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152. Tranexamic acid versus placebo to prevent bleeding in patients with haematological malignancies and severe thrombocytopenia (TREATT): a randomised, double-blind, parallel, phase 3 superiority trial

Author

Estcourt, Lise J, McQuilten, Zoe K, Bardy, Peter, Cole-Sinclair, Merrole, Collins, Graham P., Crispin, Philip J., Curnow, Elinor, Curnow, Jennifer, Degelia, Amber, Dyer, Claire, Friebe, Adam, Floro, Lajos, Grand, Effie, Hudson, Cara, Jones, Gail, Joseph, Joanne, Kallmeyer, Charlotte, Karakantza, Marina, Kerr, Paul, Last, Sara, Lobo-Clarke, Maria, Lumley, Matthew, McMullin, Mary F, Medd, Patrick G., Morton, Suzy M., Mumford, Andrew D., Mushkbar, Maria, Parsons, Joseph, Powter, Gillian, Sekhar, Mallika, Smith, Laura, Soutar, Richard, Stevenson, William S., Subramoniapillai, Elango, Szer, Jeff, Thomas, Helen, Waters, Neil A., Wei, Andrew H., Westerman, David A., Wexler, Sarah A., Wood, Erica M., Stanworth, Simon J., Abioye, Adrienne, Afghan, Rabia, Ai, Sylvia Ai, Akanni, Magbor, Alajangi, Rajesh, Alam, Usmaan, Al-Bubseeree, Bahaa, Alderson, Sophie, Alderson, Craig, Ali, Sayed, Ali, Kabir, Alighan, Rookmeen, Allam, Rebecca Allam, Allen, Tania, Al-Sakkaf, Wesam, Ames, Kate, Anderson, Jacqueline, Andrews, Colin, Angel, Ann-Marie, Anlya, Manuela Anlya, Ansari, Farah, Appleby, Rowan, Arnold, Claire, Asbjornsdottir, Hulda, Asfaw, Biruk, Atkins, Elissa, Atkinson, Leela, Aubrey, Clare, Ayesha, Noor, Babbola, Lola, Badcock, David, Badcock, Samuel, Baggio, Diva, Bailiff, Ben, Baines, Kizzy, Baker, Holly, Baker, Victoria, Ball, Lindsay, Ball, Martin, Balquin, Irwin, Banks, Emma, Banos, George, Barnett, Jaytee, Barrie, Claire, Barron, Claire, Barton, Rebecca, Bason, Nina, Batta, Bindu, Bautista, Dianne, Bayley, Angela, Bayly, Emma, Baynes, Fionnuala, Bazargan, Ali, Bazeley, Rachel, Beadle, Yvonne, Beardsmore, Claire, Beattie, Kate, Bedford, Caroline, Behal, Rachna, Behan, Daniel, Bejan, Lilihna, Bell, Sarah, Bell, Karen, Bell, Louise, Bell, Kaitlyn, Benjamin, Reuben, Bennett, Sam, Benson, Gary, Benson, Warwick, Bent, Cameron, Bergin, Krystal, Berry, Alex, Besenyei, Stephanie, Besley, Caroline, Betteridge, Scott, Beveridge, Leigh, Bhattacharyya, Abir, Billen, Annelies, Bilmon, Ian, Binns, Emma, Birt, Mark, Bishop, David, Blanco, Andrea, Bleby, Lisa, Blemnerhet, Richard, Blombery, Piers, Blyth, Emily, Blythe, Nicola, Boal, Lauren, Boden, Ali, Bokhari, Syed W.I., Bongetti, Elisa, Booth, Stephen, Borley, Jayne, Bowen, David, Bowers, Dawn, Boyd, Stephen, Bradley, Sarah, Bradman, Helen, Bretag, Peta, Brillante, Maria, Brockbank, Rachel, Brough, Yasmin, Brown, Ellen, Brown, Jo, Brown, Eleanor, Brown, Claire, Brown, Jenny, Brown, Susan, Browning, Joe, Brownsdon, Alex, Bruce, David, Brydon-Hill, Ruth, Buckwell, Andrea, Burgess, Dannielle, Burke, Glenda, Burley, Kate, Burney, Claire, Burns, David, Burrows, Samuel, burton, Kieran, Butler, Jason, Cambalova, Lenka, Camozzi, Maria C., Campbell, Philip, Campfield, Karen, Campion, Victoria, Cargo, Catherine, Carmona, Julia, Carney, Dennis, Casan, Joshua, Cashman, Helen, Catt, Lorraine, Cattell, Michael, Cavill, Megan, Chadbone, Rachel, Chaganti, Sridhar, Chai, Yee, Chai, Khai Li, Chang, Joshua, Chapman, Judith, Chapman, Oliver G., Chapter, Tamika, Charlton, Andrew, Chau, Celina, Chauhan, Saleena, Chavda, Nikesh, Chen, Frederick, Chen, Melody, Chen, Meng Xi, Chen, Melanie, Chen, Melissa, Cheok, Kathleen, Cheung, Mai, Chidgey, Luke, Chmielokliec, Karolina, Choi, Philip, Choi, Jae, Chok, Anne, Chopra, Ruchika, Christopherson, Louise, Chu, Vicky, Chua, Chong Chyn, Chudakou, Pavel, Chugh, Vidushi, Chung, Chi, Clark, Erin, Clarke, Peter, Clarke, Kathleen, Clay, Jennifer, Clayton, Laura, Clements, Mitch, Clemmens, Jonathan, Clifford, Ruth, Collett, Dave, Collins, Maia, Collyer, Emily, Connolly, Maureen, Cook, Mark, Coombs, Sarah, Coppell, Jason, Cornwell, Sophie, Corrigan, Claire, Coughlin, Elizabeth, Couling, Jennifer, Cousins, Tony, Cowan, Catriona, Cox, Christine, Cox, Catherine, Coyle, Luke, Craig, Emily, Creasey, Thomas, Croan, Laura, Croft, Jane, Crosbie, Nicola, Crowe, Josephine, Crowther, Helen, Crozier, Jane, Culleton, Naomi, Cullis, Jonathan, Cumming, Anita, Cummins, Michelle, Cunningham, Adam, Curley, Cameron, Curtis, Samantha, Cuthbert, Robert, Cuthill, Kirsty, Dahahayake, Dinusha A, Dang, Amy, Davies, Marc, Davies, Ceri, Dawson, Emily, Day, Tom, De Abrew, Kanchana, De Lavallade, Hugues, De Silva, Neelaskshi, Dean, Georgina, Deane, Christopher, Demosthenous, Lisa, Desai, Amisha, Desborough, Michael, Devanny, Ian, Dhanapal, Jay, Dhani, Sundip, Di Martino, Vicky, Dickens, Emmy, DiCorleto, Carmen, Dinnett, Louise, Dirisan, Divya, Dixon, Karen, Dixon, Kiri, Doal, Inderjit, Dobivh, J, Docanto, Maria, Doecke, Helve, Donaldson, David, Donaldson, Kylee, Donohoe, Carrie, Douglas, Ashley, Doung, Stephen, Downer, Susan, D'Rozario, James, Drummond, Malcolm, Drummond, Mark, Drummond, Samantha, Drysdale, Elizabeth, D'Souza, Ross, D'Souza, Eugene, Dunn, Alex, Dutton, David, Dyson, Martin, Ediriwicurena, Kushani, Edleston, Sharon, Edwards, Dawn, Edwards, Morgan, Edwards, Anita, Eise, Nicole, Ellis, Steven, Ellis, Hayley, Elmonley, Shareef, Enstone, Rosemarie, Eordogh, Agnes, Erb, Sharon, Evans, Shannon, Evans, Megan, Ewing, Joanne, Eyre, Toby, Facey, Adam, Fammy, Mina, Farman, Jon, Farnell, Rachel, Favero, Laura, Fay, Keith, Ferguson, Karen, Fernon, Laura, Filshie, Robin, Finnegan, Damian, Fisher, Lisa, Flanagan, Asia, Fleck, Emma, Fletcher, Simon, Flora, Harpreet, Flower, Catherine, Fodor, Ioana, Foley, Heather, Folland, Emma, Folorunso, Comfort, Forbes, Molly, Fordwor, Katrina, Foster, Polly, Fox, Vanessa, Fox, Thomas, Francis, Olesya, Fryearson, Louise, Fuery, Madonna, Fung, Jiin, Furtado, Michelle, Galloway-Browne, Leanne, Gamble, Louise, Gamgee, Jeanette, Ganapathy, Arundathi, Gardner, Hayley, Gardner, Clare, Gasmelsheed, Noha, Gately, Amy, Gaynor, Lynda, Gebreid, Alex, Geffens, Ruth, George, Rachel, Gertner, Aniko, Ghebeh, Manar, Ghirardini, Emanuela, Giddings, Melainie, Gillett, Sandra, Gillett, Karen, Giri, Pratyush, Glass, Chris, Glewis, Sarah, Gooding, Sarah, Gordon, Olivia, Gordon, Joanne, Gottlieb, David, Gowda, Koushik, Gower, Elysie, Gray, Nicola, Grayer, Jo, Greaves, Elaine, Greenaway, Sally Anne, Greenfield, Graeme, Greenwood, Matthew, Gregory, Gareth, Griffin, James, Griffith, Julia, Griffith, James, Griffiths, Lindsey, Grzegrzolka, Paulina, Gu, Yisu, Guest, Jo, Guinai, Rosanna, Gullapalli, Veena, Gunolr, A., Guo, Lina, H, Wayne, Hagua, Sophia, Haile, Senait, Hall, Richard, Hamdollah-Zadeh, Maryam, Hanif, Zahra, Hanlon, Kathleen, Hann, Nicholas, Hanna, Ramez, Hannah, Guy, Hapuarachchi, Sameera, Hardman, Jacinta, Hardy, Alison, Harris, Anthony, Harris, Kylie, Harrison, Beth, Harrison, Simon, Harrison, Lea-Anne, Harrop, Sean, Harvey, Caroline, Hatcliffe, Faye, Hawking, Jo, Hawkins, Matthew, Hayden, Janet, Hayman, Michelle, Haynes, Elizabeth, Heaney, Nicholas, Hebbard, Andrew, Hempton, Jenny, Hendunneti, Sasanka, Henry, Maeve, Heywood, Jonathan, Hildyard, Catherine, Hill, Lydia, Hilldrith, Annette, Hitev, Petar, Hiwase, Smita, Hiwase, Devendra, Hoare, Chris, Hodge, Renate, Holloway, Amy, Holt, Chloe, Holton, Kelly, Homer, Lauren, Horne, Gillian, Horvath, Noemi, Hotong, Linda, Houdyk, Kristen, Houseman, Katy, Hoxhallari, Ilda, Hsu, Hannah, Hsu, Nina, Huang, Gillian, Hudson, Kerryn, Hufton, Melanie, Hughes, Timothy, Hughes, Siobhan, Hurley, Kate, Huxley, Rosie, Ibitoye, Temitope, Ibrouf, Abubaken, Inam, Farha, Indran, Tishya, Ingham, Karen, Innes, Calum, Irvine, David, Jaafar, Sarah, Jain, Manish, Jameson, Laura, Janjua, Pardeep, Jarvis, Rebecca, Jatheendran, Abirami, Javed, Abbie, Jen, Sheila, Jobanpura, Shailesh, Jobson, Irene, John, Deborah, Johns, Sophie, Johnston, Amanda, Jones, Hollie, Jones, Francesca, Joniak, Karolina, Jovanovic, Michael, Jovic, Anita, Joyce, Lauren, Judd, Andrew, Kakarlamudi, Sudhakar, Kakaroubas, Nick, Kalita, Maggie, Kam, Shirly, Kan, Julie, Kandle, P, Kanellopoulos, Alex, Kao, Chien, Kaparou, Maria, Kartsios, Charamlampos, Katsioulas, Vicki, Kaye, Russell, Keen, Katie, Kelly, Richard, Kelly, Pauline, Kelly, Donna, Kelly, Melanie, Kennedy, Glen, Kennedy, Nola, Kenny, Angela, Kenworthy, Zoe, Kerridge, Ian, Kesavan, Murali, Khafizi, Angelika, Khakwani, Muhammad, Khalid, Amna, Khamly, Kate, Khan, Anjum, Khan, Dalia, Khan, Mojid, Khan, Lubna, Khoo, Mona, Khwaja, Asim, Kim, Grace, King, Andrew, King, Vicky, King, Donna, Kinsella, Francesca, Kipp, David, Kirandeep, Pachoo, Kirui, Laura C., Kishore, Bhuvan, Knectlhi, Christopher, Knot, Amy, Knot, Armit, Ko, Cathy, Kolaric, Caitlin, Koo, Ray, Kotadia, Mary, Kothari, Jaimal, Kottaridis, Panagiotis D., Kuiluinathan, Gajan, Kulasekararaj, Austin, Kwan, John, Kwok, Marwan, Kwok, Phillip, Kwok, Fiona, Laane, Kristiina, Lad, Deena, Laird, Jennifer, Lam, Ada, Lane, Mary, Lanenco, Monica, Lang, Susan, Langridge, Alex, Langton, Catherine, Lannon, Michelle, Latif, Annie, Latimer, Maya, Latter, Ruth, Lau, I-Jun, Lawless, Sarah, Lawless, Theresa, Leach, Mike, Leaney, Sarah, Leary, Heather, Leavy, James, LeBlanc, Abbey, Lee, Vivienne, Lee, Edwin, Lee, Jenny, Lee, Tamara, Leischkie, Marian, Leitinger, Emma, Leon, Christopher, Leonard, Jayne, Lewis, David, Lewis, Ian, Lewis, Tania, Lim, Daniel, Littlewood, Kelly, Liu, Dara, Loh, Joanna, Lokare, Anand, Lomas, Oliver, Lovell, Richard, Lowe, Theresa, Lowry, Lisa, Lubowiecki, Marcin, Lumb, Rebecca, Lynch, Gail, Macaulay, Amanda, MacDonald, Lyndsey, MacDonald-Burn, Jill, Macmillan, Margaret, Maddock, Karen, Mahaliyana, Tomas, Mahon, Cassandra, Maidment, Alison, Maier, Susie, Mairos, Michelle, Majid, Mahseeman, Mak, Ka L, Mak, Anne, Malendrayogau, Arunthrthy, Malham, Hana, Malyon, Felicity, Mandadapu, Vineela, Mandel, Laura, Mant, Sarah, Manton, Ruth, Maouche, Nadjoua, Maqbool, Muhammad G., Marchant, Gregory, Marinho, Mariana, Marks, David, Marner, Mike, Marr, Helen, Marshall, Gillian, Martin, Siobhan, Martin, Abigail, Marzolini, Maria, Mason, Kiara, Massie, Jonathan, Masson, Rebecca, Mathavan, Vidya, Mathew, Siju, Mathie, Judith, Mattocks, Lehenta, Maybury, Bernard, Mayer, Georgina, McAlister, Chyrelle, McAllister, Jo, McConnell, Stewart, McCracken, James, McCullagh, Liz, McCulloch, Rory, Mcdermott, Christopher, Mcdonald, Kerian, McGinniss, Laura, McGurk, Fiona, McIlwain, Jessica, McIver, Kirsten, Mckay, Pam, McKenna, Lorraine, Mclornan, Donal, McMahon, Coalon, McNeice, Linda, McNeill, Susan, McNickle, Molly, McQueen, Fiona, McRae, Simon, McTaggart, Bobby, Mehew, Jenny, Mehra, Varnn, Melly, Michelle, Menichelli, Tara, Micklethwatte, Ken, Mihailescue, Loredana, Mijovic, Aleksander, Millband, Hannah, Miller, Lucy, Millien, Samuel T., Milnthorpe, James, Minson, Adrian, Molnar, Eva, Monsour, Marc, Moody, Mary, Moon, Rebecca, Moore, Sally, Moore, Katy, Morgan, Kelly, Morralley, Rebecca, Morris, Denise, Morris, Kirk, Morrison, Nicole, Moss, Merinda, Mughal, Muhammad, Muir, Paul, Mukkath, David, Mulla, Aasiyu, Mulligan, Stephen, Mullings, Joanne, Mulqueen, Angela, Muluey, Caitlin, Murdoch, Sarah, Murrani, Sura, Murthy, Vidhya, Musngi, Jimmy, Mustafa, Nadreen, Mynes, Tracey, Nalpantidis, Anastasios, Nandurkar, Harshal, Nardone, Linda, Nasari, Latifa, Nash, Monica, Naylor, Georgina, Ngu, Loretta, Nguethina, Melissa, Nguyen, John, Nguyen, Joseph, Nichol, Wendy, Nicholls, Emma, Nicole, Catherine S., Nicolson, Phillip, Nielson, David, Nikolousis, Emmanouil, Nix, Georgina, Njoku, Rita, Norman, Jane, Norman, Amy, Norris, Phoebe, North, Daniel, Norwood, Megan, Notcheva, Gaynor, Novitzky-Basso, Igor, Nyaboko, Joseph, Nygren, Maria, Obu, Ingrid, O'Connell, Siobhan, O'Connor, Jody, O'Kelly, Deanna, O'Niell, Aideen, Ony, Jeremy, Oo, Kathy, Oo, April, Oppermann, Anne, Orr, Ruth, O'Sullivan, Mary, Page, Jennifer, Palfreyman, Emma, Paneesha, Shankaranarayana, Panicker, Shyam, Parbutt, Catherine, Parigi, Elesha, Paris, Gemma, Parker, Tracey, Parnell, Caroline, Parrish, Christopher, Parsons, Alex, Pasat, Mioara, Patel, Natasha, Patel, Vijay, Patel, Pooja, Patel, Chaya, Pati, Nalini, Patterson, Andrea, Paul, Lauren, Payet, Danielle, Payne, Elspeth, Peachey, Victoria, Pearson, Amanda, Peniket, Andy, Percy, Laura, Pereyra, Millicent, Pervaiz, Omer, Phalod, Gunjan D, Pham, Anh, Pho, Jason, Pickard, Keir, Pidcock, Michael, Piggin, Anna, Pishyar, Yalda, Pocock, Abigail, Pol, Ranjendres, Polzella, Paolo, Poolan, Sonia, Portingale, Vicki, Posnett, Claire, Potluri, Sandeep, Potter, Victoria, Pratt, Guy, Prodger, Catherine, Pueblo, Andres, Puliyayil, Anish, Puvanakumar, Pratheepan, Qadri, Abdul, Quach, Hang, Quinn, Michael, Rafferty, Mark, Rahman, Marzia, Raj, Kavita, Raj, Sonia, Rajendran, Ramina, Ramanan, Radha, Ramasamy, Karthik, Rampotas, Alexandros, Ranchhod, Natasha, Rashid, Sabia, Ratanjee, Sunita, Rathore, Gurpreet, Ratnasingam, Sumita, Rayat, Manjit, Rayner, Michael, Reddell-Denton, Rebecca, Redding, Nicola, Reddy, Udaya, Rehman, Atique, Rice, Carol, Riches, Iwona, Rider, Thomas, Riley, John, Rinaldi, Ciro, Roberts, Kayleigh, Roberts, Andrew, Robertson, Bryony, Robertson, Peter, Robinson, Dan, Robinson, Rebecca, Robjohns, Emma, Robledo, Laura, Rodrigues, Ana, Rofe, Chris, Roff, Bridie, Rogers, Rachel, Rolt, Jill, Rooney, Carmela, Rose, Kathy, Rose, Hannah, Ross, David, Rouf, Shahara, Rourke, Claire, Routledge, David, Ruggiero, Janet, Rule, Simon, Rumsey, Richard, Sagge, Cherry, Saldhana, Helen, Salisbury, Richard, Salisbury, Sarah, Salvaris, Ross, Sanders, Kay, Sangombe, Mirriam, Sanigorska, Anna, Santos, Kristine, Sarkis, Taylah, Sarma, Anita, Saunders, Natalie, Schmidt, Kara, Schmidtmann, Anja, Schumacher, Ann, Scorer, Tom Scorer, Scott, Asleigh, Seath, Ingrid, Sejman, Frances, Selim, Adrian, Shamim, Nadia, Shan, Jocelyn, Shanmuganathan, Naranie, Shanmugaranjan, Shaminie, Sharpe, Michelle, Sharpley, Faye, Shaw, Emma, Sheath, Cara, Sheehy, Oonagh, Shen, Vivian, Sherbide, Solomon, Sheridan, Mathew, Sheridan, Jane, Sheridon, Matthew, Shields, Tracy, Sim, Hau V, Sim, Shirlene, Sims, Matt, Singaraveloo, Lydia, Singh, Gurcharan, Singh, Jasmine, Sladesal, Shree, Sloan, Andrew, Slobodian, Peter, Smith, Sophie, Smith, Sarit, Smith, Claire, Smith, Alastair, Smith, Neil, Snowden, Katherine, Solis, Joel, Somios, Denise, Soo, Jade, Spanevello, Michelle, Spaulding, Madeleie, Spence, Laura, Spillane, Liz, Spiteri, Alisha, Sprigg, Naomi, Springett, Sally, Stafford, Lynn, Stainthorp, Katherine, Stark, Kate, Steeden, Louise, Stephen, Ella, Stephenson, Aisling, Stewart, Andrew, Stewart, Orla, Stobie, Emma, Stokes, Chelsea, Streater, Jacqui, Suddens, Charlie-Marie, Suntharalingam, Surenthini, Surana, Narinder, Sutherland, Robyn, Sutherland, Antony, Sutton, David, Sweeney, Connor, Sweet, Reilly, Szucs, Aniko P, Taheri, Leila E., Tailor, Hinesh, Tam, Constantine, Tambakis, George, Tamplin, Mary, Tan, Chee, Tan, Sui, Tan, Joanne, Tan, Zhi, Taran, Tatiana, Tarpey, Fiona, Taseka, Angela, Tasker, Suzy, Tatarczuch, Maciej, Tayabali, Sarrah, Taylor, Hannah, Taylor, Robert, Taylor, Melaine, Taylor-Moore, Ella, Teasdale, Lesley, Tebbet, Elizabeth, Tedjasepstra, Aditya, Tedjaseputra, Aditya, Tepkumkun, Oummy, Terpstra, Andrew, Thomas, Wayne, Thomas, Shanice, Thompson, Rachel, Thornton, Thomas, Thorp, Bronwyn, Thrift, Moi Yap, Thwaites, Phillipa, Timbres, Jasmine, Tindall, Lauren, Tiong, Ing Soo, Tippler, Nicole, Todd, Tony, Todd, Shirley, Toghill, Neil, Tomlinson, Eve, Tooth, Jacinta, Topp, M., Trail, Nicola, Tran, Nguyen, Tran, Elizabeth, Tran, Vi, Treder, Bona, Tribbeck, Michelle, Trochowski, Siobhan, Truslove, Maria, Tse, Tsun, Tseu, Bing, Tucker, David, Turner, Kelly, Turner, Dianne, Turner, Herleen, Turner, Gillian, Twohig, Julie, Tylee, Thomas, Uhe, Micheleine, Underhill, Lauren, V, Joanne, Van der Vliet, Georgina, Van Tonder, Tina, VanderWeyden, Carrie, Varghese, Jerry, Vaughan, Lachlan, Veale, David, Vickaryyous, Nicky, Vince, Kathryn, Von Welligh, Jacoba, Vora, Sona, Wadehra, Karan, Walker, Rebecca, Walker, Stephen, Wallace, Roslyn, Wallniosve, Stephanie, Wallwork, S., Walmsley, Zoe, Walters, Fiona, Wang, Joyce, Wang, Angela, Wang, Chen, Wanyika, Mercy, Warcel, Dana, Wardrobe, Katrina, Warnes, Kristian, Waterhouse, Christopher, Waterworth, Adam, Watson, Caroline, Watson, Edmund, Watts, Emily, Weaver, Emma, Weber, Nicholas, Webley, Kaytie, Welford, Anna, Wells, Matt, Westbury, Sarah, Westcott, Jackie, Western, Robyn, Weston, Julia, White, Jessica, White, Phillipa, Whitehead, Anna, Whitehouse, James, Wieringa, Samantha, Willan, John, Williams, Sandra, Williams, Bethany, Williamson, Stephanie, Willoughby, Brett, Wilmot, Gail, Wilmott, Rosalind, Wilson, Joanna, Wilson, Emma, Wilson, Suzy, Wilson, Heather, Wilson, Caroline, Wilson, Tanya, Wilton, Margaret, Wiltshire, Paula, Wincup, Joanne, Wolf, Julia, Wong, Henna, Wong, Cyndi, Wong, Daniel, Wong, Jonathan, Wong, Shi Qin, Wood, Sarah, Wood, Henry, Wooding, Jackie, Woolley, Kelly, Wright, Myles, Wynn-Williams, Roland, Yannakou, Costas, Yeoh, Zhi Han, Yeung, David, Young, Agnes, Yuen, Flora, Yuen, Agnes, Zaja, Oliver, Zhang, Xiao-Yin, and Zhang, Mei

Published
2024
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156. Exploring changes in children’s well-being due to COVID-19 restrictions: the Italian EpaS-ISS study

Author

Marco Giustini, Ilaria Luzi, Angela Spinelli, Silvia Andreozzi, Mauro Bucciarelli, Marta Buoncristiano, Paola Nardone, Silvia Ciardullo, and on behalf of the EPaS-ISS Group

Subjects
COVID-19, Well-being, Stay at home orders, Children, Primary school, Pediatrics, RJ1-570
Abstract

Abstract Background While existing research has explored changes in health behaviours among adults and adolescents due to the COVID-19 outbreak, the impact of quarantine on young children’s well-being is still less clear. Moreover, most of the published studies were carried out on small and non-representative samples. The aim of the EpaS-ISS study was to describe the impact of the COVID-19 pandemic on the habits and behaviours of a representative sample of school children aged mainly 8–9 years and their families living in Italy, exploring the changes in children’s well-being during the COVID-19 pandemic compared to the immediately preceding time period. Methods Data were collected using a web questionnaire. The target population was parents of children attending third-grade primary schools and living in Italy. A cluster sample design was adopted. A Well-Being Score (WBS) was calculated by summing the scores from 10 items concerning the children’s well-being. Associations between WBS and socio-demographic variables and other variables were analysed. Results A total of 4863 families participated. The children’s WBS decreased during COVID-19 (median value from 31 to 25; p = 0.000). The most statistically significant variables related to a worsening children’s WBS were: time of school closure, female gender, living in a house with only a small and unliveable outdoor area, high parents’ educational level and worsening financial situation. Conclusions According to parents ' perception, changes in daily routine during COVID-19 negatively affected children’s well-being. This study has identified some personal and contextual variables associated with the worsening of children’s WBS, which should be considered in case of similar events.

Published
2023
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157. Impact of the Suspension of Elective Surgeries for Adolescent Idiopathic Scoliosis during the COVID-19 Pandemic

Author

Matheus Neves Castanheira, Giovanni Salvatore Nardone, Rafael de Paiva Luciano, and Márcio Squassoni Leite

Subjects
adolescent, scoliosis, elective surgical procedures, unified health system, Medicine, Orthopedic surgery, RD701-811
Abstract

Abstract Objectives This study evaluated the radiographic progressions of scoliotic curves higher than 40° in patients with adolescent idiopathic scoliosis (AIS). These subjects waited for the surgical procedure while elective surgeries were on hold during the COVID-19 pandemic. Inadditiontoradiographicprogressions, this studydescribed the quality of life of these patients. Methods This study is a retrospective cohort assessing 29 AIS patients with surgical indications registered in the Brazilian public healthcare service. We compared the scoliotic radiographic measurements in two moments: at the beginning of the interruption of elective surgeries due to the COVID-19 pandemic and when these procedures resumed. Results When comparing the radiographic measurements before and after the suspension of assessments for elective surgeries, we observed a significant increase in main curve angles ( p < 0.001), with variations ranging from 0 to 68° and a median valueof10°.Insecondary curves, weobserved anincreaseinangles fromthe proximal thoracic ( p < 0.001) and lumbar ( p = 0.001) regions. However, the increase in the main thoracic region was not significant ( p = 0.317). Conclusion The suspension of elective surgeries for AIS resulted in a significant increase in the radiographic values of patients' spine deformities. This increase harmed the quality of life of these subjects and their families.

Published
2023
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159. The professional background of a referring physician predicts the diagnostic yield of small bowel capsule endoscopy in suspected small bowel bleeding

Author

Debora Compare, Costantino Sgamato, Alba Rocco, Pietro Coccoli, Durante Donnarumma, Stefano Andrea Marchitto, Sofia Cinque, Pietro Palmieri, and Gerardo Nardone

Subjects
Endoscopy Small Bowel, Capsule endoscopy, Small intestinal bleeding, Diseases of the digestive system. Gastroenterology, RC799-869
Published
2024
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160. Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form.

Author

Annarita Fanizzi, Samantha Bove, Maria Colomba Comes, Erika Francesca Di Benedetto, Agnese Latorre, Francesco Giotta, Annalisa Nardone, Alessandro Rizzo, Clara Soranno, Alfredo Zito, and Raffaella Massafra

Subjects
Medicine, Science
Abstract

Background and objectiveDetecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decision-making processes in the treatment of this malignancy. Though several machine learning models analyzing both clinical and histopathological information have been developed in literature to address this task, these approaches turned out to be unsuitable for describing this problem.MethodsIn this study, we designed a novel artificial intelligence-based approach which converts clinical information into an image-form to be analyzed through Convolutional Neural Networks. Specifically, we predicted the occurrence of an Invasive Disease Event at both 5-year and 10-year follow-ups of 696 female patients with a first invasive breast cancer diagnosis enrolled at IRCCS "Giovanni Paolo II" in Bari, Italy. After transforming each patient, represented by a vector of clinical information, to an image form, we extracted low-level quantitative imaging features by means of a pre-trained Convolutional Neural Network, namely, AlexNET. Then, we classified breast cancer patients in the two classes, namely, Invasive Disease Event and non-Invasive Disease Event, via a Support Vector Machine classifier trained on a subset of significative features previously identified.ResultsBoth 5-year and 10-year models resulted particularly accurate in predicting breast cancer recurrence event, achieving an AUC value of 92.07% and 92.84%, an accuracy of 88.71% and 88.82%, a sensitivity of 86.83% and 88.06%, a specificity of 89.55% and 89.3%, a precision of 71.93% and 84.82%, respectively.ConclusionsThis is the first study proposing an approach which converts clinical information into an image-form to develop a decision support system for identifying patients at high risk of occurrence of an Invasive Disease Event, and then defining personalized oncological therapeutic treatments for breast cancer patients.

Published
2024
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161. Redetermination of PD-L1 expression after chemio-radiation in locally advanced PDL1 negative NSCLC patients: retrospective multicentric analysis

Author

Patrizia Ciammella, Salvatore Cozzi, Paolo Borghetti, Marco Galaverni, Valerio Nardone, Maria Paola Ruggieri, Matteo Sepulcri, Vieri Scotti, Alessio Bruni, Francesca Zanelli, Roberto Piro, Elena Tagliavini, Andrea Botti, Federico Iori, Emanuele Alì, Chiara Bennati, and Marcello Tiseo

Subjects
locally advanced non-small cell lung cancer, chemo-radiation, PD-L1 expression, PD-L1 negative patients, re-biopsy, durvalumab, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

BackgroundChemoradiation therapy (CRT) is the treatment of choice for locally advanced non-small cell lung cancer (LA-NSCLC). Several clinical trials that combine programmed cell death 1 (PD1) axis inhibitors with radiotherapy are in development for patients with LA-NSCLC. However, the effect of CRT on tumor cells programmed cell death ligand-1 (PD-L1) expression is unknown.MethodsIn this multicentric retrospective study, we analyzed paired NSCLC specimens that had been obtained pre- and post-CRT. PD-L1 expression on tumor cells was studied by immunohistochemistry. The purpose of this study was to evaluate the feasibility, risk of complications, and clinical relevance of performing re-biopsy after CRT in patients with PD-L1 negative LA-NSCLC.ResultsOverall, 31 patients from 6 centers with PD-L1 negative LA-NSCLC were analyzed. The percentage of tumor cells with PD-L1 expression significantly increased between pre- and post-CRT specimens in 14 patients (45%). Nine patients had unchanged PD-L1 expression after CRT, in five patients the rebiopsy material was insufficient for PD-L1 analysis and in two patients no tumor cells at rebiopsy were found. The post-rebiopsy complication rate was very low (6%). All patients with positive PD-L1 re-biopsy received Durvalumab maintenance after CRT, except one patient who had a long hospitalization for tuberculosis reactivation. Median PFS of patients with unchanged or increased PD-L1 expression was 10 and 16.9 months, respectively.ConclusionCRT administration can induce PD-L1 expression in a considerable fraction of PD-L1 negative patients at baseline, allowing them receiving the maintenance Durvalumab in Europe. Hence, after a definitive CRT, PD-L1 redetermination should be considered in patients with LA-NSCLC PD-L1 negative, to have a better selection of maintenance Durvalumab candidates.

Published
2024
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162. A Stochastic Compartmental Model for COVID-19

Author

Sonnino, Giorgio, Mora, Fernando, and Nardone, Pasquale

Subjects
Physics - Medical Physics, Physics - Biological Physics
Abstract

We propose two stochastic models for the Coronavirus pandemic. The statistical properties of the models, in particular the correlation functions and the probability density function, have duly been computed. Our models, which generalises a model previously proposed and published in a specialised journal, take into account the adoption of the lockdown measures as well as the crucial role of the hospitals and Health Care Institutes. To accomplish this work we have analysed two scenarios: the SIS-model (Susceptible => Infectious => Susceptible) in presence of the lockdown measures and the SIS-model integrated with the action of the hospitals (always in presence of the lockdown measures). We show that in the case of the pure SIS-model, once the lockdown measures are removed, the Coronavirus will start growing again. However, in the second scenario, beyond a certain threshold of the hospital capacities, the Coronavirus is not only kept under control, but its capacity to spread tends to diminish in time. Therefore, the combined effect of the lockdown measures with the action of the hospitals and health Institutes is able to contain and dampen the spread of the SARS-CoV-2 epidemic. This result can be used during a period of time when the massive distribution of delivery of a limited number of vaccines in a given population is not yet feasible. By way of example, we analysed the data for USA and France where the intensities of the noise have been estimated by Statistical Mechanics. In particular, for USA we have analysed two possible hypotheses: USA is still subject to the first wave of infection by and USA is in the second (or third) wave of SARS-CoV-2 infection.The agreement between theoretical predictions and real data confirms the validity of our approach., Comment: 37 pages, 29 Figures, and 6 Tables

Published
2020

163. Comparison of two superconducting phases induced by a magnetic field in UTe2

Author

Knafo, W., Nardone, M., Valiska, M., Zitouni, A., Lapertot, G., Aoki, D., Knebel, G., and Braithwaite, D.

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

Superconductivity induced by a magnetic field near metamagnetism is a striking manifestation of magnetically-mediated superconducting pairing. After being observed in itinerant ferromagnets, this phenomenon was recently reported in the orthorhombic paramagnet UTe$_2$. Under a magnetic field applied along the hard magnetization axis b, superconductivity is reinforced on approaching metamagnetism at $\mu_0H_m$ = 35 T, but it abruptly disappears beyond $H_m$. On the contrary, field-induced superconductivity was reported beyond $\mu_0H_m$ = 40-50 T in a magnetic field tilted by $\simeq25-30\deg$ from b in the (b,c) plane. Here we explore the phase diagram of UTe2 under these two magnetic-field directions. Zero-resistance measurements permit to confirm unambiguously that superconductivity is established beyond Hm in the tilted-field direction. While superconductivity is locked exactly at fields either smaller (for a H || b), or larger (for H tilted by $\simeq27\deg$ from b to c), than Hm, the variations of the Fermi-liquid coefficient in the electrical resistivity and of the residual resistivity are surprisingly similar for the two field directions. The resemblance of the normal states for the two field directions puts constraints for theoretical models of superconductivity and implies that some subtle ingredients must be in play., Comment: 18 pages, 5 Figures, includes Supplementary Information (9 pages, 8 Figures)

Published
2020
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164. Dynamics of the COVID-1 -- Comparison between the Theoretical Predictions and the Real Data, and Predictions about Returning to Normal Life

Author

Sonnino, Giorgio and Nardone, Pasquale

Subjects
Quantitative Biology - Populations and Evolution
Abstract

A new coronavirus disease, called COVID-19, appeared in the Chinese region of Wuhan at the end of last year; since then the virus spread to other countries, including most of Europe. We propose a differential equation governing the evolution of the COVID-19. This dynamic equation also describes the evolution of the number of infected people for 13 common respiratory viruses (including the SARS-CoV-2). We validate our theoretical predictions with experimental data for Italy, Belgium and Luxembourg, and compare them with the predictions of the logistic model. We find that our predictions are in good agreement with the real world since the beginning of the appearance of the COVID-19; this is not the case for the logistic model that only applies to the first days. The second part of the work is devoted to modelling the descending phase, i.e. the decrease of the number of people tested positive for COVID-19. Also in this case, we propose a new set of dynamic differential equations that we solved numerically. We use our differential equations parametrised with experimental data to make several predictions, such as the date when Italy, Belgium, and Luxembourg will reach a peak number of SARS-CoV-2 infected people. The descending curves provide valuable information such as the duration of the COVID-19 epidemic in a given Country and therefore when it will be possible to return to normal life. The study of the the dynamics of COVID-19 when the population have been subject to less restrictive measures is beyond the scope of this work and it will be matter of future works., Comment: 34 pages, 19 figures, 6 tables

Published
2020

165. Ultrasound evidence for a two-component superconducting order parameter in Sr$_2$RuO$_4$

Author

Benhabib, S., Lupien, C., Paul, I., Berges, L., Dion, M., Nardone, M., Zitouni, A., Mao, Z. Q., Maeno, Y., Georges, A., Taillefer, L., and Proust, C.

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

The quasi-2D metal Sr$_2$RuO$_4$ is one of the best characterized unconventional superconductors, yet the nature of its superconducting order parameter is still highly debated. This information is crucial to determine the pairing mechanism of Cooper pairs. Here we use ultrasound velocity to probe the superconducting state of Sr$_2$RuO$_4$. This thermodynamic probe is symmetry-sensitive and can help to identify the superconducting order symmetry. Indeed, we observe a sharp jump in the shear elastic constant $c_{66}$ as the temperature is raised across the superconducting transition at $T_c$. This directly implies that the superconducting order parameter is of a two-component nature. Based on symmetry argument and given the other known properties of Sr$_2$RuO$_4$, we discuss what states are compatible with this requirement and propose that the two-component order parameter, namely $\lbrace d_{xz}; d_{yz} \rbrace$, is the most likely candidate.

Published
2020
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169. Activation of the IFN Signaling Pathway is Associated with Resistance to CDK4/6 Inhibitors and Immune Checkpoint Activation in ER-Positive Breast Cancer

Author

De Angelis, Carmine, Fu, Xiaoyong, Cataldo, Maria Letizia, Nardone, Agostina, Pereira, Resel, Veeraraghavan, Jamunarani, Nanda, Sarmistha, Qin, Lanfang, Sethunath, Vidyalakshmi, Wang, Tao, Hilsenbeck, Susan G, Benelli, Matteo, Migliaccio, Ilenia, Guarducci, Cristina, Malorni, Luca, Litchfield, Lacey M, Liu, Jiangang, Donaldson, Joshua, Selenica, Pier, Brown, David N, Weigelt, Britta, Reis-Filho, Jorge S, Park, Ben H, Hurvitz, Sara A, Slamon, Dennis J, Rimawi, Mothaffar F, Jansen, Valerie M, Jeselsohn, Rinath, Osborne, C Kent, and Schiff, Rachel

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Genetics, Breast Cancer, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Good Health and Well Being, Antineoplastic Agents, Breast Neoplasms, Cyclin-Dependent Kinase 4, Cyclin-Dependent Kinase 6, Female, Humans, Piperazines, Pyridines, Receptors, Estrogen, Signal Transduction, Tumor Cells, Cultured, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

PurposeCyclin-dependent kinase 4 (CDK4) and CDK6 inhibitors (CDK4/6i) are highly effective against estrogen receptor-positive (ER+)/HER2- breast cancer; however, intrinsic and acquired resistance is common. Elucidating the molecular features of sensitivity and resistance to CDK4/6i may lead to identification of predictive biomarkers and novel therapeutic targets, paving the way toward improving patient outcomes.Experimental designParental breast cancer cells and their endocrine-resistant derivatives (EndoR) were used. Derivatives with acquired resistance to palbociclib (PalboR) were generated from parental and estrogen deprivation-resistant MCF7 and T47D cells. Transcriptomic and proteomic analyses were performed in palbociclib-sensitive and PalboR lines. Gene expression data from CDK4/6i neoadjuvant trials and publicly available datasets were interrogated for correlations of gene signatures and patient outcomes.ResultsParental and EndoR breast cancer lines showed varying degrees of sensitivity to palbociclib. Transcriptomic analysis of these cell lines identified an association between high IFN signaling and reduced CDK4/6i sensitivity; thus an "IFN-related palbociclib-resistance Signature" (IRPS) was derived. In two neoadjuvant trials of CDK4/6i plus endocrine therapy, IRPS and other IFN-related signatures were highly enriched in patients with tumors exhibiting intrinsic resistance to CDK4/6i. PalboR derivatives displayed dramatic activation of IFN/STAT1 signaling compared with their short-term treated or untreated counterparts. In primary ER+/HER2- tumors, the IRPS score was significantly higher in lumB than lumA subtype and correlated with increased gene expression of immune checkpoints, endocrine resistance, and poor prognosis.ConclusionsAberrant IFN signaling is associated with intrinsic resistance to CDK4/6i. Experimentally, acquired resistance to palbociclib is associated with activation of the IFN pathway, warranting additional studies to clarify its involvement in resistance to CDK4/6i.

Published
2021

170. Effective Communication for Strategic Change

Author

Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, Nardone, Giorgio, Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, and Nardone, Giorgio

Published
2022
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171. Strategic Debriefing in Practice

Author

Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, Nardone, Giorgio, Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, and Nardone, Giorgio

Published
2022
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172. Strategic Debriefing: A Corrective Emotional Experience

Author

Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, Nardone, Giorgio, Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, and Nardone, Giorgio

Published
2022
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173. What You Need to Know Before You Start

Author

Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, Nardone, Giorgio, Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, and Nardone, Giorgio

Published
2022
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174. Essentials of Debriefing

Author

Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, Nardone, Giorgio, Capogna, Giorgio, Ingrassia, Pier Luigi, Capogna, Emanuele, Bernardini, Michela, Valteroni, Elisa, Pietrabissa, Giada, and Nardone, Giorgio

Published
2022
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175. Entity Manager

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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177. Collection Mapping

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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178. Advanced Queries

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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179. Criteria API

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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180. Enterprise Applications

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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181. XML Mapping Files

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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182. Using Queries

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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183. Query Language

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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184. Packaging and Deployment

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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185. Testing

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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186. Other Advanced Topics

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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187. Object-Relational Mapping

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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188. Introduction

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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189. Getting Started

Author

Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, Nardone, Massimo, Jungmann, Lukas, Keith, Mike, Schincariol, Merrick, and Nardone, Massimo

Published
2022
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190. Irvin J. Hunt: Dreaming the Present: Time, Aesthetics, and the Black Cooperative Movement

Author

Nardone, Jennifer

Subjects
University of North Carolina Press, Book publishing, Architecture and design industries, Construction and materials industries
Abstract

Irvin J. Hunt Dreaming the Present: Time, Aesthetics, and the Black Cooperative Movement Chapel Hill: University of North Carolina Press, 2022 288 pages, 21 black-and-white illustrations, 1 map ISBN: 9781469667942, [...]

Published
2023

191. Mutational Analysis of Circulating Tumor DNA in Patients With Estrogen Receptor–Positive/Human Epidermal Growth Factor Receptor 2–Negative Advanced Breast Cancer Receiving Palbociclib: Results From the TREnd Trial

Author

Migliaccio, Ilenia, Romagnoli, Dario, Galardi, Francesca, De Luca, Francesca, Biagioni, Chiara, Curigliano, Giuseppe, Criscitiello, Carmen, Minisini, Alessandro Marco, Moretti, Erica, Risi, Emanuela, Guarducci, Cristina, Nardone, Agostina, Biganzoli, Laura, Benelli, Matteo, and Malorni, Luca

Published
2024
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192. Trends in chronic hepatitis B virus infection in Italy over a 10-year period: Clues from the nationwide PITER and MASTER cohorts toward elimination

Author

Giuseppina Brancaccio, Barbara Coco, Alessandra Nardi, Maria Giovanna Quaranta, Maria Elena Tosti, Luigina Ferrigno, Irene Cacciola, Vincenzo Messina, Luchino Chessa, Filomena Morisco, Michele Milella, Francesco Barbaro, Alessia Ciancio, Francesco Paolo Russo, Nicola Coppola, Pierluigi Blanc, Ernesto Claar, Gabriella Verucchi, Massimo Puoti, Anna Linda Zignego, Liliana Chemello, Salvatore Madonia, Stefano Fagiuoli, Alfredo Marzano, Carlo Ferrari, Pietro Lampertico, Vito Di Marco, Antonio Craxì, Teresa Antonia Santantonio, Giovanni Raimondo, Maurizia R. Brunetto, Giovanni Battista Gaeta, Loreta A. Kondili, Luisa Pasulo, Carmine Coppola, Federica Pisano, Mariarosaria Romano, Carmen Porcu, Irene Francesca Bottalico, Valentina Cossiga, Xhimi Tata, Caterina Sagnelli, Piera Pierotti, Elisabetta Degasperi, Valerio Rosato, Lorenzo Badia, Dontella Ieluzzi, Monica Monti, Maria Grazia Bavetta, Luisa Cavalletto, Pierluigi Toniutto, Ezio Fornasiere, Antonio Colecchia, Alberto Ferrarese, Gerardo Nardone, Alba Rocco, Mauro Viganò, Francesco Giuseppe Foschi, Fabio Conti, Giulia Morsica, Stefania Salpietro, Carlo Torti, Chiara Costa, Alessandro Federico, Marcello Dallio, Alessia Giorgini, Marco Anselmo, Pasqualina De Leo, Serena Zaltron, Anna Cambianica, Fabio Piscaglia, Ilaria Serio, Simona Schivazappa, Antonio Mastroianni, Luciana Chidichimo, Marco Massari, Cesare Mazzaro, Aldo Marrone, Francesca Maria D'Amore, Gianpiero D'Offizi, Anna Licata, Grazia Anna Niro, Teresa Pollicino, and Alessio Aghemo

Subjects
Hepatitis B, Chronic, Hepatitis Delta, Epidemiology, Migrants, Hepatitis control, Infectious and parasitic diseases, RC109-216
Abstract

Objectives: The study measures trends in the profile of patients with chronic hepatitis B virus linked to care in Italy. Methods: A cross-sectional, multicenter, observational cohort (PITER cohort) of consecutive patients with hepatitis B surface antigen (HBsAg) over the period 2019-2021 from 46 centers was evaluated. The reference was the MASTER cohort collected over the years 2012-2015. Standard statistical methods were used. Results: The PITER cohort enrolled 4583 patients, of whom 21.8% were non-Italian natives. Compared with those in MASTER, the patients were older and more often female. The prevalence of hepatitis B e antigen (HBeAg) declined (7.2% vs 12.3; P

Published
2023
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195. Redlines and Greenspace: The Relationship between Historical Redlining and 2010 Greenspace across the United States.

Author

Nardone, Anthony, Rudolph, Kara E, Morello-Frosch, Rachel, and Casey, Joan A

Subjects
Toxicology, Environmental Sciences, Medical and Health Sciences
Abstract

IntroductionRedlining, a racist mortgage appraisal practice of the 1930s, established and exacerbated racial residential segregation boundaries in the United States. Investment risk grades assigned >80y ago through security maps from the Home Owners' Loan Corporation (HOLC) are associated with current sociodemographics and adverse health outcomes. We assessed whether historical HOLC investment grades are associated with 2010 greenspace, a health-promoting neighborhood resource.ObjectivesWe compared 2010 normalized difference vegetation index (NDVI) across previous HOLC neighborhood grades using propensity score restriction and matching.MethodsSecurity map shapefiles were downloaded from the Mapping Inequality Project. Neighborhood investment risk grades included A (best, green), B (blue), C (yellow), and D (hazardous, red, i.e., redlined). We used 2010 satellite imagery to calculate the average NDVI for each HOLC neighborhood. Our main outcomes were 2010 annual average NDVI and summer NDVI. We assigned areal-apportioned 1940 census measures to each HOLC neighborhood. We used propensity score restriction, matching, and targeted maximum likelihood estimation to limit model extrapolation, reduce confounding, and estimate the association between HOLC grade and NDVI for the following comparisons: Grades B vs. A, C vs. B, and D vs. C.ResultsAcross 102 urban areas (4,141 HOLC polygons), annual average ±standard deviation (SD) 2010 NDVI was 0.47 (±0.09), 0.43 (±0.09), 0.39 (±0.09), and 0.36 (±0.10) in Grades A-D, respectively. In analyses adjusted for current ecoregion and census region, 1940s census measures, and 1940s population density, annual average NDVI values in 2010 were estimated at -0.039 (95% CI: -0.045, -0.034), -0.024 (95% CI: -0.030, -0.018), and -0.026 (95% CI: -0.037, -0.015) for Grades B vs. A, C vs. B, and D vs. C, respectively, in the 1930s.DiscussionEstimates adjusted for historical characteristics indicate that neighborhoods assigned worse HOLC grades in the 1930s are associated with reduced present-day greenspace. https://doi.org/10.1289/EHP7495.

Published
2021

196. The role of brain radiotherapy for EGFR- and ALK-positive non-small-cell lung cancer with brain metastases: a review

Author

Nardone, Valerio, Romeo, Caterina, D’Ippolito, Emma, Pastina, Pierpaolo, D’Apolito, Maria, Pirtoli, Luigi, Caraglia, Michele, Mutti, Luciano, Bianco, Giovanna, Falzea, Antonella Consuelo, Giannicola, Rocco, Giordano, Antonio, Tagliaferri, Pierosandro, Vinciguerra, Claudia, Desideri, Isacco, Loi, Mauro, Reginelli, Alfonso, Cappabianca, Salvatore, Tassone, Pierfrancesco, and Correale, Pierpaolo

Published
2023
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199. Tunnel assessment: The Italian case

Author

Lunardi, G., primary, Cassani, G., additional, Gatti, M., additional, Amadi, A., additional, Marchiondelli, A., additional, Malacalza, M., additional, Vitiello, A., additional, Verga, S., additional, Nardone, C., additional, and Selleri, A., additional

Published
2023
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