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9. Computational Re-Entry Vulnerability Index Mapping to Guide Ablation in Patients With Postmyocardial Infarction Ventricular Tachycardia

Author

Jelvehgaran, P., O'Hara, R., Prakosa, A., Chrispin, J., Boink, G.J., Trayanova, N., Coronel, R., Oostendorp, T.F., Jelvehgaran, P., O'Hara, R., Prakosa, A., Chrispin, J., Boink, G.J., Trayanova, N., Coronel, R., and Oostendorp, T.F.

Abstract

Item does not contain fulltext, BACKGROUND: Ventricular tachycardias (VTs) in patients with myocardial infarction (MI) are often treated with catheter ablation. However, the VT induction during this procedure does not always identify all of the relevant activation pathways or may not be possible or tolerated. The re-entry vulnerability index (RVI) quantifies regional activation-repolarization differences and can detect multiple regions susceptible to re-entry without the need to induce the arrhythmia. OBJECTIVES: This study aimed to further develop and validate the RVI mapping in patient-specific computational models of post-MI VTs. METHODS: Cardiac magnetic resonance imaging data from 4 patients with post-MI VTs were used to induce VTs in a computational electrophysiological model by pacing. The RVI map of a premature beat in each patient model was used to guide virtual ablations. We compared our results with those of clinical ablation in the same patients. RESULTS: Single-site virtual RVI-guided ablation prevented VT induction in 3 of 9 cases. Multisite virtual ablations guided by RVI mapping successfully prevented re-entry in all cases (9 of 9). Overall, virtual ablation required 15-fold fewer ablation sites (235.5 ± 97.4 vs 17.0 ± 6.8) and 2-fold less ablation volume (5.34 ± 1.79 mL vs 2.11 ± 0.65 mL) than the clinical ablation. CONCLUSIONS: RVI mapping allows localization of multiple regions susceptible to re-entry and may help guide VT ablation. RVI mapping does not require the induction of arrhythmia and may result in less ablated myocardial volumes with fewer ablation sites.

Published
2023

10. Effects of body mass index-related disorders on cognition: preliminary results

Author

Yesavage JA, Kinoshita LM, Noda A, Lazzeroni LC, Fairchild JK, Taylor J, Kulick D, Friedman L, Cheng J, Zeitzer JM, and O'Hara R

Subjects
Specialties of internal medicine, RC581-951
Abstract

Jerome A Yesavage,1,2 Lisa M Kinoshita,1,2 Art Noda,2 Laura C Lazzeroni,2 Jennifer Kaci Fairchild,1,2 Joy Taylor,1,2 Doina Kulick,3 Leah Friedman,1,2 Jauhtai Cheng,1,2 Jamie M Zeitzer,1,2 Ruth O’Hara1,21Department of Veterans Affairs Health Care System, Palo Alto, CA, USA; 2Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA; 3Department of Medicine, University of Nevada School of Medicine, Reno, NV, USABackground: Well-known risk factors for cognitive impairment are also associated with obesity. Research has highlighted genetic risk factors for obesity, yet the relationship of those risk factors with cognitive impairment is unknown. The objective of this study was to determine the associations between cognition, hypertension, diabetes, sleep-disordered breathing, and obesity. Genetic risk factors of obesity were also examined.Methods: The sample consisted of 369 nondemented individuals aged 50 years or older from four community cohorts. Primary outcome measures included auditory verbal memory, as measured by the Rey Auditory Verbal Learning Test, and executive functioning, as measured by the Color–Word Interference Test of the Delis–Kaplan Executive Function System battery. Apnea–hypopnea index indicators were determined during standard overnight polysomnography. Statistical analyses included Pearson correlations and linear regressions.Results: Poor executive function and auditory verbal memory were linked to cardiovascular risk factors, but not directly to obesity. Genetic factors appeared to have a small but measureable association to obesity.Conclusion: A direct linkage between obesity and poor executive function and auditory verbal memory is difficult to discern, possibly because nonobese individuals may show cognitive impairment due to insulin resistance and the “metabolic syndrome”.Keywords: sleep-disordered breathing, hypertension, diabetes, sleep apnea, BMI, obesity

Published
2014

11. Lessons from implementing the Australian National Action Plan for Endometriosis

Author

Armour, M, Avery, J, Leonardi, M, Van Niekerk, L, Druitt, ML, Parker, MA, Girling, JE, McKinnon, B, Mikocka-Walus, A, Ng, CHM, O'Hara, R, Ciccia, D, Stanley, K, Evans, S, Armour, M, Avery, J, Leonardi, M, Van Niekerk, L, Druitt, ML, Parker, MA, Girling, JE, McKinnon, B, Mikocka-Walus, A, Ng, CHM, O'Hara, R, Ciccia, D, Stanley, K, and Evans, S

Abstract

Endometriosis is a common yet under-recognised chronic disease with one in nine (more than 830,000) women and those assigned female at birth diagnosed with endometriosis by the age of 44 years in Australia. In 2018, Australia was the first country to develop a roadmap and blueprint to tackle endometriosis in a nationwide, coordinated manner. This blueprint is outlined in the National Action Plan for Endometriosis (NAPE), created from a partnership between government, endometriosis experts and advocacy groups. The NAPE aims to improve patient outcomes in the areas of awareness and education, clinical management and care and research. As researchers and clinicians are working to improve the lives of those with endometriosis, we discuss our experiences since the launch of the plan to highlight areas of consideration by other countries when developing research priorities and clinical plans. Historically, major barriers for those with endometriosis have been twofold; first, obtaining a diagnosis and secondly, effective symptom management post-diagnosis. In recent years, there have been calls to move away from the historically accepted 'gold-standard' surgical diagnosis and single-provider specialist care. As there are currently no reliable biomarkers for endometriosis diagnosis, specialist endometriosis scans and MRI incorporating artificial intelligence offer a novel method of visualisation and promising affordable non-invasive diagnostic tool incorporating well-established technologies. The recognised challenges of ongoing pain and symptom management, a holistic interdisciplinary care approach and access to a chronic disease management plan, could lead to improved patient outcomes while reducing healthcare costs. LAY SUMMARY: Endometriosis is a chronic disease where tissue like the lining of the uterus is found in other locations around the body. For the 830,000 people living with endometriosis in Australia, this often results in an immense burden on all aspe

Published
2022

15. EP24.30: Pilot study of intra‐ and interoperator agreement of a proposed image quality scoring system for transvaginal ultrasound images.

Author

Deslandes, A., Avery, J., Leonardi, M., O'Hara, R., Maple, S., Chen, H., Knox, S., Panuccio, C., Lo, G., Hull, M.L., and Condous, G.

Subjects
IMAGE quality in imaging systems, INTER-observer reliability, TRANSVAGINAL ultrasonography, INTRACLASS correlation, OVARIES
Abstract

This article discusses a pilot study that aimed to test the reliability of a proposed scoring system for quantifying the image quality of transvaginal ultrasound (TVUS) images. The scoring system, which could be used in the development of artificial intelligence tools for diagnosing endometriosis, assigned a score of 1-3 to each image based on its quality. The study involved six raters who assessed 150 images, and the results showed poor to moderate levels of interobserver and intraobserver reliability. The authors suggest that further refinement of the scoring system may be necessary to improve reliability. [Extracted from the article]

Published
2024
Full Text
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17. Thanks to Reviewers!

Author

Adams, R, Bahnson, M, Bhaduri, S, Adams, T, Bairaktarova, D, Bielefeldt, A, Aguirre-Munoz, Z, Balakrishnan, B, Blosser, EG, Ahn, B, Beagon, U, Bodnar, C, Aleong, R, Becker, K, Borgford-Parnell, J, Amelink, C, Beddoes, K, Maura, B, Anderson, R, Bego, C, Bowe, B, Andrews, CJ, Beigpourian, B, Bowen, B, Angel, J, Bekki, J, Boyd, J, Fonseca, MA, Bennett, D, Bradburn, I, Kranov, AA, Berdanier, C, Brady, C, Bae, CL, Bernhard, J, Brawner, C, Brose, A, Case, J, Cropley, D, Brown, F, Cassady, R, Cross, K, Brown, P, Celik, S, Cunningham, P, Ben, C, Cutler, S, Brown, S, Chance, SM, Dabbagh, N, Brozina, C, Chen, H, Dallal, A, Brunhaver, S, Chen, O, Daly, S, Bryant, A, Cheville, RA, Daniel, S, Bucciarelli, L, Chiu, J, Danowitz, A, Burkholder, E, Choe, NH, Darolia, R, Burks, G, Clark, R, Davis, K, Burt, B, Clevenger, C, Davis, S, Canney, N, Cole, J, de Jong, T, Cao, Y, Coley, B, De Vries, C, Caratozzolo, P, Cooper, L, Delaine, D, Carballo, R, Cooper, M, DeMonbrun, R, Cardella, M, Craig, T, Denton, M, Di Stefano, M, Erdman, AM, Gilmartin, S, DiBiasio, D, Eris, O, Gladstone, J, Diefes-Dux, H, Evangelou, D, Glancy, A, Dika, S, Ewen, B, Godwin, A, Direito, I, Faber, C, Goldsmith, R, Dohn, N, Falconer, J, Grigg, SJ, Dolansky, M, Fantz, T, Grohs, J, Faulkner, B, Doom, D, Felder, R, Gummer, E, Douglas, E, Ferris, T, Guzey, S, Douglas, KA, Figueiredo, J, Hadgraft, R, Dounas-Frazer, D, Fiorella, L, Hammack, R, Dringenberg, E, Flores, L, Han, K, Duffy, G, Fong, C, Harding, T, Easley, D, Fowler, RR, Harper, K, Eccles, J, Friedrichsen, D, Hartmann, B, Edstrom, K, Ge, J, Hattingh, T, Ellestad, R, Gelles, L, Henderson, R, Henderson, TS, Immekus, J, Kamphorst, J, Herman, G, Inda, M, Karatas, F, Hess, J, Itabashi-Campbell, R, Kartal, O, Hieb, J, Jackson, A, Karwat, D, Higbee, S, Jankowski, N, Katz, A, Hilton, E, Javernick-Will, A, Keipi, T, Hira, A, Jensen, KJ, Kim, D, Hirshfield, L, Smith, J, Kirn, A, Knaphus-Soran, E, Holly, J, Jesiek, B, Knight, D, Horng, S-M, Johnson, A, Knott, T, Huang-Saad, A, Johnson, B, Kohl, P, Huerta, M, Johri, A, Kohtala, C, Huff, J, Jones, B, Komives, S, Hughes, B, Jones, L, Korsunskiy, E, Hughes, R, Jones, T, Kotys-Schwartz, D, Hunsu, N, Kaminski, J, Kramer, J, Hunter, C, Kampe, J-C, Inkelas, KK, Lamm, M, Lonngren, J, McCall, C, Lande, M, Lottero-Perdue, PS, McCave, E, Lappalainen, P, Aguilar, JFL, McCray, E, Lawanto, O, Lucena, J, McGee, E, Lawson, J, Luk, LYY, McGough, C, Leath, S, Lutz, B, McGowan, V, Lee, D, Ma, Y, McNair, LD, Lee, W, Madon, T, McNaughtan, J, Liberatore, M, Mamaril, N, McNeill, N, Lichtenstein, G, Mangiante, E, Mejia, J, Lima, M, Martin, B, Diaz, NM, Lima, RM, Martin, K, Menekse, M, Lin, J, Lippard, C, Mones, AM, Mesquita, DIDA, Michell, K, Litzler, E, Matthews, M, Miller, S, Lo, CK, Matusovich, H, Minichiello, A, London, J, Maynard, N, Miskioglu, EE, Longwell-Grice, R, Mazzurco, A, Yusof, KM, Mohedas, I, Nghia, TLH, Pearson, A, Monat, J, Norton, P, Pearson, N, Monteiro, F, Novoselich, BJ, Pembridge, J, Moote, J, Noy, S, Perez-Felkner, L, Mora, M, O'Hara, R, Perkins, H, O'Moore, L, Peters-Burton, E, Morgan, D, Ohland, M, Pfirman, A, Morgan, T, Okai, B, Pinto, C, Morton, T, Olds, B, Pitterson, N, Mosyjowski, E, Orr, M, Polmear, M, Murphy, T, Ortega-Alvarez, JD, Prince, T, Murray, J, Oseguera, L, Purzer, S, Murzi, H, Owen, C, Quan, GM, Nagy, G, Ozkan, DS, Quillin, K, Natarajathinam, M, Panther, G, Rayess, N, Nelson, M, Patrick, A, Reed, T, Newberry, B, Paul, K, Reeping, D, Newstetter, W, Pawley, A, Reese, M, Reid, K, Rulifson, G, Shivy, V, Renn, K, Rynearson, AM, Simpson, Z, Ricco, G, Sanchez-Pena, ML, Sitomer, A, Richards, L, Saunders-Smits, G, Siverling, E, Rios, L, Sax, L, Slaton, A, Ro, HK, Schimpf, C, Sleezer, R, Roberts, D, Rodgers, K, Schippers, M, Smith-On, C, Rodriguez, S, Schnittka, C, Schunn, C, Rogers, C, Seah, LH, Rohde, J, Rohrer, D, Secules, S, Smith, K, Smith, N, Romine, W, Seifert, C, Sochacka, N, Ross, L, Sessa, V, Stearns, E, Ross, M, Sharp, H, Steif, M, Rottmann, C, Sharp, J, Stephan, P, Rucks, L, Shaw, C, Stevens, R, Streveler, R, Tolbert, D, van Der Marel, F, Strobel, J, Toraman, S, van Hattum, N, Stump, G, Tougaw, D, Verdin, D, Su, X, Trautvetter, LC, Verleger, M, Sundararaja, N, Trenshaw, KF, Vieira, C, Trevelyan, J, Svihla, V, Troussas, C, Villanueva, I, Swan, C, Tsai, J, Vinck, D, Virguez, L, Swanson, R, Tsugawa, MA, Vitasari, P, Sweeny, K, Tuononen, T, Vossoughi, S, Swenson, J, Turner, J, Wallin, P, Talley, K, Turner, S, Tan, L, Tyson, W, Watted, A, Tang, Y, Utley, J, Webber, K, Tank, K, Vasquez, RV, Weintrop, D, Thomas, K, Valdivia, A, Weiss, E, Thompson, JD, Valentine, A, West, R, Tierney, G, Van den Bogaard, M, Wiles, D, Wilson-Lopez, AA, Xinrui, X, Zastavker, Y, Wilson, D, Xu, YJ, Zhang, G, Wolmarans, N, Yang, Y, Zhu, J, Wong, R, Yi, S, Zoltowski, CB, Woollacott, L, Yoon, SY, Adams, R, Bahnson, M, Bhaduri, S, Adams, T, Bairaktarova, D, Bielefeldt, A, Aguirre-Munoz, Z, Balakrishnan, B, Blosser, EG, Ahn, B, Beagon, U, Bodnar, C, Aleong, R, Becker, K, Borgford-Parnell, J, Amelink, C, Beddoes, K, Maura, B, Anderson, R, Bego, C, Bowe, B, Andrews, CJ, Beigpourian, B, Bowen, B, Angel, J, Bekki, J, Boyd, J, Fonseca, MA, Bennett, D, Bradburn, I, Kranov, AA, Berdanier, C, Brady, C, Bae, CL, Bernhard, J, Brawner, C, Brose, A, Case, J, Cropley, D, Brown, F, Cassady, R, Cross, K, Brown, P, Celik, S, Cunningham, P, Ben, C, Cutler, S, Brown, S, Chance, SM, Dabbagh, N, Brozina, C, Chen, H, Dallal, A, Brunhaver, S, Chen, O, Daly, S, Bryant, A, Cheville, RA, Daniel, S, Bucciarelli, L, Chiu, J, Danowitz, A, Burkholder, E, Choe, NH, Darolia, R, Burks, G, Clark, R, Davis, K, Burt, B, Clevenger, C, Davis, S, Canney, N, Cole, J, de Jong, T, Cao, Y, Coley, B, De Vries, C, Caratozzolo, P, Cooper, L, Delaine, D, Carballo, R, Cooper, M, DeMonbrun, R, Cardella, M, Craig, T, Denton, M, Di Stefano, M, Erdman, AM, Gilmartin, S, DiBiasio, D, Eris, O, Gladstone, J, Diefes-Dux, H, Evangelou, D, Glancy, A, Dika, S, Ewen, B, Godwin, A, Direito, I, Faber, C, Goldsmith, R, Dohn, N, Falconer, J, Grigg, SJ, Dolansky, M, Fantz, T, Grohs, J, Faulkner, B, Doom, D, Felder, R, Gummer, E, Douglas, E, Ferris, T, Guzey, S, Douglas, KA, Figueiredo, J, Hadgraft, R, Dounas-Frazer, D, Fiorella, L, Hammack, R, Dringenberg, E, Flores, L, Han, K, Duffy, G, Fong, C, Harding, T, Easley, D, Fowler, RR, Harper, K, Eccles, J, Friedrichsen, D, Hartmann, B, Edstrom, K, Ge, J, Hattingh, T, Ellestad, R, Gelles, L, Henderson, R, Henderson, TS, Immekus, J, Kamphorst, J, Herman, G, Inda, M, Karatas, F, Hess, J, Itabashi-Campbell, R, Kartal, O, Hieb, J, Jackson, A, Karwat, D, Higbee, S, Jankowski, N, Katz, A, Hilton, E, Javernick-Will, A, Keipi, T, Hira, A, Jensen, KJ, Kim, D, Hirshfield, L, Smith, J, Kirn, A, Knaphus-Soran, E, Holly, J, Jesiek, B, Knight, D, Horng, S-M, Johnson, A, Knott, T, Huang-Saad, A, Johnson, B, Kohl, P, Huerta, M, Johri, A, Kohtala, C, Huff, J, Jones, B, Komives, S, Hughes, B, Jones, L, Korsunskiy, E, Hughes, R, Jones, T, Kotys-Schwartz, D, Hunsu, N, Kaminski, J, Kramer, J, Hunter, C, Kampe, J-C, Inkelas, KK, Lamm, M, Lonngren, J, McCall, C, Lande, M, Lottero-Perdue, PS, McCave, E, Lappalainen, P, Aguilar, JFL, McCray, E, Lawanto, O, Lucena, J, McGee, E, Lawson, J, Luk, LYY, McGough, C, Leath, S, Lutz, B, McGowan, V, Lee, D, Ma, Y, McNair, LD, Lee, W, Madon, T, McNaughtan, J, Liberatore, M, Mamaril, N, McNeill, N, Lichtenstein, G, Mangiante, E, Mejia, J, Lima, M, Martin, B, Diaz, NM, Lima, RM, Martin, K, Menekse, M, Lin, J, Lippard, C, Mones, AM, Mesquita, DIDA, Michell, K, Litzler, E, Matthews, M, Miller, S, Lo, CK, Matusovich, H, Minichiello, A, London, J, Maynard, N, Miskioglu, EE, Longwell-Grice, R, Mazzurco, A, Yusof, KM, Mohedas, I, Nghia, TLH, Pearson, A, Monat, J, Norton, P, Pearson, N, Monteiro, F, Novoselich, BJ, Pembridge, J, Moote, J, Noy, S, Perez-Felkner, L, Mora, M, O'Hara, R, Perkins, H, O'Moore, L, Peters-Burton, E, Morgan, D, Ohland, M, Pfirman, A, Morgan, T, Okai, B, Pinto, C, Morton, T, Olds, B, Pitterson, N, Mosyjowski, E, Orr, M, Polmear, M, Murphy, T, Ortega-Alvarez, JD, Prince, T, Murray, J, Oseguera, L, Purzer, S, Murzi, H, Owen, C, Quan, GM, Nagy, G, Ozkan, DS, Quillin, K, Natarajathinam, M, Panther, G, Rayess, N, Nelson, M, Patrick, A, Reed, T, Newberry, B, Paul, K, Reeping, D, Newstetter, W, Pawley, A, Reese, M, Reid, K, Rulifson, G, Shivy, V, Renn, K, Rynearson, AM, Simpson, Z, Ricco, G, Sanchez-Pena, ML, Sitomer, A, Richards, L, Saunders-Smits, G, Siverling, E, Rios, L, Sax, L, Slaton, A, Ro, HK, Schimpf, C, Sleezer, R, Roberts, D, Rodgers, K, Schippers, M, Smith-On, C, Rodriguez, S, Schnittka, C, Schunn, C, Rogers, C, Seah, LH, Rohde, J, Rohrer, D, Secules, S, Smith, K, Smith, N, Romine, W, Seifert, C, Sochacka, N, Ross, L, Sessa, V, Stearns, E, Ross, M, Sharp, H, Steif, M, Rottmann, C, Sharp, J, Stephan, P, Rucks, L, Shaw, C, Stevens, R, Streveler, R, Tolbert, D, van Der Marel, F, Strobel, J, Toraman, S, van Hattum, N, Stump, G, Tougaw, D, Verdin, D, Su, X, Trautvetter, LC, Verleger, M, Sundararaja, N, Trenshaw, KF, Vieira, C, Trevelyan, J, Svihla, V, Troussas, C, Villanueva, I, Swan, C, Tsai, J, Vinck, D, Virguez, L, Swanson, R, Tsugawa, MA, Vitasari, P, Sweeny, K, Tuononen, T, Vossoughi, S, Swenson, J, Turner, J, Wallin, P, Talley, K, Turner, S, Tan, L, Tyson, W, Watted, A, Tang, Y, Utley, J, Webber, K, Tank, K, Vasquez, RV, Weintrop, D, Thomas, K, Valdivia, A, Weiss, E, Thompson, JD, Valentine, A, West, R, Tierney, G, Van den Bogaard, M, Wiles, D, Wilson-Lopez, AA, Xinrui, X, Zastavker, Y, Wilson, D, Xu, YJ, Zhang, G, Wolmarans, N, Yang, Y, Zhu, J, Wong, R, Yi, S, Zoltowski, CB, Woollacott, L, and Yoon, SY

Published
2021

21. Outcomes of obstructed abdominal wall hernia: results from the UK national small bowel obstruction audit

Author

Lee, MJ, Drake, TM, Sayers, AE, Walsh, CJ, Davies, MM, Fearnhead, NS, Abercrombie, J, Acheson, A, Alderson, D, Anderson, I, Bach, S, Davies, M, Hamady, Z, Hind, D, Hollyman, M, Hare, S, Lee, E, Northover, J, Lewis, C, Marriott, P, Maynard, N, Murray, D, Tierney, G, Verjee, A, Wild, J, Abbott, S, Abdulaal, Y, Afshar, S, Ah‐Chuen, J, Ahmed, T, Akhtar, M, Akram, F, Aldred, E, Ali, A, Aly, M, Amajuoyi, A, Amin, V, Anderson, D, Anderson, O, Andreou, A, Ansari, A, Appleton, S, Ardley, R, Arshad, F, Ashour, O, Asour, A, Athem, A, Athersmith, M, Ayoub, F, Azeem, H, Azhar, B, Badenoch, T, Baillie, C, Bandyopadhyay, D, Barker, J, Barker, S, Barkham, B, Baron, R, Barrie, J, Barry‐Yarrow, E, Bashir, G, Battersby, N, Bazoua, G, Behar, N, Bellam, S, Berger, C, Bhandari, S, Bhasin, S, Biggs, S, Bisset, C, Blake, L, Blencowe, N, Boam, T, Boddy, A, Boereboom, C, Bogdan, M, Bogle, R, Bohra, P, Boland, M, Bolkan, H, Borg, C, Boulton, R, Bouras, G, Boyer, M, Boyle, J, Branagan, G, Brewer, H, Briggs, C, Broadhurst, J, Brown, E, Brown, J, Brown, L, Brown, O, Burns, K, Butcher, K, Butler, M, Byrne, B, Campbell, L, Capper, C, Cartmell, M, Cash, T, Chan, S, Chandratreya, N, Chapman, J, Chapman, S, Charalabopoulos, A, Cheek, C, Chok, S, Choong, W, Chow, M, Chowdhury, J, Coe, P, Conaghan, P, Conn, G, Cook, N, Cook, T, Cooper, S, Cornish, J, Cotton, D, Cox, C, Coyne, P, Crook, R, Crozier, J, Cuffolo, G, Cunha, P, Curtis, N, Cutting, J, Da Costa, K, Silva, L, Das, B, Davenport, M, Davies, J, Davies, T, Day, A, Dayal, S, Dean, S, Demetriou, G, Dengu, F, Dennis, R, Dent, H, Dent, P, Deputy, M, Devoto, L, Di Benedetto, G, Dindyal, S, Donnelly, E, Doody, P, Douka, E, Downham, C, Dowson, H, Edent, H, Edgerton, K, Ekpete, N, El Farran, M, Elamin, O, Eljaafari, M, Elsaid, N, El‐Sharif, M, Evans, J, Evans, M, Ewe, R, Ewing, A, Exarchou, K, Fallaize, R, Faoury, M, Farag, S, Farinella, E, Faulkner, G, Ferguson, H, Fisher, O, Fletcher, J, Forouzanfar, A, Foster, A, Fox, R, Francis, N, Fretwell, V, Fung, D, Gammeri, E, Garnham, J, Geraghty, A, Gilbert, A, Gill, C, Gill, M, Gillespie, M, Giordano, P, Glasbey, J, Goh, M, Golder, A, Green, N, Gregoir, T, Grey, T, Groundwater, E, Grove, T, Growcott, S, Gunasekaran, S, Habib, H, Haddow, J, Halahakoon, V, Halkias, C, Hall, C, Hampson, A, Hancock, L, Hanna, T, Hannay, J, Harikrishnan, A, Harries, R, Harris, G, Hartley, J, Harvey, K, Hawkin, P, Hawkins, J, Healy, R, Heard, R, Heartshorne, R, Heller, S, Hendra, L, Herrod, P, Heywood, N, Hicks, G, Hobson, B, Holtham, S, Hope, C, Hopley, P, Hossain, T, Hossaini, S, Howse, F, Hubbard, T, Humphreys, A, Ikram, H, Ioannis, M, Iqbal, M, Iqbal, N, Jain, R, Jatania, J, Jenkinson, P, Jokhan, S, Jones, A, Jones, C, Jones, L, Joshi, H, Joshi, K, Joy, M, Jull, P, Kakaniaris, G, Kallam, R, Kane, E, Kang, P, Kanitkar, R, Kauser, S, Kazmi, F, Kedrzycki, M, Kelly, S, Kendall, J, Khan, M, Khan, T, King, G, Kisiel, A, Kitsis, C, Kolawole, I, Korambayil, S, Kosasih, S, Kosti, A, Kotb, A, Kouris, S, Kshatriya, K, Kumar, S, Lafaurie, G, Lal, R, Lau, A, Lazim, T, Lazzaro, A, Lee, K, Lefroy, R, Leinhardt, D, Lennon, H, Leong, K, Levy, B, Lim, E, Lim, J, Lindley, S, Liu, D, Lloyd, P, Locker, D, Lockwood, S, Lowe, C, Lund, J, Lunevicius, R, Lunt, A, Lutfi, S, Luther, A, Luwemba, S, Mahankali‐Rao, P, Mahroof, S, Mai, D, Majid, S, Malik, A, Malik, K, Mann, K, Mansour, S, Manu, N, Mapara, R, Martin, C, Martin, J, Martin, R, Mason, C, Massey, L, Mathias, J, Mathur, P, Maude, K, McArthur, D, McCain, S, McCluney, S, McFall, M, McIlroy, B, McKay, S, McKinley, N, McNair, A, McWhirter, D, Mekhail, P, Mellor, K, Merchant, J, Merker, L, Messenger, D, Miles, A, Mir, S, Mishra, A, Mistry, P, Miu, V, Moat, M, Mockford, K, Mohamed, E, Mohamed, I, Mondragon‐Pritchard, M, Moore, N, Moretti, L, Morris, H, Morrison, T, Morrison‐Jones, V, Moss, J, Moug, S, Mountford, D, Moynihan, R, Muhammad, K, Muldoon‐Smith, D, Mulholland, J, Mullan, M, Murgitroyd, E, Murugaiyan, K, Myers, A, Mykoniatis, I, Nana, G, Nash, T, Nassar, A, Newton, R, Ng, C, Ng, P, Nguyen, K, Nicholas, F, Noor, M, Nowers, J, Nugent, C, Nunn, A, Nunn, R, Obeid, N, O'Callaghan, J, O'Hara, R, Oke, O, Olivier, J, O'Neill, A, O'Neill, S, Osei‐Bordom, D, Osgood, L, Panagiotopoulos, S, Panchasara, B, Parks, R, Patel, H, Patel, P, Patel, R, Patel, S, Pawelec, K, Payne, C, Pearson, K, Perin, G, Peristerakis, I, Petronio, B, Phelan, L, Phillips, J, Pisaneschi, C, Pitt, J, Plunkett‐Reed, K, Ponchietti, L, Pouzi, A, Pouzi, M, Powell, A, Powell‐Chandler, A, Pranesh, N, Proctor, V, Pywell, S, Qureshi, A, Qureshi, N, Rahman, M, Rai, Z, Ramcharan, S, Rangarajan, K, Rashid, M, Reader, H, Rehman, A, Rehman, S, Rengifo, C, Richards, E, Richardson, N, Robinson, A, Robinson, D, Rossi, B, Rutherford, F, Sadien, I, Saghir, T, Sahnan, K, Salahia, G, Sarveswaran, J, Saunders, M, Scott, B, Scott, K, Seager, A, Seal, S, Sezen, E, Shaban, F, Shah, P, Shahmohammadi, M, Shamsiddinova, A, Shankar, S, Sharpe, A, Shatkar, V, Sheel, A, Shields, T, Shinkwin, M, Shurmer, J, Siddika, A, Siddiqui, S, Simson, R, Sinclair, P, Singh, B, Singh, S, Sivaraj, J, Skaife, P, Skelly, B, Skinner, A, Slim, N, Smart, C, Smart, N, Smith, F, Smith, I, Smith, R, Spence, G, Sreedhar, A, Steinke, J, Stevenson, L, Stewart‐Parker, E, Stott, M, Stubbs, B, Stylianides, N, Subramonia, S, Swinkin, M, Swinscoe, M, Symons, N, Tahir, W, Taj, T, Takacs, K, Tam, J, Tan, K, Tani, S, Tanner, N, Tao, D, Taylor, M, Thava, B, Thippeswamy, K, Thomas, C, Thompson, E, Thompson, R, Thompson‐Reil, C, Thorn, C, Tongo, F, Toth, G, Turnbull, A, Turnbull, J, Valero, C, Boxel, G, Varcada, M, Venn, M, Ventham, N, Venza, M, Vimalachandran, D, Virlos, I, Wade, T, Wafi, A, Waite, K, Walker, M, Walker, N, Walker, T, Walsh, U, Wardle, S, Warner, R, Watfah, J, Watson, N, Watt, J, Watts, J, Wayman, J, Weegenaar, C, West, H, West, M, Whitehurst, L, Whyler, M, Wiggans, M, Wijeyekoon, S, Williams, G, Williams, R, Williamson, A, Williamson, J, Wilson, J, Winter, A, Wolpert, L, Wong, J, Yeap, E, Yeong, T, Zaman, S, Zappa, B, and Zosimas, D

Subjects
Adult, Male, medicine.medical_specialty, National Audit of Small Bowel Obstruction Steering Group and National Audit of Small Bowel Obstruction Collaborators, Incisional hernia, lcsh:Surgery, 030230 surgery, Abdominal wall, 03 medical and health sciences, 0302 clinical medicine, Postoperative Complications, NASBO Collaborators, medicine, Humans, Hernia, Hospital Mortality, General, Emergency Treatment, Aged, Proportional Hazards Models, Aged, 80 and over, Groin, business.industry, Mortality rate, Hazard ratio, West Midlands Research Collaborative, General Medicine, Odds ratio, Original Articles, lcsh:RD1-811, Middle Aged, medicine.disease, Quality Improvement, United Kingdom, Surgery, Hernia, Abdominal, Bowel obstruction, medicine.anatomical_structure, Logistic Models, 030220 oncology & carcinogenesis, Original Article, Female, business, NASBO Steering Group, Intestinal Obstruction
Abstract

Background Abdominal wall hernia is a common surgical condition. Patients may present in an emergency with bowel obstruction, incarceration or strangulation. Small bowel obstruction (SBO) is a serious surgical condition associated with significant morbidity. The aim of this study was to describe current management and outcomes of patients with obstructed hernia in the UK as identified in the National Audit of Small Bowel Obstruction (NASBO). Methods NASBO collated data on adults treated for SBO at 131 UK hospitals between January and March 2017. Those with obstruction due to abdominal wall hernia were included in this study. Demographics, co‐morbidity, imaging, operative treatment, and in‐hospital outcomes were recorded. Modelling for factors associated with mortality and complications was undertaken using Cox proportional hazards and multivariable regression modelling. Results NASBO included 2341 patients, of whom 415 (17·7 per cent) had SBO due to hernia. Surgery was performed in 312 (75·2 per cent) of the 415 patients; small bowel resection was required in 198 (63·5 per cent) of these operations. Non‐operative management was reported in 35 (54 per cent) of 65 patients with a parastomal hernia and in 34 (32·1 per cent) of 106 patients with an incisional hernia. The in‐hospital mortality rate was 9·4 per cent (39 of 415), and was highest in patients with a groin hernia (11·1 per cent, 17 of 153). Complications were common, including lower respiratory tract infection in 16·3 per cent of patients with a groin hernia. Increased age was associated with an increased risk of death (hazard ratio 1·05, 95 per cent c.i. 1·01 to 1·10; P = 0·009) and complications (odds ratio 1·05, 95 per cent c.i. 1·02 to 1·09; P = 0·001). Conclusion NASBO has highlighted poor outcomes for patients with SBO due to hernia, highlighting the need for quality improvement initiatives in this group., This study shows that small bowel obstruction due to abdominal wall hernia is common, typically involves a co‐morbid group of patients and has poor outcomes, including high mortality rates. High mortality from this problem

Published
2020

23. Count transformation models

Author

O'Hara, Robert B, O'Hara, R B ( Robert B ), Siegfried, Sandra; https://orcid.org/0000-0002-7312-1001, Hothorn, Torsten; https://orcid.org/0000-0001-8301-0471, O'Hara, Robert B, O'Hara, R B ( Robert B ), Siegfried, Sandra; https://orcid.org/0000-0002-7312-1001, and Hothorn, Torsten; https://orcid.org/0000-0001-8301-0471

Abstract

The effect of explanatory environmental variables on a species' distribution is often assessed using a count regression model. Poisson generalized linear models or negative binomial models are common, but the traditional approach of modelling the mean after log or square root transformation remains popular and in some cases is even advocated.2. We propose a novel framework of linear models for count data. Similar to the traditional approach, the new models apply a transformation to count responses; however, this transformation is estimated from the data and not defined a priori. In contrast to simple least-squares fitting and in line with Poisson or negative binomial models, the exact discrete likelihood is optimized for parameter estimation and inference. Simple interpretation of effects in the linear predictors is possible.3. Count transformation models provide a new approach to regressing count data in a distribution-free yet fully parametric fashion, obviating the need to a priori commit to a specific parametric family of distributions or to a specific transformation. The models are a generalization of discrete Weibull models for counts and are thus able to handle over- and underdispersion. We demonstrate empirically that the models are more flexible than Poisson or negative binomial models but still maintain interpretability of multiplicative effects. A re-analysis of deer–vehicle collisions and the results of artificial simulation experiments provide evidence of the practical applicability of the model framework.4. In ecology studies, uncertainties regarding whether and how to transform count data can be resolved in the framework of count transformation models, which were designed to simultaneously estimate an appropriate transformation and the linear effects of environmental variables by maximizing the exact count log-likelihood. The application of data-driven transformations allows over- and under-dispersion to be addressed in a model-based approach. Models

Published
2020

24. Understanding variation in ambulance service non-conveyance rates: a mixed methods study

Author

O’Cathain, A., Knowles, E., Bishop-Edwards, L., Coster, J., Crum, A., Jacques, R., James, C., Lawson, R., Marsh, M., O’Hara, R., Siriwardena, A.N., Stone, T., Turner, J., and Williams, J.

Subjects
A300 Clinical Medicine, business.industry, Project commissioning, lcsh:Public aspects of medicine, Reproduction (economics), Multimethodology, Acknowledgement, MEDLINE, Library science, lcsh:RA1-1270, 030208 emergency & critical care medicine, Science park, 03 medical and health sciences, 0302 clinical medicine, Work (electrical), Political science, B780 Paramedical Nursing, Emergency medical services, 030212 general & internal medicine, B990 Subjects Allied to Medicine not elsewhere classified, business
Abstract

Background In England in 2015/16, ambulance services responded to nearly 11 million calls. Ambulance Quality Indicators show that half of the patients receiving a response by telephone or face to face were not conveyed to an emergency department. A total of 11% of patients received telephone advice only. A total of 38% of patients were sent an ambulance but were not conveyed to an emergency department. For the 10 large ambulance services in England, rates of calls ending in telephone advice varied between 5% and 17%. Rates of patients who were sent an ambulance but not conveyed to an emergency department varied between 23% and 51%. Overall non-conveyance rates varied between 40% and 68%. Objective To explain variation in non-conveyance rates between ambulance services. Design A sequential mixed methods study with five work packages. Setting Ten of the 11 ambulance services serving > 99% of the population of England. Methods (1) A qualitative interview study of managers and paramedics from each ambulance service, as well as ambulance commissioners (totalling 49 interviews undertaken in 2015). (2) An analysis of 1 month of routine data from each ambulance service (November 2014). (3) A qualitative study in three ambulance services with different published rates of calls ending in telephone advice (120 hours of observation and 20 interviews undertaken in 2016). (4) An analysis of routine data from one ambulance service linked to emergency department attendance, hospital admission and mortality data (6 months of 2013). (5) A substudy of non-conveyance for people calling 999 with breathing problems. Results Interviewees in the qualitative study identified factors that they perceived to affect non-conveyance rates. Where possible, these perceptions were tested using routine data. Some variation in non-conveyance rates between ambulance services was likely to be due to differences in the way rates were calculated by individual services, particularly in relation to telephone advice. Rates for the number of patients sent an ambulance but not conveyed to an emergency department were associated with patient-level factors: age, sex, deprivation, time of call, reason for call, urgency level and skill level of attending crew. However, variation between ambulance services remained after adjustment for patient-level factors. Variation was explained by ambulance service-level factors after adjustment for patient-level factors: the percentage of calls attended by advanced paramedics [odds ratio 1.05, 95% confidence interval (CI) 1.04 to 1.07], the perception of ambulance service staff and commissioners that advanced paramedics were established and valued within the workforce of an ambulance service (odds ratio 1.84, 95% CI 1.45 to 2.33), and the perception of ambulance service staff and commissioners that senior management was risk averse regarding non-conveyance within an ambulance service (odds ratio 0.78, 95% CI 0.63 to 0.98). Limitations Routine data from ambulance services are complex and not consistently collected or analysed by ambulance services, thus limiting the utility of comparative analyses. Conclusions Variation in non-conveyance rates between ambulance services in England could be reduced by addressing variation in the types of paramedics attending calls, variation in how advanced paramedics are used and variation in perceptions of the risk associated with non-conveyance within ambulance service management. Linking routine ambulance data with emergency department attendance, hospital admission and mortality data for all ambulance services in the UK would allow comparison of the safety and appropriateness of their different non-conveyance rates. Funding The National Institute for Health Research Health Services and Delivery Research programme.

Published
2018

27. National prospective cohort study of the burden of acute small bowel obstruction

Author

Lee, M. J., Sayers, A. E., Drake, T. M., Marriott, P. J., Anderson, I. D., Bach, S. P., Bradburn, M., Hind, D., Verjee, A., Fearnhead, N. S., Abercrombie, John, Acheson, Austin, Alderson, Derek, Anderson, Iain, Davies, Michael, Hamady, Zaed, Hollyman, Marianne, Hare, Sarah, Lee, Ellen, Northover, John, Lewis, Christopher, McFall, Malcolm, Murugananthan, Aravinth, Murray, David, Singh, Pritam, Tierney, Gillian, Walsh, Ciaran, Wild, Jonathan, Wilson, Timothy, Abbott, S, Abdulaal, Y, Afshar, S, Ah‐Chuen, J, Ahmed, T, Akhtar, M, Akram, F, Aldred, E, Ali, A, Aly, M, Amajuoyi, A, Amin, V, Anderson, D, Anderson, O, Andreou, A, Ansari, A, Appleton, S, Ardley, R, Arshad, F, Ashour, O, Asour, A, Athem, A, Athersmith, M, Ayoub, F, Azeem, H, Azhar, B, Badenoch, T, Baillie, C, Bandyopadhyay, D, Barker, J, Barker, S, Barkham, B, Baron, R, Barrie, J, Barry‐Yarrow, E, Bashir, G, Battersby, N, Bazoua, G, Behar, N, Bellam, S, Berger, C, Bhandari, S, Bhasin, S, Biggs, S, Bisset, C, Blake, L, Blencowe, N, Boam, T, Boddy, A, Boereboom, C, Bogdan, M, Bogle, R, Bohra, P, Boland, M, Bolkan, H, Borg, C, Boulton, R, Bouras, G, Boyer, M, Boyle, J, Branagan, G, Brewer, H, Briggs, C, Broadhurst, J, Brown, E, Brown, J, Brown, L, Brown, O, Burns, K, Butcher, K, Butler, M, Byrne, B, Campbell, L, Capper, C, Cartmell, M, Cash, T, Chan, S, Chandratreya, N, Chapman, J, Chapman, S, Charalabopoulos, A, Cheek, C, Chok, S, Choong, W, Chow, M, Chowdhury, J, Coe, P, Conaghan, P, Conn, G, Cook, N, Cook, T, Cooper, S, Cornish, J, Cotton, D, Cox, C, Coyne, P, Crook, R, Crozier, J, Cuffolo, G, Cunha, P, Curtis, N, Cutting, J, Da Costa, K, Silva, L, Das, B, Davenport, M, Davies, J, Davies, T, Day, A, Dayal, S, Dean, S, Demetriou, G, Dengu, F, Dennis, R, Dent, H, Dent, P, Deputy, M, Devoto, L, Di Benedetto, G, Dindyal, S, Donnelly, E, Doody, P, Douka, E, Downham, C, Dowson, H, Edent, H, Edgerton, K, Ekpete, N, El Farran, M, Elamin, O, Eljaafari, M, Elsaid, N, El‐Sharif, M, Evans, J, Evans, M, Ewe, R, Ewing, A, Exarchou, K, Fallaize, R, Faoury, M, Farag, S, Farinella, E, Faulkner, G, Ferguson, H, Fisher, O, Fletcher, J, Forouzanfar, A, Foster, A, Fox, R, Francis, N, Fretwell, V, Fung, D, Gammeri, E, Garnham, J, Geraghty, A, Gilbert, A, Gill, C, Gill, M, Gillespie, M, Giordano, P, Glasbey, J, Goh, M, Golder, A, Green, N, Gregoir, T, Grey, T, Groundwater, E, Grove, T, Growcott, S, Gunasekaran, S, Habib, H, Haddow, J, Halahakoon, V, Halkias, C, Hall, C, Hampson, A, Hancock, L, Hanna, T, Hannay, J, Harikrishnan, A, Harries, R, Harris, G, Hartley, J, Harvey, K, Hawkin, P, Hawkins, J, Healy, R, Heard, R, Heartshorne, R, Heller, S, Hendra, L, Herrod, P, Heywood, N, Hicks, G, Hobson, B, Holtham, S, Hope, C, Hopley, P, Hossain, T, Hossaini, S, Howse, F, Hubbard, T, Humphreys, A, Ikram, H, Ioannis, M, Iqbal, M, Iqbal, N, Jain, R, Jatania, J, Jenkinson, P, Jokhan, S, Jones, A, Jones, C, Jones, L, Joshi, H, Joshi, K, Joy, M, Jull, P, Kakaniaris, G, Kallam, R, Kane, E, Kang, P, Kanitkar, R, Kauser, S, Kazmi, F, Kedrzycki, M, Kelly, S, Kendall, J, Khan, M, Khan, T, King, G, Kisiel, A, Kitsis, C, Kolawole, I, Korambayil, S, Kosasih, S, Kosti, A, Kotb, A, Kouris, S, Kshatriya, K, Kumar, S, Lafaurie, G, Lal, R, Lau, A, Lazim, T, Lazzaro, A, Lee, K, Lefroy, R, Leinhardt, D, Lennon, H, Leong, K, Levy, B, Lim, E, Lim, J, Lindley, S, Liu, D, Lloyd, P, Locker, D, Lockwood, S, Lowe, C, Lund, J, Lunevicius, R, Lunt, A, Lutfi, S, Luther, A, Luwemba, S, Mahankali‐Rao, P, Mahroof, S, Mai, D, Majid, S, Malik, A, Malik, K, Mann, K, Mansour, S, Manu, N, Mapara, R, Martin, C, Martin, J, Martin, R, Mason, C, Massey, L, Mathias, J, Mathur, P, Maude, K, McArthur, D, McCain, S, McCluney, S, McIlroy, B, McKay, S, McKinley, N, McNair, A, McWhirter, D, Mekhail, P, Mellor, K, Merchant, J, Merker, L, Messenger, D, Miles, A, Mir, S, Mishra, A, Mistry, P, Miu, V, Moat, M, Mockford, K, Mohamed, E, Mohamed, I, Mondragon‐Pritchard, M, Moore, N, Moretti, L, Morris, H, Morrison, T, Morrison‐Jones, V, Moss, J, Moug, S, Mountford, D, Moynihan, R, Muhammad, K, Muldoon‐Smith, D, Mulholland, J, Mullan, M, Murgitroyd, E, Murugaiyan, K, Myers, A, Mykoniatis, I, Nana, G, Nash, T, Nassar, A, Newton, R, Ng, C, Ng, P, Nguyen, K, Nicholas, F, Noor, M, Nowers, J, Nugent, C, Nunn, A, Nunn, R, Obeid, N, O'Callaghan, J, O'Hara, R, Oke, O, Olivier, J, O'Neill, A, O'Neill, S, Osei‐Bordom, D, Osgood, L, Panagiotopoulos, S, Panchasara, B, Parks, R, Patel, H, Patel, P, Patel, R, Patel, S, Pawelec, K, Payne, C, Pearson, K, Perin, G, Peristerakis, I, Petronio, B, Phelan, L, Phillips, J, Pisaneschi, C, Pitt, J, Plunkett‐Reed, K, Ponchietti, L, Pouzi, A, Pouzi, M, Powell, A, Powell‐Chandler, A, Pranesh, N, Proctor, V, Pywell, S, Qureshi, A, Qureshi, N, Rahman, M, Rai, Z, Ramcharan, S, Rangarajan, K, Rashid, M, Reader, H, Rehman, A, Rehman, S, Rengifo, C, Richards, E, Richardson, N, Robinson, A, Robinson, D, Rossi, B, Rutherford, F, Sadien, I, Saghir, T, Sahnan, K, Salahia, G, Sarveswaran, J, Saunders, M, Scott, B, Scott, K, Seager, A, Seal, S, Sezen, E, Shaban, F, Shah, P, Shahmohammadi, M, Shamsiddinova, A, Shankar, S, Sharpe, A, Shatkar, V, Sheel, A, Shields, T, Shinkwin, M, Shurmer, J, Siddika, A, Siddiqui, S, Simson, R, Sinclair, P, Singh, B, Singh, S, Sivaraj, J, Skaife, P, Skelly, B, Skinner, A, Slim, N, Smart, C, Smart, N, Smith, F, Smith, I, Smith, R, Spence, G, Sreedhar, A, Steinke, J, Stevenson, L, Stewart‐Parker, E, Stott, M, Stubbs, B, Stylianides, N, Subramonia, S, Swinkin, M, Swinscoe, M, Symons, N, Tahir, W, Taj, T, Takacs, K, Tam, J, Tan, K, Tani, S, Tanner, N, Tao, D, Taylor, M, Thava, B, Thippeswamy, K, Thomas, C, Thompson, E, Thompson, R, Thompson‐Reil, C, Thorn, C, Tongo, F, Toth, G, Turnbull, A, Turnbull, J, Valero, C, Boxel, G, Varcada, M, Venn, M, Ventham, N, Venza, M, Vimalachandran, D, Virlos, I, Wade, T, Wafi, A, Waite, K, Walker, M, Walker, N, Walker, T, Walsh, U, Wardle, S, Warner, R, Watfah, J, Watson, N, Watt, J, Watts, J, Wayman, J, Weegenaar, C, West, H, West, M, Whitehurst, L, Whyler, M, Wiggans, M, Wijeyekoon, S, Williams, G, Williams, R, Williamson, A, Williamson, J, Wilson, J, Winter, A, Wolpert, L, Wong, J, Yeap, E, Yeong, T, Zaman, S, Zappa, B, Zosimas, D, Moug S Mondragon‐Pritchard, M, Rehan, S, and van Boxel, G

Abstract

Background: \ud Small bowel obstruction is a common surgical emergency, and is associated with high levels of morbidity and mortality across the world. The literature provides little information on the conservatively managed group. The aim of this study was to describe the burden of small bowel obstruction in the UK.\ud \ud Methods: \ud This prospective cohort study was conducted in 131 acute hospitals in the UK between January and April 2017, delivered by trainee research collaboratives. Adult patients with a diagnosis of mechanical small bowel obstruction were included. The primary outcome was in‐hospital mortality. Secondary outcomes included complications, unplanned intensive care admission and readmission within 30 days of discharge. Practice measures, including use of radiological investigations, water soluble contrast, operative and nutritional interventions, were collected.\ud \ud Results: \ud Of 2341 patients identified, 693 (29·6 per cent) underwent immediate surgery (within 24 h of admission), 500 (21·4 per cent) had delayed surgery after initial conservative management, and 1148 (49·0 per cent) were managed non‐operatively. The mortality rate was 6·6 per cent (6·4 per cent for non‐operative management, 6·8 per cent for immediate surgery, 6·8 per cent for delayed surgery; P = 0·911). The major complication rate was 14·4 per cent overall, affecting 19·0 per cent in the immediate surgery, 23·6 per cent in the delayed surgery and 7·7 per cent in the non‐operative management groups (P < 0·001). Cox regression found hernia or malignant aetiology and malnutrition to be associated with higher rates of death. Malignant aetiology, operative intervention, acute kidney injury and malnutrition were associated with increased risk of major complication.\ud \ud Conclusion: \ud Small bowel obstruction represents a significant healthcare burden. Patient‐level factors such as timing of surgery, acute kidney injury and nutritional status are factors that might be modified to improve outcomes.

Published
2019

28. A novel biomechanical approach for animal behaviour recognition using accelerometers

Author

O’Hara, Robert B, O’Hara, R B ( Robert B ), Chakravarty, Pritish; https://orcid.org/0000-0002-2975-6253, Cozzi, Gabriele; https://orcid.org/0000-0002-1744-1940, Ozgul, Arpat; https://orcid.org/0000-0001-7477-2642, Aminian, Kamiar; https://orcid.org/0000-0002-6582-5375, O’Hara, Robert B, O’Hara, R B ( Robert B ), Chakravarty, Pritish; https://orcid.org/0000-0002-2975-6253, Cozzi, Gabriele; https://orcid.org/0000-0002-1744-1940, Ozgul, Arpat; https://orcid.org/0000-0001-7477-2642, and Aminian, Kamiar; https://orcid.org/0000-0002-6582-5375

Abstract

Data from animal‐borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have been the tool of choice for characterising animal behaviour. Although machine learning models perform reasonably well, they may not rely on meaningful features, nor lend themselves to physical interpretation of the classification rules. This lack of interpretability and control over classification outcomes is of particular concern where different behaviours have different frequency of occurrence and duration, as in most natural systems, and calls for the development of alternative methods. Biomechanical approaches to human activity classification could overcome these shortcomings, yet their full potential remains untapped for animal studies. We propose a general framework for behaviour recognition using accelerometers, and develop a hybrid model where (a) biomechanical features characterise movement dynamics, and (b) a node‐based hierarchical classification scheme employs simple machine learning algorithms at each node to find feature‐value thresholds separating different behaviours. Using triaxial accelerometer data collected on 10 wild Kalahari meerkats, and annotated video recordings of each individual as groundtruth, this hybrid model was validated in three scenarios: (a) when each behaviour was equally represented (EQDIST), (b) when naturally imbalanced datasets were considered (STRAT) and (c) when data from new individuals were considered (LOIO). A linear‐kernel Support Vector Machine at each node of our classification scheme yielded an overall accuracy of >95% for each scenario. Our hybrid approach had a 2.7% better average overall accuracy than top‐performing classical machine learning approaches. Further, we showed that not all models with high overall accuracy returned accurate behaviour‐specific performance

Published
2019

37. Cross-realm assessment of climate change impacts on species' abundance trends

Author

Bowler, D.E., Hof, C., Haase, P., Kröncke, I., Schweiger, Oliver, Adrian, R., Baert, L., Bauer, H.-G., Blick, T., Brooker, R.W., Dekoninck, W., Domisch, S., Eckmann, R., Hendrickx, F., Hickler, T., Klotz, Stefan, Kraberg, A., Kühn, Ingolf, Matesanz, S., Meschede, A., Neumann, H., O’Hara, R., Russell, D.J., Sell, A.F., Sonnewald, M., Stoll, S., Sundermann, A., Tackenberg, O., Türkay, M., Valladares, F., van Herk, K., van Klink, R., Vermeulen, R., Voigtländer, K., Wagner, R., Welk, E., Wiemers, Martin, Wiltshire, K.H., Böhning-Gaese, K., Bowler, D.E., Hof, C., Haase, P., Kröncke, I., Schweiger, Oliver, Adrian, R., Baert, L., Bauer, H.-G., Blick, T., Brooker, R.W., Dekoninck, W., Domisch, S., Eckmann, R., Hendrickx, F., Hickler, T., Klotz, Stefan, Kraberg, A., Kühn, Ingolf, Matesanz, S., Meschede, A., Neumann, H., O’Hara, R., Russell, D.J., Sell, A.F., Sonnewald, M., Stoll, S., Sundermann, A., Tackenberg, O., Türkay, M., Valladares, F., van Herk, K., van Klink, R., Vermeulen, R., Voigtländer, K., Wagner, R., Welk, E., Wiemers, Martin, Wiltshire, K.H., and Böhning-Gaese, K.

Abstract

Climate change, land-use change, pollution and exploitation are among the main drivers of species’ population trends; however, their relative importance is much debated. We used a unique collection of over 1,000 local population time series in 22 communities across terrestrial, freshwater and marine realms within central Europe to compare the impacts of long-term temperature change and other environmental drivers from 1980 onwards. To disentangle different drivers, we related species’ population trends to species- and driver-specific attributes, such as temperature and habitat preference or pollution tolerance. We found a consistent impact of temperature change on the local abundances of terrestrial species. Populations of warm-dwelling species increased more than those of cold-dwelling species. In contrast, impacts of temperature change on aquatic species’ abundances were variable. Effects of temperature preference were more consistent in terrestrial communities than effects of habitat preference, suggesting that the impacts of temperature change have become widespread for recent changes in abundance within many terrestrial communities of central Europe.

Published
2017

42. Population structure, mating system, and sex-determining allele diversity of the parasitoid wasp Habrobracon hebetor

Author

Antolin, M. F., Ode, P. J., Heimpel, G. E., O'Hara, R. B., and Strand, M. R.

Subjects
Genetic load -- Analysis, Wasps -- Genetic aspects, Sex determination, Genetic -- Research, Allelomorphism -- Genetic aspects, Reproduction -- Genetic aspects, Population genetics, Heredity -- Research, Heredity -- Genetic aspects, Biological sciences
Abstract

Research has been conducted on parasitoid wasp Habrobracon hebetor's complementary sex determination. The authors have investigated the role of population structure and mating system of these species in complementary sex determination via the use of genetic analyses, and they present the results.

Published
2003

43. A cross-taxon analysis of the impact of climate change on abundance trends in central Europe

Author

Bowler, D.E., Haase, P., Kröncke, I., Tackenberg, O., Bauer, H.G., Brendel, C., Brooker, R.W., Gerisch, Michael, Henle, Klaus, Hickler, T., Hof, C., Klotz, Stefan, Kühn, Ingolf, Matesanz, S., O'Hara, R., Russell, D., Schweiger, Oliver, Valladares, F., Welk, E., Wiemers, Martin, Böhning-Gaese, K., Bowler, D.E., Haase, P., Kröncke, I., Tackenberg, O., Bauer, H.G., Brendel, C., Brooker, R.W., Gerisch, Michael, Henle, Klaus, Hickler, T., Hof, C., Klotz, Stefan, Kühn, Ingolf, Matesanz, S., O'Hara, R., Russell, D., Schweiger, Oliver, Valladares, F., Welk, E., Wiemers, Martin, and Böhning-Gaese, K.

Abstract

Advances in phenology and pole- and up-ward shifts in geographic ranges are well-documented signs that species are responding to climate change. A deeper understanding of such responses across ecologically different species groups will help to assess future consequences for entire ecosystems. A less well-studied pattern linked with climate change is increases in abundances of warm-adapted species compared with cold-adapted species. To compare how recent climate change has affected the abundances of species across different taxonomic groups, we analyzed long-term local population trends and related them to the species temperature niche, as inferred from geographic distributions. We used population data sets collected in different regions of Central Europe, primarily Germany, for bats, birds, butterflies, ground beetles, springtails and dry grassland plants. We found that temperature niche was positively associated with long-term population trends in some of the taxonomic groups (birds, butterflies, ground beetles) but was less important in others (bats, springtails, and grassland plants). This variation in the importance of temperature niche suggested that some populations have been affected more than others by climate change, which may be explained by differences in species attributes, such as generation time and microhabitat preference. Our findings indicate that relating temperature niches of species to population trends is a useful method to quantify the impact of climate change on local population abundances. We show that this widely applicable approach is particularly suited for comparative cross-system analyses to identify which types of organisms, in which habitats, are responding the most to climate change.

Published
2015

45. Completion of the sequence analysis and comparisons of genome segment 2 (encoding outer capsid protein VP2) from representative isolates of the 24 bluetongue virus serotypes

Author

Maan S, Ns, Maan, Ar, Samuel, O'Hara R, Aj, Meyer, Rao S, and Peter Mertens

Abstract

Bluetongue (BT) is a non-contagious, arthropod-transmitted viral disease of domestic and wild ruminants. It is caused by bluetongue virus (BTV), a double-stranded (ds) RNA virus that is classified within the genus Orbivirus, family Reoviridae. There are at least twenty-four serotypes of BTV worldwide, five of which (1, 2, 4, 9 and 16) have been identified recently in Europe. BTV infects ruminants and its distribution throughout temperate and tropical regions of the world is dependent on the activity and abundance of certain vector-competent species of Culicoides midge. The outer capsid protein VP2 of BTV is a major protective antigen and the primary determinant of virus serotype. For the first time, the authors have completed the sequence analysis of full-length VP2 genes from the reference strains of each of the 24 BTV serotypes and their amino acid sequences were deduced. Multiple alignment of the VP2 gene (protein) sequences revealed that the level of nucleotide (amino acid) sequence variation between serotypes ranged from 29% (23%) to 59% (73%), confirming that segment 2/VP2 is the most variable BTV gene/protein. Phylogenetic analysis of VP2 grouped together the BTV types that are known to cross-react serologically. Low identity between types was demonstrated for specific regions within the VP2 amino acid sequences that have been shown to be antigenic and play a role in virus neutralisation. The sequence data represent the completion of an important step in the creation of a comprehensive BTV sequence database, which will support more rapid molecular methods for diagnosis and identification of BTV 'types', as well as continuing molecular epidemiology and surveillance studies of BTV.

Published
2010

46. Male adaptive stupidity: male mating pattern in hybridogenetique frogs

Author

Schmeller, Dirk S., O'Hara, R., Kokko, H., Lyvet, Nathalie, Laboratoire d'Ecologie des Hydrosystèmes Fluviaux (EHF), Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2005

47. Temporal variation, duty cycle, and absolute calling effort during sustained calling of Leptodactylus mystacinus (Anura: Leptodactylidae).

Author

JANSEN, MARTIN, MASUROWA, ANASTASIA, and O'HARA, R. BOB

Abstract

We studied the within-night temporal call variation of Leptodactylus mystacinus using automated bioacoustic survey and pattern recognition techniques. Based on ca 50,000 detected calls we report on large-scale variation of dominant frequency, call duration, peak power, call interval, call period, and call rate. The "absolute" calling effort (as absolute seconds per hour spent on calling calculated as the sum of all detected calls during one hour) was between 165 and 716 s/ hour (535 ± 191) with a peak at around 23:00 h, followed by a decrease until the end of the calling period. This might be due to vocal fatigue. In comparison with literature, the overall call production was higher than expected, but calling effort is comparable to estimates from the literature for other leptodactylid frogs. We hypothesize that species-specific mating tactics might be employed to achieve high calling effort during sustained calling. Further intra- and interspecific studies should aim at studying contest behaviour in mating frogs to test this hypothesis. [ABSTRACT FROM AUTHOR]

Published
2016

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