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Tran, Khanh Bao, Lang, Justin J.; Compton, Kelly, Xu, Rixing, Acheson, Alistair R.; Henrikson, Hannah Jacqueline, Kocarnik, Jonathan M.; Penberthy, Louise, Aali, Amirali, Abbas, Qamar, Abbasi, Behzad, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abbastabar, Hedayat, Abdelmasseh, Michael, Abd-Elsalam, Sherief, Abdelwahab, Ahmed Abdelwahab, Abdoli, Gholamreza, Abdulkadir, Hanan Abdulkadir, Abedi, Aidin, Abegaz, Kedir Hussein, Abidi, Hassan, Aboagye, Richard Gyan, Abolhassani, Hassan, Absalan, Abdorrahim, Abtew, Yonas Derso, Abubaker Ali, Hiwa, Abu-Gharbieh, Eman, Achappa, Basavaprabhu, Acuna, Juan Manuel, Addison, Daniel, Addo, Isaac Yeboah, Adegboye, Oyelola A.; Adesina, Miracle Ayomikun, Adnan, Mohammad, Adnani, Qorinah Estiningtyas Sakilah, Advani, Shailesh M.; Afrin, Sumia, Afzal, Muhammad Sohail, Aggarwal, Manik, Ahinkorah, Bright Opoku, Ahmad, Araz Ramazan, Ahmad, Rizwan, Ahmad, Sajjad, Ahmad, Sohail, Ahmadi, Sepideh, Ahmed, Haroon, Ahmed, Luai A.; Ahmed, Muktar Beshir, Ahmed Rashid, Tarik, Aiman, Wajeeha, Ajami, Marjan, Akalu, Gizachew Taddesse, Akbarzadeh-Khiavi, Mostafa, Aklilu, Addis, Akonde, Maxwell, Akunna, Chisom Joyqueenet, Al Hamad, Hanadi, Alahdab, Fares, Alanezi, Fahad Mashhour, Alanzi, Turki M.; Alessy, Saleh Ali, Algammal, Abdelazeem M.; Al-Hanawi, Mohammed Khaled, Alhassan, Robert Kaba, Ali, Beriwan Abdulqadir, Ali, Liaqat, Ali, Syed Shujait, Alimohamadi, Yousef, Alipour, Vahid, Aljunid, Syed Mohamed, Alkhayyat, Motasem, Al-Maweri, Sadeq Ali Ali, Almustanyir, Sami, Alonso, Nivaldo, Alqalyoobi, Shehabaldin, Al-Raddadi, Rajaa M.; Al-Rifai, Rami H. Hani, Al-Sabah, Salman Khalifah, Al-Tammemi, Ala'a B.; Altawalah, Haya, Alvis-Guzman, Nelson, Amare, Firehiwot, Ameyaw, Edward Kwabena, Aminian Dehkordi, Javad Javad, Amirzade-Iranaq, Mohammad Hosein, Amu, Hubert, Amusa, Ganiyu Adeniyi, Ancuceanu, Robert, Anderson, Jason A.; Animut, Yaregal Animut, Anoushiravani, Amir, Anoushirvani, Ali Arash, Ansari-Moghaddam, Alireza, Ansha, Mustafa Geleto, Antony, Benny, Antwi, Maxwell Hubert, Anwar, Sumadi Lukman, Anwer, Razique, Anyasodor, Anayochukwu Edward, Arabloo, Jalal, Arab-Zozani, Morteza, Aremu, Olatunde, Argaw, Ayele Mamo, Ariffin, Hany, Aripov, Timur, Arshad, Muhammad, Artaman, Al, Arulappan, Judie, Aruleba, Raphael Taiwo, Aryannejad, Armin, Asaad, Malke, Asemahagn, Mulusew A.; Asemi, Zatollah, Asghari-Jafarabadi, Mohammad, Ashraf, Tahira, Assadi, Reza, Athar, Mohammad, Athari, Seyyed Shamsadin, Atout, Maha Moh'd Wahbi, Attia, Sameh, Aujayeb, Avinash, Ausloos, Marcel, Avila-Burgos, Leticia, Awedew, Atalel Fentahun, Awoke, Mamaru Ayenew, Awoke, Tewachew, Ayala Quintanilla, Beatriz Paulina, Ayana, Tegegn Mulatu, Ayen, Solomon Shitu, Azadi, Davood, Azadnajafabad, Sina, Azami-Aghdash, Saber, Azanaw, Melkalem Mamuye, Azangou-Khyavy, Mohammadreza, Azari Jafari, Amirhossein, Azizi, Hosein, Azzam, Ahmed Y. Y.; Babajani, Amirhesam, Badar, Muhammad, Badiye, Ashish D.; Baghcheghi, Nayereh, Bagheri, Nader, Bagherieh, Sara, Bahadory, Saeed, Baig, Atif Amin, Baker, Jennifer L.; Bakhtiari, Ahad, Bakshi, Ravleen Kaur, Banach, Maciej, Banerjee, Indrajit, Bardhan, Mainak, Barone-Adesi, Francesco, Barra, Fabio, Barrow, Amadou, Bashir, Nasir Z.; Bashiri, Azadeh, Basu, Saurav, Batiha, Abdul-Monim Mohammad, Begum, Aeysha, Bekele, Alehegn Bekele, Belay, Alemayehu Sayih, Belete, Melaku Ashagrie, Belgaumi, Uzma Iqbal, Bell, Arielle Wilder, Belo, Luis, Benzian, Habib, Berhie, Alemshet Yirga, Bermudez, Amiel Nazer C.; Bernabe, Eduardo, Bhagavathula, Akshaya Srikanth, Bhala, Neeraj, Bhandari, Bharti Bhandari, Bhardwaj, Nikha, Bhardwaj, Pankaj, Bhattacharyya, Krittika, Bhojaraja, Vijayalakshmi S.; Bhuyan, Soumitra S.; Bibi, Sadia, Bilchut, Awraris Hailu, Bintoro, Bagas Suryo, Biondi, Antonio, Birega, Mesfin Geremaw Birega, Birhan, Habitu Eshetu, Bjørge, Tone, Blyuss, Oleg, Bodicha, Belay Boda Abule, Bolla, Srinivasa Rao, Boloor, Archith, Bosetti, Cristina, Braithwaite, Dejana, Brauer, Michael, Brenner, Hermann, Briko, Andrey Nikolaevich, Briko, Nikolay Ivanovich, Buchanan, Christina Maree, Bulamu, Norma B.; Bustamante-Teixeira, Maria Teresa, Butt, Muhammad Hammad, Butt, Nadeem Shafique, Butt, Zahid A.; Caetano dos Santos, Florentino Luciano, Cámera, Luis Alberto, Cao, Chao, Cao, Yin, Carreras, Giulia, Carvalho, Márcia, Cembranel, Francieli, Cerin, Ester, Chakraborty, Promit Ananyo, Charalampous, Periklis, Chattu, Vijay Kumar, Chimed-Ochir, Odgerel, Chirinos-Caceres, Jesus Lorenzo, Cho, Daniel Youngwhan, Cho, William C. S.; Christopher, Devasahayam J.; Chu, Dinh-Toi, Chukwu, Isaac Sunday, Cohen, Aaron J.; Conde, Joao, Cortés, Sandra, Costa, Vera Marisa, Cruz-Martins, Natália, Culbreth, Garland T.; Dadras, Omid, Dagnaw, Fentaw Teshome, Dahlawi, Saad M. A.; Dai, Xiaochen, Dandona, Lalit, Dandona, Rakhi, Daneshpajouhnejad, Parnaz, Danielewicz, Anna, Dao, An Thi Minh, Darvishi Cheshmeh Soltani, Reza, Darwesh, Aso Mohammad, Das, Saswati, Davitoiu, Dragos Virgil, Davtalab Esmaeili, Elham, De la Hoz, Fernando Pio, Debela, Sisay Abebe, Dehghan, Azizallah, Demisse, Biniyam, Demisse, Fitsum Wolde, Denova-Gutiérrez, Edgar, Derakhshani, Afshin, Derbew Molla, Meseret, Dereje, Diriba, Deribe, Kalkidan Solomon, Desai, Rupak, Desalegn, Markos Desalegn, Dessalegn, Fikadu Nugusu, Dessalegni, Samuel Abebe A.; Dessie, Gashaw, Desta, Abebaw Alemayehu, Dewan, Syed Masudur Rahman, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dianatinasab, Mostafa, Diao, Nancy, Diaz, Daniel, Digesa, Lankamo Ena, Dixit, Shilpi Gupta, Doaei, Saeid, Doan, Linh Phuong, Doku, Paul Narh, Dongarwar, Deepa, dos Santos, Wendel Mombaque, Driscoll, Tim Robert, Dsouza, Haneil Larson, Durojaiye, Oyewole Christopher, Edalati, Sareh, Eghbalian, Fatemeh, Ehsani-Chimeh, Elham, Eini, Ebrahim, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, Ekwueme, Donatus U.; El Tantawi, Maha, Elbahnasawy, Mostafa Ahmed, Elbarazi, Iffat, Elghazaly, Hesham, Elhadi, Muhammed, El-Huneidi, Waseem, Emamian, Mohammad Hassan, Engelbert Bain, Luchuo, Enyew, Daniel Berhanie, Erkhembayar, Ryenchindorj, Eshetu, Tegegne, Eshrati, Babak, Eskandarieh, Sharareh, Espinosa-Montero, Juan, Etaee, Farshid, Etemadimanesh, Azin, Eyayu, Tahir, Ezeonwumelu, Ifeanyi Jude, Ezzikouri, Sayeh, Fagbamigbe, Adeniyi Francis, Fahimi, Saman, Fakhradiyev, Ildar Ravisovich, Faraon, Emerito Jose A.; Fares, Jawad, Farmany, Abbas, Farooque, Umar, Farrokhpour, Hossein, Fasanmi, Abidemi Omolara, Fatehizadeh, Ali, Fatima, Wafa, Fattahi, Hamed, Fekadu, Ginenus, Feleke, Berhanu Elfu, Ferrari, Allegra Allegra, Ferrero, Simone, Ferro Desideri, Lorenzo, Filip, Irina, Fischer, Florian, Foroumadi, Roham, Foroutan, Masoud, Fukumoto, Takeshi, Gaal, Peter Andras, Gad, Mohamed M.; Gadanya, Muktar A.; Gaipov, Abduzhappar, Galehdar, Nasrin, Gallus, Silvano, Garg, Tushar, Gaspar Fonseca, Mariana, Gebremariam, Yosef Haile, Gebremeskel, Teferi Gebru, Gebremichael, Mathewos Alemu, Geda, Yohannes Fikadu, Gela, Yibeltal Yismaw, Gemeda, Belete Negese Belete, Getachew, Melaku, Getachew, Motuma Erena, Ghaffari, Kazem, Ghafourifard, Mansour, Ghamari, Seyyed-Hadi, Ghasemi Nour, Mohammad, Ghassemi, Fariba, Ghimire, Ajnish, Ghith, Nermin, Gholamalizadeh, Maryam, Gholizadeh Navashenaq, Jamshid, Ghozy, Sherief, Gilani, Syed Amir, Gill, Paramjit Singh, Ginindza, Themba G.; Gizaw, Abraham Tamirat T.; Glasbey, James C.; Godos, Justyna, Goel, Amit, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Golitaleb, Mohamad, Gorini, Giuseppe, Goulart, Bárbara Niegia Garcia, Grosso, Giuseppe, Guadie, Habtamu Alganeh, Gubari, Mohammed Ibrahim Mohialdeen, Gudayu, Temesgen Worku, Guerra, Maximiliano Ribeiro, Gunawardane, Damitha Asanga, Gupta, Bhawna, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Gurara, Mekdes Kondale, Guta, Alemu, Habibzadeh, Parham, Haddadi Avval, Atlas, Hafezi-Nejad, Nima, Hajj Ali, Adel, Haj-Mirzaian, Arvin, Halboub, Esam S.; Halimi, Aram, Halwani, Rabih, Hamadeh, Randah R.; Hameed, Sajid, Hamidi, Samer, Hanif, Asif, Hariri, Sanam, Harlianto, Netanja I.; Haro, Josep Maria, Hartono, Risky Kusuma, Hasaballah, Ahmed I.; Hasan, S. M. Mahmudul, Hasani, Hamidreza, Hashemi, Seyedeh Melika, Hassan, Abbas M.; Hassanipour, Soheil, Hayat, Khezar, Heidari, Golnaz, Heidari, Mohammad, Heidarymeybodi, Zahra, Herrera-Serna, Brenda Yuliana, Herteliu, Claudiu, Hezam, Kamal, Hiraike, Yuta, Hlongwa, Mbuzeleni Mbuzeleni, Holla, Ramesh, Holm, Marianne, Horita, Nobuyuki, Hoseini, Mohammad, Hossain, Md Mahbub, Hossain, Mohammad Bellal Hossain, Hosseini, Mohammad-Salar, Hosseinzadeh, Ali, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Househ, Mowafa, Huang, Junjie, Hugo, Fernando N.; Humayun, Ayesha, Hussain, Salman, Hussein, Nawfal R.; Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Iftikhar, Pulwasha Maria, Ikuta, Kevin S.; Ilesanmi, Olayinka Stephen, Ilic, Irena M.; Ilic, Milena D.; Immurana, Mustapha, Innos, Kaire, Iranpour, Pooya, Irham, Lalu Muhammad, Islam, Md Shariful, Islam, Rakibul M.; Islami, Farhad, Ismail, Nahlah Elkudssiah, Isola, Gaetano, Iwagami, Masao, J, Linda Merin, Jaiswal, Abhishek, Jakovljevic, Mihajlo, Jalili, Mahsa, Jalilian, Shahram, Jamshidi, Elham, Jang, Sung-In, Jani, Chinmay T.; Javaheri, Tahereh, Jayarajah, Umesh Umesh, Jayaram, Shubha, Jazayeri, Seyed Behzad, Jebai, Rime, Jemal, Bedru, Jeong, Wonjeong, Jha, Ravi Prakash, Jindal, Har Ashish, John-Akinola, Yetunde O.; Jonas, Jost B.; Joo, Tamas, Joseph, Nitin, Joukar, Farahnaz, Jozwiak, Jacek Jerzy, Jürisson, Mikk, Kabir, Ali, Kacimi, Salah Eddine Oussama, Kadashetti, Vidya, Kahe, Farima, Kakodkar, Pradnya Vishal, Kalankesh, Laleh R.; Kalankesh, Leila R.; Kalhor, Rohollah, Kamal, Vineet Kumar, Kamangar, Farin, Kamath, Ashwin, Kanchan, Tanuj, Kandaswamy, Eswar, Kandel, Himal, Kang, HyeJung, Kanno, Girum Gebremeskel, Kapoor, Neeti, Kar, Sitanshu Sekhar, Karanth, Shama D.; Karaye, Ibraheem M.; Karch, André, Karimi, Amirali, Kassa, Bekalu Getnet, Katoto, Patrick D. M. C.; Kauppila, Joonas H.; Kaur, Harkiran, Kebede, Abinet Gebremickael, Keikavoosi-Arani, Leila, Kejela, Gemechu Gemechu, Kemp Bohan, Phillip M.; Keramati, Maryam, Keykhaei, Mohammad, Khajuria, Himanshu, Khan, Abbas, Khan, Abdul Aziz Khan, Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Moien A. B.; Khanali, Javad, Khatab, Khaled, Khatatbeh, Moawiah Mohammad, Khatib, Mahalaqua Nazli, Khayamzadeh, Maryam, Khayat Kashani, Hamid Reza, Khazeei Tabari, Mohammad Amin, Khezeli, Mehdi, Khodadost, Mahmoud, Kim, Min Seo, Kim, Yun Jin, Kisa, Adnan, Kisa, Sezer, Klugar, Miloslav, Klugarová, Jitka, Kolahi, Ali-Asghar, Kolkhir, Pavel, Kompani, Farzad, Koul, Parvaiz A.; Koulmane Laxminarayana, Sindhura Lakshmi, Koyanagi, Ai, Krishan, Kewal, Krishnamoorthy, Yuvaraj, Kucuk Bicer, Burcu, Kugbey, Nuworza, Kulimbet, Mukhtar, Kumar, Akshay, Kumar, G. Anil, Kumar, Narinder, Kurmi, Om P.; Kuttikkattu, Ambily, La Vecchia, Carlo, Lahiri, Arista, Lal, Dharmesh Kumar, Lám, Judit, Lan, Qing, Landires, Iván, Larijani, Bagher, Lasrado, Savita, Lau, Jerrald, Lauriola, Paolo, Ledda, Caterina, Lee, Sang-woong, Lee, Shaun Wen Huey, Lee, Wei-Chen, Lee, Yeong Yeh, Lee, Yo Han, Legesse, Samson Mideksa, Leigh, James, Leong, Elvynna, Li, Ming-Chieh, Lim, Stephen S.; Liu, Gang, Liu, Jue, Lo, Chun-Han, Lohiya, Ayush, Lopukhov, Platon D.; Lorenzovici, László, Lotfi, Mojgan, Loureiro, Joana A.; Lunevicius, Raimundas, Madadizadeh, Farzan, Mafi, Ahmad R.; Magdeldin, Sameh, Mahjoub, Soleiman, Mahmoodpoor, Ata, Mahmoudi, Morteza, Mahmoudimanesh, Marzieh, Mahumud, Rashidul Alam, Majeed, Azeem, Majidpoor, Jamal, Makki, Alaa, Makris, Konstantinos Christos, Malakan Rad, Elaheh, Malekpour, Mohammad-Reza, Malekzadeh, Reza, Malik, Ahmad Azam, Mallhi, Tauqeer Hussain, Mallya, Sneha Deepak, Mamun, Mohammed A.; Manda, Ana Laura, Mansour-Ghanaei, Fariborz, Mansouri, Borhan, Mansournia, Mohammad Ali, Mantovani, Lorenzo Giovanni, Martini, Santi, Martorell, Miquel, Masoudi, Sahar, Masoumi, Seyedeh Zahra, Matei, Clara N.; Mathews, Elezebeth, Mathur, Manu Raj, Mathur, Vasundhara, McKee, Martin, Meena, Jitendra Kumar, Mehmood, Khalid, Mehrabi Nasab, Entezar, Mehrotra, Ravi, Melese, Addisu, Mendoza, Walter, Menezes, Ritesh G.; Mengesha, SIsay Derso, Mensah, Laverne G.; Mentis, Alexios-Fotios A.; Mera-Mamián, Andry Yasmid Mera, Meretoja, Tuomo J.; Merid, Mehari Woldemariam, Mersha, Amanual Getnet, Meselu, Belsity Temesgen, Meshkat, Mahboobeh, Mestrovic, Tomislav, Miao Jonasson, Junmei, Miazgowski, Tomasz, Michalek, Irmina Maria, Mijena, Gelana Fekadu Worku, Miller, Ted R.; Mir, Shabir Ahmad, Mirinezhad, Seyed Kazem, Mirmoeeni, Seyyedmohammadsadeq, Mirza-Aghazadeh-Attari, Mohammad, Mirzaei, Hamed, Mirzaei, Hamid Reza, Misganaw, Abay Sisay, Misra, Sanjeev, Mohammad, Karzan Abdulmuhsin, Mohammadi, Esmaeil, Mohammadi, Mokhtar, Mohammadian-Hafshejani, Abdollah, Mohammadpourhodki, Reza, Mohammed, Arif, Mohammed, Shafiu, Mohan, Syam, Mohseni, Mohammad, Moka, Nagabhishek, Mokdad, Ali H.; Molassiotis, Alex, Molokhia, Mariam, Momenzadeh, Kaveh, Momtazmanesh, Sara, Monasta, Lorenzo, Mons, Ute, Montasir, Ahmed Al, Montazeri, Fateme, Montero, Arnulfo, Moosavi, Mohammad Amin, Moradi, Abdolvahab, Moradi, Yousef, Moradi Sarabi, Mostafa, Moraga, Paula, Morawska, Lidia, Morrison, Shane Douglas, Morze, Jakub, Mosapour, Abbas, Mostafavi, Ebrahim, Mousavi, Seyyed Meysam, Mousavi Isfahani, Haleh, Mousavi Khaneghah, Amin, Mpundu-Kaambwa, Christine, Mubarik, Sumaira, Mulita, Francesk, Munblit, Daniel, Munro, Sandra B.; Murillo-Zamora, Efrén, Musa, Jonah, Nabhan, Ashraf F.; Nagarajan, Ahamarshan Jayaraman, Nagaraju, Shankar Prasad, Nagel, Gabriele, Naghipour, Mohammadreza, Naimzada, Mukhammad David, Nair, Tapas Sadasivan, Naqvi, Atta Abbas, Narasimha Swamy, Sreenivas, Narayana, Aparna Ichalangod, Nassereldine, Hasan, Natto, Zuhair S.; Nayak, Biswa Prakash, Ndejjo, Rawlance, Nduaguba, Sabina Onyinye, Negash, Wogene Wogene, Nejadghaderi, Seyed Aria, Nejati, Kazem, Neupane Kandel, Sandhya, Nguyen, Huy Van Nguyen, Niazi, Robina Khan, Noor, Nurulamin M.; Noori, Maryam, Noroozi, Nafise, Nouraei, Hasti, Nowroozi, Ali, Nuñez-Samudio, Virginia, Nzoputam, Chimezie Igwegbe, Nzoputam, Ogochukwu Janet, Oancea, Bogdan, Odukoya, Oluwakemi Ololade, Oghenetega, Onome Bright, Ogunsakin, Ropo Ebenezer, Oguntade, Ayodipupo Sikiru, Oh, In-Hwan, Okati-Aliabad, Hassan, Okekunle, Akinkunmi Paul, Olagunju, Andrew T.; Olagunju, Tinuke O.; Olakunde, Babayemi Oluwaseun, Olufadewa, Isaac Iyinoluwa, Omer, Emad, Omonisi, Abidemi E. Emmanuel, Ong, Sokking, Onwujekwe, Obinna E.; Orru, Hans, Otstavnov, Stanislav S.; Oulhaj, Abderrahim, Oumer, Bilcha, Owopetu, Oluwatomi Funbi, Oyinloye, Babatunji Emmanuel, P A, Mahesh, Padron-Monedero, Alicia, Padubidri, Jagadish Rao, Pakbin, Babak, Pakshir, Keyvan, Pakzad, Reza, Palicz, Tamás, Pana, Adrian, Pandey, Anamika, Pandey, Ashok, Pant, Suman, Pardhan, Shahina, Park, Eun-Cheol, Park, Eun-Kee, Park, Seoyeon, Patel, Jay, Pati, Siddhartha, Paudel, Rajan, Paudel, Uttam, Paun, Mihaela, Pazoki Toroudi, Hamidreza, Peng, Minjin, Pereira, Jeevan, Pereira, Renato B.; Perna, Simone, Perumalsamy, Navaraj, Pestell, Richard G.; Pezzani, Raffaele, Piccinelli, Cristiano, Pillay, Julian David, Piracha, Zahra Zahid, Pischon, Tobias, Postma, Maarten J.; Pourabhari Langroudi, Ashkan, Pourshams, Akram, Pourtaheri, Naeimeh, Prashant, Akila, Qadir, Mirza Muhammad Fahd, Quazi Syed, Zahiruddin, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Radhakrishnan, Raghu Anekal, Radhakrishnan, Venkatraman, Raeisi, Mojtaba, Rafiee, Ata, Rafiei, Alireza, Raheem, Nasiru, Rahim, Fakher, Rahman, Md Obaidur, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Shayan, Rahmanian, Vahid, Rajai, Nazanin, Rajesh, Aashish, Ram, Pradhum, Ramezanzadeh, Kiana, Rana, Juwel, Ranabhat, Kamal, Ranasinghe, Priyanga, Rao, Chythra R.; Rao, Sowmya J.; Rashedi, Sina, Rashidi, Amirfarzan, Rashidi, Mahsa, Rashidi, Mohammad-Mahdi, Ratan, Zubair Ahmed, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Rawassizadeh, Reza, Razeghinia, Mohammad Sadegh, Rehman, Ashfaq Ur, Rehman, Inayat ur, Reitsma, Marissa B.; Renzaho, Andre M. N.; Rezaei, Maryam, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaei, Saeid, Rezaeian, Mohsen, Rezapour, Aziz, Riad, Abanoub, Rikhtegar, Reza, Rios-Blancas, Maria, Roberts, Thomas J.; Rohloff, Peter, Romero-Rodríguez, Esperanza, Roshandel, Gholamreza, Rwegerera, Godfrey M.; S, Manjula, Saber-Ayad, Maha Mohamed, Saberzadeh-Ardestani, Bahar, Sabour, Siamak, Saddik, Basema, Sadeghi, Erfan, Saeb, Mohammad Reza, Saeed, Umar, Safaei, Mohsen, Safary, Azam, Sahebazzamani, Maryam, Sahebkar, Amirhossein, Sahoo, Harihar, Sajid, Mirza Rizwan, Salari, Hedayat, Salehi, Sana, Salem, Marwa Rashad, Salimzadeh, Hamideh, Samodra, Yoseph Leonardo, Samy, Abdallah M.; Sanabria, Juan, Sankararaman, Senthilkumar, Sanmarchi, Francesco, Santric-Milicevic, Milena M.; Saqib, Muhammad Arif Nadeem, Sarveazad, Arash, Sarvi, Fatemeh, Sathian, Brijesh, Satpathy, Maheswar, Sayegh, Nicolas, Schneider, Ione Jayce Ceola, Schwarzinger, Michaël, Šekerija, Mario, Senthilkumaran, Subramanian, Sepanlou, Sadaf G.; Seylani, Allen, Seyoum, Kenbon, Sha, Feng, Shafaat, Omid, Shah, Pritik A.; Shahabi, Saeed, Shahid, Izza, Shahrbaf, Mohammad Amin, Shahsavari, Hamid R.; Shaikh, Masood Ali, Shaka, Mohammed Feyisso, Shaker, Elaheh, Shannawaz, Mohammed, Sharew, Mequannent Melaku Sharew, Sharifi, Azam, Sharifi-Rad, Javad, Sharma, Purva, Shashamo, Bereket Beyene, Sheikh, Aziz, Sheikh, Mahdi, Sheikhbahaei, Sara, Sheikhi, Rahim Ali, Sheikhy, Ali, Shepherd, Peter Robin, Shetty, Adithi, Shetty, Jeevan K.; Shetty, Ranjitha S.; Shibuya, Kenji, Shirkoohi, Reza, Shirzad-Aski, Hesamaddin, Shivakumar, K. M.; Shivalli, Siddharudha, Shivarov, Velizar, Shobeiri, Parnian, Shokri Varniab, Zahra, Shorofi, Seyed Afshin, Shrestha, Sunil, Sibhat, Migbar Mekonnen, Siddappa Malleshappa, Sudeep K.; Sidemo, Negussie Boti, Silva, Diego Augusto Santos, Silva, Luís Manuel Lopes Rodrigues, Silva Julian, Guilherme, Silvestris, Nicola, Simegn, Wudneh, Singh, Achintya Dinesh, Singh, Ambrish, Singh, Garima, Singh, Harpreet, Singh, Jasvinder A.; Singh, Jitendra Kumar, Singh, Paramdeep, Singh, Surjit, Sinha, Dhirendra Narain, Sinke, Abiy H.; Siraj, Md Shahjahan, Sitas, Freddy, Siwal, Samarjeet Singh, Skryabin, Valentin Yurievich, Skryabina, Anna Aleksandrovna, Socea, Bogdan, Soeberg, Matthew J.; Sofi-Mahmudi, Ahmad, Solomon, Yonatan, Soltani-Zangbar, Mohammad Sadegh, Song, Suhang, Song, Yimeng, Sorensen, Reed J. D.; Soshnikov, Sergey, Sotoudeh, Houman, Sowe, Alieu, Sufiyan, Mu'awiyyah Babale, Suk, Ryan, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sultana, Saima, Sur, Daniel, Szócska, Miklós, Tabaeian, Seidamir Pasha, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabuchi, Takahiro, Tadbiri, Hooman, Taheri, Ensiyeh, Taheri, Majid, Taheri Soodejani, Moslem, Takahashi, Ken, Talaat, Iman M.; Tampa, Mircea, Tan, Ker-Kan, Tat, Nathan Y.; Tat, Vivian Y.; Tavakoli, Ahmad, Tavakoli, Arash, Tehrani-Banihashemi, Arash, Tekalegn, Yohannes, Tesfay, Fisaha Haile, Thapar, Rekha, Thavamani, Aravind, Thoguluva Chandrasekar, Viveksandeep, Thomas, Nihal, Thomas, Nikhil Kenny, Ticoalu, Jansje Henny Vera, Tiyuri, Amir, Tollosa, Daniel Nigusse, Topor-Madry, Roman, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Traini, Eugenio, Tran, Mai Thi Ngoc, Tripathy, Jaya Prasad, Ukke, Gebresilasea Gendisha, Ullah, Irfan, Ullah, Saif, Ullah, Sana, Unnikrishnan, Bhaskaran, Vacante, Marco, Vaezi, Maryam, Valadan Tahbaz, Sahel, Valdez, Pascual R.; Vardavas, Constantine, Varthya, Shoban Babu, Vaziri, Siavash, Velazquez, Diana Zuleika, Veroux, Massimiliano, Villeneuve, Paul J.; Violante, Francesco S.; Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vo, Bay, Vu, Linh Gia, Wadood, Abdul Wadood, Waheed, Yasir, Walde, Mandaras Tariku, Wamai, Richard G.; Wang, Cong, Wang, Fang, Wang, Ning, Wang, Yu, Ward, Paul, Waris, Abdul, Westerman, Ronny, Wickramasinghe, Nuwan Darshana, Woldemariam, Melat, Woldu, Berhanu, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Yadav, Lalit, Yahyazadeh Jabbari, Seyed Hossein, Yang, Lin, Yazdanpanah, Fereshteh, Yeshaw, Yigizie, Yismaw, Yazachew, Yonemoto, Naohiro, Younis, Mustafa Z.; Yousefi, Zabihollah, Yousefian, Fatemeh, Yu, Chuanhua, Yu, Yong, Yunusa, Ismaeel, Zahir, Mazyar, Zaki, Nazar, Zaman, Burhan Abdullah, Zangiabadian, Moein, Zare, Fariba, Zare, Iman, Zareshahrabadi, Zahra, Zarrintan, Armin, Zastrozhin, Mikhail Sergeevich, Zeineddine, Mohammad A.; Zhang, Dongyu, Zhang, Jianrong, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhou, Linghui, Zodpey, Sanjay, Zoladl, Mohammad, Vos, Theo, Hay, Simon I.; Force, Lisa M.; Murray, Christopher J. L..
The Lancet ; 400(10352):563-591, 2022.
Article in English | ProQuest Central | ID: covidwho-1991370

ABSTRACT

Summary Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk–outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4·45 million (95% uncertainty interval 4·01–4·94) deaths and 105 million (95·0–116) DALYs for both sexes combined, representing 44·4% (41·3–48·4) of all cancer deaths and 42·0% (39·1–45·6) of all DALYs. There were 2·88 million (2·60–3·18) risk-attributable cancer deaths in males (50·6% [47·8–54·1] of all male cancer deaths) and 1·58 million (1·36–1·84) risk-attributable cancer deaths in females (36·3% [32·5–41·3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20·4% (12·6–28·4) and DALYs by 16·8% (8·8–25·0), with the greatest percentage increase in metabolic risks (34·7% [27·9–42·8] and 33·3% [25·8–42·0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Funding Bill & Melinda Gates Foundation.

2.
Can J Anaesth ; 2022 Aug 09.
Article in English | MEDLINE | ID: covidwho-1982372

ABSTRACT

PURPOSE: Older critically ill patients with COVID-19 have been the most vulnerable during the ongoing pandemic, with men being more prone to hospitalization and severe disease than women. We aimed to explore sex-specific differences in treatment and outcome after intensive care unit (ICU) admission in this cohort. METHODS: We performed a sex-specific analysis in critically ill patients ≥ 70 yr of age with COVID-19 who were included in the international prospective multicenter COVIP study. All patients were analyzed for ICU admission and treatment characteristics. We performed a multilevel adjusted regression analysis to elucidate associations of sex with 30-day mortality. RESULTS: A total of 3,159 patients (69.8% male, 30.2% female; median age, 75 yr) were included. Male patients were significantly fitter than female patients as determined by the Clinical Frailty Scale (fit, 67% vs 54%; vulnerable, 14% vs 19%; frail, 19% vs 27%; P < 0.001). Male patients more often underwent tracheostomy (20% vs 14%; odds ratio [OR], 1.57; P < 0.001), vasopressor therapy (69% vs 62%; OR, 1.25; P = 0.02), and renal replacement therapy (17% vs 11%; OR, 1.96; P < 0.001). There was no difference in mechanical ventilation, life-sustaining treatment limitations, and crude 30-day mortality (50% male vs 49% female; OR, 1.11; P = 0.19), which remained true after adjustment for disease severity, frailty, age and treatment limitations (OR, 1.17; 95% confidence interval, 0.94 to 1.45; P = 0.16). CONCLUSION: In this analysis of sex-specific treatment characteristics and 30-day mortality outcomes of critically ill patients with COVID-19 ≥ 70 yr of age, we found more tracheostomy and renal replacement therapy in male vs female patients, but no significant association of patient sex with 30-day mortality. STUDY REGISTRATION: www. CLINICALTRIALS: gov (NCT04321265); registered 25 March 2020).


RéSUMé: OBJECTIF: Les patients âgés gravement malades atteints de la COVID-19 ont été les plus vulnérables pendant la pandémie actuelle, les hommes étant plus sujets à l'hospitalisation et aux maladies graves que les femmes. Nous avons cherché à explorer les différences spécifiques au sexe dans le traitement et les devenirs après l'admission à l'unité de soins intensifs (USI) dans cette cohorte. MéTHODE: Nous avons effectué une analyse spécifique au sexe chez des patients gravement malades âgés de ≥ 70 ans atteints de COVID-19 qui ont été inclus dans l'étude prospective multicentrique internationale COVIP. Tous les patients ont été analysés pour connaître les détails de leur admission à l'USI et les caractéristiques de leur traitement. Nous avons réalisé une analyse de régression ajustée à plusieurs niveaux pour élucider les associations entre le sexe et la mortalité à 30 jours. RéSULTATS: Au total, 3159 patients (69,8 % d'hommes, 30,2 % de femmes; âge médian, 75 ans) ont été inclus. Les patients de sexe masculin étaient significativement plus en forme que les patientes, tel que déterminé par l'échelle de fragilité clinique (bonne santé, 67 % vs 54 %; vulnérables, 14 % vs 19 %; fragiles, 19 % vs 27 %; P < 0,001). Les patients de sexe masculin ont plus souvent bénéficié d'une trachéostomie (20 % vs 14 %; rapport de cotes [RC], 1,57; P < 0,001), d'un traitement vasopresseur (69 % vs 62 %; RC, 1,25; P = 0,02) et d'un traitement substitutif de l'insuffisance rénale (17 % vs 11 %; RC, 1,96; P < 0,001). Il n'y avait aucune différence en matière de ventilation mécanique, de limites des traitements de maintien en vie et de mortalité brute à 30 jours (50 % d'hommes vs 49 % de femmes; RC, 1,11; P = 0,19), ce qui est demeuré le cas après ajustement pour tenir compte de la gravité de la maladie, de la fragilité, de l'âge et des limites du traitement (RC, 1,17 ; intervalle de confiance à 95 %, 0,94 à 1,45; P = 0,16). CONCLUSION: Dans cette analyse des caractéristiques de traitement spécifiques au sexe et des résultats de mortalité à 30 jours des patients gravement malades atteints de COVID-19 de ≥ 70 ans, nous avons noté un nombre plus élevé de trachéotomies et de traitements substitutifs de l'insuffisance rénale chez les hommes vs les femmes, mais aucune association significative entre le sexe des patients et la mortalité à 30 jours. ENREGISTREMENT DE L'éTUDE: www.ClinicalTrials.gov (NCT04321265); enregistré le 25 mars 2020.

4.
J Crit Care ; 71: 154050, 2022 May 04.
Article in English | MEDLINE | ID: covidwho-1819524

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, intensive care units (ICU) introduced restrictions to in-person family visiting to safeguard patients, healthcare personnel, and visitors. METHODS: We conducted a web-based survey (March-July 2021) investigating ICU visiting practices before the pandemic, at peak COVID-19 ICU admissions, and at the time of survey response. We sought data on visiting policies and communication modes including use of virtual visiting (videoconferencing). RESULTS: We obtained 667 valid responses representing ICUs in all continents. Before the pandemic, 20% (106/525) had unrestricted visiting hours; 6% (30/525) did not allow in-person visiting. At peak, 84% (558/667) did not allow in-person visiting for patients with COVID-19; 66% for patients without COVID-19. This proportion had decreased to 55% (369/667) at time of survey reporting. A government mandate to restrict hospital visiting was reported by 53% (354/646). Most ICUs (55%, 353/615) used regular telephone updates; 50% (306/667) used telephone for formal meetings and discussions regarding prognosis or end-of-life. Virtual visiting was available in 63% (418/667) at time of survey. CONCLUSIONS: Highly restrictive visiting policies were introduced at the initial pandemic peaks, were subsequently liberalized, but without returning to pre-pandemic practices. Telephone became the primary communication mode in most ICUs, supplemented with virtual visits.

5.
PLoS One ; 17(4): e0267426, 2022.
Article in English | MEDLINE | ID: covidwho-1817496

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic may have a potentially serious effect on mental health and increase the risk of anxiety, depression, and post-traumatic stress disorders in people. In this study, we aimed to determine the prevalence of psychological illness and the impact of the COVID-19 pandemic on the Libyan population's mental health. METHOD: A cross-sectional survey, conducted in both online and paper modes and consisting of five sections, was completed in more than 30 cities and towns across Libya. The first section consisted of questions on basic demographic characteristics. The second section contained a survey related to the lockdown status, activities, related stress levels, and quarantine. The third section comprised the self-administered 9-item Patient Health Questionnaire (PHQ-9). The fourth section contained the 7-item Generalized Anxiety Disorder Scale (GAD-7), and the fifth section contained the Impact of Event Scale-Revised (IES-R). RESULT: Of the 31,557 respondents, 4,280 (13.6%) reported severe depressive symptoms, with a mean [standard deviation (SD)] PHQ-9 score of 8.32 (5.44); 1,767 (5.6%) reported severe anxiety symptoms, with a mean (SD) GAD-7 score of 6 (4.6); and 6,245 (19.8%) of the respondents reported post-traumatic stress disorder (PTSD), with a mean (SD) score of 15.3 (18.85). In multivariate analysis, young age, being female, unmarried, educated, or victims of domestic violence or abuse, work suspension during the pandemic, and having increased workload, financial issues, suicidal thoughts, or a family member with or hospitalized due to COVID-19 were significantly associated with a high likelihood of depressive and anxiety symptoms, as well as PTSD. Internal displacement due to civil war was also associated with PTSD. CONCLUSION: To our knowledge, this is the first study to analyze the psychological impacts of the COVID-19 pandemic and civil war in Libya. Further study on the development of strategies and interventions aimed at reducing the mental disease burden on the Libyan population is warranted.


Subject(s)
COVID-19 , Mental Health , COVID-19/epidemiology , Communicable Disease Control , Cross-Sectional Studies , Female , Humans , Libya/epidemiology , Male , Pandemics
6.
Front Psychol ; 11: 570435, 2020.
Article in English | MEDLINE | ID: covidwho-1792938

ABSTRACT

OBJECTIVE: We aim to determine the psychological status of medical students during the COVID-19 outbreak and civil war in Libya. METHODS: A cross-sectional study was conducted among medical students from 15 medical schools between April 20 and May 1, 2020. The demographic characteristics, generalized anxiety disorder 7-item (GAD-7) scale, and patient health questionnaire (PHQ-9) results were collected. RESULTS: Of the 3,500 students, 2,430 completed the survey. The mean (± SD) score of anxiety symptoms determined by the GAD-7 was 7.2 (5.1). A total of 268 (11%) students had a GAD-7 score of ≥15, which is indicative of moderate to severe anxiety. A total of 1,568 (64.5%) students showed different degrees of anxiety: mild, 910 (37.5%); moderate, 390 (16%); and severe, 268 (11%). Anxiety was significantly associated with living status and internal displacement (P < 0.05). The mean (+ SD) score of depressive symptoms determined by the PHQ-9 was 9.7 (6.3). A total of 525 (21.6%) students had a PHQ-9 score of ≥15, which is indicative of moderate to severe depression. A total of 1,896 (88%) students were diagnosed with mild (PHQ ≥ 5) depression. Suicidal ideation was present in 552 patients (22.7%). Depression was only statistically associated with the year of study (P = 0.009). CONCLUSION: These data highlight that medical students in Libya are at risk for depression, especially under the current stressful environment of the civil war and the COVID-19 outbreak.

7.
J Intern Med ; 292(3): 438-449, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1774862

ABSTRACT

BACKGROUND: Previous studies reported regional differences in end-of-life care (EoLC) for critically ill patients in Europe. OBJECTIVES: The purpose of this post-hoc analysis of the prospective multicentre COVIP study was to investigate variations in EoLC practices among older patients in intensive care units during the coronavirus disease 2019 pandemic. METHODS: A total of 3105 critically ill patients aged 70 years and older were enrolled in this study (Central Europe: n = 1573; Northern Europe: n = 821; Southern Europe: n = 711). Generalised estimation equations were used to calculate adjusted odds ratios (aORs) to population averages. Data were adjusted for patient-specific variables (demographic, disease-specific) and health economic data (gross domestic product, health expenditure per capita). The primary outcome was any treatment limitation, and 90-day mortality was a secondary outcome. RESULTS: The frequency of the primary endpoint (treatment limitation) was highest in Northern Europe (48%), intermediate in Central Europe (39%) and lowest in Southern Europe (24%). The likelihood for treatment limitations was lower in Southern than in Central Europe (aOR 0.39; 95% confidence interval [CI] 0.21-0.73; p = 0.004), even after multivariable adjustment, whereas no statistically significant differences were observed between Northern and Central Europe (aOR 0.57; 95%CI 0.27-1.22; p = 0.15). After multivariable adjustment, no statistically relevant mortality differences were found between Northern and Central Europe (aOR 1.29; 95%CI 0.80-2.09; p = 0.30) or between Southern and Central Europe (aOR 1.07; 95%CI 0.66-1.73; p = 0.78). CONCLUSION: This study shows a north-to-south gradient in rates of treatment limitation in Europe, highlighting the heterogeneity of EoLC practices across countries. However, mortality rates were not affected by these results.


Subject(s)
COVID-19 , Terminal Care , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/therapy , Critical Illness/epidemiology , Critical Illness/therapy , Europe/epidemiology , Humans , Intensive Care Units , Prospective Studies
8.
JMIR Med Inform ; 10(3): e32949, 2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1770908

ABSTRACT

BACKGROUND: The COVID-19 pandemic caused by SARS-CoV-2 is challenging health care systems globally. The disease disproportionately affects the elderly population, both in terms of disease severity and mortality risk. OBJECTIVE: The aim of this study was to evaluate machine learning-based prognostication models for critically ill elderly COVID-19 patients, which dynamically incorporated multifaceted clinical information on evolution of the disease. METHODS: This multicenter cohort study (COVIP study) obtained patient data from 151 intensive care units (ICUs) from 26 countries. Different models based on the Sequential Organ Failure Assessment (SOFA) score, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB) were derived as baseline models that included admission variables only. We subsequently included clinical events and time-to-event as additional variables to derive the final models using the same algorithms and compared their performance with that of the baseline group. Furthermore, we derived baseline and final models on a European patient cohort, which were externally validated on a non-European cohort that included Asian, African, and US patients. RESULTS: In total, 1432 elderly (≥70 years old) COVID-19-positive patients admitted to an ICU were included for analysis. Of these, 809 (56.49%) patients survived up to 30 days after admission. The average length of stay was 21.6 (SD 18.2) days. Final models that incorporated clinical events and time-to-event information provided superior performance (area under the receiver operating characteristic curve of 0.81; 95% CI 0.804-0.811), with respect to both the baseline models that used admission variables only and conventional ICU prediction models (SOFA score, P<.001). The average precision increased from 0.65 (95% CI 0.650-0.655) to 0.77 (95% CI 0.759-0.770). CONCLUSIONS: Integrating important clinical events and time-to-event information led to a superior accuracy of 30-day mortality prediction compared with models based on the admission information and conventional ICU prediction models. This study shows that machine-learning models provide additional information and may support complex decision-making in critically ill elderly COVID-19 patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04321265; https://clinicaltrials.gov/ct2/show/NCT04321265.

9.
Ann Intensive Care ; 12(1): 26, 2022 Mar 18.
Article in English | MEDLINE | ID: covidwho-1753126

ABSTRACT

PURPOSE: Critically ill old intensive care unit (ICU) patients suffering from Sars-CoV-2 disease (COVID-19) are at increased risk for adverse outcomes. This post hoc analysis investigates the association of the Activities of Daily Living (ADL) with the outcome in this vulnerable patient group. METHODS: The COVIP study is a prospective international observational study that recruited ICU patients ≥ 70 years admitted with COVID-19 (NCT04321265). Several parameters including ADL (ADL; 0 = disability, 6 = no disability), Clinical Frailty Scale (CFS), SOFA score, intensive care treatment, ICU- and 3-month survival were recorded. A mixed-effects Weibull proportional hazard regression analyses for 3-month mortality adjusted for multiple confounders. RESULTS: This pre-specified analysis included 2359 patients with a documented ADL and CFS. Most patients evidenced independence in their daily living before hospital admission (80% with ADL = 6). Patients with no frailty and no disability showed the lowest, patients with frailty (CFS ≥ 5) and disability (ADL < 6) the highest 3-month mortality (52 vs. 78%, p < 0.001). ADL was independently associated with 3-month mortality (ADL as a continuous variable: aHR 0.88 (95% CI 0.82-0.94, p < 0.001). Being "disable" resulted in a significant increased risk for 3-month mortality (aHR 1.53 (95% CI 1.19-1.97, p 0.001) even after adjustment for multiple confounders. CONCLUSION: Baseline Activities of Daily Living (ADL) on admission provides additional information for outcome prediction, although most critically ill old intensive care patients suffering from COVID-19 had no restriction in their ADL prior to ICU admission. Combining frailty and disability identifies a subgroup with particularly high mortality. TRIAL REGISTRATION NUMBER: NCT04321265.

10.
ESC Heart Fail ; 9(3): 1756-1765, 2022 06.
Article in English | MEDLINE | ID: covidwho-1739148

ABSTRACT

AIMS: Chronic heart failure (CHF) is a major risk factor for mortality in coronavirus disease 2019 (COVID-19). This prospective international multicentre study investigates the role of pre-existing CHF on clinical outcomes of critically ill old (≥70 years) intensive care patients with COVID-19. METHODS AND RESULTS: Patients with pre-existing CHF were subclassified as having ischaemic or non-ischaemic cardiac disease; patients with a documented ejection fraction (EF) were subclassified according to heart failure EF: reduced (HFrEF, n = 132), mild (HFmrEF, n = 91), or preserved (HFpEF, n = 103). Associations of heart failure characteristics with the 30 day mortality were analysed in univariate and multivariate logistic regression analyses. Pre-existing CHF was reported in 566 of 3917 patients (14%). Patients with CHF were older, frailer, and had significantly higher SOFA scores on admission. CHF patients showed significantly higher crude 30 day mortality [60% vs. 48%, P < 0.001; odds ratio 1.87, 95% confidence interval (CI) 1.5-2.3] and 3 month mortality (69% vs. 56%, P < 0.001). After multivariate adjustment for confounders (SOFA, age, sex, and frailty), no independent association of CHF with mortality remained [adjusted odds ratio (aOR) 1.2, 95% CI 0.5-1.5; P = 0.137]. More patients suffered from pre-existing ischaemic than from non-ischaemic disease [233 vs. 328 patients (n = 5 unknown aetiology)]. There were no differences in baseline characteristics between ischaemic and non-ischaemic disease or between HFrEF, HFmrEF, and HFpEF. Crude 30 day mortality was significantly higher in HFrEF compared with HFpEF (64% vs. 48%, P = 0.042). EF as a continuous variable was not independently associated with 30 day mortality (aOR 0.98, 95% CI 0.9-1.0; P = 0.128). CONCLUSIONS: In critically ill older COVID-19 patients, pre-existing CHF was not independently associated with 30 day mortality. TRIAL REGISTRATION NUMBER: NCT04321265.


Subject(s)
COVID-19 , Heart Failure , COVID-19/complications , COVID-19/epidemiology , Chronic Disease , Critical Care , Critical Illness , Heart Failure/complications , Heart Failure/epidemiology , Hospitalization , Humans , Prognosis , Prospective Studies , Stroke Volume
11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-323810

ABSTRACT

Background: The Covid-19 pandemic led to significant changes and disruptions to medical education worldwide. We evaluated medical student perceived views on training, their experiences and changes to teaching methods during the pandemic. Methods: An online survey of medical students was conducted in the Autumn of 2020. An international network of collaborators facilitated participant recruitment. Students were surveyed on their perceived overall impact of Covid-19 on their training and several exposure variables. Univariate analyses and adjusted multivariable analysis were performed to determine strengths in associations. Results: A total of 1604 eligible participants from 45 countries took part in this survey and 56.3% (n=860) of these were female. The median age was 21 (Inter Quartile Range:21-23). Nearly half (49.6%, n=796) of medical students were in their clinical years. The majority (n=1356, 84.5%) were residents of a low or middle income country. A total of 1305 (81.4%) participants reported that the Covid-19 pandemic had an overall negative impact on their training. On adjusted analysis, being 21 or younger, females, those reporting a decline in conventional lectures and ward based teaching were more likely to report an overall negative impact on their training ( p≤ 0.001). However, an increase in clinical responsibilities was associated with lower odds of participants reporting a negative impact on training ( p <0.001). The participant’s resident nation economy and stage of training were associated with some of the participant training experiences surveyed ( p <0.05). Conclusion: Medical students reported an overall significant negative impact of the Covid-19 pandemic on their undergraduate training. The efficacy of novel virtual methods of teaching to supplement traditional teaching methods warrants further research.

12.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-313582

ABSTRACT

Background: The COVID-19 pandemic has led highly developed healthcare systems to the brink of collapse due to the large numbers of patients being admitted into hospitals. One of the potential prognostic indicators in patients with COVID-19 is frailty. The degree of frailty could be used to assist both the triage into intensive care, and decisions regarding treatment limitations. Our study sought to determine the interaction of frailty and age in elderly COVID-19 ICU patients. Methods: A prospective multi-centre study of COVID-19 patients ≥ 70 years admitted to intensive care in 138 ICUs from 28 countries was conducted. The primary endpoint was 30-day mortality. Frailty was assessed using the Clinical Frailty Scale (CFS). Additionally, comorbidities, management strategies and treatment limitations were recorded. Results: The study included 1346 patients (28% female) with a median age of 75 years (IQR 72-78, range 70-96), 16.3% were older than 80 years and 21% of the patients were frail. The overall survival at 30 days was 59% (95%CI 56-62), with 66% (63-69) in fit, 53% (47-61) in vulnerable and 41% (35-47) in frail patients (p<0.001). In frail patients, there was no difference in 30 day survival between different age categories. Frailty was linked to an increased use of treatment limitations and less use of mechanical ventilation. In a model controlling for age, disease severity, sex, treatment limitations and comorbidities, frailty was independently associated with lower survival. Conclusion: Frailty provides relevant prognostic information in elderly COVID-19 patients in addition to age and comorbidities.

13.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-308691

ABSTRACT

Abstract Introduction The COVID-19 pandemic has resulted in a significant burden on healthcare systems causing disruption to medical and surgical training of doctors globally. Aims and objectives This is the first international survey assessing the perceived impact of the COVID-19 pandemic on training of doctors of all grades and specialties. Methods An online global survey was disseminated using Survey Monkey® between 4th August 2020 and 17th November 2020. A global network of collaborators facilitated participant recruitment. Data was collated anonymously with informed consent and analysed using univariate and adjusted multivariable analysis. Results 743 doctors of median age 27 (IQR: 25-30) were included with the majority (56.8%, n=422) being male. Two-thirds of doctors were in a training post (66.5%, n=494), 52.9% (n=393) in a surgical specialty and 53.0% (n= 394) in low- and middle-income countries. 69.2% (n=514) reported an overall perceived negative impact of the COVID-19 pandemic on their training. A significant decline was noted among non-virtual teaching methods such as face-to-face lectures, tutorials, ward-based teaching, theatre sessions, conferences, simulation sessions and morbidity and mortality meetings (p≤0.05). Doctors from low or middle-income countries were associated with perceived inadequate supervision while performing invasive procedures under general, local or regional anaesthetic. (p≤0.05) Conclusion In addition to the detrimental impact of the COVID-19 pandemic on healthcare infrastructure, there has been an indirect consequence of disrupted training within medical and surgical subspecialties. A focus on reconfiguration of training programs through a variety of additional resources will become imperative to reduce the long-term sequalae of COVID-19 on doctors’ training.

14.
Age Ageing ; 51(2)2022 02 02.
Article in English | MEDLINE | ID: covidwho-1684499

ABSTRACT

BACKGROUND: health-related quality of life (HRQoL) is an important patient-centred outcome in patients surviving ICU admission for COVID-19. It is currently not clear which domains of the HRQoL are most affected. OBJECTIVE: to quantify HRQoL in order to identify areas of interventions. DESIGN: prospective observation study. SETTING: admissions to European ICUs between March 2020 and February 2021. SUBJECTS: patients aged 70 years or older admitted with COVID-19 disease. METHODS: collected determinants include SOFA-score, Clinical Frailty Scale (CFS), number and timing of ICU procedures and limitation of care, Katz Activities of Daily Living (ADL) dependence score. HRQoL was assessed at 3 months after ICU admission with the Euro-QoL-5D-5L questionnaire. An outcome of ≥4 on any of Euro-QoL-5D-5L domains was considered unfavourable. RESULTS: in total 3,140 patients from 14 European countries were included in this study. Three months after inclusion, 1,224 patients (39.0%) were alive and the EQ-5D-5L from was obtained. The CFS was associated with an increased odds ratio for an unfavourable HRQoL outcome after 3 months; OR 1.15 (95% confidence interval (CI): 0.71-1.87) for CFS 2 to OR 4.33 (95% CI: 1.57-11.9) for CFS ≧ 7. The Katz ADL was not statistically significantly associated with HRQoL after 3 months. CONCLUSIONS: in critically ill old intensive care patients suffering from COVID-19, the CFS is associated with the subjectively perceived quality of life. The CFS on admission can be used to inform patients and relatives on the risk of an unfavourable qualitative outcome if such patients survive.


Subject(s)
COVID-19 , Quality of Life , Activities of Daily Living , Aged , Humans , Intensive Care Units , Prospective Studies , SARS-CoV-2
15.
J Med Internet Res ; 23(2): e20812, 2021 02 25.
Article in English | MEDLINE | ID: covidwho-1574241

ABSTRACT

BACKGROUND: Since the onset of the COVID-19 pandemic, several health care programs intended to provide telemedicine services have been introduced in Libya. Many physicians have used these services to provide care and advice to their patients remotely. OBJECTIVE: This study aimed to provide an overview of physicians' awareness, knowledge, attitude, and skill in using telehealth services in Libya. METHODS: In this cross-sectional study, we administered a web-based survey to health care workers in Libya in May 2020. The questionnaire collected information on physicians' general demographic characteristics, ability to use a computer, and telemedicine awareness, knowledge, attitude, and skills. RESULTS: Among 673 health care workers who responded to the survey, 377 (56%) and 248 (36.8%) reported high awareness and high computer skill scores, respectively, for telemedicine. Furthermore, 582 (86.5%) and 566 (82.6%) health care workers reported high knowledge and high attitude scores, respectively. We observed no significant differences in awareness, knowledge, attitude, and skill scores among physicians employed at public, private, or both types of hospitals. We observed significant differences in the mean awareness (P<.001), attitude (P=.001), and computer skill scores (P<.001) , where the score distribution of the groups based on the ability to use computers was not similar. Knowledge scores did not significantly differ among the three groups (P=.37). Respondents with professional computer skills had significantly higher awareness (χ23=14.5; P<.001) and attitude (χ23=13.5; P=.001) scores than those without professional computer skills. We observed significant differences in the mean computer skill scores of the groups (χ23=199.6; P<.001). CONCLUSIONS: The consequences of the COVID-19 pandemic are expected to persist for a long time. Hence, policy programs such as telemedicine services, which aim to address the obstacles to medical treatment owing to physical distancing measures, will likely continue for a long time. Therefore, there is a need to train and support health care workers and initiate government programs that provide adequate and supportive health care services to patients in transitional countries.


Subject(s)
COVID-19/epidemiology , Health Knowledge, Attitudes, Practice , Telemedicine/methods , Adult , COVID-19/therapy , Cross-Sectional Studies , Developing Countries , Female , Health Personnel , Humans , Male , Pandemics , SARS-CoV-2/isolation & purification
16.
Front Med (Lausanne) ; 8: 735860, 2021.
Article in English | MEDLINE | ID: covidwho-1518494

ABSTRACT

Background: Data regarding delivery of evidence-based care to critically ill patients in Intensive Care Units (ICU) during the COVID-19 pandemic is crucial but lacking. This study aimed to evaluate the implementation rate of the ABCDEF bundle, which is a collection of six evidence-based ICU care initiatives which are strongly recommended to be incorporated into clinical practice, and ICU diaries for patients with and without COVID-19 infections in ICUs, and to analyze the impact of COVID-19 on implementation of each element of the bundle and independent associated factors. Methods: A world-wide 1-day point prevalence study investigated the delivery of the ABCDEF bundle and ICU diary to patients without or with COVID-19 infections on 27 January 2021 via an online questionnaire. Multivariable logistic regression analysis with adjustment for patient demographics evaluated the impact of COVID-19 and identified factors in ICU administrative structures and policies independently associated with delivery. Results: From 54 countries and 135 ICUs, 1,229 patients were eligible, and 607 (49%) had COVID-19 infections. Implementation rates were: entire bundle (without COVID-19: 0% and with COVID-19: 1%), Element A (regular pain assessment: 64 and 55%), Element B (both spontaneous awakening and breathing trials: 17 and 10%), Element C (regular sedation assessment: 45 and 61%), Element D (regular delirium assessment: 39 and 35%), Element E (exercise: 22 and 25%), Element F (family engagement/empowerment: 16 and 30%), and ICU diary (17 and 21%). The presence of COVID-19 was not associated with failure to implement individual elements. Independently associated factors for each element in common between the two groups included presence of a specific written protocol, application of a target/goal, and tele-ICU management. A lower income status country and a 3:1 nurse-patient ratio were significantly associated with non-implementation of elements A, C, and D, while a lower income status country was also associated with implementation of element F. Conclusions: Regardless of COVID-19 infection status, implementation rates for the ABCDEF bundle, for each element individually and an ICU diary were extremely low for patients without and with COVID-19 infections during the pandemic. Strategies to facilitate implementation of and adherence to the complete ABCDEF bundle should be optimized and addressed based on unit-specific barriers and facilitators.

17.
Clin Hemorheol Microcirc ; 79(1): 109-120, 2021.
Article in English | MEDLINE | ID: covidwho-1477773

ABSTRACT

PURPOSECritically ill elderly patients who suffer from Sars-CoV-2 disease are at high risk for organ failure. The modified MELD-XI score has not been evaluated for outcome prediction in these most vulnerable patients.METHODSThe Corona Virus disease (COVID19) in Very Elderly Intensive Care Patients study (COVIP, NCT04321265) prospectively recruited patients on intensive care units (ICU), who were = 70 years. Data were collected from March 2020 to February 2021. The MELD-XI score was calculated using the highest serum bilirubin and creatinine on ICU admission. Univariate and multivariable logistic regression analyses were performed to assess associations between the MELD-XI score and mortality. The primary outcome was 30-day-mortality, the secondary outcomes were ICU- and 3-month-mortality.RESULTSIn total, data from 2,993 patients were analyzed. Most patients had a MELD-XI <12 on admission (76%). The patients with MELD-XI = 12 had a significantly higher 30-day-, ICU- and 3-month-mortality (44%vs 64%, and 42%vs. 59%, and 57%vs. 76%, p < 0.001). After adjustment for multiple confounders, MELD-XI = 12 remained significantly associated with 30-day- (aOR 1.572, CI 1.268-1.949, p < 0.001), ICU-, and 3-month-mortality.CONCLUSIONIn critically ill elderly intensive care patients with COVID-19, the MELD-XI score constitutes a valuable tool for an early outcome prediction.


Subject(s)
COVID-19 , Critical Illness , Aged , Humans , Prognosis , SARS-CoV-2 , Severity of Illness Index
18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-291174

ABSTRACT

Background: Although the number of patients with COVID-19 infection is increasing and concerns for their long-term disabilities are increasing, there is a lack of data about the delivery of the ABCDEF-bundle and supportive care in Intensive Care Units (ICUs). The aim of this study is to investigate the implementation of the ABCDEF-bundle and supportive care provided to patients with COVID-19 infections in ICUs. Methods: This was a world-wide two-day point prevalence study, on June 3 and July 1, 2020. A total of 212 ICUs in 38 countries (166 ICUs on Day 1 and 212 on Day 2) participated. Clinicians in each participating ICU completed web-based online surveys. The implementation rate for elements of the ABCDEF-bundle, other supportive ICU care measures and implementation associated structures were investigated. RESULTS Data for 262 patients was collected during the two-day study. Of patients included, 124 (47.3%) underwent mechanical ventilation (MV) and 12 (4.6%) patients were treated with extracorporeal membrane oxygenation (ECMO). The proportion of patients with implementation of each element was: Element A (regular pain assessment) 45%;B (both spontaneous awakening and breathing trials) 28%;C (regular sedation assessment) 52%;D (regular delirium assessment) 38%;E (early mobility and exercise) 47%;and F (family engagement and empowerment) 16%. The implementation of element E for patients on MV was 16% and ECMO was 17%. Supportive care, such as providing protein throughout the ICU stay (under 1.2g/kg for more than 50% of the patients) and introduction of an ICU diary (25%) was inadequate. A higher implementation rate of elements A and D were recognized in ICUs with specific protocols for ICU care and lower numbers of ICU beds exclusively for patients with COVID-19 infection. Element E was implemented at a higher rate in ICUs with more ICU beds for patients with COVID-19 infection. CONCLUSIONS This worldwide two-day point prevalence study found low implementation of the ABCDEF-bundle. Specific protocols and the number of ICU beds reserved for patients with COVID-19 infections might be key factors to deliver appropriate supportive care.Trial registration: UMIN, UMIN000040405. Registered 14 May 2020, https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000046103

19.
J Med Case Rep ; 15(1): 461, 2021 Sep 09.
Article in English | MEDLINE | ID: covidwho-1403258

ABSTRACT

INTRODUCTION: We report a case of Severe acute respiratory syndrome coronavirus-2 infection with acute pancreatitis as the only presenting symptom. To the best of our knowledge, there are few case reports of the same presentation. CASE PRESENTATION: An otherwise healthy 44-year-old white male from Egypt presented to the hospital with severe epigastric pain and over ten attacks of nonprojectile vomiting (first, gastric content, then bilious). Acute pancreatitis was suspected and confirmed by serum amylase, serum lipase, and computed tomography scan that showed mild diffuse enlargement of the pancreas. The patient did not have any risk factor for acute pancreatitis, and extensive investigations did not reveal a clear etiology. Given a potential occupational exposure, a nasopharyngeal swab for polymerase chain reaction testing for severe acute respiratory syndrome coronavirus 2 was done, which was positive despite the absence of the typical symptoms of severe acute respiratory syndrome coronavirus 2 such as fever and respiratory symptoms. The patient was managed conservatively. For pancreatitis, he was kept nil per os for 2 days and received intravenous lactated Ringer's (10 ml per kg per hour), nalbuphine, alpha chymotrypsin, omeprazole, and cyclizine lactate. For severe acute respiratory syndrome coronavirus 2, he received a 5-day course of intravenous azithromycin (500 mg per day). He improved quickly and was discharged by the fifth day. We know that abdominal pain is not a rare symptom of severe acute respiratory syndrome coronavirus 2, and we also know that elevated levels of serum amylase and lipase were reported in severe acute respiratory syndrome coronavirus-2 patients, especially those with severe symptoms. However, the association between severe acute respiratory syndrome coronavirus-2 infection and idiopathic acute pancreatitis is rare and has been reported only a few times. CONCLUSION: We believe further studies should be conducted to determine the extent of pancreatic involvement in severe acute respiratory syndrome coronavirus-2 patients and the possible causality between severe acute respiratory syndrome coronavirus 2 and acute pancreatitis. We reviewed the literature regarding the association between severe acute respiratory syndrome coronavirus 2 and acute pancreatitis patients. Published data suggest that severe acute respiratory syndrome coronavirus 2 possibly could be a risk factor for acute pancreatitis.


Subject(s)
COVID-19 , Pancreatitis , Acute Disease , Adult , Humans , Male , Pancreatitis/diagnosis , Pancreatitis/etiology , SARS-CoV-2 , Tomography, X-Ray Computed
20.
Ann Intensive Care ; 11(1): 128, 2021 Aug 21.
Article in English | MEDLINE | ID: covidwho-1367683

ABSTRACT

PURPOSE: Lactate is an established prognosticator in critical care. However, there still is insufficient evidence about its role in predicting outcome in COVID-19. This is of particular concern in older patients who have been mostly affected during the initial surge in 2020. METHODS: This prospective international observation study (The COVIP study) recruited patients aged 70 years or older (ClinicalTrials.gov ID: NCT04321265) admitted to an intensive care unit (ICU) with COVID-19 disease from March 2020 to February 2021. In addition to serial lactate values (arterial blood gas analysis), we recorded several parameters, including SOFA score, ICU procedures, limitation of care, ICU- and 3-month mortality. A lactate concentration ≥ 2.0 mmol/L on the day of ICU admission (baseline) was defined as abnormal. The primary outcome was ICU-mortality. The secondary outcomes 30-day and 3-month mortality. RESULTS: In total, data from 2860 patients were analyzed. In most patients (68%), serum lactate was lower than 2 mmol/L. Elevated baseline serum lactate was associated with significantly higher ICU- and 3-month mortality (53% vs. 43%, and 71% vs. 57%, respectively, p < 0.001). In the multivariable analysis, the maximum lactate concentration on day 1 was independently associated with ICU mortality (aOR 1.06 95% CI 1.02-1.11; p = 0.007), 30-day mortality (aOR 1.07 95% CI 1.02-1.13; p = 0.005) and 3-month mortality (aOR 1.15 95% CI 1.08-1.24; p < 0.001) after adjustment for age, gender, SOFA score, and frailty. In 826 patients with baseline lactate ≥ 2 mmol/L sufficient data to calculate the difference between maximal levels on days 1 and 2 (∆ serum lactate) were available. A decreasing lactate concentration over time was inversely associated with ICU mortality after multivariate adjustment for SOFA score, age, Clinical Frailty Scale, and gender (aOR 0.60 95% CI 0.42-0.85; p = 0.004). CONCLUSION: In critically ill old intensive care patients suffering from COVID-19, lactate and its kinetics are valuable tools for outcome prediction. TRIAL REGISTRATION NUMBER: NCT04321265.

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