135 results on '"Le Manach, Yannick"'
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2. Bleeding Independently associated with Mortality after noncardiac Surgery (BIMS): an international prospective cohort study establishing diagnostic criteria and prognostic importance
- Author
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Roshanov, Pavel S., Eikelboom, John W., Sessler, Daniel I., Kearon, Clive, Guyatt, Gordon H., Crowther, Mark, Tandon, Vikas, Borges, Flavia Kessler, Lamy, Andre, Whitlock, Richard, Biccard, Bruce M., Szczeklik, Wojciech, Panju, Mohamed, Spence, Jessica, Garg, Amit X., McGillion, Michael, VanHelder, Tomas, Kavsak, Peter A., de Beer, Justin, Winemaker, Mitchell, Le Manach, Yannick, Sheth, Tej, Pinthus, Jehonathan H., Siegal, Deborah, Thabane, Lehana, Simunovic, Marko R.I., Mizera, Ryszard, Ribas, Sebastian, and Devereaux, Philip J.
- Published
- 2021
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3. Counterfactual clinical prediction models could help to infer individualized treatment effects in randomized controlled trials—An illustration with the International Stroke Trial
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Nguyen, Tri-Long, Collins, Gary S., Landais, Paul, and Le Manach, Yannick
- Published
- 2020
- Full Text
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4. Maternal and neonatal outcomes after caesarean delivery in the African Surgical Outcomes Study: a 7-day prospective observational cohort study
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Abadagan, Hippolyte, Abbas, N, Abdelatif, A Ibrahim, Abdoulaye, Traoré, Abd-rouf, A, Abduljalil, A, Abdulrahman, A, Abdurazig, S, Abokris, A, Abozaid, W, Abugassa, SOA, Abuhdema, F, Abujanah, SA, Abusamra, R, Abushnaf, A, Abusnina, SA, Abuzalout, TS, Ackermann, HM, Adamu, YB, Addanfour, A, Adeleke, DM, Adigun, TA, Adisa, AO, Adjignon, Sèhivè Valéry, Adu-Aryee, NA, Afolabi, BB, Agaba, AFX, Agaba, PKA, Aghadi, K, Agilla, H, Ahmed, B, Ahmed, El-Z, Ahmed, Al-J, Ahmed, M, Ahossi, Rene, Aji, SA, Akanyun, S, Akhideno, I, Akhter, M, Akinyemi, OA, Akkari, M, Akodjenou, Joseph, AL Samateh, AL, al Shams, ES, Alagbe-Briggs, OT, Alakkari, EA, Alalem, RB, Alashhab, M, Alatise, OI, Alatresh, A, Alayeb Alayeb, MSI, Albakosh, BA, Albert, F, Alberts, ANJD, Aldarrat, AD, Alfari, A, Alfetore, A, Algbali, M, Algddar, A, Algedar, HA, Alghafoud, IA, Alghazali, A, Alhajj, M, Alhendery Alhendery, A, Alhoty, FFH, Ali, A, Ali, YA, Alioune, Beye Seïdina, Alkassem, MA, Alkchr, MA, Alkesa, TS, Alkilani, A, Alkobty Alkobty, F, Allaye, Thomas, Alleesaib, SBM, Alli, A, Allopi, K, Allorto, NL, Almajbery, A, Almesmary, R, Almisslati, SHA, Almoraid, F, Alobeidi, H, Alomami, MA, Alphonsus, Christella S, Alqawi, OA, Alraheem, AA, Alsabri, SA, Alsayed, A, Alsellabi, B, Al-Serksi, M, Alshareef, MSA, Altagazi, AA, Aluvale, JS, Alwahedi, HW, Alzahra, EA, Alzarouk, MA, Al-Zubaidy, K, Amadou, M, Amadou, Maiga, Amanor-Boadu, Simbo D, Amer, Al-A, Amisi, BT, Amuthenu, MA, Anabah, TWA, Anani, Felix, Anderson, PGR, Andriamampionona, AGB, Andrianina, L, Anele, A, Angelin, R, Anjar, N, Antùnez, O, Antwi-Kusi, Akwasi, Anyanwu, LJC, Aribi, AA, Arowolo, OA, Arrey, O, Ashebir, Daniel Zemenfes, Assefa, SB, Assoum, Guy, Athanse, V, Athombo, JS, Atiku, M, Atito-Narh, E, Atomabe, Anatole, Attia, A, Aungraheeta, M, Aurélia, DMA, Ayandipo, OO, Ayebale, AET, Azzaidey, HMZ, Babajee, NB, Badi, HB, Badianga, EK, Baghni, RB, Bahta, MT, Bai, M, Baitchu, Y, Baloyi, AM, Bamuza, KA, Bamuza, MI, Bangure, L, Bankole, OB, Barongo, ML, Barow, MM, Basenero, Apollo, Bashiya, L, Basson, CH, Bechan, Sudha, Belhaj, S, Ben Mansour, MM, Benali, D, Benamour, ASB, Berhe, A, Bertie, JD, Bester, JJA, Bester, M, Bezuidenhout, JD, Bhagwan, K, Bhagwandass, DR, Bhat, KAP, Bhuiyan, MMZU, Biccard, Bruce M, Bigirimana, F, Bikuelo, CJ, Bilby, BE, Bingidimi, SS, Bischof, KE, Bishop, David G, Bitta, C, Bittaye, M, Biyase, Thuli, Blake, CA, Blignaut, E, Blignaut, F, BN Tanjong, BN, Bogoslovskiy, A, Boloko, PM, Boodhun, SKB, Bori, I, Boufas, F, Brand, M, Brouckaert, Nicholas T, Bruwer, JD, Buccimazza, I, Bula Bula, IM, Bulamba, Fred, Businge, BC, Bwambale, YB, Cacala, SRC, Cadersa, MA, Cairns, Chris, Carlos, F, Casey, ME, Castro, AC, Chabayanzara, ND, Chaibou, MS, Chaibva, TNO, Chakafa, NK, Chalo, C, Changfoot, C, Chari, MC, Chelbi, L, Chibanda, JT, Chifamba, HN, Chikh, N, Chikumba, E, Chimberengwa, P, Chirengwa, J, Chitungo, FM, Chiwanga, MC, Chokoe, MM, Chokwe, TM, Chrirangi, B, Christian, M, Church, B, Cisekedi, JC, Clegg-Lamptey, JN, Cloete, Estie, Coltman, Megan, Conradie, W, Constance, N, Coulibaly, Youssouf, Cronje, L, Da Silva, MA, Daddy, H, Dahim, L, Daliri, D, Dambaki, MS, Dasrath, A, Davids, JG, Davies, Gareth L, De Lange, JT, de Wet, JB, Dedekind, B, Degaulle, MA, Dehal, V, Deka, PD, Delinikaytis, S, Desalu, IS, Dewanou, Hubert, Deye, MB Moussa, Dhege, C, Diale, BSG, Dibwe, DF, Diedericks, BJS, Dippenaar, JM, Dippenaar, L, Diyoyo, MP, Djessouho, Edith, Dlamini, SN, Dodiyi-Manuel, A, Dokolwana, BA, Domoyyeri, DP, Drummond, Leanne W, du Plessis, DE, du Plessis, WM, du Preez, LJ, Dube, K, Dube, NZ, Dullab, KD, Duvenhage, R, Echem, RC, Edaigbini, SA, Egote, AK, Ehouni, A, Ekwen, G, Ekwunife, NC, El Hensheri, M, Elfaghi, IE, Elfagieh, MA, Elfallah, S, Elfiky, Mahmoud, Elgelany, S, Elghallal, AM, Elghandouri, MG, Elghazal, ZS, Elghobashy, AM, Elharati, FT, Elkhogia, Abdulaziz M, Elkhwildi, RM, Ellis, S, Elmadani, L, Elmadany, HB, Elmehdawi, H, Elmgadmi, A, Eloi, H, Elrafifi, D, Elsaadi, G, Elsaity, RB, Elshikhy, A, Eltaguri, M, Elwerfelli, A, Elyasir, IE, Elzoway, AZ, Elzufri, AM, Enendu, EO, Enicker, BC, Enwerem, EO, Esayas, R, Eshtiwi, M, Eshwehdi, AA, Esterhuizen, JL, Esterhuizen, Tonya M, Etuk, EB, Eurayet, O, Eyelade, OR, Fanjandrainy, RF, Fanou, Lionelle, Farina, Z, Fawzy, Maher, Feituri, A, Fernandes, NL, Ford, LM, Forget, Patrice, François, T, Freeman, T, Freeman, YBM, Gacii, VM, Gadi, B, Gagara, M, Gakenia, A, Gallou, PD, Gama, GGN, Gamal, MG, Gandy, YG, Ganesh, A, Gangaly, Diallo, Garcia, M, Gatheru, AP, Gaya, SSD, Gbéhadé, Oswald, Gerbel, G, Ghnain, A, Gigabhoy, R, Giles, DG, Girmaye, GT, Gitau, S, Githae, B, Gitta, Said, Gobin, Veekash, Goga, Riaz, Gomati, AAG, Gonzalez, ME, Gopall, J, Gordon, Christina Salmina, Gorelyk, O, Gova, M, Govender, K, Govender, P, Govender, S, Govindasamy, V, Green-Harris, JTK, Greenwood, MB, Grey-Johnson, SV, Grobbelaar, Mariette, Groenewald, MA, Grünewald, KK, Guegni, Ambroise, Guenane, M, Gueye, S, Guezo, Marius, Gunguwo, T, Gweder, MG, Gwila, M, Habimana, L, Hadecon, Rodrigue, Hadia, E, Hamadi, L, Hammouda, M, Hampton, MI, Hanta, R, Hardcastle, Tim C, Hariniaina, JA, Hariparsad, S, Harissou, AH, Harrichandparsad, R, Hasan, SHA, Hashmi, HB, Hayes, MP, Hdud, A, Hebli, SH, Heerah, HMSN, Hersi, S, Hery, AH, Hewitt-Smith, Adam, Hlako, TC, Hodges, SCH, Hodgson, Richard Eric, Hokoma, M, Holder, H, Holford, EB, Horugavye, E, Houston, C, Hove, M, Hugo, D, Human, CM, Hurri, H, Huwidi, O, Ibrahim, AI, Ibrahim, Traoré, Idowu, OK, Igaga, IE, Igenge, John, Ihezie, O, Ikandi, K, Ike, IAR, Ikuku, JJN, Ilbarasi, MN, Ilunga, IBB, Ilunga, JPM, Imbangu, NAV, Imessaoudene, Z, Imposo, DH, Iraya, AM, Isaacs, M, Isiguzo, M, Issoufou, A, Izquirdo, P, Jaber, A, Jaganath, UV, Jallow, CS, Jamabo, S, Jamal, ZS, Janneh, L, Jannetjies, MJ, Jasim, I, Jaworska, Megan AJ, Jay Narain, S, Jermi, K, Jimoh, R, Jithoo, S, Johnson, M, Joomye, S, Judicael, RM, Judicaël, M, Juwid, A, Jwambi, LP, Kabango, R, Kabangu, JK, Kabatoro, DK, Kabongo, AN, Kabongo, K, Kabongo, LT, Kabongo, MD, Kady, N, Kafu, S, Kaggya, M, Kaholongo, BNK, Kairuki, PCK, Kakololo, SI, Kakudji, K, Kalisa, Amina, Kalisa, R, Kalufwelu, MR, Kalume, S, Kamanda, RJ, Kangili, MK, Kanoun, H, Kapesa, Kapp, P, Karanja, JK, Karar, M, Kariuki, K, Kaseke, K, Kashuupulwa, PNK, Kasongo, KJP, Kassa, SK, Kateregga, GK, Kathrada, MIS, Katompwa, PM, Katsukunya, L, Kavuma, KAM, Khalfallah, Khamajeet, A, Khetrish, SB, Kibandwa, Kibochi, W, Kilembe, AM, Kintu, AK, Kipng'etich, B, Kiprop, B, Kissoon, VMK, Kisten, Theroshnie K, Kiwanuka, JK, Kluyts, Hyla-Louise, Knox, MEK, Koledale, AK, Koller, VL, Kolotsi, MA, Kongolo, M, Konwuoh, ND, Koperski, WJ, Koraz, MYK, Kornilov, AA, Koto, M Zach, Kransingh, Samantha, Krick, D, Kruger, S, Kruse, C, Kuhn, W, Kuhn, WP, Kukembila, AM, Kule, KL, Kumar, M, Kusel, Belinda S, Kusweje, VK, Kuteesa, KJ, Kutor, YY, Labib, MA, Laksari, M, Lanos, F, Lawal, TA, Le Manach, Yannick, Lee, C, Lekoloane, RM, Lelo, SN, Lerutla, B, Lerutla, MT, Levin, AI, Likongo, TB, Limbajee, ML, Linyama, DM, Lionnet, C, Liwani, MM, Loots, E, Lopez, A Garrido, Lubamba, CLC, Lumbala, KF, Lumbamba, AJM, Lumona, John, Lushima, RF, Luthuli, L, Luweesi, HL, Lyimo, TSK, Maakamedi, HM, Mabaso, BM, Mabina, M, Maboya, ME, Macharia, I, Macheka, AM, Machowski, AZ, Madiba, Thandinkosi E, Madsen, ASM, Madzimbamuto, Farai, Madzivhe, LJ, Mafafo, SC, Maghrabi, M, Mahamane, Diango Djibo, Maharaj, A, Maharaj, AD, Mahmud, MR, Mahoko, M, Mahomedy, NA, Mahomva, O, Mahureva, TM, Maila, RK, Maimane, DM, Maimbo, M, Maina, SN, Maiwald, Dela A, Maiyalagan, MD, Majola, N, Makgofa, N, Makhanya, V, Makhaye, WP, Makhlouf, NM, Makhoba, S, Makopa, EK, Makori, O, Makupe, Alex M, Makwela, MA, Malefo, ME, Malongwe, SM, Maluleke, DM, Maluleke, MR, Mamadou, K Touré, Mamaleka, MP, Mampangula, Y, Mamy, RM, Mananjara, MNR, Mandarry, MTM, Mangoo, DM, Manirimbere, C, Manneh, A, Mansour, A, Mansour, I, Manvinder, M, Manyere, DV, Manzini, VT, Manzombi, JK, Mapanda, PM, Marais, LC, Maranga, O, Maritz, JPB, Mariwa, FK, Masela, RS, Mashamba, MM, Mashava, Doreen M, Mashile, MV, Mashoko, E, Masia, OR, Masipa, JN, Masiyambiri, ATM, Matenchi, MW, Mathangani, W, Mathe, RC, Matola, Christopher Y, Matondo, PM, Matos-Puig, R, Matoug, FFH, Matubatuba, JT, Mavesere, HP, Mavhungu, R, Maweni, S, Mawire, CJM, Mawisa, T, Mayeza, S, Mbadi, R, Mbayabu, M, Mbewe, N, Mbombo, WD, Mbuyi, T, Mbuyi, WMS, Mbuyisa, MW, Mbwele, Bernard, Mehyaoui, RM, Menkiti, ID, Mesarieki, LVM, Metali, A, Mewanou, Serge, Mgonja, L, Mgoqo, N, Mhatu, S, Mhlari, TM, Miima, S, Milod, IM, Minani, P, Mitema, F, Mlotshwa, A, Mmasi, JE, Mniki, T, Mofikoya, BO, Mogale, JO, Mohamed, A, Mohamed, S, Mohamed, TS, Mohamed, AM, Mohamed, P, Mohammed, I, Mohammed, FAM, Mohammed, M, Mohammed, NM, Mohlala, MP, Mokretar, R, Molokoane, FM, Mongwe, KN, Montenegro, L, Montwedi, OD, Moodie, QK, Moopanar, M, Morapedi, M, Morulana, TG, Moses, VL, Mossy, P, Mostafa, H, Motilall, SR, Motloutsi, SP, Moussa, Kanté, Moutari, M, Moyo, OM, Mphephu, PE, Mrara, Busi, Msadabwe, C, Mtongwe, VM, Mubeya, FK, Muchiri, K, Mugambi, J, Muguti, GIM, Muhammad, AB, Mukama, IF, Mukenga, MM, Mukinda, FK, Mukuna, PM, Mungherera, ARW, Munlemvo, Dolly M, Munyaradzi, TW, Munyika, AA, Muriithi, JM, Muroonga, MP, Murray, R, Mushangwe, VK, Mushaninga, M, Musiba, VEM, Musowoya, JM, Mutahi, S, Mutasiigwa, MGH, Mutizira, G, Muturi, A, Muzenda, T, Mvwala, KR, Mvwama, NM, Mwale, A, Mwaluka, CN, Mwamba, JD, Mwanga, HAM, Mwangi, CM, Mwansa, S, Mwenda, V, Mwepu, IM, Mwiti, TM, Mzezewa, SZ, Nabela, L, Nabukenya, MTN, Nabulindo, SM, Naicker, K, Naidoo, D, Naidoo, L, Naidoo, LC, Naidoo, N, Naidoo, R, Naidoo, RD, Naidoo, S, Naidoo, TD, Naidu, TK, Najat, NZ, Najm, Y, Nakandungile, F, Nakangombe, P, Namata, CN, Namegabe, ES, Nansook, A, Nansubuga, NP, Nantulu, C, Nascimento, Rodrigue, Naude, GT, Nchimunya, H, Ndaie, MA, Ndarukwa, PN, Ndasi, Henry, Ndayisaba, Gabriel, Ndegwa, D, Ndikumana, R, Ndonga, Andrew KN, Ndung'u, C, Neil, MC, Nel, MS, Neluheni, EV, Nesengani, DS, Nesengani, NT, Netshimboni, LE, Ngalala, AM, Ngari, BM, Ngari, NBM, Ngatia, E, Ngcobo, GK, Ngcobo, TS, Ngorora, D, Ngouane, D, Ngugi, K, Ngumi, Zipporah WW, Nibe, Z, Ninise, E, Niyondiko, JC, Njenga, PW, Njenga, MN, Njoroge, M, Njoroge, S, Njuguna, W, Njuki, PN, Nkesha, T, Nkuebe, TN, Nkuliyingoma, NP, Nkunjana, M, Nkwabi, Ernest, Nkwine, RN, Nnaji, C, Notoane, I, Nsalamba, Shaaban, Ntlhe, LM, Ntoto, C, Ntueba, B, Nyassi, MT, Nyatela-Akinrinmade, Z, Nyawanda, HO, Nyokabi, NN, Nziene, VN, Obadiah, S, Ochieng, OJP, Odia, PK, Oduor, OEO, Ogboli-Nwasor, EO, Ogendo, SWO, Ogunbode, O, Ogundiran, TO, Ogutu, O, Ojewola, RW, Ojujo, M, Ojuka, DO, Okelo, OS, Okiya, S, Okonu, N, Olang, PR, Omigbodun, Akinyinka O, Omoding, S, Omoshoro-Jones, J, Onyango, R, Onyegbule, A, Orjiako, O, Osazuwa, MO, Oscar, Kpatinvo, Osinaike, BB, Osinowo, AO, Othin, OM, Otman, FFH, Otokwala, J, Ouanes, F, Oumar, Ongoïba, Ousseini, AO, Padayachee, S, Pahlana, SM, Pansegrouw, J, Paruk, FP, Patel, MB, Patel-Mujajati, Ushmaben, Patience, AP, Pearse, Rupert M, Pembe, JD, Pengemale, GN, Perez, N, Perez, MF Aguilera, Peter, A Mallier, Phaff, M, Pheeha, RM, Pienaar, BH, Pillay, V, Pilusa, KA, Pochana, MP, Polishchuk, O, Porrill, Owen S, Post, EF, Prosper, A, Pupyshev, M, Rabemazava, A, Rabiou, MS, Rademan, L, Rademeyer, M, Raherison, RAR, Rajah, FR, Rajcoomar, MSR, Rakhda, Z, Rakotoarijaona, AHR, Rakotoarisoa, AHN, Rakotoarison, Sylvia R, Rakotoarison, RR, Rakotoniaina, François, Ramadan, L, Ramananasoa, MLR, Rambau, M, Ramchurn, TPR, Ramilson, HE, Ramjee, Rajesh J, Ramnarain, H, Ramos, R, Rampai, TJ, Ramphal, SR, Ramsamy, T, Ramuntshi, R, Randolph, R, Randriambololona, DMA, Ras, WAP, Rasolondraibe, RAF, Rasolonjatovo, JDLC, Rautenbach, RM, Ray, S, Rayne, Sarah R, Razanakoto, FAR, Reddy, SR, Reed, Anthony R, Rian, JR, Rija, FR, Rink, B, Robelie, AT, Roberts, CA, Rocher, AGL, Rocher, S, Rodseth, Reitze N, Rois, I, Rois, W, Rokhsi, S, Roos, J, Rorke, Nicolette F, Roura, H, Rousseau, FJ, Rousseau, N, Royas, L, Roytowski, D, Rungan, Devan, Rwehumbiza, SSR, Ryabchiy, BB, Ryndine, V, Saaiman, CR, Sabwa, HK, Sadat, S, Saed, SS, Salaheddin, E, Salaou, H, Saleh, M, Salisu-Kabara, HM, Sama, Hamza Doles, Samateh, Ahmadou L, Sam-Awortwi (Jnr), W, Samuel, N, Sanduku, DK, Sani, Chaibou M, Sanyang, LN, Sarah, HN, Sarkin-Pawa, A, Sathiram, R, Saurombe, T, Schutte, H, Sebei, MP, Sedekounou, MD, Segooa, MP, Semenya, EM, Semo, BO, Sendagire, CS, Senoga, SA, Senusi, FS, Serdyn, T, Seshibe, MD, Shah, GB, Shamamba, R, Shambare, CS, Shangase, TN, Shanin, SH, Shefren, IE, Sheshe, AA, Shittu, OB, Shkirban, AS, Sholadoye, T, Shubba, A, Sigcu, N, Sihope, SE, Sikazwe, DS, Sikombe, BS, Simaga Abdoul, K, Simo, WAG, Singata, K, Singh, AS, Singh, S, Singh, Usha, Sinoamadi, V, Sipuka, N, Sithole, NLM, Sitima, S, Skinner, David Lee, Skinner, GC, Smith, OI, Smits, CAG, Sofia, MSI, Sogoba, Gaoussou, Sohoub, A, Sookun, SS, Sosinska, O, Souhe, Rosalie, Souley, G, Souleymane, Thiam, Spicer, JM, Spijkerman, Sandra, Steinhaus, H, Steyn, A, Steyn, G, Steyn, HC, Stoltenkamp, Heidi L, Stroyer, S, Swaleh, A, Swayeb, E, Szpytko, AJ, Taiwo, NA, Tarhuni, A, Tarloff, D, Tchaou, Blaise, Tchegnonsi, Charles, Tchoupa, M, Teeka, MO, Thakoor, B, Theunissen, MM, Thomas, BP, Thomas, MB, Thotharam, A, Tobiko, O, Torborg, AM, Tshisekedi, SM, Tshisola, SK, Tshitangano, R, Tshivhula, F, Tshuma, HT, Tumukunde, Janat, Tun, M, Udo, IA, Uhuebor, DI, Umeh, KU, Usenbo, AO, Uwiteyimbabazi, JdD, Van der Merwe, DJ, van der Merwe, FH, van der Walt, JE, van Dyk, Dominique, Van Dyk, JG, van Niekerk, JJS, van Wyk, S, van Zyl, HA, Veerasamy, B, Venter, PJ, Vermeulen, AJ, Villarreal, R, Visser, J, Visser, L, Voigt, M, von Rahden, Richard P, Wafa, A, Wafula, A, Wambugu, PK, Waryoba, P, Waweru, EN, Weideman, M, Wise, Robert D, Wynne, EE, Yahya, AI, Yahya, AA, Yahya, R, Yakubu, Y, Yanga, JJ, Yangazov, YM, Yousef, O, Yousef, G, Youssouf, Coulibaly, Yunus, AA, Yusuf, AS, Zeiton, AZ, Zentuti, HZ, Zepharine, Henry, Zerihun, AB, Zhou, S, Zidan, A, Zié, Sanogo Zimogo, Zinyemba, CZ, Zo, A, Zomahoun, Lidwine, Zoobei, NZ, Zoumenou, Eugene, Zubia, NZ, Bishop, David, Dyer, Robert A, Maswime, Salome, Tumukunde, Janat T, Madzimbamuto, Farai D, Ndonga, Andrew K N, Ngumi, Zipporah W W, and Mehyaoui, Ryad
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- 2019
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5. A multicentre observational study on management of general anaesthesia in elderly patients at high-risk of postoperative adverse outcomes
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Bruder, N., Vaisse, C., Bechis, C., Bernard, L., Leone, M., Poirier, M., Vincent, A., Abdelkrim, N., Paugam, C., Lion, F., Montravers, P., Langeron, O., Raux, M., Baussier, M., Xu, K., Bart, F., Dagois, S., Plaud, B., Rabuel, C., Roland, E., Biais, M., Nouette-Gaulain, K., Cabart, A., Hanouz, J.L., Lambert, C., Godet, T., Thibault, S., Bouhemad, B., Chambade, E., Bouzat, P., Garot, M., Lebuffe, G., Lallemant, F., Lemery, C., Tavernier, B., de Jong, A., Jaber, S., Verzilli, D., Delannoy, M., Meistelman, C., Carles, M., Tran, L., Bertran, S., Cuvillon, P., Ripart, J., Simon-Pene, S., Boisson, M., Debaene, B., Beloeil, H., Godet, G., Collange, O., Mertes, P.M., Diemunsch, P., Joganah, D., Oehlkern, L., Baulieu, M., Beauchesne, B., Beraud, A.M., Berthier-Berrada, S., Bien, J.Y., Dupont, G., Gavory, J., Lambert, P., Lanoiselée, J., Zufferey, P., Ferré, F., Martin, C., Minville, V., Planté, B., Baffeleuf, B., Ben Abdelkarim, M., David, J.S., Incagnoli, P., Khaled, M., Laplace, M.C., Lefevre, M., Piriou, V., Aubrun, F., Cero, V., Delsuc, C., Faulcon, C., Meuret, P., Rimmelé, T., Truc, C., Molliex, Serge, Passot, Sylvie, Morel, Jerome, Futier, Emmanuel, Lefrant, Jean Yves, Constantin, Jean Michel, Le Manach, Yannick, and Pereira, Bruno
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- 2019
- Full Text
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6. The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications
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Abadagan, Hippolyte, Abbas, N., Abdelatif, A. 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- 2018
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- View/download PDF
7. Postoperative Remote Automated Monitoring: Need for and State of the Science
- Author
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McGillion, Michael H., Duceppe, Emmanuelle, Allan, Katherine, Marcucci, Maura, Yang, Stephen, Johnson, Ana P., Ross-Howe, Sara, Peter, Elizabeth, Scott, Ted, Ouellette, Carley, Henry, Shaunattonie, Le Manach, Yannick, Paré, Guillaume, Downey, Bernice, Carroll, Sandra L., Mills, Joseph, Turner, Andrew, Clyne, Wendy, Dvirnik, Nazari, Mierdel, Sandra, Poole, Laurie, Nelson, Matthew, Harvey, Valerie, Good, Amber, Pettit, Shirley, Sanchez, Karla, Harsha, Prathiba, Mohajer, David, Ponnambalam, Sem, Bhavnani, Sanjeev, Lamy, Andre, Whitlock, Richard, and Devereaux, P.J.
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- 2018
- Full Text
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8. Magnitude and direction of missing confounders had different consequences on treatment effect estimation in propensity score analysis
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Nguyen, Tri-Long, Collins, Gary S., Spence, Jessica, Fontaine, Charles, Daurès, Jean-Pierre, Devereaux, Philip J., Landais, Paul, and Le Manach, Yannick
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- 2017
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9. Simple randomization did not protect against bias in smaller trials
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Nguyen, Tri-Long, Collins, Gary S., Lamy, André, Devereaux, Philip J., Daurès, Jean-Pierre, Landais, Paul, and Le Manach, Yannick
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- 2017
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10. Tranexamic acid and rosuvastatin in patients at risk of cardiovascular events after noncardiac surgery: a pilot of the POISE-3 randomized controlled trial
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Marcucci, Maura, Duceppe, Emmanuelle, Le Manach, Yannick, Kearon, Clive, Eikelboom, John W., Pohl, Kayla, Vincent, Jessica, Darvish-Kazem, Saeed, Srinathan, Sadeesh K., Neary, John D. D., Parlow, Joel L., Kurz, Andrea, Gross, Peter L., Mrkobrada, Marko, Balasubramanian, Kumar, Sessler, Daniel I., and Devereaux, P. J.
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- 2020
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11. Long-term survival of elderly patients after intensive care unit admission for acute respiratory infection: a population-based, propensity score-matched cohort study
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Guillon, Antoine, Hermetet, Coralie, Barker, Kimberly A., Jouan, Youenn, Gaborit, Christophe, Ehrmann, Stephan, Le Manach, Yannick, Dequin, Pierre-François, and Grammatico-Guillon, Leslie
- Published
- 2020
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12. Improvement in staff behavior during surgical procedures to prevent post-operative complications (ARIBO2): study protocol for a cluster randomised trial
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Birgand, Gabriel, Haudebourg, Thomas, Grammatico-Guillon, Leslie, Ferrand, Léa, Moret, Leila, Gouin, François, Mauduit, Nicolas, Leux, Christophe, Le Manach, Yannick, Lepelletier, Didier, Tavernier, Elsa, Lucet, Jean-Christophe, and Giraudeau, Bruno
- Published
- 2019
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13. The Prognostic Value of Pre-Operative and Post-Operative B-Type Natriuretic Peptides in Patients Undergoing Noncardiac Surgery: B-Type Natriuretic Peptide and N-Terminal Fragment of Pro-B-Type Natriuretic Peptide: A Systematic Review and Individual Patient Data Meta-Analysis
- Author
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Rodseth, Reitze N., Biccard, Bruce M., Le Manach, Yannick, Sessler, Daniel I., Lurati Buse, Giovana A., Thabane, Lehana, Schutt, Robert C., Bolliger, Daniel, Cagini, Lucio, Cardinale, Daniela, Chong, Carol P.W., Chu, Rong, Cnotliwy, Miłosław, Di Somma, Salvatore, Fahrner, René, Lim, Wen Kwang, Mahla, Elisabeth, Manikandan, Ramaswamy, Puma, Francesco, Pyun, Wook B., Radović, Milan, Rajagopalan, Sriram, Suttie, Stuart, Vanniyasingam, Thuvaraha, van Gaal, William J., Waliszek, Marek, and Devereaux, P.J.
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- 2014
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14. Comparison of the ability of double‐robust estimators to correct bias in propensity score matching analysis. A Monte Carlo simulation study
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Nguyen, Tri‐Long, Collins, Gary S., Spence, Jessica, Devereaux, Philip J., Daurès, Jean‐Pierre, Landais, Paul, and Le Manach, Yannick
- Published
- 2017
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15. Statistical Inefficiencies in the Development of a Prediction Model
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Collins, Gary S. and Le Manach, Yannick
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- 2017
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16. Randomized Evidence for Reduction of Perioperative Mortality
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Landoni, Giovanni, Rodseth, Reitze N., Santini, Francesco, Ponschab, Martin, Ruggeri, Laura, Székely, Andrea, Pasero, Daniela, Augoustides, John G., Del Sarto, Paolo A., Krzych, Lukasz J., Corcione, Antonio, Slullitel, Alexandre, Cabrini, Luca, Le Manach, Yannick, Almeida, Rui M.S., Bignami, Elena, Biondi-Zoccai, Giuseppe, Bove, Tiziana, Caramelli, Fabio, Cariello, Claudia, Carpanese, Anna, Clarizia, Luciano, Comis, Marco, Conte, Massimiliano, Covello, Remo D., De Santis, Vincenzo, Feltracco, Paolo, Giordano, Gianbeppe, Pittarello, Demetrio, Gottin, Leonardo, Guarracino, Fabio, Morelli, Andrea, Musu, Mario, Pala, Giovanni, Pasin, Laura, Pezzoli, Ivana, Paternoster, Gianluca, Remedi, Rossella, Roasio, Agostino, Zucchetti, Mariachiara, Petrini, Flavia, Finco, Gabriele, Ranieri, Marco, and Zangrillo, Alberto
- Published
- 2012
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17. The motor component does not convey all the mortality prediction capacity of the Glasgow Coma Scale in trauma patients
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Vivien, Benoît, Yeguiayan, Jean-Michel, Le Manach, Yannick, Bonithon-Kopp, Claire, Mirek, Sébastien, Garrigue, Delphine, Freysz, Marc, and Riou, Bruno
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- 2012
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18. Association between pre-operative statin use and major cardiovascular complications among patients undergoing non-cardiac surgery: the VISION study
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Berwanger, Otavio, Le Manach, Yannick, Suzumura, Erica Aranha, Biccard, Bruce, Srinathan, Sadeesh K., Szczeklik, Wojciech, Santo, Jose A. Espirito, Santucci, Eliana, Cavalcanti, Alexandre B., Archbold, R. Andrew, and Devereaux, P. J.
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- 2016
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19. Large Study But Weak Test of Internal Validation: Comment on the Article by Solomon et al
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Collins, Gary S. and Le Manach, Yannick
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- 2015
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20. Statins: A new pharmacological agent for free flap surgery?
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Karsenti, Guillaume, Le Manach, Yannick, Bouvier, Stéphanie, Chaine, André, and Bertolus, Chloé
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- 2010
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21. Perioperative Statin Therapy Is Associated With a Significant and Dose-Dependent Reduction of Adverse Cardiovascular Outcomes After Coronary Artery Bypass Graft Surgery
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Ouattara, Alexandre, Benhaoua, Hamina, Le Manach, Yannick, Mabrouk-Zerguini, Nejma, Itani, Omar, Osman, Amer, Landi, Marc, Riou, Bruno, and Coriat, Pierre
- Published
- 2009
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22. Analytical comparison of the new point-of-care troponin T immunoassay on AQT90Flex® analyzer (Radiometer) and the high-sensitivity troponin T immunoassay on ModularE170® (Roche Diagnostics)
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Monneret, Denis, Abbes, Rachel Ahmed Ben, Omarjee, Riyadh, Devilliers, Catherine, Le Manach, Yannick, Raux, Mathieu, Coriat, Pierre, Imbert-Bismut, Françoise, and Bonnefont-Rousselot, Dominique
- Published
- 2014
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23. In vivo accuracy of two intraparenchymal intracranial pressure monitors
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Lescot, Thomas, Reina, Vincent, Le Manach, Yannick, Boroli, Filippo, Chauvet, Dorian, Boch, Anne-Laure, and Puybasset, Louis
- Published
- 2011
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24. Clonidine in Patients Undergoing Noncardiac Surgery
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Devereaux, P. J., Sessler, Daniel I., Leslie, Kate, Kurz, Andrea, Mrkobrada, Marko, Alonso-Coello, Pablo, Villar, Juan Carlos, Sigamani, Alben, Biccard, Bruce M., Meyhoff, Christian S., Parlow, Joel L., Guyatt, Gordon, Robinson, Andrea, Garg, Amit X., Rodseth, Reitze N., Botto, Fernando, Buse, Giovanna Lurati, Xavier, Denis, Chan, Matthew T.V., Tiboni, Maria, Cook, Deborah, Kumar, Priya A., Forget, Patrice, Malaga, German, Fleischmann, Edith, Amir, Mohammed, Eikelboom, John, Mizera, Richard, Torres, David, Wang, C. Y., VanHelder, Tomas, Paniagua, Pilar, Berwanger, Otavio, Srinathan, Sadeesh, Graham, Michelle, Pasin, Laura, Le Manach, Yannick, Gao, Peggy, Pogue, Janice, Whitlock, Richard, Lamy, André, Kearon, Clive, Chow, Clara, Pettit, Shirley, Chrolavicius, Susan, and Yusuf, Salim
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- 2014
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25. Aspirin in Patients Undergoing Noncardiac Surgery
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Devereaux, P. J., Mrkobrada, Marko, Sessler, Daniel I., Leslie, Kate, Alonso-Coello, Pablo, Kurz, Andrea, Villar, Juan Carlos, Sigamani, Alben, Biccard, Bruce M., Meyhoff, Christian S., Parlow, Joel L., Guyatt, Gordon, Robinson, Andrea, Garg, Amit X., Rodseth, Reitze N., Botto, Fernando, Buse, Giovanna Lurati, Xavier, Denis, Chan, Matthew T.V., Tiboni, Maria, Cook, Deborah, Kumar, Priya A., Forget, Patrice, Malaga, German, Fleischmann, Edith, Amir, Mohammed, Eikelboom, John, Mizera, Richard, Torres, David, Wang, C. Y., VanHelder, Tomas, Paniagua, Pilar, Berwanger, Otavio, Srinathan, Sadeesh, Graham, Michelle, Pasin, Laura, Le Manach, Yannick, Gao, Peggy, Pogue, Janice, Whitlock, Richard, Lamy, André, Kearon, Clive, Baigent, Colin, Chow, Clara, Pettit, Shirley, Chrolavicius, Susan, and Yusuf, Salim
- Published
- 2014
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26. Combined measurements of N-terminal pro-brain natriuretic peptide and cardiac troponins in potential organ donors
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Nicolas-Robin, Armelle, Salvi, Nadège, Medimagh, Sassi, Amour, Julien, Le Manach, Yannick, Coriat, Pierre, Riou, Bruno, and Langeron, Olivier
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- 2007
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27. Variations in pulse oximetry plethysmographic waveform amplitude induced by passive leg raising in spontaneously breathing volunteers
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Delerme, Samuel, Renault, Robin, Le Manach, Yannick, Lvovschi, Virginie, Bendahou, Mouhssine, Riou, Bruno, and Ray, Patrick
- Published
- 2007
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28. Comparing treatment effects between propensity scores and randomized controlled trials: improving conduct and reporting
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Collins, Gary S. and Le Manach, Yannick
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- 2012
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29. Impact of aspirin with or without clopidogrel on postoperative bleeding and blood transfusion in coronary surgical patients treated prophylactically with a low-dose of aprotinin
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Ouattara, Alexandre, Bouzguenda, Hassine, Le Manach, Yannick, Léger, Philippe, Mercadier, Anne, Leprince, Pascal, Bonnet, Nicolas, Montalescot, Gilles, Riou, Bruno, and Coriat, Pierre
- Published
- 2007
30. Evaluation of Biomarkers in Critical Care and Perioperative Medicine: A Clinician’s Overview of Traditional Statistical Methods and Machine Learning Algorithms.
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Soussi, Sabri, Collins, Gary S., Jüni, Peter, Mebazaa, Alexandre, Gayat, Etienne, and Le Manach, Yannick
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- 2021
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31. Of Railroads and Roller Coasters: Considerations for Perioperative Blood Pressure Management?
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Le Manach, Yannick, Meyhoff, Christian S., Collins, Gary S., Aasvang, Eske K., and London, Martin J.
- Published
- 2020
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32. Improvement in staff behavior during surgical procedures to prevent post-operative complications (ARIBO2): study protocol for a cluster randomised trial.
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Birgand, Gabriel, Haudebourg, Thomas, Grammatico-Guillon, Leslie, Ferrand, Léa, Moret, Leila, Gouin, François, Mauduit, Nicolas, Leux, Christophe, Le Manach, Yannick, Lepelletier, Didier, Tavernier, Elsa, Lucet, Jean-Christophe, and Giraudeau, Bruno
- Subjects
HOSPITAL personnel attitudes ,SURGICAL complications ,SURGICAL site infections ,PATIENT safety ,OPERATIVE surgery ,ORTHOPEDIC surgery ,NOISE - Abstract
Background: Inappropriate staff behaviour during surgical procedures may disrupt the surgical performance and compromise patient safety. We developed an innovative monitoring and feedback system combined with an adaptive approach to optimise staff behaviour intraoperatively and prevent post-operative complications (POC) in orthopaedic surgery.Methods/design: This protocol describes a parallel-group, cluster randomised, controlled trial with orthopaedic centre as the unit of randomisation. The intervention period will last 6 months and will be based on the monitoring of two surrogates of staff behaviour: the frequency of doors opening and the level of noise. Both will be collected from incision to wound closure, using wireless sensors and sonometers, and recorded and analysed on a dedicated platform (Livepulse®). Staff from centres randomised to the intervention arm will be informed in real time on their own data through an interactive dashboard available in each operating room (OR), and a posteriori for hip and knee replacement POC. Aggregated data from all centres will also be displayed for benchmarking. A lean method will be applied in each centre by a local multidisciplinary team to analyse baseline situations, determine the target condition, analyse the root cause(s), and take countermeasures. The education and awareness of participants on the impact of their behaviour on patient safety will assist the quality improvement process. The control centres will be blinded to monitoring data and quality improvement approaches. The primary outcome will be any POC occurring during the 30 days post operation. We will evaluate this outcome using local and national routinely collected data from hospital discharge and disease databases. Thirty orthopaedic centres will be randomised for a total of 9945 hip and knee replacement surgical procedures.Discussion: The field of human factors and behaviour in the OR seems to offer potential room for improvement. An intervention providing goal-setting, monitoring, feedback and action planning may reduce the traffic flow and interruptions/distractions of the surgical team during procedures, preventing subsequent POCs. The results of this trial will provide important data on the impact of OR staff behaviour on patient safety, and promote best practice during surgical procedures.Trial Registration: ClinicalTrials.gov, NCT03158181 . [ABSTRACT FROM AUTHOR]- Published
- 2019
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33. The Fragility and Reliability of Conclusions of Anesthesia and Critical Care Randomized Trials With Statistically Significant Findings: A Systematic Review.
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Grolleau, François, Collins, Gary S., Smarandache, Andrei, Pirracchio, Romain, Gakuba, Clément, Boutron, Isabelle, Busse, Jason W., Devereaux, P. J., and Le Manach, Yannick
- Published
- 2019
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34. Retrospective Evaluation of a Restrictive Transfusion Strategy in Older Adults with Hip Fracture.
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Zerah, Lorene, Dourthe, Lucile, Cohen‐Bittan, Judith, Verny, Marc, Raux, Mathieu, Mézière, Anthony, Khiami, Frédéric, Tourette, Cendrine, Neri, Christian, Le Manach, Yannick, Riou, Bruno, Vallet, Hélène, and Boddaert, Jacques
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BLOOD transfusion ,HIP fractures ,HOSPITAL care of older people ,CARDIOVASCULAR system abnormalities ,MEDICAL rehabilitation ,HEMOGLOBINS ,GERIATRIC care units ,UTILIZATION of hospital emergency service ,THERAPEUTICS ,ATRIAL fibrillation risk factors ,MYOCARDIAL infarction risk factors ,HEART failure risk factors ,STROKE risk factors ,ELDER care ,CARDIOVASCULAR diseases risk factors ,CONFIDENCE intervals ,BONE fractures ,HIP joint injuries ,HOSPITAL care ,HOSPITAL emergency services ,REHABILITATION centers ,RETROSPECTIVE studies ,ODDS ratio ,OLD age - Abstract
Objectives: To compare the association between a restrictive transfusion strategy and cardiovascular complications during hospitalization for hip fracture with the association between a liberal transfusion strategy and cardiovascular complications, accounting for all transfusions from the emergency department to postacute rehabilitation settings. Design: Retrospective study. Setting: Perioperative geriatric care unit. Participants: All individuals aged 70 and older admitted to the emergency department for hip fracture and hospitalized in our perioperative geriatric care unit (N=667; n=193 in the liberal transfusion group, n=474 in the restrictive transfusion group) from July 2009 to April 2016. Intervention: A restrictive transfusion strategy (hemoglobin level threshold ≥8 g/dL or symptoms) used from January 2012 to April 2016 was compared with the liberal transfusion strategy (hemoglobin level threshold ≥10 g/dL) used from July 2009 to December 2011. Measurements: Primary endpoint was in‐hospital acute cardiovascular complications (heart failure, myocardial infarction, atrial fibrillation or stroke). Results: The change to a restrictive transfusion strategy was associated with fewer acute cardiovascular complications (odds ratio=0.45, 95% confidence interval (CI)=0.31–0.67, p<.001), without any noticeable difference in in‐hospital or 6‐month mortality. The change also led to a reduction in packed red blood cell units used per participant (median 1, interquartile range (IQR) 0–2 in restrictive vs median 2, IQR 0–3 in liberal transfusion strategy, P<.001). In rehabilitation settings, the frequency of transfusion was greater with the restrictive transfusion strategy than the liberal transfusion strategy (18% vs 9%, P<.001). Conclusion: A restrictive transfusion strategy in older adults with hip fracture was found to be safe and was associated with fewer cardiovascular complications but more transfusions in rehabilitation settings. Prospective studies are needed to confirm these findings. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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35. Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance.
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Nguyen, Tri-Long, Collins, Gary S., Spence, Jessica, Daurès, Jean-Pierre, Devereaux, P. J., Landais, Paul, and Le Manach, Yannick
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PROPENSITY score matching ,CONFOUNDING variables ,MONTE Carlo method ,REGRESSION analysis ,LOGISTIC regression analysis - Abstract
Background: Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression.Methods: We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds.Results: We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions.Conclusion: If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering. [ABSTRACT FROM AUTHOR]- Published
- 2017
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36. Comparison of the Prognostic Significance of Initial Blood Lactate and Base Deficit in Trauma Patients.
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Raux, Mathieu, Le Manach, Yannick, Gauss, Tobias, Baumgarten, Romain, Hamada, Sophie, Harrois, Anatole, Riou, Bruno, Duranteau, Jacques, Langeron, Olivier, Mantz, Jean, Paugam-Burtz, Catherine, Vigue, Bernard, and TRAUMABASE Group
- Subjects
- *
ACADEMIC medical centers , *ACID-base imbalances , *COMPARATIVE studies , *LACTIC acid , *LONGITUDINAL method , *RESEARCH methodology , *MEDICAL cooperation , *PROGNOSIS , *RESEARCH , *TRAUMA centers , *MEDICAL triage , *WOUNDS & injuries , *EVALUATION research , *RETROSPECTIVE studies , *RECEIVER operating characteristic curves , *HOSPITAL mortality - Abstract
Background: Initial blood lactate and base deficit have been shown to be prognostic biomarkers in trauma, but their respective performances have not been compared.Methods: Blood lactate levels and base deficit were measured at admission in trauma patients in three level 1 trauma centers. This was a retrospective analysis of prospectively acquired data. The association of initial blood lactate and base deficit with mortality was tested using receiver operating characteristics curve, logistic regression using triage scores (Revised Trauma Score and Mechanism Glasgow scale and Arterial Pressure score), and Trauma Related Injury Severity Score as a reference standard. The authors also used a reclassification method.Results: The authors evaluated 1,075 trauma patients (mean age, 39 ± 18 yr, with 90% blunt and 10% penetrating injuries and a mortality of 13%). At admission, blood lactate was elevated in 425 (39%) patients and base deficit was elevated in 725 (67%) patients. Blood lactate was correlated with base deficit (R = 0.54; P < 0.001). Using logistic regression, blood lactate was a better predictor of death than base deficit when considering its additional predictive value to triage scores and Trauma Related Injury Severity Score. This result was confirmed using a reclassification method but only in the subgroup of normotensive patients (n = 745).Conclusions: Initial blood lactate should be preferred to base deficit as a biologic variable in scoring systems built to assess the initial severity of trauma patients. [ABSTRACT FROM AUTHOR]- Published
- 2017
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- View/download PDF
37. Isolated cardiac troponin rise does not modify the prognosis in elderly patients with hip fracture.
- Author
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Vallet, Hélène, Breining, Alice, Manach, Yannick Le, Cohen-Bittan, Judith, Mézière, Anthony, Raux, Mathieu, Verny, Marc, Riou, Bruno, Khiami, Frédéric, Boddaert, Jacques, and Le Manach, Yannick
- Published
- 2017
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38. Improving medication safety: Development and impact of a multivariate model-based strategy to target high-risk patients.
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Nguyen, Tri-Long, Leguelinel-Blache, Géraldine, Kinowski, Jean-Marie, Roux-Marson, Clarisse, Rougier, Marion, Spence, Jessica, Le Manach, Yannick, and Landais, Paul
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MEDICATION safety ,MEDICATION errors ,DECISION making ,DRUG prescribing ,MULTIVARIATE analysis - Abstract
Background: Preventive strategies to reduce clinically significant medication errors (MEs), such as medication review, are often limited by human resources. Identifying high-risk patients to allow for appropriate resource allocation is of the utmost importance. To this end, we developed a predictive model to identify high-risk patients and assessed its impact on clinical decision-making. Methods: From March 1
st to April 31st 2014, we conducted a prospective cohort study on adult inpatients of a 1,644-bed University Hospital Centre. After a clinical evaluation of identified MEs, we fitted and internally validated a multivariate logistic model predicting their occurrence. Through 5,000 simulated randomized controlled trials, we compared two clinical decision pathways for intervention: one supported by our model and one based on the criterion of age. Results: Among 1,408 patients, 365 (25.9%) experienced at least one clinically significant ME. Eleven variables were identified using multivariable logistic regression and used to build a predictive model which demonstrated fair performance (c-statistic: 0.72). Major predictors were age and number of prescribed drugs. When compared with a decision to treat based on the criterion of age, our model enhanced the interception of potential adverse drug events by 17.5%, with a number needed to treat of 6 patients. Conclusion: We developed and tested a model predicting the occurrence of clinically significant MEs. Preliminary results suggest that its implementation into clinical practice could be used to focus interventions on high-risk patients. This must be confirmed on an independent set of patients and evaluated through a real clinical impact study. [ABSTRACT FROM AUTHOR]- Published
- 2017
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- View/download PDF
39. Withholding versus Continuing Angiotensin-converting Enzyme Inhibitors or Angiotensin II Receptor Blockers before Noncardiac Surgery: An Analysis of the Vascular events In noncardiac Surgery patIents cOhort evaluatioN Prospective Cohort.
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Roshanov, Pavel S., Rochwerg, Bram, Patel, Ameen, Salehian, Omid, Duceppe, Emmanuelle, Belley-Côté, Emilie P., Guyatt, Gordon H., Sessler, Daniel I., Le Manach, Yannick, Borges, Flavia K., Tandon, Vikas, Worster, Andrew, Thompson, Alexandra, Koshy, Mithin, Devereaux, Breagh, Spencer, Frederick A., Sanders, Robert D., Sloan, Erin N., Morley, Erin E., and Paul, James
- Published
- 2017
- Full Text
- View/download PDF
40. Health-Economic Researches in Perioperative Medicine.
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Landais, Paul, Chkair, Sihame, Chevallier, Thierry, Lomma, Mariella, Le Manach, Yannick, and Daurès, Jean-Pierre
- Published
- 2016
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41. Causal Inference in Anesthesia and Perioperative Observational Studies.
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Nguyen, Tri-Long, Winter, Audrey, Spence, Jessica, Leguelinel-Blache, Géraldine, Landais, Paul, and Le Manach, Yannick
- Published
- 2016
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42. Apheresis platelets are more frequently associated with adverse reactions than pooled platelets both in recipients and in donors: a study from French hemovigilance data.
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Daurat, Aurélien, Roger, Claire, Gris, JeanChristophe, Daurat, Gérald, Feissel, Michel, Le Manach, Yannick, Lefrant, JeanYves, and Muller, Laurent
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BLOOD transfusion reaction ,BLOOD platelet transfusion ,BLOOD donors ,DIRECTED blood donations ,BLOOD collection ,DISEASES - Abstract
Background: Controversy exists regarding the safety of the different types of platelet (PLT) concentrates. This study was aimed at comparing the rate of adverse reactions associated with apheresis PLT concentrates (APCs) and pooled PLT concentrates (PPCs) both in donors and in recipients.Study Design and Methods: From the French national hemovigilance system, types and numbers of recipient adverse reactions were compared over a period from 2009 to 2011. Donor adverse reactions were available for 2010 and 2011. This study involved 23 of 26 French regions. Main outcomes were the rates of adverse reaction in recipients and serious adverse reaction in donors.Results: There were 790,854 PLT transfusions during the study period (477,747 [60%] with APCs, 313,107 [40%] with PPCs). APCs were associated with more adverse reactions (6244 vs. 2469 per 1,000,000, p < 0.001) and more severe and life-threatening reactions (respectively, 241 vs. 131 per 1,000,000, p < 0.001; and 182 vs. 121 per 1,000,000, p = 0.04). Mortality rates due to an adverse transfusion reaction were similar (15 vs. 6 per 1,000,000, p = 0.5). In donors, the number of whole blood (WB) donations was 4,722,685 whereas 266,095 apheresis procedures were performed. Serious adverse reactions were more frequent for apheresis procedures than for WB donations (5445 vs. 803 per 1,000,000, p < 0.001).Conclusion: Our findings suggest that apheresis PLTs may be more hazardous than pooled PLTs both in recipients and in donors. This study calls for randomized trials to confirm or refute these results. [ABSTRACT FROM AUTHOR]- Published
- 2016
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- View/download PDF
43. Preoperative Score to Predict Postoperative Mortality (POSPOM): Derivation and Validation.
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Manach, Yannick Le, Collins, Gary, Rodseth, Reitze, Bihan-Benjamin, Christine Le, Biccard, Bruce, Riou, Bruno, DevereauX, P. J., Landais, Paul, Le Manach, Yannick, and Le Bihan-Benjamin, Christine
- Published
- 2016
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44. Outcomes After Hip Fracture Surgery Compared With Elective Total Hip Replacement.
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Le Manach, Yannick, Collins, Gary, Bhandari, Mohit, Bessissow, Amal, Boddaert, Jacques, Khiami, Frédéric, Chaudhry, Harman, De Beer, Justin, Riou, Bruno, Landais, Paul, Winemaker, Mitchell, Boudemaghe, Thierry, and Devereaux, P. J.
- Subjects
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AGE distribution , *DEMOGRAPHY , *BONE fractures , *HIP joint injuries , *PAIRED comparisons (Mathematics) , *RESEARCH funding , *SURGICAL complications , *ELECTIVE surgery , *TOTAL hip replacement , *COMORBIDITY , *LOGISTIC regression analysis , *HOSPITAL mortality - Abstract
Importance: Patients undergoing surgery for a hip fracture have a higher risk of mortality and major complications compared with patients undergoing an elective total hip replacement (THR) operation. The effect of older age and comorbidities associated with hip fracture on this increased perioperative risk is unknown.Objective: To determine if there was a difference in hospital mortality among patients who underwent hip fracture surgery relative to an elective THR, after adjustment for age, sex, and preoperative comorbidities.Design, Setting, and Participants: Using the French National Hospital Discharge Database from January 2010 to December 2013, patients older than 45 years undergoing hip surgery at French hospitals were included. The International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10), codes were used to determine patients' comorbidities and complications after surgery. A population matched for age, sex, and preoperative comorbidities of patients who underwent elective THR or hip fracture surgery was created using a multivariable logistic model and a greedy matching algorithm with a 1:1 ratio.Exposure: Hip fracture.Main Outcomes and Measures: Postoperative in-hospital mortality.Results: A total of 690,995 eligible patients were included from 864 centers in France. Patients undergoing elective THR surgery (n = 371,191) were younger, more commonly men, and had less comorbidity compared with patients undergoing hip fracture surgery. Following hip fracture surgery (n = 319,804), 10,931 patients (3.42%) died before hospital discharge and 669 patients (0.18%) died after elective THR. Multivariable analysis of the matched populations (n = 234,314) demonstrated a higher risk of mortality (1.82% for hip fracture surgery vs 0.31% for elective THR; absolute risk increase, 1.51% [95% CI, 1.46%-1.55%]; relative risk [RR], 5.88 [95% CI, 5.26-6.58]; P < .001) and of major postoperative complications (5.88% for hip fracture surgery vs 2.34% for elective THR; absolute risk increase, 3.54% [95% CI, 3.50%-3.59%]; RR, 2.50 [95% CI, 2.40-2.62]; P < .001) among patients undergoing hip fracture surgery.Conclusions and Relevance: In a large cohort of French patients, hip fracture surgery compared with elective THR was associated with a higher risk of in-hospital mortality after adjustment for age, sex, and measured comorbidities. Further studies are needed to define the causes for these differences. [ABSTRACT FROM AUTHOR]- Published
- 2015
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45. Analytical comparison of the new point-of-care troponin T immunoassay on AQT90Flex® analyzer (Radiometer) and the high-sensitivity troponin T immunoassay on ModularE170® (Roche Diagnostics).
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Monneret, Denis, Abbes, Rachel Ahmed Ben, Omarjee, Riyadh, Devilliers, Catherine, Le Manach, Yannick, Raux, Mathieu, Coriat, Pierre, Imbert-Bismut, Françoise, and Bonnefont-Rousselot, Dominique
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TROPONIN ,RANGE of measurement ,STATISTICAL correlation ,CHEST pain ,BIOMARKERS - Abstract
The article discusses a study which aims to compare troponin quantification (POC-Tn) on AQT90Flex analyzer and high-sensitivity Troponine T (hs-TnT) concentrations. Findings reveal excellent correlation between the two concentrations. It suggests further studies on chest pain unit to make firm conclusions about the subject.
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- 2014
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46. Impact of Aspirin and Clopidogrel Interruption on Platelet Function in Patients Undergoing Major Vascular Surgery.
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Le Manach, Yannick, Kahn, David, Bachelot-Loza, Christilla, Le Sache, Frederic, Smadja, David M., Remones, Veronique, Loriot, Marie-Anne, Coriat, Pierre, and Gaussem, Pascale
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ASPIRIN , *CLOPIDOGREL , *PLATELET function tests , *VASCULAR surgery , *PREOPERATIVE care , *PLATELET aggregation inhibitors - Abstract
Aims: To investigate functional platelet recovery after preoperative withdrawal of aspirin and clopidogrel and platelet function 5 days after treatment resumption. Methods/Results: We conducted an observational study, which prospectively included consecutive patients taking aspirin, taking clopidogrel, and untreated controls (15 patients in each group). The antiplatelet drugs were withdrawn five days before surgery (baseline) and were reintroduced two days after surgery. Platelet function was evaluated by optical aggregation in the presence of collagen, arachidonic acid (aspirin) and ADP (clopidogrel) and by VASP assay (clopidogrel). Platelet-leukocyte complex (PLC) level was quantified at each time-point. At baseline, platelet function was efficiently inhibited by aspirin and had recovered fully in most patients 5 days after drug withdrawal. PLC levels five days after aspirin reintroduction were similar to baseline (+4±10%; p = 0.16), in line with an effective platelet inhibition. Chronic clopidogrel treatment was associated with variable platelet inhibition and its withdrawal led to variable functional recovery. PLC levels were significantly increased five days after clopidogrel reintroduction (+10±15%; p = 0.02), compared to baseline. Conclusions: Aspirin withdrawal 5 days before high-bleeding-risk procedures was associated with functional platelet recovery, and its reintroduction two days after surgery restored antiplaletet efficacy five days later. This was not the case of clopidogrel, and further work is therefore needed to define its optimal perioperative management. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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47. Postoperative Admission to a Dedicated Geriatric Unit Decreases Mortality in Elderly Patients with Hip Fracture.
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Boddaert, Jacques, Cohen-Bittan, Judith, Khiami, Frédéric, Le Manach, Yannick, Raux, Mathieu, Beinis, Jean-Yves, Verny, Marc, and Riou, Bruno
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GERIATRIC care units ,OLDER patients ,POSTOPERATIVE care ,HIP fractures ,MORTALITY ,HIP surgery ,COMORBIDITY - Abstract
Background: Elderly patients with hip fracture have a 5 to 8 fold increased risk of death during the months following surgery. We tested the hypothesis that early geriatric management of these patients focused on co-morbidities and rehabilitation improved long term mortality. Methods and Findings: In a cohort study over a 6 year period, we compared patients aged >70 years with hip fracture admitted to orthopedic versus geriatric departments in a time series analysis corresponding to the creation of a dedicated geriatric unit. Co-morbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each cohort was compared to matched cohorts extracted from a national registry (n = 51,275) to validate the observed results. Main outcome measure was 6-month mortality. We included 131 patients in the orthopedic cohort and 203 in the geriatric cohort. Co-morbidities were more frequent in the geriatric cohort (median CIRS: 8 vs 5, P<0.001). In the geriatric cohort, the proportion of patients who never walked again decreased (6% versus 22%, P<0.001). At 6 months, re-admission (14% versus 29%, P = 0.007) and mortality (15% versus 24%, P = 0.04) were decreased. When co-morbidities were taken into account, the risk ratio of death at 6 months was reduced (0·43, 95%CI 0·25 to 0·73, P = 0.002). Using matched cohorts, the average treatment effects on the treated associated to early geriatric management indicated a reduction in hospital mortality (−63%; 95% CI: −92% to −6%, P = 0.006). Conclusions: Early admission to a dedicated geriatric unit improved 6-month mortality and morbidity in elderly patients with hip fracture. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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48. Postoperative B-type natriuretic peptide for prediction of major cardiac events in patients undergoing noncardiac surgery: systematic review and individual patient meta-analysis.
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Rodseth, Reitze N, Biccard, Bruce M, Chu, Rong, Lurati Buse, Giovana A, Thabane, Lehana, Bakhai, Ameet, Bolliger, Daniel, Cagini, Lucio, Cahill, Thomas J, Cardinale, Daniela, Chong, Carol P W, Cnotliwy, Miloslaw, Di Somma, Salvatore, Fahrner, René, Lim, Wen K, Mahla, Elisabeth, Le Manach, Yannick, Manikandan, Ramaswamy, Pyun, Wook B, and Rajagopalan, Sriram
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- 2013
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49. Precision of noninvasive hemoglobin-level measurement by pulse co-oximetry in patients admitted to intensive care units for severe gastrointestinal bleeds.
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Coquin, Julien, Dewitte, Antoine, Le Manach, Yannick, Caujolle, Marie, Joannes-Boyau, Olivier, Fleureau, Catherine, Janvier, Gérard, and Ouattara, Alexandre
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- 2012
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50. What Do Prehospital Trauma Scores Predict Besides Mortality?
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Raux, Mathieu, Sartorius, Danielle, Le Manach, Yannick, David, Jean-Stéphane, Riou, Bruno, and Vivien, Benoît
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- 2011
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