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911 results on '"Delacourt, C"'

11. Corrélations phénotype-génotype des patients pédiatriques porteurs de mutations bi-alléliques du gène lié au surfactant ABCA3

Author

Fleury, M., primary, Hadchouel, A., additional, Epaud, R., additional, Benhamida, M., additional, Berteloot, L., additional, Brouard, J., additional, L’Herminé, A. Coulomb, additional, Corvol, H., additional, Cros, P., additional, Delacourt, C., additional, Pointe, H. Ducou le, additional, Dubus, J.C., additional, Egron, C., additional, Fanen, P., additional, Fayon, M., additional, Fletcher, C., additional, Forgeron, A., additional, Giovannini-Chami, L., additional, Jedidi, N., additional, Marguet, C., additional, Rouchaud, A. Masson-, additional, Mazenq, J., additional, Petat, H., additional, Renoux, M.C., additional, Roditis, L., additional, Sileo, C., additional, Thumerelle, C., additional, Vigier, C., additional, Legendre, M., additional, De Becdelièvre, A., additional, Louvrier, C., additional, and Nathan, N., additional

Published
2024
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14. Recommandations pratiques pour l’utilisation et l’interprétation des tests de détection de l’interféron gamma dans le diagnostic de l’infection tuberculeuse latente et de la tuberculose maladie

Author

Bergot, E., Abiteboul, D., Andréjak, C., Antoun, F., Barras, E., Blanc, F.-X., Bourgarit, A., Charlois-Ou, C., Delacourt, C., Dirou, S., Gerin, M., Guerin, S., Haustraete, É., Henry, B., Lucet, J.-C., Maitre, T., Morin, J., Le Palud, P., Pommelet, V., Rivoisy, C., Robert, J., Veziris, N., and Herrmann, J.-L.

Published
2018
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19. Atteinte respiratoire dans le cadre des nécrolyses épidermiques pédiatriques : description et analyse d’une série rétrospective monocentrique française de 22 patients

Author

Schmartz, S., primary, Welfringer-Morin, A., additional, Le Bourgeois, M., additional, Delacourt, C., additional, Berteloot, L., additional, Hadj-Rabia, S., additional, Bellon, N., additional, Moulin, F., additional, De Saint Blanquat, L., additional, Garcelon, N., additional, Drummond, D., additional, and Bodemer, C., additional

Published
2022
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20. Recommandations sur l’utilisation des nouveaux outils diagnostiques étiologiques des infections respiratoires basses de l’enfant de plus de trois mois

Author

Dubus, J.-C., Delacourt, C., Marguet, C., Houdouin, V., Pouessel, G., Angoulvant, F., Brouard, J., Derelle, J., Fayon, M., Ferroni, A., Gangneux, J.-P., Hau, I., Le Bourgeois, M., Lorrot, M., Menotti, J., Nathan, N., Vabret, A., Wallet, F., Bonacorsi, S., Cohen, R., de Blic, J., Deschildre, A., Gandemer, V., Pin, I., Labbe, A., Le Roux, P., Martinot, A., and Rammaert, B.

Published
2014
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34. Effect of systematic tuberculosis detection on mortality in young children with severe pneumonia in countries with high incidence of tuberculosis: a stepped-wedge cluster-randomised trial

Author

Marcy, O, Wobudeya, E, Font, H, Vessière, A, Chabala, C, Khosa, C, Taguebue, J-V, Moh, R, Mwanga-Amumpaire, J, Lounnas, M, Mulenga, V, Mavale, S, Chilundo, J, Rego, D, Nduna, B, Shankalala, P, Chirwa, U, De Lauzanne, A, Dim, B, Tiogouo Ngouana, E, Folquet Amorrissani, M, Cisse, L, Amon Tanoh Dick, F, Komena, EA, Kwedi Nolna, S, Businge, G, Natukunda, N, Cumbe, S, Mbekeka, P, Kim, A, Kheang, C, Pol, S, Maleche-Obimbo, E, Seddon, JA, Mao, TE, Graham, SM, Delacourt, C, Borand, L, Bonnet, M, Serre, A, Badrichani, A, Razafimanantsoa, M, Poublan, J, Roucher, C, Occelli, E, Beuscart, A, Charpin, A, Habiyambere, G, Mesnier, S, Balestre, E, Bhatta, B, Maillard, A-L, Orne-Gliemann, J, Baillet, E, Koskas, N, D'Elbée, M, Gabillard, D, Huyen, M, Espérou, H, Couffin-Cadiergues, S, Kuppers, A, Hamze, B, BORAND, L, de LAUZANNE, A, DIM, B, Keang, C, PRING, L, YIN, S, SARITH, C, PHAN, C, NHEUONG, S, LY, S, KAING, S, SRENG, V, LUN, E, SAY, L, SUOM, S, FERHY, R, SO, D, BORN, S, PAL, S, NANG, B, MAO, TE, KIM, A, Srey, V, Kan, P, Hout, L, Ith, S, Oum, S, Sau, S, Ho, KH, Kith, D, Nuch, N, Horm, CL, Sophon, C, Roeungdeth, B, MENG, C, RITH, R, PHY, S, SOR, C, SAO, V, KHAT, S, MAK, B, UY, A, KHAY, S, SOM, K, HACH, R, SOK, H, KUON, S, HENG, S, SENG, A, NIM, S, PAN, R, KIM, S, SREY LEAP, K, NET, B, NOUN, V, LAY, D, MANY, C, Seng, S, Ly, V, So, S, Oun, S, CHEY, S, CHHEA, R, BAONG, L, THOUNG, V, KHEANG, C, BY, B, Nguon, V, MEACH, E, Tek, S, Ngeav, S, Lun, T, HEM, D, CHUT, N, SARIK, S, NANG, H, MEACH, M, SRENG, S, SAR, D, KIN, R, ROS, P, DORN, C, KAK, C, Sambath, SL, Son, L, Bin, L, Pengong, E, Khutsorn, S, Seang, S, Soun, V, Vong, V, Khoeung, C, Um, P, Bou, S, Song Pich, S, Nim, P, Khat, S, Ban Si, N, Ream, S, Ing, S, Chann, P, Ngeth, S, Sun, M, Chhoeung, S, Sean, S, Prak, R, Amboua Schouame Onambele, A, Hycenth, N, Melingui, B, Nkembe Medounmga, A, Hougnang Tatmi, L, Etemgoua, N, Kouesso, V, Bugin, J, Nzedjom, C, Ngoya, R, Eyike, J, Loudjom, E, Lonsti, R, Dang, L, Bintar, E, Njayong, C, Ngonsoa O, C, Ndzeukap, I, Dzoyem, P, Dzokou, C, Dindo, B, Aka Bony, R, Kouadio, C, Danho, S, Goli, M, Folquet, M, Itchy, MV, Sidibé, A, Cissé, L, Ouattara, J, Konaté, M, Amon-Tanoh Dick, F, Cardena, M, Adonis-Koffi, L, Eugenie, D, Kouamé, F, Menan, H, Inwoley, A, Ouassa, T, Nguessan, MS, Manhiça, E, Zitha, A, Chiúle, V, Muxanga, E, Gune, I, Lima, Y, Ribeiro, J, Maxanguana, F, Morais, N, Manhiça, J, Give, J, Atumane, J, Lucas, G, Thai, A, Chave, A, Guambe, L, Issa, F, Carneiro, R, Pene, N, Florindo, N, Machel, D, Cumbane, C, Mendes, H, Kitungwa, M, Muianga, V, Tamele, H, Sulude, A, Mabota, R, Comandante, H, Massangaie, A, Businge, GB, Namulinda, F, Sserunjogi, R, Nassozi, R, Barungi, C, Aanyu, H, Muwonge, D, Kagoya, E, Aciparu, S, Chemutai, S, Ntambi, S, Wasswa, A, Nangozi, J, Tagoola, A, Kenneth, S, Lubega, JP, Nassali, A, Tagobera, J, Agwang, C, Kalembe, F, Ajambo, A, Aguti, E, Kasibante, S, Matende, H, Odongo, IO, Mwanga Amumpaire, J, Ngabirano, G, Kakwenza, P, Nuwamanya, S, Nyangoma, M, Nabbuto, J, Abok, F, Arinaitwe, R, Birungi, D, Mwesigwa, E, Atwine, D, Mbega, H, Orikiriza, P, Taremwa, I, Turyashemererwa, E, Derrick, H, Nyehangane, D, Kaitano, R, Logoose, S, Businge, S, Ntambi, C, Mugabi, J, Mzee, J, Besigye, J, Kanzira, S, Turyatemba, P, Twebaze, F, Hambulo, C, Kapotwe, V, Ngambi, M, Kasakwa, K, Kapula, C, Zulu, S, Nawakwi, G, Siasulingana, T, Chilonga, J, Chimbini, M, Chilanga, M, Inambao, M, Mwambazi, M, Halende, B, Mumba, W, Mankunshe, E, Silavwe, M, Chakopo, M, Moono, R, Marcy, O, Wobudeya, E, Font, H, Vessière, A, Chabala, C, Khosa, C, Taguebue, J-V, Moh, R, Mwanga-Amumpaire, J, Lounnas, M, Mulenga, V, Mavale, S, Chilundo, J, Rego, D, Nduna, B, Shankalala, P, Chirwa, U, De Lauzanne, A, Dim, B, Tiogouo Ngouana, E, Folquet Amorrissani, M, Cisse, L, Amon Tanoh Dick, F, Komena, EA, Kwedi Nolna, S, Businge, G, Natukunda, N, Cumbe, S, Mbekeka, P, Kim, A, Kheang, C, Pol, S, Maleche-Obimbo, E, Seddon, JA, Mao, TE, Graham, SM, Delacourt, C, Borand, L, Bonnet, M, Serre, A, Badrichani, A, Razafimanantsoa, M, Poublan, J, Roucher, C, Occelli, E, Beuscart, A, Charpin, A, Habiyambere, G, Mesnier, S, Balestre, E, Bhatta, B, Maillard, A-L, Orne-Gliemann, J, Baillet, E, Koskas, N, D'Elbée, M, Gabillard, D, Huyen, M, Espérou, H, Couffin-Cadiergues, S, Kuppers, A, Hamze, B, BORAND, L, de LAUZANNE, A, DIM, B, Keang, C, PRING, L, YIN, S, SARITH, C, PHAN, C, NHEUONG, S, LY, S, KAING, S, SRENG, V, LUN, E, SAY, L, SUOM, S, FERHY, R, SO, D, BORN, S, PAL, S, NANG, B, MAO, TE, KIM, A, Srey, V, Kan, P, Hout, L, Ith, S, Oum, S, Sau, S, Ho, KH, Kith, D, Nuch, N, Horm, CL, Sophon, C, Roeungdeth, B, MENG, C, RITH, R, PHY, S, SOR, C, SAO, V, KHAT, S, MAK, B, UY, A, KHAY, S, SOM, K, HACH, R, SOK, H, KUON, S, HENG, S, SENG, A, NIM, S, PAN, R, KIM, S, SREY LEAP, K, NET, B, NOUN, V, LAY, D, MANY, C, Seng, S, Ly, V, So, S, Oun, S, CHEY, S, CHHEA, R, BAONG, L, THOUNG, V, KHEANG, C, BY, B, Nguon, V, MEACH, E, Tek, S, Ngeav, S, Lun, T, HEM, D, CHUT, N, SARIK, S, NANG, H, MEACH, M, SRENG, S, SAR, D, KIN, R, ROS, P, DORN, C, KAK, C, Sambath, SL, Son, L, Bin, L, Pengong, E, Khutsorn, S, Seang, S, Soun, V, Vong, V, Khoeung, C, Um, P, Bou, S, Song Pich, S, Nim, P, Khat, S, Ban Si, N, Ream, S, Ing, S, Chann, P, Ngeth, S, Sun, M, Chhoeung, S, Sean, S, Prak, R, Amboua Schouame Onambele, A, Hycenth, N, Melingui, B, Nkembe Medounmga, A, Hougnang Tatmi, L, Etemgoua, N, Kouesso, V, Bugin, J, Nzedjom, C, Ngoya, R, Eyike, J, Loudjom, E, Lonsti, R, Dang, L, Bintar, E, Njayong, C, Ngonsoa O, C, Ndzeukap, I, Dzoyem, P, Dzokou, C, Dindo, B, Aka Bony, R, Kouadio, C, Danho, S, Goli, M, Folquet, M, Itchy, MV, Sidibé, A, Cissé, L, Ouattara, J, Konaté, M, Amon-Tanoh Dick, F, Cardena, M, Adonis-Koffi, L, Eugenie, D, Kouamé, F, Menan, H, Inwoley, A, Ouassa, T, Nguessan, MS, Manhiça, E, Zitha, A, Chiúle, V, Muxanga, E, Gune, I, Lima, Y, Ribeiro, J, Maxanguana, F, Morais, N, Manhiça, J, Give, J, Atumane, J, Lucas, G, Thai, A, Chave, A, Guambe, L, Issa, F, Carneiro, R, Pene, N, Florindo, N, Machel, D, Cumbane, C, Mendes, H, Kitungwa, M, Muianga, V, Tamele, H, Sulude, A, Mabota, R, Comandante, H, Massangaie, A, Businge, GB, Namulinda, F, Sserunjogi, R, Nassozi, R, Barungi, C, Aanyu, H, Muwonge, D, Kagoya, E, Aciparu, S, Chemutai, S, Ntambi, S, Wasswa, A, Nangozi, J, Tagoola, A, Kenneth, S, Lubega, JP, Nassali, A, Tagobera, J, Agwang, C, Kalembe, F, Ajambo, A, Aguti, E, Kasibante, S, Matende, H, Odongo, IO, Mwanga Amumpaire, J, Ngabirano, G, Kakwenza, P, Nuwamanya, S, Nyangoma, M, Nabbuto, J, Abok, F, Arinaitwe, R, Birungi, D, Mwesigwa, E, Atwine, D, Mbega, H, Orikiriza, P, Taremwa, I, Turyashemererwa, E, Derrick, H, Nyehangane, D, Kaitano, R, Logoose, S, Businge, S, Ntambi, C, Mugabi, J, Mzee, J, Besigye, J, Kanzira, S, Turyatemba, P, Twebaze, F, Hambulo, C, Kapotwe, V, Ngambi, M, Kasakwa, K, Kapula, C, Zulu, S, Nawakwi, G, Siasulingana, T, Chilonga, J, Chimbini, M, Chilanga, M, Inambao, M, Mwambazi, M, Halende, B, Mumba, W, Mankunshe, E, Silavwe, M, Chakopo, M, and Moono, R

Abstract

Background: Tuberculosis diagnosis might be delayed or missed in children with severe pneumonia because this diagnosis is usually only considered in cases of prolonged symptoms or antibiotic failure. Systematic tuberculosis detection at hospital admission could increase case detection and reduce mortality. Methods: We did a stepped-wedge cluster-randomised trial in 16 hospitals from six countries (Cambodia, Cameroon, Côte d'Ivoire, Mozambique, Uganda, and Zambia) with high incidence of tuberculosis. Children younger than 5 years with WHO-defined severe pneumonia received either the standard of care (control group) or standard of care plus Xpert MTB/RIF Ultra (Xpert Ultra; Cepheid, Sunnyvale, CA, USA) on nasopharyngeal aspirate and stool samples (intervention group). Clusters (hospitals) were progressively switched from control to intervention at 5-week intervals, using a computer-generated random sequence, stratified on incidence rate of tuberculosis at country level, and masked to teams until 5 weeks before switch. We assessed the effect of the intervention on primary (12-week all-cause mortality) and secondary (including tuberculosis diagnosis) outcomes, using generalised linear mixed models. The primary analysis was by intention to treat. We described outcomes in children with severe acute malnutrition in a post hoc analysis. This study is registered with ClinicalTrials.gov (NCT03831906) and the Pan African Clinical Trial Registry (PACTR202101615120643). Findings: From March 21, 2019, to March 30, 2021, we enrolled 1401 children in the control group and 1169 children in the intervention group. In the intervention group, 1140 (97·5%) children had nasopharyngeal aspirates and 942 (80·6%) had their stool collected; 24 (2·1%) had positive Xpert Ultra. At 12 weeks, 110 (7·9%) children in the control group and 91 (7·8%) children in the intervention group had died (adjusted odds ratio [OR] 0·986, 95% CI 0·597–1·630, p=0·957), and 74 (5·3%) children in the control group

Published
2022

43. Cliff Change Detection Using Siamese Kpconv Deep Network on 3d Point Clouds

Author

de Gélis, Iris, Bessin, Z., Letortu, P., Jaud, M., Delacourt, C., Costa, S., Maquaire, O., Davidson, R., Corpetti, T., Lefèvre, Sébastien, Magellium, Observation de l’environnement par imagerie complexe (OBELIX), SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire Géosciences Océan (LGO), Université de Bretagne Sud (UBS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Littoral, Environnement, Télédétection, Géomatique (LETG - Brest), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Nantes Université (Nantes Univ)-Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Humanités, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), Nantes Université (Nantes Univ), Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Normandie Université (NU), Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes ), Université de Brest (UBO)-Université de Rennes 2 (UR2)-Nantes Université (Nantes Univ)-Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (Nantes Univ - IGARUN), and ANR-17-EURE-0015,ISBlue,Interdisciplinary Graduate School for the Blue planet(2017)

Subjects
Erosion detection, [SDU]Sciences of the Universe [physics], cliffs, deep learning, 3D point clouds, change detection, ComputingMilieux_MISCELLANEOUS
Abstract

Mainly depending on their lithology, coastal cliffs are prone to changes due to erosion. This erosion could increase due to climate change leading to potential threats for coastal users, assets, or infrastructure. Thus, it is important to be able to understand and characterize cliff face changes at fine scale. Usually, monitoring is conducted thanks to distance computation and manual analysis of each cliff face over 3D point clouds to be able to study 3D dynamics of cliffs. This is time consuming and inclined to each one judgment in particular when dealing with 3D point clouds data. Indeed, 3D point clouds characteristics (sparsity, impossibility of working on a classical top view representation, volume of data, …) make their processing harder than 2D images. Last decades, an increase of performance of machine learning methods for earth observation purposes has been performed. To the best of our knowledge, deep learning has never been used for 3D change detection and categorization in coastal cliffs. Lately, Siamese KPConv brings successful results for change detection and categorization into 3D point clouds in urban area. Although the case study is different by its more random characteristics and its complex geometry, we demonstrate here that this method also allows to extract and categorize changes on coastal cliff face. Results over the study area of Petit Ailly cliffs in Varengeville-sur-Mer (France) are very promising qualitatively as well as quantitatively: erosion is retrieved with an intersection over union score of 83.86 %.

Published
2022
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47. Efficacité d’une supplémentation orale en méthionine chez les patients atteints de protéinose alvéolaire primitive par mutations du gène MARS

Author

Hadchouel, A., primary, Drummond, D., additional, Pontoizeau, C., additional, Hurtado-Nedelec, M., additional, El Benna, J., additional, Gachelin, E., additional, Perisson, C., additional, Vigier, C., additional, Schiff, M., additional, Lacaille, F., additional, Molina, T.J., additional, Berteloot, L., additional, Renolleau, S., additional, Ottolenghi, C., additional, Tréluyer, J.M., additional, De Blic, J., additional, and Delacourt, C., additional

Published
2022
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48. Pathologie du surfactant : diagnostic, présentation initiale, évolution et prise en charge des enfants porteurs d’une mutation SFTPC

Author

Sarfati, E., primary, Berthelot, L., additional, Sileo, C., additional, Abou Taam, R., additional, Nathan, N., additional, Reix, P., additional, Thumerelle, C., additional, Giovannini-Chami, L., additional, Dubus, J.C., additional, Renoux, M.C., additional, Bremont, F., additional, Hullo, E., additional, Marguet, C., additional, Hadchouel, A., additional, De Becdelièvre, A., additional, Fanen, P., additional, Legendre, M., additional, Delacourt, C., additional, Clement, A., additional, Epaud, R., additional, and Delestrain, C., additional

Published
2022
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