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1. Effects of a high-dose 24-h infusion of tranexamic acid on death and thromboembolic events in patients with acute gastrointestinal bleeding (HALT-IT): an international randomised, double-blind, placebo-controlled trial

Author

Roberts, Ian, Shakur-Still, Haleema, Afolabi, Adefemi, Akere, Adegboyega, Arribas, Monica, Brenner, Amy, Chaudhri, Rizwana, Gilmore, Ian, Halligan, Kenneth, Hussain, Irshad, Jairath, Vipul, Javaid, Kiran, Kayani, Aasia, Lisman, Ton, Mansukhani, Raoul, Mutti, Muttiullah, Arif Nadeem, Muhammad, Pollok, Richard, Simmons, Jonathan, Soomro, Majid, Stanworth, Simon, Veitch, Andrew, Hawkey, Christopher, Cuzick, Jack, Henry, David, Metcalfe, Chris, Gray, Richard, Barkun, Alan, David, Suresh, Devereaux, Philip, Brady, Tony, Coats, Timothy, Edwards, Phil, Ker, Katharine, Manno, Daniela, Austin, Emma, Bal, Kiran, Balogun, Eni, Barrow, Collette, Beaumont, Danielle, Benyahia, Myriam, Brooks, Imogen, Cargill, Madeleine, Carrington, Laura, Frimley, Lauren, Geer, Amber, Gilbert, Daniel, Gilliam, Catherine, Gil Onandia, Julio, Golfi, Nayia, Hetherington, Daniel, Howe, Courtenay, Hughes, Carolyn, I'anson, David, Jackson, Rob, Joshi, Miland, Kansagra, Sneha, Kawahara, Taemi, Kostrov, Sergey, Miah, Hakim, Ndungu, Bernard, Needham, Kelly, Outtandy, Aroudra, Pearson, Daniel, Pepple, Tracey, Prowse, Danielle, Quashi, Nigel, Quinn, Anna, Ramos, Maria, Ranopa, Laura, Reid, Mia, Roukas, Chris, Squires, Chelci, Tanner, Jemma, Thayne, Andrew, Uddin, Ruhama, Fawole, Bukola, Bello, Folasade Adenike, Olayemi, Oladapo, Okunade, Olujide, Adetayo, Olusade, Khamis, Hussein, Shukri Bin Jahit, Mohammad, Gogichaishvili, Tamar, Mateescu, Radu Bogdan, Adhikaree, Ajay, Abdo, Abdelmounem Eltayeib, Zaher, Mohammad, Deasy, Conor, Alvarez Gregori, Joaquin, Wellsh, Bobby, Lawton, Luke, Kamath, Raghavendra, Barry, Adrian, Carpio, Racquel, Finney, Kay, Maguire, Holly, James, Martin, Coffey, Frank, Gough, Chris, Sawers, Lisa, Thi, Aye-Aye, Burnett, Claire, Jacques, Nicola, Murray, Victoria, Jarman, Heather, Lambe, Christine, Rounding, Sarah, Tucker, Simon, Al-Idari, Romaih, Guest, Samuel, Stoddard, Emma, Yeo, David, Bergin, Colin, Hardy, Elaine, Thunder, Joanne, Jhalli, Paul, Hartley, Edward, Jarvis, Catherine, Swann, Carly, Reed, Matthew, Gallagher, Bernadette, Grahamslaw, Julia, O'Brien, Rachel, Harris, Timothy, Bellhouse, Geoffrey, Boulton, Olivia, Skene, Imogen, Stanley, Adrian, Johnstone, Janet, Maguire, Donogh, Thornton, Susan, Banks, Matthew, Bercades, Georgia, Marks, Daniel, Ryu, Jung, Dowty, Claire, Pott, Jason, East, James, Bailey, Adam, Beer, Sally, Davies, Sian, Appelboam, Andrew, Mackle, Daisy, Small, Jennifer, Vorwerk, Christiane, Atkins, Rachel, Bradbury, Isobel, Bryceland, Catriona, McClelland, Lisa, Thomas, Martin, Clayton, Kate, Michael, Angiy, Haig, Stephen, Al-Nahhas, Saif, Godfrey, Tim, Boger, Philip, Comer, Rachel, Watkins, Barbara, Afolabi, Ola, Afzal, Shazad, Cowton, Amanda, Everett, Simon, Fazakerley, Ruth, Onoviran, Felicia, Snook, Jonathon, Berry, Jackie, Simpson, Diane, Keep, Jeff, Cotton, Hannah, Helyar, Sinead, Rutter, Matthew, Johnston, Tracey, O'Rourke, Laura, Chan, Louisa, Tambellini, Joanna, Trodd, Dawn, Shutt, James, Moreton, Sarah, Oglesby, Abby, Boyle, Adrian, Haeger, Nicola, Hardwick, Susie, Kendall, Jason, Faulkner, Beverley, Worner, Ruth, Hearnshaw, Sarah, Doona, Mary, Price, Maria, Hunter, Laura, Bell, Maggie, Loureiro, Vania, Kehoe, Anthony, Jefferey, Alison, Squire, Rosalyn, Hartin, David, Bell, Stephanie, Newman, Alexandra, Gagg, James, Foot, Jayne, Wakeford, Sue, May, Gabrielle, Bartram, Thomas, Cumpstay, Paul, Parker, Lucy, Das, Rita, Pahary, Sheik, Wright, Gavin, Butt, Georgina, Christmas, Natasha, Wilson, Sarah, Ashfaq, Mohammed, Chandler, Louise, Demetriou, Carrie, Kaye, Philip, Carley, Simon, Brown, Andrew, Jones, Lucy, Whileman, Amanda, Greenaway, John, Tregonning, Julie, Kuhrt, Avril, Goodacre, Steve, Jones, John, Owen, Charlotte, Mitra, Anu, Harper-Payne, Abby, Trudgill, Nigel, Hayes, Anne, Butt, Faheem, Clifford, Gayle, Kinnon, Andrew, Fowler, Susan, Pillay, Kris, Gidwani, Shweta, McNair, Alistair, Omer, Omer, de Weymarn, Tanya, Amin, Adnan, Martin, Jane, Mathieu, Nick, Barnes, Simon, Turvill, James, Sweeting, Helen, Draegebo, Morten, McNaught, Marion, Grocutt, Mandy, Margalef, Jordi, Humphrey, Julian, Jackson, Richard, Bellis, Fionn, Hunt, Jane, Stevenson, Alastair, Watson, Nicholas, Barden, Steven, Paterson, Stuart, Macdonald, Chris, Hobday, David, Orugun, Olu, Allison, Andrew, Dyer, Tristan, McBride, Samuel, Sawicki, Wojciech, Rayner, Ben, Flowerdew, Lynsey, Barbour, Jamie, Klein, Jason, Hood, Stephen, Palmer, Nicola, de Wolff, Jacob, Shenoy, Achuth, Swallow, Peter, Srirajaskanthan, Rajaventhan, Arshad, Hamza, Aslam, Naeem, Bangash, Anam, Qamar, Muhammad, Zahoor, Haroon, Arshad, Saba, ain Ghalib, Quratul, Hameed, Tehseen, Saif, Tayyaba, Shafi, Wajahat, Ali, Abid, Khan, Shehroze, Muaaz, Muhammad, Taj, Ahmad, Ghafoor, Aamir, Afridi, Aamir, Ahmad, Mansoor, Aslam, Mujahid, Kumar, Sandeep, Ali, Mohsin, Bughio, Ubedullah, Chang, Adil, Shaikh, Sana, Ahmad, Syed, Ali, Zeeshan, Waqar, Marium, Mushir, Aiman, Sattar, Sadaf, Goraya, Saifullah, Aslam, Sharmeen, Fatima, Nighat, Noreen, Saadia, Saleem, Sheraz, Rahman, Fazal, Iqbal, Nadeem, Khalid, Mohammad, Riaz, Umar, Umar, Muhammad, Akhter, Tayyab, Khan, Javaria, Misbah, Noureen, Afzal, Muhammad, Kayani, Mobeen, Shah, Syed, Tarar, Shahida, Khan, Sherbat, Iqbal, Yasir, Khan, Essa, Reki, Maqbool, Hussain, Tanveer, Iqbal, Shafqat, Khurram, Muhammad, Shafi, Muhammad, Shaikh, Abrar, Ahmed, Aijaz, Kumar, Ameet, Sachdev, Pinkey, Nasir, Khalid Mahmood, Chaudhry, Zafar Iqbal, Zubair, Muhammad, Tayyab, Ghias, Mushtaq, Junaid, Nasir, Muhammad, Khan, Amir, Ali, Amjad, Ali, Sajjad, Uddin, Wasim, Ahmed, Sohaib, Kazmi, Tazaeen, Channa, Saleh, Aman, Adeeqa, Shaikh, Mouzam, Rizvi, Tahir, Hussain, Amjad, Baqai, Haider Zaigham, Rasheed, Zakawat, Khan, Abdus, Irfan, Adeela, Husain, Aamir, Aslam, Asifa, Yahya, Khalid, Azhar, Salman, Ul Haq, Mansoor, Afzal, Adeel, Imran, Muhammad, Saeed, Iram, Yusuf, Aasim, Hassan, Mariam, Marwat, Mumtaz, Ishfaq, Muhammad, Bashir, Tahir, Kumar, Santosh, Yaqoob, Sajjad, Wahid, Abdul, Fakoya, Tinuola, Oke, Temitope, Tejan, Edries, Olaomi, Oluwole, Badejo, Olawale, Nnaemaka, Okafor, Ukwu, Nancy, Arowolo, Olukayode, Aderounmu, Adewale, Wuraola, Funmilola, Ugiagbe, Rose, Atiri, Alexander, Eghaghe, Enadeghe, Adekoya, Adeleke, Tade, Adedayo Oluyomi, Shonoiki, Olatunji, Olatoke, Samuel, Raji, Toafiq, Ekwunife, Christopher, Onyekpere, Chigozirim, Ahmed, Adamu, Muhammad, Daniyan, Odeghe, Emuobor, Lesi, Olufunmilayo, Osueni, Azeberoje, Samaila, Adamu, Nahuche, Aminu, Ajayi, Akande, Dongo, Andrew, Ijoma, Uchenna, Adebanjo, Ademola Tolulope, Igetei, Rufina, Yilkudi, Monday, Osisanya, Kehinde, Okeke, Edith Nonyelum, Enwere, Oguamanam Okezie, Esmat, Serag, Ashoush, Omar, Naga, Mazen, Nagy, Fady, Saiid, Mostafa, Shaker, Ahmed, Helmy, Ashraf, Saafan, Saafan, Abdel Monem, Mohammed, Din, Jiffre, Azis, Khairul, Brukan, Muhyuddin, Singh, Sanjay, Zakaria, Andee, Farid, Shaik, Hashim, Nizam, Mafauzy, Masykurin, Najmi, Wan, Amri, Nil, Yi, Xin, Hisyam, Mohammad, Ng, Elaine, Ramli, Zuhrirahimi, Yee Lim, Shyang, Voon, Kelvin, Young Yam, Sir, Jahit, Mohammad, Joon, Lee, Melikidze, Besik, Kazaishvili, Davit, Grubelashvili, Nino, Mosidze, Baadur, Tomadze, Gia, Megreladze, Avto, Oprita, Ruxandra, Pestroiu Calescu, Dorina, Chioncel, Camelia, Ragea, Andrei, Mateescu, Bogdan, Busuioc, Bogdan, Voiosu, Andrei, Cotirlet, Adrian, Pintilie, Iulia, Jinga, Mariana, Balaban, Daniel, Tanău, Marcel, Negreanu, Lucian, Bataga, Simona, Priya, Khushboo, Baral, Shankar, K.C., Anuj, Sah, Vijay, Yadav, Vijay, Abdo, Abdelmounem, Ahmed, Dalia, Al Anazi, Marzouqah, Al Balkhi, Areej, Álvarez Gregori, Joaquín, Fornieles Pérez, Helio, and Beqiri, Arben

Published
2020
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2. Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study

Author

Guest, Claire, Dewhirst, Sarah Y, Lindsay, Steve W, Allen, David J, Aziz, Sophie, Baerenbold, Oliver, Bradley, John, Chabildas, Unnati, Chen-Hussey, Vanessa, Clifford, Samuel, Cottis, Luke, Dennehy, Jessica, Foley, Erin, Gezan, Salvador A, Gibson, Tim, Greaves, Courtenay K, Kleinschmidt, Immo, Lambert, Sébastien, Last, Anna, Morant, Steve, Parker, Josephine E A, Pickett, John, Quilty, Billy J, Rooney, Ann, Shah, Manil, Somerville, Mark, Squires, Chelci, Walker, Martin, Logan, James G, Jones, Robert, Assis, Ana, Borthwick, Ewan, Caton, Laura, Edwards, Rachel, Heal, Janette, Hill, David, Jahan, Nazifa, Johnson, Cecelia, Kaye, Angela, Kirkpatrick, Emily, Kisha, Sarah, Ledeatte Williams, Zaena, Moar, Robert, Owonibi, Tolulope, Purcell, Benjamin, Rixson, Christopher, Spencer, Freya, Stefanidis, Anastasios, Stewart, Sophie, Tytheridge, Scott, Wakley, Sian, Wildman, Shanice, Aziz, Catherine, Care, Helen, Curtis, Emily, Dowse, Claire, Makepeace, Alan, Oultram, Sally-Anne, Smith, Jayde, Shenton, Fiona, Hutchins, Harry, Mart, Robert, Cartwright, Jo-anne, Forsey, Miranda, Goodsell, Kerry, Kittridge, Lauren, Nicholson, Anne, Ramos, Angelo, Ritches, Joanne, Setty, Niranjan, Vertue, Mark, Bergstrom, Malin, Chaudhary, Zain, De Wilton, Angus, Gaskell, Kate, Houlihan, Catherine, Jones, Imogen, Margaritis, Marios, Miralhes, Patricia, Owens, Leah, Rampling, Tommy, Rickman, Hannah, Boffito, Marta, Fernandez, Candida, Cotterell, Bryony, Guerdette, Anne-Marie, Tsaknis, George, Turns, Margaret, Walsh, Joanne, Frankland, Lisa, West, Raha, Holland, Maureen, Keenan, Natalie, Wassall, Helen, Young, Megan, Rangeley, Jade, Saalmink, Gwendolyn, Adlakha, Sanjay, Buckley, Philip, Allsop, Lynne, Smith, Susan, Sowter, Donna, Campbell, Alison, Jones, Julie, Laird, Steve, O’Toole, Sarah, Ryan, Courteney, Evans, Jessica, Rand, James, Schumacher, Natasha, Hazelton, Tracey, Dodgson, Andrew, Glasgow, Susannah, Kadiu, Denise, Lopuszansky, Orianne, Oommen, Anu, Prabhu, Joshi, Pursell, Molly, Turner, Jane, Walton, Hollie, Andrews, Robert, Cruickshank, Irena, Thompson, Catherine, Wainwright, Tania, Roebuck, Alun, Lawrence, Tara, Netherton, Kimberley, Hewitt, Claire, Shephardson, Sarah, Crasto, Winston Andrew, Lake, Judith, Musanhu, Rosemary, Walker, Rebecca, Burns, Karen, Higham, Andrew, Le Bas, Julie, Mackenzie, Nicola, Thatcher, Hilary, Beadle, Shannen, Buckley, Sarah, Castle, Gail, Fletcher, Aimee, Holbrook, Sara, Kane, Patricia, Lindley, Kate, Lowry, Tracey, Lupton, Stephanie, Oddy, Sharon, Slater, Lynda, Sylvester, Martin, Agwuh, Kenneth, Maxwell, Veronica, Ryder, Stephen, Topham, Kirsty, Egbuniwe, Obi, Matthews, Rebecca, Arenas-Pinto, Alejandro, Prymas, Paulina, Severn, Abigail, Shaw, Amber, Begum, Safia, Lenton, Daniel, Scriven, James, Leeman, Lucy, Rudge, Karen, Storr, Emma, Alvarez, Ana, Forster, Kate, Hind, Daniel, Cook, Natalie, Peeling, Rosanna, Carey, Peter, Wilson, Anne, and Davis, Jane

Subjects
Volatile Organic Compounds, Dogs, SARS-CoV-2, fungi, Animals, COVID-19, Humans, Mass Screening, General Medicine, Asymptomatic Infections, Sensitivity and Specificity
Abstract

Background A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry. Methods Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening. Results About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95–100) to 100% and specificity from 99% (95% CI 97–100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76–87) to 94% (95% CI 89–98) and specificity ranging from 76% (95% CI 70–82) to 92% (95% CI 88–96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only. Conclusions People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people. Trial Registration NCT04509713 (clinicaltrials.gov).

Published
2022

4. The Curious Case of the Flood in the Night Time

Author

Kuchera, Martin, Price, Jon, O'Rourke, Elizabeth, Lie, Esther, Squires, Chelci, Wilkinson, Alistair, Spurring, Sally, Keith, Lindsay, keith, Lindsay, Griffiths, Wyn, Elizabeth, O'Rourke, Kuchera, Martin, Price, Jon, O'Rourke, Elizabeth, Lie, Esther, Squires, Chelci, Wilkinson, Alistair, Spurring, Sally, Keith, Lindsay, keith, Lindsay, Griffiths, Wyn, and Elizabeth, O'Rourke

Abstract

The Curious Case of the Flood in the Night Time was a brand new immersive theatrical performance created by the authors and performed for the first time in the Albany Theatre, Deptford, London, in February 2018 as part of the SMASHfestUK 2018: Flood! festival (see p24 of brochure for listing). In the play, which was designed for a young audience (Key stage 2 + parents/guardians/family), the audience play the role of the Jury in an inquest into the death of a local man, who was found dead on his houseboat in Deptford Creek. As the inquest proceeds, the audience/jury are shown evidence and testimony from witnesses about the events of the night of the death. This includes forensic tests and other forms of evidence which come together to form a picture of what happened that night. At the end of the performance the Jury have to vote on whether they believe the death was by foul play or natural causes. The evidence points them towards a mosquito-borne disease, the likes of which will become more prevalent in the UK due to the effects of climate change. The play was performed on 2 occasions during SMASHfestUK 2018: Flood! and both performances were sold-out, with 80 tickets available for each showing.

Published
2018

5. Using trained dogs and organic semi-conducting sensors to identify asymptomatic and mild SARS-CoV-2 infections: an observational study.

Author

Guest C, Dewhirst SY, Lindsay SW, Allen DJ, Aziz S, Baerenbold O, Bradley J, Chabildas U, Chen-Hussey V, Clifford S, Cottis L, Dennehy J, Foley E, Gezan SA, Gibson T, Greaves CK, Kleinschmidt I, Lambert S, Last A, Morant S, Parker JEA, Pickett J, Quilty BJ, Rooney A, Shah M, Somerville M, Squires C, Walker M, and Logan JG

Subjects
Animals, Asymptomatic Infections, Humans, Mass Screening, SARS-CoV-2, Sensitivity and Specificity, Volatile Organic Compounds analysis, COVID-19 diagnosis, Dogs
Abstract

Background: A rapid, accurate, non-invasive diagnostic screen is needed to identify people with SARS-CoV-2 infection. We investigated whether organic semi-conducting (OSC) sensors and trained dogs could distinguish between people infected with asymptomatic or mild symptoms, and uninfected individuals, and the impact of screening at ports-of-entry., Methods: Odour samples were collected from adults, and SARS-CoV-2 infection status confirmed using RT-PCR. OSC sensors captured the volatile organic compound (VOC) profile of odour samples. Trained dogs were tested in a double-blind trial to determine their ability to detect differences in VOCs between infected and uninfected individuals, with sensitivity and specificity as the primary outcome. Mathematical modelling was used to investigate the impact of bio-detection dogs for screening., Results: About, 3921 adults were enrolled in the study and odour samples collected from 1097 SARS-CoV-2 infected and 2031 uninfected individuals. OSC sensors were able to distinguish between SARS-CoV-2 infected individuals and uninfected, with sensitivity from 98% (95% CI 95-100) to 100% and specificity from 99% (95% CI 97-100) to 100%. Six dogs were able to distinguish between samples with sensitivity ranging from 82% (95% CI 76-87) to 94% (95% CI 89-98) and specificity ranging from 76% (95% CI 70-82) to 92% (95% CI 88-96). Mathematical modelling suggests that dog screening plus a confirmatory PCR test could detect up to 89% of SARS-CoV-2 infections, averting up to 2.2 times as much transmission compared to isolation of symptomatic individuals only., Conclusions: People infected with SARS-CoV-2, with asymptomatic or mild symptoms, have a distinct odour that can be identified by sensors and trained dogs with a high degree of accuracy. Odour-based diagnostics using sensors and/or dogs may prove a rapid and effective tool for screening large numbers of people.Trial Registration NCT04509713 (clinicaltrials.gov)., (© The Author(s) 2022. Published by Oxford University Press on behalf of International Society of Travel Medicine.)

Published
2022
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