Citations

Clear

1587 citation(s) found for "Wei, Wei‐Qi".

Global, Regional, and National Burden of Nontraumatic Subarachnoid Hemorrhage
Collaborators, GBD 2021 Global Subarachnoid Hemorrhage Risk Factors, Rautalin, Ilari, Stark, Benjamin, Johnson, Catherine O., Kaprio, Jaakko , Korja, Miikka, Krishnamurthi, Rita , Nair, Balakrishnan , Vergouwen, Mervyn D. I. , Abdelkader, Atef , Abdullahi, Auwal , Abualruz, Hasan , Abukhadijah, Hana J , Adamu, Lawan Hassan, Adegboye, Oyelola A. , Adzigbli, Leticia Akua, Agyemang‐Duah, Williams , Ahinkorah, Bright Opoku, Ahmad, Aqeel , Ahmad, Danish , Ahmadzade, Amir Mahmoud , Akkaif, Mohammed Ahmed , Ali, Mohammed Usman, Alif, Sheikh Mohammad , Alimohamadi, Yousef, Alsabri, Mohammed , Altaf, Awais , Alvis‐Guzmán, Nelson , Alwafi, Hassan , Al‐Wardat, Mohammad , Alyahya, Mohammad S. , Amin, Tarek Tawfik , Amindarolzarbi, Alireza , Amusa, Ganiyu , Angappan, Dhanalakshmi , Anuoluwa, Boluwatife Stephen, Anwar, Saleha, Anyasodor, Anayochukwu Edward , Apostol, Geminn Louis Carace, Areda, Demelash, Artamonov, Anton A, Artanti, Kurnia Dwi , Ashemo, Mubarek Yesse , Athar, Mohammad , Aujayeb, Avinash , Awotidebe, Adedapo Wasiu , Azadnajafabad, Sina , Aziz, Shahkaar , Bagheri, Nasser , Taqanaki, Pegah Bahrami , Bahramian, Saeed , Bai, Ruhai , Baig, Atif Amin , Baltatu, Ovidiu Constantin , Bam, Kiran, Barker‐Collo, Suzanne , Bärnighausen, Till , Bastan, Mohammad‐Mahdi , Basu, Sanjay , Bell, Shelly L, Benseñor, Isabela M , Berhie, Alemshet Yirga , Bhagavathula, Akshaya Srikanth , Bhaskar, Sonu , Bhat, Ajay Nagesh, Bhat, Vivek , Birhan, Mekuriaw Mesfin , Borhany, Hamed, Breitner, Susanne , Bulamu, Norma B. , Butt, Zahid A , Cabral, Lucas Scotta , Santos, Florentino Luciano Caetano dos , Cámera, Luis Alberto , Capodici, Angelo , Chadwick, Joshua , Chakraborty, Promit Ananyo , Chanie, Gashaw Sisay , Chattu, Vijay Kumar , Chi, Gerald, Chichagi, Fatemeh , Columbus, Alyssa , Criqui, Michael H, Ohadi, Mohammad Amin Dabbagh , Dadras, Omid , Dalli, Lachlan L. , Debopadhaya, Shayom , Dervišević, Emina , Devanbu, Vinoth Gnana Chellaiyan, Dewan, Syed Masudur Rahman , Dhane, Amol S. , Chi, Thanh, Phuong, Thao Huynh, Dohare, Sushil , Докова, Клара , Dowou, Robert Kokou , Dsouza, Haneil Larson , Dutta, Siddhartha , Dziedzic, Arkadiusz , E’mar, Abdel Rahman, Edvardsson, David , Efendi, Ferry, Nahas, Nevine El , Elgendy, Islam Y. , Eltaha, Chadi, Emeto, Theophilus I. , Fakhradiyev, Ildar , Faris, Pawan , Fauk, Nelsensius Klau , Fazylov, Timur, Fekadu, Ginenus , Fetensa, Getahun, Fischer, Florian, Foschi, Matteo , Fridayani, Ni Kadek Yuni, Gaipov, Abduzhappar , Gajjar, Avi A. , Ganesan, Balasankar , Gebregergis, Miglas Welay, Gebremeskel, Teferi Gebru , Getie, Molla , Ghadirian, Fataneh , Ghasemzadeh, Afsaneh , Gholamalizadeh, Maryam , Gil, Artyom , Goleij, Pouya , Goulart, Alessandra C. , Goulart, Bárbara Niegia Garcia de , Guan, Shi‐Yang , Gupta, Sapna , Habibzadeh, Farrokh , Hadi, Najah R, Hankey, Graeme J. , Harlianto, Netanja I. , Hasani, Hamidreza, Hasnain, Md Saquib , Haubold, Johannes , Havmoeller, Rasmus, Hay, Simon I , Hbid, Youssef , Heidari, Golnaz , Hiraike, Yuta, Hoan, Nguyen Quoc , Hosseinzadeh, Mehdi , Hwang, Bing‐Fang , Ibitoye, Segun Emmanuel , Ikiroma, Adalia , Isola, Gaetano , Iwagami, Masao , Jacob, Louis, Jain, Akhil, Jakovljević, Mihajlo , Jatau, Abubakar Ibrahim , Jawaid, Talha, Jayapal, Sathish Kumar , Jonas, Jost B, Joseph, Nitin , Jürisson, Mikk , Kadashetti, Vidya, Kalani, Rizwan, Kamireddy, Arun , Kandel, Himal , Behnagh, Arman Karimi , Kashoo, Faizan , Kayode, Gbenga A , Kazemi, Foad , Khader, Yousef , Khaing, Inn Kynn , Khan, Fayaz Ahmad , Khan, Mohammad Jobair , Kashani, Hamid Reza Khayat , Khosla, Atulya Aman , Kim, Kwanghyun , Kim, Yun Jin , Korzh, Oleksii , Krishan, Kewal , Krishna, Varun, Krishnamoorthy, Vijay , Kuddus, Mohammed , Kulimbet, Mukhtar , Lahariya, Chandrakant, Lai, Daphne Teck Ching , Lai, Hanpeng , Laksono, Tri, Lallukka, Tea , Latifinaibin, Kaveh, Le, Nhi Huu Hanh, Le, Thao T. , Lee, Munjae , Lee, Yo Han , Lenzi, Jacopo , Leonardi, Matilde, Li, Ming‐Chieh , Li, Xiaopan , Lim, Stephen S , Lin, Jialing , Saute, Ricardo Lutzky , Malik, Ahmad Azam , Marateb, Hamid Reza , Maroufi, Seyed Farzad , Maugeri, Andrea , McPhail, Steven , Mehndiratta, Man Mohan, Mestrovic, Tomislav, Mettananda, Chamila Dinushi Kukulege , Miazgowski, Tomasz , Minervini, Giuseppe , Mithra, Prasanna , Mohamed, Abdalla Z. , Mohammad, Ameen Mosa , Mohammed, Shafiu , Moni, Mohammad Ali , Moradi, Yousef, Moraga, Paula , Morawska, Lídia , Munjal, Kavita , Murray, Christopher J L , Nagarajan, Ahamarshan Jayaraman , Naik, Ganesh R. , Najdaghi, Soroush , Davani, Delaram Narimani , DELETE-ME, Nawsherwan, Nazri-Panjaki, Athare , Negoi, Ruxandra Irina , Nematollahi, Soroush , Nguyen, Hau Thi Hien, Nguyen, Hau Thi Hien, Nguyen, Phat Tuan , Nguyễn, Văn Thành , Niazi, Robina Khan, Nikoobar, Ali , Sá, Antonio Tolentino Nogueira de , Nomura, Shuhei , Nzoputam, Chimezie Igwegbe , Oancea, Bogdan , Ojo-Akosile, Tolulope R, Oliveira, Gláucia Maria Moraes de , Olorukooba, Abdulhakeem Abayomi , Osuagwu, Uchechukwu Levi , Ouyahia, Amel, A, Mahesh Padukudru P, Panagiotakos, Demosthenes B. , Parikh, Romil R., Park, Seoyeon , Pedersini, Paolo , Peprah, Emmanuel , Perico, Norberto, Petermann-Rocha, Fanny Emily, Plotnikov, Evgenii , Полибин, Р. В. , Postma, Maarten J. , Prasad, Manya , Qian, Gangzhen , Rahmanian, Mohammad , Rajaa, Sathish , Rajput, Prashant , Ramadan, Mahmoud M. , Rane, Amey, Rashidi, Mohammad‐Mahdi , Razo, Christian , Reddy, Murali Mohan Rama Krishna, Remuzzi, Giuseppe, Rezaei, Negar , Rezaeian, Mohsen , Rocha, Hermano Alexandre Lima , Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo , Romoli, Michele, Romozzi, Marina, Roy, Nitai , Saddik, Basema Ahmad, Sahoo, Pragyan Monalisa , Salaroli, Luciane Bresciani , Samuel, Vijaya Paul, Samy, Abdallah M , Santric-Milicevic, Milena M., Saravanan, Aswini, Schlaich, Markus P. , Sethi, Yashendra , Seylani, Allen, Shaaban, Ahmed Nabil , Shafie, Mahan , Shaikh, Summaiya Zareen , Shamsutdinova, Alfiya, Sharifan, Amin , Rad, Javad Sharifi, Sharma, Vishal, Shashamo, Bereket Beyene , Shetty, Premalatha K, Shigematsu, Mika, Shorofi, Seyed Afshin, Singh, Paramdeep , Singh, Puneetpal , Singh, Surjit , Sobia, Farrukh , Solanki, Shipra, Soraneh, Soroush , Spartalis, Michael, Srinivasamurthy, Suresh Kumar , Stanikzai, Muhammad Haroon , Sun, Zhong , Swain, Chandan Kumar , Damavandi, Payam Tabaee , Tabatabaeizadeh, Seyed-Amir, Tabche, Celine , Taiba, Jabeen , Tamuzi, Jacques Lukenze , Tan, Ker‐Kan , Teramoto, Masayuki , Thakur, Ramna, Thankappan, Kavumpurathu Raman , Thayakaran, Rasiah , Thirunavukkarasu, Sathish, Ticoalu, Jansje Henny Vera, Tiwari, Krishna Raj , Tonelli, Marcello , Topór-Mądry, Roman , Tovani-Palone, Marcos Roberto Roberto, Tran, Jasmine, Tran, Thang Huu , Duc, Nguyen Tran Minh , Truelsen, Thomas Clement, Unim, Brigid, Vahdati, Sanaz, Vaithinathan, Asokan Govindaraj , Eynde, Jef Van den , Vladimirov, Sergey Konstantinovitch , Waheed, Yasir, Wahood, Waseem , Walde, Mandaras Tariku, Wang, Yanzhong , Wickramasinghe, Nuwan Darshana , Wolfe, Charles D. A., Wubie, Yihun Miskir, Xiao, Hong , Xu, Xiaoyue , Yano, Yuichiro , Yarahmadi, Amir , Ye, Pengpeng, Yon, Dong Keon , Zanghì, Aurora , Zare, Iman, Zastrozhin, Michael, Zhang, Zhi-Jiang , Zhang, Zhiqiang , Zhang, Zhiqiang, Zhao, Hanqing , Zhou, Shang Cheng, Zhumagaliuly, Abzal , Zia, Hafsa, Roth, Gregory A., Topór‐Mądry, Roman , Oliveira, Arão Belitardo , Rahim, Fakher , Saddik, Basema , Waheed, Yasir , Liu, Xuefeng , Zhang, Yunquan , Ozair, Ahmad , Buendía, Jefferson Antonio , Korja, Miikka , Baig, Atif Amin , Shanawaz, Mohd , Elgendy, Islam Y , Hankey, Graeme J , Alif, Sheikh M , Rezaei, Negar , Bhagavathula, Akshaya Srikanth , Van den Eynde, Jef , Ozair, Ahmad , Collaborators, GBD 2021 Global Subarachnoid Hemorrhage Risk Factors, Rautalin, Ilari Matias , Volovici, Victor , Ranta, Annemarei , Rinkel, Gabriël J.E. , Abate, Yohannes Habtegiorgis, Abbastabar, Hedayat , Abd-Allah, Foad , Abdi, Parsa , Abdollahi, Arash , Abiodun, Olugbenga Olusola , Aboagye, Richard Gyan , Abouzid, Mohamed , Abtahi, Dariush , Abu‐Rumeileh, Samir , Abualhasan, Ahmed , Abu‐Zaid, Ahmed , Addo, Isaac Yeboah , Adedoyin, Rufus Adesoji , Adra, Saryia , Ahinkorah, Bright Opoku , Ahmed, Ali , Ahmed, Haroon , Ahmed, Syed Anees , Aji, Budi , Al‐Ajlouni, Yazan A. , Al‐Aly, Ziyad , ALBashtawy, Mohammed , Aljunid, Syed Mohamed , Alomari, Mahmoud A. , Alrawashdeh, Ahmad , Alsabri, Mohammed A., Salman, Rustam Al‐Shahi , Al‐Tammemi, Ala’a B. , Al‐Worafi, Yaser Mohammed , Aly, Hany Z. , Alzoubi, Karem Hasan , Amani, Reza, Anderlini, Deanna , Anil, Abhishek , Arabloo, Jalal , Ärnlöv, Johan , Arumugam, Ashokan , Aryan, Zahra , Jafarabadi, Mohammad Asghari , Ashraf, Tahira , Athari, Seyyed Shamsadin , Azzam, Ahmed Y , Babu, Giridhara R. , Bako, Abdulaziz Tijjani , Banach, Maciej , Bandyopadhyay, Soham , Banik, Biswajit , Bardhan, Mainak , Barqawi, Hiba Jawdat , Barua, Lingkan , Beyene, Kebede Abera , Bhat, Vivek, Bhatti, Gurjit Kaur , Bhatti, Jasvinder Singh , Bijani, Ali , Bikbov, Boris , Birhanu, Mulugeta Molla , Bitra, Veera Raghavulu , Boloor, Archith , Brenner, Hermann , Bugiardini, Raffaele , Călina, Daniela Cornelia , Campos, Luciana Aparecida , Campos‐Nonato, Ismael , Carvalho, Félix , Castañeda-Orjuela, Carlos A , Catapano, Alberico Luigi , Cegolon, Luca , Chakraborty, Chiranjib , Chakraborty, Sandip , Chandika, Rama Mohan , Chaudhary, Anis Ahmad , Chi, Gerald , Ching, Patrick R , Chopra, Hitesh , Choudhari, Sonali Gajanan , Chowdhury, E. , Chu, Dinh‐Toi , Chung, Sheng‐Chia , Silva, Alanna Gomes da , Dai, Xiaochen , Dalal, Koustuv , D’Amico, Emanuele , Dashti, Mohsen , Davletov, Kairat , Cruz-Góngora, Vanessa Vianey De la , Delgado‐Enciso, Iván , Devanbu, Vinoth Gnana Chellaiyan, Dibas, Mahmoud , Doheim, Mohamed Fahmy , Dongarwar, Deepa , D’Oria, Mario , Doshi, Ojas Prakashbhai , Doshi, Rajkumar , Efendi, Defi , Efendi, Ferry , Elhadi, Muhammed , Eltahir, Mohd. Elmagzoub , Fabin, Natalia , Fagbamigbe, Adeniyi Francis , Fahim, Ayesha , Fares, Jawad , Ferreira, Nuno Bravo , Gandhi, Aravind P. , Garg, Ravindra Kumar , Gebrehiwot, Mesfin , Ghadimi, Delaram J. , Ghahramani, Sulmaz , Ghazy, Ramy Mohamed , Ghozy, Sherief , Gilani, Jaleed Ahmed , Gnedovskaya, Elena V. , Hadei, Mostafa , Hamidi, Samer , Hanifi, Nasrin , Haro, Josep María , Hasan, Faizul , Tabatabaei, Mahgol Sadat Hassan Zadeh , Heidari, Mohammad , Hemmati, Mehdi , Holla, Ramesh , Hostiuc, Sorin , Huang, Junjie , Huynh, Hong-Han , Ikeda, Nayu , Ilaghi, Mehran , Ilesanmi, Olayinka Stephen , Ilić, Irena , Ilić, Milena , Islam, Md. Rabiul , Ismail, Nahlah Elkudssiah , Iso, Hiroyasu , Jafarzadeh, Abdollah , Jairoun, Ammar Abdulrahman , Kalani, Rizwan, Kamal, Vineet Kumar , Kanchan, Tanuj , Karami, Jafar , Karaye, Ibraheem M. , Karimi, Yeganeh , Kesse‐Guyot, Emmanuelle , Khan, Fayaz, Khatatbeh, Haitham , Khatatbeh, Moawiah Mohammad , Kheirallah, Khalid Ahmed , Khidri, Feriha Fatima , Khormali, Moein , Kısa, Adnan , Kısa, Sezer , Kivimäki, Mika , Kolahi, Ali‐Asghar , Kompani, Farzad , Kostev, Karel , Kothari, Nikhil , Kunutsor, Setor K. , Kurniasari, Maria Dyah , Kusuma, Dian Palupi , Kytö, Ville , Vecchia, Carlo La , Lahariya, Chandrakant , Latief, Kamaluddin , Lee, Seung Won , Lee, Wei‐Chen , Leonardi, Matilde, Liu, Xuefeng , Lohner, Valerie , Lorenzovici, László , Lotufo, Paulo A. , Lucchetti, Giancarlo , Lusk, Jay B. , Amin, Hawraz Ibrahim M. , Malhotra, Armaan Kush , Malhotra, Kashish , Malta, Déborah Carvalho , Mansournia, Mohammad Alì , Mantovani, LG , Manu, Emmanuel, Marino, Mirko , Martínez, Ramón , Martini, Santi , Martorell, Miquel , Marzo, Roy Rillera , Mathangasinghe, Yasith , Mathews, Elezebeth , Mehmood, Asim , Mehrabani-Zeinabad, Kamran , Menezes, Ritesh G. , Meo, Sultan A , Meretoja, Atte , Meštrović, Tomislav , Sá, Ana Carolina Micheletti Gomide Nogueira de , Minh, Le Huu Nhat , Mirică, Andreea , Мirrakhimov, Erkin М , Mirza‐Aghazadeh‐Attari, Mohammad , Mishra, Ajay Kumar , Mohamed, Ahmed Ismail , Mohammadi, Soheil , Mohammadian-Hafshejani, Abdollah , Mokdad, Ali H. , Molinaro, Sabrina , Momani, Shaher , Ghalibaf, AmirAli Moodi , Moradi, Maryam , Msherghi, Ahmed A.A. , Ansari, Noureddin Nakhostin , Nargus, Shumaila , Natto, Zuhair S. , Nauman, Javaid , DELETE-ME, Nawsherwan, Nayak, Vinod C , Newton, Charles R. , Nigatu, Yeshambel T. , Noubiap, Jean Jacques , Nugen, Fred , Oduro, Michael Safo , Okati‐Aliabad, Hassan , Okeke, Sylvester Reuben , Okekunle, Akinkunmi Paul , Olagunju, Andrew T , Olaiya, Muideen Tunbosun , Olufadewa, Isaac Iyinoluwa , Ornello, Raffaele , Ortiz‐Prado, Esteban , Ouyahia, Amel , Owolabi, Mayowa , Padrón‐Monedero, Alicia , Padubidri, Jagadish Rao , Panos, Leonidas D , Pantazopoulos, Ioannis N. , Parikh, Romil R., Patel, Jay , Patel, Urvish , Patoulias, Dimitrios , Pereira, Gavin F , Perianayagam, Arokiasamy , Perna, Simone , Petermann‐Rocha, Fanny , Philip, Anil K. , Пирадов, М. А. , Pradhan, Jalandhar , Puvvula, Jagadeesh , Qasim, Nameer Hashim , Raggi, Alberto , Rahimi‐Movaghar, Vafa , Rahman, Muhammad Aziz , Rahmani, Amir Masoud , Sanati, Ali Rajabpour , Ramasamy, Shakthi Kumaran , Ramazanu, Sheena , Rathish, Devarajan , Rawaf, Salman , Redwan, Elrashdy M , Remuzzi, Giuseppe , Romoli, Michele, Romozzi, Marina , Ross, Allen Guy , Rout, Himanshu Sekhar , Roy, Priyanka , Saad, Aly M A , Saadatian, Zahra , Sabour, Siamak , Sacco, Simona , Sadeghi, Erfan , Saeed, Usman, Sharif‐Askari, Fatemeh Saheb , Sahebkar, Amirhossein , Sajib, Md Refat Uz Zaman , Saleh, Mohamed A. , Samodra, Yoseph Leonardo , MİLİCEVİC, Milena Santric, Saravanan, Aswini , Sarkar, Tanmay, Sarode, Sachin Chakradhar , Sartorius, Benn , Satpathy, Maheswar , Schneider, Ione Jayce Ceola , Schuermans, Art , Selvaraj, Siddharthan , Senthilkumaran, Subramanian , Sepanlou, Sadaf Ghajarieh , Shahwan, Moyad Jamal , Shamim, Muhammad Aaqib , Shamsi, Anas , Shannawaz, Mohammed , Rad, Javad Sharifi, Sharma, Vishal , Shittu, Aminu , Shiue, Ivy , Shlobin, Nathan A. , Siddig, Emmanuel Edwar , Spartalis, Michael , Stanaway, Jeffrey D , Starodubova, Antonina Vladimirovna , Szarpak, Łukasz , Tabatabaeizadeh, Seyed‐Amir , Tabatabaeizadeh, Seyed-Amir, Talaat, Iman Mamdouh , Temsah, Mohamad‐Hani , Thakur, Ramna , Thirunavukkarasu, Sathish, Tiwari, Krishna, Truyen, Thien Tan Tri Tai , Tsai, Daniel Hsiang‐Te , Ullah, Atta , Unnikrishnan, Bhaskaran , Unsworth, Carolyn Anne, Usman, Jibrin Sammani , Valizadeh, Rohollah , Varghese, Joe , Vasankari, Tommi Juhani , Venketasubramanian, Narayanaswamy , Vervoort, Dominique , Villafañe, Jorge Hugo , Vinayak, Manish , Wafa, Hatem A , Walde, Mandaras Tariku, Willeit, Peter , Wolfe, Charles D.A. , Wolfe, Charles D. A., Yamagishi, Kazumasa , Yaribeygi, Habib , Yaya, Sanni , Ye, Pengpeng, Yonemoto, Naohiro , Yu, Chuanhua , Zastrozhin, Michael, Zhang, Chen , Zhang, Zhiqiang, Zielińska, Magdalena , Zyoud, Samer H. , Roth, Gregory A. , Feigin, Valery L. , Kulimbet, Mukhtar , Rahim, Fakher

Mayo Clinic

JAMA Neurology | May 23, 2025 | Volume: 82 | Issue: 8 | Pages: 765

10.1001/jamaneurol.2025.1522 | PMID 40406922 Get It

Importance Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure. Objective To estimate the worldwide burden of SAH. Design, Setting, and Participants Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021. Exposures SAH and 14 modifiable risk factors. Main Outcomes and Measures Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor–specific population attributable fractions (PAFs). Results In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution. Conclusions and Relevance Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH.
Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment
Zhao, Yihao , Yuan, Cuiyun, Liang, Ying , Li, Yang , Li, Chunxia , Zhao, Man, Hu, Jun , Zhong, Ningze , Liu, Wei , Liu, Chenbin , Liu, Wei

Mayo Clinic

Technology in Cancer Research & Treatment | May 22, 2025 | Volume: 24 | Issue: No issue available | Pages: No page available

10.1177/15330338251345895 | PMID 40400421 Get It

Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. Manual QA is tedious, time-consuming, and prone to subjective experiences. Automatic segmentation reduces physician workload and improves consistency. However, an effective QA process for these automatic contours remains an unmet need in clinical practice. Materials and Methods The patient data used in this study was derived from the AAPM Thoracic Auto-Segmentation Challenge dataset, including left and right lungs, heart, esophagus, and spinal cord. Two groups of organ-at-risk (OAR) were generated. A ResNet-152 network was used as a feature extractor, and a one-class support vector machine (OC-SVM) was employed to classify contours as ‘high’ or ‘low’ quality. To evaluate the generalizability, we generated low-quality contours using translation and resizing techniques and assessed correlations between detection limits and metrics such as volume, Dice similarity coefficient (DSC), 95% Hausdorff distance (HD95), and mean surface distance (MSD). Results The proposed OC-SVM model outperformed binary classifiers n metrics such as balanced accuracy and area under the receiver operating characteristic curve (AUC) . It demonstrated superior performance in detecting various types of contour errors while maintaining high interpretability. Strong correlations were observed between detection limits and contour metrics. Conclusion Our proposed model integrates an attention mechanism with a one-class classification framework to automate QA for OAR delineations. This approach effectively detects diverse types of contour errors with high accuracy, significantly reducing the burden on physicians during radiotherapy planning.
Consensus Statement on Robotic Nipple Sparing Mastectomy Expert Panel
Ryu, Jai Min , Mok, Chi Wei , Toesca, Antonio , Lai, Hung‐Wen , Kuo, Wen‐Ling , Cheng, Fiona Tsui-Fen , Song, Seung Yong , Johnson, Jeffrey , Shin, Hyukjai , Park, Hyung Seok , Johnson, Jeffrey E , Cheng, Fiona Tsui-Fen

Mayo Clinic

Journal of Breast Cancer | May 19, 2025 | Volume: 28 | Issue: 3 | Pages: 180

10.4048/jbc.2025.0030 | PMID 40432351 Get It

Expert Strategies: Skull Base Reconstruction—Global Perspectives, Insights, and Algorithms through a Mixed Methods Approach
Talati, Vidit , Patel, Jagatkumar A. , Nguyen, Theodore V. , Pang, Jonathan C. , Liu, Lauren , Craig, John R. , Papagiannopoulos, Peter , Phillips, Katie M. , Tajudeen, Bobby A. , Adappa, Nithin D. , Sedaghat, Ahmad R. , Anand, Vijay K. , Batra, Pete S., Bergsneider, Marvin, Casiano, Roy R. , Cavallo, Luigi Maria , Cohen, Marc A. , Eloy, Jean Anderson , Evans, James J., Fernandez‐Miranda, Juan C. , Ferrari, Marco , Froelich, Sébastien , Gardner, Paul A. , Gray, Stacey T. , Hanna, Ehab Y., Harvey, Richard J. , Hong, Sang Duk , Hwang, Peter H. , Kong, Doo‐Sik , Lan, Ming‐Ying , Lee, John Y. K. , Levine, Corinna G. , Meço, Cem , Nicolai, Piero, Nyquist, Gurston , Omura, Kazuhiro , Patel, Zara M. , Celda, María Peris, Prevedello, Danny M., Rabinowitz, Mindy, Raza, Shaan M., Sargi, Zoukaa , Schlosser, Rodney J. , Schwartz, Theodore H. , Sindwani, Raj , Stamm, Aldo Cassol , Thorp, Brian D. , Wang, Marilene B. , Wang, Wei‐Hsin , Witterick, Ian , Won, Tae‐Bin , Woodworth, Bradford A. , Wormald, Peter‐John, Zada, Gabriel , Su, Shirley Y. , Kuan, Edward C , Talati, Vidit , Nguyen, Theodore V , Pang, Jonathan C , Craig, John R , Sedaghat, Ahmad R , Wang, Eric W , Ferrari, Marco , Georgalas, Christos , Harvey, Richard J , Hwang, Peter H , Lan, Ming-Ying , Omura, Kazuhiro , Patel, Zara , Neto, Carlos Pinheiro, Schlosser, Rodney J , Snyderman, Carl H , Woodworth, Bradford A , Meço, Cem , Su, Shirley Y , Abiri, Arash , Goshtasbi, Khodayar , Adappa, Nithin D. , Bergsneider, Marvin , Bernal‐Sprekelsen, Manuel , Bleier, Benjamin S. , Cappabianca, Paolo , Carrau, Ricardo L. , Castelnuovo, Paolo , Dallan, Iacopo , El‐Sayed, Ivan H. , Hanna, Ehab Y., Kelly, Daniel F. , Liu, James K. , Locatelli, Davide , McKean, Erin L. , Nicolai, Piero , Passeri, Thibault , Pinheiro‐Neto, Carlos , Prevedello, Danny M., Recinos, Pablo F. , Rosen, Marc R , Turri‐Zanoni, Mario , Wormald, Peter‐John

Mayo Clinic

International Forum of Allergy & Rhinology | May 15, 2025 | Volume: 15 | Issue: 10 | Pages: 1032-1069

10.1002/alr.23596 | PMID 40371737 Get It

ABSTRACT Objective There is limited consensus on endoscopic skull base surgery (ESBS) reconstruction principles. This study aims to generate comprehensive themes regarding ESBS reconstruction by pooling the experiences of ESBS experts, with comparison to a literature review of current published evidence. Methods Structured qualitative interviews of ESBS experts regarding postoperative management and reconstruction of various defect locations were conducted. Results A total of 68 experts comprising 40 academic teams across 13 countries with an average of 18 years of ESBS experience were included. We propose 10 stepwise algorithms for common skull base reconstruction scenarios based on these expert interviews. When available, the nasoseptal flap is used for all high_flow cerebrospinal leak defects. Multilayered reconstruction is favored at all anatomical subsites with increasing number of layers for increasing defect size and complexity. Heterogeneity exists in terms of inlay technique and materials, free grafting versus various pedicled flap options for low‐flow defects or in the absence of a nasal septum, nasal packing, tissue sealant, lumbar drain use, and postoperative management. Commonalities and discrepancies between experts were summarized. Conclusion Skull base reconstruction and post‐ESBS management is highly complex with a wide variety of practice patterns and expert strategies. Further research of higher quality evidence is warranted to identify optimal management patterns, though the current work aims to inform surgeons on these controversial areas by drawing from numerous experiences.
Reporting guideline for the use of Generative Artificial intelligence tools in MEdical Research: the GAMER Statement
Luo, Xufei , Ranisch, Robert , Daher, Mohammad , Lam, Kyle , Eriksen, Alexander Viktor , Hsu, Che-Wei , Ozaki, Akihiko , Khanna, Sahil , Bian, Zhaoxiang , Chen, Yaolong , Estill, Janne , Litvin, Andrey , Giuffrè, Mauro , Lam, Kyle , Hsu, Che-Wei , Ozaki, Akihiko , Chen, Yaolong , Tham, Yih Chung , Moraes, Fábio Ynoe de , Su, Kuan‐Pin , Begagić, Emir

Mayo Clinic

BMJ Evidence-Based Medicine | May 13, 2025 | Volume: 30 | Issue: 6 | Pages: 390-400

10.1136/bmjebm-2025-113825 | PMID 40360239 Get It

Objectives Generative artificial intelligence (GAI) tools can enhance the quality and efficiency of medical research, but their improper use may result in plagiarism, academic fraud and unreliable findings. Transparent reporting of GAI use is essential, yet existing guidelines from journals and institutions are inconsistent, with no standardised principles. Design and setting International online Delphi study. Participants International experts in medicine and artificial intelligence. Main outcome measures The primary outcome measure is the consensus level of the Delphi expert panel on the items of inclusion criteria for GAMER (Rreporting guideline for the use of Generative Artificial intelligence tools in MEdical Research). Results The development process included a scoping review, two Delphi rounds and virtual meetings. 51 experts from 26 countries participated in the process (44 in the Delphi survey). The final checklist comprises nine reporting items: general declaration, GAI tool specifications, prompting techniques, tool’s role in the study, declaration of new GAI model(s) developed, artificial intelligence-assisted sections in the manuscript, content verification, data privacy and impact on conclusions. Conclusion GAMER provides universal and standardised guideline for GAI use in medical research, ensuring transparency, integrity and quality.
Deciphering C/EBPα'S Role in Fate Plasticity in Murine and Patient Tissue Derived AT2 Cells
Cai, Jiyang , Sawhney, Amitoj Singh , Deskin, B. , Gibbard, D., Ali, Gibran , Lemire, E., Haber, Adam L. , Wei, Zihao , Bungum, Aaron O., Schrandt, Amy, Cai, Jiyang , Olson, A., Warren, R., Langhe, Stijn De , Inde, Zintis , Sarosiek, Kristopher A. , Brownfield, Douglas

Mayo Clinic

American Journal of Respiratory and Critical Care Medicine | May 11, 2025 | Volume: 211 | Issue: Supplement_1 | Pages: A7930-A7930

10.1164/ajrccm.2025.211.abstracts.a7930 Get It

Abstract RATIONALE: Alveolar Type 2 (AT2) cells play a critical role in maintaining alveolar function and facilitating repair processes in the lung. Despite recent advancement on transcriptomic mapping of cell identities and AT fate selection, the mechanisms governing AT2 fate plasticity remain elusive. Notably, in AT2-derived pulmonary diseases such as COPD and IPF, disruptions in AT2 differentiation are observed, suggesting alterations may exist in the regulation of fate plasticity. Therefore, a refined model describing the regulation of AT2 fate plasticity is needed, along with an assessment of the model's conservation across murine and human AT2s. METHODS: We performed scRNA-sequencing, ATAC-seq, and bioinformatic analysis on samples across murine lung development and validating findings by immunostaining of embryonic lungs. We conducted organotypic cultures as well as genetically engineered mouse model experiments to assess changes in AT2 fate plasticity in. Further, we established a Mayo Clinic patient lung cell biorepository from patient tissue derived AT2s. In parallel, we performed long read scRNA-sequencing for isoform discovery, organotypic culture and immunostaining in human AT2 organoids, to characterize the presence of similar regulatory mechanisms. RESULTS: Throughout the late embryonic and early perinatal period, we found a window of fate plasticity exists in AT2s whereby they retain the capacity to give rise to AT1s, and that its being closed over time by the bZIP transcription factor C/EBPα, as its genetic deletion in AT2s results in regaining fate plasticity. By ATAC-seq and ChIP-seq, we found C/EBPα binds closely to the Dlk1 locus, a Notch signaling regulator implicated in AT2-to-AT1 conversion that is upregulated following Cebpa deletion. Following adult lung injury, we found C/EBPα downregulation is required for re-accessing AT2 fate plasticity and is likely mediated by the dominant negative C/EBP family member CHOP. Finally, we observe Cebpa loss also activates a “defender” AT2 state enriched in interferon stimulated antipathogenic gene expression that is distinct from its reparative state and propose AT2s can toggle between these states following infection to robustly protect and repair alveoli.Further, we validated the presence of C/EBPα and absence of Dlk1 in human AT2s isolated from healthy adult patients, which persists following in vitro expansion. We conclude that AT2 cells window of fate plasticity is dictated by a molecular circuit involving C/EBPα suppressing and Dlk1. Future works aim to remove C/EBPα in human AT2s to reopen their fate plasticity for cell therapy.
Lower Lobe Mucus Plug Distribution is Associated With Increased Risk for Future Acute Exacerbations Among Tobacco-exposed Persons
Mettler, S.K., Campo, M. Iturrioz, Yen, A., Sonavane, S., Wang, Wei , Cho, M.H. , Mettler, Sofia K. , Wan, Emily S. , Borgaonkar, Ruchita , Nardelli, Pietro , Grumley, Scott , Estépar, R. San José , Díaz, Alejandro A.

Mayo Clinic

American Journal of Respiratory and Critical Care Medicine | May 11, 2025 | Volume: 211 | Issue: Supplement_1 | Pages: A2944-A2944

10.1164/ajrccm.2025.211.abstracts.a2944 Get It

Abstract Introduction / Rationale Mucus plugs (MPs) on chest computed tomography (CT) are associated with increased respiratory symptoms, worse lung function, and elevated mortality and acute exacerbations among individuals with GOLD2-4 COPD. Whether mucus plug distribution in the upper versus lower lobes differentially impacts future acute exacerbations (AEs) has been incompletely explored. Methods Data from current and former tobacco users, ages 40-80, with ≥10 pack-years, at the enrollment visit in COPDGene were analyzed. MPs were visually-assessed on chest CTs using a sequential reading system; the MP score was calculated as the number of bronchopulmonary segments with plugs (range 0-18). Among subjects with MPs, the percent of lower lobe MPs (%LLMPs) was calculated as the number of bronchopulmonary segments in the right and left lower lobes divided by the total number of bronchopulmonary segments (range 0-100%). Moderate-to-severe AEs were assessed prospectively biannually for up to 15.5 years. Zero-inflated Poisson regression, adjusting for age, sex, BMI, race, smoking status, pack-years, FEV1% predicted, history of AEs (year prior to enrollment), and clinical center assessed the relationship between %LLMPs, total MPs, and prospective AEs; duration of follow-up was included as the offset. Subgroup analyses by lung function category (GOLD0, GOLD 1-4 COPD, and Preserved Ratio Impaired Spirometry, PRISm) were also performed using the same model. Results Among 10,198 tobacco-exposed individuals, 9,406 subjects (mean age 59.7±9.0, 53.4% male, 68% non-Hispanic white) had chest CT scans scored for MPs. The overall prevalence of MP>0 was 30.4%, with an average MP score of 0.78±1.88 and average %LLMP of 48%±39%. The prevalence of MPs varied by lung function category (20.1% GOLD0, 26.2% PRISm, 40.8% COPD) as did the mean MP score (0.28±0.93 GOLD0, 0.49±1.38 PRISm, 1.30±2.42 COPD) (Figure 1). The %LLMP also varied by lung function category (33%±39% GOLD0, 38%±37% PRISm, 57%±37% COPD). Among subjects with MPs>0 (n=2,857), higher %LLMP was associated with a significantly increased risk for future AEs (adjusted rate ratio (aRR) [95%CI]= 1.11[1.05-1.17]; Figure 1). Subgroup analyses by lung function category supported a significant association between increased %LLMP and future AEs in GOLD0 (aRR 1.45 [1.25-1.69]), but not in the COPD or PRISm subgroups (Figure 1). Conclusions A higher proportion of lower lobe mucus plugs is significantly associated with increased risk for future AEs among tobacco-exposed persons. Despite having the lowest burden of MPs, the highest risk for prospective AEs with increasing %LLMP was observed in the subgroup with normal spirometry (GOLD0).
A Proposal for HPV-Associated Oropharyngeal Carcinoma in the Ninth Edition Clinical TNM Classification
Huang, Shao Hui, Su, Jie , Koyfman, Shlomo A. , Hoebers, Frank , Bahig, Houda , Yu, Eugene , Bartlett, Eric , Davis, Robin L. , Woody, N.M. , Nelson, Kristoff , Lavigne, Danny , Nguyen‐Tan, Phuc Félix, Létourneau‐Guillon, Laurent , Filion, Édith, Nagelschneider, Alex A. , Abel, Kathryn M. Van , Postma, Alida A. , Palm, Walter M. , Lydiatt, William M. , Patel, Snehal G. , Routman, David, Van Abel, Kathryn M , Huang, Shao Hui, Routman, David M. , Spreafico, Anna , Lee, Jonathan Wei Jie , Stock, Sarah Jane , Daniel, J. , Hoeben, Ann , Chua, Melvin L.K. , Xu, Wei , O'Sullivan, Brian P

Mayo Clinic

JAMA Otolaryngology–Head & Neck Surgery | May 8, 2025 | Volume: 151 | Issue: 7 | Pages: 655

10.1001/jamaoto.2025.0848 | PMID 40338536 Get It

Importance A subset of Union for International Cancer Control ( UICC )/ American Joint Committee on Cancer ( AJCC ) eighth edition TNM stage I and II human papillomavirus–positive oropharyngeal carcinoma has undesirable outcomes, which might have contributed to a lack of success in phase III deintensification trials. Refining clinical stage groups, especially in the overabundant cN1/stage I group, has become important for treatment selection. Objective To assess the prognostic importance of pretreatment lymph node (LN) characteristics to optimize case distribution and outcome homogeneity within the N classification system. Design, Setting, and Participants This is an international multi-institutional retrospective prognostic cohort study. Analysis of human papillomavirus–positive oropharyngeal carcinoma treated curatively from 4 institutions (International Collaboration of Oropharyngeal Cancer Network for N-Classification [ICON-N] dataset) provided a refined clinical staging proposal; an independent dataset (Centre Hospitalier de l’Université de Montréal [CHUM] dataset) validated the proposal. Neuroradiologists reviewed pretreatment computed tomography and/or magnetic resonance imaging for nodal features, including presence or absence of abnormal LN(s), retropharyngeal LN, laterality, number of abnormal LN, and imaging-detected extranodal extension (iENE). Data were collected from February to May 2023, and data were analyzed from June to July 2023. Exposures Definitive chemoradiotherapy/radiotherapy or definitive surgery with or without postoperative chemoradiotherapy/radiotherapy. Main Outcomes and Measures The primary end point was overall survival. A Cox proportional hazards multivariable model was used to estimate adjusted hazard ratios (AHRs) and to derive an optimal clinical TNM stage classification (AHR-stage schema) incorporating the strongest prognostic nodal features within the UICC/AJCC eighth edition TNM framework after confirming the prognostication of iENE status. The performance (according to overall normalized scores and ranking) of the AHR-stage schema against the current UICC/AJCC eighth edition TNM staging system was evaluated for hazard consistency, hazard discrimination, prognostic importance, and sample size balance. Validation was performed in the CHUM dataset. Results The ICON-N dataset comprised 2053 patients, including 1898 (92.5%) with cN-positive disease and 155 (7.5%) with cN0 disease; a total of 298 (14.5%) were female, and the mean (SD) age was 60.6 (9.3) years. iENE-positive disease was identified in 710 of 1898 patients with cN-positive disease (37.4%). The median (range) follow-up was 5.1 (0.1-14.7) years. iENE was the strongest prognostic nodal feature in multivariable analysis; the AHR for iENE-positive vs iENE-positive disease was 2.43 (95% CI, 1.96-3.03) in the ICON-N dataset and 2.04 (95% CI, 1.28-3.23) in the CHUM dataset (n = 451). Reclassifying iENE-positive cases 1 stratum higher for N categorization without altering iENE-negative cases yielded an AHR-stage schema that outperformed the current TNM staging system in disease-free and overall survival with a lower (ie, better) overall normalized score (2 vs 3). Conclusions and Relevance In this study, reclassifying each N category 1 stratum higher for iENE-positive disease resulted in better disease-free and overall survival. The proposed new classification outperformed the currently TNM staging system in risk stratification and may facilitate future clinical trial design, outcomes research, and patient care.
Store-operated Ca 2+ entry is involved in endothelium-to-mesenchymal transition in lung vascular endothelial cells
Babicheva, Aleksandra , Elmadbouh, Ibrahim , Song, Shanshan , Thompson, Michael A, Powers, Ryan, Jain, Pritesh, Izadi, Amin , Chen, Jiyuan , Yung, Lauren, Parmisano, Sophia , Paquin, Cole, Wang, Ting , Shyy, John Y.-J. , Thistlethwaite, Patricia A. , Makino, Ayako , Yuan, Jason X.‐J. , Shyy, John Y-J , Makino, Ayako , Prakash, Y S , Pabelick, Christina M , Yuan, Jason X-J , Babicheva, Aleksandra , Izadi, Amin, Wang, Wei‐Ting , Chen, Yuqin , Alotaibi, Mona , Shyy, John Y.-J., Wang, Jian , Prakash, Y. S. , Pabelick, Christina M.

Mayo Clinic

American Journal of Physiology-Lung Cellular and Molecular Physiology | May 7, 2025 | Volume: 328 | Issue: 6 | Pages: L844-L857

10.1152/ajplung.00400.2024 | PMID 40331589 Get It

EndMT has been reported to contribute to the pathogenesis of PAH. In this study, we aimed to determine the role of Ca 2+ signaling in the development of EndMT in human lung vascular endothelial cells. Our data suggest that TGF-β 1 requires store-operated Ca 2+ entry through STIM1/Orai channels to induce SNAI-mediated EndMT. For the first time, we demonstrated that TGF-β 1 -induced EndMT is a Ca 2+ -dependent event, whereas inhibition of STIM1/Orai interaction attenuated EndMT in response to TGF-β 1 .