, Andriaccio, L, Ansu, K, Apostolidi, A, Arai, N, Araki, H, Araki, S, Arbi, A, Arechiga, O, Armstrong, S, Arnold, T, Aronoff, S, Arriaga, W, Arroyo, J, Arteaga, D, Asahara, S, Asai, A, Asai, N, Asano, S, Asawa, M, Asmee, MF, Aucella, F, Augustin, M, Avery, A, Awad, A, Awang, IY, Awazawa, M, Axler, A, Ayub, W, Azhari, Z, Baccaro, R, Badin, C, Bagwell, B, Bahlmann-Kroll, E, Bahtar, AZ, Bains, D, Bajaj, H, Baker, R, Baldini, E, Banas, B, Banerjee, D, Banno, S, Bansal, S, Barberi, S, Barnes, S, Barnini, C, Barot, C, Barrett, K, Barrios, R, Bartolomei Mecatti, B, Barton, I, Barton, J, Basily, W, Bavanandan, S, Baxter, A, Becker, L, Beddhu, S, Beige, J, Beigh, S, Bell, S, Benck, U, Beneat, A, Bennett, A, Bennett, D, Benyon, S, Berdeprado, J, Bergler, T, Bergner, A, Berry, M, Bevilacqua, M, Bhairoo, J, Bhandari, S, Bhandary, N, Bhatt, A, Bhattarai, M, Bhavsar, M, Bian, W, Bianchini, F, Bianco, S, Bilous, R, Bilton, J, Bilucaglia, D, Bird, C, Birudaraju, D, Biscoveanu, M, Blake, C, Bleakley, N, Bocchicchia, K, Bodine, S, Bodington, R, Boedecker, S, Bolduc, M, Bolton, S, Bond, C, Boreky, F, Boren, K, Bouchi, R, Bough, L, Bovan, D, Bowler, C, Bowman, L, Brar, N, Braun, C, Breach, A, Breitenfeldt, M, Brettschneider, B, Brewer, A, Brewer, G, Brindle, V, Brioni, E, Brown, C, Brown, H, Brown, L, Brown, R, Brown, S, Browne, D, Bruce, K, Brueckmann, M, Brunskill, N, Bryant, M, Brzoska, M, Bu, Y, Buckman, C, Budoff, M, Bullen, M, Burke, A, Burnette, S, Burston, C, Busch, M, Bushnell, J, Butler, S, Büttner, C, Byrne, C, Caamano, A, Cadorna, J, Cafiero, C, Cagle, M, Cai, J, Calabrese, K, Calvi, C, Camilleri, B, Camp, S, Campbell, D, Campbell, R, Cao, H, Capelli, I, Caple, M, Caplin, B, Cardone, A, Carle, J, Carnall, V, Caroppo, M, Carr, S, Carraro, G, Carson, M, Casares, P, Castillo, C, Castro, C, Caudill, B, Cejka, V, Ceseri, M, Cham, L, Chamberlain, A, Chambers, J, Chan, CBT, Chan, JYM, Chan, YC, Chang, E, Chant, T, Chavagnon, T, Chellamuthu, P, Chen, F, Chen, J, Chen, P, Chen, TM, Chen, Y, Cheng, C, Cheng, H, Cheng, MC, Ching, CH, Chitalia, N, Choksi, R, Chukwu, C, Chung, K, Cianciolo, G, Cipressa, L, Clark, S, Clarke, H, Clarke, R, Clarke, S, Cleveland, B, Cole, E, Coles, H, Condurache, L, Connor, A, Convery, K, Cooper, A, Cooper, N, Cooper, Z, Cooperman, L, Cosgrove, L, Coutts, P, Cowley, A, Craik, R, Cui, G, Cummins, T, Dahl, N, Dai, H, Dajani, L, D'Amelio, A, Damian, E, Damianik, K, Danel, L, Daniels, C, Daniels, T, Darbeau, S, Darius, H, Dasgupta, T, Davies, J, Davies, L, Davis, A, Davis, J, Davis, L, Dayanandan, R, Dayi, S, Dayrell, R, De Nicola, L, Debnath, S, Deeb, W, Degenhardt, S, DeGoursey, K, Delaney, M, DeRaad, R, Derebail, V, Dev, D, Devaux, M, Dhall, P, Dhillon, G, Dienes, J, Dobre, M, Doctolero, E, Dodds, V, Domingo, D, Donaldson, D, Donaldson, P, Donhauser, C, Donley, V, Dorestin, S, Dorey, S, Doulton, T, Draganova, D, Draxlbauer, K, Driver, F, Du, H, Dube, F, Duck, T, Dugal, T, Dugas, J, Dukka, H, Dumann, H, Durham, W, Dursch, M, Dykas, R, Easow, R, Eckrich, E, Eden, G, Edmerson, E, Edwards, H, Ee, LW, Eguchi, J, Ehrl, Y, Eichstadt, K, Eid, W, Eilerman, B, Ejima, Y, Eldon, H, Ellam, T, Elliott, L, Ellison, R, Emberson, J, Epp, R, Er, A, Espino-Obrero, M, Estcourt, S, Estienne, L, Evans, G, Evans, J, Evans, S, Fabbri, G, Fajardo-Moser, M, Falcone, C, Fani, F, Faria-Shayler, P, Farnia, F, Farrugia, D, Fechter, M, Fellowes, D, Feng, F, Fernandez, J, Ferraro, P, Field, A, Fikry, S, Finch, J, Finn, H, Fioretto, P, Fish, R, Fleischer, A, Fleming-Brown, D, Fletcher, L, Flora, R, Foellinger, C, Foligno, N, Forest, S, Forghani, Z, Forsyth, K, Fottrell-Gould, D, Fox, P, Frankel, A, Fraser, D, Frazier, R, Frederick, K, Freking, N, French, H, Froment, A, Fuchs, B, Fuessl, L, Fujii, H, Fujimoto, A, Fujita, A, Fujita, K, Fujita, Y, Fukagawa, M, Fukao, Y, Fukasawa, A, Fuller, T, Funayama, T, Fung, E, Furukawa, M, Furukawa, Y, Furusho, M, Gabel, S, Gaidu, J, Gaiser, S, Gallo, K, Galloway, C, Gambaro, G, Gan, CC, Gangemi, C, Gao, M, Garcia, K, Garcia, M, Garofalo, C, Garrity, M, Garza, A, Gasko, S, Gavrila, M, Gebeyehu, B, Geddes, A, Gentile, G, George, A, George, J, Gesualdo, L, Ghalli, F, Ghanem, A, Ghate, T, Ghavampour, S, Ghazi, A, Gherman, A, Giebeln-Hudnell, U, Gill, B, Gillham, S, Girakossyan, I, Girndt, M, Giuffrida, A, Glenwright, M, Glider, T, Gloria, R, Glowski, D, Goh, BL, Goh, CB, Gohda, T, Goldenberg, R, Goldfaden, R, Goldsmith, C, Golson, B, Gonce, V, Gong, Q, Goodenough, B, Goodwin, N, Goonasekera, M, Gordon, A, Gordon, J, Gore, A, Goto, H, Gowen, D, Grace, A, Graham, J, Grandaliano, G, Gray, M, Greene, T, Greenwood, G, Grewal, B, Grifa, R, Griffin, D, Griffin, S, Grimmer, P, Grobovaite, E, Grotjahn, S, Guerini, A, Guest, C, Gunda, S, Guo, B, Guo, Q, Haack, S, Haase, M, Haaser, K, Habuki, K, Hadley, A, Hagan, S, Hagge, S, Haller, H, Ham, S, Hamal, S, Hamamoto, Y, Hamano, N, Hamm, M, Hanburry, A, Haneda, M, Hanf, C, Hanif, W, Hansen, J, Hanson, L, Hantel, S, Haraguchi, T, Harding, E, Harding, T, Hardy, C, Hartner, C, Harun, Z, Harvill, L, Hasan, A, Hase, H, Hasegawa, F, Hasegawa, T, Hashimoto, A, Hashimoto, C, Hashimoto, M, Hashimoto, S, Haskett, S, Hawfield, A, Hayami, T, Hayashi, M, Hayashi, S, Hazara, A, Healy, C, Hecktman, J, Heine, G, Henderson, H, Henschel, R, Hepditch, A, Herfurth, K, Hernandez, G, Hernandez Pena, A, Hernandez-Cassis, C, Herzog, C, Hewins, S, Hewitt, D, Hichkad, L, Higashi, S, Higuchi, C, Hill, C, Hill, L, Himeno, T, Hing, A, Hirakawa, Y, Hirata, K, Hirota, Y, Hisatake, T, Hitchcock, S, Hodakowski, A, Hodge, W, Hogan, R, Hohenstatt, U, Hohenstein, B, Hooi, L, Hope, S, Hopley, M, Horikawa, S, Hosein, D, Hosooka, T, Hou, L, Hou, W, Howie, L, Howson, A, Hozak, M, Htet, Z, Hu, X, Hu, Y, Huang, J, Huda, N, Hudig, L, Hudson, A, Hugo, C, Hull, R, Hume, L, Hundei, W, Hunt, N, Hunter, A, Hurley, S, Hurst, A, Hutchinson, C, Hyo, T, Ibrahim, FH, Ibrahim, S, Ihana, N, Ikeda, T, Imai, A, Imamine, R, Inamori, A, Inazawa, H, Ingell, J, Inomata, K, Inukai, Y, Ioka, M, Irtiza-Ali, A, Isakova, T, Isari, W, Iselt, M, Ishiguro, A, Ishihara, K, Ishikawa, T, Ishimoto, T, Ishizuka, K, Ismail, R, Itano, S, Ito, H, Ito, K, Ito, M, Ito, Y, Iwagaitsu, S, Iwaita, Y, Iwakura, T, Iwamoto, M, Iwasa, M, Iwasaki, H, Iwasaki, S, Izumi, K, Izumi, T, Jaafar, SM, Jackson, C, Jackson, Y, Jafari, G, Jahangiriesmaili, M, Jain, N, Jansson, K, Jasim, H, Jeffers, L, Jenkins, A, Jesky, M, Jesus-Silva, J, Jeyarajah, D, Jiang, Y, Jiao, X, Jimenez, G, Jin, B, Jin, Q, Jochims, J, Johns, B, Johnson, C, Johnson, T, Jolly, S, Jones, L, Jones, S, Jones, T, Jones, V, Joseph, M, Joshi, S, Judge, P, Junejo, N, Junus, S, Kachele, M, Kadoya, H, Kaga, H, Kai, H, Kajio, H, Kaluza-Schilling, W, Kamaruzaman, L, Kamarzarian, A, Kamimura, Y, Kamiya, H, Kamundi, C, Kan, T, Kanaguchi, Y, Kanazawa, A, Kanda, E, Kanegae, S, Kaneko, K, Kang, HY, Kano, T, Karim, M, Karounos, D, Karsan, W, Kasagi, R, Kashihara, N, Katagiri, H, Katanosaka, A, Katayama, A, Katayama, M, Katiman, E, Kato, K, Kato, M, Kato, N, Kato, S, Kato, T, Kato, Y, Katsuda, Y, Katsuno, T, Kaufeld, J, Kavak, Y, Kawai, I, Kawai, M, Kawase, A, Kawashima, S, Kazory, A, Kearney, J, Keith, B, Kellett, J, Kelley, S, Kershaw, M, Ketteler, M, Khai, Q, Khairullah, Q, Khandwala, H, Khoo, KKL, Khwaja, A, Kidokoro, K, Kielstein, J, Kihara, M, Kimber, C, Kimura, S, Kinashi, H, Kingston, H, Kinomura, M, Kinsella-Perks, E, Kitagawa, M, Kitajima, M, Kitamura, S, Kiyosue, A, Kiyota, M, Klauser, F, Klausmann, G, Kmietschak, W, Knapp, K, Knight, C, Knoppe, A, Knott, C, Kobayashi, M, Kobayashi, R, Kobayashi, T, Koch, M, Kodama, S, Kodani, N, Kogure, E, Koizumi, M, Kojima, H, Kojo, T, Kolhe, N, Komaba, H, Komiya, T, Komori, H, Kon, SP, Kondo, M, Kong, W, Konishi, M, Kono, K, Koshino, M, Kosugi, T, Kothapalli, B, Kozlowski, T, Kraemer, B, Kraemer-Guth, A, Krappe, J, Kraus, D, Kriatselis, C, Krieger, C, Krish, P, Kruger, B, Ku Md Razi, KR, Kuan, Y, Kubota, S, Kuhn, S, Kumar, P, Kume, S, Kummer, I, Kumuji, R, Küpper, A, Kuramae, T, Kurian, L, Kuribayashi, C, Kurien, R, Kuroda, E, Kurose, T, Kutschat, A, Kuwabara, N, Kuwata, H, La Manna, G, Lacey, M, Lafferty, K, LaFleur, P, Lai, V, Laity, E, Lambert, A, Langlois, M, Latif, F, Latore, E, Laundy, E, Laurienti, D, Lawson, A, Lay, M, Leal, I, Lee, AK, Lee, J, Lee, KQ, Lee, R, Lee, SA, Lee, YY, Lee-Barkey, Y, Leonard, N, Leoncini, G, Leong, CM, Lerario, S, Leslie, A, Lewington, A, Li, N, Li, X, Li, Y, Liberti, L, Liberti, ME, Liew, A, Liew, YF, Lilavivat, U, Lim, SK, Lim, YS, Limon, E, Lin, H, Lioudaki, E, Liu, H, Liu, J, Liu, L, Liu, Q, Liu, X, Liu, Z, Loader, D, Lochhead, H, Loh, CL, Lorimer, A, Loudermilk, L, Loutan, J, Low, CK, Low, CL, Low, YM, Lozon, Z, Lu, Y, Lucci, D, Ludwig, U, Luker, N, Lund, D, Lustig, R, Lyle, S, Macdonald, C, MacDougall, I, Machicado, R, MacLean, D, Macleod, P, Madera, A, Madore, F, Maeda, K, Maegawa, H, Maeno, S, Mafham, M, Magee, J, Mah, DY, Mahabadi, V, Maiguma, M, Makita, Y, Makos, G, Manco, L, Mangiacapra, R, Manley, J, Mann, P, Mano, S, Marcotte, G, Maris, J, Mark, P, Markau, S, Markovic, M, Marshall, C, Martin, M, Martinez, C, Martinez, S, Martins, G, Maruyama, K, Maruyama, S, Marx, K, Maselli, A, Masengu, A, Maskill, A, Masumoto, S, Masutani, K, Matsumoto, M, Matsunaga, T, Matsuoka, N, Matsushita, M, Matthews, M, Matthias, S, Matvienko, E, Maurer, M, Maxwell, P, Mazlan, N, Mazlan, SA, Mbuyisa, A, McCafferty, K, McCarroll, F, McCarthy, T, McClary-Wright, C, McCray, K, McDermott, P, McDonald, C, McDougall, R, McHaffie, E, McIntosh, K, McKinley, T, McLaughlin, S, McLean, N, McNeil, L, Measor, A, Meek, J, Mehta, A, Mehta, R, Melandri, M, Mené, P, Meng, T, Menne, J, Merritt, K, Merscher, S, Meshykhi, C, Messa, P, Messinger, L, Miftari, N, Miller, R, Miller, Y, Miller-Hodges, E, Minatoguchi, M, Miners, M, Minutolo, R, Mita, T, Miura, Y, Miyaji, M, Miyamoto, S, Miyatsuka, T, Miyazaki, M, Miyazawa, I, Mizumachi, R, Mizuno, M, Moffat, S, Mohamad Nor, FS, Mohamad Zaini, SN, Mohamed Affandi, FA, Mohandas, C, Mohd, R, Mohd Fauzi, NA, Mohd Sharif, NH, Mohd Yusoff, Y, Moist, L, Moncada, A, Montasser, M, Moon, A, Moran, C, Morgan, N, Moriarty, J, Morig, G, Morinaga, H, Morino, K, Morisaki, T, Morishita, Y, Morlok, S, Morris, A, Morris, F, Mostafa, S, Mostefai, Y, Motegi, M, Motherwell, N, Motta, D, Mottl, A, Moys, R, Mozaffari, S, Muir, J, Mulhern, J, Mulligan, S, Munakata, Y, Murakami, C, Murakoshi, M, Murawska, A, Murphy, K, Murphy, L, Murray, S, Murtagh, H, Musa, MA, Mushahar, L, Mustafa, R, Mustafar, R, Muto, M, Nadar, E, Nagano, R, Nagasawa, T, Nagashima, E, Nagasu, H, Nagelberg, S, Nair, H, Nakagawa, Y, Nakahara, M, Nakamura, J, Nakamura, R, Nakamura, T, Nakaoka, M, Nakashima, E, Nakata, J, Nakata, M, Nakatani, S, Nakatsuka, A, Nakayama, Y, Nakhoul, G, Naverrete, G, Navivala, A, Nazeer, I, Negrea, L, Nethaji, C, Newman, E, Ng, TJ, Ngu, LLS, Nimbkar, T, Nishi, H, Nishi, M, Nishi, S, Nishida, Y, Nishiyama, A, Niu, J, Niu, P, Nobili, G, Nohara, N, Nojima, I, Nolan, J, Nosseir, H, Nozawa, M, Nunn, M, Nunokawa, S, Oda, M, Oe, M, Oe, Y, Ogane, K, Ogawa, W, Ogihara, T, Oguchi, G, Ohsugi, M, Oishi, K, Okada, Y, Okajyo, J, Okamoto, S, Okamura, K, Olufuwa, O, Oluyombo, R, Omata, A, Omori, Y, Ong, LM, Ong, YC, Onyema, J, Oomatia, A, Oommen, A, Oremus, R, Orimo, Y, Ortalda, V, Osaki, Y, Osawa, Y, Osmond Foster, J, O'Sullivan, A, Otani, T, Othman, N, Otomo, S, O'Toole, J, Owen, L, Ozawa, T, Padiyar, A, Page, N, Pajak, S, Paliege, A, Pandey, A, Pandey, R, Pariani, H, Park, J, Parrigon, M, Passauer, J, Patecki, M, Patel, M, Patel, R, Patel, T, Patel, Z, Paul, R, Paulsen, L, Pavone, L, Peixoto, A, Peji, J, Peng, BC, Peng, K, Pennino, L, Pereira, E, Perez, E, Pergola, P, Pesce, F, Pessolano, G, Petchey, W, Petr, EJ, Pfab, T, Phelan, P, Phillips, R, Phillips, T, Phipps, M, Piccinni, G, Pickett, T, Pickworth, S, Piemontese, M, Pinto, D, Piper, J, Plummer-Morgan, J, Poehler, D, Polese, L, Poma, V, Postal, A, Pötz, C, Power, A, Pradhan, N, Pradhan, R, Preiss, E, Preston, K, Prib, N, Price, L, Provenzano, C, Pugay, C, Pulido, R, Putz, F, Qiao, Y, Quartagno, R, Quashie-Akponeware, M, Rabara, R, Rabasa-Lhoret, R, Radhakrishnan, D, Radley, M, Raff, R, Raguwaran, S, Rahbari-Oskoui, F, Rahman, M, Rahmat, K, Ramadoss, S, Ramanaidu, S, Ramasamy, S, Ramli, R, Ramli, S, Ramsey, T, Rankin, A, Rashidi, A, Raymond, L, Razali, WAFA, Read, K, Reiner, H, Reisler, A, Reith, C, Renner, J, Rettenmaier, B, Richmond, L, Rijos, D, Rivera, R, Rivers, V, Robinson, H, Rocco, M, Rodriguez-Bachiller, I, Rodriquez, R, Roesch, C, Roesch, J, Rogers, J, Rohnstock, M, Rolfsmeier, S, Roman, M, Romo, A, Rosati, A, Rosenberg, S, Ross, T, Roura, M, Roussel, M, Rovner, S, Roy, S, Rucker, S, Rump, L, Ruocco, M, Ruse, S, Russo, F, Russo, M, Ryder, M, Sabarai, A, Saccà, C, Sachson, R, Sadler, E, Safiee, NS, Sahani, M, Saillant, A, Saini, J, Saito, C, Saito, S, Sakaguchi, K, Sakai, M, Salim, H, Salviani, C, Sampson, A, Samson, F, Sandercock, P, Sanguila, S, Santorelli, G, Santoro, D, Sarabu, N, Saram, T, Sardell, R, Sasajima, H, Sasaki, T, Satko, S, Sato, A, Sato, D, Sato, H, Sato, J, Sato, T, Sato, Y, Satoh, M, Sawada, K, Schanz, M, Scheidemantel, F, Schemmelmann, M, Schettler, E, Schettler, V, Schlieper, GR, Schmidt, C, Schmidt, G, Schmidt, U, Schmidt-Gurtler, H, Schmude, M, Schneider, A, Schneider, I, Schneider-Danwitz, C, Schomig, M, Schramm, T, Schreiber, A, Schricker, S, Schroppel, B, Schulte-Kemna, L, Schulz, E, Schumacher, B, Schuster, A, Schwab, A, Scolari, F, Scott, A, Seeger, W, Segal, M, Seifert, L, Seifert, M, Sekiya, M, Sellars, R, Seman, MR, Shah, S, Shainberg, L, Shanmuganathan, M, Shao, F, Sharma, K, Sharpe, C, Sheikh-Ali, M, Sheldon, J, Shenton, C, Shepherd, A, Shepperd, M, Sheridan, R, Sheriff, Z, Shibata, Y, Shigehara, T, Shikata, K, Shimamura, K, Shimano, H, Shimizu, Y, Shimoda, H, Shin, K, Shivashankar, G, Shojima, N, Silva, R, Sim, CSB, Simmons, K, Sinha, S, Sitter, T, Sivanandam, S, Skipper, M, Sloan, K, Sloan, L, Smith, R, Smyth, J, Sobande, T, Sobata, M, Somalanka, S, Song, X, Sonntag, F, Sood, B, Sor, SY, Soufer, J, Sparks, H, Spatoliatore, G, Spinola, T, Squyres, S, Srivastava, A, Stanfield, J, Staylor, K, Steele, A, Steen, O, Steffl, D, Stegbauer, J, Stellbrink, C, Stellbrink, E, Stevenson, A, Stewart-Ray, V, Stickley, J, Stoffler, D, Stratmann, B, Streitenberger, S, Strutz, F, Stubbs, J, Stumpf, J, Suazo, N, Suchinda, P, Suckling, R, Sudin, A, Sugamori, K, Sugawara, H, Sugawara, K, Sugimoto, D, Sugiyama, H, Sugiyama, T, Sullivan, M, Sumi, M, Suresh, N, Sutton, D, Suzuki, H, Suzuki, R, Suzuki, Y, Swanson, E, Swift, P, Syed, S, Szerlip, H, Taal, M, Taddeo, M, Tailor, C, Tajima, K, Takagi, M, Takahashi, K, Takahashi, M, Takahashi, T, Takahira, E, Takai, T, Takaoka, M, Takeoka, J, Takesada, A, Takezawa, M, Talbot, M, Taliercio, J, Talsania, T, Tamori, Y, Tamura, R, Tamura, Y, Tan, CHH, Tan, EZZ, Tanabe, A, Tanabe, K, Tanaka, A, Tanaka, N, Tang, S, Tang, Z, Tanigaki, K, Tarlac, M, Tatsuzawa, A, Tay, JF, Tay, LL, Taylor, J, Taylor, K, Te, A, Tenbusch, L, Teng, KS, Terakawa, A, Terry, J, Tham, ZD, Tholl, S, Thomas, G, Thong, KM, Tietjen, D, Timadjer, A, Tindall, H, Tipper, S, Tobin, K, Toda, N, Tokuyama, A, Tolibas, M, Tomita, A, Tomita, T, Tomlinson, J, Tonks, L, Topf, J, Topping, S, Torp, A, Torres, A, Totaro, F, Toth, P, Toyonaga, Y, Tripodi, F, Trivedi, K, Tropman, E, Tschope, D, Tse, J, Tsuji, K, Tsunekawa, S, Tsunoda, R, Tucky, B, Tufail, S, Tuffaha, A, Turan, E, Turner, H, Turner, J, Turner, M, Tye, YL, Tyler, A, Tyler, J, Uchi, H, Uchida, H, Uchida, T, Udagawa, T, Ueda, S, Ueda, Y, Ueki, K, Ugni, S, Ugwu, E, Umeno, R, Unekawa, C, Uozumi, K, Urquia, K, Valleteau, A, Valletta, C, van Erp, R, Vanhoy, C, Varad, V, Varma, R, Varughese, A, Vasquez, P, Vasseur, A, Veelken, R, Velagapudi, C, Verdel, K, Vettoretti, S, Vezzoli, G, Vielhauer, V, Viera, R, Vilar, E, Villaruel, S, 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2024
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6. Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

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Staplin, N, Haynes, R, Judge, PK, Wanner, C, Green, JB, Emberson, J, Preiss, D, Mayne, KJ, Ng, SYA, Sammons, E, Zhu, D, Hill, M, Stevens, W, Wallendszus, K, Brenner, S, Cheung, AK, Liu, ZH, Li, J, Hooi, LS, Liu, WJ, Kadowaki, T, Nangaku, M, Levin, A, Cherney, D, Maggioni, AP, Pontremoli, R, Deo, R, Goto, S, Rossello, X, Tuttle, KR, Steubl, D, Petrini, M, Seidi, S, Landray, MJ, Baigent, C, Herrington, WG, Abat, S, Abd Rahman, R, Abdul Cader, R, Abdul Hafidz, MI, Abdul Wahab, MZ, Abdullah, NK, Abdul-Samad, T, Abe, M, Abraham, N, Acheampong, S, Achiri, P, Acosta, JA, Adeleke, A, Adell, V, Adewuyi-Dalton, R, Adnan, N, Africano, A, Agharazii, M, Aguilar, F, Aguilera, A, Ahmad, M, Ahmad, MK, Ahmad, NA, Ahmad, NH, Ahmad, NI, Ahmad Miswan, N, Ahmad Rosdi, H, Ahmed, I, Ahmed, S, Aiello, J, Aitken, A, AitSadi, R, Aker, S, Akimoto, S, Akinfolarin, A, Akram, S, Alberici, F, Albert, C, Aldrich, L, Alegata, M, Alexander, L, Alfaress, S, Alhadj Ali, M, Ali, A, Alicic, R, Aliu, A, Almaraz, R, 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Miyazawa, I, Mizumachi, R, Mizuno, M, Moffat, S, Mohamad Nor, FS, Mohamad Zaini, SN, Mohamed Affandi, FA, Mohandas, C, Mohd, R, Mohd Fauzi, NA, Mohd Sharif, NH, Mohd Yusoff, Y, Moist, L, Moncada, A, Montasser, M, Moon, A, Moran, C, Morgan, N, Moriarty, J, Morig, G, Morinaga, H, Morino, K, Morisaki, T, Morishita, Y, Morlok, S, Morris, A, Morris, F, Mostafa, S, Mostefai, Y, Motegi, M, Motherwell, N, Motta, D, Mottl, A, Moys, R, Mozaffari, S, Muir, J, Mulhern, J, Mulligan, S, Munakata, Y, Murakami, C, Murakoshi, M, Murawska, A, Murphy, K, Murphy, L, Murray, S, Murtagh, H, Musa, MA, Mushahar, L, Mustafa, R, Mustafar, R, Muto, M, Nadar, E, Nagano, R, Nagasawa, T, Nagashima, E, Nagasu, H, Nagelberg, S, Nair, H, Nakagawa, Y, Nakahara, M, Nakamura, J, Nakamura, R, Nakamura, T, Nakaoka, M, Nakashima, E, Nakata, J, Nakata, M, Nakatani, S, Nakatsuka, A, Nakayama, Y, Nakhoul, G, Naverrete, G, Navivala, A, Nazeer, I, Negrea, L, Nethaji, C, Newman, E, Ng, TJ, Ngu, LLS, Nimbkar, T, Nishi, H, Nishi, M, Nishi, S, Nishida, Y, Nishiyama, A, Niu, J, Niu, P, Nobili, G, Nohara, N, Nojima, I, Nolan, J, Nosseir, H, Nozawa, M, Nunn, M, Nunokawa, S, Oda, M, Oe, M, Oe, Y, Ogane, K, Ogawa, W, Ogihara, T, Oguchi, G, Ohsugi, M, Oishi, K, Okada, Y, Okajyo, J, Okamoto, S, Okamura, K, Olufuwa, O, Oluyombo, R, Omata, A, Omori, Y, Ong, LM, Ong, YC, Onyema, J, Oomatia, A, Oommen, A, Oremus, R, Orimo, Y, Ortalda, V, Osaki, Y, Osawa, Y, Osmond Foster, J, O'Sullivan, A, Otani, T, Othman, N, Otomo, S, O'Toole, J, Owen, L, Ozawa, T, Padiyar, A, Page, N, Pajak, S, Paliege, A, Pandey, A, Pandey, R, Pariani, H, Park, J, Parrigon, M, Passauer, J, Patecki, M, Patel, M, Patel, R, Patel, T, Patel, Z, Paul, R, Paulsen, L, Pavone, L, Peixoto, A, Peji, J, Peng, BC, Peng, K, Pennino, L, Pereira, E, Perez, E, Pergola, P, Pesce, F, Pessolano, G, Petchey, W, Petr, EJ, Pfab, T, Phelan, P, Phillips, R, Phillips, T, Phipps, M, Piccinni, G, Pickett, T, Pickworth, S, Piemontese, M, Pinto, D, Piper, J, Plummer-Morgan, J, Poehler, D, Polese, L, Poma, V, Postal, A, Pötz, C, Power, A, Pradhan, N, Pradhan, R, Preiss, E, Preston, K, Prib, N, Price, L, Provenzano, C, Pugay, C, Pulido, R, Putz, F, Qiao, Y, Quartagno, R, Quashie-Akponeware, M, Rabara, R, Rabasa-Lhoret, R, Radhakrishnan, D, Radley, M, Raff, R, Raguwaran, S, Rahbari-Oskoui, F, Rahman, M, Rahmat, K, Ramadoss, S, Ramanaidu, S, Ramasamy, S, Ramli, R, Ramli, S, Ramsey, T, Rankin, A, Rashidi, A, Raymond, L, Razali, WAFA, Read, K, Reiner, H, Reisler, A, Reith, C, Renner, J, Rettenmaier, B, Richmond, L, Rijos, D, Rivera, R, Rivers, V, Robinson, H, Rocco, M, Rodriguez-Bachiller, I, Rodriquez, R, Roesch, C, Roesch, J, Rogers, J, Rohnstock, M, Rolfsmeier, S, Roman, M, Romo, A, Rosati, A, Rosenberg, S, Ross, T, Roura, M, Roussel, M, Rovner, S, Roy, S, Rucker, S, Rump, L, Ruocco, M, Ruse, S, Russo, F, Russo, M, Ryder, M, Sabarai, A, Saccà, C, Sachson, R, Sadler, E, Safiee, NS, Sahani, M, Saillant, A, Saini, J, Saito, C, Saito, S, Sakaguchi, K, Sakai, M, Salim, H, Salviani, C, Sampson, A, Samson, F, Sandercock, P, Sanguila, S, Santorelli, G, Santoro, D, Sarabu, N, Saram, T, Sardell, R, Sasajima, H, Sasaki, T, Satko, S, Sato, A, Sato, D, Sato, H, Sato, J, Sato, T, Sato, Y, Satoh, M, Sawada, K, Schanz, M, Scheidemantel, F, Schemmelmann, M, Schettler, E, Schettler, V, Schlieper, GR, Schmidt, C, Schmidt, G, Schmidt, U, Schmidt-Gurtler, H, Schmude, M, Schneider, A, Schneider, I, Schneider-Danwitz, C, Schomig, M, Schramm, T, Schreiber, A, Schricker, S, Schroppel, B, Schulte-Kemna, L, Schulz, E, Schumacher, B, Schuster, A, Schwab, A, Scolari, F, Scott, A, Seeger, W, Segal, M, Seifert, L, Seifert, M, Sekiya, M, Sellars, R, Seman, MR, Shah, S, Shainberg, L, Shanmuganathan, M, Shao, F, Sharma, K, Sharpe, C, Sheikh-Ali, M, Sheldon, J, Shenton, C, Shepherd, A, Shepperd, M, Sheridan, R, Sheriff, Z, Shibata, Y, Shigehara, T, Shikata, K, Shimamura, K, Shimano, H, Shimizu, Y, Shimoda, H, Shin, K, Shivashankar, G, Shojima, N, Silva, R, Sim, CSB, Simmons, K, Sinha, S, Sitter, T, Sivanandam, S, Skipper, M, Sloan, K, Sloan, L, Smith, R, Smyth, J, Sobande, T, Sobata, M, Somalanka, S, Song, X, Sonntag, F, Sood, B, Sor, SY, Soufer, J, Sparks, H, Spatoliatore, G, Spinola, T, Squyres, S, Srivastava, A, Stanfield, J, Staylor, K, Steele, A, Steen, O, Steffl, D, Stegbauer, J, Stellbrink, C, Stellbrink, E, Stevenson, A, Stewart-Ray, V, Stickley, J, Stoffler, D, Stratmann, B, Streitenberger, S, Strutz, F, Stubbs, J, Stumpf, J, Suazo, N, Suchinda, P, Suckling, R, Sudin, A, Sugamori, K, Sugawara, H, Sugawara, K, Sugimoto, D, Sugiyama, H, Sugiyama, T, Sullivan, M, Sumi, M, Suresh, N, Sutton, D, Suzuki, H, Suzuki, R, Suzuki, Y, Swanson, E, Swift, P, Syed, S, Szerlip, H, Taal, M, Taddeo, M, Tailor, C, Tajima, K, Takagi, M, Takahashi, K, Takahashi, M, Takahashi, T, Takahira, E, Takai, T, Takaoka, M, Takeoka, J, Takesada, A, Takezawa, M, Talbot, M, Taliercio, J, Talsania, T, Tamori, Y, Tamura, R, Tamura, Y, Tan, CHH, Tan, EZZ, Tanabe, A, Tanabe, K, Tanaka, A, Tanaka, N, Tang, S, Tang, Z, Tanigaki, K, Tarlac, M, Tatsuzawa, A, Tay, JF, Tay, LL, Taylor, J, Taylor, K, Te, A, Tenbusch, L, Teng, KS, Terakawa, A, Terry, J, Tham, ZD, Tholl, S, Thomas, G, Thong, KM, Tietjen, D, Timadjer, A, Tindall, H, Tipper, S, Tobin, K, Toda, N, Tokuyama, A, Tolibas, M, Tomita, A, Tomita, T, Tomlinson, J, Tonks, L, Topf, J, Topping, S, Torp, A, Torres, A, Totaro, F, Toth, P, Toyonaga, Y, Tripodi, F, Trivedi, K, Tropman, E, Tschope, D, Tse, J, Tsuji, K, Tsunekawa, S, Tsunoda, R, Tucky, B, Tufail, S, Tuffaha, A, Turan, E, Turner, H, Turner, J, Turner, M, Tye, YL, Tyler, A, Tyler, J, Uchi, H, Uchida, H, Uchida, T, Udagawa, T, Ueda, S, Ueda, Y, Ueki, K, Ugni, S, Ugwu, E, Umeno, R, Unekawa, C, Uozumi, K, Urquia, K, Valleteau, A, Valletta, C, van Erp, R, Vanhoy, C, Varad, V, Varma, R, Varughese, A, Vasquez, P, Vasseur, A, Veelken, R, Velagapudi, C, Verdel, K, Vettoretti, S, Vezzoli, G, Vielhauer, V, Viera, R, Vilar, E, Villaruel, S, Vinall, L, Vinathan, J, Visnjic, M, Voigt, E, von-Eynatten, M, Vourvou, M, Wada, J, Wada, T, Wada, Y, Wakayama, K, Wakita, Y, Walters, T, Wan Mohamad, WH, Wang, L, Wang, W, Wang, X, Wang, Y, Wanninayake, S, Watada, H, Watanabe, K, Watanabe, M, Waterfall, H, Watkins, D, Watson, S, Weaving, L, Weber, B, Webley, Y, Webster, A, Webster, M, Weetman, M, Wei, W, Weihprecht, H, Weiland, L, Weinmann-Menke, J, Weinreich, T, Wendt, R, Weng, Y, Whalen, M, Whalley, G, Wheatley, R, Wheeler, A, Wheeler, J, Whelton, P, White, K, Whitmore, B, Whittaker, S, Wiebel, J, Wiley, J, Wilkinson, L, Willett, M, Williams, A, Williams, E, Williams, K, Williams, T, Wilson, A, Wilson, P, Wincott, L, Wines, E, Winkelmann, B, Winkler, M, Winter-Goodwin, B, Witczak, J, Wittes, J, Wittmann, M, Wolf, G, Wolf, L, Wolfling, R, Wong, C, Wong, E, Wong, HS, Wong, LW, Wong, YH, Wonnacott, A, Wood, A, Wood, L, Woodhouse, H, Wooding, N, Woodman, A, Wren, K, Wu, J, Wu, P, Xia, S, Xiao, H, Xiao, X, Xie, Y, Xu, C, Xu, Y, Xue, H, Yahaya, H, Yalamanchili, H, Yamada, A, Yamada, N, Yamagata, K, Yamaguchi, M, Yamaji, Y, Yamamoto, A, Yamamoto, S, Yamamoto, T, Yamanaka, A, Yamano, T, Yamanouchi, Y, Yamasaki, N, Yamasaki, Y, Yamashita, C, Yamauchi, T, Yan, Q, Yanagisawa, E, Yang, F, Yang, L, Yano, S, Yao, S, Yao, Y, Yarlagadda, S, Yasuda, Y, Yiu, V, Yokoyama, T, Yoshida, S, Yoshidome, E, Yoshikawa, H, Young, A, Young, T, Yousif, V, Yu, H, Yu, Y, Yuasa, K, Yusof, N, Zalunardo, N, Zander, B, Zani, R, Zappulo, F, Zayed, M, Zemann, B, Zettergren, P, Zhang, H, Zhang, L, Zhang, N, Zhang, X, Zhao, J, Zhao, L, Zhao, S, Zhao, Z, Zhong, H, Zhou, N, Zhou, S, Zhu, L, Zhu, S, Zietz, M, Zippo, M, Zirino, F, and Zulkipli, FH

Published
2024
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20. COMPREHENSIVE REVIEW ON PLANT GROWTH PROMOTING RHIZOBACTERIA IN RELEVANCE TO ABIOTIC STRESS TOLERANCE OF PLANTS.

Author

ANITHA, R., DHANUSHKODI, V., SHANMUGANATHAN, M., KARUNAKARAN, V., NAGESWARI, R., SRITHARAN, N., BRINDAVATHY, R., and SASSIKUMAR, D.

Subjects
ABIOTIC stress, SUSTAINABLE agriculture, RHIZOBACTERIA, SYNTHETIC fertilizers, CROP growth, PLANT growth, PLANT hormones, CHELATING agents
Abstract

The rhizosphere represents an intricate microenvironment, consisting of a complex network involving soil, root and soil microbes. Conditions in the rhizosphere exert a direct influence on the growth and yield of crops. The unregulated and widespread application of synthetic fertilizers has emerged as a grave concern for the sustainability of agriculture and the equilibrium of ecosystems. These chemical substances accumulate within the soil, leach into water sources and release into the atmosphere, persisting for decades and posing a substantial threat to the overall ecosystem. This issue is of significant concern, necessitating a potential solution that can only be realized through the involvement of microorganisms and organic amendments. Plant growth promoting rhizobacteria (PGPR) has assumed a pivotal role in addressing this concern. The established role of microorganisms in enhancing plant growth, managing nutrients and exerting biocontrol is well-documented. PGPR, present in the rhizosphere, has the capacity to transform numerous nutrients that are initially inaccessible to plants into forms that can be readily utilized. Additionally, PGPR synthesize plant hormones, secondary metabolites, antibiotics, stressrelieving compounds, chelating agents, and signaling molecules, enabling interactions with both beneficial and pathogenic organisms within the rhizosphere. Moreover, PGPR is involved in the improvement of soil physical properties, chemical properties and overall functioning that offers direct or indirect benefits to crop growth. [ABSTRACT FROM AUTHOR]

Published
2024
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28. Acute changes in myocardial tissue characteristics during hospitalization in patients with COVID-19

Author

Shanmuganathan, M, Kotronias, RA, Burrage, MK, Ng, Y, Banerjee, A, Xie, C, Fletcher, A, Manley, P, Borlotti, A, Emfietzoglou, M, Mentzer, AJ, Marin, F, Raman, B, Tunnicliffe, EM, Neubauer, S, Piechnik, SK, Channon, KM, Ferreira, VM, and investigators, Oxford Acute Myocardial Infarction (OxAMI)

Abstract

Background: Patients with a history of COVID-19 infection are reported to have cardiac abnormalities on cardiovascular magnetic resonance (CMR) during convalescence. However, it is unclear whether these abnormalities were present during the acute COVID-19 illness and how they may evolve over time. Methods: We prospectively recruited unvaccinated patients hospitalized with acute COVID-19 (n = 23), and compared them with matched outpatient controls without COVID-19 (n = 19) between May 2020 and May 2021. Only those without a past history of cardiac disease were recruited. We performed in-hospital CMR at a median of 3 days (IQR 1–7 days) after admission, and assessed cardiac function, edema and necrosis/fibrosis, using left and right ventricular ejection fraction (LVEF, RVEF), T1-mapping, T2 signal intensity ratio (T2SI), late gadolinium enhancement (LGE) and extracellular volume (ECV). Acute COVID-19 patients were invited for follow-up CMR and blood tests at 6 months. Results: The two cohorts were well matched in baseline clinical characteristics. Both had normal LVEF (62 ± 7 vs. 65 ± 6%), RVEF (60 ± 6 vs. 58 ± 6%), ECV (31 ± 3 vs. 31 ± 4%), and similar frequency of LGE abnormalities (16 vs. 14%; all p > 0.05). However, measures of acute myocardial edema (T1 and T2SI) were significantly higher in patients with acute COVID-19 when compared to controls (T1 = 1,217 ± 41 ms vs. 1,183 ± 22 ms; p = 0.002; T2SI = 1.48 ± 0.36 vs. 1.13 ± 0.09; p Conclusion: Unvaccinated patients hospitalized for acute COVID-19 demonstrated CMR imaging evidence of acute myocardial edema, which normalized at 6 months, while biventricular function and scar burden were similar when compared to controls. Acute COVID-19 appears to induce acute myocardial edema in some patients, which resolves in convalescence, without significant impact on biventricular structure and function in the acute and short-term. Further studies with larger numbers are needed to confirm these findings.

Published
2023

31. Rapid neutrophil mobilization by VCAM-1+ endothelial cell-derived extracellular vesicles

Author

Akbar, N, Braithwaite, AT, Corr, EM, Koelwyn, GJ, van Solingen, C, Cochain, C, Saliba, A-E, Corbin, A, Pezzolla, D, Møller Jørgensen, M, Bæk, R, Edgar, L, De Villiers, C, Gunadasa-Rohling, M, Banerjee, A, Paget, D, Lee, C, Hogg, E, Costin, A, Dhaliwal, R, Johnson, E, Krausgruber, T, Riepsaame, J, Melling, GE, Shanmuganathan, M, Bock, C, Carter, DRF, Channon, KM, Riley, PR, Udalova, IA, Moore, KJ, Anthony, D, Choudhury, RP, and (OxAMI), Oxford Acute Myocardial Infarction Study

Subjects
Exosome, Myocardial infarction, Physiology, Physiology (medical), Programming, Cardiology and Cardiovascular Medicine, Spleen
Abstract

Aims Acute myocardial infarction rapidly increases blood neutrophils ( Methods and results Here, we show that injury to the myocardium rapidly mobilizes neutrophils from the spleen to peripheral blood and induces their transcriptional activation prior to arrival at the injured tissue. Time course analysis of plasma-EV composition revealed a rapid and selective increase in EVs bearing VCAM-1. These EVs, which were also enriched for miRNA-126, accumulated preferentially in the spleen where they induced local inflammatory gene and chemokine protein expression, and mobilized splenic-neutrophils to peripheral blood. Using CRISPR/Cas9 genome editing, we generated VCAM-1-deficient EC-EVs and showed that its deletion removed the ability of EC-EVs to provoke the mobilization of neutrophils. Furthermore, inhibition of miRNA-126 in vivo reduced myocardial infarction size in a mouse model. Conclusions Our findings show a novel EV-dependent mechanism for the rapid mobilization of neutrophils to peripheral blood from a splenic reserve and establish a proof of concept for functional manipulation of EV-communications through genetic alteration of parent cells.

Published
2023

32. Comparative and integrated analysis of plasma extracellular vesicle isolation methods in healthy volunteers and patients following myocardial infarction

Author

Paget, D, Checa, A, Zöhrer, B, Heilig, R, Shanmuganathan, M, Dhaliwal, R, Johnson, E, Jørgensen, MM, Bæk, R, Wheelock, CE, Channon, KM, Fischer, R, Anthony, DC, Choudhury, RP, Akbar, N, and (OxAMI), Oxford Acute Myocardial Infarction Study

Subjects
ultracentrifugation, acoustic trapping, immunoaffinity capture, size exclusion chromatography, human, precipitation, plasma, omics
Abstract

Plasma extracellular vesicle (EV) number and composition are altered following myocardial infarction (MI), but to properly understand the significance of these changes it is essential to appreciate how the different isolation methods affect EV characteristics, proteome and sphingolipidome. Here, we compared plasma EV isolated from platelet-poor plasma from four healthy donors and six MI patients at presentation and 1-month post-MI using ultracentrifugation (UC), polyethylene glycol precipitation, acoustic trapping, size-exclusion chromatography (SEC) and immunoaffinity capture. The isolated EV were evaluated by Nanoparticle Tracking Analysis (NTA), Western blot, transmission electron microscopy (TEM), an EV-protein array, untargeted proteomics (LC-MS/MS) and targeted sphingolipidomics (LC-MS/MS). The application of the five different plasma EV isolation methods in patients presenting with MI showed that the choice of plasma EV isolation method influenced the ability to distinguish elevations in plasma EV concentration following MI, enrichment of EV-cargo (EV-proteins and sphingolipidomics) and associations with the size of the infarct determined by cardiac magnetic resonance imaging 6 months post-MI. Despite the selection bias imposed by each method, a core of EV-associated proteins and lipids was detectable using all approaches. However, this study highlights how each isolation method comes with its own idiosyncrasies and makes the comparison of data acquired by different techniques in clinical studies problematic.

Published
2022

35. Artificial Intelligence for Contrast-Free MRI: Scar Assessment in Myocardial Infarction Using Deep Learning-Based Virtual Native Enhancement

Author

Zhang, Q, Burrage, MK, Shanmuganathan, M, Gonzales, RA, Lukaschuk, E, Thomas, KE, Mills, R, Leal Pelado, J, Nikolaidou, C, Popescu, IA, Lee, YP, Zhang, X, Dharmakumar, R, Myerson, SG, Rider, O, Channon, KM, Neubauer, S, Piechnik, SK, Ferreira, VM, and Study, Oxford Acute Myocardial Infarction (OxAMI)

Subjects
Cicatrix, Deep Learning, Swine, Artificial Intelligence, Physiology (medical), Myocardium, Myocardial Infarction, Animals, Contrast Media, Magnetic Resonance Imaging, Cine, Gadolinium, Cardiology and Cardiovascular Medicine, Magnetic Resonance Imaging
Abstract

Background: Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan without contrast-associated problems. Methods: Virtual native enhancement (VNE) is a novel technology that can produce virtual LGE-like images without the need for contrast. VNE combines cine imaging and native T1 maps to produce LGE-like images using artificial intelligence. VNE was developed for patients with previous myocardial infarction from 4271 data sets (912 patients); each data set comprises slice position-matched cine, T1 maps, and LGE images. After quality control, 3002 data sets (775 patients) were used for development and 291 data sets (68 patients) for testing. The VNE generator was trained using generative adversarial networks, using 2 adversarial discriminators to improve the image quality. The left ventricle was contoured semiautomatically. Myocardial scar volume was quantified using the full width at half maximum method. Scar transmurality was measured using the centerline chord method and visualized on bull’s-eye plots. Lesion quantification by VNE and LGE was compared using linear regression, Pearson correlation ( R ), and intraclass correlation coefficients. Proof-of-principle histopathologic comparison of VNE in a porcine model of myocardial infarction also was performed. Results: VNE provided significantly better image quality than LGE on blinded analysis by 5 independent operators on 291 data sets (all P R , 0.89; intraclass correlation coefficient, 0.94) and transmurality ( R , 0.84; intraclass correlation coefficient, 0.90) in 66 patients (277 test data sets). Two cardiovascular magnetic resonance experts reviewed all test image slices and reported an overall accuracy of 84% for VNE in detecting scars when compared with LGE, with specificity of 100% and sensitivity of 77%. VNE also showed excellent visuospatial agreement with histopathology in 2 cases of a porcine model of myocardial infarction. Conclusions: VNE demonstrated high agreement with LGE cardiovascular magnetic resonance for myocardial scar assessment in patients with previous myocardial infarction in visuospatial distribution and lesion quantification with superior image quality. VNE is a potentially transformative artificial intelligence–based technology with promise in reducing scan times and costs, increasing clinical throughput, and improving the accessibility of cardiovascular magnetic resonance in the near future.

Published
2022

38. TVnet: automated global analysis of tricuspid valve plane motion in CMR long-axis cines with residual neural networks for assessment of right ventricular function

Author

Gonzales, RA, Lamy, J, Thomas, KE, Zhang, Q, Shanmuganathan, M, Heiberg, E, Ferreira, VM, Piechnik, SK, and Peters, DC

Subjects
Radiology, Nuclear Medicine and imaging, General Medicine, Cardiology and Cardiovascular Medicine
Abstract

Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Clarendon Fund, John Fell Oxford University Press Research Fund, Oxford BHF Centre of Research Excellence (RE/18/3/34214), Alison Brading Memorial Graduate Scholarship in Medical Science, National Institute for Health Research Oxford Biomedical Research Centre, National Institutes of Health (R01HL144706). Background Right ventricular (RV) function evaluation is an integral part of comprehensive cardiac assessment, including for pulmonary hypertension, congenital heart disease and arrhythmogenic RV cardiomyopathy (ARVC) [1]. It is commonly assessed by measuring tricuspid annular plane systolic excursion (TAPSE) and peak systolic velocity (RV s’) on echocardiography [2]. However, it is highly sensitive to imaging window and small changes in the beam angle, limiting reliability [3]. Cardiovascular magnetic resonance (CMR) is the imaging gold-standard for assessing RV structure and function, and is highly reproducible. CMR can assess tricuspid valve (TV) motion using four-chamber (4Ch) and RV two-chamber (2Ch) cines, with high diagnostic performance when compared against single-plane analysis [4]. However, manual placement of the TV insertion points is highly time-consuming for routine clinical workflows. TVnet, a deep-learning framework for automatically tracking the TV in 4Ch cines [5] has been recently validated, but without the orthogonal plane (RV 2Ch) which is helpful to more reliably characterise TV motion. Purpose We further extend TVnet to automatically track RV 2Ch cines and derive analysis of global TV motion parameters (global TAPSE and RV s’) on par with expert level performance. Methods 74 patients undergoing CMR (1.5T Siemens MR scanner) with 4Ch and RV 2Ch views were retrospectively included in this ethically-approved study. The patients had the following cardiovascular conditions: myocardial infarction (n=43), ARVC (n=28) and Takotsubo cardiomyopathy (n=3). The dual-stage deep-learning pipeline with a residual neural network backbone [5, 6] (Figure 1A) was trained using 69 patient datasets and 15 patients were randomly chosen for testing. The TVnet trained on 4Ch cines [5] was used to automatically annotate the 4Ch cines of the testing set for global analysis comparison. For manual reference, the software Segment [7] was used to manually annotate the TV insertion points in all imaging data (1,865 RV 2Ch images, 375 4Ch images). The global TAPSE and RV s’ were derived as the mean perpendicular motion from the end-diastolic plane from both chamber views (Figure 1B). Results TVnet achieved a fast processing accuracy ( Conclusion TVnet demonstrated excellent performance in both tracking the TV insertion points in RV 2Ch cines and deriving global TAPSE and RV s’ compared to manual reference. TVnet can eventually provide a complete automatic inline analysis of TV plane motion for a fast, reliable and reproducible assessment of RV function in routine clinical workflows. (A) TVnet pipeline (B) Metric derivationCorrelation and Bland-Altman plots

Published
2022

39. Long-term prognosis after acute ST-segment elevation myocardial infarction is determined by characteristics in both non-infarcted and infarcted myocardium on cardiovascular magnetic resonance imaging

Author

Shanmuganathan, M, Masi, A, Burrage, MK, Kotronias, RA, Borlotti, A, Scarsini, R, Banerjee, A, Terentes-Printzios, D, Zhang, Q, Hann, E, Tunnicliffe, E, Lucking, A, Langrish, J, Kharbanda, R, de Maria, GL, Banning, AP, Choudhury, RP, Channon, KM, Piechnik, SK, Ferreira, VM, and investigators, Oxford Acute Myocardial Infarction (OxAMI) Study

Published
2022

43. Angiography-derived index of microcirculatory resistance as a novel, pressure-wire-free tool to assess coronary microcirculation in ST elevation myocardial infarction

Author

De Maria, GL, Scarsini, R, Shanmuganathan, M, Kotronias, RA, Terentes-Printzios, D, Borlotti, A, Langrish, JP, Lucking, AJ, Choudhury, RP, Kharbanda, R, Ferreira, VM, Investigators, Oxford Acute Myocardial Infarction (OXAMI) Study, Channon, KM, Garcia-Garcia, HM, and Banning, AP

Subjects
Male, Cardiac Catheterization, medicine.medical_specialty, medicine.medical_treatment, Coronary Artery Disease, Coronary microcirculation, Coronary Angiography, Cardiac Catheters, STEMI, Hyperaemia, Index of microcirculatory resistance, Predictive Value of Tests, St elevation myocardial infarction, Coronary Circulation, Internal medicine, Transducers, Pressure, medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Angioplasty, Balloon, Coronary, Cardiac imaging, Aged, Original Paper, medicine.diagnostic_test, business.industry, Microcirculation, Area under the curve, Reproducibility of Results, Percutaneous coronary intervention, Magnetic resonance imaging, Middle Aged, Microvascular obstruction, Coronary Vessels, Magnetic Resonance Imaging, Quantitative flow ratio, Microvascular dysfunction, Angiography, Cardiology, Radiographic Image Interpretation, Computer-Assisted, ST Elevation Myocardial Infarction, Female, Stents, Vascular Resistance, medicine.symptom, Cardiology and Cardiovascular Medicine, business, Blood Flow Velocity
Abstract

Immediate assessment of coronary microcirculation during treatment of ST elevation myocardial infarction (STEMI) may facilitate patient stratification for targeted treatment algorithms. Use of pressure-wire to measure the index of microcirculatory resistance (IMR) is possible but has inevitable practical restrictions. We aimed to develop and validate angiography-derived index of microcirculatory resistance (IMRangio) as a novel and pressure-wire-free index to facilitate assessment of the coronary microcirculation. 45 STEMI patients treated with primary percutaneous coronary intervention (pPCI) were enrolled. Immediately before stenting and at completion of pPCI, IMR was measured within the infarct related artery (IRA). At the same time points, 2 angiographic views were acquired during hyperaemia to measure quantitative flow ratio (QFR) from which IMRangio was derived. In a subset of 15 patients both IMR and IMRangio were also measured in the non-IRA. Patients underwent cardiovascular magnetic resonance imaging (CMR) at 48 h for assessment of microvascular obstruction (MVO). IMRangio and IMR were significantly correlated (ρ: 0.85, p 1.55% of left ventricular mass) (p = 0.03 and p = 0.005, respectively). Post-pPCI IMRangio presented and area under the curve (AUC) of 0.96 (CI95% 0.92–1.00, p 40U and of 0.81 (CI95% 0.65–0.97, p 1.55%. IMRangio is a promising tool for the assessment of coronary microcirculation. Assessment of IMR without the use of a pressure-wire may enable more rapid, convenient and cost-effective assessment of coronary microvascular function. Electronic supplementary material The online version of this article (10.1007/s10554-020-01831-7) contains supplementary material, which is available to authorized users.

Published
2020

46. Effects of Diet on the Microbiome and Serum Metabolome of South Asian Infants at 1 Year

Author

Sonia S. Anand, Sandi M. Azab, de Souza Rj, Shanmuganathan M, Bruce Cy, Jennifer C. Stearns, and Philip Britz-McKibbin

Subjects
Dimethylglycine, chemistry.chemical_compound, Methionine, chemistry, Metabolite, Cohort, Metabolome, Breastfeeding, Physiology, Microbiome, Biology, Cohort study
Abstract

Diet is known to affect the gut microbiome and metabolome composition in adults, but this has not been fully explored in infants. Dietary patterns from 1 year-old infants (n=182) from the South Asian Birth Cohort (START) study were compared to gut microbiome alpha and beta diversity and to taxa abundance differences. Diet – serum metabolite associations were identified using multivariate analysis (partial least squares-discriminant analysis, PLS-DA) and univariate analysis (T-Test). Dietary biomarkers identified from START were also examined in a separate cohort of white Caucasian infants (CHILD Cohort Study, n=82). Lastly, the association of diet with gut microbiome and serum biomarkers, considering maternal, perinatal and infant characteristics was investigated using multivariate forward stepwise regression. A dietary pattern characterized by breastfeeding, supplemented by formula and dairy was the strongest predictor of the gut microbiome that also differentiated the serum metabolome of infants. The formula and dairy dietary pattern was associated with a panel of circulating metabolites in both cohorts, including: S-methylcysteine, branched-chain/aromatic amino acids, lysine, dimethylglycine, and methionine. Breastfeeding status, the prominent feature of the dietary pattern, was also associated with a sub-set of serum metabolites in both cohorts. In START, this diet pattern was associated with the metabolites tryptophan betaine, 2-hydroxybutyric acid, tyrosine, phenylalanine, and trimethyl-N-oxide. In the CHILD Cohort Study(CHILD), breastfeeding status was associated with the metabolites aminooctanoic acid, 3-hydroxybutyric acid, and methyl-proline. The results of our study suggest that breastfeeding has the largest effect on the composition of the gut microbiome and the serum metabolome at 1 year, even when solid food diet and other covariates are considered.

Published
2021

50. Predicting Significant Right Ventricular Failure Post-LVAD Implantation Using CMR Compared to Echocardiography and Right Heart Catheterisation

Author

Shanmuganathan, M., primary, Rajani, P., additional, Androulakis, E., additional, Moledina, S., additional, Sarri, G., additional, Robertus, J., additional, Kiff, K., additional, Baston, V., additional, Dar, O., additional, Riesgo-Gil, F., additional, Simon, A., additional, Stock, U., additional, and Wong, J., additional

Published
2021
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