49 results on '"McQuillan, B"'
Search Results
2. The Diagnostic Yield and Clinical Utility of CMR in Myocardial Infarction With Non-Obstructed Coronary Arteries
- Author
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Giudicatti, L., primary, Telyuk, P., additional, Pasupathy, S., additional, Chieng, D., additional, McQuillan, B., additional, Austin, D., additional, Maredia, N., additional, Hillis, G., additional, Beltrame, J., additional, Dwivedi, G., additional, and Rajwani, A., additional
- Published
- 2023
- Full Text
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3. Pooled Safety and Efficacy of Inclisiran in Patients With Statin Intolerance (ORION-10 and ORION-11)
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McQuillan, B., primary, Wright, R., additional, Kallend, D., additional, Raal, F., additional, Stoekenbroek, R., additional, Koenig, W., additional, Leiter, L., additional, Landmesser, U., additional, Schwartz, G., additional, Wijngaard, P., additional, Kastelein, J., additional, and Ray, K., additional
- Published
- 2023
- Full Text
- View/download PDF
4. Variability of Antiplatelet and Statin Prescription In Australia for Myocardial Infarction With Non-Obstructed Coronary Arteries
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Giudicatti, L., primary, Pasupathy, S., additional, Chieng, D., additional, McQuillan, B., additional, Hillis, G., additional, Beltrame, J., additional, Dwivedi, G., additional, and Rajwani, A., additional
- Published
- 2023
- Full Text
- View/download PDF
5. P109 Predicting major adverse cardiovascular events using symptom subtypes of severe obstructive sleep apnoea
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Shenoy, B, primary, McArdle, N, additional, Walsh, J, additional, Cadby, G, additional, Hillman, D, additional, McQuillan, B, additional, Hung, J, additional, Dhaliwal, S, additional, Mukherjee, S, additional, Palmer, L, additional, and Singh, B, additional
- Published
- 2022
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6. Clinical Predictors of Impactful Cardiac Magnetic Resonance Imaging in Myocardial Infarction with Non-Obstructed Coronary Arteries
- Author
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Giudicatti, L., Telyuk, P., Gilbert, G., Pasupathy, S., Beltrame, J., Maredia, N., Ihdayhid, A., McQuillan, B., Spiro, J., Schultz, C., Chieng, D., Hillis, G., Austin, D., Dwivedi, G., and Rajwani, A.
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- 2024
- Full Text
- View/download PDF
7. Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation
- Author
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Lu, J., Hutchens, R., Hung, J., Bennamoun, M., McQuillan, B., Briffa, T., Sohel, F., Murray, K., Stewart, J., Chow, B., Sanfilippo, F., Dwivedi, G., Lu, J., Hutchens, R., Hung, J., Bennamoun, M., McQuillan, B., Briffa, T., Sohel, F., Murray, K., Stewart, J., Chow, B., Sanfilippo, F., and Dwivedi, G.
- Abstract
Background Appropriate anticoagulant therapy for patients with atrial fibrillation (AF) requires assessment of stroke and bleeding risks. However, risk stratification schemas such as CHA2DS2-VASc and HAS-BLED have modest predictive capacity for patients with AF. Multilabel machine learning (ML) techniques may improve predictive performance and support decision-making for anticoagulant therapy. We compared the performance of multilabel ML models with the currently used risk scores for predicting outcomes in AF patients. Methods This was a retrospective cohort study of 9670 patients, mean age 76.9 years, 46% women, who were hospitalized with non-valvular AF, and had 1-year follow-up. The outcomes were ischemic stroke (167), major bleeding (430) admissions, all-cause death (1912) and event-free survival (7387). Discrimination and calibration of ML models were compared with clinical risk scores by area under the curve (AUC). Risk stratification was assessed using net reclassification index (NRI). Results Multilabel gradient boosting classifier chain provided the best AUCs for stroke (0.685 95% CI 0.676, 0.694), major bleeding (0.709 95% CI 0.703, 0.716) and death (0.765 95% CI 0.763, 0.768) compared to multi-layer neural networks and classifier chain using support vector machine. It provided modest performance improvement for stroke compared to AUC of CHA2DS2-VASc (0.652, NRI = 3.2%, p-value = 0.1), but significantly improved major bleeding prediction compared to AUC of HAS-BLED (0.522, NRI = 22.8%, p-value < 0.05). It also achieved greater discriminant power for death compared with AUC of CHA2DS2-VASc (0.606, p-value < 0.05). ML models identified additional risk features such as hemoglobin level, renal function. Conclusions Multilabel ML models can outperform clinical risk stratification scores for predicting the risk of major bleeding and death in non-valvular AF patients.
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- 2022
8. Lawson Criterion for Ignition Exceeded in an Inertial Fusion Experiment
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Abu-Shawareb, H, Acree, R, Adams, P, Adams, J, Addis, B, Aden, R, Adrian, P, Afeyan, BB, Aggleton, M, Aghaian, L, Aguirre, A, Aikens, D, Akre, J, Albert, F, Albrecht, M, Albright, BJ, Albritton, J, Alcala, J, Alday, C, Alessi, DA, Alexander, N, Alfonso, J, Alfonso, N, Alger, E, Ali, SJ, Ali, ZA, Alley, WE, Amala, P, Amendt, PA, Amick, P, Ammula, S, Amorin, C, Ampleford, DJ, Anderson, RW, Anklam, T, Antipa, N, Appelbe, B, Aracne-Ruddle, C, Araya, E, Arend, M, Arnold, P, Arnold, T, Asay, J, Atherton, LJ, Atkinson, D, Atkinson, R, Auerbach, JM, Austin, B, Auyang, L, Awwal, AS, Ayers, J, Ayers, S, Ayers, T, Azevedo, S, Bachmann, B, Back, CA, Bae, J, Bailey, DS, Bailey, J, Baisden, T, Baker, KL, Baldis, H, Barber, D, Barberis, M, Barker, D, Barnes, A, Barnes, CW, Barrios, MA, Barty, C, Bass, I, Batha, SH, Baxamusa, SH, Bazan, G, Beagle, JK, Beale, R, Beck, BR, Beck, JB, Bedzyk, M, Beeler, RG, Behrendt, W, Belk, L, Bell, P, Belyaev, M, Benage, JF, Bennett, G, Benedetti, LR, Benedict, LX, Berger, R, Bernat, T, Bernstein, LA, Berry, B, Bertolini, L, Besenbruch, G, Betcher, J, Bettenhausen, R, Betti, R, Bezzerides, B, Bhandarkar, SD, Bickel, R, Biener, J, Biesiada, T, Bigelow, K, Bigelow-Granillo, J, Bigman, V, Bionta, RM, Birge, NW, Bitter, M, Black, AC, Bleile, R, Bleuel, DL, Bliss, E, Blue, B, Boehly, T, Boehm, K, Boley, CD, Bonanno, R, Bond, EJ, Bond, T, Bonino, MJ, Borden, M, Bourgade, J-L, Bousquet, J, Bowers, J, Bowers, M, Boyd, R, Bozek, A, Bradley, DK, Bradley, KS, Bradley, PA, Bradley, L, Brannon, L, Brantley, PS, Braun, D, Braun, T, Brienza-Larsen, K, Briggs, TM, Britten, J, Brooks, ED, Browning, D, Bruhn, MW, Brunner, TA, Bruns, H, Brunton, G, Bryant, B, Buczek, T, Bude, J, Buitano, L, Burkhart, S, Burmark, J, Burnham, A, Burr, R, Busby, LE, Butlin, B, Cabeltis, R, Cable, M, Cabot, WH, Cagadas, B, Caggiano, J, Cahayag, R, Caldwell, SE, Calkins, S, Callahan, DA, Calleja-Aguirre, J, Camara, L, Camp, D, Campbell, EM, Campbell, JH, Carey, B, Carey, R, Carlisle, K, 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Davidovits, S, Davis, P, Davis, J, Dawson, S, Day, RD, Day, TH, Dayton, M, Deck, C, Decker, C, Deeney, C, DeFriend, KA, Deis, G, Delamater, ND, Delettrez, JA, Demaret, R, Demos, S, Dempsey, SM, Desjardin, R, Desjardins, T, Desjarlais, MP, Dewald, EL, DeYoreo, J, Diaz, S, Dimonte, G, Dittrich, TR, Divol, L, Dixit, SN, Dixon, J, Dodd, ES, Dolan, D, Donovan, A, Donovan, M, Döppner, T, Dorrer, C, Dorsano, N, Douglas, MR, Dow, D, Downie, J, Downing, E, Dozieres, M, Draggoo, V, Drake, D, Drake, RP, Drake, T, Dreifuerst, G, DuBois, DF, DuBois, PF, Dunham, G, Dylla-Spears, R, Dymoke-Bradshaw, AKL, Dzenitis, B, Ebbers, C, Eckart, M, Eddinger, S, Eder, D, Edgell, D, Edwards, MJ, Efthimion, P, Eggert, JH, Ehrlich, B, Ehrmann, P, Elhadj, S, Ellerbee, C, Elliott, NS, Ellison, CL, Elsner, F, Emerich, M, Engelhorn, K, England, T, English, E, Epperson, P, Epstein, R, Erbert, G, Erickson, MA, Erskine, DJ, Erlandson, A, Espinosa, RJ, Estes, C, Estabrook, KG, Evans, S, Fabyan, A, Fair, J, Fallejo, R, Farmer, N, Farmer, WA, Farrell, M, Fatherley, VE, Fedorov, M, Feigenbaum, E, Feit, M, Ferguson, W, Fernandez, JC, Fernandez-Panella, A, Fess, S, Field, JE, Filip, CV, Fincke, JR, Finn, T, Finnegan, SM, Finucane, RG, Fischer, M, Fisher, A, Fisher, J, Fishler, B, Fittinghoff, D, Fitzsimmons, P, Flegel, M, Flippo, KA, Florio, J, Folta, J, Folta, P, Foreman, LR, Forrest, C, Forsman, A, Fooks, J, Foord, M, Fortner, R, Fournier, K, Fratanduono, DE, Frazier, N, Frazier, T, Frederick, C, Freeman, MS, Frenje, J, Frey, D, Frieders, G, Friedrich, S, Froula, DH, Fry, J, Fuller, T, Gaffney, J, Gales, S, Le Galloudec, B, Le Galloudec, KK, Gambhir, A, Gao, L, Garbett, WJ, Garcia, A, Gates, C, Gaut, E, Gauthier, P, Gavin, Z, Gaylord, J, Geissel, M, Génin, F, Georgeson, J, Geppert-Kleinrath, H, Geppert-Kleinrath, V, Gharibyan, N, Gibson, J, Gibson, C, Giraldez, E, Glebov, V, Glendinning, SG, Glenn, S, Glenzer, SH, Goade, S, Gobby, PL, Goldman, SR, Golick, B, Gomez, M, Goncharov, V, Goodin, D, Grabowski, P, Grafil, E, Graham, P, Grandy, J, Grasz, E, Graziani, F, Greenman, G, Greenough, JA, Greenwood, A, Gregori, G, Green, T, Griego, JR, Grim, GP, Grondalski, J, Gross, S, Guckian, J, Guler, N, Gunney, B, Guss, G, Haan, S, Hackbarth, J, Hackel, L, Hackel, R, Haefner, C, Hagmann, C, Hahn, KD, Hahn, S, Haid, BJ, Haines, BM, Hall, BM, Hall, C, Hall, GN, Hamamoto, M, Hamel, S, Hamilton, CE, Hammel, BA, Hammer, JH, Hampton, G, Hamza, A, Handler, A, Hansen, S, Hanson, D, Haque, R, Harding, D, Harding, E, Hares, JD, Harris, DB, Harte, JA, Hartouni, EP, Hatarik, R, Hatchett, S, Hauer, AA, Havre, M, Hawley, R, Hayes, J, Hayes, S, Hayes-Sterbenz, A, Haynam, CA, Haynes, DA, Headley, D, Heal, A, Heebner, JE, Heerey, S, Heestand, GM, Heeter, R, Hein, N, Heinbockel, C, Hendricks, C, Henesian, M, Heninger, J, Henrikson, J, Henry, EA, Herbold, EB, Hermann, MR, Hermes, G, Hernandez, JE, Hernandez, VJ, Herrmann, MC, Herrmann, HW, Herrera, OD, Hewett, D, Hibbard, R, Hicks, DG, Hill, D, Hill, K, Hilsabeck, T, Hinkel, DE, Ho, DD, Ho, VK, Hoffer, JK, Hoffman, NM, Hohenberger, M, Hohensee, M, Hoke, W, Holdener, D, Holdener, F, Holder, JP, Holko, B, Holunga, D, Holzrichter, JF, Honig, J, Hoover, D, Hopkins, D, Berzak Hopkins, L, Hoppe, M, Hoppe, ML, Horner, J, Hornung, R, Horsfield, CJ, Horvath, J, Hotaling, D, House, R, Howell, L, Hsing, WW, Hu, SX, Huang, H, Huckins, J, Hui, H, Humbird, KD, Hund, J, Hunt, J, Hurricane, OA, Hutton, M, Huynh, KH-K, Inandan, L, Iglesias, C, Igumenshchev, IV, Izumi, N, Jackson, M, Jackson, J, Jacobs, SD, James, G, Jancaitis, K, Jarboe, J, Jarrott, LC, Jasion, D, Jaquez, J, Jeet, J, Jenei, AE, Jensen, J, Jimenez, J, Jimenez, R, Jobe, D, Johal, Z, Johns, HM, Johnson, D, Johnson, MA, Gatu Johnson, M, Johnson, RJ, Johnson, S, Johnson, SA, Johnson, T, Jones, K, Jones, O, Jones, M, Jorge, R, Jorgenson, HJ, Julian, M, Jun, BI, Jungquist, R, Kaae, J, Kabadi, N, Kaczala, D, Kalantar, D, Kangas, K, Karasiev, VV, Karasik, M, Karpenko, V, Kasarky, A, Kasper, K, Kauffman, R, Kaufman, MI, Keane, C, Keaty, L, Kegelmeyer, L, Keiter, PA, Kellett, PA, Kellogg, J, Kelly, JH, Kemic, S, Kemp, AJ, Kemp, GE, Kerbel, GD, Kershaw, D, Kerr, SM, Kessler, TJ, Key, MH, Khan, SF, Khater, H, Kiikka, C, Kilkenny, J, Kim, Y, Kim, Y-J, Kimko, J, Kimmel, M, Kindel, JM, King, J, Kirkwood, RK, Klaus, L, Klem, D, Kline, JL, Klingmann, J, Kluth, G, Knapp, P, Knauer, J, Knipping, J, Knudson, M, Kobs, D, Koch, J, Kohut, T, Kong, C, Koning, JM, Koning, P, Konior, S, Kornblum, H, Kot, LB, Kozioziemski, B, Kozlowski, M, Kozlowski, PM, Krammen, J, Krasheninnikova, NS, Kraus, B, Krauser, W, Kress, JD, Kritcher, AL, Krieger, E, Kroll, JJ, Kruer, WL, Kruse, MKG, Kucheyev, S, Kumbera, M, Kumpan, S, Kunimune, J, Kustowski, B, Kwan, TJT, Kyrala, GA, Laffite, S, Lafon, M, LaFortune, K, Lahmann, B, Lairson, B, Landen, OL, Langenbrunner, J, Lagin, L, Land, T, Lane, M, Laney, D, Langdon, AB, Langer, SH, Langro, A, Lanier, NE, Lanier, TE, Larson, D, Lasinski, BF, Lassle, D, LaTray, D, 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TJ, Munteanu, FM, Nafziger, J, Nagayama, T, Nagel, SR, Nast, R, Negres, RA, Nelson, A, Nelson, D, Nelson, J, Nelson, S, Nemethy, S, Neumayer, P, Newman, K, Newton, M, Nguyen, H, Di Nicola, J-MG, Di Nicola, P, Niemann, C, Nikroo, A, Nilson, PM, Nobile, A, Noorai, V, Nora, R, Norton, M, Nostrand, M, Note, V, Novell, S, Nowak, PF, Nunez, A, Nyholm, RA, O'Brien, M, Oceguera, A, Oertel, JA, Okui, J, Olejniczak, B, Oliveira, J, Olsen, P, Olson, B, Olson, K, Olson, RE, Opachich, YP, Orsi, N, Orth, CD, Owen, M, Padalino, S, Padilla, E, Paguio, R, Paguio, S, Paisner, J, Pajoom, S, Pak, A, Palaniyappan, S, Palma, K, Pannell, T, Papp, F, Paras, D, Parham, T, Park, H-S, Pasternak, A, Patankar, S, Patel, MV, Patel, PK, Patterson, R, Patterson, S, Paul, B, Paul, M, Pauli, E, Pearce, OT, Pearcy, J, Pedrotti, B, Peer, A, Pelz, LJ, Penetrante, B, Penner, J, Perez, A, Perkins, LJ, Pernice, E, Perry, TS, Person, S, Petersen, D, Petersen, T, Peterson, DL, Peterson, EB, Peterson, JE, Peterson, JL, 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BT, Sinars, D, Singh, P, Sio, H, Skulina, K, Skupsky, S, Slutz, S, Sluyter, M, Smalyuk, VA, Smauley, D, Smeltser, RM, Smith, C, Smith, I, Smith, J, Smith, L, Smith, R, Sohn, R, Sommer, S, Sorce, C, Sorem, M, Soures, JM, Spaeth, ML, Spears, BK, Speas, S, Speck, D, Speck, R, Spears, J, Spinka, T, Springer, PT, Stadermann, M, Stahl, B, Stahoviak, J, Stanton, LG, Steele, R, Steele, W, Steinman, D, Stemke, R, Stephens, R, Sterbenz, S, Sterne, P, Stevens, D, Stevers, J, Still, CB, Stoeckl, C, Stoeffl, W, Stolken, JS, Stolz, C, Storm, E, Stone, G, Stoupin, S, Stout, E, Stowers, I, Strauser, R, Streckart, H, Streit, J, Strozzi, DJ, Suratwala, T, Sutcliffe, G, Suter, LJ, Sutton, SB, Svidzinski, V, Swadling, G, Sweet, W, Szoke, A, Tabak, M, Takagi, M, Tambazidis, A, Tang, V, Taranowski, M, Taylor, LA, Telford, S, Theobald, W, Thi, M, Thomas, A, Thomas, CA, Thomas, I, Thomas, R, Thompson, IJ, Thongstisubskul, A, Thorsness, CB, Tietbohl, G, Tipton, RE, Tobin, M, Tomlin, N, Tommasini, R, Toreja, AJ, Torres, J, Town, RPJ, Townsend, S, Trenholme, J, Trivelpiece, A, Trosseille, C, Truax, H, Trummer, D, Trummer, S, Truong, T, Tubbs, D, Tubman, ER, Tunnell, T, Turnbull, D, Turner, RE, Ulitsky, M, Upadhye, R, Vaher, JL, VanArsdall, P, VanBlarcom, D, Vandenboomgaerde, M, VanQuinlan, R, Van Wonterghem, BM, Varnum, WS, Velikovich, AL, Vella, A, Verdon, CP, Vermillion, B, Vernon, S, Vesey, R, Vickers, J, Vignes, RM, Visosky, M, Vocke, J, Volegov, PL, Vonhof, S, Von Rotz, R, Vu, HX, Vu, M, Wall, D, Wall, J, Wallace, R, Wallin, B, Walmer, D, Walsh, CA, Walters, CF, Waltz, C, Wan, A, Wang, A, Wang, Y, Wark, JS, Warner, BE, Watson, J, Watt, RG, Watts, P, Weaver, J, Weaver, RP, Weaver, S, Weber, CR, Weber, P, Weber, SV, Wegner, P, Welday, B, Welser-Sherrill, L, Weiss, K, Widmann, K, Wheeler, GF, Whistler, W, White, RK, Whitley, HD, Whitman, P, Wickett, ME, Widmayer, C, Wiedwald, J, Wilcox, R, Wilcox, S, Wild, C, Wilde, BH, Wilde, CH, Wilhelmsen, K, Wilke, MD, Wilkens, H, Wilkins, P, Wilks, SC, Williams, EA, Williams, GJ, Williams, W, Williams, WH, Wilson, DC, Wilson, B, Wilson, E, Wilson, R, Winters, S, Wisoff, J, Wittman, M, Wolfe, J, Wong, A, Wong, KW, Wong, L, Wong, N, Wood, R, Woodhouse, D, Woodruff, J, Woods, DT, Woods, S, Woodworth, BN, Wooten, E, Wootton, A, Work, K, Workman, JB, Wright, J, Wu, M, Wuest, C, Wysocki, FJ, Xu, H, Yamaguchi, M, Yang, B, Yang, ST, Yatabe, J, Yeamans, CB, Yee, BC, Yi, SA, Yin, L, Young, B, Young, CS, Young, CV, Young, P, Youngblood, K, Zacharias, R, Zagaris, G, Zaitseva, N, Zaka, F, Ze, F, Zeiger, B, Zika, M, Zimmerman, GB, Zobrist, T, Zuegel, JD, Zylstra, AB, Indirect Drive ICF Collaboration, Collaboration, Indirect Drive ICF, AWE Plc, Lawrence Livermore National Laboratory, and U.S Department of Energy
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General Physics ,02 Physical Sciences ,General Physics and Astronomy ,Indirect Drive ICF Collaboration ,01 Mathematical Sciences ,09 Engineering - Abstract
For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion.
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- 2022
9. O022 Long-term cardiovascular risk in obstructive sleep apnoea: a sleep clinic cohort study
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Shenoy, B, primary, Singh, B, additional, Cadby, G, additional, McQuillan, B, additional, Hung, J, additional, Rea, S, additional, Walsh, J, additional, Eastwood, P, additional, Hillman, D, additional, Mukherjee, S, additional, Palmer, L, additional, and McArdle, N, additional
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- 2021
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10. Association of hypertension with mortality in patients hospitalised with COVID-19
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Bhatia, KS, Sritharan, HP, Ciofani, J, Chia, J, Allahwala, UK, Chui, K, Nour, D, Vasanthakumar, S, Khandadai, D, Jayadeva, P, Bhagwandeen, R, Brieger, D, Choong, C, Delaney, A, Dwivedi, G, Harris, B, Hillis, G, Hudson, B, Javorski, G, Jepson, N, Kanagaratnam, L, Kotsiou, G, Lee, A, Lo, ST, MacIsaac, AI, McQuillan, B, Ranasinghe, I, Walton, A, Weaver, J, Wilson, W, Yong, ASC, Zhu, J, Van Gaal, W, Kritharides, L, Chow, CK, Bhindi, R, Bhatia, KS, Sritharan, HP, Ciofani, J, Chia, J, Allahwala, UK, Chui, K, Nour, D, Vasanthakumar, S, Khandadai, D, Jayadeva, P, Bhagwandeen, R, Brieger, D, Choong, C, Delaney, A, Dwivedi, G, Harris, B, Hillis, G, Hudson, B, Javorski, G, Jepson, N, Kanagaratnam, L, Kotsiou, G, Lee, A, Lo, ST, MacIsaac, AI, McQuillan, B, Ranasinghe, I, Walton, A, Weaver, J, Wilson, W, Yong, ASC, Zhu, J, Van Gaal, W, Kritharides, L, Chow, CK, and Bhindi, R
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OBJECTIVE: To assess whether hypertension is an independent risk factor for mortality among patients hospitalised with COVID-19, and to evaluate the impact of ACE inhibitor and angiotensin receptor blocker (ARB) use on mortality in patients with a background of hypertension. METHOD: This observational cohort study included all index hospitalisations with laboratory-proven COVID-19 aged ≥18 years across 21 Australian hospitals. Patients with suspected, but not laboratory-proven COVID-19, were excluded. Registry data were analysed for in-hospital mortality in patients with comorbidities including hypertension, and baseline treatment with ACE inhibitors or ARBs. RESULTS: 546 consecutive patients (62.9±19.8 years old, 51.8% male) hospitalised with COVID-19 were enrolled. In the multivariable model, significant predictors of mortality were age (adjusted OR (aOR) 1.09, 95% CI 1.07 to 1.12, p<0.001), heart failure or cardiomyopathy (aOR 2.71, 95% CI 1.13 to 6.53, p=0.026), chronic kidney disease (aOR 2.33, 95% CI 1.02 to 5.32, p=0.044) and chronic obstructive pulmonary disease (aOR 2.27, 95% CI 1.06 to 4.85, p=0.035). Hypertension was the most prevalent comorbidity (49.5%) but was not independently associated with increased mortality (aOR 0.92, 95% CI 0.48 to 1.77, p=0.81). Among patients with hypertension, ACE inhibitor (aOR 1.37, 95% CI 0.61 to 3.08, p=0.61) and ARB (aOR 0.64, 95% CI 0.27 to 1.49, p=0.30) use was not associated with mortality. CONCLUSIONS: In patients hospitalised with COVID-19, pre-existing hypertension was the most prevalent comorbidity but was not independently associated with mortality. Similarly, the baseline use of ACE inhibitors or ARBs had no independent association with in-hospital mortality.
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- 2021
11. Sodium-glucose Co-transporter 2 Inhibitor use and Barriers to Prescription in a Tertiary Cardiology Department
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Ng, D., primary and McQuillan, B., additional
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- 2021
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12. Factors Influencing Delay in Door to Balloon Time in Inter-Hospital Transfer STEMI Patients
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Shoaib, M., primary, Wollard, E., additional, Huish, W., additional, Aguila, J., additional, and McQuillan, B., additional
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- 2021
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13. Impact of Pre-Hospital Activation of ST-segment Elevation Myocardial Infarction on Rate of False Positive Activation and Door to Balloon Time
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Shoaib, M., primary, Woollard, E., additional, Huish, W., additional, Aguila, J., additional, and McQuillan, B., additional
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- 2021
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14. 230 Machine learning models for predicting ischemic stroke and major bleeding risk in patients with atrial fibrillation
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Lu, J., Dwivedi, G., Sanfilippo, F., Bennamoun, M., Hung, J., Briffa, T., Sohel, F., Hutchens, R., Stewart, J., Chow, B., McQuillan, B., Lu, J., Dwivedi, G., Sanfilippo, F., Bennamoun, M., Hung, J., Briffa, T., Sohel, F., Hutchens, R., Stewart, J., Chow, B., and McQuillan, B.
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Background Risk scores such as CHA2DS2-VASc and HAS-BLED are used to assess stroke and bleeding risk respectively and choose appropriate antithrombotic therapy in patients with atrial fibrillation (AF). The application of ML models may improve risk prediction and identification of potential risk factors. Objective To investigate the usefulness of ML methods in estimating one-year risk of ischemic stroke and major bleeding in patients after hospitalisation with AF. Methods We identified adults with a history of non-valvular AF or atrial flutter who were admitted to a tertiary or secondary hospital in Perth, Western Australia from 2009 to 2016 using linked clinical and administrative data. Based on all the available risk factors in the data including individual risk factors in the scores, we built ML models and compared their predictive performance [Area under the receiver operating characteristic curve (AUC)] with the standard risk scores. Results There were 9,634 patients in the study cohort with a mean age of 77 years and 46% were female. 2407 patients died (n=1636) or were readmitted for ischemic stroke (n=157) and major bleeding (n=614) within one year after the first admission. All-cause death was treated as a competing risk. Gradient Boosting Machine identified nonconventional risk factors and achieved the best prediction (ischemic stroke: AUC 0.67 vs 0.64 for CHA2DS2-VASc; major bleeding: AUC 0.66 vs 0.53 for HAS-BLED). Conclusion ML models can identify nonconventional risk factors and also outperform commonly used risk scores for predicting ischemic stroke and major bleeding in patients with AF.
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- 2020
15. 230 Machine Learning Models for Predicting Ischemic Stroke and Major Bleeding Risk in Patients with Atrial Fibrillation
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Lu, J., primary, Dwivedi, G., additional, Sanfilippo, F., additional, Bennamoun, M., additional, Hung, J., additional, Briffa, T., additional, Sohel, F., additional, Hutchens, R., additional, Stewart, J., additional, Chow, B., additional, and McQuillan, B., additional
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- 2020
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16. Factors Associated with Escalating Hospitalisations for Non–Valvular Atrial Fibrillation in Western Australia Between 2000 and 2013
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Weber, C., primary, Hung, J., additional, Hickling, S., additional, McQuillan, B., additional, Li, I., additional, and Briffa, T., additional
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- 2018
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17. Ischaemic Stroke and the Echo ‘Bubble Study’: Are we Screening the Right Patients? A Multicentre Experience from Western Australia
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Maggiore, P., primary, Bellinge, J., additional, Chieng, D., additional, White, D., additional, Lan, N., additional, Jaltotage, B., additional, Ali, U., additional, Gordon, M., additional, Chung, K., additional, Stobie, P., additional, Ng, J., additional, Hankey, G., additional, and McQuillan, B., additional
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- 2018
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18. A Positive Score for Depressive Symptoms Using the Patient Health Questionnaire-9: To What Extent is This Information Used to Inform Care in the Community?
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Crittenden, J., primary, Collins, S., additional, and McQuillan, B., additional
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- 2018
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19. Appropriate Selection of Oral Anticoagulant (OAC) Therapy for Stroke Prevention Among Older Subjects with Atrial Fibrillation (AF) Has Improved Over Time but an Evidence Treatment Gap Persists
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Hutchens, R., primary, McQuillan, B., additional, Briffa, T., additional, and Hung, J., additional
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- 2017
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20. Familial Hypercholesterolaemia and Lipoprotein(a) Phenotypes in a Community-Based Cohort: Associations with Carotid Intima-Media Thickness, Focal Plaque and Cardiovascular Outcomes
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Ellis, K., primary, Ooi, E., additional, Barrett, H., additional, Chan, D., additional, Hung, J., additional, Thompson, P., additional, Beilby, J., additional, Watts, G., additional, and McQuillan, B., additional
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- 2017
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21. Translating the Evidence in Atrial Fibrillation Management. Can We Improve Appropriate Use of Anticoagulation Through the Use of an Electronic Clinical Decision Support Tool?
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Hutchens, R., primary, McQuillan, B., additional, Briffa, T., additional, and Hung, J., additional
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- 2017
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22. Underutilisation of Oral Anticoagulation (OAC) Therapy for Stroke Prevention in Non-Valvular Atrial Fibrillation (AF) Management Among Women
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Hutchens, R., primary, McQuillan, B., additional, Briffa, T., additional, and Hung, J., additional
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- 2017
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23. Contemporary Management of Acute Coronary Syndrome in a Large Urban Tertiary Referral Centre
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Naing, P., primary, Chung, K., additional, Htwe, S., additional, Pattani, S., additional, De Varona, G., additional, Stobie, P., additional, Bhullar, D., additional, Yeow, W., additional, and McQuillan, B., additional
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- 2017
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24. Management of Suspected Acute Coronary Syndromes in a Regional Australian Hospital: An Audit of Adherence with Guidelines.
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Quartermaine, T., primary and McQuillan, B., additional
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- 2017
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25. Echocardiographic Pulmonary Left Atrial Ratio (ePLAR): Is it a Clinically Useful, Noninvasive Measure to Help Identify Patients with Left-Heart Causes of Pulmonary Hypertension?
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Ng, P., primary and McQuillan, B., additional
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- 2016
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26. How to : white background photography : shooting against white
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McQuillan, Bryce
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- 2021
27. Differences in cardiovascular risk factors and carotid IMT in Australian Indians and Caucasians with type-2 diabetes mellitus; an ethnic predisposition to atherosclerosis?
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Harmer, J., Chow, C., McQuillan, B., and Celermajer, D.
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CARDIOVASCULAR diseases risk factors , *INFORMATION manipulation theory , *CAUCASIAN race , *TYPE 2 diabetes , *DISEASE susceptibility , *ATHEROSCLEROSIS ,CAROTID artery abnormalities - Published
- 2015
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28. Assessment of management for heart failure with preserved ejection fraction.
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Lee, F., Bachmann, D., and McQuillan, B.
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HEART failure treatment , *DISEASE management , *GRAFT rejection , *HEART transplantation , *MEDICAL research - Published
- 2015
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29. Trends in incidence and prevalence of hospitalisation for atrial fibrillation and associated mortality in Western Australia, 1995–2010.
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Briffa, T., Hung, J., Knuiman, M., McQuillan, B., Chew, D., Eikelboom, J., Hankey, G., Nedkoff, L., Weerasooriya, R., Liu, A., and Stobie, P.
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HOSPITAL admission & discharge , *ATRIAL fibrillation , *AUSTRALIANS , *CARDIOLOGY , *MEDICAL research , *DISEASES - Published
- 2015
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30. Online sexual abuse and exploitation of children in the Philippines: An exploratory study of outcomes after reintegration into the community.
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Scroger M, Draper RS, and McQuillan B
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- Humans, Philippines, Female, Male, Adolescent, Child, Survivors psychology, Internet, Psychosocial Functioning, Child Abuse, Sexual psychology
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Background: This study examined psychosocial outcomes for Filipino survivors of online sexual abuse and exploitation of children (OSAEC)., Objective: This study aimed to identify relationships between demographic variables, self-reported and caregiver-reported trauma symptoms, and psychosocial functioning among Filipino youth who have experienced OSAEC., Participants and Setting: This study utilized inclusion criteria of survivors of OSAEC between ages 12 and 18 who received residential care and were reintegrated into the community for at least one year (N = 48). Participants were in care at shelters associated with Project PAVE in the Philippines., Methods: As measured by three assessment tools, relationships between demographic variables and psychosocial functioning were explored for risk and protective factors of trauma symptoms and psychosocial functioning to better understand this population's needs post-integration., Results: Results suggest survivors continue to experience psychosocial symptoms after reintegration. Caregivers reported survivors reintegrated outside the home had significantly higher externalizing symptoms (MR = 6.67; H(3) = 14.85, p = .002, η
2 = 0.27) compared to survivors reintegrated within the home and survivors who trafficked themselves to have higher internalizing symptoms (MR = 16.79; H(3) = 11.80; p = .008, η2 = 0.20) than survivors trafficked by a relative. Caregivers reported survivors who resided in the shelter for one month or less to have higher internalizing symptoms (MR = 20.12; H(2) = 11.06; p = .004; η2 = 0.20) than survivors who resided in the shelter for six months or longer., Conclusion: This study highlights the importance of further research to better understand the needs of this vulnerable population in order to guide the most effective intervention, aftercare, and reintegration programs to support survivors and their caregivers., (Copyright © 2024 Elsevier Ltd. All rights reserved.)- Published
- 2024
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31. Predicting multifaceted risks using machine learning in atrial fibrillation: insights from GLORIA-AF study.
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Lu J, Bisson A, Bennamoun M, Zheng Y, Sanfilippo FM, Hung J, Briffa T, McQuillan B, Stewart J, Figtree G, Huisman MV, Dwivedi G, and Lip GYH
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Aims: Patients with atrial fibrillation (AF) have a higher risk of ischaemic stroke and death. While anticoagulants are effective at reducing these risks, they increase the risk of bleeding. Current clinical risk scores only perform modestly in predicting adverse outcomes, especially for the outcome of death. We aimed to test the multi-label gradient boosting decision tree (ML-GBDT) model in predicting risks for adverse outcomes in a prospective global AF registry., Methods and Results: We studied patients from phase II/III of the Global Registry on Long-Term Oral Anti-Thrombotic Treatment in Patients with Atrial Fibrillation registry between 2011 and 2020. The outcomes were all-cause death, ischaemic stroke, and major bleeding within 1 year following the AF. We trained the ML-GBDT model and compared its discrimination with the clinical scores in predicting patient outcomes. A total of 25 656 patients were included [mean age 70.3 years (SD 10.3); 44.8% female]. Within 1 year after AF, ischaemic stroke occurred in 215 (0.8%), major bleeding in 405 (1.6%), and death in 897 (3.5%) patients. Our model achieved an optimized area under the curve in predicting death (0.785, 95% CI: 0.757-0.813) compared with the Charlson Comorbidity Index (0.747, P = 0.007), ischaemic stroke (0.691, 0.626-0.756) compared with CHA
2 DS2 -VASc (0.613, P = 0.028), and major bleeding (0.698, 0.651-0.745) as opposed to HAS-BLED (0.607, P = 0.002), with improvement in net reclassification index (10.0, 12.5, and 23.6%, respectively)., Conclusion: The ML-GBDT model outperformed clinical risk scores in predicting the risks in patients with AF. This approach could be used as a single multifaceted holistic tool to optimize patient risk assessment and mitigate adverse outcomes when managing AF., Competing Interests: Conflict of interest: none declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)- Published
- 2024
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32. Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment.
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Abu-Shawareb H, Acree R, Adams P, Adams J, Addis B, Aden R, Adrian P, Afeyan BB, Aggleton M, Aghaian L, Aguirre A, Aikens D, Akre J, Albert F, Albrecht M, Albright BJ, Albritton J, Alcala J, Alday C, Alessi DA, Alexander N, Alfonso J, Alfonso N, Alger E, Ali SJ, Ali ZA, Allen A, Alley WE, Amala P, Amendt PA, Amick P, Ammula S, Amorin C, Ampleford DJ, Anderson RW, Anklam T, Antipa N, Appelbe B, Aracne-Ruddle C, Araya E, Archuleta TN, Arend M, Arnold P, Arnold T, Arsenlis A, Asay J, Atherton LJ, Atkinson D, Atkinson R, Auerbach JM, Austin B, Auyang L, Awwal AAS, Aybar N, Ayers J, Ayers S, Ayers T, Azevedo S, Bachmann B, Back CA, Bae J, Bailey DS, Bailey J, Baisden T, Baker KL, Baldis H, Barber D, Barberis M, Barker D, Barnes A, Barnes CW, Barrios MA, Barty C, Bass I, Batha SH, Baxamusa SH, Bazan G, Beagle JK, Beale R, Beck BR, Beck JB, Bedzyk M, Beeler RG, Beeler RG, Behrendt W, Belk L, Bell P, Belyaev M, Benage JF, Bennett G, Benedetti LR, Benedict LX, Berger RL, Bernat T, Bernstein LA, Berry B, Bertolini L, Besenbruch G, Betcher J, Bettenhausen R, Betti R, Bezzerides B, Bhandarkar SD, Bickel R, Biener J, Biesiada T, Bigelow K, Bigelow-Granillo J, Bigman V, Bionta RM, Birge NW, Bitter M, Black AC, Bleile R, Bleuel DL, Bliss E, Bliss E, Blue B, Boehly T, Boehm K, Boley CD, Bonanno R, Bond EJ, Bond T, Bonino MJ, Borden M, Bourgade JL, Bousquet J, Bowers J, Bowers M, Boyd R, Boyle D, Bozek A, Bradley DK, Bradley KS, Bradley PA, Bradley L, Brannon L, Brantley PS, Braun D, Braun T, Brienza-Larsen K, Briggs R, Briggs TM, Britten J, Brooks ED, Browning D, Bruhn MW, Brunner TA, Bruns H, Brunton G, Bryant B, Buczek T, Bude J, Buitano L, Burkhart S, Burmark J, Burnham A, Burr R, Busby LE, Butlin B, Cabeltis R, Cable M, Cabot WH, Cagadas B, Caggiano J, Cahayag R, Caldwell SE, Calkins S, Callahan DA, Calleja-Aguirre J, Camara L, Camp D, Campbell EM, Campbell JH, Carey B, Carey R, Carlisle K, Carlson L, Carman L, Carmichael J, Carpenter A, Carr C, Carrera JA, Casavant D, Casey A, Casey DT, Castillo A, Castillo E, Castor JI, Castro C, Caughey W, Cavitt R, Celeste J, Celliers PM, Cerjan C, Chandler G, Chang B, Chang C, Chang J, Chang L, Chapman R, Chapman TD, Chase L, Chen H, Chen H, Chen K, Chen LY, Cheng B, Chittenden J, Choate C, Chou J, Chrien RE, Chrisp M, Christensen K, Christensen M, Christiansen NS, Christopherson AR, Chung M, Church JA, Clark A, Clark DS, Clark K, Clark R, Claus L, Cline B, Cline JA, Cobble JA, Cochrane K, Cohen B, Cohen S, Collette MR, Collins GW, Collins LA, Collins TJB, Conder A, Conrad B, Conyers M, Cook AW, Cook D, Cook R, Cooley JC, Cooper G, Cope T, Copeland SR, Coppari F, Cortez J, Cox J, Crandall DH, Crane J, Craxton RS, Cray M, Crilly A, Crippen JW, Cross D, Cuneo M, Cuotts G, Czajka CE, Czechowicz D, Daly T, Danforth P, Danly C, Darbee R, Darlington B, Datte P, Dauffy L, Davalos G, Davidovits S, Davis P, Davis J, Dawson S, Day RD, Day TH, Dayton M, Deck C, Decker C, Deeney C, DeFriend KA, Deis G, Delamater ND, Delettrez JA, Demaret R, Demos S, Dempsey SM, Desjardin R, Desjardins T, Desjarlais MP, Dewald EL, DeYoreo J, Diaz S, Dimonte G, Dittrich TR, Divol L, Dixit SN, Dixon J, Do A, Dodd ES, Dolan D, Donovan A, Donovan M, Döppner T, Dorrer C, Dorsano N, Douglas MR, Dow D, Downie J, Downing E, Dozieres M, Draggoo V, Drake D, Drake RP, Drake T, Dreifuerst G, Drury O, DuBois DF, DuBois PF, Dunham G, Durocher M, Dylla-Spears R, Dymoke-Bradshaw AKL, Dzenitis B, Ebbers C, Eckart M, Eddinger S, Eder D, Edgell D, Edwards MJ, Efthimion P, Eggert JH, Ehrlich B, Ehrmann P, Elhadj S, Ellerbee C, Elliott NS, Ellison CL, Elsner F, Emerich M, Engelhorn K, England T, English E, Epperson P, Epstein R, Erbert G, Erickson MA, Erskine DJ, Erlandson A, Espinosa RJ, Estes C, Estabrook KG, Evans S, Fabyan A, Fair J, Fallejo R, Farmer N, Farmer WA, Farrell M, Fatherley VE, Fedorov M, Feigenbaum E, Fehrenbach T, Feit M, Felker B, Ferguson W, Fernandez JC, Fernandez-Panella A, Fess S, Field JE, Filip CV, Fincke JR, Finn T, Finnegan SM, Finucane RG, Fischer M, Fisher A, Fisher J, Fishler B, Fittinghoff D, Fitzsimmons P, Flegel M, Flippo KA, Florio J, Folta J, Folta P, Foreman LR, Forrest C, Forsman A, Fooks J, Foord M, Fortner R, Fournier K, Fratanduono DE, Frazier N, Frazier T, Frederick C, Freeman MS, Frenje J, Frey D, Frieders G, Friedrich S, Froula DH, Fry J, Fuller T, Gaffney J, Gales S, Le Galloudec B, Le Galloudec KK, Gambhir A, Gao L, Garbett WJ, Garcia A, Gates C, Gaut E, Gauthier P, Gavin Z, Gaylord J, Geddes CGR, Geissel M, Génin F, Georgeson J, Geppert-Kleinrath H, Geppert-Kleinrath V, Gharibyan N, Gibson J, Gibson C, Giraldez E, Glebov V, Glendinning SG, Glenn S, Glenzer SH, Goade S, Gobby PL, Goldman SR, Golick B, Gomez M, Goncharov V, Goodin D, Grabowski P, Grafil E, Graham P, Grandy J, Grasz E, Graziani FR, Greenman G, Greenough JA, Greenwood A, Gregori G, Green T, Griego JR, Grim GP, Grondalski J, Gross S, Guckian J, Guler N, Gunney B, Guss G, Haan S, Hackbarth J, Hackel L, Hackel R, Haefner C, Hagmann C, Hahn KD, Hahn S, Haid BJ, Haines BM, Hall BM, Hall C, Hall GN, Hamamoto M, Hamel S, Hamilton CE, Hammel BA, Hammer JH, Hampton G, Hamza A, Handler A, Hansen S, Hanson D, Haque R, Harding D, Harding E, Hares JD, Harris DB, Harte JA, Hartouni EP, Hatarik R, Hatchett S, Hauer AA, Havre M, Hawley R, Hayes J, Hayes J, Hayes S, Hayes-Sterbenz A, Haynam CA, Haynes DA, Headley D, Heal A, Heebner JE, Heerey S, Heestand GM, Heeter R, Hein N, Heinbockel C, Hendricks C, Henesian M, Heninger J, Henrikson J, Henry EA, Herbold EB, Hermann MR, Hermes G, Hernandez JE, Hernandez VJ, Herrmann MC, Herrmann HW, Herrera OD, Hewett D, Hibbard R, Hicks DG, Higginson DP, Hill D, Hill K, Hilsabeck T, Hinkel DE, Ho DD, Ho VK, Hoffer JK, Hoffman NM, Hohenberger M, Hohensee M, Hoke W, Holdener D, Holdener F, Holder JP, Holko B, Holunga D, Holzrichter JF, Honig J, Hoover D, Hopkins D, Berzak Hopkins LF, Hoppe M, Hoppe ML, Horner J, Hornung R, Horsfield CJ, Horvath J, Hotaling D, House R, Howell L, Hsing WW, Hu SX, Huang H, Huckins J, Hui H, Humbird KD, Hund J, Hunt J, Hurricane OA, Hutton M, Huynh KH, Inandan L, Iglesias C, Igumenshchev IV, Ivanovich I, Izumi N, Jackson M, Jackson J, Jacobs SD, James G, Jancaitis K, Jarboe J, Jarrott LC, Jasion D, Jaquez J, Jeet J, Jenei AE, Jensen J, Jimenez J, Jimenez R, Jobe D, Johal Z, Johns HM, Johnson D, Johnson MA, Gatu Johnson M, Johnson RJ, Johnson S, Johnson SA, Johnson T, Jones K, Jones O, Jones M, Jorge R, Jorgenson HJ, Julian M, Jun BI, Jungquist R, Kaae J, Kabadi N, Kaczala D, Kalantar D, Kangas K, Karasiev VV, Karasik M, Karpenko V, Kasarky A, Kasper K, Kauffman R, Kaufman MI, Keane C, Keaty L, Kegelmeyer L, Keiter PA, Kellett PA, Kellogg J, Kelly JH, Kemic S, Kemp AJ, Kemp GE, Kerbel GD, Kershaw D, Kerr SM, Kessler TJ, Key MH, Khan SF, Khater H, Kiikka C, Kilkenny J, Kim Y, Kim YJ, Kimko J, Kimmel M, Kindel JM, King J, Kirkwood RK, Klaus L, Klem D, Kline JL, Klingmann J, Kluth G, Knapp P, Knauer J, Knipping J, Knudson M, Kobs D, Koch J, Kohut T, Kong C, Koning JM, Koning P, Konior S, Kornblum H, Kot LB, Kozioziemski B, Kozlowski M, Kozlowski PM, Krammen J, Krasheninnikova NS, Krauland CM, Kraus B, Krauser W, Kress JD, Kritcher AL, Krieger E, Kroll JJ, Kruer WL, Kruse MKG, Kucheyev S, Kumbera M, Kumpan S, Kunimune J, Kur E, Kustowski B, Kwan TJT, Kyrala GA, Laffite S, Lafon M, LaFortune K, Lagin L, Lahmann B, Lairson B, Landen OL, Land T, Lane M, Laney D, Langdon AB, Langenbrunner J, Langer SH, Langro A, Lanier NE, Lanier TE, Larson D, Lasinski BF, Lassle D, LaTray D, Lau G, Lau N, Laumann C, Laurence A, Laurence TA, Lawson J, Le HP, Leach RR, Leal L, Leatherland A, LeChien K, Lechleiter B, Lee A, Lee M, Lee T, Leeper RJ, Lefebvre E, Leidinger JP, LeMire B, Lemke RW, Lemos NC, Le Pape S, Lerche R, Lerner S, Letts S, Levedahl K, Lewis T, Li CK, Li H, Li J, Liao W, Liao ZM, Liedahl D, Liebman J, Lindford G, Lindman EL, Lindl JD, Loey H, London RA, Long F, Loomis EN, Lopez FE, Lopez H, Losbanos E, Loucks S, Lowe-Webb R, Lundgren E, Ludwigsen AP, Luo R, Lusk J, Lyons R, Ma T, Macallop Y, MacDonald MJ, MacGowan BJ, Mack JM, Mackinnon AJ, MacLaren SA, MacPhee AG, Magelssen GR, Magoon J, Malone RM, Malsbury T, Managan R, Mancini R, Manes K, Maney D, Manha D, Mannion OM, Manuel AM, Manuel MJ, Mapoles E, Mara G, Marcotte T, Marin E, Marinak MM, Mariscal DA, Mariscal EF, Marley EV, Marozas JA, Marquez R, Marshall CD, Marshall FJ, Marshall M, Marshall S, Marticorena J, Martinez JI, Martinez D, Maslennikov I, Mason D, Mason RJ, Masse L, Massey W, Masson-Laborde PE, Masters ND, Mathisen D, Mathison E, Matone J, Matthews MJ, Mattoon C, Mattsson TR, Matzen K, Mauche CW, Mauldin M, McAbee T, McBurney M, Mccarville T, McCrory RL, McEvoy AM, McGuffey C, Mcinnis M, McKenty P, McKinley MS, McLeod JB, McPherson A, Mcquillan B, Meamber M, Meaney KD, Meezan NB, Meissner R, Mehlhorn TA, Mehta NC, Menapace J, Merrill FE, Merritt BT, Merritt EC, Meyerhofer DD, Mezyk S, Mich RJ, Michel PA, Milam D, Miller C, Miller D, Miller DS, Miller E, Miller EK, Miller J, Miller M, Miller PE, Miller T, Miller W, Miller-Kamm V, Millot M, Milovich JL, Minner P, Miquel JL, Mitchell S, Molvig K, Montesanti RC, Montgomery DS, Monticelli M, Montoya A, Moody JD, Moore AS, Moore E, Moran M, Moreno JC, Moreno K, Morgan BE, Morrow T, Morton JW, Moses E, Moy K, Muir R, Murillo MS, Murray JE, Murray JR, Munro DH, Murphy TJ, Munteanu FM, Nafziger J, Nagayama T, Nagel SR, Nast R, Negres RA, Nelson A, Nelson D, Nelson J, Nelson S, Nemethy S, Neumayer P, Newman K, Newton M, Nguyen H, Di Nicola JG, Di Nicola P, Niemann C, Nikroo A, Nilson PM, Nobile A, Noorai V, Nora RC, Norton M, Nostrand M, Note V, Novell S, Nowak PF, Nunez A, Nyholm RA, O'Brien M, Oceguera A, Oertel JA, Oesterle AL, Okui J, Olejniczak B, Oliveira J, Olsen P, Olson B, Olson K, Olson RE, Opachich YP, Orsi N, Orth CD, Owen M, Padalino S, Padilla E, Paguio R, Paguio S, Paisner J, Pajoom S, Pak A, Palaniyappan S, Palma K, Pannell T, Papp F, Paras D, Parham T, Park HS, Pasternak A, Patankar S, Patel MV, Patel PK, Patterson R, Patterson S, Paul B, Paul M, Pauli E, Pearce OT, Pearcy J, Pedretti A, Pedrotti B, Peer A, Pelz LJ, Penetrante B, Penner J, Perez A, Perkins LJ, Pernice E, Perry TS, Person S, Petersen D, Petersen T, Peterson DL, Peterson EB, Peterson JE, Peterson JL, Peterson K, Peterson RR, Petrasso RD, Philippe F, Phillion D, Phipps TJ, Piceno E, Pickworth L, Ping Y, Pino J, Piston K, Plummer R, Pollack GD, Pollaine SM, Pollock BB, Ponce D, Ponce J, Pontelandolfo J, Porter JL, Post J, Poujade O, Powell C, Powell H, Power G, Pozulp M, Prantil M, Prasad M, Pratuch S, Price S, Primdahl K, Prisbrey S, Procassini R, Pruyne A, Pudliner B, Qiu SR, Quan K, Quinn M, Quintenz J, Radha PB, Rainer F, Ralph JE, Raman KS, Raman R, Rambo PW, Rana S, Randewich A, Rardin D, Ratledge M, Ravelo N, Ravizza F, Rayce M, Raymond A, Raymond B, Reed B, Reed C, Regan S, Reichelt B, Reis V, Reisdorf S, Rekow V, Remington BA, Rendon A, Requieron W, Rever M, Reynolds H, Reynolds J, Rhodes J, Rhodes M, Richardson MC, Rice B, Rice NG, Rieben R, Rigatti A, Riggs S, Rinderknecht HG, Ring K, Riordan B, Riquier R, Rivers C, Roberts D, Roberts V, Robertson G, Robey HF, Robles J, Rocha P, Rochau G, Rodriguez J, Rodriguez S, Rosen MD, Rosenberg M, Ross G, Ross JS, Ross P, Rouse J, Rovang D, Rubenchik AM, Rubery MS, Ruiz CL, Rushford M, Russ B, Rygg JR, Ryujin BS, Sacks RA, Sacks RF, Saito K, Salmon T, Salmonson JD, Sanchez J, Samuelson S, Sanchez M, Sangster C, Saroyan A, Sater J, Satsangi A, Sauers S, Saunders R, Sauppe JP, Sawicki R, Sayre D, Scanlan M, Schaffers K, Schappert GT, Schiaffino S, Schlossberg DJ, Schmidt DW, Schmit PF, Smidt JM, Schneider DHG, Schneider MB, Schneider R, Schoff M, Schollmeier M, Schroeder CR, Schrauth SE, Scott HA, Scott I, Scott JM, Scott RHH, Scullard CR, Sedillo T, Seguin FH, Seka W, Senecal J, Sepke SM, Seppala L, Sequoia K, Severyn J, Sevier JM, Sewell N, Seznec S, Shah RC, Shamlian J, 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Theobald W, Thi M, Thomas A, Thomas CA, Thomas I, Thomas R, Thompson IJ, Thongstisubskul A, Thorsness CB, Tietbohl G, Tipton RE, Tobin M, Tomlin N, Tommasini R, Toreja AJ, Torres J, Town RPJ, Townsend S, Trenholme J, Trivelpiece A, Trosseille C, Truax H, Trummer D, Trummer S, Truong T, Tubbs D, Tubman ER, Tunnell T, Turnbull D, Turner RE, Ulitsky M, Upadhye R, Vaher JL, VanArsdall P, VanBlarcom D, Vandenboomgaerde M, VanQuinlan R, Van Wonterghem BM, Varnum WS, Velikovich AL, Vella A, Verdon CP, Vermillion B, Vernon S, Vesey R, Vickers J, Vignes RM, Visosky M, Vocke J, Volegov PL, Vonhof S, Von Rotz R, Vu HX, Vu M, Wall D, Wall J, Wallace R, Wallin B, Walmer D, Walsh CA, Walters CF, Waltz C, Wan A, Wang A, Wang Y, Wark JS, Warner BE, Watson J, Watt RG, Watts P, Weaver J, Weaver RP, Weaver S, Weber CR, Weber P, Weber SV, Wegner P, Welday B, Welser-Sherrill L, Weiss K, Wharton KB, Wheeler GF, Whistler W, White RK, Whitley HD, Whitman P, Wickett ME, Widmann K, Widmayer C, Wiedwald J, Wilcox R, Wilcox S, Wild C, Wilde BH, Wilde CH, Wilhelmsen K, Wilke MD, Wilkens H, Wilkins P, Wilks SC, Williams EA, Williams GJ, Williams W, Williams WH, Wilson DC, Wilson B, Wilson E, Wilson R, Winters S, Wisoff PJ, Wittman M, Wolfe J, Wong A, Wong KW, Wong L, Wong N, Wood R, Woodhouse D, Woodruff J, Woods DT, Woods S, Woodworth BN, Wooten E, Wootton A, Work K, Workman JB, Wright J, Wu M, Wuest C, Wysocki FJ, Xu H, Yamaguchi M, Yang B, Yang ST, Yatabe J, Yeamans CB, Yee BC, Yi SA, Yin L, Young B, Young CS, Young CV, Young P, Youngblood K, Yu J, Zacharias R, Zagaris G, Zaitseva N, Zaka F, Ze F, Zeiger B, Zika M, Zimmerman GB, Zobrist T, Zuegel JD, and Zylstra AB
- Abstract
On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.
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- 2024
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33. Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation.
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Lu J, Hutchens R, Hung J, Bennamoun M, McQuillan B, Briffa T, Sohel F, Murray K, Stewart J, Chow B, Sanfilippo F, and Dwivedi G
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- Humans, Female, Aged, Male, Retrospective Studies, Risk Assessment, Hemorrhage, Anticoagulants adverse effects, Risk Factors, Atrial Fibrillation complications, Atrial Fibrillation drug therapy, Stroke drug therapy
- Abstract
Background: Appropriate anticoagulant therapy for patients with atrial fibrillation (AF) requires assessment of stroke and bleeding risks. However, risk stratification schemas such as CHA
2 DS2 -VASc and HAS-BLED have modest predictive capacity for patients with AF. Multilabel machine learning (ML) techniques may improve predictive performance and support decision-making for anticoagulant therapy. We compared the performance of multilabel ML models with the currently used risk scores for predicting outcomes in AF patients., Methods: This was a retrospective cohort study of 9670 patients, mean age 76.9 years, 46% women, who were hospitalized with non-valvular AF, and had 1-year follow-up. The outcomes were ischemic stroke (167), major bleeding (430) admissions, all-cause death (1912) and event-free survival (7387). Discrimination and calibration of ML models were compared with clinical risk scores by area under the curve (AUC). Risk stratification was assessed using net reclassification index (NRI)., Results: Multilabel gradient boosting classifier chain provided the best AUCs for stroke (0.685 95% CI 0.676, 0.694), major bleeding (0.709 95% CI 0.703, 0.716) and death (0.765 95% CI 0.763, 0.768) compared to multi-layer neural networks and classifier chain using support vector machine. It provided modest performance improvement for stroke compared to AUC of CHA2 DS2 -VASc (0.652, NRI = 3.2%, p-value = 0.1), but significantly improved major bleeding prediction compared to AUC of HAS-BLED (0.522, NRI = 22.8%, p-value < 0.05). It also achieved greater discriminant power for death compared with AUC of CHA2 DS2 -VASc (0.606, p-value < 0.05). ML models identified additional risk features such as hemoglobin level, renal function., Conclusions: Multilabel ML models can outperform clinical risk stratification scores for predicting the risk of major bleeding and death in non-valvular AF patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)- Published
- 2022
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34. Impact of Pre-Hospital Activation of STEMI on False Positive Activation Rate and Door to Balloon Time.
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Shoaib M, Huish W, Woollard EL, Aguila J, Coxall D, Alexander M, Hicks D, and McQuillan B
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- Emergency Service, Hospital, Hospitals, Humans, Retrospective Studies, Time Factors, Percutaneous Coronary Intervention methods, ST Elevation Myocardial Infarction diagnosis, ST Elevation Myocardial Infarction etiology, ST Elevation Myocardial Infarction surgery
- Abstract
Background: Pre-hospital identification of ST-segment elevation myocardial infarction (STEMI) by paramedical staff reduces reperfusion time. However, the impact of this approach on the rate of unnecessary activation of coronary catheterisation lab (CCL) remains unclear., Methods: The study reviewed consecutive STEMI patients over 3 years (July 2015 to June 2018) from all primary percutaneous coronary intervention (PPCI) centres and inter-hospital transfers (IHT) from non-PPCI capable centres in Western Australia. Out-of-hospital cardiac arrests (OOHCA) and STEMI calls for in-patients receiving treatment for other medical reasons were excluded., Results: During the 3 years study period, 1,736 STEMI cases were recorded. Pre-hospital (PH) activation occurred in 799 (46%) cases. Median door to balloon time (D2BT) was 68 minutes (IQR 63 mins). D2BT for PH activation (40 min [IQR 25 min]) was significantly lower than both the PPCI centre emergency department (ED) activation (86 min [IQR 55 min]) and IHT activation groups (108 min [IQR 55 min]), p-value <0.00001. In PH activation group 98% patients received primary PCI in less than 90 minutes compared to 54% and 26% patients in the ED and the IHT activation groups, respectively. False positive STEMI activation rate was lower in the PH activation group (2.75%) compared to ED activation (5.4%) and IHT group (6%), p-value 0.0115. The false positive rate did not vary significantly between working hours and out-of-hour calls (5% vs 4%, p-value=0.304). Pericarditis, coronary artery disease other than STEMI, atypical chest pain, and stress induced cardiomyopathy were the common diagnoses in false positive activations., Conclusion: Pre-hospital activation of STEMI leads to reduced door to balloon times without a significant increase in inappropriate procedures, though false positive activation rates are unclear. The majority of STEMI patients transferred from non-PPCI centres failed to receive reperfusion therapy within 90 minutes of initial hospital presentation. Further studies are required to assess the benefits of thrombolysis in selected patients in inter-hospital transfer group., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)
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- 2022
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35. Alcohol Consumption and Cardiovascular Outcomes in Patients With Nonalcoholic Fatty Liver Disease: A Population-Based Cohort Study.
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Janjua M, Knuiman M, Divitini M, McQuillan B, Olynyk JK, Jeffrey GP, and Adams LA
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- Alcohol Drinking adverse effects, Australia epidemiology, Cohort Studies, Female, Humans, Male, Cardiovascular Diseases epidemiology, Non-alcoholic Fatty Liver Disease epidemiology
- Abstract
Low-level alcohol consumption is associated with reduced cardiovascular disease (CVD) in the general population. It is unclear whether this association is seen in patients with nonalcoholic fatty liver disease (NAFLD) who have an increased risk of CVD. We examined the association between alcohol consumption and CVD-related outcomes in subjects with NAFLD from a general population cohort. Subjects participating in the 1994-1995 Busselton Health survey underwent clinical and biochemical assessment. NAFLD was identified using the Fatty Liver Index of >60, and alcohol consumption quantified using a validated questionnaire. CVD hospitalizations and death during the ensuing 20 years were ascertained using the Western Australian data linkage system. A total of 659 of 4,843 patients were diagnosed with NAFLD. The average standard drinks per week was 8.0 for men and 4.0 for women. Men consuming 8-21 drinks per week had a 38% (hazard ratio [HR] 0.62, 95% confidence interval [CI] 0.43-0.90) lower risk of CVD hospitalization as compared with men consuming 1-7 drinks per week. With both men and women combined, consumption of 8-21 drinks per week was associated with a 32% (HR 0.68, 95% CI 0.49-0.93) reduction in CVD hospitalization in minimally adjusted and 29% (HR 0.71, 95% CI 0.51-0.99) in fully adjusted models. No protective association was observed with binge drinking. There was no association between alcohol consumption and CVD death. Conclusion: Low to moderate alcohol consumption is associated with fewer CVD hospitalizations but not CVD death in subjects with NAFLD., (© 2021 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.)
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- 2022
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36. Prehospital continuous positive airway pressure (CPAP) for acute respiratory distress: a randomised controlled trial.
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Finn JC, Brink D, Mckenzie N, Garcia A, Tohira H, Perkins GD, Arendts G, Fatovich DM, Hendrie D, McQuillan B, Summers Q, Celenza A, Mukherjee A, Smedley B, Pereira G, Ball S, Williams T, and Bailey P
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- Continuous Positive Airway Pressure, Humans, Emergency Medical Services, Respiratory Distress Syndrome therapy
- Abstract
Objective: To compare the efficacy of continuous positive airway pressure (CPAP) versus usual care for prehospital patients with severe respiratory distress., Methods: We conducted a parallel group, individual patient, non-blinded randomised controlled trial in Western Australia between March 2016 and December 2018. Eligible patients were aged ≥40 years with acute severe respiratory distress of non-traumatic origin and unresponsive to initial treatments by emergency medical service (EMS) paramedics. Patients were randomised (1:1) to usual care or usual care plus CPAP. The primary outcomes were change in dyspnoea score and change in RR at ED arrival, and hospital length of stay., Results: 708 patients were randomly assigned (opaque sealed envelope) to usual care (n=346) or CPAP (n=362). Compared with usual care, patients randomised to CPAP had a greater reduction in dyspnoea scores (usual care -1.0, IQR -3.0 to 0.0 vs CPAP -3.5, IQR -5.2 to -2.0), median difference -2.0 (95% CI -2.5 to -1.6); and RR (usual care -4.0, IQR -9.0 to 0.0 min
-1 vs CPAP -8.0, IQR -14.0 to -4.0 min-1 ), median difference -4.0 (95% CI -5.0 to -4.0) min-1 . There was no difference in hospital length of stay (usual care 4.2, IQR 2.1 to 7.8 days vs CPAP 4.8, IQR 2.5 to 7.9 days) for the n=624 cases admitted to hospital, median difference 0.36 (95% CI -0.17 to 0.90)., Conclusions: The use of prehospital CPAP by EMS paramedics reduced dyspnoea and tachypnoea in patients with acute respiratory distress but did not impact hospital length of stay., Trial Registration Number: ACTRN12615001180505., Competing Interests: Competing interests: Several of the authors are affiliated with St John Western Australia, as follows: DB, AG, PB (employees); JF, SB (adjunct research positions); JF (research funding)., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)- Published
- 2022
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37. Association of hypertension with mortality in patients hospitalised with COVID-19.
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Bhatia KS, Sritharan HP, Ciofani J, Chia J, Allahwala UK, Chui K, Nour D, Vasanthakumar S, Khandadai D, Jayadeva P, Bhagwandeen R, Brieger D, Choong C, Delaney A, Dwivedi G, Harris B, Hillis G, Hudson B, Javorski G, Jepson N, Kanagaratnam L, Kotsiou G, Lee A, Lo ST, MacIsaac AI, McQuillan B, Ranasinghe I, Walton A, Weaver J, Wilson W, Yong ASC, Zhu J, Van Gaal W, Kritharides L, Chow CK, and Bhindi R
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- Adult, Aged, Aged, 80 and over, Angiotensin Receptor Antagonists therapeutic use, Angiotensin-Converting Enzyme Inhibitors therapeutic use, Antihypertensive Agents therapeutic use, Australia epidemiology, COVID-19 diagnosis, COVID-19 therapy, Comorbidity, Female, Humans, Hypertension diagnosis, Hypertension drug therapy, Male, Middle Aged, Prevalence, Prognosis, Registries, Risk Assessment, Risk Factors, Time Factors, COVID-19 mortality, Hospital Mortality, Hospitalization, Hypertension mortality
- Abstract
Objective: To assess whether hypertension is an independent risk factor for mortality among patients hospitalised with COVID-19, and to evaluate the impact of ACE inhibitor and angiotensin receptor blocker (ARB) use on mortality in patients with a background of hypertension., Method: This observational cohort study included all index hospitalisations with laboratory-proven COVID-19 aged ≥18 years across 21 Australian hospitals. Patients with suspected, but not laboratory-proven COVID-19, were excluded. Registry data were analysed for in-hospital mortality in patients with comorbidities including hypertension, and baseline treatment with ACE inhibitors or ARBs., Results: 546 consecutive patients (62.9±19.8 years old, 51.8% male) hospitalised with COVID-19 were enrolled. In the multivariable model, significant predictors of mortality were age (adjusted OR (aOR) 1.09, 95% CI 1.07 to 1.12, p<0.001), heart failure or cardiomyopathy (aOR 2.71, 95% CI 1.13 to 6.53, p=0.026), chronic kidney disease (aOR 2.33, 95% CI 1.02 to 5.32, p=0.044) and chronic obstructive pulmonary disease (aOR 2.27, 95% CI 1.06 to 4.85, p=0.035). Hypertension was the most prevalent comorbidity (49.5%) but was not independently associated with increased mortality (aOR 0.92, 95% CI 0.48 to 1.77, p=0.81). Among patients with hypertension, ACE inhibitor (aOR 1.37, 95% CI 0.61 to 3.08, p=0.61) and ARB (aOR 0.64, 95% CI 0.27 to 1.49, p=0.30) use was not associated with mortality., Conclusions: In patients hospitalised with COVID-19, pre-existing hypertension was the most prevalent comorbidity but was not independently associated with mortality. Similarly, the baseline use of ACE inhibitors or ARBs had no independent association with in-hospital mortality., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Published
- 2021
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38. Antithrombotic Therapy in Atrial Fibrillation Management in Western Australia: Temporal Trends and Evidence-Treatment Gaps.
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Hutchens R, Hung J, Briffa T, and McQuillan B
- Subjects
- Administration, Oral, Adult, Aged, Anticoagulants therapeutic use, Female, Fibrinolytic Agents therapeutic use, Humans, Male, Retrospective Studies, Risk Factors, Western Australia epidemiology, Atrial Fibrillation complications, Atrial Fibrillation drug therapy, Atrial Fibrillation epidemiology, Stroke epidemiology, Stroke etiology, Stroke prevention & control
- Abstract
Objective: To describe temporal trends in appropriate antithrombotic therapy use in hospitalised atrial fibrillation (AF) patients and identify evidence-treatment gaps in clinical practice., Design: Retrospective cohort study from January 2009-March 2016., Setting: Tertiary and secondary teaching hospitals in Perth, Western Australia., Participants: Hospitalised adults with non-valvular AF., Results: We identified 11,294 index AF admissions, with a mean age of 76.9 years, 45.8% women and 86.3% at high risk of stroke (CHA
2 DS2 -VASc score ≥2 in men and ≥3 in women). In high risk subjects use of appropriate antithrombotic therapy improved over time with increasing oral anticoagulant (OAC) use and declining sole antiplatelet use (both trend p<0.001). However, by study end only 45.3% of high-risk patients were receiving OAC therapy. In low risk patients, receipt of OAC therapy was steady throughout the study at 40.5% (trend p=0.10). The gender gap in OAC use narrowed over time, with no significant difference between high risk men and women by study end. Use of OAC therapy in elderly patients (age ≥75 years) remained lower than younger patients (age <65 years) over the entire period, with only 31% of elderly patients receiving OAC therapy at study end. From 2012 onwards use of non-vitamin K oral anticoagulants (NOACs) doubled each year with declining warfarin use (both trend p<0.001)., Conclusion: Despite substantial uptake of NOACs, OAC therapy in AF patients at high risk of stroke remains under-utilised in Western Australia and over-utilised in low risk patients. Further work is required to reduce treatment-risk mismatch for stroke prevention in AF patients., (Copyright © 2021. Published by Elsevier B.V.)- Published
- 2021
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39. Ischaemic Stroke and the Echocardiographic "Bubble Study": Are We Screening the Right Patients?
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Maggiore P, Bellinge J, Chieng D, White D, Lan NSR, Jaltotage B, Ali U, Gordon M, Chung K, Stobie P, Ng J, Hankey GJ, and McQuillan B
- Subjects
- Adult, Aged, Female, Humans, Male, Mass Screening, Middle Aged, Retrospective Studies, Risk Factors, Stroke diagnostic imaging, Stroke etiology, Stroke prevention & control, Echocardiography, Transesophageal, Foramen Ovale, Patent complications, Foramen Ovale, Patent diagnostic imaging, Ischemic Attack, Transient diagnostic imaging, Ischemic Attack, Transient etiology, Ischemic Attack, Transient prevention & control
- Abstract
Background: Patent foramen ovale (PFO) is a potential mechanism for paradoxical embolism in cryptogenic ischaemic stroke or transient ischaemic attack (TIA). PFO is typically demonstrated with agitated saline ("bubble study", BS) during echocardiography. We hypothesised that the BS is frequently requested in patients that have a readily identifiable cause of stroke, that any PFO detected is likely incidental, and its detection often does not alter management., Methods: This was a retrospective observational study of patients with recent ischaemic stroke/TIA referred for a BS. Patient demographics, stroke risk factors, vascular/cerebral imaging results and transoesophageal echocardiogram (TOE) reports were recorded. A "modified" Risk of Paradoxical Embolism (RoPE) score was calculated. Change in management was defined as antiplatelet/anticoagulant therapy alteration or referral for PFO closure. Bubble Study complications were recorded., Results: Among 715 patients with ischaemic stroke/TIA referred for a BS, 8.7% had atrial fibrillation and 9.2% had carotid stenosis ≥70%. At least three stroke risk factors were present in 39.3% and only 47.1% of patients screened had a "modified" RoPE score of >5. A PFO was detected in 248 patients of whom only 31% (77/248) had a subsequent change in management. Of BS performed, 1/924 patients (0.1%) suffered a TIA as a complication., Conclusions: The echocardiographic BS is frequently performed in patients that have a readily identifiable cause of stroke and whose PFO unlikely relates to the stroke/TIA. Bubble Study findings resulted in a change in management in the minority. The procedure is safe but the complication rate warrants informed consent., (Copyright © 2018 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). All rights reserved.)
- Published
- 2019
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40. A 5α-reductase (SRD5A2) polymorphism is associated with serum testosterone and sex hormone-binding globulin in men, while aromatase (CYP19A1) polymorphisms are associated with oestradiol and luteinizing hormone reciprocally.
- Author
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Yeap BB, Knuiman MW, Handelsman DJ, Ho KKY, Hui J, Divitini ML, Arscott GM, McQuillan B, Hung J, and Beilby JP
- Subjects
- Adult, Age Factors, Aged, Cross-Sectional Studies, Humans, Male, Middle Aged, Aromatase genetics, Cholestenone 5 alpha-Reductase genetics, Estradiol blood, Luteinizing Hormone blood, Polymorphism, Single Nucleotide, Sex Hormone-Binding Globulin analysis, Testosterone blood
- Abstract
Context: Pituitary luteinizing hormone (LH) stimulates testicular production of testosterone (T) which is metabolized to dihydrotestosterone (DHT) by 5α-reductase and to oestradiol (E2) by aromatase. How the activity of population variants in these enzymes impacts on gonadal function is unclear. We examined whether polymorphisms in 5α-reductase (SRD5A2) and aromatase (CYP19A1) genes predict circulating sex hormone concentrations., Design: Cross-sectional analysis of 1865 community-dwelling men aged 50.4 ± 16.8 years., Measurements: Early morning sera assayed for T, DHT and E2 (mass spectrometry), and SHBG and LH (immunoassay). Two SRD5A2 and eleven CYP19A1 polymorphisms were analysed by PCR. Regression models were adjusted for age and cardiometabolic risk factors., Results: SRD5A2 polymorphism rs9282858 GA vs. GG was associated with higher serum T (+1.5 nmol/L, P < 0.001) and higher SHBG (+3.3 nmol/L, P = 0.001). CYP19A1 polymorphisms were associated with higher serum E2 and lower LH in reciprocal fashion, from which the two-copy haplotype rs10046 = T/rs2899470 = G/rs11575899 = I/rs700518 = G/rs17703883 = T was associated with higher E2 (63.4 vs. 56.5 pmol/L, P = 0.001) and lower LH (3.9 vs. 4.5 IU/L, P = 0.001) compared to null copies. Conversely, rs10046 = C/rs2899470 = T/rs11575899 = D/rs700518 = A/rs17703883 = C was associated with lower E2 (51.8 vs. 62.0 pmol/L, P = 0.001) and higher LH (5.7 vs. 3.9 IU/L, P < 0.001). These haplotypes were associated primarily with differences in E2 in men <65 years and LH in men ≥65 years., Conclusions: A 5α-reductase polymorphism predicts circulating T and SHBG, while aromatase polymorphisms predict E2 and LH in reciprocal fashion. Age and aromatase polymorphisms interact to affect E2 and LH. How these functional polymorphisms impact on male reproductive and general health outcomes requires further study., (© 2018 John Wiley & Sons Ltd.)
- Published
- 2019
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41. Drivers of hospitalisation trends for non-valvular atrial fibrillation in Western Australia, 2000-2013.
- Author
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Weber C, Hung J, Hickling S, Li I, McQuillan B, and Briffa T
- Subjects
- Adult, Aged, Aged, 80 and over, Atrial Fibrillation epidemiology, Female, Follow-Up Studies, Humans, Incidence, Male, Middle Aged, Retrospective Studies, Risk Factors, Time Factors, Western Australia epidemiology, Atrial Fibrillation therapy, Hospitalization trends, Population Surveillance
- Abstract
Objective: To determine if increasing hospitalisations for non-valvular atrial fibrillation (NVAF) in Western Australia (WA) was due to incident (first-ever) or repeat hospitalisations, an ageing population structure, changing procedural practice or a combination of these factors., Methods: We conducted a longitudinal retrospective population study on all WA residents aged 25-94 years between 2000 and 2013, with a principal hospital discharge diagnosis of NVAF. Person-linked hospital morbidity and mortality records were used to measure annual rate ratios (RRs) and 95% confidence intervals (CIs) in the total and incident NVAF (25-94 years) hospitalisations, further stratified by sex and by age-specific standardised groups (25-44, 45-64, 65-75, 75-84, 85-94 years)., Results: There were 55,532 total hospitalisations for NVAF between 2000 and 2013, patient mean age 68.3 years, and 58% male. Annual age- and sex- standardised rates for total NVAF hospitalisation increased by 3.0%/year (RR 1.030; 95%CI; 1.028, 1.038), and in both men and women. The largest absolute increase in hospitalisation rate occurred in those aged 85-94 years (∆613/100,000 men and women combined). Incident NVAF hospitalisations showed a borderline decline of 0.5%/year (RR 0.99; 95%CI; 0.99, 1.0) with a statistically significant trend in women but not men. The rate of AF admissions associated with a catheter ablation increased by 13%/year (95%CI; 13.1%, 15.3%)., Conclusion: The increasing rates of total hospitalisation for NVAF is driven more by repeat than incident admissions, escalating hospitalisations in the very elderly, and more frequent interventional procedures. These drivers have major economic and healthcare planning implications., (Copyright © 2018. Published by Elsevier B.V.)
- Published
- 2019
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42. Helping doctors in training to STEP-UP: A leadership and quality improvement programme in the Belfast Health and Social Care Trust.
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Donaghy G, McKeever K, Flanagan C, O'Kane D, McQuillan B, Cash J, Jack C, and Lundy C
- Subjects
- Curriculum, Humans, Program Development, Program Evaluation methods, Education, Medical, Graduate, Leadership, Physicians, Quality Improvement, Specialization
- Abstract
Introduction: Medical engagement in healthcare organisations can improve service development and patient experience. Doctors in training have limited opportunities to engage in service improvement work and develop leadership skills., Method: We describe the Specialist Trainees Engaged in Leadership Programme (STEP) , a programme developed to introduce concepts of medical leadership and quality improvement skills in the Belfast Trust. STEP started in 2013 and over 140 trainees have now participated in the programme., Results: Over 42 quality improvement projects have been completed with the support of the programme. Evaluation of STEP has demonstrated an improvement across all domains explored throughout the duration of the programme, with benefits for the individual trainee and the wider organisation., Discussion: We describe the programme in detail. The STEP curriculum can easily be adapted to meet the needs of NHS trainees, allowing them to understand the objectives and strategy of their employers and improve their ability to plan and deliver safe, effective, patient-centred care., Competing Interests: Provenance: externally peer-reviewed. None of the authors have any competing interests or funding to declare.
- Published
- 2018
43. Perceptions about interpersonal relationships and school environment among middle school students with asthma.
- Author
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Rhee H, McQuillan B, Chen DG, and Atis S
- Subjects
- Adolescent, Asthma epidemiology, Child, Cross-Sectional Studies, Female, Humans, Male, Peer Group, Prevalence, School Teachers, Schools, Students, Asthma psychology, Attitude, Interpersonal Relations
- Abstract
Objectives: To examine interpersonal relationships involving peers and teachers and perceptions about school environment among middle school students with asthma in comparison to their healthy counterparts. The study also assesses asthma prevalence in a large sample of middle school students representing different geographic locations., Methods: Cross-sectional data were collected from 1059 middle school students in grades 6-8 enrolled in schools in a northeastern region of the United States. Students reported their chronic health conditions including asthma and completed questionnaires measuring perceptions about their relationships with peers and teachers as well as school environment. Analyses of covariance (ANCOVAs) were used to compare students with asthma and their healthy counterparts in the study variables., Results: Asthma was reported by 16.5% of the sample (n = 169). The rate was higher among minority students (23%) than their white counterparts (15%). Greater proportion of urban students (28%) reported asthma than rural (18%) and suburban (14%) students. Students with asthma reported significantly poorer relationships with peers (B = -1.74, p <.001) and teachers (B = -1.41, p =.009), and their perceptions about overall school environment (B = -1.30, p =.009) were also lower than their healthy counterparts. Race showed no significant effects on school factors., Conclusion: Overall asthma prevalence was substantially higher than the national average of adolescent asthma, particularly those residing in the urban area. Poor perceptions of interpersonal relationships with peers and teachers among students with asthma may indicate compromised quality of life. Suboptimal interpersonal relationships and school environment need to be identified and adequately addressed, given their implications for asthma management at the school setting among middle school students.
- Published
- 2017
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44. Neutral associations of testosterone, dihydrotestosterone and estradiol with fatal and non-fatal cardiovascular events, and mortality in men aged 17-97 years.
- Author
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Chan YX, Knuiman MW, Hung J, Divitini ML, Beilby JP, Handelsman DJ, Beilin J, McQuillan B, and Yeap BB
- Subjects
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Cohort Studies, Follow-Up Studies, Humans, Male, Mass Spectrometry, Middle Aged, Young Adult, Cardiovascular Diseases mortality, Dihydrotestosterone blood, Estradiol blood, Testosterone blood
- Abstract
Context: Lower testosterone (T) is associated with poorer health outcomes in older men, however, the relationship between T, dihydrotestosterone (DHT) and estradiol (E2) with cardiovascular disease (CVD) in younger to middle-aged men remains unclear., Objectives: We assessed associations between endogenous sex hormones with mortality (all-cause and CVD) and CVD events, in a cohort of men aged 17-97 years., Participants and Methods: Sex hormones were assayed using mass spectrometry in 2143 men from the 1994/5 Busselton Health Survey. Outcomes to December 2010 were analysed., Results: Of the 1804 men included in the analysis, mean age was 50·3 ± 16·8 years and 68·9% of men were aged <60. Mean follow-up period was 14·9 years. There were 319 deaths, 141 CVD deaths and 399 CVD events. Compared to the full cohort, men who died had lower baseline T (12·0 ± 4·4 vs 13·6 ± 4·9 nmol/l), free T (181·9 ± 52·9 vs 218·3 ± 63·8 pmol/l) and DHT (1·65 ± 0·64 vs 1·70 ± 0·72 nmol/l), but higher E2 (64·0 ± 32 vs 60·1 ± 30·2 pmol/l). After adjustment for risk factors, T was not associated with mortality (adjusted HR = 0·90, 95% CI 0·79-1·04; P = 0·164 for every increase in 1 SD of T), CVD deaths (adjusted HR = 1·04, 95% CI 0·84-1·29; P = 0·708) or CVD events (adjusted HR = 1·03, 95% CI 0·92-1·15, P = 0·661). No associations were found for free T, DHT or E2. Results were similar for men older and younger than 60 years., Conclusions: In predominantly middle-aged men, T, DHT and E2 do not influence mortality or CVD outcomes. This neutral association of hormones with CVD contrasts with prior studies of older men., (© 2016 John Wiley & Sons Ltd.)
- Published
- 2016
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45. REACTED - Reducing Acute Chest pain Time in the ED: A prospective pre-/post-interventional cohort study, stratifying risk using early cardiac multi-markers, probably increases discharges safely.
- Author
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Mountain D, Ercleve T, Allely P, McQuillan B, Yamen E, Beilby J, Lim EM, Rogers J, and Geelhoed E
- Subjects
- Acute Disease, Aged, Female, Humans, Length of Stay statistics & numerical data, Male, Middle Aged, Patient Safety, Practice Guidelines as Topic, Prospective Studies, Retrospective Studies, Risk Assessment, Western Australia, Biomarkers blood, Chest Pain diagnosis, Chest Pain therapy, Emergency Service, Hospital organization & administration, Patient Discharge statistics & numerical data, Troponin blood
- Abstract
Objective: ED chest pain assessments can be challenging, lengthy and contribute to overcrowding. Rapid accurate risk stratification strategies should improve ED length of stay (EDLOS). Emergency, Biochemistry and Cardiology implemented new guidelines using paired (<3 h) multiple cardiac markers to stratify patients. The intervention would reduce chest pain EDLOS. We observed for safety and disposition effects., Methods: This is a single-site, prospective observational, before and after intervention study. In December 2009, paired multiple cardiac markers, the second at least 4 h from pain, replaced late troponins. The 4 h rule (ED flow improvement) started in April 2009 (unplanned confounder). Demographics, clinical features, risk assessment and disposition; preferably prospective. Administrative datasets provided disposition outcomes, 4 months pre-/post-intervention. Follow up with partially blinded adjudications assessed for 45 day major adverse cardiac events (MACE). Before intervention, consecutive patients were enrolled with mixed prospective/retrospective data. After, sampling occurred whenever prospective data were collected., Results: Adjudicated patients were n = 1029 (14.2% MI, 14.9% MACE), 426 before, 603 after. EDLOS reduced 87 min (416-329; P < 0.001), similar to triage 2 patients without chest pain. Possibly, avoidable MACE occurred in five of 598 discharges (0.8%, CI 0.3-1.8%) with non-significant decreases (0.5%, CI 0.1-1.8%) post-intervention. Disposition changes included greater observation ward use (3.8-12.3%; P < 0.001), more discharges (47.4-52.9%, P = 0.002), less transfers (9.3-6.9%, P = 0.014) and less late inpatient discharge decisions (15.2-8.7%, P = 0.001)., Conclusion: Paired cardiac markers performed adequately for avoidable MACE, and disposition improved significantly. A confounding system change meant the reduced EDLOS (primary outcome) was unable to be associated with the intervention., (© 2016 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.)
- Published
- 2016
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46. Plasma Proprotein Convertase Subtilisin Kexin Type 9 as a Predictor of Carotid Atherosclerosis in Asymptomatic Adults.
- Author
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Chan DC, Pang J, McQuillan BM, Hung J, Beilby JP, Barrett PH, and Watts GF
- Subjects
- Adult, Aged, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Risk Factors, Sex Factors, Carotid Artery Diseases blood, Carotid Artery Diseases diagnostic imaging, Carotid Intima-Media Thickness, Proprotein Convertase 9 blood
- Abstract
Background: Atherosclerosis is a lipid-driven inflammatory disease of the arterial wall involving complex and multifactorial processes. Proprotein convertase subtilisin kexin type 9 (PCSK9) may play a role in the development of atherosclerosis., Methods: We investigated the associations between serum PCSK9 and carotid intima-medial wall thickness (IMT), a measure of subclinical atherosclerosis that predicts cardiovascular events, in 295 asymptomatic subjects from community. Carotid IMT was determined by high-resolution B-mode carotid ultrasonography and serum PCSK9 was measured by immunoassay., Results: In univariate analysis, serum PCSK9 concentration was positively (P<0.05 in all) associated with age (r=0.204), BMI (r=0.149), waist circumference (r=0.139), systolic blood pressures (r=0.116), glucose (r=0.211), insulin (r=0.178), HOMA score (r=0.195), plasma triglyceride (r=0.285), total cholesterol (r=0.241) and LDL-cholesterol concentrations (r=0.172). In multivariate regression including male gender, hypertension, smoking status, HOMA score, obesity, LDL-cholesterol, lipoprotein (a) or markers of inflammation, serum PCSK9 remained an independent predictor of mean carotid IMT (P<0.001)., Conclusions: These data suggest that serum levels of PCSK9 may contribute to increased risk of subclinical carotid atherosclerosis independent of conventional risk factors. Whether PCSK9 inhibition improves cardiovascular outcomes remains to be demonstrated in large, ongoing clinical trials., (Copyright © 2015 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.)
- Published
- 2016
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47. Trends in incidence and prevalence of hospitalization for atrial fibrillation and associated mortality in Western Australia, 1995-2010.
- Author
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Briffa T, Hung J, Knuiman M, McQuillan B, Chew DP, Eikelboom J, Hankey GJ, Teng TH, Nedkoff L, Weerasooriya R, Liu A, and Stobie P
- Subjects
- Adult, Aged, Aged, 80 and over, Female, Humans, Incidence, Male, Middle Aged, Mortality trends, Prevalence, Western Australia epidemiology, Atrial Fibrillation diagnosis, Atrial Fibrillation mortality, Hospitalization trends, Population Surveillance methods
- Abstract
Objective: Hospitalization for atrial fibrillation (AF) is a large and growing public health problem. We examined current trends in the incidence, prevalence, and associated mortality of first-ever hospitalization for AF., Methods: Linked hospital admission data were used to identify all Western Australia residents aged 35-84 years with prevalent AF and incident (first-ever) hospitalization for AF as a principal or secondary diagnosis during 1995-2010., Results: There were 57,552 incident hospitalizations, mean age 69.8 years, with 41.4% women. Over the calendar periods, age- and sex-standardized incidence of hospitalization for AF as any diagnosis declined annually by 1.1% (95% CI; 0.93, 1.29), while incident AF as a principal diagnosis increased annually by 1.2% (95% CI; 0.84, 1.50). Incident AF hospitalization was higher among men than women, and 15-fold higher in the 75-84 compared with 35-64 year age group. The age- and sex-standardized prevalence of AF increased annually by 2.0% (95% CI; 1.88, 2.03) over the same period. Comorbidity trends were mixed with diabetes and valvular heart disease increasing, and hypertension, coronary artery disease, heart failure, cerebrovascular disease, and chronic kidney disease decreasing. The 1-year all-cause mortality after incident AF hospitalization declined from 17.6% to 14.6% (trend P<0.001), with an adjusted hazard ratio of 0.86 (95% CI; 0.81, 0.91)., Conclusion: This contemporary study shows that incident AF hospitalization is not increasing except for AF as a principal diagnosis, while population prevalence of hospitalized AF has risen substantially. The high 1-year mortality following incident AF hospitalization has improved only modestly over the recent period., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)
- Published
- 2016
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48. Epidemiological and Mendelian Randomization Studies of Dihydrotestosterone and Estradiol and Leukocyte Telomere Length in Men.
- Author
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Yeap BB, Knuiman MW, Divitini ML, Hui J, Arscott GM, Handelsman DJ, McLennan SV, Twigg SM, McQuillan B, Hung J, and Beilby JP
- Subjects
- 3-Oxo-5-alpha-Steroid 4-Dehydrogenase genetics, Adolescent, Adult, Aged, Aged, 80 and over, Aging genetics, Aromatase genetics, Genetic Association Studies statistics & numerical data, Humans, Male, Membrane Proteins genetics, Mendelian Randomization Analysis, Middle Aged, Telomere metabolism, Western Australia epidemiology, Young Adult, Dihydrotestosterone blood, Estradiol blood, Leukocytes metabolism, Polymorphism, Single Nucleotide, Telomere Homeostasis genetics
- Abstract
Context: Advancing age is accompanied by an accumulation of ill health and shortening of chromosomal telomeres signifying biological aging. T is metabolized to DHT by 5α-reductase (SRD5A2) and to estradiol (E2) by aromatase (CYP19A1). Telomerase preserves telomeres, and T and E2 regulate telomerase expression and activity in vitro., Objective: The objective of the study was to establish whether circulating T or its metabolites, DHT or E2, and single-nucleotide polymorphisms in SRD5A2 or CYP19A1 associate with leucocyte telomere length (LTL) in men., Participants and Methods: Early-morning serum T, DHT, and E2 were assayed using mass spectrometry, and SRD5A2 and CYP19A1 single-nucleotide polymorphisms and LTL analyzed by PCR in 980 men from the Western Australian Busselton Health Survey who participated in the study. LTL was expressed as the T/S ratio., Results: Men were aged (mean ± SD) 53.7 ± 15.6 years. LTL decreased linearly with age, from the T/S ratio of 1.89 ± 0.41 at younger than 30 years to 1.50 ± 0.49 at 70 to younger than 80 years (r = -0.225, P < .0001). After adjustment for age, DHT and E2 were positively correlated with LTL (DHT, r = 0.069, P = .030; E2, r = 0.068, P = .034). The SRD5A2 rs9282858 polymorphism was associated with serum DHT but not with LTL. Three dominant alleles of CYP19A1 were each associated with lower serum E2 and shorter LTL: rs2899470 T (E2, 59.3 vs 68.6 pmol/L, P < .0001; T/S ratio, 1.54 vs 1.62, P = .045), rs10046 C (60.5 vs 68.1 pmol/L, P = .0005, 1.54 vs 1.62, P = .035), and rs700518 A (59.9 vs 68.9 pmol/L, P < .0001, 1.54 vs 1.63, P = .020). A single-copy haplotype C/T/I/A/T rs10046/rs2899470/rs11575899/rs700518/rs17703883 (52% prevalence) was associated with both lower E2 and shorter LTL., Conclusions: In men, serum DHT and E2 correlate with LTL independently of age. Aromatase gene polymorphisms include three dominant alleles that are associated with both lower serum E2 and shorter LTL. E2 influences telomere length in vivo, thus warranting further studies to examine whether hormonal interventions might slow biological aging in men.
- Published
- 2016
- Full Text
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49. Higher ferritin levels, but not serum iron or transferrin saturation, are associated with Type 2 diabetes mellitus in adult men and women free of genetic haemochromatosis.
- Author
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Yeap BB, Divitini ML, Gunton JE, Olynyk JK, Beilby JP, McQuillan B, Hung J, and Knuiman MW
- Subjects
- Adolescent, Adult, Aged, Aged, 80 and over, Blood Pressure, Cohort Studies, Cross-Sectional Studies, Female, Genotype, Hemochromatosis genetics, Humans, Insulin Resistance, Male, Middle Aged, Multivariate Analysis, Regression Analysis, Young Adult, Diabetes Mellitus, Type 2 blood, Ferritins blood, Iron blood, Iron Overload blood, Transferrin metabolism
- Abstract
Context: Iron overload predisposes to diabetes and higher ferritin levels have been associated with diabetes. However, it is unclear whether ferritin reflects differences in iron-related parameters between diabetic and nondiabetic persons. We examined associations of serum ferritin, iron and transferrin saturation with Type 2 diabetes in adults without genetic predisposition to iron overload., Design, Participants and Measurements: Cross-sectional analysis of community-dwelling men and women aged 17-97 years from the Busselton Health Survey, Western Australia. Men and women carrying genotypes associated with haemochromatosis (C282Y/C282Y or C282Y/H63D) were excluded. Serum ferritin, iron and transferrin saturation were assayed., Results: There were 1834 men (122 with diabetes, 6·6%) and 2351 women (141 with diabetes, 6%). In men, higher serum ferritin was associated with diabetes after adjusting for age, smoking, alcohol, cardiovascular history, body mass index (BMI), waist, blood pressure, lipids, C-reactive protein (CRP), adiponectin, alanine transaminase (ALT) and gamma-glutamyl transpeptidase (GGT) [odds ratio (OR): 1·29 per 1 unit increase log ferritin, 95% confidence interval (CI) = 1·01-1·65, P = 0·043]. In women, higher serum ferritin was associated with diabetes [fully adjusted OR: 1·31 per 1 unit increase log ferritin, 95% CI = 1·04-1·63, P = 0·020; 1·84 for tertile (T) 3 vs T1, 95% CI = 1·09-3·11]. Neither iron levels nor transferrin saturation were associated with diabetes risk in men or women. Higher ferritin was not associated with insulin resistance in nondiabetic adults., Conclusions: In adults, higher ferritin levels are independently associated with prevalent diabetes while iron and transferrin saturation are not. Ferritin is a robust biomarker for diabetes risk, but further investigation is needed to clarify whether this relationship is mediated via iron metabolism., (© 2014 John Wiley & Sons Ltd.)
- Published
- 2015
- Full Text
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