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2. Global burden of bacterial antimicrobial resistance 1990–2021: a systematic analysis with forecasts to 2050

Author

Naghavi, Mohsen, Vollset, Stein Emil, Ikuta, Kevin S, Swetschinski, Lucien R, Gray, Authia P, Wool, Eve E, Robles Aguilar, Gisela, Mestrovic, Tomislav, Smith, Georgia, Han, Chieh, Hsu, Rebecca L, Chalek, Julian, Araki, Daniel T, Chung, Erin, Raggi, Catalina, Gershberg Hayoon, Anna, Davis Weaver, Nicole, Lindstedt, Paulina A, Smith, Amanda E, Altay, Umut, Bhattacharjee, Natalia V, Giannakis, Konstantinos, Fell, Frederick, McManigal, Barney, Ekapirat, Nattwut, Mendes, Jessica Andretta, Runghien, Tilleye, Srimokla, Oraya, Abdelkader, Atef, Abd-Elsalam, Sherief, Aboagye, Richard Gyan, Abolhassani, Hassan, Abualruz, Hasan, Abubakar, Usman, Abukhadijah, Hana J, Aburuz, Salahdein, Abu-Zaid, Ahmed, Achalapong, Sureerak, Addo, Isaac Yeboah, Adekanmbi, Victor, Adeyeoluwa, Temitayo Esther, Adnani, Qorinah Estiningtyas Sakilah, Adzigbli, Leticia Akua, Afzal, Muhammad Sohail, Afzal, Saira, Agodi, Antonella, Ahlstrom, Austin J, Ahmad, Aqeel, Ahmad, Sajjad, Ahmad, Tauseef, Ahmadi, Ali, Ahmed, Ayman, Ahmed, Haroon, Ahmed, Ibrar, Ahmed, Mohammed, Ahmed, Saeed, Ahmed, Syed Anees, Akkaif, Mohammed Ahmed, Al Awaidy, Salah, Al Thaher, Yazan, Alalalmeh, Samer O, AlBataineh, Mohammad T, Aldhaleei, Wafa A, Al-Gheethi, Adel Ali Saeed, Alhaji, Nma Bida, Ali, Abid, Ali, Liaqat, Ali, Syed Shujait, Ali, Waad, Allel, Kasim, Al-Marwani, Sabah, Alrawashdeh, Ahmad, Altaf, Awais, Al-Tammemi, Alaa B., Al-Tawfiq, Jaffar A, Alzoubi, Karem H, Al-Zyoud, Walid Adnan, Amos, Ben, Amuasi, John H, Ancuceanu, Robert, Andrews, Jason R, Anil, Abhishek, Anuoluwa, Iyadunni Adesola, Anvari, Saeid, Anyasodor, Anayochukwu Edward, Apostol, Geminn Louis Carace, Arabloo, Jalal, Arafat, Mosab, Aravkin, Aleksandr Y, Areda, Demelash, Aremu, Abdulfatai, Artamonov, Anton A, Ashley, Elizabeth A, Asika, Marvellous O, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Awoke, Tewachew, Azadnajafabad, Sina, Azam, James Mba, Aziz, Shahkaar, Azzam, Ahmed Y., Babaei, Mahsa, Babin, Francois-Xavier, Badar, Muhammad, Baig, Atif Amin, Bajcetic, Milica, Baker, Stephen, Bardhan, Mainak, Barqawi, Hiba Jawdat, Basharat, Zarrin, Basiru, Afisu, Bastard, Mathieu, Basu, Saurav, Bayleyegn, Nebiyou Simegnew, Belete, Melaku Ashagrie, Bello, Olorunjuwon Omolaja, Beloukas, Apostolos, Berkley, James A, Bhagavathula, Akshaya Srikanth, Bhaskar, Sonu, Bhuyan, Soumitra S, Bielicki, Julia A, Briko, Nikolay Ivanovich, Brown, Colin Stewart, Browne, Annie J, Buonsenso, Danilo, Bustanji, Yasser, Carvalheiro, Cristina G, Castañeda-Orjuela, Carlos A, Cenderadewi, Muthia, Chadwick, Joshua, Chakraborty, Sandip, Chandika, Rama Mohan, Chandy, Sara, Chansamouth, Vilada, Chattu, Vijay Kumar, Chaudhary, Anis Ahmad, Ching, Patrick R, Chopra, Hitesh, Chowdhury, Fazle Rabbi, Chu, Dinh-Toi, Chutiyami, Muhammad, Cruz-Martins, Natalia, da Silva, Alanna Gomes, Dadras, Omid, Dai, Xiaochen, Darcho, Samuel D, Das, Saswati, De la Hoz, Fernando Pio, Dekker, Denise Myriam, Dhama, Kuldeep, Diaz, Daniel, Dickson, Benjamin Felix Rothschild, Djorie, Serge Ghislain, Dodangeh, Milad, Dohare, Sushil, Dokova, Klara Georgieva, Doshi, Ojas Prakashbhai, Dowou, Robert Kokou, Dsouza, Haneil Larson, Dunachie, Susanna J, Dziedzic, Arkadiusz Marian, Eckmanns, Tim, Ed-Dra, Abdelaziz, Eftekharimehrabad, Aziz, Ekundayo, Temitope Cyrus, El Sayed, Iman, Elhadi, Muhammed, El-Huneidi, Waseem, Elias, Christelle, Ellis, Sally J, Elsheikh, Randa, Elsohaby, Ibrahim, Eltaha, Chadi, Eshrati, Babak, Eslami, Majid, Eyre, David William, Fadaka, Adewale Oluwaseun, Fagbamigbe, Adeniyi Francis, Fahim, Ayesha, Fakhri-Demeshghieh, Aliasghar, Fasina, Folorunso Oludayo, Fasina, Modupe Margaret, Fatehizadeh, Ali, Feasey, Nicholas A, Feizkhah, Alireza, Fekadu, Ginenus, Fischer, Florian, Fitriana, Ida, Forrest, Karen M, Fortuna Rodrigues, Celia, Fuller, John E, Gadanya, Muktar A, Gajdács, Márió, Gandhi, Aravind P, Garcia-Gallo, Esteban E, Garrett, Denise O, Gautam, Rupesh K, Gebregergis, Miglas Welay, Gebrehiwot, Mesfin, Gebremeskel, Teferi Gebru, Geffers, Christine, Georgalis, Leonidas, Ghazy, Ramy Mohamed, Golechha, Mahaveer, Golinelli, Davide, Gordon, Melita, Gulati, Snigdha, Gupta, Rajat Das, Gupta, Sapna, Gupta, Vijai Kumar, Habteyohannes, Awoke Derbie, Haller, Sebastian, Harapan, Harapan, Harrison, Michelle L, Hasaballah, Ahmed I, Hasan, Ikramul, Hasan, Rumina Syeda, Hasani, Hamidreza, Haselbeck, Andrea Haekyung, Hasnain, Md Saquib, Hassan, Ikrama Ibrahim, Hassan, Shoaib, Hassan Zadeh Tabatabaei, Mahgol Sadat, Hayat, Khezar, He, Jiawei, Hegazi, Omar E, Heidari, Mohammad, Hezam, Kamal, Holla, Ramesh, Holm, Marianne, Hopkins, Heidi, Hossain, Md Mahbub, Hosseinzadeh, Mehdi, Hostiuc, Sorin, Hussein, Nawfal R, Huy, Le Duc, Ibáñez-Prada, Elsa D, Ikiroma, Adalia, Ilic, Irena M, Islam, Sheikh Mohammed Shariful, Ismail, Faisal, Ismail, Nahlah Elkudssiah, Iwu, Chidozie Declan, Iwu-Jaja, Chinwe Juliana, Jafarzadeh, Abdollah, Jaiteh, Fatoumatta, Jalilzadeh Yengejeh, Reza, Jamora, Roland Dominic G, Javidnia, Javad, Jawaid, Talha, Jenney, Adam W J, Jeon, Hyon Jin, Jokar, Mohammad, Jomehzadeh, Nabi, Joo, Tamas, Joseph, Nitin, Kamal, Zul, Kanmodi, Kehinde Kazeem, Kantar, Rami S, Kapisi, James Apollo, Karaye, Ibraheem M, Khader, Yousef Saleh, Khajuria, Himanshu, Khalid, Nauman, Khamesipour, Faham, Khan, Ajmal, Khan, Mohammad Jobair, Khan, Muhammad Tariq, Khanal, Vishnu, Khidri, Feriha Fatima, Khubchandani, Jagdish, Khusuwan, Suwimon, Kim, Min Seo, Kisa, Adnan, Korshunov, Vladimir Andreevich, Krapp, Fiorella, Krumkamp, Ralf, Kuddus, Mohammed, Kulimbet, Mukhtar, Kumar, Dewesh, Kumaran, Emmanuelle A P, Kuttikkattu, Ambily, Kyu, Hmwe Hmwe, Landires, Iván, Lawal, Basira Kankia, Le, Thao Thi Thu, Lederer, Ingeborg Maria, Lee, Munjae, Lee, Seung Won, Lepape, Alain, Lerango, Temesgen Leka, Ligade, Virendra S, Lim, Cherry, Lim, Stephen S, Limenh, Liknaw Workie, Liu, Chaojie, Liu, Xiaofeng, Liu, Xuefeng, Loftus, Michael J, M Amin, Hawraz Ibrahim, Maass, Kelsey Lynn, Maharaj, Sandeep B, Mahmoud, Mansour Adam, Maikanti-Charalampous, Panagiota, Makram, Omar M, Malhotra, Kashish, Malik, Ahmad Azam, Mandilara, Georgia D, Marks, Florian, Martinez-Guerra, Bernardo Alfonso, Martorell, Miquel, Masoumi-Asl, Hossein, Mathioudakis, Alexander G, May, Juergen, McHugh, Theresa A, Meiring, James, Meles, Hadush Negash, Melese, Addisu, Melese, Endalkachew Belayneh, Minervini, Giuseppe, Mohamed, Nouh Saad, Mohammed, Shafiu, Mohan, Syam, Mokdad, Ali H, Monasta, Lorenzo, Moodi Ghalibaf, AmirAli, Moore, Catrin E, Moradi, Yousef, Mossialos, Elias, Mougin, Vincent, Mukoro, George Duke, Mulita, Francesk, Muller-Pebody, Berit, Murillo-Zamora, Efren, Musa, Sani, Musicha, Patrick, Musila, Lillian A, Muthupandian, Saravanan, Nagarajan, Ahamarshan Jayaraman, Naghavi, Pirouz, Nainu, Firzan, Nair, Tapas Sadasivan, Najmuldeen, Hastyar Hama Rashid, Natto, Zuhair S, Nauman, Javaid, Nayak, Biswa Prakash, Nchanji, G Takop, Ndishimye, Pacifique, Negoi, Ionut, Negoi, Ruxandra Irina, Nejadghaderi, Seyed Aria, Nguyen, QuynhAnh P, Noman, Efaq Ali, Nwakanma, Davis C, O'Brien, Seamus, Ochoa, Theresa J, Odetokun, Ismail A, Ogundijo, Oluwaseun Adeolu, Ojo-Akosile, Tolulope R, Okeke, Sylvester Reuben, Okonji, Osaretin Christabel, Olagunju, Andrew T, Olivas-Martinez, Antonio, Olorukooba, Abdulhakeem Abayomi, Olwoch, Peter, Onyedibe, Kenneth Ikenna, Ortiz-Brizuela, Edgar, Osuolale, Olayinka, Ounchanum, Pradthana, Oyeyemi, Oyetunde T, P A, Mahesh Padukudru, Paredes, Jose L, Parikh, Romil R, Patel, Jay, Patil, Shankargouda, Pawar, Shrikant, Peleg, Anton Y, Peprah, Prince, Perdigão, João, Perrone, Carlo, Petcu, Ionela-Roxana, Phommasone, Koukeo, Piracha, Zahra Zahid, Poddighe, Dimitri, Pollard, Andrew J, Poluru, Ramesh, Ponce-De-Leon, Alfredo, Puvvula, Jagadeesh, Qamar, Farah Naz, Qasim, Nameer Hashim, Rafai, Clotaire Donatien, Raghav, Pankaja, Rahbarnia, Leila, Rahim, Fakher, Rahimi-Movaghar, Vafa, Rahman, Mosiur, Rahman, Muhammad Aziz, Ramadan, Hazem, Ramasamy, Shakthi Kumaran, Ramesh, Pushkal Sinduvadi, Ramteke, Pramod W, Rana, Rishabh Kumar, Rani, Usha, Rashidi, Mohammad-Mahdi, Rathish, Devarajan, Rattanavong, Sayaphet, Rawaf, Salman, Redwan, Elrashdy Moustafa Mohamed, Reyes, Luis Felipe, Roberts, Tamalee, Robotham, Julie V, Rosenthal, Victor Daniel, Ross, Allen Guy, Roy, Nitai, Rudd, Kristina E, Sabet, Cameron John, Saddik, Basema Ahmad, Saeb, Mohammad Reza, Saeed, Umar, Saeedi Moghaddam, Sahar, Saengchan, Weeravoot, Safaei, Mohsen, Saghazadeh, Amene, Saheb Sharif-Askari, Narjes, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahu, Maitreyi, Saki, Morteza, Salam, Nasir, Saleem, Zikria, Saleh, Mohamed A, Samodra, Yoseph Leonardo, Samy, Abdallah M, Saravanan, Aswini, Satpathy, Maheswar, Schumacher, Austin E, Sedighi, Mansour, Seekaew, Samroeng, Shafie, Mahan, Shah, Pritik A, Shahid, Samiah, Shahwan, Moyad Jamal, Shakoor, Sadia, Shalev, Noga, Shamim, Muhammad Aaqib, Shamshirgaran, Mohammad Ali, Shamsi, Anas, Sharifan, Amin, Shastry, Rajesh P, Shetty, Mahabalesh, Shittu, Aminu, Shrestha, Sunil, Siddig, Emmanuel Edwar, Sideroglou, Theologia, Sifuentes-Osornio, Jose, Silva, Luís Manuel Lopes Rodrigues, Simões, Eric A F, Simpson, Andrew J H, Singh, Amit, Singh, Surjit, Sinto, Robert, Soliman, Sameh S M, Soraneh, Soroush, Stoesser, Nicole, Stoeva, Temenuga Zhekova, Swain, Chandan Kumar, Szarpak, Lukasz, T Y, Sree Sudha, Tabatabai, Shima, Tabche, Celine, Taha, Zanan Mohammed-Ameen, Tan, Ker-Kan, Tasak, Nidanuch, Tat, Nathan Y, Thaiprakong, Areerat, Thangaraju, Pugazhenthan, Tigoi, Caroline Chepngeno, Tiwari, Krishna, Tovani-Palone, Marcos Roberto, Tran, Thang Huu, Tumurkhuu, Munkhtuya, Turner, Paul, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Noor, Ullah, Saeed, Vaithinathan, Asokan Govindaraj, Valenti, Mario, Vos, Theo, Vu, Huong T L, Waheed, Yasir, Walker, Ann Sarah, Walson, Judd L, Wangrangsimakul, Tri, Weerakoon, Kosala Gayan, Wertheim, Heiman F L, Williams, Phoebe C M, Wolde, Asrat Arja, Wozniak, Teresa M, Wu, Felicia, Wu, Zenghong, Yadav, Mukesh Kumar Kumar, Yaghoubi, Sajad, Yahaya, Zwanden Sule, Yarahmadi, Amir, Yezli, Saber, Yismaw, Yazachew Engida, Yon, Dong Keon, Yuan, Chun-Wei, Yusuf, Hadiza, Zakham, Fathiah, Zamagni, Giulia, Zhang, Haijun, Zhang, Zhi-Jiang, Zielińska, Magdalena, Zumla, Alimuddin, Zyoud, Sa'ed H. H, Zyoud, Samer H, Hay, Simon I, Stergachis, Andy, Sartorius, Benn, Cooper, Ben S, Dolecek, Christiane, and Murray, Christopher J L

Published
2024
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6. Improving antibiotic prescribing to reduce antimicrobial resistance in UTIs: the IPAP‐UTI programme.

Author

Hammond, Ashley, Muller‐Pebody, Berit, Ellis, Kate B, Brown, Colin S, Denham, Anthony, Hopkins, Susan, and Hay, Alastair D

Subjects
*ANTIBIOTICS, *URINARY tract infections, *POLICY sciences, *COST control, *DRUG resistance in microorganisms, *PRIMARY health care, *ANTIMICROBIAL stewardship, *PHYSICIAN practice patterns, *QUALITY assurance, *DRUG prescribing, *LENGTH of stay in hospitals
Abstract

Unchecked antimicrobial resistance is lethal and carries a high economic burden on the global economy. Primary care is central to the success of health service antibiotic stewardship programmes, as most of these infections are managed in the community. This article examines a pioneering programme that aims to reduce resistance to antibiotics commonly used to treat lower urinary tract infections. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Reporting England's progress towards the ambitions in the UK action plan for antimicrobial resistance: the English surveillance programme for antimicrobial utilisation and resistance (ESPAUR).

Author

Ashiru-Oredope, Diane, Cunningham, Neil, Casale, Ella, Muller-Pebody, Berit, Hope, Russell, Brown, Colin S, and Hopkins, Susan

Subjects
DRUG resistance in microorganisms, ANTIFUNGAL agents, ANTIMICROBIAL stewardship, ANTIMALARIALS, DRUG resistance in bacteria, AMBITION, CORPORATION reports
Abstract

The plans for a new antimicrobial utilization and resistance national surveillance programme, alongside the development of quality measures and methods to monitor unintended outcomes of antimicrobial stewardship and both public and professional behaviour interventions were published in 2013. Since then, England has published an annual surveillance report including outlining progress against the ambitions of the UK national action plans on antimicrobial resistance (2013 to 2018 and 2019 to 2024). A decade later we provide a brief update on progress so far, with a focus on key highlights from the latest report published in November 2022. We also provide our recommendations for areas of focus as we move into the next decade. From an initial focus on antibiotic consumption and resistance, the report now includes surveillance data for antifungals, antivirals (including novel agents, such as those targeting SARS-CoV-2) and antimalarials. Evaluation of key stewardship interventions including professional and public engagement initiatives are also reported, as well as progress against NHS England's (NHSE's) improvement measures. [ABSTRACT FROM AUTHOR]

Published
2023
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16. Risk of bloodstream infection in children admitted to paediatric intensive care units in England and Wales following emergency inter-hospital transfer

Author

Harron, Katie, Mok, Quen, Parslow, Roger, Muller-Pebody, Berit, Gilbert, Ruth, and Ramnarayan, Padmanabhan

Subjects
Blood -- Medical examination, Infection -- Risk factors, Pediatric intensive care, Health care industry
Abstract

Purpose Adherence to full sterile procedures may be compromised when central venous catheters are inserted as part of emergency resuscitation and stabilisation, particularly outside the intensive care unit. Half of emergency admissions to paediatric intensive care units (PICU) in the UK occur after stabilisation at other hospitals. We determined whether bloodstream infection (BSI) occurred more frequently in children admitted to PICU after inter-hospital transfer compared to within-hospital admissions. Methods Data on emergency admissions to 20 PICUs in England and Wales for children Results A total of 32,861/62,515 (53 %) admissions were inter-hospital transfers. Multivariable regression showed no significant difference in rates of PICU-acquired BSI by source of admission (incidence-rate ratio for inter-hospital transfer versus within-hospital admission = 0.97; 95 % CI 0.87-1.07) after adjusting for other risk-factors. Rates decreased more rapidly between 2003 and 2012 for inter-hospital transfers: 17.0 % (95 % CI 14.9-19.0 % per year) compared with 12.4 % (95 % CI 9.9-14.9 % per year) for within-hospital admissions. The median time to first PICU-acquired BSI did not differ significantly between inter-hospital transfers (7 days; IQR 4-13) and within-hospital admissions (8 days; IQR 4-15). Conclusions Nationally, inter-hospital transfer is no longer a significant risk factor for PICU-acquired BSI. Given the large proportion of infection occurring in the second week of admission, initiatives to further reduce PICU-acquired BSI should focus on maintaining sterile procedures after admission., Author(s): Katie Harron [sup.1], Quen Mok [sup.2], Roger Parslow [sup.3], Berit Muller-Pebody [sup.4], Ruth Gilbert [sup.1], Padmanabhan Ramnarayan [sup.2] Author Affiliations: (1) grid.83440.3b, 0000000121901201, UCL Institute of Child Health, , [...]

Published
2014
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17. Vancomycin may not be necessary

Author

Henderson, Katherine L, Muller-Pebody, Berit, Ladhani, Shamez, Sharland, Mike, and Johnson, Alan P

Published
2010

19. Identifying possible false matches in anonymized hospital administrative data without patient identifiers

Author

Hagger-Johnson, Gareth, Harron, Katie, Gonzalez-Izquierdo, Arturo, Cortina-Borja, Mario, Dattani, Nirupa, Muller-Pebody, Berit, Parslow, Roger, Gilbert, Ruth, and Goldstein, Harvey

Subjects
Algorithms -- Usage -- Analysis, Medical records -- Analysis, Hospital admission and discharge -- Analysis, Medical care quality -- Analysis, Business, Health care industry
Abstract

Objective. To identify data linkage errors in the form of possible false matches, where two patients appear to share the same unique identification number. Data Source. Hospital Episode Statistics (HES) in England, United Kingdom. Study Design. Data on births and re-admissions for infants (April 1, 2011 to March 31, 2012; age 0-1 year) and adolescents (April 1, 2004 to March 31, 2011; age 10-19 years). Data Collection/Extraction Methods. Hospital records pseudo-anonymized using an algorithm designed to link multiple records belonging to the same person. Six implausible clinical scenarios were considered possible false matches: multiple births sharing HESID, re-admission after death, two birth episodes sharing HESID, simultaneous admission at different hospitals, infant episodes coded as deliveries, and adolescent episodes coded as births. Principal Findings. Among 507,778 infants, possible false matches were relatively rare (n = 433, 0.1 percent). The most common scenario (simultaneous admission at two hospitals, n = 324) was more likely for infants with missing data, those born preterm, and for Asian infants. Among adolescents, this scenario (n = 320) was more common for males, younger patients, the Mixed ethnic group, and those re-admitted more frequently. Conclusions. Researchers can identify clinically implausible scenarios and patients affected, at the data cleaning stage, to mitigate the impact of possible linkage errors. Key Words. Computerized patient medical records, data linkage, data quality, medical errors, Hospital Episode Statistics (HES) are used to capture all admissions to National Health Service (NHS) hospitals in England. An algorithm is used to create a unique and anonymous identifier (the [...]

Published
2015
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20. Risk-adjusted monitoring of blood-stream infection in paediatric intensive care: a data linkage study

Author

Harron, Katie, Wade, Angie, Muller-Pebody, Berit, Goldstein, Harvey, Parslow, Roger, Gray, Jim, and Hartley, John C.

Subjects
United Kingdom. National Health Service, Infection control -- Health aspects, Infection -- Risk factors, Patient monitoring equipment -- Health aspects, Pediatric intensive care -- Health aspects, Health care industry
Abstract

Purpose National monitoring of variation in the quality of infection control in paediatric intensive care units (PICUs) requires comparisons of risk-adjusted rates. To inform the development of a national monitoring system, we evaluated the effects of risk-adjustment and outcome definition on comparisons of blood-stream infection (BSI) rates in PICU, using linkage of risk-factor data captured by national audit (PICANet) with laboratory records of BSI. Methods Admission data for two children's hospitals 2003-2010 were extracted from PICANet and linked using multiple identifiers with laboratory BSI records. We calculated trends of PICU-acquired BSI, defined as BSI occurring between at least 2 days after admission until up to 2 days following discharge. In one PICU, we compared rates of all PICU-acquired BSI with clinically significant PICU-acquired BSI submitted to the national surveillance system. Results Of 20,924 admissions, 1,428 (6.8 %) were linked to 1,761 PICU-acquired BSI episodes. The crude incidence rate-ratio for PICU-acquired BSI between PICUs was 1.15 [95 % confidence interval (CI) 1.05-1.26] but increased to 1.26 (1.14-1.39) after risk-adjustment. Rates of PICU-acquired BSI were 13.44 (95 % CI 12.60-14.28) per 1,000 bed-days at PICU 1 and 18.05 (95 % CI 16.80-19.32) at PICU 2. Of PICU-acquired BSI at PICU 2, 41 % was classified as clinically significant. Rates of PICU-acquired BSI decreased by 10 % per year between 2003 and 2010 for skin organisms and 8 % for non-skin organisms. Conclusions Risk-adjustment and standardisation of outcome measures are essential for fair comparisons of BSI rates between PICUs. Linkage of risk-factor data and BSI surveillance is feasible and could allow national risk-adjusted monitoring., Author(s): Katie Harron [sup.1], Angie Wade [sup.1], Berit Muller-Pebody [sup.2], Harvey Goldstein [sup.1], Roger Parslow [sup.3], Jim Gray [sup.4], John C. Hartley [sup.5], Quen Mok [sup.6], Ruth Gilbert [sup.1] Author [...]

Published
2013
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22. Screening for Candida auris in patients admitted to eight intensive care units in England, 2017 to 2018

Author

Sharp, Ashley, primary, Muller-Pebody, Berit, additional, Charlett, Andre, additional, Patel, Bharat, additional, Gorton, Rebecca, additional, Lambourne, Jonathan, additional, Cummins, Martina, additional, Alcolea-Medina, Adela, additional, Wilks, Mark, additional, Smith, Robin, additional, Mack, Damien, additional, Hopkins, Susan, additional, Dodgson, Andrew, additional, Burns, Phillipa, additional, Perera, Nelun, additional, Lim, Felicia, additional, Rao, Gopal, additional, Khanna, Priya, additional, Johnson, Elizabeth, additional, Borman, Andrew, additional, Schelenz, Silke, additional, Guy, Rebecca, additional, Conneely, Joanna, additional, Manuel, Rohini J, additional, and Brown, Colin S, additional

Published
2021
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23. Antimicrobial-impregnated central venous catheters for preventing neonatal bloodstream infection: the PREVAIL RCT

Author

Gilbert, Ruth, primary, Brown, Michaela, additional, Faria, Rita, additional, Fraser, Caroline, additional, Donohue, Chloe, additional, Rainford, Naomi, additional, Grosso, Alessandro, additional, Sinha, Ajay K, additional, Dorling, Jon, additional, Gray, Jim, additional, Muller-Pebody, Berit, additional, Harron, Katie, additional, Moitt, Tracy, additional, McGuire, William, additional, Bojke, Laura, additional, Gamble, Carrol, additional, and Oddie, Sam J, additional

Published
2020
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26. Mycobacterium abscessus Genomic Clusters Span Geography and Patient Groups

Author

Lipworth, Samuel, primary, Hough, Natasha, additional, Weston, Natasha, additional, Muller-Pebody, Berit, additional, Phin, Nick, additional, Myers, Richard, additional, Chapman, Stephen, additional, Flight, William, additional, Alexander, Eliza, additional, Smith, E. Grace, additional, Robinson, Esther, additional, Peto, Timothy E. A., additional, Crook, Derrick W., additional, Walker, A. Sarah, additional, Hopkins, Susan, additional, Eyre, David William, additional, and Walker, Timothy M., additional

Published
2020
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30. When do big problems far away become smaller than the problems closer to home: Lessons for antimicrobial resistance from Father Ted

Author

Donker, Tjibbe, Hopkins, Katie L., Hopkins, Susan, Muller-Pebody, Berit, Peto, Tim E.A., Johnson, Alan P., Woodford, Neil, Crook, Derrick W., Sarah Walker, A., and Robotham, Julie V.

Abstract

Infection prevention and control strategies aimed at reducing the occurrence of Carbapenemase-Producing Enterobacteriaceae (CPE) and other antimicrobial-resistant organisms often include advice about screening patients coming from hospitals with a known resistance problem, to prevent introductions into new hospitals by shared patients. We argue that, despite being an efficient method of identifying cases, admission screening for introduction prevention is only effective if the absolute number of imported cases from other hospitals outnumbers the cases coming from the hospital’s own patient population, and therefore is only a feasible control strategy during the start of an epidemic. When determining whether import screening is still advisable, we therefore need to be continuously reminded of how Father Ted so eloquently summarised the principles of perspective: “These are small, but the ones out there are far away”.

Published
2019
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31. National mycology laboratory diagnostic capacity for invasive fungal diseases in 2017: Evidence of sub-optimal practice

Author

Schelenz, Silke, primary, Owens, Katie, additional, Guy, Rebecca, additional, Rautemaa-Richardson, Riina, additional, Manuel, Rohini J., additional, Richardson, Malcolm, additional, Moore, Caroline, additional, Enoch, David A., additional, Micallef, Christianne, additional, Howard, Philip, additional, Agrawal, Samir G., additional, Johnson, Elizabeth M., additional, and Muller-Pebody, Berit, additional

Published
2019
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34. Antimicrobial-impregnated central venous catheters for prevention of neonatal bloodstream infection (PREVAIL): an open-label, parallel-group, pragmatic, randomised controlled trial

Author

Gilbert, Ruth, primary, Brown, Michaela, additional, Rainford, Naomi, additional, Donohue, Chloe, additional, Fraser, Caroline, additional, Sinha, Ajay, additional, Dorling, Jon, additional, Gray, Jim, additional, McGuire, William, additional, Gamble, Carrol, additional, Oddie, Sam J, additional, Gilbert, Ruth, additional, Sinha, Ajay K., additional, Oddie, Sam J., additional, Wane, Rachel, additional, Hubbard, Marie, additional, Astles, Rosalind, additional, Ewer, Andrew K., additional, Jackson, Rachel, additional, Ranganna, Ranganath, additional, Booth, Nicola, additional, Yajamanyam, Phani Kiran, additional, Harvey, Karen, additional, Aladangady, Narendra, additional, Mathew, Asha, additional, Pilling, Elizabeth, additional, Bayliss, Pauline, additional, Maddock, Natasha, additional, Woodhead, Louise, additional, Chang, MaySze, additional, Dharmaraj, Sandeep, additional, Lodge, Claire, additional, Navarra, Helen, additional, Roehr, Charles, additional, Barlow, Sheula, additional, Yadav, Mahesh, additional, Abbott, Claire, additional, Johnson, Kathryn, additional, Batra, Dushyant, additional, Hooton, Yvonne, additional, Cairns, Pamela, additional, Chapman, Jennifer, additional, Sharma, Bal Krishnan, additional, Smith, Helen, additional, Ali, Imdad, additional, Lancoma-Malcolm, Ivone, additional, Muller-Pebody, Berit, additional, Harron, Katie, additional, and Moitt, Tracy, additional

Published
2019
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40. Monitoring Antimicrobial Resistance and Drug Usage in the Human and Livestock Sector and Foodborne Antimicrobial Resistance in Six European Countries.

Author

Varona, Octavio Mesa, Chaintarli, Katerina, Muller-Pebody, Berit, Anjum, Muna F, Eckmanns, Tim, Norström, Madelaine, Boone, Ides, and Tenhagen, Bernd-Alois

Subjects
DRUG resistance in microorganisms, DRUG resistance, ANTI-infective agents, ANIMAL health surveillance, FOOD animals, LIVESTOCK, FOOD microbiology
Abstract

Introduction: Antimicrobial resistance (AMR), associated with antimicrobial use (AMU), is a major public concern. Surveillance and monitoring systems are essential to assess and control the trends in AMU and AMR. However, differences in the surveillance and monitoring systems between countries and sectors make comparisons challenging. The purpose of this article is to describe all surveillance and monitoring systems for AMU and AMR in the human and livestock sectors, as well as national surveillance and monitoring systems for AMR in food, in six European countries (Spain, Germany, France, the Netherlands, the United Kingdom and Norway) as a baseline for developing suggestions to overcome current limitations in comparing AMU and AMR data. Methods: A literature search in 2018 was performed to identify relevant peer-reviewed articles and national and European grey reports as well as AMU/AMR databases. Results: Comparison of AMU and AMR systems across the six countries showed a lack of standardization and harmonization with different AMU data sources (prescription vs sales data) and units of AMU and AMR being used. The AMR data varied by sample type (clinical/non-clinical), laboratory method (disk diffusion, microdilution, and VITEK, among others), data type, ie quantitative (minimum inhibition concentration (MIC) in mg/L/inhibition zone (IZ) in mm) vs qualitative data (susceptible-intermediate-resistant (SIR)), the standards used (EUCAST/CLSI among others), and/or the evaluation criteria adopted (epidemiological or clinical). Discussion: A One Health approach for AMU and AMR requires harmonization in various aspects between human, animal and food systems at national and international levels. Additionally, some overlap between systems of AMU and AMR has been encountered. Efforts should be made to improve standardization and harmonization and allow more meaningful analyses of AMR and AMU surveillance data under a One Health approach. [ABSTRACT FROM AUTHOR]

Published
2020
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43. ESPAUR 2016

Author

Hopkins, Susan, Johnson, Alan, Muller-Pebody, Berit, Ashiru-Oredope, Diane, and Schelenz, Silke

Published
2016
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44. Improving feedback of surveillance data on antimicrobial consumption, resistance and stewardship in England: putting the data at your Fingertips

Author

Johnson, Alan P., primary, Muller-Pebody, Berit, additional, Budd, Emma, additional, Ashiru-Oredope, Diane, additional, Ladenheim, David, additional, Hain, Doris, additional, Hope, Russell, additional, Bhattacharya, Alex, additional, Elgohari, Suzanne, additional, Guy, Rebecca, additional, Henderson, Katherine, additional, Puleston, Richard, additional, Rooney, Graeme, additional, Thelwall, Simon, additional, Wellington, Edgar, additional, Lamagni, Theresa, additional, and Hopkins, Susan, additional

Published
2016
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45. Evaluating bias due to data linkage error in electronic healthcare records

Author

Harron, Katie, Wade, Angie, Gilbert, Ruth, Muller-Pebody, Berit, and Goldstein, Harvey

Subjects
Epidemiology
Abstract

BACKGROUND: Linkage of electronic healthcare records is becoming increasingly important for research purposes. However, linkage error due to mis-recorded or missing identifiers can lead to biased results. We evaluated the impact of linkage error on estimated infection rates using two different methods for classifying links: highest-weight (HW) classification using probabilistic match weights and prior-informed imputation (PII) using match probabilities. METHODS: A gold-standard dataset was created through deterministic linkage of unique identifiers in admission data from two hospitals and infection data recorded at the hospital laboratories (original data). Unique identifiers were then removed and data were re-linked by date of birth, sex and Soundex using two classification methods: i) HW classification - accepting the candidate record with the highest weight exceeding a threshold and ii) PII-imputing values from a match probability distribution. To evaluate methods for linking data with different error rates, non-random error and different match rates, we generated simulation data. Each set of simulated files was linked using both classification methods. Infection rates in the linked data were compared with those in the gold-standard data. RESULTS: In the original gold-standard data, 1496/20924 admissions linked to an infection. In the linked original data, PII provided least biased results: 1481 and 1457 infections (upper/lower thresholds) compared with 1316 and 1287 (HW upper/lower thresholds). In the simulated data, substantial bias (up to 112%) was introduced when linkage error varied by hospital. Bias was also greater when the match rate was low or the identifier error rate was high and in these cases, PII performed better than HW classification at reducing bias due to false-matches. CONCLUSIONS: This study highlights the importance of evaluating the potential impact of linkage error on results. PII can help incorporate linkage uncertainty into analysis and reduce bias due to linkage error, without requiring identifiers.

Published
2014

46. Detection of the plasmid-mediatedmcr-1gene conferring colistin resistance in human and food isolates ofSalmonella entericaandEscherichia coliin England and Wales

Author

Doumith, Michel, primary, Godbole, Gauri, additional, Ashton, Philip, additional, Larkin, Lesley, additional, Dallman, Tim, additional, Day, Martin, additional, Day, Michaela, additional, Muller-Pebody, Berit, additional, Ellington, Matthew J., additional, de Pinna, Elizabeth, additional, Johnson, Alan P., additional, Hopkins, Katie L., additional, and Woodford, Neil, additional

Published
2016
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48. CATheter Infections in CHildren (CATCH): a randomised controlled trial and economic evaluation comparing impregnated and standard central venous catheters in children

Author

Harron, Katie, primary, Mok, Quen, additional, Dwan, Kerry, additional, Ridyard, Colin H, additional, Moitt, Tracy, additional, Millar, Michael, additional, Ramnarayan, Padmanabhan, additional, Tibby, Shane M, additional, Muller-Pebody, Berit, additional, Hughes, Dyfrig A, additional, Gamble, Carrol, additional, and Gilbert, Ruth E, additional

Published
2016
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49. Non-susceptibility ofEscherichia coli,Klebsiellaspp.,Pseudomonasspp.,Streptococcus pneumoniaeandStaphylococcus aureusin the UK: temporal trends in England, Northern Ireland, Scotland and Wales

Author

Guy, Rebecca, primary, Geoghegan, Lourda, additional, Heginbothom, Maggie, additional, Howe, Robin, additional, Muller-Pebody, Berit, additional, Reilly, Jacqui S., additional, Wilson, Julie, additional, Wiuff, Camilla, additional, Wyatt, Tim, additional, and Johnson, Alan P., additional

Published
2016
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50. Carbapenemase-Producing Gram-Negative Bacteria in England: Results From the First Year of Enhanced Surveillance

Author

Freeman, Rachel, primary, Ironmonger, Dean, additional, Puleston, Richard, additional, Hopkins, Katie, additional, Staves, Peter, additional, Cleary, Paul, additional, Hope, Russell, additional, Muller-Pebody, Berit, additional, Hopkins, Susan, additional, Hawkey, Peter M., additional, Woodford, Neil, additional, and Johnson, Alan P., additional

Published
2016
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