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34 results on '"Adam, Karen"'

1. How Asynchronous Events Encode Video

Author

Adam, Karen, Scholefield, Adam, and Vetterli, Martin

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

As event-based sensing gains in popularity, theoretical understanding is needed to harness this technology's potential. Instead of recording video by capturing frames, event-based cameras have sensors that emit events when their inputs change, thus encoding information in the timing of events. This creates new challenges in establishing reconstruction guarantees and algorithms, but also provides advantages over frame-based video. We use time encoding machines to model event-based sensors: TEMs also encode their inputs by emitting events characterized by their timing and reconstruction from time encodings is well understood. We consider the case of time encoding bandlimited video and demonstrate a dependence between spatial sensor density and overall spatial and temporal resolution. Such a dependence does not occur in frame-based video, where temporal resolution depends solely on the frame rate of the video and spatial resolution depends solely on the pixel grid. However, this dependence arises naturally in event-based video and allows oversampling in space to provide better time resolution. As such, event-based vision encourages using more sensors that emit fewer events over time., Comment: 6 pages, 4 figures

Published
2022

2. A Time Encoding approach to training Spiking Neural Networks

Author

Adam, Karen

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

While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs). In this paper, we provide an extra tool to help us understand and train SNNs by using theory from the field of time encoding. Time encoding machines (TEMs) can be used to model integrate-and-fire neurons and have well-understood reconstruction properties. We will see how one can take inspiration from the field of TEMs to interpret the spike times of SNNs as constraints on the SNNs' weight matrices. More specifically, we study how to train one-layer SNNs by solving a set of linear constraints, and how to train two-layer SNNs by leveraging the all-or-none and asynchronous properties of the spikes emitted by SNNs. These properties of spikes result in an alternative to backpropagation which is not possible in the case of simultaneous and graded activations as in classical ANNs., Comment: 5 pages, 5 figures, submitted to IEEE ICASSP 2022

Published
2021

3. Asynchrony Increases Efficiency: Time Encoding of Videos and Low-Rank Signals

Author

Adam, Karen, Scholefield, Adam, and Vetterli, Martin

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

In event-based sensing, many sensors independently and asynchronously emit events when there is a change in their input. Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling, because (1) the output is a stream of events where the important information lies in the timing of the events, and (2) the sensor can easily be controlled to output information only when interesting activity occurs at the input. Moreover, event-based sampling can often provide better resolution than standard uniform sampling. Not only does this occur because individual event-based sensors have higher temporal resolution, it also occurs because the asynchrony of events allows for less redundant and more informative encoding. We would like to explain how such curious results come about. To do so, we use ideal time encoding machines as a proxy for event-based sensors. We explore time encoding of signals with low rank structure, and apply the resulting theory to video. We then see how the asynchronous firing times of the time encoding machines allow for better reconstruction than in the standard sampling case, if we have a high spatial density of time encoding machines that fire less frequently., Comment: 12 pages, 8 figures

Published
2021
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4. Guardians ad Litem for Children and/or Parents in Family Law Cases involving Substance Use Disorder.

Author

Adam, Karen S.

Subjects
Parent and child (Law) -- Laws, regulations and rules, Guardian ad litem -- Laws, regulations and rules, Substance-related disorders -- Diagnosis -- Care and treatment -- Laws, regulations and rules, Best interests of the child doctrine -- Analysis, Child welfare -- Laws, regulations and rules, Substance abuse -- Care and treatment, Government regulation
Abstract

Substance use disorder (SUD), including alcohol use disorder (AUD), is a complex issue for lawyers and judges in many kinds of cases, including civil, probate, criminal, juvenile, and family. Its [...]

Published
2024

5. Matrix recovery from bilinear and quadratic measurements

Author

Pacholska, Michalina, Adam, Karen, Scholefield, Adam, and Vetterli, Martin

Subjects
Electrical Engineering and Systems Science - Signal Processing, Mathematics - Rings and Algebras, 15A29 (Primary) 15A69, 15A54 (Secondary), G.0
Abstract

Matrix (or operator) recovery from linear measurements is a well-studied problem. However, there are situations where only bilinear or quadratic measurements are available. A bilinear or quadratic problem can easily be transformed into a linear one, but it raises questions when the linearized problem is solvable and what is the cost of linearization. In this work, we study a few specific cases of this general problem and show when the bilinear problem is solvable. Using this result and certain properties of polynomial rings, we present a scenario when the quadratic problem can be linearized at the cost of just a linear number of additional measurements. Finally, we link our results back to two applications that inspired it: Time Encoding Machines and Continuous Localisation., Comment: 19 pages, 4 figures, Changes since the first version: added section on TEMs, fixed typos, added and updated references

Published
2020

6. Encoding and Decoding Mixed Bandlimited Signals using Spiking Integrate-and-Fire Neurons

Author

Adam, Karen, Scholefield, Adam, and Vetterli, Martin

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Conventional sampling focuses on encoding and decoding bandlimited signals by recording signal amplitudes at known time points. Alternately, sampling can be approached using biologically-inspired schemes. Among these are integrate-and-fire time encoding machines (IF-TEMs). They behave like simplified versions of spiking neurons and encode their input using spike times rather than amplitudes. Moreover, when multiple of these neurons jointly process a set of mixed signals, they form one layer in a feedforward spiking neural network. In this paper, we investigate the encoding and decoding potential of such a layer. We propose a setup to sample a set of bandlimited signals, by mixing them and sampling the result using different IF-TEMs. We provide conditions for perfect recovery of the set of signals from the samples in the noiseless case, and suggest an algorithm to perform the reconstruction., Comment: To appear in ICASSP 2020. Code is available at https://github.com/karenadam/Multi-Channel-Time-Encoding

Published
2019

7. Sampling and Reconstruction of Bandlimited Signals with Multi-Channel Time Encoding

Author

Adam, Karen, Scholefield, Adam, and Vetterli, Martin

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Sampling is classically performed by recording the amplitude of an input signal at given time instants; however, sampling and reconstructing a signal using multiple devices in parallel becomes a more difficult problem to solve when the devices have an unknown shift in their clocks. Alternatively, one can record the times at which a signal (or its integral) crosses given thresholds. This can model integrate-and-fire neurons, for example, and has been studied by Lazar and T\'oth under the name of ``Time Encoding Machines''. This sampling method is closer to what is found in nature. In this paper, we show that, when using time encoding machines, reconstruction from multiple channels has a more intuitive solution, and does not require the knowledge of the shifts between machines. We show that, if single-channel time encoding can sample and perfectly reconstruct a $\mathbf{2\Omega}$-bandlimited signal, then $\mathbf{M}$-channel time encoding with shifted integrators can sample and perfectly reconstruct a signal with $\mathbf{M}$ times the bandwidth. Furthermore, we present an algorithm to perform this reconstruction and prove that it converges to the correct unique solution, in the noiseless case, without knowledge of the relative shifts between the integrators of the machines. This is quite unlike classical multi-channel sampling, where unknown shifts between sampling devices pose a problem for perfect reconstruction., Comment: 16 pages, 11 figures. Submitted to Transactions of Signal Processing

Published
2019
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8. IMPACT-Global Hip Fracture Audit: Nosocomial infection, risk prediction and prognostication, minimum reporting standards and global collaborative audit: Lessons from an international multicentre study of 7,090 patients conducted in 14 nations during the COVID-19 pandemic

Author

Abdul-Jabar, Hani, Abu-Rajab, Rashid, Abugarja, Ahmed, Adam, Karen, Aguado Hernández, Héctor J., Améstica Lazcano, Gedeón, Anderson, Sarah, Ansar, Mahmood, Antrobus, Jonathan, Aragón Achig, Esteban Javier, Archunan, Maheswaran, Arrieta Salinas, Mirentxu, Ashford–Wilson, Sarah, Assens Gibert, Cristina, Athanasopoulou, Katerina, Awadelkarim, Mohamed, Baird, Stuart, Bajada, Stefan, Balakrishnan, Shobana, Balasubramanian, Sathishkumar, Ballantyne, James A., Bárcena Goitiandia, Leopoldo, Barkham, Benjamin, Barmpagianni, Christina, Barres-Carsi, Mariano, Barrett, Sarah, Baskaran, Dinnish, Bell, Jean, Bell, Katrina, Bell, Stuart, Bellelli, Giuseppe, Benchimol, Javier Alberto, Boietti, Bruno Rafael, Boswell, Sally, Braile, Adriano, Brennan, Caitlin, Brent, Louise, Brooke, Ben, Bruno, Gaetano, Burahee, Abdus, Burns, Shirley, Calabrò, Giampiero, Campbell, Lucy, Carabelli, Guido Sebastian, Carnegie, Carol, Carretero Cristobal, Guillermo, Caruana, Ethan, Cassinello Ogea, M.a Concepción, Castellanos Robles, Juan, Castillon, Pablo, Chakrabarti, Anil, Cecere, Antonio Benedetto, Chen, Ping, Clarke, Jon V., Collins, Grace, Corrales Cardenal, Jorge E., Corsi, Maurizio, Cózar Adelantado, Gara María, Craxford, Simon, Crooks, Melissa, Cuarental-García, Javier, Cuthbert, Rory, Dall, Graham, Daskalakis, Ioannis, De Cicco, Annalisa, de la Fuente de Dios, Diana, Demaria, Pablo, Dereix, John, Díaz Jiménez, Julian, Dinamarca Montecinos, José Luis, Do Le, Ha Phuong, Donoso Coppa, Juan Pablo, Drosos, Georgios, Duffy, Andrew, East, Jamie, Eastwood, Deborah, Elbahari, Hassan, Elias de Molins Peña, Carmen, Elmamoun, Mamoun, Emmerson, Ben, Escobar Sánchez, Daniel, Faimali, Martina, Farré-Mercadé, Maria Victòria, Farrow, Luke, Fayez, Almari, Fell, Adam, Fenner, Christopher, Ferguson, David, Finlayson, Louise, Flores Gómez, Aldo, Freeman, Nicholas, French, Jonathan, Gabardo Calvo, Santiago, Gagliardo, Nicola, Garcia Albiñana, Joan, García Cruz, Guillermo, García de Cortázar Antolín, Unai, García Virto, Virginia, Gealy, Sophie, Gil Caballero, Sandra Marcela, Gill, Moneet, González González, María Soledad, Gopireddy, Rajesh, Guntley, Diane, Gurung, Binay, Guzmán Rosales, Guadalupe, Haddad, Nedaa, Hafeez, Mahum, Haller, Petra, Halligan, Emer, Hardie, John, Hawker, Imogen, Helal, Amr, Herrera Cruz, Mariana, Herreros Ruiz-Valdepeñas, Ruben, Horton, James, Howells, Sean, Howieson, Alan, Hughes, Luke, Hünicken Torrez, Flavia Lorena, Hurtado Ortega, Ana, Huxley, Peter, Hamid, Hytham K.S., Ilahi, Nida, Iliadis, Alexis, Inman, Dominic, Jadhao, Piyush, Jandoo, Rajan, Jawad, Lucy, Jayatilaka, Malwattage Lara Tania, Jenkins, Paul J., Jeyapalan, Rathan, Johnson, David, Johnston, Andrew, Joseph, Sarah, Kapoor, Siddhant, Karagiannidis, Georgios, Karanam, Krishna Saga, Kattakayam, Freddy, Konarski, Alastair, Kontakis, Georgios, Labrador Hernández, Gregorio, Lancaster, Victoria, Landi, Giovanni, Le, Brian, Liew, Ignatius, Logishetty, Kartik, Lopez Marquez, Andrew Carlomaria Daniel, Lopez, Judit, Lum, Joann, Macpherson, Gavin J., Madan, Suvira, Mahroof, Sabreena, Malik-Tabassum, Khalid, Mallina, Ravi, Maqsood, Afnan, Marson, Ben, Martin Legorburo, M. José, Martin-Perez, Encarna, Martínez Jiménez, Tania, Martinez Martin, Javier, Mayne, Alistair, Mayor, Amy, McAlinden, Gavan, McLean, Lucille, McDonald, Lorna, McIntyre, Joshua, McKay, Pamela, McKean, Greg, McShane, Heather, Medici, Antonio, Meeke, Chelsea, Meldrum, Evonne, Mendez, Mijail, Mercer, Scott, Merino Perez, Josu, Mesa-Lampré, María-Pilar, Mighton, Shuna, Milne, Kirsty, Mohamed Yaseen, Muhammed, Moppett, Iain, Mora, Jesus, Morales-Zumel, Sira, Moreno Fenoll, Irene Blanca, Mousa, Adham, Murray, Alastair W., Murray, Elspeth V., Nair, Radhika, Neary, Fiona, Negri, Giacomo, Negus, Oliver, Newham-Harvey, Fiona, Ng, Nigel, Nightingale, Jess, Noor Mohamed Anver, Sumiya, Nunag, Perrico, O'Hare, Matthew, Ollivere, Ben, Ortés Gómez, Raquel, Owens, AnneMarie, Page, Siobhan, Palloni, Valentina, Panagiotopoulos, Andreas, Panagiotopoulos, Elias, Panesar, Paul, Papadopoulos, Antonios, Spyridon, Papagiannis, Pareja Sierra, Teresa, Park, Chang, Parwaiz, Hammad, Paterson-Byrne, Paul, Patton, Sam, Pearce, Jack, Porter, Marina, Pellegrino, Achille, Pèrez Cuellar, Arturo, Pezzella, Raffaele, Phadnis, Ashish, Pinder, Charlotte, Piper, Danielle, Powell-Bowns, Matilda, Prieto Martín, Rocío, Probert, Annabel, Ramesh, Ashwanth, Ramírez de Arellano, Manuel Vicente Mejía, Renton, Duncan, Rickman, Stephen, Robertson, Alastair, Roche Albero, Adrian, Rodrigo Verguizas, José Alberto, Rodríguez Couso, Myriam, Rooney, Joanna, Sáez-López, Pilar, Saldaña-Díaz, Andres, Santulli, Adriano, Sanz Pérez, Marta Isabel, Sarraf, Khaled M., Scarsbrook, Christine, Scott, Chloe E.H., Scott, Jennifer, Shah, Sachi, Sharaf, Sharief, Sharma, Sidharth, Shirley, Denise, Siano, Antonio, Simpson, James, Singh, Abhinav, Singh, Amit, Sinnett, Tim, Sisodia, Gurudatt, Smith, Philomena, Sophena Bert, Eugenia, Steel, Michael, Stewart, Avril, Stewart, Claire, Sugand, Kapil, Sullivan, Niall, Sweeting, Lauren, Symes, Michael, Tan, Dylan Jun Hao, Tancredi, Francesco, Tatani, Irini, Thomas, Philip, Thomson, Fraser, Toner, Niamh S., Tong, Anna, Toro, Antonio, Tosounidis, Theodoros, Tottas, Stylianos, Trinidad Leo, Andrea, Tucker, Damien, Vemulapalli, Krishna, Ventura Garces, Diego, Vernon, Olivia Katherine, Viveros Garcia, Juan Carlos, Ward, Alex, Ward, Kirsty, Watson, Kate, Weerasuriya, Thisara, Wickramanayake, Udara, Wilkinson, Hannah, Windley, Joseph, Wood, Janet, Wynell-Mayow, William, Zatti, Giovanni, Zeiton, Moez, Zurrón Lobato, Miriam, Hall, Andrew J., Clement, Nicholas D., Ojeda-Thies, Cristina, MacLullich, Alasdair MJ., Toro, Giuseppe, Johansen, Antony, White, Tim O., and Duckworth, Andrew D.

Published
2022
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10. IMPACT-Global Hip Fracture Audit: Nosocomial infection, risk prediction and prognostication, minimum reporting standards and global collaborative audit. Lessons from an international multicentre study of 7,090 patients conducted in 14 nations during the COVID-19 pandemic

Author

Hall, Andrew J., Clement, Nicholas D., Ojeda-Thies, Cristina, MacLullich, Alasdair MJ., Toro, Giuseppe, Johansen, Antony, White, Tim O., Duckworth, Andrew D., Abdul-Jabar, Hani, Abu-Rajab, Rashid, Abugarja, Ahmed, Adam, Karen, Aguado Hernández, Héctor J., Améstica Lazcano, Gedeón, Anderson, Sarah, Ansar, Mahmood, Antrobus, Jonathan, Aragón Achig, Esteban Javier, Archunan, Maheswaran, Arrieta Salinas, Mirentxu, Ashford-Wilson, Sarah, Assens Gibert, Cristina, Athanasopoulou, Katerina, Awadelkarim, Mohamed, Baird, Stuart, Bajada, Stefan, Balakrishnan, Shobana, Balasubramanian, Sathishkumar, Ballantyne, James A., Bárcena Goitiandia, Leopoldo, Barkham, Benjamin, Barmpagianni, Christina, Barres-Carsi, Mariano, Barrett, Sarah, Baskaran, Dinnish, Bell, Jean, Bell, Katrina, Bell, Stuart, Bellelli, Giuseppe, Benchimol, Javier Alberto, Boietti, Bruno Rafael, Boswell, Sally, Braile, Adriano, Brennan, Caitlin, Brent, Louise, Brooke, Ben, Bruno, Gaetano, Burahee, Abdus, Burns, Shirley, Calabrò, Giampiero, Campbell, Lucy, Carabelli, Guido Sebastian, Carnegie, Carol, Carretero Cristobal, Guillermo, Caruana, Ethan, Cassinello Ogea, M. a Concepción, Castellanos Robles, Juan, Castillon, Pablo, Chakrabarti, Anil, Cecere, Antonio Benedetto, Chen, Ping, Clarke, Jon V., Collins, Grace, Corrales Cardenal, Jorge E., Corsi, Maurizio, Cózar Adelantado, Gara María, Craxford, Simon, Crooks, Melissa, Cuarental-García, Javier, Cuthbert, Rory, Dall, Graham, Daskalakis, Ioannis, De Cicco, Annalisa, Diana, de la Fuente de Dios, Demaria, Pablo, Dereix, John, Díaz Jiménez, Julian, Dinamarca Montecinos, José Luis, Do Le, Ha Phuong, Donoso Coppa, Juan Pablo, Drosos, Georgios, Duffy, Andrew, East, Jamie, Eastwood, Deborah, Elbahari, Hassan, Elias de Molins Peña, Carmen, Elmamoun, Mamoun, Emmerson, Ben, Escobar Sánchez, Daniel, Faimali, Martina, Farré-Mercadé, Maria Victòria, Farrow, Luke, Fayez, Almari, Fell, Adam, Fenner, Christopher, Ferguson, David, Finlayson, Louise, Flores Gómez, Aldo, Freeman, Nicholas, French, Jonathan, Gabardo Calvo, Santiago, Gagliardo, Nicola, Garcia Albiñana, Joan, García Cruz, Guillermo, García de Cortázar Antolín, Unai, García Virto, Virginia, Gealy, Sophie, Gil Caballero, Sandra Marcela, Gill, Moneet, González González, María Soledad, Gopireddy, Rajesh, Guntley, Diane, Gurung, Binay, Guzmán Rosales, Guadalupe, Haddad, Nedaa, Hafeez, Mahum, Haller, Petra, Halligan, Emer, Hardie, John, Hawker, Imogen, Helal, Amr, Herrera Cruz, Mariana, Herreros Ruiz-Valdepeñas, Ruben, Horton, James, Howells, Sean, Howieson, Alan, Hughes, Luke, Hünicken Torrez, Flavia Lorena, Hurtado Ortega, Ana, Huxley, Peter, Hamid, Hytham K. S., Ilahi, Nida, Iliadis, Alexis, Inman, Dominic, Jadhao, Piyush, Jandoo, Rajan, Jawad, Lucy, Jayatilaka, Malwattage Lara Tania, Jenkins, Paul J., Jeyapalan, Rathan, Johnson, David, Johnston, Andrew, Joseph, Sarah, Kapoor, Siddhant, Karagiannidis, Georgios, Karanam, Krishna Saga, Kattakayam, Freddy, Konarski, Alastair, Kontakis, Georgios, Labrador Hernández, Gregorio, Lancaster, Victoria, Landi, Giovanni, Le, Brian, Liew, Ignatius, Logishetty, Kartik, Lopez Marquez, Andrew Carlomaria Daniel, Lopez, Judit, Lum, Joann, Macpherson, Gavin J., Madan, Suvira, Mahroof, Sabreena, Malik-Tabassum, Khalid, Mallina, Ravi, Maqsood, Afnan, Marson, Ben, Martin Legorburo, M José, Martin-Perez, Encarna, Martínez Jiménez, Tania, Martinez Martin, Javier, Mayne, Alistair, Mayor, Amy, McAlinden, Gavan, McLean, Lucille, McDonald, Lorna, McIntyre, Joshua, McKay, Pamela, McKean, Greg, McShane, Heather, Medici, Antonio, Meeke, Chelsea, Meldrum, Evonne, Mendez, Mijail, Mercer, Scott, Merino Perez, Josu, Mesa-Lampré, María-Pilar, Mighton, Shuna, Milne, Kirsty, Mohamed Yaseen, Muhammed, Moppett, Iain, Mora, Jesus, Morales-Zumel, Sira, Moreno Fenoll, Irene Blanca, Mousa, Adham, Murray, Alastair W., Murray, Elspeth V., Nair, Radhika, Neary, Fiona, Negri, Giacomo, Negus, Oliver, Newham-Harvey, Fiona, Ng, Nigel, Nightingale, Jess, Noor Mohamed Anver, Sumiya, Nunag, Perrico, O'Hare, Matthew, Ollivere, Ben, Ortés Gómez, Raquel, Owens, AnneMarie, Page, Siobhan, Palloni, Valentina, Panagiotopoulos, Andreas, Panagiotopoulos, Elias, Panesar, Paul, Papadopoulos, Antonios, Spyridon, Papagiannis, Pareja Sierra, Teresa, Park, Chang, Parwaiz, Hammad, Paterson-Byrne, Paul, Patton, Sam, Pearce, Jack, Porter, Marina, Pellegrino, Achille, Pèrez Cuellar, Arturo, Pezzella, Raffaele, Phadnis, Ashish, Pinder, Charlotte, Piper, Danielle, Powell-Bowns, Matilda, Prieto Martín, Rocío, Probert, Annabel, Ramesh, Ashwanth, Ramírez de Arellano, Manuel Vicente Mejía, Renton, Duncan, Rickman, Stephen, Robertson, Alastair, Roche Albero, Adrian, Rodrigo Verguizas, José Alberto, Rodríguez Couso, Myriam, Rooney, Joanna, Sáez-López, Pilar, Saldaña-Díaz, Andres, Santulli, Adriano, Sanz Pérez, Marta Isabel, Sarraf, Khaled M., Scarsbrook, Christine, Scott, Chloe E. H., Scott, Jennifer, Shah, Sachi, Sharaf, Sharief, Sharma, Sidharth, Shirley, Denise, Siano, Antonio, Simpson, James, Singh, Abhinav, Singh, Amit, Sinnett, Tim, Sisodia, Gurudatt, Smith, Philomena, Sophena Bert, Eugenia, Steel, Michael, Stewart, Avril, Stewart, Claire, Sugand, Kapil, Sullivan, Niall, Sweeting, Lauren, Symes, Michael, Tan, Dylan Jun Hao, Tancredi, Francesco, Tatani, Irini, Thomas, Philip, Thomson, Fraser, Toner, Niamh S., Tong, Anna, Toro, Antonio, Tosounidis, Theodoros, Tottas, Stylianos, Trinidad Leo, Andrea, Tucker, Damien, Vemulapalli, Krishna, Ventura Garces, Diego, Vernon, Olivia Katherine, Viveros Garcia, Juan Carlos, Ward, Alex, Ward, Kirsty, Watson, Kate, Weerasuriya, Thisara, Wickramanayake, Udara, Wilkinson, Hannah, Windley, Joseph, Wood, Janet, Wynell-Mayow, William, Zatti, Giovanni, Zeiton, Moez, Zurrón Lobato, Miriam, Hall, A, Clement, N, Ojeda-Thies, C, Maclullich, A, Toro, G, Johansen, A, White, T, Duckworth, A, Abdul-Jabar, H, Abu-Rajab, R, Abugarja, A, Adam, K, Aguado Hernández, H, Améstica Lazcano, G, Anderson, S, Ansar, M, Antrobus, J, Aragón Achig, E, Archunan, M, Arrieta Salinas, M, Ashford-Wilson, S, Assens Gibert, C, Athanasopoulou, K, Awadelkarim, M, Baird, S, Bajada, S, Balakrishnan, S, Balasubramanian, S, Ballantyne, J, Bárcena Goitiandia, L, Barkham, B, Barmpagianni, C, Barres-Carsi, M, Barrett, S, Baskaran, D, Bell, J, Bell, K, Bell, S, Bellelli, G, Benchimol, J, Boietti, B, Boswell, S, Braile, A, Brennan, C, Brent, L, Brooke, B, Bruno, G, Burahee, A, Burns, S, Calabrò, G, Campbell, L, Carabelli, G, Carnegie, C, Carretero Cristobal, G, Caruana, E, Cassinello Ogea, M, Castellanos Robles, J, Castillon, P, Chakrabarti, A, Cecere, A, Chen, P, Clarke, J, Collins, G, Corrales Cardenal, J, Corsi, M, Cózar Adelantado, G, Craxford, S, Crooks, M, Cuarental-García, J, Cuthbert, R, Dall, G, Daskalakis, I, De Cicco, A, Diana, D, Demaria, P, Dereix, J, Díaz Jiménez, J, Dinamarca Montecinos, J, Do Le, H, Donoso Coppa, J, Drosos, G, Duffy, A, East, J, Eastwood, D, Elbahari, H, Elias de Molins Peña, C, Elmamoun, M, Emmerson, B, Escobar Sánchez, D, Faimali, M, Farré-Mercadé, M, Farrow, L, Fayez, A, Fell, A, Fenner, C, Ferguson, D, Finlayson, L, Flores Gómez, A, Freeman, N, French, J, Gabardo Calvo, S, Gagliardo, N, Garcia Albiñana, J, García Cruz, G, García de Cortázar Antolín, U, García Virto, V, Gealy, S, Gil Caballero, S, Gill, M, González González, M, Gopireddy, R, Guntley, D, Gurung, B, Guzmán Rosales, G, Haddad, N, Hafeez, M, Haller, P, Halligan, E, Hardie, J, Hawker, I, Helal, A, Herrera Cruz, M, Herreros Ruiz-Valdepeñas, R, Horton, J, Howells, S, Howieson, A, Hughes, L, Hünicken Torrez, F, Hurtado Ortega, A, Huxley, P, Hamid, H, Ilahi, N, Iliadis, A, Inman, D, Jadhao, P, Jandoo, R, Jawad, L, Jayatilaka, M, Jenkins, P, Jeyapalan, R, Johnson, D, Johnston, A, Joseph, S, Kapoor, S, Karagiannidis, G, Karanam, K, Kattakayam, F, Konarski, A, Kontakis, G, Labrador Hernández, G, Lancaster, V, Landi, G, Le, B, Liew, I, Logishetty, K, Lopez Marquez, A, Lopez, J, Lum, J, Macpherson, G, Madan, S, Mahroof, S, Malik-Tabassum, K, Mallina, R, Maqsood, A, Marson, B, Martin Legorburo, M, Martin-Perez, E, Martínez Jiménez, T, Martinez Martin, J, Mayne, A, Mayor, A, Mcalinden, G, Mclean, L, Mcdonald, L, Mcintyre, J, Mckay, P, Mckean, G, Mcshane, H, Medici, A, Meeke, C, Meldrum, E, Mendez, M, Mercer, S, Merino Perez, J, Mesa-Lampré, M, Mighton, S, Milne, K, Mohamed Yaseen, M, Moppett, I, Mora, J, Morales-Zumel, S, Moreno Fenoll, I, Mousa, A, Murray, A, Murray, E, Nair, R, Neary, F, Negri, G, Negus, O, Newham-Harvey, F, Ng, N, Nightingale, J, Noor Mohamed Anver, S, Nunag, P, O'Hare, M, Ollivere, B, Ortés Gómez, R, Owens, A, Page, S, Palloni, V, Panagiotopoulos, A, Panagiotopoulos, E, Panesar, P, Papadopoulos, A, Spyridon, P, Pareja Sierra, T, Park, C, Parwaiz, H, Paterson-Byrne, P, Patton, S, Pearce, J, Porter, M, Pellegrino, A, Pèrez Cuellar, A, Pezzella, R, Phadnis, A, Pinder, C, Piper, D, Powell-Bowns, M, Prieto Martín, R, Probert, A, Ramesh, A, Ramírez de Arellano, M, Renton, D, Rickman, S, Robertson, A, Roche Albero, A, Rodrigo Verguizas, J, Rodríguez Couso, M, Rooney, J, Sáez-López, P, Saldaña-Díaz, A, Santulli, A, Sanz Pérez, M, Sarraf, K, Scarsbrook, C, Scott, C, Scott, J, Shah, S, Sharaf, S, Sharma, S, Shirley, D, Siano, A, Simpson, J, Singh, A, Sinnett, T, Sisodia, G, Smith, P, Sophena Bert, E, Steel, M, Stewart, A, Stewart, C, Sugand, K, Sullivan, N, Sweeting, L, Symes, M, Tan, D, Tancredi, F, Tatani, I, Thomas, P, Thomson, F, Toner, N, Tong, A, Toro, A, Tosounidis, T, Tottas, S, Trinidad Leo, A, Tucker, D, Vemulapalli, K, Ventura Garces, D, Vernon, O, Viveros Garcia, J, Ward, A, Ward, K, Watson, K, Weerasuriya, T, Wickramanayake, U, Wilkinson, H, Windley, J, Wood, J, Wynell-Mayow, W, Zatti, G, Zeiton, M, Zurrón Lobato, M, Hall, Andrew J., Clement, Nicholas D., Ojeda-Thies, Cristina, Maclullich, Alasdair MJ., Toro, Giuseppe, Johansen, Antony, White, Tim O., Duckworth, Andrew D., Abdul-Jabar, Hani, Abu-Rajab, Rashid, Abugarja, Ahmed, Adam, Karen, Aguado Hernández, Héctor J., Améstica Lazcano, Gedeón, Anderson, Sarah, Ansar, Mahmood, Antrobus, Jonathan, Aragón Achig, Esteban Javier, Archunan, Maheswaran, Arrieta Salinas, Mirentxu, Ashford-Wilson, Sarah, Assens Gibert, Cristina, Athanasopoulou, Katerina, Awadelkarim, Mohamed, Baird, Stuart, Bajada, Stefan, Balakrishnan, Shobana, Balasubramanian, Sathishkumar, Ballantyne, James A., Bárcena Goitiandia, Leopoldo, Barkham, Benjamin, Barmpagianni, Christina, Barres-Carsi, Mariano, Barrett, Sarah, Baskaran, Dinnish, Bell, Jean, Bell, Katrina, Bell, Stuart, Bellelli, Giuseppe, Benchimol, Javier Alberto, Boietti, Bruno Rafael, Boswell, Sally, Braile, Adriano, Brennan, Caitlin, Brent, Louise, Brooke, Ben, Bruno, Gaetano, Burahee, Abdu, Burns, Shirley, Calabrò, Giampiero, Campbell, Lucy, Carabelli, Guido Sebastian, Carnegie, Carol, Carretero Cristobal, Guillermo, Caruana, Ethan, Cassinello Ogea, M. a Concepción, Castellanos Robles, Juan, Castillon, Pablo, Chakrabarti, Anil, Cecere, Antonio Benedetto, Chen, Ping, Clarke, Jon V., Collins, Grace, Corrales Cardenal, Jorge E., Corsi, Maurizio, Cózar Adelantado, Gara María, Craxford, Simon, Crooks, Melissa, Cuarental-García, Javier, Cuthbert, Rory, Dall, Graham, Daskalakis, Ioanni, De Cicco, Annalisa, Diana, de la Fuente de Dio, Demaria, Pablo, Dereix, John, Díaz Jiménez, Julian, Dinamarca Montecinos, José Lui, Do Le, Ha Phuong, Donoso Coppa, Juan Pablo, Drosos, Georgio, Duffy, Andrew, East, Jamie, Eastwood, Deborah, Elbahari, Hassan, Elias de Molins Peña, Carmen, Elmamoun, Mamoun, Emmerson, Ben, Escobar Sánchez, Daniel, Faimali, Martina, Farré-Mercadé, Maria Victòria, Farrow, Luke, Fayez, Almari, Fell, Adam, Fenner, Christopher, Ferguson, David, Finlayson, Louise, Flores Gómez, Aldo, Freeman, Nichola, French, Jonathan, Gabardo Calvo, Santiago, Gagliardo, Nicola, Garcia Albiñana, Joan, García Cruz, Guillermo, García de Cortázar Antolín, Unai, García Virto, Virginia, Gealy, Sophie, Gil Caballero, Sandra Marcela, Gill, Moneet, González González, María Soledad, Gopireddy, Rajesh, Guntley, Diane, Gurung, Binay, Guzmán Rosales, Guadalupe, Haddad, Nedaa, Hafeez, Mahum, Haller, Petra, Halligan, Emer, Hardie, John, Hawker, Imogen, Helal, Amr, Herrera Cruz, Mariana, Herreros Ruiz-Valdepeñas, Ruben, Horton, Jame, Howells, Sean, Howieson, Alan, Hughes, Luke, Hünicken Torrez, Flavia Lorena, Hurtado Ortega, Ana, Huxley, Peter, Hamid, Hytham K. S., Ilahi, Nida, Iliadis, Alexi, Inman, Dominic, Jadhao, Piyush, Jandoo, Rajan, Jawad, Lucy, Jayatilaka, Malwattage Lara Tania, Jenkins, Paul J., Jeyapalan, Rathan, Johnson, David, Johnston, Andrew, Joseph, Sarah, Kapoor, Siddhant, Karagiannidis, Georgio, Karanam, Krishna Saga, Kattakayam, Freddy, Konarski, Alastair, Kontakis, Georgio, Labrador Hernández, Gregorio, Lancaster, Victoria, Landi, Giovanni, Le, Brian, Liew, Ignatiu, Logishetty, Kartik, Lopez Marquez, Andrew Carlomaria Daniel, Lopez, Judit, Lum, Joann, Macpherson, Gavin J., Madan, Suvira, Mahroof, Sabreena, Malik-Tabassum, Khalid, Mallina, Ravi, Maqsood, Afnan, Marson, Ben, Martin Legorburo, M José, Martin-Perez, Encarna, Martínez Jiménez, Tania, Martinez Martin, Javier, Mayne, Alistair, Mayor, Amy, Mcalinden, Gavan, Mclean, Lucille, Mcdonald, Lorna, Mcintyre, Joshua, Mckay, Pamela, Mckean, Greg, Mcshane, Heather, Medici, Antonio, Meeke, Chelsea, Meldrum, Evonne, Mendez, Mijail, Mercer, Scott, Merino Perez, Josu, Mesa-Lampré, María-Pilar, Mighton, Shuna, Milne, Kirsty, Mohamed Yaseen, Muhammed, Moppett, Iain, Mora, Jesu, Morales-Zumel, Sira, Moreno Fenoll, Irene Blanca, Mousa, Adham, Murray, Alastair W., Murray, Elspeth V., Nair, Radhika, Neary, Fiona, Negri, Giacomo, Negus, Oliver, Newham-Harvey, Fiona, Ng, Nigel, Nightingale, Je, Noor Mohamed Anver, Sumiya, Nunag, Perrico, O'Hare, Matthew, Ollivere, Ben, Ortés Gómez, Raquel, Owens, Annemarie, Page, Siobhan, Palloni, Valentina, Panagiotopoulos, Andrea, Panagiotopoulos, Elia, Panesar, Paul, Papadopoulos, Antonio, Spyridon, Papagianni, Pareja Sierra, Teresa, Park, Chang, Parwaiz, Hammad, Paterson-Byrne, Paul, Patton, Sam, Pearce, Jack, Porter, Marina, Pellegrino, Achille, Pèrez Cuellar, Arturo, Pezzella, Raffaele, Phadnis, Ashish, Pinder, Charlotte, Piper, Danielle, Powell-Bowns, Matilda, Prieto Martín, Rocío, Probert, Annabel, Ramesh, Ashwanth, Ramírez de Arellano, Manuel Vicente Mejía, Renton, Duncan, Rickman, Stephen, Robertson, Alastair, Roche Albero, Adrian, Rodrigo Verguizas, José Alberto, Rodríguez Couso, Myriam, Rooney, Joanna, Sáez-López, Pilar, Saldaña-Díaz, Andre, Santulli, Adriano, Sanz Pérez, Marta Isabel, Sarraf, Khaled M., Scarsbrook, Christine, Scott, Chloe E. H., Scott, Jennifer, Shah, Sachi, Sharaf, Sharief, Sharma, Sidharth, Shirley, Denise, Siano, Antonio, Simpson, Jame, Singh, Abhinav, Singh, Amit, Sinnett, Tim, Sisodia, Gurudatt, Smith, Philomena, Sophena Bert, Eugenia, Steel, Michael, Stewart, Avril, Stewart, Claire, Sugand, Kapil, Sullivan, Niall, Sweeting, Lauren, Symes, Michael, Tan, Dylan Jun Hao, Tancredi, Francesco, Tatani, Irini, Thomas, Philip, Thomson, Fraser, Toner, Niamh S., Tong, Anna, Toro, Antonio, Tosounidis, Theodoro, Tottas, Styliano, Trinidad Leo, Andrea, Tucker, Damien, Vemulapalli, Krishna, Ventura Garces, Diego, Vernon, Olivia Katherine, Viveros Garcia, Juan Carlo, Ward, Alex, Ward, Kirsty, Watson, Kate, Weerasuriya, Thisara, Wickramanayake, Udara, Wilkinson, Hannah, Windley, Joseph, Wood, Janet, Wynell-Mayow, William, Zatti, Giovanni, Zeiton, Moez, and Zurrón Lobato, Miriam

Subjects
Risk, Frailty, Communicable disease, Prognosi, COVID-19, Audit, Orthopaedic, Trauma, Hip fracture, Reporting standard, Meta-audit, Nosocomial, Infection, Geriatric, Outcome
Abstract

Aims: This international study aimed to assess: 1) the prevalence of preoperative and postoperative COVID-19 among patients with hip fracture, 2) the effect on 30-day mortality, and 3) clinical factors associated with the infection and with mortality in COVID-19-positive patients. Methods: A multicentre collaboration among 112 centres in 14 countries collected data on all patients presenting with a hip fracture between 1st March-31st May 2020. Demographics, residence, place of injury, presentation blood tests, Nottingham Hip Fracture Score, time to surgery, management, ASA grade, length of stay, COVID-19 and 30-day mortality status were recorded. Results: A total of 7090 patients were included, with a mean age of 82.2 (range 50–104) years and 4959 (69.9%) being female. Of 651 (9.2%) patients diagnosed with COVID-19, 225 (34.6%) were positive at presentation and 426 (65.4%) were positive postoperatively. Positive COVID-19 status was independently associated with male sex (odds ratio (OR) 1.38, p = 0.001), residential care (OR 2.15, p < 0.001), inpatient fall (OR 2.23, p = 0.003), cancer (OR 0.63, p = 0.009), ASA grades 4 (OR 1.59, p = 0.008) or 5 (OR 8.28, p < 0.001), and longer admission (OR 1.06 for each increasing day, p < 0.001). Patients with COVID-19 at any time had a significantly lower chance of 30-day survival versus those without COVID-19 (72.7% versus 92.6%, p < 0.001). COVID-19 was independently associated with an increased 30-day mortality risk (hazard ratio (HR) 2.83, p < 0.001). Increasing age (HR 1.03, p = 0.028), male sex (HR 2.35, p < 0.001), renal disease (HR 1.53, p = 0.017), and pulmonary disease (HR 1.45, p = 0.039) were independently associated with a higher 30-day mortality risk in patients with COVID-19 when adjusting for confounders. Conclusion: The prevalence of COVID-19 in hip fracture patients during the first wave of the pandemic was 9%, and was independently associated with a three-fold increased 30-day mortality risk. Among COVID-19-positive patients, those who were older, male, with renal or pulmonary disease had a significantly higher 30-day mortality risk.

Published
2022

11. IMPACT-Global Hip Fracture Audit: Nosocomial infection, risk prediction and prognostication, minimum reporting standards and global collaborative audit

Author

Hall, Andrew J., primary, Clement, Nicholas D., additional, Ojeda-Thies, Cristina, additional, MacLullich, Alasdair MJ., additional, Toro, Giuseppe, additional, Johansen, Antony, additional, White, Tim O., additional, Duckworth, Andrew D., additional, Abdul-Jabar, Hani, additional, Abu-Rajab, Rashid, additional, Abugarja, Ahmed, additional, Adam, Karen, additional, Aguado Hernández, Héctor J., additional, Améstica Lazcano, Gedeón, additional, Anderson, Sarah, additional, Ansar, Mahmood, additional, Antrobus, Jonathan, additional, Aragón Achig, Esteban Javier, additional, Archunan, Maheswaran, additional, Arrieta Salinas, Mirentxu, additional, Ashford–Wilson, Sarah, additional, Assens Gibert, Cristina, additional, Athanasopoulou, Katerina, additional, Awadelkarim, Mohamed, additional, Baird, Stuart, additional, Bajada, Stefan, additional, Balakrishnan, Shobana, additional, Balasubramanian, Sathishkumar, additional, Ballantyne, James A., additional, Bárcena Goitiandia, Leopoldo, additional, Barkham, Benjamin, additional, Barmpagianni, Christina, additional, Barres-Carsi, Mariano, additional, Barrett, Sarah, additional, Baskaran, Dinnish, additional, Bell, Jean, additional, Bell, Katrina, additional, Bell, Stuart, additional, Bellelli, Giuseppe, additional, Benchimol, Javier Alberto, additional, Boietti, Bruno Rafael, additional, Boswell, Sally, additional, Braile, Adriano, additional, Brennan, Caitlin, additional, Brent, Louise, additional, Brooke, Ben, additional, Bruno, Gaetano, additional, Burahee, Abdus, additional, Burns, Shirley, additional, Calabrò, Giampiero, additional, Campbell, Lucy, additional, Carabelli, Guido Sebastian, additional, Carnegie, Carol, additional, Carretero Cristobal, Guillermo, additional, Caruana, Ethan, additional, Cassinello Ogea, M.a Concepción, additional, Castellanos Robles, Juan, additional, Castillon, Pablo, additional, Chakrabarti, Anil, additional, Cecere, Antonio Benedetto, additional, Chen, Ping, additional, Clarke, Jon V., additional, Collins, Grace, additional, Corrales Cardenal, Jorge E., additional, Corsi, Maurizio, additional, Cózar Adelantado, Gara María, additional, Craxford, Simon, additional, Crooks, Melissa, additional, Cuarental-García, Javier, additional, Cuthbert, Rory, additional, Dall, Graham, additional, Daskalakis, Ioannis, additional, De Cicco, Annalisa, additional, de la Fuente de Dios, Diana, additional, Demaria, Pablo, additional, Dereix, John, additional, Díaz Jiménez, Julian, additional, Dinamarca Montecinos, José Luis, additional, Do Le, Ha Phuong, additional, Donoso Coppa, Juan Pablo, additional, Drosos, Georgios, additional, Duffy, Andrew, additional, East, Jamie, additional, Eastwood, Deborah, additional, Elbahari, Hassan, additional, Elias de Molins Peña, Carmen, additional, Elmamoun, Mamoun, additional, Emmerson, Ben, additional, Escobar Sánchez, Daniel, additional, Faimali, Martina, additional, Farré-Mercadé, Maria Victòria, additional, Farrow, Luke, additional, Fayez, Almari, additional, Fell, Adam, additional, Fenner, Christopher, additional, Ferguson, David, additional, Finlayson, Louise, additional, Flores Gómez, Aldo, additional, Freeman, Nicholas, additional, French, Jonathan, additional, Gabardo Calvo, Santiago, additional, Gagliardo, Nicola, additional, Garcia Albiñana, Joan, additional, García Cruz, Guillermo, additional, García de Cortázar Antolín, Unai, additional, García Virto, Virginia, additional, Gealy, Sophie, additional, Gil Caballero, Sandra Marcela, additional, Gill, Moneet, additional, González González, María Soledad, additional, Gopireddy, Rajesh, additional, Guntley, Diane, additional, Gurung, Binay, additional, Guzmán Rosales, Guadalupe, additional, Haddad, Nedaa, additional, Hafeez, Mahum, additional, Haller, Petra, additional, Halligan, Emer, additional, Hardie, John, additional, Hawker, Imogen, additional, Helal, Amr, additional, Herrera Cruz, Mariana, additional, Herreros Ruiz-Valdepeñas, Ruben, additional, Horton, James, additional, Howells, Sean, additional, Howieson, Alan, additional, Hughes, Luke, additional, Hünicken Torrez, Flavia Lorena, additional, Hurtado Ortega, Ana, additional, Huxley, Peter, additional, Hamid, Hytham K.S., additional, Ilahi, Nida, additional, Iliadis, Alexis, additional, Inman, Dominic, additional, Jadhao, Piyush, additional, Jandoo, Rajan, additional, Jawad, Lucy, additional, Jayatilaka, Malwattage Lara Tania, additional, Jenkins, Paul J., additional, Jeyapalan, Rathan, additional, Johnson, David, additional, Johnston, Andrew, additional, Joseph, Sarah, additional, Kapoor, Siddhant, additional, Karagiannidis, Georgios, additional, Karanam, Krishna Saga, additional, Kattakayam, Freddy, additional, Konarski, Alastair, additional, Kontakis, Georgios, additional, Labrador Hernández, Gregorio, additional, Lancaster, Victoria, additional, Landi, Giovanni, additional, Le, Brian, additional, Liew, Ignatius, additional, Logishetty, Kartik, additional, Lopez Marquez, Andrew Carlomaria Daniel, additional, Lopez, Judit, additional, Lum, Joann, additional, Macpherson, Gavin J., additional, Madan, Suvira, additional, Mahroof, Sabreena, additional, Malik-Tabassum, Khalid, additional, Mallina, Ravi, additional, Maqsood, Afnan, additional, Marson, Ben, additional, Martin Legorburo, M. José, additional, Martin-Perez, Encarna, additional, Martínez Jiménez, Tania, additional, Martinez Martin, Javier, additional, Mayne, Alistair, additional, Mayor, Amy, additional, McAlinden, Gavan, additional, McLean, Lucille, additional, McDonald, Lorna, additional, McIntyre, Joshua, additional, McKay, Pamela, additional, McKean, Greg, additional, McShane, Heather, additional, Medici, Antonio, additional, Meeke, Chelsea, additional, Meldrum, Evonne, additional, Mendez, Mijail, additional, Mercer, Scott, additional, Merino Perez, Josu, additional, Mesa-Lampré, María-Pilar, additional, Mighton, Shuna, additional, Milne, Kirsty, additional, Mohamed Yaseen, Muhammed, additional, Moppett, Iain, additional, Mora, Jesus, additional, Morales-Zumel, Sira, additional, Moreno Fenoll, Irene Blanca, additional, Mousa, Adham, additional, Murray, Alastair W., additional, Murray, Elspeth V., additional, Nair, Radhika, additional, Neary, Fiona, additional, Negri, Giacomo, additional, Negus, Oliver, additional, Newham-Harvey, Fiona, additional, Ng, Nigel, additional, Nightingale, Jess, additional, Noor Mohamed Anver, Sumiya, additional, Nunag, Perrico, additional, O'Hare, Matthew, additional, Ollivere, Ben, additional, Ortés Gómez, Raquel, additional, Owens, AnneMarie, additional, Page, Siobhan, additional, Palloni, Valentina, additional, Panagiotopoulos, Andreas, additional, Panagiotopoulos, Elias, additional, Panesar, Paul, additional, Papadopoulos, Antonios, additional, Spyridon, Papagiannis, additional, Pareja Sierra, Teresa, additional, Park, Chang, additional, Parwaiz, Hammad, additional, Paterson-Byrne, Paul, additional, Patton, Sam, additional, Pearce, Jack, additional, Porter, Marina, additional, Pellegrino, Achille, additional, Pèrez Cuellar, Arturo, additional, Pezzella, Raffaele, additional, Phadnis, Ashish, additional, Pinder, Charlotte, additional, Piper, Danielle, additional, Powell-Bowns, Matilda, additional, Prieto Martín, Rocío, additional, Probert, Annabel, additional, Ramesh, Ashwanth, additional, Ramírez de Arellano, Manuel Vicente Mejía, additional, Renton, Duncan, additional, Rickman, Stephen, additional, Robertson, Alastair, additional, Roche Albero, Adrian, additional, Rodrigo Verguizas, José Alberto, additional, Rodríguez Couso, Myriam, additional, Rooney, Joanna, additional, Sáez-López, Pilar, additional, Saldaña-Díaz, Andres, additional, Santulli, Adriano, additional, Sanz Pérez, Marta Isabel, additional, Sarraf, Khaled M., additional, Scarsbrook, Christine, additional, Scott, Chloe E.H., additional, Scott, Jennifer, additional, Shah, Sachi, additional, Sharaf, Sharief, additional, Sharma, Sidharth, additional, Shirley, Denise, additional, Siano, Antonio, additional, Simpson, James, additional, Singh, Abhinav, additional, Singh, Amit, additional, Sinnett, Tim, additional, Sisodia, Gurudatt, additional, Smith, Philomena, additional, Sophena Bert, Eugenia, additional, Steel, Michael, additional, Stewart, Avril, additional, Stewart, Claire, additional, Sugand, Kapil, additional, Sullivan, Niall, additional, Sweeting, Lauren, additional, Symes, Michael, additional, Tan, Dylan Jun Hao, additional, Tancredi, Francesco, additional, Tatani, Irini, additional, Thomas, Philip, additional, Thomson, Fraser, additional, Toner, Niamh S., additional, Tong, Anna, additional, Toro, Antonio, additional, Tosounidis, Theodoros, additional, Tottas, Stylianos, additional, Trinidad Leo, Andrea, additional, Tucker, Damien, additional, Vemulapalli, Krishna, additional, Ventura Garces, Diego, additional, Vernon, Olivia Katherine, additional, Viveros Garcia, Juan Carlos, additional, Ward, Alex, additional, Ward, Kirsty, additional, Watson, Kate, additional, Weerasuriya, Thisara, additional, Wickramanayake, Udara, additional, Wilkinson, Hannah, additional, Windley, Joseph, additional, Wood, Janet, additional, Wynell-Mayow, William, additional, Zatti, Giovanni, additional, Zeiton, Moez, additional, and Zurrón Lobato, Miriam, additional

Published
2022
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13. Licensed Legal Advocates: A Randomized Study of Non-Lawyer Services for Survivors of Domestic Violence

Author

Findley, Jessica, Griffin, Christopher, Butler, Stacy, and Adam, Karen

Subjects
Legal Profession, Other Social and Behavioral Sciences, FOS: Law, Law and Society, Social and Behavioral Sciences, Law, Family Law
Abstract

The purpose of this study is to empirically evaluate the success of a new model of legal services provision for survivors of domestic violence. The State of Arizona approved Licensed Legal Advocates to provide limited legal advice to survivors within a narrowly defined scope of service (e.g., family law, orders of protection). Licensed Legal Advocates will operate on a pilot basis in Pima County (Tucson), AZ, and field partner Emerge! Center Against Domestic Abuse will provide services. Consenting participants in Emerge programs for survivors will be randomized to work with a Licensed Legal Advocate (who may offer limited advice) or a Lay Legal Advocate (who may only offer information on legal procedures and forms). The current standard of care for legal information is provided by Lay Legal Advocates. The study team hypothesizes that the Licensed Advocates will have a measurable effect on whether and how efficiently survivors’ civil legal needs are met in Pima County. The results of this study will inform the expansion of limited-scope licensed advocacy for other legal issues and in other jurisdictions.

Published
2022
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14. A Time Encoding Approach to Training Spiking Neural Networks

Author

Adam, Karen

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, Quantitative Biology::Neurons and Cognition, Computer Science::Neural and Evolutionary Computation, FOS: Electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), LCAV-MSP, Electrical Engineering and Systems Science - Signal Processing, Machine Learning (cs.LG)
Abstract

While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs). In this paper, we provide an extra tool to help us understand and train SNNs by using theory from the field of time encoding. Time encoding machines (TEMs) can be used to model integrate-and-fire neurons and have well-understood reconstruction properties. We will see how one can take inspiration from the field of TEMs to interpret the spike times of SNNs as constraints on the SNNs' weight matrices. More specifically, we study how to train one-layer SNNs by solving a set of linear constraints, and how to train two-layer SNNs by leveraging the all-or-none and asynchronous properties of the spikes emitted by SNNs. These properties of spikes result in an alternative to backpropagation which is not possible in the case of simultaneous and graded activations as in classical ANNs., Comment: 5 pages, 5 figures, submitted to IEEE ICASSP 2022

Published
2022
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16. IMPACT-Global Hip Fracture Audit: Nosocomial infection, risk prediction and prognostication, minimum reporting standards and global collaborative audit. Lessons from an international multicentre study of 7,090 patients conducted in 14 nations during the COVID-19 pandemic

Author

Hall, A, Clement, N, Ojeda-Thies, C, Maclullich, A, Toro, G, Johansen, A, White, T, Duckworth, A, Abdul-Jabar, H, Abu-Rajab, R, Abugarja, A, Adam, K, Aguado Hernández, H, Améstica Lazcano, G, Anderson, S, Ansar, M, Antrobus, J, Aragón Achig, E, Archunan, M, Arrieta Salinas, M, Ashford-Wilson, S, Assens Gibert, C, Athanasopoulou, K, Awadelkarim, M, Baird, S, Bajada, S, Balakrishnan, S, Balasubramanian, S, Ballantyne, J, Bárcena Goitiandia, L, Barkham, B, Barmpagianni, C, Barres-Carsi, M, Barrett, S, Baskaran, D, Bell, J, Bell, K, Bell, S, Bellelli, G, Benchimol, J, Boietti, B, Boswell, S, Braile, A, Brennan, C, Brent, L, Brooke, B, Bruno, G, Burahee, A, Burns, S, Calabrò, G, Campbell, L, Carabelli, G, Carnegie, C, Carretero Cristobal, G, Caruana, E, Cassinello Ogea, M, Castellanos Robles, J, Castillon, P, Chakrabarti, A, Cecere, A, Chen, P, Clarke, J, Collins, G, Corrales Cardenal, J, Corsi, M, Cózar Adelantado, G, Craxford, S, Crooks, M, Cuarental-García, J, Cuthbert, R, Dall, G, Daskalakis, I, De Cicco, A, Diana, D, Demaria, P, Dereix, J, Díaz Jiménez, J, Dinamarca Montecinos, J, Do Le, H, Donoso Coppa, J, Drosos, G, Duffy, A, East, J, Eastwood, D, Elbahari, H, Elias de Molins Peña, C, Elmamoun, M, Emmerson, B, Escobar Sánchez, D, Faimali, M, Farré-Mercadé, M, Farrow, L, Fayez, A, Fell, A, Fenner, C, Ferguson, D, Finlayson, L, Flores Gómez, A, Freeman, N, French, J, Gabardo Calvo, S, Gagliardo, N, Garcia Albiñana, J, García Cruz, G, García de Cortázar Antolín, U, García Virto, V, Gealy, S, Gil Caballero, S, Gill, M, González González, M, Gopireddy, R, Guntley, D, Gurung, B, Guzmán Rosales, G, Haddad, N, Hafeez, M, Haller, P, Halligan, E, Hardie, J, Hawker, I, Helal, A, Herrera Cruz, M, Herreros Ruiz-Valdepeñas, R, Horton, J, Howells, S, Howieson, A, Hughes, L, Hünicken Torrez, F, Hurtado Ortega, A, Huxley, P, Hamid, H, Ilahi, N, Iliadis, A, Inman, D, Jadhao, P, Jandoo, R, Jawad, L, Jayatilaka, M, Jenkins, P, Jeyapalan, R, Johnson, D, Johnston, A, Joseph, S, Kapoor, S, Karagiannidis, G, Karanam, K, Kattakayam, F, Konarski, A, Kontakis, G, Labrador Hernández, G, Lancaster, V, Landi, G, Le, B, Liew, I, Logishetty, K, Lopez Marquez, A, Lopez, J, Lum, J, Macpherson, G, Madan, S, Mahroof, S, Malik-Tabassum, K, Mallina, R, Maqsood, A, Marson, B, Martin Legorburo, M, Martin-Perez, E, Martínez Jiménez, T, Martinez Martin, J, Mayne, A, Mayor, A, Mcalinden, G, Mclean, L, Mcdonald, L, Mcintyre, J, Mckay, P, Mckean, G, Mcshane, H, Medici, A, Meeke, C, Meldrum, E, Mendez, M, Mercer, S, Merino Perez, J, Mesa-Lampré, M, Mighton, S, Milne, K, Mohamed Yaseen, M, Moppett, I, Mora, J, Morales-Zumel, S, Moreno Fenoll, I, Mousa, A, Murray, A, Murray, E, Nair, R, Neary, F, Negri, G, Negus, O, Newham-Harvey, F, Ng, N, Nightingale, J, Noor Mohamed Anver, S, Nunag, P, O'Hare, M, Ollivere, B, Ortés Gómez, R, Owens, A, Page, S, Palloni, V, Panagiotopoulos, A, Panagiotopoulos, E, Panesar, P, Papadopoulos, A, Spyridon, P, Pareja Sierra, T, Park, C, Parwaiz, H, Paterson-Byrne, P, Patton, S, Pearce, J, Porter, M, Pellegrino, A, Pèrez Cuellar, A, Pezzella, R, Phadnis, A, Pinder, C, Piper, D, Powell-Bowns, M, Prieto Martín, R, Probert, A, Ramesh, A, Ramírez de Arellano, M, Renton, D, Rickman, S, Robertson, A, Roche Albero, A, Rodrigo Verguizas, J, Rodríguez Couso, M, Rooney, J, Sáez-López, P, Saldaña-Díaz, A, Santulli, A, Sanz Pérez, M, Sarraf, K, Scarsbrook, C, Scott, C, Scott, J, Shah, S, Sharaf, S, Sharma, S, Shirley, D, Siano, A, Simpson, J, Singh, A, Sinnett, T, Sisodia, G, Smith, P, Sophena Bert, E, Steel, M, Stewart, A, Stewart, C, Sugand, K, Sullivan, N, Sweeting, L, Symes, M, Tan, D, Tancredi, F, Tatani, I, Thomas, P, Thomson, F, Toner, N, Tong, A, Toro, A, Tosounidis, T, Tottas, S, Trinidad Leo, A, Tucker, D, Vemulapalli, K, Ventura Garces, D, Vernon, O, Viveros Garcia, J, Ward, A, Ward, K, Watson, K, Weerasuriya, T, Wickramanayake, U, Wilkinson, H, Windley, J, Wood, J, Wynell-Mayow, W, Zatti, G, Zeiton, M, Zurrón Lobato, M, Hall, Andrew J., Clement, Nicholas D., Ojeda-Thies, Cristina, MacLullich, Alasdair MJ., Toro, Giuseppe, Johansen, Antony, White, Tim O., Duckworth, Andrew D., Abdul-Jabar, Hani, Abu-Rajab, Rashid, Abugarja, Ahmed, Adam, Karen, Aguado Hernández, Héctor J., Améstica Lazcano, Gedeón, Anderson, Sarah, Ansar, Mahmood, Antrobus, Jonathan, Aragón Achig, Esteban Javier, Archunan, Maheswaran, Arrieta Salinas, Mirentxu, Ashford-Wilson, Sarah, Assens Gibert, Cristina, Athanasopoulou, Katerina, Awadelkarim, Mohamed, Baird, Stuart, Bajada, Stefan, Balakrishnan, Shobana, Balasubramanian, Sathishkumar, Ballantyne, James A., Bárcena Goitiandia, Leopoldo, Barkham, Benjamin, Barmpagianni, Christina, Barres-Carsi, Mariano, Barrett, Sarah, Baskaran, Dinnish, Bell, Jean, Bell, Katrina, Bell, Stuart, Bellelli, Giuseppe, Benchimol, Javier Alberto, Boietti, Bruno Rafael, Boswell, Sally, Braile, Adriano, Brennan, Caitlin, Brent, Louise, Brooke, Ben, Bruno, Gaetano, Burahee, Abdus, Burns, Shirley, Calabrò, Giampiero, Campbell, Lucy, Carabelli, Guido Sebastian, Carnegie, Carol, Carretero Cristobal, Guillermo, Caruana, Ethan, Cassinello Ogea, M. a Concepción, Castellanos Robles, Juan, Castillon, Pablo, Chakrabarti, Anil, Cecere, Antonio Benedetto, Chen, Ping, Clarke, Jon V., Collins, Grace, Corrales Cardenal, Jorge E., Corsi, Maurizio, Cózar Adelantado, Gara María, Craxford, Simon, Crooks, Melissa, Cuarental-García, Javier, Cuthbert, Rory, Dall, Graham, Daskalakis, Ioannis, De Cicco, Annalisa, Diana, de la Fuente de Dios, Demaria, Pablo, Dereix, John, Díaz Jiménez, Julian, Dinamarca Montecinos, José Luis, Do Le, Ha Phuong, Donoso Coppa, Juan Pablo, Drosos, Georgios, Duffy, Andrew, East, Jamie, Eastwood, Deborah, Elbahari, Hassan, Elias de Molins Peña, Carmen, Elmamoun, Mamoun, Emmerson, Ben, Escobar Sánchez, Daniel, Faimali, Martina, Farré-Mercadé, Maria Victòria, Farrow, Luke, Fayez, Almari, Fell, Adam, Fenner, Christopher, Ferguson, David, Finlayson, Louise, Flores Gómez, Aldo, Freeman, Nicholas, French, Jonathan, Gabardo Calvo, Santiago, Gagliardo, Nicola, Garcia Albiñana, Joan, García Cruz, Guillermo, García de Cortázar Antolín, Unai, García Virto, Virginia, Gealy, Sophie, Gil Caballero, Sandra Marcela, Gill, Moneet, González González, María Soledad, Gopireddy, Rajesh, Guntley, Diane, Gurung, Binay, Guzmán Rosales, Guadalupe, Haddad, Nedaa, Hafeez, Mahum, Haller, Petra, Halligan, Emer, Hardie, John, Hawker, Imogen, Helal, Amr, Herrera Cruz, Mariana, Herreros Ruiz-Valdepeñas, Ruben, Horton, James, Howells, Sean, Howieson, Alan, Hughes, Luke, Hünicken Torrez, Flavia Lorena, Hurtado Ortega, Ana, Huxley, Peter, Hamid, Hytham K. S., Ilahi, Nida, Iliadis, Alexis, Inman, Dominic, Jadhao, Piyush, Jandoo, Rajan, Jawad, Lucy, Jayatilaka, Malwattage Lara Tania, Jenkins, Paul J., Jeyapalan, Rathan, Johnson, David, Johnston, Andrew, Joseph, Sarah, Kapoor, Siddhant, Karagiannidis, Georgios, Karanam, Krishna Saga, Kattakayam, Freddy, Konarski, Alastair, Kontakis, Georgios, Labrador Hernández, Gregorio, Lancaster, Victoria, Landi, Giovanni, Le, Brian, Liew, Ignatius, Logishetty, Kartik, Lopez Marquez, Andrew Carlomaria Daniel, Lopez, Judit, Lum, Joann, Macpherson, Gavin J., Madan, Suvira, Mahroof, Sabreena, Malik-Tabassum, Khalid, Mallina, Ravi, Maqsood, Afnan, Marson, Ben, Martin Legorburo, M José, Martin-Perez, Encarna, Martínez Jiménez, Tania, Martinez Martin, Javier, Mayne, Alistair, Mayor, Amy, McAlinden, Gavan, McLean, Lucille, McDonald, Lorna, McIntyre, Joshua, McKay, Pamela, McKean, Greg, McShane, Heather, Medici, Antonio, Meeke, Chelsea, Meldrum, Evonne, Mendez, Mijail, Mercer, Scott, Merino Perez, Josu, Mesa-Lampré, María-Pilar, Mighton, Shuna, Milne, Kirsty, Mohamed Yaseen, Muhammed, Moppett, Iain, Mora, Jesus, Morales-Zumel, Sira, Moreno Fenoll, Irene Blanca, Mousa, Adham, Murray, Alastair W., Murray, Elspeth V., Nair, Radhika, Neary, Fiona, Negri, Giacomo, Negus, Oliver, Newham-Harvey, Fiona, Ng, Nigel, Nightingale, Jess, Noor Mohamed Anver, Sumiya, Nunag, Perrico, O'Hare, Matthew, Ollivere, Ben, Ortés Gómez, Raquel, Owens, AnneMarie, Page, Siobhan, Palloni, Valentina, Panagiotopoulos, Andreas, Panagiotopoulos, Elias, Panesar, Paul, Papadopoulos, Antonios, Spyridon, Papagiannis, Pareja Sierra, Teresa, Park, Chang, Parwaiz, Hammad, Paterson-Byrne, Paul, Patton, Sam, Pearce, Jack, Porter, Marina, Pellegrino, Achille, Pèrez Cuellar, Arturo, Pezzella, Raffaele, Phadnis, Ashish, Pinder, Charlotte, Piper, Danielle, Powell-Bowns, Matilda, Prieto Martín, Rocío, Probert, Annabel, Ramesh, Ashwanth, Ramírez de Arellano, Manuel Vicente Mejía, Renton, Duncan, Rickman, Stephen, Robertson, Alastair, Roche Albero, Adrian, Rodrigo Verguizas, José Alberto, Rodríguez Couso, Myriam, Rooney, Joanna, Sáez-López, Pilar, Saldaña-Díaz, Andres, Santulli, Adriano, Sanz Pérez, Marta Isabel, Sarraf, Khaled M., Scarsbrook, Christine, Scott, Chloe E. H., Scott, Jennifer, Shah, Sachi, Sharaf, Sharief, Sharma, Sidharth, Shirley, Denise, Siano, Antonio, Simpson, James, Singh, Abhinav, Singh, Amit, Sinnett, Tim, Sisodia, Gurudatt, Smith, Philomena, Sophena Bert, Eugenia, Steel, Michael, Stewart, Avril, Stewart, Claire, Sugand, Kapil, Sullivan, Niall, Sweeting, Lauren, Symes, Michael, Tan, Dylan Jun Hao, Tancredi, Francesco, Tatani, Irini, Thomas, Philip, Thomson, Fraser, Toner, Niamh S., Tong, Anna, Toro, Antonio, Tosounidis, Theodoros, Tottas, Stylianos, Trinidad Leo, Andrea, Tucker, Damien, Vemulapalli, Krishna, Ventura Garces, Diego, Vernon, Olivia Katherine, Viveros Garcia, Juan Carlos, Ward, Alex, Ward, Kirsty, Watson, Kate, Weerasuriya, Thisara, Wickramanayake, Udara, Wilkinson, Hannah, Windley, Joseph, Wood, Janet, Wynell-Mayow, William, Zatti, Giovanni, Zeiton, Moez, Zurrón Lobato, Miriam, Hall, A, Clement, N, Ojeda-Thies, C, Maclullich, A, Toro, G, Johansen, A, White, T, Duckworth, A, Abdul-Jabar, H, Abu-Rajab, R, Abugarja, A, Adam, K, Aguado Hernández, H, Améstica Lazcano, G, Anderson, S, Ansar, M, Antrobus, J, Aragón Achig, E, Archunan, M, Arrieta Salinas, M, Ashford-Wilson, S, Assens Gibert, C, Athanasopoulou, K, Awadelkarim, M, Baird, S, Bajada, S, Balakrishnan, S, Balasubramanian, S, Ballantyne, J, Bárcena Goitiandia, L, Barkham, B, Barmpagianni, C, Barres-Carsi, M, Barrett, S, Baskaran, D, Bell, J, Bell, K, Bell, S, Bellelli, G, Benchimol, J, Boietti, B, Boswell, S, Braile, A, Brennan, C, Brent, L, Brooke, B, Bruno, G, Burahee, A, Burns, S, Calabrò, G, Campbell, L, Carabelli, G, Carnegie, C, Carretero Cristobal, G, Caruana, E, Cassinello Ogea, M, Castellanos Robles, J, Castillon, P, Chakrabarti, A, Cecere, A, Chen, P, Clarke, J, Collins, G, Corrales Cardenal, J, Corsi, M, Cózar Adelantado, G, Craxford, S, Crooks, M, Cuarental-García, J, Cuthbert, R, Dall, G, Daskalakis, I, De Cicco, A, Diana, D, Demaria, P, Dereix, J, Díaz Jiménez, J, Dinamarca Montecinos, J, Do Le, H, Donoso Coppa, J, Drosos, G, Duffy, A, East, J, Eastwood, D, Elbahari, H, Elias de Molins Peña, C, Elmamoun, M, Emmerson, B, Escobar Sánchez, D, Faimali, M, Farré-Mercadé, M, Farrow, L, Fayez, A, Fell, A, Fenner, C, Ferguson, D, Finlayson, L, Flores Gómez, A, Freeman, N, French, J, Gabardo Calvo, S, Gagliardo, N, Garcia Albiñana, J, García Cruz, G, García de Cortázar Antolín, U, García Virto, V, Gealy, S, Gil Caballero, S, Gill, M, González González, M, Gopireddy, R, Guntley, D, Gurung, B, Guzmán Rosales, G, Haddad, N, Hafeez, M, Haller, P, Halligan, E, Hardie, J, Hawker, I, Helal, A, Herrera Cruz, M, Herreros Ruiz-Valdepeñas, R, Horton, J, Howells, S, Howieson, A, Hughes, L, Hünicken Torrez, F, Hurtado Ortega, A, Huxley, P, Hamid, H, Ilahi, N, Iliadis, A, Inman, D, Jadhao, P, Jandoo, R, Jawad, L, Jayatilaka, M, Jenkins, P, Jeyapalan, R, Johnson, D, Johnston, A, Joseph, S, Kapoor, S, Karagiannidis, G, Karanam, K, Kattakayam, F, Konarski, A, Kontakis, G, Labrador Hernández, G, Lancaster, V, Landi, G, Le, B, Liew, I, Logishetty, K, Lopez Marquez, A, Lopez, J, Lum, J, Macpherson, G, Madan, S, Mahroof, S, Malik-Tabassum, K, Mallina, R, Maqsood, A, Marson, B, Martin Legorburo, M, Martin-Perez, E, Martínez Jiménez, T, Martinez Martin, J, Mayne, A, Mayor, A, Mcalinden, G, Mclean, L, Mcdonald, L, Mcintyre, J, Mckay, P, Mckean, G, Mcshane, H, Medici, A, Meeke, C, Meldrum, E, Mendez, M, Mercer, S, Merino Perez, J, Mesa-Lampré, M, Mighton, S, Milne, K, Mohamed Yaseen, M, Moppett, I, Mora, J, Morales-Zumel, S, Moreno Fenoll, I, Mousa, A, Murray, A, Murray, E, Nair, R, Neary, F, Negri, G, Negus, O, Newham-Harvey, F, Ng, N, Nightingale, J, Noor Mohamed Anver, S, Nunag, P, O'Hare, M, Ollivere, B, Ortés Gómez, R, Owens, A, Page, S, Palloni, V, Panagiotopoulos, A, Panagiotopoulos, E, Panesar, P, Papadopoulos, A, Spyridon, P, Pareja Sierra, T, Park, C, Parwaiz, H, Paterson-Byrne, P, Patton, S, Pearce, J, Porter, M, Pellegrino, A, Pèrez Cuellar, A, Pezzella, R, Phadnis, A, Pinder, C, Piper, D, Powell-Bowns, M, Prieto Martín, R, Probert, A, Ramesh, A, Ramírez de Arellano, M, Renton, D, Rickman, S, Robertson, A, Roche Albero, A, Rodrigo Verguizas, J, Rodríguez Couso, M, Rooney, J, Sáez-López, P, Saldaña-Díaz, A, Santulli, A, Sanz Pérez, M, Sarraf, K, Scarsbrook, C, Scott, C, Scott, J, Shah, S, Sharaf, S, Sharma, S, Shirley, D, Siano, A, Simpson, J, Singh, A, Sinnett, T, Sisodia, G, Smith, P, Sophena Bert, E, Steel, M, Stewart, A, Stewart, C, Sugand, K, Sullivan, N, Sweeting, L, Symes, M, Tan, D, Tancredi, F, Tatani, I, Thomas, P, Thomson, F, Toner, N, Tong, A, Toro, A, Tosounidis, T, Tottas, S, Trinidad Leo, A, Tucker, D, Vemulapalli, K, Ventura Garces, D, Vernon, O, Viveros Garcia, J, Ward, A, Ward, K, Watson, K, Weerasuriya, T, Wickramanayake, U, Wilkinson, H, Windley, J, Wood, J, Wynell-Mayow, W, Zatti, G, Zeiton, M, Zurrón Lobato, M, Hall, Andrew J., Clement, Nicholas D., Ojeda-Thies, Cristina, MacLullich, Alasdair MJ., Toro, Giuseppe, Johansen, Antony, White, Tim O., Duckworth, Andrew D., Abdul-Jabar, Hani, Abu-Rajab, Rashid, Abugarja, Ahmed, Adam, Karen, Aguado Hernández, Héctor J., Améstica Lazcano, Gedeón, Anderson, Sarah, Ansar, Mahmood, Antrobus, Jonathan, Aragón Achig, Esteban Javier, Archunan, Maheswaran, Arrieta Salinas, Mirentxu, Ashford-Wilson, Sarah, Assens Gibert, Cristina, Athanasopoulou, Katerina, Awadelkarim, Mohamed, Baird, Stuart, Bajada, Stefan, Balakrishnan, Shobana, Balasubramanian, Sathishkumar, Ballantyne, James A., Bárcena Goitiandia, Leopoldo, Barkham, Benjamin, Barmpagianni, Christina, Barres-Carsi, Mariano, Barrett, Sarah, Baskaran, Dinnish, Bell, Jean, Bell, Katrina, Bell, Stuart, Bellelli, Giuseppe, Benchimol, Javier Alberto, Boietti, Bruno Rafael, Boswell, Sally, Braile, Adriano, Brennan, Caitlin, Brent, Louise, Brooke, Ben, Bruno, Gaetano, Burahee, Abdus, Burns, Shirley, Calabrò, Giampiero, Campbell, Lucy, Carabelli, Guido Sebastian, Carnegie, Carol, Carretero Cristobal, Guillermo, Caruana, Ethan, Cassinello Ogea, M. a Concepción, Castellanos Robles, Juan, Castillon, Pablo, Chakrabarti, Anil, Cecere, Antonio Benedetto, Chen, Ping, Clarke, Jon V., Collins, Grace, Corrales Cardenal, Jorge E., Corsi, Maurizio, Cózar Adelantado, Gara María, Craxford, Simon, Crooks, Melissa, Cuarental-García, Javier, Cuthbert, Rory, Dall, Graham, Daskalakis, Ioannis, De Cicco, Annalisa, Diana, de la Fuente de Dios, Demaria, Pablo, Dereix, John, Díaz Jiménez, Julian, Dinamarca Montecinos, José Luis, Do Le, Ha Phuong, Donoso Coppa, Juan Pablo, Drosos, Georgios, Duffy, Andrew, East, Jamie, Eastwood, Deborah, Elbahari, Hassan, Elias de Molins Peña, Carmen, Elmamoun, Mamoun, Emmerson, Ben, Escobar Sánchez, Daniel, Faimali, Martina, Farré-Mercadé, Maria Victòria, Farrow, Luke, Fayez, Almari, Fell, Adam, Fenner, Christopher, Ferguson, David, Finlayson, Louise, Flores Gómez, Aldo, Freeman, Nicholas, French, Jonathan, Gabardo Calvo, Santiago, Gagliardo, Nicola, Garcia Albiñana, Joan, García Cruz, Guillermo, García de Cortázar Antolín, Unai, García Virto, Virginia, Gealy, Sophie, Gil Caballero, Sandra Marcela, Gill, Moneet, González González, María Soledad, Gopireddy, Rajesh, Guntley, Diane, Gurung, Binay, Guzmán Rosales, Guadalupe, Haddad, Nedaa, Hafeez, Mahum, Haller, Petra, Halligan, Emer, Hardie, John, Hawker, Imogen, Helal, Amr, Herrera Cruz, Mariana, Herreros Ruiz-Valdepeñas, Ruben, Horton, James, Howells, Sean, Howieson, Alan, Hughes, Luke, Hünicken Torrez, Flavia Lorena, Hurtado Ortega, Ana, Huxley, Peter, Hamid, Hytham K. S., Ilahi, Nida, Iliadis, Alexis, Inman, Dominic, Jadhao, Piyush, Jandoo, Rajan, Jawad, Lucy, Jayatilaka, Malwattage Lara Tania, Jenkins, Paul J., Jeyapalan, Rathan, Johnson, David, Johnston, Andrew, Joseph, Sarah, Kapoor, Siddhant, Karagiannidis, Georgios, Karanam, Krishna Saga, Kattakayam, Freddy, Konarski, Alastair, Kontakis, Georgios, Labrador Hernández, Gregorio, Lancaster, Victoria, Landi, Giovanni, Le, Brian, Liew, Ignatius, Logishetty, Kartik, Lopez Marquez, Andrew Carlomaria Daniel, Lopez, Judit, Lum, Joann, Macpherson, Gavin J., Madan, Suvira, Mahroof, Sabreena, Malik-Tabassum, Khalid, Mallina, Ravi, Maqsood, Afnan, Marson, Ben, Martin Legorburo, M José, Martin-Perez, Encarna, Martínez Jiménez, Tania, Martinez Martin, Javier, Mayne, Alistair, Mayor, Amy, McAlinden, Gavan, McLean, Lucille, McDonald, Lorna, McIntyre, Joshua, McKay, Pamela, McKean, Greg, McShane, Heather, Medici, Antonio, Meeke, Chelsea, Meldrum, Evonne, Mendez, Mijail, Mercer, Scott, Merino Perez, Josu, Mesa-Lampré, María-Pilar, Mighton, Shuna, Milne, Kirsty, Mohamed Yaseen, Muhammed, Moppett, Iain, Mora, Jesus, Morales-Zumel, Sira, Moreno Fenoll, Irene Blanca, Mousa, Adham, Murray, Alastair W., Murray, Elspeth V., Nair, Radhika, Neary, Fiona, Negri, Giacomo, Negus, Oliver, Newham-Harvey, Fiona, Ng, Nigel, Nightingale, Jess, Noor Mohamed Anver, Sumiya, Nunag, Perrico, O'Hare, Matthew, Ollivere, Ben, Ortés Gómez, Raquel, Owens, AnneMarie, Page, Siobhan, Palloni, Valentina, Panagiotopoulos, Andreas, Panagiotopoulos, Elias, Panesar, Paul, Papadopoulos, Antonios, Spyridon, Papagiannis, Pareja Sierra, Teresa, Park, Chang, Parwaiz, Hammad, Paterson-Byrne, Paul, Patton, Sam, Pearce, Jack, Porter, Marina, Pellegrino, Achille, Pèrez Cuellar, Arturo, Pezzella, Raffaele, Phadnis, Ashish, Pinder, Charlotte, Piper, Danielle, Powell-Bowns, Matilda, Prieto Martín, Rocío, Probert, Annabel, Ramesh, Ashwanth, Ramírez de Arellano, Manuel Vicente Mejía, Renton, Duncan, Rickman, Stephen, Robertson, Alastair, Roche Albero, Adrian, Rodrigo Verguizas, José Alberto, Rodríguez Couso, Myriam, Rooney, Joanna, Sáez-López, Pilar, Saldaña-Díaz, Andres, Santulli, Adriano, Sanz Pérez, Marta Isabel, Sarraf, Khaled M., Scarsbrook, Christine, Scott, Chloe E. H., Scott, Jennifer, Shah, Sachi, Sharaf, Sharief, Sharma, Sidharth, Shirley, Denise, Siano, Antonio, Simpson, James, Singh, Abhinav, Singh, Amit, Sinnett, Tim, Sisodia, Gurudatt, Smith, Philomena, Sophena Bert, Eugenia, Steel, Michael, Stewart, Avril, Stewart, Claire, Sugand, Kapil, Sullivan, Niall, Sweeting, Lauren, Symes, Michael, Tan, Dylan Jun Hao, Tancredi, Francesco, Tatani, Irini, Thomas, Philip, Thomson, Fraser, Toner, Niamh S., Tong, Anna, Toro, Antonio, Tosounidis, Theodoros, Tottas, Stylianos, Trinidad Leo, Andrea, Tucker, Damien, Vemulapalli, Krishna, Ventura Garces, Diego, Vernon, Olivia Katherine, Viveros Garcia, Juan Carlos, Ward, Alex, Ward, Kirsty, Watson, Kate, Weerasuriya, Thisara, Wickramanayake, Udara, Wilkinson, Hannah, Windley, Joseph, Wood, Janet, Wynell-Mayow, William, Zatti, Giovanni, Zeiton, Moez, and Zurrón Lobato, Miriam

Abstract

Aims: This international study aimed to assess: 1) the prevalence of preoperative and postoperative COVID-19 among patients with hip fracture, 2) the effect on 30-day mortality, and 3) clinical factors associated with the infection and with mortality in COVID-19-positive patients. Methods: A multicentre collaboration among 112 centres in 14 countries collected data on all patients presenting with a hip fracture between 1st March-31st May 2020. Demographics, residence, place of injury, presentation blood tests, Nottingham Hip Fracture Score, time to surgery, management, ASA grade, length of stay, COVID-19 and 30-day mortality status were recorded. Results: A total of 7090 patients were included, with a mean age of 82.2 (range 50–104) years and 4959 (69.9%) being female. Of 651 (9.2%) patients diagnosed with COVID-19, 225 (34.6%) were positive at presentation and 426 (65.4%) were positive postoperatively. Positive COVID-19 status was independently associated with male sex (odds ratio (OR) 1.38, p = 0.001), residential care (OR 2.15, p < 0.001), inpatient fall (OR 2.23, p = 0.003), cancer (OR 0.63, p = 0.009), ASA grades 4 (OR 1.59, p = 0.008) or 5 (OR 8.28, p < 0.001), and longer admission (OR 1.06 for each increasing day, p < 0.001). Patients with COVID-19 at any time had a significantly lower chance of 30-day survival versus those without COVID-19 (72.7% versus 92.6%, p < 0.001). COVID-19 was independently associated with an increased 30-day mortality risk (hazard ratio (HR) 2.83, p < 0.001). Increasing age (HR 1.03, p = 0.028), male sex (HR 2.35, p < 0.001), renal disease (HR 1.53, p = 0.017), and pulmonary disease (HR 1.45, p = 0.039) were independently associated with a higher 30-day mortality risk in patients with COVID-19 when adjusting for confounders. Conclusion: The prevalence of COVID-19 in hip fracture patients during the first wave of the pandemic was 9%, and was independently associated with a three-fold increased 30-day mortality risk.

Published
2022

18. Timing is Everything

Author

Adam, Karen

Abstract

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of choosing the right time to sample a system, when efficiency is a key consideration. Time encoding machines, or, alternately, integrate-and-fire neurons, encode their inputs using spikes, the timings of which depend on the input and therefore hold information about it. These devices can be made more power efficient than their clocked counterparts and have thus been studied in the fields of signal processing, event-based vision, computational neuroscience and machine learning. However, their timing-based spiking output has so far often been considered a nuisance that one must make do with, rather than a potential advantage. In this thesis, we show that this timing-based output equips spiking devices with capabilities that are out of reach for classical encoding and processing systems. We first discover the benefits of time encoding on multi-channel encoding and recovery of a signal: with time encoding, clock alignment is easy to solve, although it poses problems in the classical sampling scenario. Then, we study the time encoding of low-dimensional signals and see that the asynchrony of spikes allows for a lower sample complexity in comparison with synchronous sampling. Thanks to this same asynchrony, time encoding of video results in an entanglement between spatial sampling density and temporal resolution---a relationship which is not present in frame-based video. Finally, we show that the all-or-none nature of the spikes allows training spiking neural networks in a layer-by-layer fashion---a feat that is impossible with clocked, artificial neural networks, due to the credit assignment problem. The second part of this thesis shows that choosing the right timing of samples can be crucial to ensure efficiency when performing nanoscale magnetic sensing. We are given a stochastic process, where each sample at time t follows a Bernoulli distribution, and which is characterized by oscillation frequencies that we are interested in recovering. We search for an optimal approach to sample this process, such that the variance of the frequencies' estimates is minimized, given constraints on the measurement time. The models we assume stem from the field of nanoscale magnetic sensing, where the number of parameters to be estimated varies with the number of spins one is trying to sense. We present an adaptive approach to choosing samples in both the single-spin and two-spin cases and compare the adaptive algorithm's performance to classical approaches to sampling. In both parts of the thesis, we move away from classical amplitude sampling and consider cases where timing takes the forefront and amplitude information is merely binary, to shows that timing can carry information and that it can control the amount of information gain.

Published
2022
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31. Providers must be aware of psychostimulant abuse in youths

Author

Adam, Karen C.

Subjects
Dexedrine (Medication) -- Usage, Ritalin (Medication) -- Usage, Cylert (Medication) -- Usage, Drug therapy, Usage, Demographic aspects, Amphetamines -- Usage, Attention deficit hyperactivity disorder -- Drug therapy, Drug abuse -- Demographic aspects -- Drug therapy, Mental health services -- Usage, Psychiatric services -- Usage, Attention-deficit hyperactivity disorder -- Drug therapy
Abstract

Psychostimulant drugs, when taken orally as prescribed, are an effective course of treatment for adolescents diagnosed with attention-deficit disorder/attention-deficit/hyperactivity disorder (ADD/ADHD). But many adolescents are discovering the power of these [...]

Published
2001

32. From the Field

Author

Adam, Karen C.

Subjects
Drug therapy, Usage, Analysis, Attention deficit hyperactivity disorder -- Drug therapy, Drug abuse -- Analysis -- Drug therapy, Central nervous system stimulants -- Usage -- Analysis, Stimulants -- Usage -- Analysis, Attention-deficit hyperactivity disorder -- Drug therapy
Abstract

Providers must be aware of psychostimulant abuse in youths Psychostimulant drugs, when taken orally as prescribed, are an effective course of treatment for adolescents diagnosed with attention deficit disorder/attention-deficit/hyperactivity disorder [...]

Published
2001

33. Timing is Everything

Author

Adam, Karen, Vetterli, Martin, and Scholefield, Adam James

Subjects
sampling, event video, spiking neural networks, nanoscale magnetic sensing, adaptive sampling, time encoding
Abstract

In this thesis, timing is everything. In the first part, we mean this literally, as we tackle systems that encode information using timing alone. In the second part, we adopt the standard, metaphoric interpretation of this saying and show the importance of choosing the right time to sample a system, when efficiency is a key consideration. Time encoding machines, or, alternately, integrate-and-fire neurons, encode their inputs using spikes, the timings of which depend on the input and therefore hold information about it. These devices can be made more power efficient than their clocked counterparts and have thus been studied in the fields of signal processing, event-based vision, computational neuroscience and machine learning. However, their timing-based spiking output has so far often been considered a nuisance that one must make do with, rather than a potential advantage. In this thesis, we show that this timing-based output equips spiking devices with capabilities that are out of reach for classical encoding and processing systems. We first discover the benefits of time encoding on multi-channel encoding and recovery of a signal: with time encoding, clock alignment is easy to solve, although it poses problems in the classical sampling scenario. Then, we study the time encoding of low-dimensional signals and see that the asynchrony of spikes allows for a lower sample complexity in comparison with synchronous sampling. Thanks to this same asynchrony, time encoding of video results in an entanglement between spatial sampling density and temporal resolution---a relationship which is not present in frame-based video. Finally, we show that the all-or-none nature of the spikes allows training spiking neural networks in a layer-by-layer fashion---a feat that is impossible with clocked, artificial neural networks, due to the credit assignment problem. The second part of this thesis shows that choosing the right timing of samples can be crucial to ensure efficiency when performing nanoscale magnetic sensing. We are given a stochastic process, where each sample at time t follows a Bernoulli distribution, and which is characterized by oscillation frequencies that we are interested in recovering. We search for an optimal approach to sample this process, such that the variance of the frequencies' estimates is minimized, given constraints on the measurement time. The models we assume stem from the field of nanoscale magnetic sensing, where the number of parameters to be estimated varies with the number of spins one is trying to sense. We present an adaptive approach to choosing samples in both the single-spin and two-spin cases and compare the adaptive algorithm's performance to classical approaches to sampling. In both parts of the thesis, we move away from classical amplitude sampling and consider cases where timing takes the forefront and amplitude information is merely binary, to shows that timing can carry information and that it can control the amount of information gain.

34. Mary & George Sanderson.

Author

Adam, Karen

Abstract

The article presents the author's insights concerning the elderly people who influenced her life, such as Mary Sanderson and late George Sanderson.

Published
2010

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