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Maroufi, Seyed Farzad

https://orcid.org/0000-0001-7542-0411

Mayo Clinic

Tehran University of Medical Sciences

Citations 9

A233 Impact of aspiration catheter inner diameter on first-pass effect: a systematic review and meta-analysis
Reda, Abdullah, Maroufi, Seyed Farzad , Ramanathan, Kadirvel, Kallmes, David F. , Jazayeri, Seyed Behnam , Cortese, Jonathan , Hamouda, Abdelrahman M. , Ghozy, Sherief , Ramanathan, Kadirvel

8. Ischemic stroke – 8.13 Future directions in stroke management | September 3, 2025 | Volume: No volume available | Issue: No issue available | Pages: A87-A88

10.1136/jnis-2025-esmint.134 Get It

Impact of aspiration catheter inner diameter on first-pass effect: A systematic review and meta-analysis
Jazayeri, Seyed Behnam , Cortese, Jonathan , Reda, Abdelrahman, Maroufi, Seyed Farzad , Ghozy, Sherief , Kadirvel, Ramanathan , Kallmes, David F. , Cortese, Jonathan , Maroufi, Seyed Farzad , Ghozy, Sherief , Kadirvel, Ram , Kallmes, David F , Reda, Abdullah , Reda, Abdelrahman

Interventional Neuroradiology | June 10, 2025 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1177/15910199251345637 Get It

Background The first-pass effect (FPE) refers to the complete or near-complete revascularization with a single pass of mechanical thrombectomy devices. While previous claims suggest a link between larger catheters and the effectiveness of contact aspiration (CA) thrombectomy, no extensive research has confirmed if larger distal inner diameter (ID) catheters achieve higher FPE rates. Methods We searched PubMed, Scopus, and Web of Science to assess the impact of aspiration catheter distal ID size on FPE. The primary outcome was FPE rate, defined as thrombolysis in cerebral ischemia (TICI) grades 2c-3 at first pass, and the secondary outcome was modified FPE (TICI 2b-3 in a single pass). Aspiration catheters were categorized based on distal ID: 0.060–0.069 (medium bore), 0.070–0.074 (large bore), and greater than 0.074 inches (super-large bore). Rates of FPE were pooled using random effect models and compared using a Chi-square test. Results Our study included 34 articles with 4831 patients. FPE rates were 27.7% (95% CI, 15.1–45.3) for medium bore, 46.6% (95% CI, 33.7–59.9) for large, and 58.3% (95% CI, 44.8–70.7) for super-large catheters. The FPE rate was significantly higher for super-large bore catheters compared with other groups (χ² = 7.26, p = 0.03). A similar trend was observed for modified FPE rates, which were 51.1% (95% CI, 45.3–56.8) for medium bore, 60.0% (95% CI, 52.8–66.8) for large bore, and 80% (95% CI, 56.3–94.2) for super-large bore catheters (χ² = 8.14, p = 0.03). Conclusion Our analysis indicates that larger CA catheters are correlated with higher FPE rates.
Machine Learning–Based Rupture Risk Prediction for Intracranial Aneurysms: A Systematic Review and Meta-Analysis
Maroufi, Seyed Farzad , Pachón-Londoño, María José , Ghoche, Maged T. , Nguyen, Brandon , Turcotte, Evelyn L. , Patra, Devi P. , Olson, Vita A. , Halpin, Brooke S. , Bathini, Abhijith , Meyer, Jenna H., Krishna, Chandan , Charbel, Fady T. , Batjer, H. Hunt , Maroufi, S. Farzad, Ghoche, Maged, Olson, Vita, Bendok, Bernard R , Bathini, Abhijith R , Wang, Zhen , Morcos, Jacques J. , Bendok, Bernard R.

Neurosurgery | May 30, 2025 | Volume: 97 | Issue: 5 | Pages: 1072-1082

10.1227/neu.0000000000003531 Get It

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machine learning (ML) models may improve clinical practice by adding precision to risk assessment. This study aims to comprehensively assess the current landscape of ML applications in predicting the risk of aneurysm rupture and compare the performance with the widely used PHASES score. METHODS: A systematic review of PubMed, Scopus, and Web of Science was conducted. All studies using ML tools to predict the rupture risk of intracranial aneurysms were included. Meta-analysis was conducted with consideration to the ML algorithms and compared with the PHASES score. RESULTS: Thirty-six studies involving 22 462 patients were included in the final analysis. ML techniques, including 124 models using 25 algorithms, were employed. Among various ML models, while they had comparable diagnostic performance, deep learning exhibited a slightly better performance profile (sensitivity = 0.792, specificity = 0.788, and accuracy = 0.778 in external validation). Based on our analysis, ML, regardless of the algorithm, provides comparable sensitivity (0.743 vs 0.771, P = .60) and higher specificity (0.763 vs 0.507, P < .01) compared with the PHASES score. Consistently, pooling the area under the receiver operating characteristic curve (AUC) for 60 ML models and 5 PHASES score data, ML models exhibited higher AUC (0.84 vs 0.64, P < .01). Using hemodynamic parameters as input for models improved specificity ( P < .01) in the test sets without any significant changes in the sensitivity. The later improvement was not observed in the external validation sets. CONCLUSION: ML techniques have the potential to enhance the prediction of intracranial aneurysm rupture compared with traditional approaches, like the PHASES score. Incorporating hemodynamic parameters may further enhance the accuracy of ML models. Feature prospective studies are required to validate the utility of ML models for clinical integration.
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

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

10.1001/jamaneurol.2025.1522 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.
Risk factors for unruptured intracranial aneurysms in asymptomatic patients with autosomal dominant polycystic kidney disease: who needs screening? A systematic review and meta-analysis
Nguyen, Brandon , Halpin, Brooke S. , Olson, Vita A. , Putzler, Dillon , Ghoche, Maged T. , Pachón-Londoño, María José , Turcotte, Evelyn L. , Maroufi, Seyed Farzad , Segovia, Diana, Patra, Devi P. , Meyer, Fredric B. , Almader‐Douglas, Diana , Halpin, Brooke, Olson, Vita, Ghoche, Maged, Wang, Zhen , Bendok, Bernard R.

Journal of Neurosurgery | February 14, 2025 | Volume: 143 | Issue: 1 | Pages: 220-231

10.3171/2024.9.jns241175 Get It

OBJECTIVE Patients with autosomal dominant polycystic kidney disease (ADPKD) have been identified to have a significantly increased risk of developing intracranial aneurysms (IAs). These patients are diagnosed at younger ages and are also at increased risk for IA rupture. The objective of this systematic review and meta-analysis was to identify risk factors associated with IA detection during screening of asymptomatic ADPKD patients. METHODS The authors searched for studies reporting the prevalence of IA among patients with ADPKD screened using MRA, CTA, or DSA on PubMed, Embase, Google Scholar, Scopus, Web of Science, Cochrane Database of Systematic Reviews, and ClinicalTrials.gov prior to August 2023 by using individualized standardized search strategies. Eligibility of all retrieved studies was assessed according to the PRISMA guidelines. Risk of bias of the included observational studies was assessed using the Newcastle-Ottawa Scale. Meta-analysis was performed using a random-effects model. RESULTS Twenty-four observational studies involving 5907 patients with ADPKD were identified for quantitative analysis. The authors observed an overall prevalence of IA of 12.6%. They identified several risk factors for IA with statistically significantly increased odds for unruptured IA (UIA) detection, including female sex (18 studies, OR 1.63, 95% CI 1.37–1.94, I 2 = 0%), family history of either IA or subarachnoid hemorrhage (SAH) (12 studies, OR 2.17, 95% CI 1.68–2.81, I 2 = 0%), family history of SAH (3 studies, OR 2.67, 95% CI 1.25–5.71, I 2 = 66.0%), stage 3 or greater chronic kidney disease (CKD) (4 studies, OR 2.55, 95% CI 1.84–3.54, I 2 = 0%), and hypertension (13 studies, OR 1.41, 95% CI 1.04–1.91, I 2 = 34%). Age > 45 years, family history of ADPKD, smoking status, and presence of liver cysts did not reach statistical significance as risk factors during this meta-analysis. CONCLUSIONS The results of the authors’ meta-analysis suggest increased risk of UIA detection in screening of ADPKD patients who are female, have a family history of IA or SAH, have hypertension, or have moderate or more severe CKD. Given the increased prevalence of IA in ADPKD patients with these risk factors, these patients may stand to benefit from screening for IA early in treatment or at time of diagnosis, even if neurologically asymptomatic.
Impact of smoking on the detection of brain aneurysms in general population screening: a systematic review and meta-analysis
Ghoche, Maged T. , Maroufi, Seyed Farzad , Maalouf, Jorge Fouad , Pachón-Londoño, María José , Nguyen, Brandon , Halpin, Brooke S. , Turcotte, Evelyn L. , Patra, Devi P. , Krishna, Chandan , Turkmani, Ali , Ogilvy, Christopher S., Ogilvy, Christopher S. , Patra, Devi, Ogilvy, Christopher S , Maalouf, Joy M. El, Wang, Zhen , Bendok, Bernard R.

Journal of Neurosurgery | December 27, 2024 | Volume: 142 | Issue: 5 | Pages: 1397-1405

10.3171/2024.7.jns241015 Get It

OBJECTIVE While the relationship between smoking and subarachnoid hemorrhage is well established, data regarding the probability of detecting unruptured intracranial aneurysms (UIAs) in smokers remain sparse. The aim of this systematic review and meta-analysis is to provide a comprehensive understanding of the relationship between smoking and the likelihood of identifying UIAs in healthy asymptomatic patients who underwent brain imaging for indications unrelated to UIAs. METHODS A systematic review was conducted following the PRISMA guidelines. The PubMed and Scopus databases were searched for studies published before March 2024 that reported on the presence of UIAs in healthy asymptomatic patients who had undergone brain imaging for indications unrelated to UIAs. Three independent reviewers assessed the eligibility of all retrieved studies. Risk of bias for the included observational studies was assessed using the methodological index for non-randomized studies. Data on UIA prevalence, smoking status, and patient and aneurysm characteristics were extracted. The association between smoking and the presence of UIA was studied. A prevalence proportional meta-analysis was conducted across the included studies. A meta-analysis was performed with a random-effects model by using summary statistics from the included studies. RESULTS Six studies involving 47,788 patients who had undergone brain imaging were identified for quantitative analysis. The pooled UIA prevalence in the sample was 3.07% (95% CI 2.27%–4.16%). Patients who smoked had higher rates of aneurysm detection than the patients who did not smoke (pooled prevalence of 2.96%, 95% CI 2.68%–3.27% vs 2.23%, 95% CI 2.08%–2.39%). Although the relation between the two was not statistically significant (p = 0.06), smoking was associated with higher odds for UIA detection, yielding an OR of 1.34 (95% CI 1.07–1.67) with an I 2 value of 53%. CONCLUSIONS This study suggests a potentially higher risk of UIAs in patients who smoked than in those who never smoked. However, the results of this meta-analysis revealed that smoking was not statistically associated with higher UIA detection. This result could be explained by the limited number of studies published on this topic. If these findings reach statistical significance in future larger studies, it could justify revising guidelines to include cigarette smokers in intracranial aneurysm screening.
Cigarette Smoking and Observed Growth of Unruptured Intracranial Aneurysms: A Systematic Literature Review and Meta-Analysis
Pachón-Londoño, María José , Ghoche, Maged T. , Nguyen, Brandon , Maroufi, Seyed Farzad , Olson, Vita A. , Patra, Devi P. , Turcotte, Evelyn L. , Halpin, Brooke S. , Krishna, Chandan , Turkmani, Ali , Meyer, Fredric B. , Nguyen, Brandon A , Olson, Vita, Halpin, Brooke S , Bendok, Bernard R , Wang, Zhen , Bendok, Bernard R.

Stroke | September 24, 2024 | Volume: 55 | Issue: 10 | Pages: 2420-2430

10.1161/strokeaha.124.047539 Get It

BACKGROUND: Smoking and observed growth of intracranial aneurysms are known risk factors for rupture. The mechanism by which smoking increases this risk is not completely elucidated. Furthermore, an association between smoking and aneurysm growth has not been clearly defined in the literature. We hypothesize that smoking is associated with aneurysm growth, which, in turn, may serve as one of the mechanisms by which smoking drives rupture risk. METHODS: We report a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. Using the R software, we performed a meta-analysis to investigate the association between smoking and the growth of unruptured intracranial aneurysms. Studies on familial aneurysms and genetic syndromes known to increase the risk of aneurysms were excluded. RESULTS: Eighteen observational studies were included with a total of 3535 patients and 4289 aneurysms with a mean follow-up period ranging from 17 to 226 months. The mean age among the studies ranged from 38.4 to 73.9 years; 74% of patients were female. Ever-smoking status (odds ratio, 1.10 [95% CI, 0.87–1.38]) and current smoking status (odds ratio, 1.43 [95% CI, 0.84–2.43]) did not show a statistically significant association with growth of intracranial aneurysms. Patients currently smoking did not have a statistically significant association with the growth of intracranial aneurysms (odds ratio, 1.18 [95% CI, 0.72–1.93]) compared with patients without a smoking history. No significant association was found in patients who previously smoked compared with patients who never smoked (odds ratio, 1.46 [95% CI, 0.88–2.43]). CONCLUSIONS: Smoking is not clearly associated with the growth of unruptured intracranial aneurysms, despite trends being observed, there is no statistical association. The mechanism by which smoking increases rupture risk might not be growth. In patients for whom observation is recommended, the absence of growth over time in the setting of smoking history does not, therefore, imply protection from rupture.
Efficacy and safety of flow diverters in retreatment of recurrent intracranial aneurysms—A systematic review and meta-analysis
Zarrintan, Armin , Ghozy, Sherief , Maroufi, Seyed Farzad , Reda, Abdullah, Brinjikji, Waleed , Kadirvel, Ramanathan , Kallmes, David F. , Gajjar, Aryan , Ghozy, Sherief , Zarrintan, Armin

Interventional Neuroradiology | September 14, 2024 | Volume: 32 | Issue: 4 | Pages: 1729-1740

10.1177/15910199241282713 Get It

Background and purpose Treatment of recurrent intracranial aneurysms after their initial therapy has been a significant challenge in the field of neurointervention. Recently flow diverters stents are widely used for treating intracranial aneurysms. In this systematic review and meta-analysis, we assessed the safety and efficacy of flow diverter in treating recurrent or recanalized intracranial aneurysms. Methods This meta-analysis is reported following the PRISMA 2020 guidelines. We conducted a systematic review of literature in the PubMed, Embase, Web of Sciences, and Scopus databases. Pooled prevalence and the corresponding 95% are calculated from extracted data using a random-effect model. Results The systematic literature search included 21 studies involving 411 patients, with 135 (32.8%) being male and 276 (67.2%) being females with a total number of 447 aneurysms. The overall rate of adequate occlusion was 90.67% (95% CI: 84.23%–94.65%), and the rates were comparable between the surgery (93.48%), coiling (91.78%), and stenting (85.77%) groups. The overall pooled rate of complete occlusion was 81.80 (95% CI: 71.14%–89.13%). On doing a subgroup analysis, the complete occlusion rates were 89.68%, 84.39%, and 73.47% for the surgery, coiling, and stenting groups, respectively. The overall mortality rate and achieving modified Rankin scale score of 0-2 was 1.28% (95% CI: 0.45%–3.64%) and (95% CI: 89.92%–97.84%), respectively. No significant heterogeneity is noted in the included studies. Conclusion Flow diverter stents are an effective and safe method for retreating recurrent or residual intracranial aneurysms with a high rate of complete and adequate occlusion. The rate of mortality, intracerebral hemorrhage, and overall and procedural complications following using flow diverters for intracranial aneurysms is low.
Letter: Thrombosed Posterior Inferior Cerebellar Artery Aneurysm Mimicking a Medulla Oblongata Cavernous Malformation: 2-Dimensional Operative Video
Maroufi, Seyed Farzad , Turcotte, Evelyn L. , Bendok, Bernard R. , Bendok, Bernard R

Operative Neurosurgery | July 26, 2024 | Volume: 27 | Issue: 3 | Pages: 403-404

10.1227/ons.0000000000001296 Get It