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Transcatheter Aortic Valve Replacement is Associated With a Lower Risk of Aortic Dissection Than Surgical Aortic Valve Replacement: A Propensity Score-Matched Analysis
Doma, Mohamed , Kritya, Mangesh , Ramadan, Adham, Félix, Iuri Ferreira , Shlkamy, Seif, Lingamsetty, Shanmukh Sai Pavan , Ismayl, Mahmoud , Mahesh, Ashwin, Ferreira Felix, Iuri , Lingamsetty, Shanmukh S P , Ismayl, Mahmoud , Goldsweig, Andrew M , Doma, Mohamed , Ramadan, Adham, Kamel, Ibrahim, Mahmoud, Ahmed , Goldsweig, Andrew M.

Mayo Clinic

Reviews in Cardiovascular Medicine | July 30, 2026 | Volume: 27 | Issue: 7 | Pages: No page available

10.31083/rcm50574 | PMID 42534156 Get It

Background:Aortic valve replacement is the primary treatment for aortic valve disease and can be performed using either transcatheter (TAVR) or surgical (SAVR) approaches. The risk of aortic dissection (AD) with TAVR compared with SAVR remains unclear. We aimed to compare AD risk between TAVR and SAVR using a large, real-world cohort. Methods:We conducted a retrospective cohort analysis using the TriNetX research network. Patients with a diagnosis of aortic stenosis, aortic insufficiency, mixed aortic valve disease (AVD), or unspecified AVDwho underwent either TAVR or SAVR were included. A 1:1 propensity score-matching (PSM) based on baseline characteristics was performed to adjust for potential confounding. Logistic regression and Cox proportional hazards models were used to estimate odds ratios (ORs) and hazard ratios (HRs), with 95% confidence intervals (CIs).Results:Among 95,043 patients undergoing isolated aortic valve replacement, 20,237 matched pairs were analyzed after 1:1 PSM. Baseline characteristics were well balanced, with a mean age of 73.3 ± 9.3 years in the TAVR group and 73.2 ± 8.5 years in the SAVR group; 60.8% and 60.7% were male, respectively. TAVR was associated with significantly lower odds of composite AD than SAVR at all time points (1-year OR 0.60; 95% CI 0.44–0.82; 3-year OR 0.64; 95% CI 0.48–0.83; 5-year OR 0.66; 95% CI 0.51–0.85; p < 0.01 for all). Stratified analyses demonstrated lower odds of both Stanford type A and type B AD at all time points. Kaplan–Meier analysis demonstrated a separation in composite AD-free survival between the two groups (HR 0.66; 95% CI 0.51–0.86; p = 0.002).Conclusion:In this large, real-world cohort, despite a low event rate, TAVR was associated with a significantly lower likelihood of composite AD than SAVR.
Global Burden of Elevated LDL-C
Collaborators, GBD 2023 LDL Cholesterol, Razo, Christian, DeCleene, Nicole K., Johnson, Catherine O., Stark, Benjamin, LeGrand, Kate, Aalruz, Hasan, Abaraogu, Ukachukwu O., Abdelnabi, Mahmoud, Abd-Elsalam, Sherief, Abdelwahab, Siddig Ibrahim, Abdollahi, Arash, Abdrabou, Mostafa M., Abdul‐Rahman, Toufik , Getahun, Habtamu Abebe, Abiodun, Olumide, Abohashem, Shady, Abonie, Ulric Sena , Abourashed, Nagah M , Abramov, Dmitry, Abrar, Mohammed Mehdi, Farha, Rana Kamal Abu, Abubakar, Bilyaminu, Aburuz, Salahdein, Abushanab, Dina, Adams, Lisa C., Adamu, Nuhu Lawan Lawan, Adegbile, Oluwatobi E , Adegoke, Nurudeen A., Adekola, Saheed Ayodeji, Adeleke, Olumide Thomas , Adesina, Miracle Ayomikun, Afoakwah, Clifford, Afolabi, Aanuoluwapo Adeyimika, Afrashteh, Fatemeh , Afrifa-Yamoah, Ebenezer, Agyemang‐Duah, Williams , Ahmad, Suhaib, Ahmed, Asma , Ahmed, Gasha Salih, Ahmed, Luai A., Ahmed, Mehrunnisha Sharif, Ahmed, Meqdad Saleh , Ahmed, M. , Ahmed, Mushood, Ahmed, Syed Anees, Ahmed, Zohra, Aiyer, Aishwarya, Ajami, Marjan, Akalanka, Kasuni H.M. , Akhtar, Muhammad Nadeem, Akrami, Ashley E, Akyea, Ralph Kwame, Hasan, Syed Mahfuz Al , Zoubi, Mohammad Ahmmad Mahmoud Al, Alahdab, Fares , Al-Ahmad, Mohammad M. , Alajajian, Stephen , Alajlani, Muaaz , Alalwan, Tariq A., Al-Amri, Issa Sulaiman, Alanzi, Turki M., Alarifi, Abdullah, Al-Azzam, Sayer, Albashtawy, Mohammed, Al-Dewik, Nader, Algahtani, Fahad D., Algammal, Abdelazeem M, Alhalaiqa, Fadwa Naji, Ali, Mohammad Daud , Ali, Mohammed Usman, Ali, Rafat, Ali, Syed Shujait, AL-Iede, Montaha, Alipour, Morteza, Al-Jabi, Samah W., Alkhatib, Mayson H. , Allawi, Raad Hatim , Allemailem, Khaled S. , (6837737), Mohammed Z. 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Zubbair, Malta, Deborah Carvalho, MAMAND, DOSTE RASHID, Maniya, Muhammad Talha, Mansoor, Farheen, Mansourian, Marjan, Manzoor, Shaista, Marghani, Basma Hamed, Martinez-Piedra, Ramon, Martini, Santi, Martorell, Miquel, März, Winfried, Marzouk, Sammer, Masi, Stefano, Masrouri, Soroush , Maude, Richard J. , Mavrovounis, Georgios, McPhail, Steven M., Mendoza, Walter, Menezes, Ritesh G., Mengistie, Emiru Ayalew, Menon, Tara P., Mestrovic, Tomislav, Mettananda, Chamila Dinushi Kukulege, Metwally, Mohamed M.M., Jonasson, Junmei Miao , Mikrajab, Muhammad Agus Naufal, Minhas, Abdul Mannan Khan, Mirrakhimov, Erkin M., Mitra, Sayan , Mitra, Tridip, Modi, Dhruti, Mohamed, Mona Gamal, Ahmed, Khabab Abbasher Hussien Mohamed, Mohammad, Ameen Mosa , Mohammadi, Saeed, Mohammed, Omer, Mohan, Syam , Molla, Tewodros Shibabaw, Molokhia, Mariam, Moni, Mohammad Ali, Namin, Sara Montazeri , Morovvati, Mahdis, Heris, Reza Mosaddeghi, Motappa, Rohith, Mousavi, Seyed Ahmad , Kiasary, Seyed Mohamad Sadegh Mousavi, Yousefi, Kimia Mozahheb , Mubarik, Sumaira, Munkhsaikhan, Yanjinlkham, Musa, Sani, Mwita, Julius C., Nabipoorashrafi, SeyedAli, Nagarajan, Ahamarshan Jayaraman , Naik, Ganesh R., Naik, Hiten, Nainu, Firzan, Nartey, Yvonne , Nassar, Mahmoud, Natto, Zuhair S., Naureen, Zakira, Nawaiseh, Hala Khaled, Nayak, Biswa Prakash, Nayak, Vinod C., Nazari, Mojdeh, Ndakotsu, Andrew , Nega, Amanuel Tebabal , Nega, Mulata H., Negash, Abigia Ashenafi, Negoi, Ionut, Nguyễn, Cao Duy, Nguyen, Cuong Tat , Nguyen, Hau Thi Hien, Nguyen, Nghia Phu , Nguyen, Phat Tuan , Nguyen, Van Thanh, Niazi, Robina Khan, Nomura, Shuhei , Noreen, Mamoona , Nawsherwan, Noubiap, Jean Jacques, Nugen, Fred, Nur, Aqsha, Odediji, Saheed Adeyinka, Ogunmodede, O.S., Ojedoyin, Olusegun Olatunji , Ojo, Oluwafemi Adeleke , Okati-Aliabad, Hassan, Oliveira, Gláucia Maria Moraes, Olorukooba, Abdulhakeem Abayomi, Ong, Qi Chwen, Orru, H, Ortiz, A., Ortiz-Prado, Esteban, Osborne, Augustus, Osei, George Nkrumah , Ostrominski, John W. , Oumer, Abdu, Ouyahia, Amel, Owolabi, Mayowa O., Oyebola, Kolapo, Ozsahin, Ilker, Anand, Mahesh Padukudru, Palicz, Tamás , Panda, Sujogya Kumar , Pandi-Perumal, Seithikurippu R., Panos, Georgios D., Papadimopoulos, Ilias, Parija, Pragyan Paramita , Parikh, Romil R., Pascucci, Eleonora, Pasovic, Maja , Passera, Roberto, Patel, Mitesh, Patel, Niki Rut, Patel, Satyananda, Patil, Ashlesh, Patil, Shankargouda, Patoulias, Dimitrios, Pattnaik, Snigdha, Toroudi, Hamidreza Pazoki, Pekarcikova, Jarmila, Peprah, Prince, Pereira, Gavin, Pirera, Edoardo , Plotnikov, Evgenii, Poluru, Ramesh, Prasad, Manya, Prashant, Akila, Prates, Elton Junio Sady, Pugliese, Nicola Riccardo, Puvvula, Jagadeesh, Qi, Xiang, Qureshi, Ali, Radhakrishnan, Venkatraman, Raghav, Pankaja, Raghav, Yashpal Singh Raghav, Raghuveer, Pracheth , Rahim, Fakher , Rahim, Hawbash Mohammed-Amin, Rahimi, Sajjad, Rahman, Fryad Majeed, Rahman, M Sajjadur , Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rajendran, Judah, Rajput, Prashant, Ramasamy, Chitra, Ramasamy, Shakthi Kumaran, Rao, Asad Gul , Rao, Mithun , Rao, Sowmya J, Rasouli-Saravani, Ashkan, Rath, Shree, Rathi, Isha, Rawaf, David Laith , Rawaf, Salman, Reddy, Murali Mohan Rama Krishna, Rezaei, Mina, Rezaei, Nazila, Rezaeian, Mohsen , Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Ross, Allen Guy Patrick, Rubeshkumar, Polani, Rwegerera, Godfrey Mutashambara , Saad, Aly M. A., Sabet, Cameron John, Sadarangani, Kabir P., Rafiei, Seyed Kiarash Sadat, Sadeghi, Ehsan, Sadeghi, Erfan, Sadeghi, Masoumeh, Sadek, Bassem, Sadek, Mustafa, Sadr, Hossein, Saeb, Mohammad Reza, Saeed, Umar, Saeedi, Maryam , Safiullah, Muhammad , Sahebkar, Amirhossein, Sajadi, S Mohammad, Saleh, Mohamed A., Salehi, Mahdi , Salimi, Sohrab, Samargandy, Saad, Samy, Abdallah M., Saravanan, Aswini , Sarfo, Jacob Owusu, Sarode, Gargi Sachin, Sarode, Sachin C., Sathian, Brijesh, Far, Mehrdad Savabi, Schlaich, Markus P., Schuermans, Art, Sejben, Anita, Semreen, Mohammad H., Senol, Yigit Can, Sessa, Francesco, Sewor, Christian , Seylani, Allen, Shahrahmani, Fatemeh, Shahwan, Moyad Jamal, Sham, Sunder, Shan, Dan, Sharifan, Amin , Sharma, Kamal, Sharma, Ravi Kumar, Sharma, Ujjawal , Shehzadi, Somia , Shetty, Mahabalesh, Shetty, Pavanchand H, Shi, Fanchao , Shi, Huizhong , Shi, Yongfeng, Shiri, Rahman , Shittu, Aminu, Shiue, Ivy, Shoaib, Ambreen, Shool, Sina, Shorofi, Seyed Afshin, Shuval, Kerem, Sia, Ching-Hui, Silva, Luís Manuel Lopes Rodrigues, Singh, Amit, Singh, Baljinder, Singh, Harmanjit, Singh, Harpreet, Singh, Lucky, Singh, Paramdeep, Singh, Siddharth , Singh, Sunil Kumar, Singh, Surjit, Singh, Vanshika , Sinha, Mukesh Kumar, Skryabin, Valentin Yurievich, Sokhal, Balamrit Singh , Sood, Prashant , Soraneh, Soroush , Sorensen, Reed J D , Srivastav, Prateek , Stanikzai, Muhammad Haroon , Starodubova, Antonina V., Stubbs, Peter, Suhag, Alisha, Sulaiman, Sahabi K., Odidi, Muritala Suleiman, Sulistiyorini, Desy , Sun, Jing , Sun, Zhong, Szarpak, Lukasz, Ty, Sree Sudha, Damavandi, Payam Tabaee, Tabatabaei, Seyyed Mohammad, Tabatabai, Shima, Tagiisuran, Balamurugan, Ali, Eman Taha Osman, Soodejani, Moslem Taheri, Taiba, Jabeen, Tajabadi, Shima, Talic, Stella, Talukder, Ashis, Adugna, Dessalegn Tamiru, Tampa, Mircea, Tan, Jianye, Tanabayeva, Dariga, Tanashat, Mohammad , Tang, Jiahao , Tantisattamo, Ekamol, Tariq, Saba, Temsah, Reem, Teramoto, Masayuki, Tesfamariam, Wegen Beyene , Tewari, Jay , Thakar, Vidhi, Thangavelu, Lakshmi, Tharwat, Ismaeel, Thiruvengadam, Muthu , Thomas, Nikhil Kenny, Ticoalu, Jansje Henny Vera, Tiwari, Krishna, Tleshev, Madi, Tonelli, Marcello, Topór-Mądry, Roman , Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Tran, An Thien, Tran, Thang Huu, Duc, Nguyen Tran Minh , Tricò, Domenico , Tse, Gary, Tseriotis, Vasilis-Spyridon, Tualeka, Abdul Rohim , Tye, Sok Cin , Ullah, Riaz, Umair, Muhammad, Umar, Lawan , Ozsahin, Dilber Uzun, Uzunçıbuk, Hande, Vaithinathan, Asokan Govindaraj , Vakili, Omid , Eynde, Jef Van den, Varghese, Joe, Vellingiri, Balachandar, Verma, Poonam, Villalobos-Daniel, Victor E., Vlassov, Vasily, Wang, Nelson, Wang, Qingzhi, Wang, Wanzhou, Wang, Wei, Wang, Yanzhong, Wang, Zhihua, Wani, Tanveer A.A., Wei, Melissa Y., Weintraub, Robert G., Wibowo, Yohanes Cakrapradipta, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Witts, William Kwame , Wonde, Tewodros Eshete , Wongsin, Utoomporn , Wu, Peng, Xiao, Guangqin, Xie, Wanqing , Xu, Suowen, Xu, Wanqing, Yadav, Vikas , Yahoo, Saba, Yang, Hanwen, Yano, Yuichiro , Yao, Haiqiang , Yarahmadi, Amir, Yin, Dehui , Yismaw, Yazachew Engida, Yon, Dong Keon, Yu, Chuanhua, Yu, Elaine A., Yu, Hairui , Yu, Yong , Yuan, Quan, Zafar, Mubashir , Zaghampour, Manijeh, Zamora, Nelson, Zanghì, Aurora , Zargar, Seema , Zeariya, Mohammed G M, Zeru, Eyael M, Zhang, Beijian, Zhang, Hanyu, Zhang, Julio Min Fei, Zhang, Yunquan, Zhang, Zhichang, Zhanuzakov, Murat , Zhao, Zhongyi, Zheng, Ming‐Hua , Zhong, Anthony , Zhong, Claire Chenwen, Zhou, Hao, Zhou, Jiayan, Zhou, Xiao-Dong, Zhu, Zhengyang , Zhumagaliuly, Abzal, Zitoun, Osama A. , Zoghi, Ghazal , Zoromba, Mohamed Ali, Zumla, Alimuddin, Zyoud, Sa’ed H., Hay, Simon I., Mokdad, Ali H., Murray, Christopher J. L., Roth, Gregory A., Sun, Zhong , Hay, Simon I , Roever, Leonardo , Krishan, Kewal , Moni, Mohammad Ali , Buendía, Jefferson Antonio , Badar, Muhammad , Wickramasinghe, Nuwan Darshana , Nassar, Mahmoud , Dewan, Syed Masudur Rahman , Naik, Ganesh R. , Wang, Yanzhong , Rath, Shree , Karakasis, Paschalis , Zheng, Ming-Hua , Taiba, Jabeen , Razo, Christian , DeCleene, Nicole K., LeGrand, Kate E , Abaraogu, Ukachukwu Okoroafor , ElHafeez, Samar Abd , Abdelmasseh, Michael , Abdelnabi, Mahmoud , Abd‐Elsalam, Sherief , Elshenawy, Rasha Abdelsalam , Abdelwahab, Siddig İbrahim , Abdolizadeh, Ali , Abdollahi, Arash, Abdoun, Meriem , Abdrabou, Mostafa M. , Abdulah, Deldar Morad , Abdullahi, Auwal , Shenkut, Melese, Abiodun, Olugbenga Olusola , Abiodun, Olumide A , Abohashem, Shady , Abtahi, Dariush , Farha, Rana Kamal Abu , Abubakar, Bilyaminu , Abuhelwa, Ahmad Y. , Abukhadijah, Hana J , Aburuz, Salahdein , Adamu, Nuhu Lawan , Adane, Mesafint Molla , Addo, Isaac Yeboah , Adedokun, Kamoru Ademola , Adekola, Saheed Ayodeji, Adesina, Miracle Ayomikun , Adisu, Molalign Aligaz , Adnan, Mohd , Afoakwah, Clifford , Afolabi, Aanuoluwapo Adeyimika, Afrifa‐Yamoah, Ebenezer , Afzal, Saira , Agordoh, Percival Delali , Ahmad, Aqeel , Ahmad, Khabir , Ahmad, Sajjad , Ahmed, Gasha Salih, Ahmed, Nesredin , Ajami, Marjan , Akhtar, Muhammad Nadeem , Akindele, Mukadas Oyeniran , Akkaif, Mohammed Ahmed , Akyea, Ralph Kwame , Zoubi, Mohammad Ahmmad Mahmoud Al, Alalwan, Tariq A. , Al‐Aly, Ziyad , Al-Amri, Issa Sulaiman , Alanzi, Turki Matar Khalaf, Al-Ashwal, Fahmi Y. , Al‐Azayzih, Ahmad , Al-Azzam, Sayer , Al-Bashaireh, Ahmad M. , ALBashtawy, Mohammed , Aleidi, Shereen M. , Algahtani, Fahad D. , AlHabib, Khalid F. , Ali, Abid , Ali, Asgar , Ali, Bassam R. , Al‐Iede, Montaha , Alif, Sheikh Mohammad , Alipour, Morteza, Al‐Jabi, Samah W. , Aljunid, Syed Mohamed , Alkubati, Sameer Abdulmalik , Almagharbeh, Wesam Taher , Almahmeed, Wael , Almazan, Joseph Uy , Alniss, Hasan Yaser , Alomari, Mahmoud A. , Alotaibi, Haifa F. , Alqahtani, Saleh A. , Alqudimat, Mohammad R. , Al-Qudimat, Ahmad Rajeh , Al‐Raddadi, Rajaa , Alsbou, Mohammed , Alshahrani, Najim Zafer , Al-Shami, Ali Salman , Altaf, Awais , Althobiani, Malik A , Alwafi, Hassan , Al‐Worafi, Yaser Mohammed , Aly, Hany Z. , Al‐Zalabani, Abdulmohsen H. , Alzoubi, Abdallah , Alzoubi, Karem Hasan , Amafah, Joy, Amin, Amr , Amini, Saeed, Amini‐Salehi, Ehsan , Amusa, Ganiyu , Ang, Song Peng , Anieto, Ebuka Miracle , Anil, Abhishek , Anjana, Dr. Prapti, Anvari, Saeid, Appati, Walter , Arabloo, Jalal , Arafat, Mosab , Areda, Demelash, Arefnezhad, Reza , Torre, Jorge Arias de la, Aripov, Timur , Arockiaraj, Jesu , Asdaq, Syed Mohammed Basheeruddin , Ashraf, Syed Amir , Ashraf, Tahira , Ataç, Ömer , Athar, Mohammad , Athari, Seyyed Shamsadin , Aurangzeb, Khursheed , Awan, Sana Javaid , Awol, Kemal Lemnuro, Awotidebe, Adedapo Wasiu , Aylı, Berrak Itır , Azarboo, Alireza , Aziz, Sadat Abdulla , Azzolino, Domenico , Babu, Abraham Samuel , Babu, Giridhara R. , Badiye, Ashish , Baghlaf, Khlood K , Baig, Atif Amin , Bakhshali, Mohamad Amin , Banach, Maciej , Banik, Palash Chandra , Barqawi, Hiba Jawdat , Barrow, Amadou , Barua, Lingkan , Bashir, Shahid , Bashiri, Azadeh , Bastan, Mohammad‐Mahdi , Bayih, Mulat Tirfie , Beeraka, Narasimha Murthy , Begum, Tahmina , Behera, Priyamadhaba , Behnam, Babak , Ramírez, Diana Fernanda Bejarano , Belo, Luı́s , Berihun, Abiye Assefa , Bhattacharjee, Priyadarshini , Bhatti, Gurjit Kaur , Bhatti, Jasvinder Singh , Biswas, Atanu , Biswas, Bijit , Bizzozero‐Peroni, Bruno , Bodur, Mahmut , Bogale, Sitotaw Kerie , Bohn, Lucimére , Boloor, Archith , Carvajal, Alejandro Botero , Boudalia, Sofiane , Bugiardini, Raffaele , Busch, Felix , Bustanji, Yasser, Campos, Luciana Aparecida , Catapano, Alberico Luigi , Cegolon, Luca , Cenko, Edina , Cerin, Ester , Chakraborty, Chiranjib , Chandika, Rama Mohan , Chandrasekar, Eeshwar K , Chandrasekaran, Baskaran , Chattu, Vijay Kumar , Chaudhary, Anis Ahmad , Chaudhuri, Sirshendu , Cheema, Asad Ali Ahmed , Chichagi, Fatemeh , Ching, Patrick R , Cho, William C.S., Choi, Dong‐Woo , Chong, Bryan , Chopra, Deepti , Chopra, Hitesh , Choudhari, Sonali Gajanan , Chu, Dinh‐Toi , Chukwu, Chidozie Williams , Chung, Sheng‐Chia , Chung, S. Y. , Cicero, Arrigo F.G. , Cosma, Claudia , Criqui, Michael H. , Dadras, Omid , Dai, Xiaochen , Dai, Zhaoli , Dalakoti, Mayank , D’Amico, Emanuele , Tesfa, Endalamaw , Danpanichkul, Pojsakorn , Darcho, Samuel Demissie , Davletov, Dimash , Davletov, Kairat , Dejenie, Tadesse Asmamaw , Bo’, Cristian Del , Delgado‐Enciso, Iván , Denova‐Gutiérrez, Edgar , Dergaa, Ismail , Dervišević, Emina , Devegowda, Devananda , Dewan, Syed Masudur Rahman , Dhimal, Meghnath , Dhungel, Bibha , Do, Thanh Chi, Phuong, Thao Huynh, Doshi, Ojas Prakashbhai , Doshi, Rajkumar , Dourado, Paulo Magno Martins , Dowou, Robert Kokou , Du, Mi , Duncan, Bruce Bartholow , Durães, André Rodrigues , Ebohon, Osamudiamen , Eftekhari, Behrad , Eladl, Mohamed Ahmed , Eldaboush, Ahmed , Elgendy, Islam Y. , Elhadi, Muhammed , El‐Huneidi, Waseem , Elmonem, Mohamed A. , Elmoselhi, Adel B. , Fabin, Natalia , Fadaka, Adewale Oluwaseun , Fagbamigbe, Adeniyi Francis , Fakorede, Sodiq , Fatima, Zareen , Fayaz, Mohammad , Fazylov, Timur, Fernández‐Jiménez, Rodrigo , Fischer, Florian, Fogacci, Federica , Foschi, Matteo , Gadanya, Muktar A., Gajdács, Márió , Galali, Yaseen , Ganesan, Balasankar , Gangachannaiah, Shivaprakash , Gašević, Danijela , Habtemichael, Mizan , Getacher, Lemma , Jolfayi, Amir Ghaffari , Ghamkhar, Arin, Ghazy, Ramy Mohamed , Ghimire, Sailaja, Ghith, Nermin , Gil, Artyom , Gill, Paramjit Singh , Gnedovskaya, Elena V. , Goh, Lay Hoon , Gohari, Kimiya, Golechha, Mahaveer , Goulart, Alessandra C. , Goyal, Aman , Grada, Ayman , Gu, Long , Gubari, Mohammed Ibrahim Mohialdeen , Guha, Avirup , Gunawardane, Damitha Asanga , Gupta, Rajeev , Gurgoglione, Filippo Luca , Guzmán-Esquivel, José , Guzmán-Muñoz, Eduardo , Haghtalab, Arian , Halder, Pritam , Hamdy, Nadia Μ. , Hammad, Eman A. , Hanif, Asif , Hanifi, Nasrin , Hankey, Graeme J. , Harsini, Sara , Hartmann, Phillipp , Hasan, Ikramul , Hashempur, Mohammad Hashem , Hassan, Amr , Hassan, Ibrahim Nagmeldin , Hayat, Khezar , Hezam, Kamal , Hiraike, Yuta , Holla, Ramesh , Hostiuc, Sorin , Htay, Mila Nu Nu , Huang, Junjie, Hushmandi, Kiavash , Hwang, Bing‐Fang , Ibitoye, Segun Emmanuel , Ibrahim, Khalid S. , Ibrayeva, Anel , Ikram, Jibran, Ilesanmi, Olayinka Stephen , Ilić, Irena , Ilić, Milena , Imodoye, Sikiru O. , Inbaraj, Leeberk Raja , Ionescu, Radu Tudor, Iqhrammullah, Muhammad , Irham, Lalu Muhammad , Ishaqui, Azfar Athar , Ismail, Nahlah Elkudssiah , Ismoldayev, Yerlan, Isola, Gaetano , Izquierdo‐Condoy, Juan S. , Jacob, Jaison , Jahanshahi, Ali , Jamal, Armaan , Jamali, Navid , James, Jerin , Jamshidi, Masoud , Jawaid, Talha, Jayasinghe, Yovanthi Anurangi , Jemal, Mohammed , Jeong, Seogsong , Jeswani, Bijay Mukesh , Jibat, Nathan Tolemariam , Jokar, Mohammad , Joó, Tamás , Joseph, Akaninyene Paul , Joseph, Mickaël Antoine , Joseph, Nitin , Joshi, Krupal , Jürisson, Mikk , K, Vaishali , Kakkar, Ashish Kumar , Kalani, Rizwan , Kalavani, Khalil , Kalra, Sanjay , Kamorudeen, Ramat T. , Kamyshnyi, Oleksandr , Kanaan, Saddam Fuad , Kanmodi, Kehinde Kazeem , Kantar, Rami S. , Kapoor, Neeti , Karajizadeh, Mehrdad , Karakasis, Paschalis , Karasneh, Reema A. , Kashoo, Faizan , Kashyap, Manoj Kumar , Kausar, Mohd Adnan , Kazemian, Sina , Kebede, Yabets Tesfaye , Kesse‐Guyot, Emmanuelle , Khademi, Reza , Khader, Yousef , Khajuria, Himanshu , Khaleel, Anas , Khalid, Sidra , Khalili, Anita , Khalili, Pantea , Khan, Maseer , Khan, Mohammad Idreesh , Khasbage, Sameer Uttamaro , Khatatbeh, Moawiah Mohammad , Khosla, Pavan , Khosravi, Sepehr , Kimokoti, Ruth W , Kısa, Adnan , Kishore, Ladli , Kivimäki, Mika , Kokkorakis, Michail , Kolahi, Ali‐Asghar , Kompani, Farzad , Kondybayeva, Аida , Korzh, Oleksii , Kostev, Karel , Laxminarayana, Sindhura Lakshmi Koulmane , Kua, Chong-Han , Kuddus, Mohammed , Kumar, Chandan , Kumar, G Anil , Kumar, Jogender , Kumar, Laksh , Kundu, Amartya , Kundu, Satyajit , Kunutsor, Setor K. , Kurniasari, Maria Dyah , Kytö, Ville , Lahariya, Chandrakant , Lakanova, Balzhan, Lantos, Tamás , Larebo, Yilma Markos , Lasrado, Savita , Lee�, HwaMin , Lee, Wei‐Chen , Leivaditis, Vasileios , Lenjisa, Jimma Likisa , Li, Ming‐Chieh , Li, Qiang , Li, Shaojie , Lim, Lee-Ling , Lodhi, Madeeha Shahzad , Lokunarangoda, Niroshan Chandrajith , López-Gil, José Francisco , Lorkowski, Stefan , Lucchetti, Giancarlo , Lui, Pauline Po Yee , Lv, Lei , Lytvyak, Ellina , Amin, Hawraz Ibrahim M. , Maffia, Pasquale , Magaña‐Gómez, Javier A. , Mahalleh, Mehrdad , Malik, Ahmad Azam , Malik, Tabarak , Malta, Déborah Carvalho , Mamand, Doste R. , Maniya, Muhammad Talha , Mannethodi, Kamaruddeen , Mansoor, Farheen, Mansourian, Marjan , Maqsood, Kaleem , Marateb, Hamid Reza , Marghani, Basma H. , Marino, Mirko , Martínez, Ramón , Martini, Daniela , Martini, Santi , Martorell, Miquel , März, Winfried , Marzouk, Sammer , Masi, Stefano , Mathur, Neeta , Matozinhos, Fernanda Penido , Mattiello, Rita , Mavrovounis, Georgios , McPhail, Steven , Mehto, Subhash , Meles, Hadush Negash , Menezes, Godfred Antony , Menon, Tara Pattilachan, Mensah, George A. , Merlino, Giovanni , Meštrović, Tomislav , Mettananda, Chamila Dinushi Kukulege , Mettananda, Sachith , Metwally, Mohamed M M, Mikrajab, Muhammad Agus, Minhas, Abdul Mannan Khan , Mittal, Madhukar , Mohamed, Nouh Saad , Ahmed, Khabab Abbasher Hussien Mohamed , Mohammad, Taj , Mohammadi, Abbas , Mohammadi, Mokhtar , Mohammadian-Hafshejani, Abdollah , Mohsen, Yazan , Shibabaw, Tewodros , Molokhia, Mariam , Monazzami, Amirabbas , Ghalibaf, AmirAli Moodi , Morovvati, Mahdis, Motappa, Rohith , Mozafar, Mehrdad , Mubarik, Sumaira , Muhammad, Jibran Sualeh , Munkhsaikhan, Yanjinlkham, Munshi, Anjana , Musa, Sani , Muthu, Sathish , Mwita, Julius Chacha , Myung, Woojae , Nainu, Firzan , Nargus, Shumaila , Nasrollahizadeh, Amir , Nassar, Mahmoud, Nauman, Javaid , Navaratna, Samidi Nirasha Kumari , Nawaiseh, Hala K. , Nayak, Biswa Prakash, Nega, Mulata Haile , Negash, Abigia Ashenafi , Negoi, Ionuţ , Abadi, Reza Nejad Shahrokh , Nematollahi, Mohammad Hadi , Nieddu, Luciano , Nketia, Richmond , Noubiap, Jean Jacques , Nri-Ezedi, Chisom Adaobi , Ntsekhe, Mpiko , Nugen, Fred , Oancea, Bogdan , Odat, Ramez M. , Oddi, Fabio Massimo , Oh, In‐Hwan , Okekunle, Akinkunmi Paul , Okonji, Osaretin Christabel , Olorukooba, Abdulhakeem Abayomi , Ong, Qi Chwen , Ordak, Michał , Orscelik, Atakan , Ortiz‐Prado, Esteban , Osuagwu, Uchechukwu Levi , Oumer, Abdu , Ouyahia, Amel , Özşahin, İlker , Padrón‐Monedero, Alicia , Padubidri, Jagadish Rao , Panos, Georgios D. , Papa, Mario Virgilio , Pardhan, Shahina , Passera, Roberto , Patel, Kunal Nitinkumar , Patel, Neel Navinkumar , Patel, Satyananda, Patil, Shankargouda, Patoulias, Dimitrios , Pattnaik, Snigdha, Toroudi, Hamidreza Pazoki, Pekarčíková, Jarmila , Peprah, Prince , Pereira, Gavin, Perico, Norberto , Perna, Simone , Petermann‐Rocha, Fanny , Pirnejad, Habibollah , Plotnikov, Evgenii, Poddighe, Dimitri , Poluru, Ramesh , Porntaveetus, Thantrira , Pradhan, Pranil Man Singh , Prasad, Manya , Prashant, Akila , Pugliese, Nicola Riccardo , Puvvula, Jagadeesh , Qiu, Jia-Yong , Radhakrishnan, Venkatraman, Raghav, Pankaja Raghav, Rahamon, Sheu Kadiri , Rahim, Hawbash Mohammed-Amin , Rahimi, Sajjad , Rahman, Muhammad Aziz , Raj, Jeffrey Pradeep , Raja, Adarsh , Rajendran, Judah , Rajput, Prashant , Ramadan, Mahmoud M. , Ramasamy, Chitra, Ramasamy, Shakthi Kumaran, Rashedi, Vahid , Rasouli‐Saravani, Ashkan , Rath, Shree , Rathi, Isha , Rathish, Devarajan , Rauniyar, Santosh Kumar , Rawassizadeh, Reza , Ray, Asit , Redwan, Elrashdy M , Rehman, Najeeb Ur , Remuzzi, Giuseppe , Rezaei, Nazila , Romadlon, Debby Syahru , Romoli, Michele , Rony, Moustaq Karim Khan , Ross, Allen Guy , Roy, Sharmistha , Roy, Shubhanjali , Russo, Michele , Saber-Ayad, Maha Mohamed , Sabet, Cameron John , Sadarangani, Kabir P. , Rafiei, Seyed Kiarash Sadat , Saddique, Muhammad Nabeel , Sadee, Bashdar Abuzed , Sadeghi, Masoumeh , Sadek, Bassem Shaban , Sadr, Hossein, Saeb, Mohammad Reza , Saeed, Mοhd , Saeedi, Maryam , Saghazadeh, Amene , Sagoe, Dominic , Sah, Ashok Kumar , Sharif‐Askari, Fatemeh Saheb , Sahebkar, Amirhossein , Sajadi, S. Mohammad, Sajid, Mirza Rizwan , Saki, Morteza , Sakshaug, Joseph W. , Salami, Afeez Abolarinwa , Saleem, Rahman Shah Zaib , Salihu, Abubakar Tijjani , Salimi, Sohrab , Samargandy, Saad J. , Samodra, Yoseph Leonardo , Samy, Abdallah M., Sarfo, Jacob Owusu , Sarmadi, Mohammad , Sarode, Gargi Sachin , Sassano, Michele , Sathian, Brijesh , Narayanan, Mukesh Kumar Sathya , Schlaich, Markus P. , Schuermans, Art , Schwarz, Ghil , Sejben, Anita , Selvaraj, Siddharthan , Semreen, Mohammad H. , Şenol, Yiğit Can , Şerban, Dragoş , Sethi, Yashendra , Setiawan, Christianus Heru , Shahid, Samiah , Shahini, Endrit , Shahrahmani, Fatemeh, Shahwan, Moyad Jamal , Shamim, Muhammad Aaqib , Shamsi, Anas , Shan, Dan, Shanawaz, Mohd , Shannawaz, Mohammed , Sharif, Nadim , Sharma, Bhoopesh Kumar , Sharma, Bunty, Sharma, Manoj , Sharma, Vishal , Shastry, Shamee , Sheidaei, Ali , Shenoy, Rekha R. , Shimels, Tariku , Shittu, Aminu , Shoaib, Ambreen , Shool, Sina , Shrestha, Sunil , Shuval, Kerem , Sia, Ching‐Hui , Siddig, Emmanuel Edwar , Siddiqi, Ahmed Kamal , Siddiqua, Ayesha , Silva, Diego Augusto Santos , Simkhada, Padam Prasad , Singh, Amit Kumar, Singh, Baljinder, Singh, Harpreet, Singh, Jasvinder A. , Singh, Lucky, Singh, Poornima Suryanath , Singh, Puneetpal , Sinha, Mukesh Kumar , Sinha, Ratnesh , Skryabin, Valentin Yurievich , Sorrentino, Michele , Spartalis, Michael , Stachteas, Panagiotis , Владимировна, Стародубова Антонина, Straube, Sebastian , Stubbs, Peter W. , Su, Chen‐Yang , Subramaniyan, Vetriselvan , Suhag, Alisha , Sulaieva, Oksana , Sun, Jing , Swain, Chandan Kumar , Szarpak, Łukasz , Y, Sree Sudha T, Damavandi, Payam Tabaee , Tabarés‐Seisdedos, Rafael , Tabatabaeizadeh, Seyed‐Amir , Tabche, Celine , Tadele, Afework , Ali, Eman T. , Soodejani, Moslem Taheri , Tajabadi, Shima, Talic, Stella , Talukder, Ashis , Zadeh, Seyed Saeed Tamehri , Tampa, Mircea Ştefan , Tantisattamo, Ekamol , Tariku, Mengistie Kassahun , Tavangar, Seyed Mohammad , Tedla, Mebrahtu G. , Teramoto, Masayuki , Tesfu, Azimeraw Arega , Tharwat, Ismaeel, Tharwat, Samar , Thienemann, Friedrich , Tiruye, Tenaw Yimer , Tleshev, Madi, Tomo, Sojit , Tonelli, Marcello , Touvier, Mathilde , Tran, An Thien, Tran, Thang Huu, Tristan, Christopher Daniel , Tse, Gary , Tseriotis, Vasilis‐Spyridon , Udoakang, Aniefiok John , Ullah, Atta , Ullah, Saeed , Umair, Muhammad, Upadhya, Dinesh , Upadhyay, Era , Usman, Jibrin Sammani , Ozsahin, Dilber Uzun , Uzunçıbuk, Hande , Varghese, Joe , Vasankari, Tommi Juhani , Vellingiri, Balachandar , Venketasubramanian, Narayanaswamy , Verma, Akshaya Kumar , Villalobos-Daniel, Victor Eduardo , Wan, Jin‐Yi , Wang, Cong , Wang, Nelson , Wang, Shaopan , Wang, Shu , Wang, Youxin , Wani, Tanveer A. , Waqar, Ahmed Bilal , Weintraub, Robert G, Wibowo, Yohanes Cakrapradipta, Wicaksana, Anggi Lukman , Wickramasinghe, Dakshitha Praneeth , Wilandika, Angga , Xu, Site , Xu, Suowen , Xu, Xiaoyue , Yadegar, Amirhossein , Yahoo, Saba, Yamagishi, Kazumasa , Yaribeygi, Habib , Yesuf, Subah Abderehim , Yon, Dong Keon , Yonemoto, Naohiro , Yuan, Quan, Yuzbashian, Emad , Zamagni, Giulia , Zawiah, Mohammed , Zeariya, Mohammed G M, Zeru, Eyael M, Zhang, Casper J. P. , Zhong, Claire Chenwen , Zhou, Xiao-Dong, Zhumagaliuly, Abzal , Zoromba, Mohamed Ali , Zumla, Alimuddin I. , Zyoud, Ahed H. , Zyoud, Shaher H. , Mokdad, Ali H. , Murray, Christopher J. L., Roth, Gregory A., Kheirallah, Khalid Ahmed , Saad, Aly M A , Sadeghi, Erfan

Mayo Clinic

JAMA | July 29, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jama.2026.8628 | PMID 42525403 Get It

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.
Computable phenotypes for research using real-world data: experiences from the NIH pragmatic trials collaboratory
Conte, Marisa , Fiol, Guilherme Del , Campbell, James R, Marsolo, Keith, Ezenwa, Miriam O. , Darby, Juanita E. , Matthie, Nadine , Ho, P Michael, Pressman, Alice, Justice, Morgan, Fist, Alex , Staman, Karen, Wu, Hulin, Conte, Marisa L , Del Fiol, Guilherme , Stephens, Kari A , Darby, Juanita E , Reynolds Geary, Carol , Faurot, Keturah R , Schlaeger, Judith M. , Campbell, James R., Cheville, Andrea , Stephens, Kari A. , Boyd, Andrew D. , Ho, P. Michael , Pressman, Alice , Geary, Carol , Faurot, Keturah R. , Staman, Karen L. , Wu, Hulin, Richesson, Rachel

Mayo Clinic

JAMIA Open | July 29, 2026 | Volume: 9 | Issue: 4 | Pages: No page available

10.1093/jamiaopen/ooag158 | PMID 42559354 Get It

Abstract Objectives Embedded pragmatic clinical trials (ePCTs) are conducted as part of routine clinical care and therefore use data collected from real-world data sources, such as electronic health record systems and administrative claims. A common approach for using these types of data across all phases of trial conduct is to create a computable phenotype (an explicitly defined data query data, including specified data types, data codes, and logical parameters) to capture patients with a clinical condition, exposure, symptom, characteristic, treatment, or outcome of interest. Materials and Methods The Electronic Health Record (EHR) Core Working Group of the NIH Pragmatic Trials Collaboratory captured the experiences of investigators in developing, adapting, and applying computable phenotype definitions in their studies. Results Four case studies describe different approaches to developing and using computable phenotypes in pragmatic trials. Discussion We recommend: (1) developing computable phenotypes as part of a team with multiple areas of expertise; (2) appropriate validation; (3) dissemination of salient details regarding phenotype creation; and (4) capturing and reporting any modifications made to phenotypes during the conduct of the trial. Conclusion A range of issues and decisions influence how computable phenotypes are developed and used in pragmatic clinical trials. Multidisciplinary teams that understand the context of the data, including the reason the data are collected and potential sources of bias, are best suited for the development and validation of phenotypes for ePCTs.
Peripheral cellular transcriptional changes are associated with Alzheimer’s disease related phenotypes 2330291
Wang, Xue, Tsai, Wei, Nguyen, Thuy , Reyes, Denise, Lowe, Val, Petersen, Ronald, Kantarci, Kejal, Carrasquillo, Minerva, Nho, Kwangsik, Saykin, Andrew, Reddy, Joseph, Allen, Mariet , Ertekin-Taner, Nilüfer, Chen, Xuan , Tsai, Wei, Lowe, Val J. , Petersen, Ronald C. , Kantarci, Kejal , Carrasquillo, Minerva M. , Nho, Kwangsik T. , Saykin, Andrew J. , Reddy, Joseph S. , Ertekin‐Taner, Nilüfer

Mayo Clinic

The Journal of Immunology | July 28, 2026 | Volume: 215 | Issue: Supplement_1 | Pages: No page available

10.1093/jimmun/vkag141.1795 Get It

Abstract Introduction Alzheimer’s disease (AD) is characterized by pathologies including amyloid, tau, neurodegeneration reflected in established blood biomarkers and track with clinical changes. However, the association between peripheral cell-specific signatures and AD-related phenotypes remain poorly characterized. Methods We analyzed bulk blood transcriptome data from the Mayo Clinic Study of Aging (MCSA) and Emory University Vascular study. We used BayesPrism, CIBERSORTx, and an in-house pipeline CNNreg to deconvolute these data and obtain peripheral cell proportions. Cell type specific transcripts were estimated with BayesPrism. We compared cell proportions between cases (AD/MCI) and controls. Association analysis was performed between cell type specific transcripts and AD-related phenotypes including diagnosis and cognition. Meta-analysis of transcripts associations and gene ontology analysis were conducted to assess the enriched pathways for significant genes. Results In MCSA, B and CD4+ T cells proportions are significantly lower while that of myeloid cells higher in cases. The Emory cohort had similar trends. We identified transcripts associated with AD-related phenotypes in CD4+ T and CD8+ T cells. In CD4+ T cells, transcripts downregulated in case are enriched in response to stimulus pathway, whereas those upregulated in negative regulation of immune response. Downregulation of CD4+ T genes enriched in extracellular matrix disassembly and epigenetic regulation and upregulation of those in protein localization associate with better cognition. In CD8+T cells, genes pertinent to vascular development were downregulated while those to metabolic processes were upregulated in cases. Downregulation of CD8+T genes involved in lipid transportation and upregulation of those in mitochondria associate with better cognition. Conclusion We identified peripheral cellular transcriptional changes associated with AD/MCI phenotypes and involved in important biological pathways, revealing potential disease mechanisms in AD. Funding Source RF1 AG051504 Topic Categories Neuroimmunology (NEUR)
Surgical Care in Rural and Underserved Populations: National Analysis of Attending Surgeons
Jacobsen, Nathan, Wong, Ryan, Ernst, Michael, Haran, Christa, Jabaay, Maxwell, Conrad-Schnetz, Kristen, Wallen, Tyler , Alexander, Vincent S , Wong, Ryan , Vogel, Andrew D. , Jabaay, Maxwell J, Conrad-Schnetz, Kristen J.

Mayo Clinic

Journal of the American College of Surgeons | July 27, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1097/xcs.0000000000002111 | PMID 42505035 Get It

Background: Rural communities face worsening surgical access because of hospital closures and workforce shortages. Although osteopathic physicians have historically practiced in rural settings, their contribution to the contemporary rural surgical workforce remains poorly defined. Study Design: Cross-sectional analysis of 74,404 US attending surgeons across seven specialties using the 2023 Centers for Medicare & Medicaid Services Doctors and Clinicians database. Practice addresses were linked to 2020 Rural-Urban Commuting Area codes, Area Deprivation Index quintiles, and census tract population density. Rural practice (mean Rural-Urban Commuting Area score ≥4) was modeled using multivariable logistic regression adjusted for specialty, graduation cohort, sex, Census division, and state urbanization, with state-clustered standard errors. Results: Rural practice was more common among DO than MD surgeons (18.3% vs 9.7%; risk difference, 8.6 percentage points; 95% CI, 7.6–9.6). Across all specialties, DO surgeons practiced in more socioeconomically deprived communities. After adjustment, DO surgeons had twice the odds of rural practice compared with MD surgeons (OR, 2.05; 95% CI, 1.85–2.28). Rural areas had 13.8 surgeons per 100,000 residents versus 23.6 per 100,000 in metropolitan areas. Surgeons graduating in 2010 or later had approximately half the odds of rural practice compared with those graduating in 1979 or earlier (adjusted OR, 0.48; 95% CI, 0.42–0.56). Conclusions: Osteopathic surgeons disproportionately practice in rural and socioeconomically disadvantaged communities, identifying an important workforce component for maintaining rural surgical access. The declining likelihood of rural practice among more recent training cohorts raises concerns regarding the future rural surgical workforce.
Resting Metabolic Rate in Collegiate Male Wrestlers: Cross-validation and Development of Prediction Equations
Dobbs, Ward C. , Magee, Meghan K., Ja, Fields, Sims, Jesse N. L., Saine, Noelle D., Jones, Margaret T., Jagim, Andrew R. , Fields, Jennifer B.

Mayo Clinic

Medicine & Science in Sports & Exercise | July 23, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1249/mss.0000000000004071 | PMID 42492233 Get It

Purpose: The purpose of the current study was to cross-validate previously developed RMR prediction equations using laboratory measurements of RMR as a criterion. Methods: National Collegiate Athletic Association (NCAA) Division I (n = 60) and III (n = 113) male wrestlers participated in the current study (n = 173; Age: 19.6 ± 1.5 yrs.; Height: 176.3 ± 6.3 cm; Weight: 76.6 ± 10.9 kg; Body Fat: 11.4 ± 3.0%). Indirect calorimetry was used to measure RMR and Skinfold thickness was used to estimate body fat percentage (BF%) during the preseason period under standardized dress (underwear only), fasting, and resting conditions. Results: Mean measured RMR was 2102±341 kcal·d −1 . All body mass-based RMR prediction equations significantly underestimated the measured RMR, with the exception of the Jagim and Schofield equations. The Tinsley fat-free mass (FFM) equation and the Cunningham equation had the lowest constant error (CE) values when compared to measured RMR (mean bias ± standard error: 80 ± 20 kcal and 126 ± 20 kcal·d −1 , respectively). Linear regression indicated the Tinsley FFM (R 2 = 0.422, RMSE = 279 kcals, %RMSE = 13.3%), and Cunningham FFM equations had the closest agreement to measured RMR (R 2 = 0.422, RMSE = 301 kcals, %RMSE = 14.3%), along with the Jagim equation for a body mass-based prediction equation (R 2 = 0.377, RMSE = 338 kcals, %RMSE = 16.1%). The standard error of the estimate (SEE) ranged from 260 to 272 kcal·day −1 across equations. Coefficients of determination (R 2 ) ranged from 37% to 42%. The new body mass and FFM-based equations exhibited good agreement based on the CE (26 and -13 kcal·day −1 ), RMSE (274 and 252 kcal·day −1 ), respectively. Conclusions: The newly developed equations demonstrated mean bias <2% of measured RMR.
Endoscopic Ultrasound-Guided Gallbladder Drainage
Baron, Todd H., Umar, Shifa, Lam, Gregory, Pannala, Rahul , Amateau, Stuart, Tielleman, Thomas, Khodorskiy, Dmitriy O., Companioni, Rafael Ching, Bedi, Gurneet, Torres, Ricardo Marrero, Chudy‐Onwugaje, Kenechukwu, Bhogal, Neil, Gelrud, Andrés , Gabr, Moamen, Shin, Eun Ji, Adler, Douglas G., Irani, Shayan , Kushnir, Vladimir, Sachdev, Mankanwal S., Sharma, Neil, Tyberg, Amy , Widmer, Jessica, Widmer, Jessica L , Canakis, Andrew , Baron, Todd H. , Amateau, Stuart K. , Tielleman, Thomas , Companioni, Rafael A. Ching, Chudy‐Onwugaje, Kenechukwu , Gabr, Moamen , Shin, Eun Ji , Adler, Douglas G. , Kushnir, Vladimir , Sachdev, Mankanwal S. , Sharma, Neil

Mayo Clinic

Journal of Clinical Gastroenterology | July 23, 2026 | Volume: 60 | Issue: 8 | Pages: 685-694

10.1097/mcg.0000000000002409 | PMID 42490390 Get It

Acute cholecystitis affects ∼200,000 individuals annually in the United States, with laparoscopic cholecystectomy as the gold standard treatment. However, in high-risk surgical candidates, alternative drainage methods are necessary. Percutaneous transhepatic gallbladder drainage (PT-GBD) has traditionally served as the primary alternative intervention, offering rapid decompression, but is limited by a negative impact on the patient’s quality of life, the risk of long-term or even permanent tube placement, adverse events, and high recurrence rates. Endoscopic approaches, such as endoscopic transpapillary gallbladder drainage (ET-GBD) and, more recently, endoscopic ultrasound-guided gallbladder drainage (EUS-GBD), have emerged as viable alternatives to PT-GBD. EUS-GBD, first introduced in 2007, offers technical and clinical outcomes comparable to PT-GBD with fewer adverse events, shorter hospital stays, and lower rates of recurrence. The introduction of lumen-apposing metal stents (LAMS) has revolutionized EUS-GBD, simplifying deployment and enabling subsequent internal gallbladder access, which allows additional interventions such as cholecystoscopy and stone removal. EUS-GBD is now supported by international guidelines, and 1 device has achieved FDA approval for the management of acute cholecystitis in nonsurgical candidates. Proper patient selection is essential, guided by multidisciplinary evaluation, with EUS-GBD contraindicated in specific scenarios such as gallbladder perforation, coagulopathy, and large-volume ascites. Technical considerations include choice of access site (transgastric versus transduodenal), stent type, and procedural route [direct (freehand) or wire-guided]. Postprocedural care and stent management remain variable and nonstandardized. Emerging data suggest that interval cholecystectomy can still be performed safely after EUS-GBD. As adoption of EUS-GBD with LAMS expands, structured training and standardization of practice are crucial to optimizing outcomes.
Characteristics of Gender-Diverse Patients With Breast Cancer
Cortina, Chandler S., Brazauskas, Ruta , Flanagan, Meghan R., Dill, Ellen D., Joseph, Kathe-Ann P., Trifonov, Alexandr , Kim, Esther A. , Kantor, Olga, Barmettler, Gabi , Rosenberger, Laura H., Jordan, Sumanas W., Perez, Megan M. , Jimenez, Rachel B., Smart, Alicia , Walker, J C, Lautner, Meeghan A., Siegel, Emily L., Brabender, Danielle , Al-Hilli, Zahraa, Cassidy, Michael R., Weiss, Anna, McCaffrey, Rachel L., Lee, M Catherine, Kaoutzanis, Christodoulos, Nguyen, Khoa N., Son, Jennifer D., Williams, Austin D., Madrigrano, Andrea, McLaughlin, Sarah A., Stolley, Melinda, Cortina, Chandler S. , Flanagan, Meghan R. , Mukhtar, Rita A. , Kantor, Olga , Rezak, Kristen M. , Rosenberger, Laura H. , Jimenez, Rachel , Kopkash, Katherine A. , Hughes, Tasha M. , Walker, Jasmine C. , Lautner, Meeghan Ann, Siegel, Emily , Al‐Hilli, Zahraa , Cassidy, Michael Ryan , Weiss, Anna, McCaffrey, Rachel Louise , Kaoutzanis, Christodoulos , Son, Jennifer D. , Williams, Austin David , Petroll, Andrew E. , Stolley, Melinda R.

Mayo Clinic

JAMA Network Open | July 23, 2026 | Volume: 9 | Issue: 7 | Pages: e2624824

10.1001/jamanetworkopen.2026.24824 | PMID 42490110 Get It

Importance Limited granular data exist on breast cancer in transgender, nonbinary, and/or gender-diverse (TGD) individuals. Objective To describe patient demographic and tumor clinicopathological variables, clinically relevant risk factors, method of breast cancer detection, treatment characteristics, and locoregional outcomes and to estimate a 5-year breast cancer–specific survival (BCSS). Design, Setting, and Participants This cohort study obtained data on patients treated from 1990 to 2023 from 22 US academic medical centers using institutional databases, electronic medical records, and tumor registries. Included participants were TGD individuals 18 years or older with stage 0 to IV breast cancer. A comparative breast cancer cohort was selected from the 2016 to 2021 Surveillance, Epidemiology, and End Results Program (SEER) breast cancer dataset. Data were analyzed from January to October 2025. Exposure Breast cancer. Main Outcomes and Measures Estimated 5-year BCSS and locoregional recurrence rates. Wilcoxon rank sum and χ 2 tests were used to compare continuous and categorical variables. Kaplan-Meier analysis was used to estimate 5-year BCSS. Results A total of 112 TGD persons (median [IQR] age at diagnosis, 42.5 [36.5-51.0] years; 104 individuals [92.9%] were assigned female at birth) with breast cancer and 1 with bilateral disease were included in the analysis. Forty-three patients (38.4%) used gender-affirming hormone therapy before diagnosis. Among the entire cohort, 58 patients (51.8%) detected their own breast cancer, 68 (60.7%) had a familial breast cancer history, and 16 (14.3%) had a pathogenic germline variant. Tumors were predominantly hormone receptor positive (96 [85.7%]) and early stage (29 [25.7%] ductal carcinoma in situ [DCIS]; 51 [45.1%] stage I). The TGD cohort, compared with patients with breast cancer in the SEER dataset (N = 480 915), was younger (median [IQR] age, 42.5 [36.5-51.0] years vs 62.0 [52.0-72.0] years), had a higher proportion of persons assigned male at birth (8 [7.1%] vs 3522 [0.7%]), more often had progesterone receptor–positive disease (89 [79.5%] vs 335 491 [69.8%]), and presented with earlier-stage disease (eg, DCIS: 29 [25.9%] vs 79 604 [16.6%]). With a median (IQR) follow-up time for the TGD cohort of 38 (24-74) months, 5-year BCSS was favorable at 96.2% (95% CI, 85.3%-99.0%). Conclusions and Relevance This cohort study of TGD patients with breast cancer found that this population was young and often detected their own tumors via self-examination, suggesting opportunities to improve early detection through screening for individuals at elevated risk. Although short-term BCSS appeared favorable, prospective research is essential to define evidence-based guidelines and elucidate long-term outcomes.
Pathology-Based Validation of Quantitative SPECT/CT in Patients With Suspected Transthyretin Amyloid Cardiomyopathy
Tersalvi, Gregorio , Bois, Melanie C. , Scott, Christopher G. , Carey, Patricia , Garmany, Armin , Davies, Daniel R. , HOFFMAN, Andrew C., Zhang, Jun , Hruska, Carrie B. , Jouni, Hayan, Rodriguez-Porcel, Martin G., Askew, J. Wells , Bois, John P. , Young, Kathleen A. , Anavekar, Nandan S., CHANG, IAN C., Grogan, Martha , Maleszewski, Joseph J. , Homb, Andrew, Redfield, Margaret M. , Dispenzieri, Angela , Maleszewski, Joseph J , Homb, Andrew C, Redfield, Margaret M , Chareonthaitawee, Panithaya , Johnson, Geoffrey B , AbouEzzeddine, Omar F , Hruska, Carrie B , Scott, Christopher , Tersalvi, Gregorio , Carey, Patricia , Rodriguez‐Porcel, Martin , Anavekar, Nandan S., Dispenzieri, Angela , Chareonthaitawee, Panithaya , Johnson, Geoffrey B. , AbouEzzeddine, Omar F.

Mayo Clinic

Circulation: Cardiovascular Imaging | July 23, 2026 | Volume: 19 | Issue: 8 | Pages: No page available

10.1161/circimaging.126.019832 | PMID 42488949 Get It

BACKGROUND: Technetium-based cardiac amyloid radionuclide imaging enables noninvasive diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM), but conventional planar and visual semiquantitative approaches have important limitations. We developed the quantitative 3-dimensional Mayo 3D Score, defined as the ratio of mean left ventricular myocardial radiotracer uptake to right atrial blood-pool uptake using computed tomography (CT)-fused single-photon emission CT (SPECT) volumes of interest, and sought to validate its diagnostic performance against myocardial pathology. METHODS: Consecutive patients who underwent 99m Tc-pyrophosphate SPECT/CT at Mayo Clinic for suspected ATTR-CM between June 2017 and January 2025 with archived myocardial tissue were included. Baseline characteristics, including demographics, echocardiogram, biomarkers, visual semiquantitative, and Mayo 3D Score metrics, were collected. Myocardial specimens underwent histopathologic confirmation of amyloid, with amyloid subtype determination and further semiquantitative grading of amyloid burden and deposition patterns. RESULTS: Among 230 patients (median age, 72 years; 78% male), 107 (47%) had ATTR-CM, of whom 9 had hereditary ATTR-CM. The Mayo 3D Score showed excellent discrimination against pathology (area under the receiver operating characteristic curve, 0.92 [0.88–0.96]), exceeding planar Perugini (0.87 [0.83–0.92]; P =0.006), and heart-to-contralateral lung ratio (0.86 [0.81–0.91]; P =0.004) and comparable to SPECT Perugini (0.90 [0.86–0.94]; P =0.12). A cutoff ≥1.0 yielded 86.0% sensitivity, 92.7% specificity, 91.1% positive predictive value, and 88.4% negative predictive value. Among ATTR-positive cases, the Mayo 3D Score correlated strongly with semiquantitative amyloid burden (Spearman ρ=0.69), was higher in pericellular than nodular deposition patterns ( P <0.001), and was not associated with vascular involvement ( P =0.42). CONCLUSIONS: In patients with suspected ATTR-CM undergoing 99m Tc-pyrophosphate SPECT/CT, the Mayo 3D Score demonstrated superior diagnostic performance compared with planar metrics and comparable to SPECT Perugini, while correlating with myocardial ATTR burden and deposition patterns on pathology. These findings support its integration as a quantitative adjunct within clinical diagnostic ATTR-CM workflows.
Ulcerative Colitis Management in Adults
Loeb, Lauren , Davis, Andrew M., Kinnucan, Jami A., Loeb, Lauren P, Kinnucan, Jami

Mayo Clinic

JAMA | July 22, 2026 | Volume: 336 | Issue: 12 | Pages: 1061

10.1001/jama.2026.8803 | PMID 42485028 Get It

This JAMA Clinical Guidelines Synopsis summarizes the American College of Gastroenterology’s (ACG) 2025 clinical guideline update on management of ulcerative colitis in adults.