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52. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Steinmetz, Jaimie D, Seeher, Katrin Maria, Schiess, Nicoline, Nichols, Emma, Cao, Bochen, Servili, Chiara, Cavallera, Vanessa, Cousin, Ewerton, Hagins, Hailey, Moberg, Madeline E, Mehlman, Max L, Abate, Yohannes Habtegiorgis, Abbas, Jaffar, Abbasi, Madineh Akram, Abbasian, Mohammadreza, Abbastabar, Hedayat, Abdelmasseh, Michael, Abdollahi, Mohammad, Abdollahi, Mozhan, Abdollahifar, Mohammad-Amin, Abd-Rabu, Rami, Abdulah, Deldar Morad, Abdullahi, Auwal, Abedi, Aidin, Abedi, Vida, Abeldańo Zuńiga, Roberto Ariel, Abidi, Hassan, Abiodun, Olumide, Aboagye, Richard Gyan, Abolhassani, Hassan, Aboyans, Victor, Abrha, Woldu Aberhe, Abualhasan, Ahmed, Abu-Gharbieh, Eman, Aburuz, Salahdein, Adamu, Lawan Hassan, Addo, Isaac Yeboah, Adebayo, Oladimeji M, Adekanmbi, Victor, Adekiya, Tayo Alex, Adikusuma, Wirawan, Adnani, Qorinah Estiningtyas Sakilah, Adra, Saryia, Afework, Tsion, Afolabi, Aanuoluwapo Adeyimika, Afraz, Ali, Afzal, Saira, Aghamiri, Shahin, Agodi, Antonella, Agyemang-Duah, Williams, 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Saswati, Das, Subasish, Dascalu, Ana Maria, Dash, Nihar Ranjan, Dashti, Mohsen, De la Hoz, Fernando Pio, de la Torre-Luque, Alejandro, De Leo, Diego, Dean, Frances E, Dehghan, Amin, Dehghan, Azizallah, Dejene, Hiwot, Demant, Daniel, Demetriades, Andreas K, Demissie, Solomon, Deng, Xinlei, Desai, Hardik Dineshbhai, Devanbu, Vinoth Gnana Chellaiyan, Dhama, Kuldeep, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dias da Silva, Diana, Diaz, Daniel, Dibas, Mahmoud, Ding, Delaney D, Dinu, Monica, Dirac, M Ashworth, Diress, Mengistie, Do, Thanh Chi, Do, Thao Huynh Phuong, Doan, Khanh Duy Khanh, Dodangeh, Milad, Doheim, Mohamed Fahmy, Dokova, Klara Georgieva, Dongarwar, Deepa, Dsouza, Haneil Larson, Dube, John, Duraisamy, Senbagam, Durojaiye, Oyewole Christopher, Dutta, Sulagna, Dziedzic, Arkadiusz Marian, Edinur, Hisham Atan, Eissazade, Negin, Ekholuenetale, Michael, Ekundayo, Temitope Cyrus, El Nahas, Nevine, El Sayed, Iman, Elahi Najafi, Mohammad Amin, Elbarazi, Iffat, Elemam, Noha Mousaad, Elgar, Frank J, Elgendy, Islam Y, Elhabashy, Hala Rashad, Elhadi, Muhammed, Elilo, Legesse Tesfaye, Ellenbogen, Richard G, Elmeligy, Omar Abdelsadek Abdou, Elmonem, Mohamed A, Elshaer, Mohammed, Elsohaby, Ibrahim, Emamverdi, Mehdi, Emeto, Theophilus I, Endres, Matthias, Esezobor, Christopher Imokhuede, Eskandarieh, Sharareh, Fadaei, Abdolmajid, Fagbamigbe, Adeniyi Francis, Fahim, Ayesha, Faramarzi, Ali, Fares, Jawad, Farjoud Kouhanjani, Mohsen, Faro, Andre, Farzadfar, Farshad, Fatehizadeh, Ali, Fathi, Mobina, Fathi, Saeid, Fatima, Syeda Anum Fatima, Feizkhah, Alireza, Fereshtehnejad, Seyed-Mohammad, Ferrari, Alize J, Ferreira, Nuno, Fetensa, Getahun, Firouraghi, Neda, Fischer, Florian, Fonseca, Ana Catarina, Force, Lisa M, Fornari, Arianna, Foroutan, Behzad, Fukumoto, Takeshi, Gadanya, Muktar A, Gaidhane, Abhay Motiramji, Galali, Yaseen, Galehdar, Nasrin, Gan, Quan, Gandhi, Aravind P, Ganesan, Balasankar, Gardner, William M, Garg, Naval, Gau, Shuo-Yan, Gautam, Rupesh K, Gebre, Teshome, Gebrehiwot, Mesfin, Gebremeskel, Gebreamlak Gebremedhn, Gebreslassie, Haftay Gebremedhin, Getacher, Lemma, Ghaderi Yazdi, Bardiya, Ghadirian, Fataneh, Ghaffarpasand, Fariborz, Ghanbari, Reza, Ghasemi, MohammadReza, Ghazy, Ramy Mohamed, Ghimire, Sailaja, Gholami, Ali, Gholamrezanezhad, Ali, Ghotbi, Elena, Ghozy, Sherief, Gialluisi, Alessandro, Gill, Paramjit Singh, Glasstetter, Logan M, Gnedovskaya, Elena V, Golchin, Ali, Golechha, Mahaveer, Goleij, Pouya, Golinelli, Davide, Gomes-Neto, Mansueto, Goulart, Alessandra C, Goyal, Anmol, Gray, Richard J, Grivna, Michal, Guadie, Habtamu Alganeh, Guan, Bin, Guarducci, Giovanni, Guicciardi, Stefano, Gunawardane, Damitha Asanga, Guo, Hanbing, Gupta, Bhawna, Gupta, Rajeev, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vivek Kumar, Gutiérrez, Reyna Alma, Habibzadeh, Farrokh, Hachinski, Vladimir, Haddadi, Rasool, Hadei, Mostafa, Hadi, Najah R, Haep, Nils, Haile, Teklehaimanot Gereziher, Haj-Mirzaian, Arvin, Hall, Brian J, Halwani, Rabih, Hameed, Sajid, Hamiduzzaman, Mohammad, Hammoud, Ahmad, Han, Hannah, Hanifi, Nasrin, Hankey, Graeme J, Hannan, Md. Abdul, Hao, Junwei, Harapan, Harapan, Hareru, Habtamu Endashaw, Hargono, Arief, Harlianto, Netanja I., Haro, Josep Maria, Hartman, Nicholas Nathaniel, Hasaballah, Ahmed I., Hasan, Faizul, Hasani, Hamidreza, Hasanian, Mohammad, Hassan, Amr, Hassan, Shoaib, Hassanipour, Soheil, Hassankhani, Hadi, Hassen, Mohammed Bheser, Haubold, Johannes, Hay, Simon I, Hayat, Khezar, Hegazy, Mohamed I, Heidari, Golnaz, Heidari, Mohammad, Heidari-Soureshjani, Reza, Hesami, Hamed, Hezam, Kamal, Hiraike, Yuta, Hoffman, Howard J, Holla, Ramesh, Hopf, Kathleen Pillsbury, Horita, Nobuyuki, Hossain, Md Mahbub, Hossain, Md. Belal, Hossain, Sahadat, Hosseinzadeh, Hassan, Hosseinzadeh, Mehdi, Hostiuc, Sorin, Hu, Chengxi, Huang, Junjie, Huda, Md. Nazmul, Hussain, Javid, Hussein, Nawfal R, Huynh, Hong-Han, Hwang, Bing-Fang, Ibitoye, Segun Emmanuel, Ilaghi, Mehran, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Immurana, Mustapha, Iravanpour, Farideh, Islam, Sheikh Mohammed Shariful, Ismail, Faisal, Iso, Hiroyasu, Isola, Gaetano, Iwagami, Masao, Iwu, Chidozie C D, Iyer, Mahalaxmi, Jaan, Ali, Jacob, Louis, Jadidi-Niaragh, Farhad, Jafari, Mahboobeh, Jafarinia, Morteza, Jafarzadeh, Abdollah, Jahankhani, Kasra, Jahanmehr, Nader, Jahrami, Haitham, Jaiswal, Abhishek, Jakovljevic, Mihajlo, Jamora, Roland Dominic G, Jana, Somnath, Javadi, Nilofer, Javed, Saad, Javeed, Saad, Jayapal, Sathish Kumar, Jayaram, Shubha, Jiang, Heng, Johnson, Catherine Owens, Johnson, Walter D, Jokar, Mohammad, Jonas, Jost B, Joseph, Abel, Joseph, Nitin, Joshua, Charity Ehimwenma, Jürisson, Mikk, Kabir, Ali, Kabir, Zubair, Kabito, Gebisa Guyasa, Kadashetti, Vidya, Kafi, Fatemeh, Kalani, Rizwan, Kalantar, Farnaz, Kaliyadan, Feroze, Kamath, Ashwin, Kamath, Sagarika, Kanchan, Tanuj, Kandel, Amit, Kandel, Himal, Kanmodi, Kehinde Kazeem, Karajizadeh, Mehrdad, Karami, Jafar, Karanth, Shama D, Karaye, Ibraheem M, Karch, André, Karimi, Aliasghar, Karimi, Hanie, Karimi Behnagh, Arman, Kasraei, Hengameh, Kassebaum, Nicholas J, Kauppila, Joonas H, Kaur, Harkiran, Kaur, Navjot, Kayode, Gbenga A, Kazemi, Foad, Keikavoosi-Arani, Leila, Keller, Cathleen, Keykhaei, Mohammad, Khadembashiri, Mohammad Amin, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajuria, Himanshu, Khalaji, Amirmohammad, Khamesipour, Faham, Khammarnia, Mohammad, Khan, Maseer, Khan, Moien AB, Khan, Yusra H, Khan Suheb, Mahammed Ziauddin, Khanmohammadi, Shaghayegh, Khanna, Tripti, Khatab, Khaled, Khatatbeh, Haitham, Khatatbeh, Moawiah Mohammad, Khateri, Sorour, Khatib, Mahalaqua Nazli, Khayat Kashani, Hamid Reza, Khonji, Mohammad Saeid, khorashadizadeh, Fatemeh, Khormali, Moein, Khubchandani, Jagdish, Kian, Saeid, Kim, Grace, Kim, Jihee, Kim, Min Seo, Kim, Yun Jin, Kimokoti, Ruth W, Kisa, Adnan, Kisa, Sezer, Kivimäki, Mika, Kochhar, Sonali, Kolahi, Ali-Asghar, Koly, Kamrun Nahar, Kompani, Farzad, Koroshetz, Walter J, Kosen, Soewarta, Kourosh Arami, Masoumeh, Koyanagi, Ai, Kravchenko, Michael A, Krishan, Kewal, Krishnamoorthy, Vijay, Kuate Defo, Barthelemy, Kuddus, Md Abdul, Kumar, Ashish, Kumar, G Anil, Kumar, Manasi, Kumar, Nithin, Kumsa, Netsanet Bogale, Kundu, Satyajit, Kurniasari, Maria Dyah, Kusuma, Dian, Kuttikkattu, Ambily, Kyu, Hmwe Hmwe, La Vecchia, Carlo, Ladan, Muhammad Awwal, Lahariya, Chandrakant, Laksono, Tri, Lal, Dharmesh Kumar, Lallukka, Tea, Lám, Judit, Lami, Faris Hasan, Landires, Iván, Langguth, Berthold, Lasrado, Savita, Latief, Kamaluddin, Latifinaibin, Kaveh, Lau, Kathryn Mei-Ming, Laurens, Matthew B, Lawal, Basira Kankia, Le, Long Khanh Dao, Le, Thao Thi Thu, Ledda, Caterina, Lee, Munjae, Lee, Sang-woong, Lee, Seung Won, Lee, Wei-Chen, Lee, Yo Han, Leonardi, Matilde, Lerango, Temesgen L, Li, Ming-Chieh, Li, Wei, Ligade, Virendra S, Lim, Stephen S, Linehan, Christine, Liu, Chaojie, Liu, Jue, Liu, Wei, Lo, Chun-Han, Lo, Warren David, Lobo, Stany W, Logroscino, Giancarlo, Lopes, Graciliana, Lopukhov, Platon D, Lorenzovici, László, Lorkowski, Stefan, Loureiro, Joana A, Lubinda, Jailos, Lucchetti, Giancarlo, Lutzky Saute, Ricardo, Ma, Zheng Feei, Mabrok, Mahmoud, Machoy, Monika, Madadizadeh, Farzan, Magdy Abd El Razek, Mohammed, Maghazachi, Azzam A, Maghbouli, Nastaran, Mahjoub, Soleiman, Mahmoudi, Morteza, Majeed, Azeem, Malagón-Rojas, Jeadran N., Malakan Rad, Elaheh, Malhotra, Kashish, Malik, Ahmad Azam, Malik, Iram, Mallhi, Tauqeer Hussain, Malta, Deborah Carvalho, Manilal, Aseer, Mansouri, Vahid, Mansournia, Mohammad Ali, Marasini, Bishnu P, Marateb, Hamid Reza, Maroufi, Seyed Farzad, Martinez-Raga, Jose, Martini, Santi, Martins-Melo, Francisco Rogerlândio, Martorell, Miquel, März, Winfried, Marzo, Roy Rillera, Massano, João, Mathangasinghe, Yasith, Mathews, Elezebeth, Maude, Richard James, Maugeri, Andrea, Maulik, Pallab K, Mayeli, Mahsa, Mazaheri, Maryam, McAlinden, Colm, McGrath, John J, Meena, Jitendra Kumar, Mehndiratta, Man Mohan, Mendez-Lopez, Max Alberto Mendez, Mendoza, Walter, Mendoza-Cano, Oliver, Menezes, Ritesh G, Merati, Mohsen, Meretoja, Atte, Merkin, Alexander, Mersha, Abera M, Mestrovic, Tomislav, Mi, Tianyue, Miazgowski, Tomasz, Michalek, Irmina Maria, Mihretie, Ephrem Tesfaye, Minh, Le Huu Nhat, Mirfakhraie, Reza, Mirica, Andreea, Mirrakhimov, Erkin M, Mirzaei, Mehdi, Misganaw, Awoke, Misra, Sanjeev, Mithra, Prasanna, Mizana, Biru Abdissa, Mohamadkhani, Ashraf, Mohamed, Nouh Saad, Mohammadi, Esmaeil, Mohammadi, Hiwa, Mohammadi, Shadieh, Mohammadi, Soheil, Mohammadshahi, Marita, Mohammed, Mustapha, Mohammed, Salahuddin, Mohammed, Shafiu, Mohan, Syam, Mojiri-forushani, Hoda, Moka, Nagabhishek, Mokdad, Ali H, Molinaro, Sabrina, Möller, Holger, Monasta, Lorenzo, Moniruzzaman, Md, Montazeri, Fateme, Moradi, Maryam, Moradi, Yousef, Moradi-Lakeh, Maziar, Moraga, Paula, Morovatdar, Negar, Morrison, Shane Douglas, Mosapour, Abbas, Mosser, Jonathan F, Mossialos, Elias, Motaghinejad, Majid, Mousavi, Parsa, Mousavi, Seyed Ehsan, Mubarik, Sumaira, Muccioli, Lorenzo, Mughal, Faraz, Mukoro, George Duke, Mulita, Admir, Mulita, Francesk, Musaigwa, Fungai, Mustafa, Ahmad, Mustafa, Ghulam, Muthu, Sathish, Nagarajan, Ahamarshan Jayaraman, Naghavi, Pirouz, Naik, Ganesh R, Nainu, Firzan, Nair, Tapas Sadasivan, Najmuldeen, Hastyar Hama Rashid, Nakhostin Ansari, Noureddin, Nambi, Gopal, Namdar Areshtanab, Hossein, Nargus, Shumaila, Nascimento, Bruno Ramos, Naser, Abdallah Y, Nashwan, Abdulqadir J J, Nasoori, Hadis, Nasreldein, Ahmed, Natto, Zuhair S, Nauman, Javaid, Nayak, Biswa Prakash, Nazri-Panjaki, Athare, Negaresh, Mohammad, Negash, Hadush, Negoi, Ionut, Negoi, Ruxandra Irina, Negru, Serban Mircea, Nejadghaderi, Seyed Aria, Nematollahi, Mohammad Hadi, Nesbit, Olivia D, Newton, Charles Richard James, Nguyen, Dang H, Nguyen, Hau Thi Hien, Nguyen, Hien Quang, 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Pacheco-Barrios, Kevin, Padubidri, Jagadish Rao, Pal, Pramod Kumar, Palange, Padmavali Nanaji, Palladino, Claudia, Palladino, Raffaele, Palma-Alvarez, Raul Felipe, Pan, Feng, Panagiotakos, Demosthenes, Panda-Jonas, Songhomitra, Pandey, Anamika, Pandey, Ashok, Pandian, Jeyaraj Durai, Pangaribuan, Helena Ullyartha, Pantazopoulos, Ioannis, Pardhan, Shahina, Parija, Pragyan Paramita, Parikh, Romil R, Park, Seoyeon, Parthasarathi, Ashwaghosha, Pashaei, Ava, Patel, Jay, Patil, Shankargouda, Patoulias, Dimitrios, Pawar, Shrikant, Pedersini, Paolo, Pensato, Umberto, Pereira, David M, Pereira, Jeevan, Pereira, Maria Odete, Peres, Mario F P, Perico, Norberto, Perna, Simone, Petcu, Ionela-Roxana, Petermann-Rocha, Fanny Emily, Pham, Hoang Tran, Phillips, Michael R, Pinilla-Monsalve, Gabriel D, Piradov, Michael A, Plotnikov, Evgenii, Poddighe, Dimitri, Polat, Burcu, Poluru, Ramesh, Pond, Constance Dimity, Poudel, Govinda Raj, Pouramini, Alireza, Pourbagher-Shahri, Ali Mohammad, Pourfridoni, Mohammad, Pourtaheri, Naeimeh, Prakash, Peralam Yegneswaran, Prakash, Sanjay, Prakash, V, Prates, Elton Junio Sady, Pritchett, Natalie, Purnobasuki, Hery, Qasim, Nameer Hashim, Qattea, Ibrahim, Qian, Gangzhen, Radhakrishnan, Venkatraman, Raee, Pourya, Raeisi Shahraki, Hadi, Rafique, Ibrar, Raggi, Alberto, Raghav, Pankaja Raghav, Rahati, Meghdad M, Rahim, Fakher, Rahimi, Zahra, Rahimifard, Mahban, Rahman, Md Obaidur, Rahman, Mohammad Hifz Ur, Rahman, Mosiur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Rahmani, Shayan, Rahmani Youshanlouei, Hamed, Rahmati, Masoud, Raj Moolambally, Sheetal, Rajabpour-Sanati, Ali, Ramadan, Hazem, Ramasamy, Shakthi Kumaran, Ramasubramani, Premkumar, Ramazanu, Sheena, Rancic, Nemanja, Rao, Indu Ramachandra, Rao, Sowmya J, Rapaka, Deepthi, Rashedi, Vahid, Rashid, Ahmed Mustafa, Rashidi, Mohammad-Mahdi, Rashidi Alavijeh, Mehran, Rasouli-Saravani, Ashkan, Rawaf, Salman, Razo, Christian, Redwan, Elrashdy Moustafa Mohamed, Rekabi Bana, Atefe, Remuzzi, Giuseppe, Rezaei, Nazila, Rezaei, Negar, Rezaei, Nima, Rezaeian, Mohsen, Rhee, Taeho Gregory, Riad, Abanoub, Robinson, Stephen R, Rodrigues, Mónica, Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo, Rogowski, Emma L B, Romoli, Michele, Ronfani, Luca, Roy, Priyanka, Roy Pramanik, Koushik, Rubagotti, Enrico, Ruiz, Milagros A, Russ, Tom C, S Sunnerhagen, Katharina, Saad, Aly M A, Saadatian, Zahra, Saber, Korosh, SaberiKamarposhti, Morteza, Sacco, Simona, Saddik, Basema, Sadeghi, Erfan, Sadeghian, Saeid, Saeed, Umar, Saeed, Usman, Safdarian, Mahdi, Safi, Sher Zaman, Sagar, Rajesh, Sagoe, Dominic, Saheb Sharif-Askari, Fatemeh, Saheb Sharif-Askari, Narjes, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahraian, Mohammad Ali, Sajedi, Seyed Aidin, Sakshaug, Joseph W, Saleh, Mohamed A, Salehi Omran, Hossein, Salem, Marwa Rashad, Salimi, Sohrab, Samadi Kafil, Hossein, Samadzadeh, Sara, Samargandy, Saad, Samodra, Yoseph Leonardo, Samuel, Vijaya Paul, Samy, Abdallah M, Sanadgol, Nima, Sanjeev, Rama Krishna, Sanmarchi, Francesco, Santomauro, Damian Francesco, Santri, Ichtiarini Nurullita, Santric-Milicevic, Milena M, Saravanan, Aswini, Sarveazad, Arash, Satpathy, Maheswar, Saylan, Mete, Sayyah, Mehdi, Scarmeas, Nikolaos, Schlaich, Markus P, Schuermans, Art, Schwarzinger, Michaël, Schwebel, David C, Selvaraj, Siddharthan, Sendekie, Ashenafi Kibret, Sengupta, Pallav, Senthilkumaran, Subramanian, Serban, Dragos, Sergindo, Mihretu Tagesse, Sethi, Yashendra, SeyedAlinaghi, SeyedAhmad, Seylani, Allen, Shabani, Mohammad, Shabany, Maryam, Shafie, Mahan, Shahabi, Saeed, Shahbandi, Ataollah, Shahid, Samiah, Shahraki-Sanavi, Fariba, Shahsavari, Hamid R, Shahwan, Moyad Jamal, Shaikh, Masood Ali, Shaji, KS, Sham, Sunder, Shama, Adisu Tafari T, Shamim, Muhammad Aaqib, Shams-Beyranvand, Mehran, Shamsi, Mohammad Anas, Shanawaz, Mohd, Sharath, Medha, Sharfaei, Sadaf, Sharifan, Amin, Sharma, Manoj, Sharma, Rajesh, Shashamo, Bereket Beyene, Shayan, Maryam, Sheikhi, Rahim Ali, Shekhar, Shashank, Shen, Jiabin, Shenoy, Suchitra M, Shetty, Pavanchand H, Shiferaw, Desalegn Shiferaw, Shigematsu, Mika, Shiri, Rahman, Shittu, Aminu, Shivakumar, K M, Shokri, Fereshteh, Shool, Sina, Shorofi, Seyed Afshin, Shrestha, Sunil, Siankam Tankwanchi, Akhenaten Benjamin, Siddig, Emmanuel Edwar, Sigfusdottir, Inga Dora, Silva, João Pedro, Silva, Luís Manuel Lopes Rodrigues, Sinaei, Ehsan, Singh, Balbir Bagicha, Singh, Garima, Singh, Paramdeep, Singh, Surjit, Sirota, Sarah Brooke, Sivakumar, Shravan, Sohag, Abdullah Al Mamun, Solanki, Ranjan, Soleimani, Hamidreza, Solikhah, Solikhah, Solomon, Yerukneh, Solomon, Yonatan, Song, Suhang, Song, Yimeng, Sotoudeh, Houman, Spartalis, Michael, Stark, Benjamin A, Starnes, Joseph R, Starodubova, Antonina V, Stein, Dan J, Steiner, Timothy J, Stovner, Lars Jacob, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sultana, Abida, Sun, Jing, Sunkersing, David, Sunny, Angel, Susianti, Hani, Swain, Chandan Kumar, Szeto, Mindy D, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabai, Shima, Tabish, Mohammad, Taheri, Majid, Tahvildari, Azin, Tajbakhsh, Ardeshir, Tampa, Mircea, Tamuzi, Jacques JL Lukenze, Tan, Ker-Kan, Tang, Haosu, Tareke, Minale, Tarigan, Ingan Ukur, Tat, Nathan Y, Tat, Vivian Y, Tavakoli Oliaee, Razieh, Tavangar, Seyed Mohammad, Tavasol, Arian, Tefera, Yibekal Manaye, Tehrani-Banihashemi, Arash, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Teramoto, Masayuki, Tesfaye, Amensisa Hailu, Tesfaye, Edosa Geta, Tesler, Riki, Thakali, Ocean, Thangaraju, Pugazhenthan, Thapa, Rajshree, Thapar, Rekha, Thomas, Nikhil Kenny, Thrift, Amanda G, Ticoalu, Jansje Henny Vera, Tillawi, Tala, Toghroli, Razie, Tonelli, Marcello, Tovani-Palone, Marcos Roberto, Traini, Eugenio, Tran, Nghia Minh, Tran, Ngoc-Ha, Tran, Phu Van, Tromans, Samuel Joseph, Truelsen, Thomas Clement, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsegay, Guesh Mebrahtom, Tsermpini, Evangelia Eirini, Tualeka, Abdul Rohim, Tufa, Derara Girma, Ubah, Chukwudi S, Udoakang, Aniefiok John, Ulhaq, Inam, Umair, Muhammad, Umakanthan, Srikanth, Umapathi, Krishna Kishore, Unim, Brigid, Unnikrishnan, Bhaskaran, Vaithinathan, Asokan Govindaraj, Vakilian, Alireza, Valadan Tahbaz, Sahel, Valizadeh, Rohollah, Van den Eynde, Jef, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vaziri, Siavash, Vellingiri, Balachandar, Venketasubramanian, Narayanaswamy, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafańe, Jorge Hugo, Villani, Leonardo, Vinueza Veloz, Andres Fernando, Viskadourou, Maria, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Volovat, Simona Ruxandra, Vu, Loc Tri, Vujcic, Isidora S, Wagaye, Birhanu, Waheed, Yasir, Wahood, Waseem, Walde, Mandaras Tariku, Wang, Fang, Wang, Shu, Wang, Yanzhong, Wang, Yuan-Pang, Waqas, Muhammad, Waris, Abdul, Weerakoon, Kosala Gayan, Weintraub, Robert G, Weldemariam, Abrha Hailay, Westerman, Ronny, Whisnant, Joanna L, Wickramasinghe, Dakshitha Praneeth, Wickramasinghe, Nuwan Darshana, Willekens, Barbara, Wilner, Lauren B, Winkler, Andrea Sylvia, Wolfe, Charles D A, Wu, Ai-Min, Wulf Hanson, Sarah, Xu, Suowen, Xu, Xiaoyue, Yadollahpour, Ali, Yaghoubi, Sajad, Yahya, Galal, Yamagishi, Kazumasa, Yang, Lin, Yano, Yuichiro, Yao, Yao, Yehualashet, Sisay Shewasinad, Yeshaneh, Alex, Yesiltepe, Metin, Yi, Siyan, Yiğit, Arzu, Yiğit, Vahit, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yu, Chuanhua, Yusuf, Hadiza, Zadey, Siddhesh, Zahedi, Mohammad, Zakham, Fathiah, Zaki, Nazar, Zali, Alireza, Zamagni, Giulia, Zand, Ramin, Zandieh, Ghazal G Z, Zangiabadian, Moein, Zarghami, Amin, Zastrozhin, Mikhail Sergeevich, Zeariya, Mohammed G M, Zegeye, Zelalem Banjaw, Zeukeng, Francis, Zhai, Chunxia, Zhang, Chen, Zhang, Haijun, Zhang, Yunquan, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Yang, Zheng, Peng, Zhou, Hengxing, Zhu, Bin, Zhumagaliuly, Abzal, Zielińska, Magdalena, Zikarg, Yossef Teshome, Zoladl, Mohammad, Murray, Christopher J L, Ong, Kanyin Liane, Feigin, Valery L, Vos, Theo, and Dua, Tarun
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- 2024
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53. Radiologistsʼ Rating for Comparative Qualitative Assessment of Intravoxel Incoherent Motion Using Novel Analysis Methods
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Baidya Kayal, Esha, Kandasamy, Devasenathipathy, Yadav, Richa, Khare, Kedar, Bakhshi, Sameer, Sharma, Raju, and Mehndiratta, Amit
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- 2024
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54. Visual Tracking Nonlinear Model Predictive Control Method for Autonomous Wind Turbine Inspection.
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Abdelhakim Amer, Mohit Mehndiratta, Jonas le Fevre Sejersen, Huy Xuan Pham, and Erdal Kayacan
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- 2023
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55. Numerical Solution for 1-D Consolidation of Partially Saturated Soil Under Cyclic Loading
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Singh, D. K., Mehndiratta, S., Vishwakarma, R. J., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Shrikhande, Manish, editor, Agarwal, Pankaj, editor, and Kumar, P. C. Ashwin, editor
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- 2023
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56. Consolidation of Layered Soils with Variable Compressibility
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Singh, Deepak Kumar, Kumawat, Chitranshu, Mehndiratta, Siddharth, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Agnihotri, Arvind Kumar, editor, Reddy, Krishna R., editor, and Chore, H. S., editor
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- 2023
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57. The application of nanoparticles as advanced drug delivery systems in Attenuating COPD
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Jessamine, Victoria, Mehndiratta, Samir, De Rubis, Gabriele, Paudel, Keshav Raj, Shetty, Saritha, Suares, Divya, Chellappan, Dinesh Kumar, Oliver, Brian G., Hansbro, Phillip M., and Dua, Kamal
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- 2024
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58. Bibliometric Analysis of the Impact of Blockchain Technology on the Tourism Industry
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Anand, Garima, primary, Shandilya, Anish, additional, Gupta, Varuna, additional, and Mehndiratta, Vandana, additional
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- 2023
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59. The application of nanoparticles as advanced drug delivery systems in Attenuating COPD
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Victoria Jessamine, Samir Mehndiratta, Gabriele De Rubis, Keshav Raj Paudel, Saritha Shetty, Divya Suares, Dinesh Kumar Chellappan, Brian G. Oliver, Phillip M. Hansbro, and Kamal Dua
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Drug delivery ,COPD ,Nanoparticles ,Polymeric nanoparticles ,miRNA nanotherapeutics ,Clinical trials ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a dilapidating condition which is characterized by inflammation, an excess in free radical generation and airway obstruction. Currently, the drugs commercially available for the management of COPD pose several limitations such as systemic adverse effects, including bone density loss and an increased risk of developing pneumonia. Moreover, another limitation includes the need for regular and frequent dosing regimens; which can affect the adherence to the therapy. Furthermore, these current treatments provide symptomatic relief; however, they cannot stop the progression of COPD. Comparatively, nanoparticles (NPs) provide great therapeutic potential to treat COPD due to their high specificity, biocompatibility, and higher bioavailability. Furthermore, the NP-based drug delivery systems involve less frequent dosing requirements and in smaller doses which assist in minimizing side effects. In this review, the benefits and limitations of conventional therapies are explored, while providing an in-depth insight on advanced applications of NP-based systems in the treatment of COPD.
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- 2024
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60. A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis
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Antonio Cerdán Cerdá, Nicola Toschi, Constantina A Treaba, Valeria Barletta, Elena Herranz, Ambica Mehndiratta, Jose A Gomez-Sanchez, Caterina Mainero, and Silvia De Santis
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axonal pathology ,multiple sclerosis ,MRI ,Medicine ,Science ,Biology (General) ,QH301-705.5 - Abstract
Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.
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- 2024
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61. Organizational Formation for Priority Setting: Historical Perspectives and Thematic Analysis of India’s Health Technology Assessment Agency
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Victoria Y. Fan, Abha Mehndiratta, Jubilee Ahazie, Javier Guzman, Shankar Prinja, T. Sundararaman, and Soumya Swaminathan
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Health technology assessment ,India ,organizational behavior ,political economy ,priority setting ,Medicine (General) ,R5-920 ,Public aspects of medicine ,RA1-1270 - Abstract
Countries pursuing universal health coverage must set priorities to determine which benefits to add to a national health program, but the roles that organizations play are less understood. This article investigates the case of the formation of an organization with a mandate for choice of technology for public health interventions and priorities, the Health Technology Assessment India. First, we narrate a chronology of agenda setting and adoption of national policy for organizational formation drawing on historical documentation, publicly available literature, and lived experiences from coauthors. Next, we conduct a thematic analysis that examines windows of opportunity, enabling factors, barriers and conditions, roles of stakeholders, messaging and framing, and specific administrative and bureaucratic tools that facilitated organization formation. This case study shows that organizational formation relied on the identification of multiple champions with sufficient seniority and political authority across a wide group of organizations, forming a coalition of broad base support, who were keen to advance health technology assessment policy development and organizational placement or formation. The champions in turn could use their roles for policy decisions that used private and public events to raise priority and commitment to the decisions, carefully considered organizational placement and formation, and developed the network of organizations for the generation of technical evidence and capacity building for health technology assessment, strengthened by international networks and organizations with financing, expertise, and policymaker relationships.
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- 2023
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62. Harnessing Health Technology Assessment in Latin America and the Caribbean: Keeping the Region on Course
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Ursula Giedion, Manuel Antonio Espinoza, Pamela Góngora-Salazar, Abha Mehndiratta, and Dan Ollendorff
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Health technology assessment ,Latin America and the Caribbean ,low- and middle-income countries ,priority-setting ,universal health coverage ,Medicine (General) ,R5-920 ,Public aspects of medicine ,RA1-1270 - Abstract
Latin America and the Caribbean has made significant progress toward universal health coverage (UHC), but health spending efficiency, equity, and sustainability remain major challenges—and progress is hindered by the difficult macroeconomic context. Health technology assessment (HTA) can make resource allocation more efficient and equitable when systematically used to inform coverage decisions. We highlight five considerations that need to be taken into account to realize the full potential of HTA in the LAC region: i) explicitly link HTA to decision-making and anchor it in legal frameworks, ii) systematically incorporate the opportunity cost as a core principle into HTA activities informing coverage decisions, iii) make the internationally available evidence more fit for purpose for low- and middle-income countries (LMICs), iv) incorporate pragmatism as a key principle of HTA activities in the region, and v) institutionalize the monitoring of HTA processes and results.
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- 2023
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63. International Partnerships to Develop Evidence-informed Priority Setting Institutions: Ten Years of Experience from the International Decision Support Initiative (iDSI)
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Peter Baker, Edwine Barasa, Kalipso Chalkidou, Lumbwe Chola, Anthony Culyer, Saudamini Dabak, Victoria Y. Fan, Katrine Frønsdal, Lieke Fleur Heupink, Wanrudee Isaranuwatchai, Rahab Mbau, Abha Mehndiratta, Justice Nonvignon, Francis Ruiz, Yot Teerawattananon, Anna Vassall, and Javier Guzman
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Health economics ,health technology assessment ,institutionalization [tbc with journal] ,low- and middle-income countries ,priority setting ,Medicine (General) ,R5-920 ,Public aspects of medicine ,RA1-1270 - Abstract
All health systems must set priorities. Evidence-informed priority-setting (EIPS) is a specific form of systematic priority-setting which involves explicit consideration of evidence to determine the healthcare interventions to be provided. The international Decision Support Initiative (iDSI) was established in 2013 as a collaborative platform to catalyze faster progress on EIPS, particularly in low- and middle-income countries. This article summarizes the successes, challenges, and lessons learned from ten years of iDSI partnering with countries to develop EIPS institutions and processes. This is a thematic documentary analysis, structured by iDSI’s theory of change, extracting successes, challenges, and lessons from three external evaluations and 19 internal reports to funders. We identified three phases of iDSI’s work—inception (2013–15), scale-up (2016–2019), and focus on Africa (2019–2023). iDSI has established a global platform for coordinating EIPS, advanced the field, and supported regional networks in Asia and Africa. It has facilitated progress in securing high-level commitment to EIPS, strengthened EIPS institutions, and developed capacity for health technology assessments. This has resulted in improved decisions on service provision, procurement, and clinical care. Major lessons learned include the importance of sustained political will to develop EIPS; a clear EIPS mandate; inclusive governance structures appropriate to health financing context; politically sensitive and country-led support to EIPS, taking advantage of policy windows for EIPS reforms; regional networks for peer support and long-term sustainability; utilization of context appropriate methods such as adaptive HTA; and crucially, donor-funded global health initiatives supporting and integrating with national EIPS systems, not undermining them.
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- 2023
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64. Dissecting the in vitro fate of plant-derived bioactive encapsulated nanoparticles in lung diseases
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Bani Saeid, Ayeh, Patel, Vyoma K., Mehndiratta, Samir, Rajput, Rashi, Kundu, Ramesh Kumar, Singh, Sachin Kumar, Chellappan, Dinesh Kumar, Kokkinis, Sofia, De Rubis, Gabriele, Collet, Trudi, Paudel, Keshav Raj, Hansbro, Philip Michael, and Dua, Kamal
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- 2023
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65. Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization–Lancet Neurology Commission
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Feigin, Valery L, Abd-Allah, Foad, Akinyemi, Rufus O, Bhattacharjee, Natalia V, Brainin, Michael, Cao, Jackie, Caso, Valeria, Dalton, Bronte, Davis, Alan, Dempsey, Robert, Duprey, Joseph, Feng, Wuwei, Ford, Gary A, Gall, Seana, Gandhi, Dorcas, Good, David C, Hachinski, Vladimir, Hacke, Werner, Hankey, Graeme J, Ishida, Marie, Johnson, Walter, Kim, Julie, Lavados, Pablo, Lindsay, Patrice, Mahal, Ajay, Martins, Sheila, Murray, Christopher, Nguyen, Thuy Phuong, Norrving, Bo, Olaiya, Muideen T, Olalusi, Oladotun V, Pandian, Jeyaraj, Phan, Hoang, Platz, Thomas, Ranta, Anna, Rehman, Sabah, Roth, Greg, Sebastian, Ivy Anne, Smith, Amanda E, Suwanwela, Nijasri C, Sylaja, P N, Thapa, Rajshree, Thrift, Amanda G, Uvere, Ezinne, Vollset, Stein Emil, Yavagal, Dileep, Yaria, Joseph, Owolabi, Mayowa O, Abera, Semaw Ferede, Akinyemi, Rufus, Dempsey, Robert J, Ibrahim, Norlinah Mohamed, Liu, Liping, Ovbiagele, Bruce, Piradov, Michael, Suwanwela, Nijasri, Abanto, Carlos, Addissie, Adamu, Adeleye, Amos O, Adilbekov, Yerzhan, Adilbekova, Bibigul, Adoukonou, Thierry A, Aguiar de Sousa, Diana, Akhmetzhanova, Zauresh, Akpalu, Albert, El Alaoui-Faris, Mustapha, Ameriso, Sebastian F, Andonova, Silva, Arsovska, Anita, Awoniyi, Folorunso E, Bakhiet, Moiz, Barboza, Miguel A, Basri, Hamidon, Bath, Philip M, Bereczki, Daniel, Beretta, Simone, Berkowitz, Aaron L, Bernhardt, Julie, Berzina, Guna, Bhavsar, Bhavan, Bisharyan, Mher S, Bohara, Manoj, Bovet, Pascal, Budincevic, Hrvoje, Cadilhac, Dominique A, Čerimagić, Denis, Charway-Felli, Augustina, Chen, Christopher, Chin, Jerome H, Christensen, Hanne, Chwojnicki, Kamil, Conforto, Adriana B, Correia, Manuel, Mora Cuervo, Daissy L, Członkowska, Anna, D'Amelio, Marco, Danielyan, Kristine E, Davis, Stephen, Demarin, Vida, Demchuk, Andrew M, Dichgans, Martin, Dokova, Klara, Donnan, Geoffrey, Duran, Juan Carlos, Ekeng, Gloria, Elkind, Mitchell S, Endres, Matthias, Fischer, Urs, Flomin, Yuriy, Gankpe, Fortuné, Gavidia, Martin, Gaye Saavedra, Andrés, Gebreyohanns, Mehari, George, Mary, Gierlotka, Marek, Giroud, Maurice, Gnedovskaya, Elena V, Gonçalves, Ivete Pillo, Gongora-Rivera, Fernando, Gunaratne, Padma S, Hamadeh, Randah R, Hamzat, Tal-hatu K, Heldner, Mirjam R, Ibrahim, Etedal, Ihle-Hansen, Hanne, Jee, Sungju, Jiann-Shing, Jeng, Johnston, S Clay, Jovanovic, Dejana, Jurjāns, Kristaps, Kalani, Rizwan, Kalkonde, Yogeshwar, Kamenova, Saltanat, Karaszewski, Bartosz, Kelly, Peter, Kiechl, Stefan, Kondybayeva, Aida, Kõrv, Janika, Kozera, Grzegorz, Kravchenko, Michael, Krespi, Yakup, Krishnamurthi, Rita, Kruja, Jera, Kutluk, Kursad, Langhorne, Peter, Law, Zhe K, Lebedynets, Dmytro, Lee, Tsong-Hai, Leung, Thomas W, Liebeskind, David S, López-Jaramillo, Patricio, Lotufo, Paulo A, Machline-Carrion, M Julia, Maia, Luis F, Malojcic, Branko, Markus, Hugh S, Marquez-Romero, Juan M, Medina, Marco T, Medukhanova, Sabina, Mehndiratta, Man Mohan, Miglāne, Evija, Mihejeva, Illa, Mikulik, Robert, Mirrakhimov, Erkin, Mohl, Stephanie, Munakomi, Sunil, Murphy, Sean, Musa, Kamarul I, Nasreldein, Ahmed, Nogueira, Raul G, Nolte, Christian H, Noubiap, Jean Jacques, Novarro-Escudero, Nelson, Ocampo, Cassandra, O'Donnell, Martin, Ogun, Yomi, Ogunniyi, Adesola, Oraby, Mohammed I, Ōrken, Dilek N, Ōzdemir, Atilla O, Ozturk, Serefnur, Paccot, Mélanie, Pereira, Telmo, Peeters, André, Potpara, Tatjana, Proios, Hariklia, Rathore, Farooq A, Sacco, Ralph L, Sahathevan, Ramesh, Sandset, Else S, Renato Santos, Irving, Saposnik, Gustavo, Sarfo, Fred S, Sargento-Freitas, João, Sharma, Mukul, Shaw, Louise, Sheth, Kevin N, Shin, Yong-Il, Shobhana, A, Silva, S Nishan, Tedim Cruz, Vitor, Thakur, Kiran, Thapa, Lekh Jung, Toni, Danilo, Topcuoglu, Mehmetakif A, Torales, Julio, Towfighi, Amytis, Truelsen, Thomas, Tsiskaridze, Alexander, Tulloch-Reid, Marshall, Useche, Juan N, Vanacker, Peter, Vassilopoulou, Sophia, Vukorepa, Gorana, Vuletic, Vladimira, Wahab, Kolawole W, Wang, Wenzhi, Wijeratne, Tissa, Wojtyniak, Bogdan, Wolfe, Charles, Yacouba, Mapoure N, Yang, Jie, Yifru, Yared M, Yock-Corrales, Adriana, Yonemoto, Naohiro, Yperzeele, Laetitia, and Zagożdżon, Pawel
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- 2023
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66. McLeod syndrome and acanthocytosis
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Mehndiratta M
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Neurology. Diseases of the nervous system ,RC346-429 - Published
- 2011
67. Characterization of thalamic lesions and their correlates in multiple sclerosis by ultra-high-field MRI.
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Mehndiratta, Ambica, Treaba, Constantina, Barletta, Valeria, Herranz, Elena, Ouellette, Russell, Sloane, Jacob, Klawiter, Eric, Kinkel, Revere, and Mainero, Caterina
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Multiple sclerosis ,atrophy ,central venule ,ovoid ,periventricular ,thalamus ,Atrophy ,Cognitive Dysfunction ,Humans ,Magnetic Resonance Imaging ,Multiple Sclerosis ,Thalamus - Abstract
BACKGROUND: Thalamic pathology is a marker for neurodegeneration and multiple sclerosis (MS) disease progression. OBJECTIVE: To characterize (1) the morphology of thalamic lesions, (2) their relation to cortical and white matter (WM) lesions, and (3) clinical measures, and to assess (4) the imaging correlates of thalamic atrophy. METHODS: A total of 90 MS patients and 44 healthy controls underwent acquisition of 7 Tesla images for lesion segmentation and 3 Tesla scans for atrophy evaluation. Thalamic lesions were classified according to the shape and the presence of a central venule. Regression analysis identified the predictors of (1) thalamic atrophy, (2) neurological disability, and (3) information processing speed. RESULTS: Thalamic lesions were mostly ovoid than periventricular, and for the great majority (78%) displayed a central venule. Lesion volume in the thalamus, cortex, and WM did not correlate with each other. Thalamic atrophy was only associated with WM lesion volume (p = 0.002); subpial and WM lesion volumes were associated with neurological disability (p = 0.016; p
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- 2021
68. Reforms in technical education sector: evidence from World Bank-assisted Technical Education Quality Improvement Programme in India
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Dubey, Amlendu, Mehndiratta, Amit, Sagar, Mahim, and Kashiramka, Smita
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- 2019
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69. Stroke Care during the COVID-19 Pandemic: International Expert Panel Review.
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Venketasubramanian, Narayanaswamy, Anderson, Craig, Ay, Hakan, Aybek, Selma, Brinjikji, Waleed, de Freitas, Gabriel, Del Brutto, Oscar, Fassbender, Klaus, Fujimura, Miki, Goldstein, Larry, Haberl, Roman, Hankey, Graeme, Heiss, Wolf-Dieter, Lestro Henriques, Isabel, Kase, Carlos, Kim, Jong, Koga, Masatoshi, Kokubo, Yoshihiro, Kuroda, Satoshi, Lee, Kiwon, Lee, Tsong-Hai, Liebeskind, David, Lip, Gregory, Meairs, Stephen, Medvedev, Roman, Mehndiratta, Man, Mohr, Jay, Nagayama, Masao, Pantoni, Leonardo, Papanagiotou, Panagiotis, Parrilla, Guillermo, Pastori, Daniele, Pendlebury, Sarah, Pettigrew, Luther, Renjen, Pushpendra, Rundek, Tatjana, Schminke, Ulf, Shinohara, Yukito, Tang, Wai, Toyoda, Kazunori, Wartenberg, Katja, Wasay, Mohammad, and Hennerici, Michael
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Coronavirus disease 2019 ,Management ,Review ,Stroke ,Angiotensin Receptor Antagonists ,COVID-19 ,Heparin ,Low-Molecular-Weight ,Humans ,SARS-CoV-2 ,Spike Glycoprotein ,Coronavirus ,Stroke - Abstract
BACKGROUND: Coronavirus disease 2019 (COVID-19) has placed a tremendous strain on healthcare services. This study, prepared by a large international panel of stroke experts, assesses the rapidly growing research and personal experience with COVID-19 stroke and offers recommendations for stroke management in this challenging new setting: modifications needed for prehospital emergency rescue and hyperacute care; inpatient intensive or stroke units; posthospitalization rehabilitation; follow-up including at-risk family and community; and multispecialty departmental developments in the allied professions. SUMMARY: The severe acute respiratory syndrome coronavirus 2 uses spike proteins binding to tissue angiotensin-converting enzyme (ACE)-2 receptors, most often through the respiratory system by virus inhalation and thence to other susceptible organ systems, leading to COVID-19. Clinicians facing the many etiologies for stroke have been sobered by the unusual incidence of combined etiologies and presentations, prominent among them are vasculitis, cardiomyopathy, hypercoagulable state, and endothelial dysfunction. International standards of acute stroke management remain in force, but COVID-19 adds the burdens of personal protections for the patient, rescue, and hospital staff and for some even into the postdischarge phase. For pending COVID-19 determination and also for those shown to be COVID-19 affected, strict infection control is needed at all times to reduce spread of infection and to protect healthcare staff, using the wealth of well-described methods. For COVID-19 patients with stroke, thrombolysis and thrombectomy should be continued, and the usual early management of hypertension applies, save that recent work suggests continuing ACE inhibitors and ARBs. Prothrombotic states, some acute and severe, encourage prophylactic LMWH unless bleeding risk is high. COVID-19-related cardiomyopathy adds risk of cardioembolic stroke, where heparin or warfarin may be preferable, with experience accumulating with DOACs. As ever, arteritis can prove a difficult diagnosis, especially if not obvious on the acute angiogram done for clot extraction. This field is under rapid development and may generate management recommendations which are as yet unsettled, even undiscovered. Beyond the acute management phase, COVID-19-related stroke also forces rehabilitation services to use protective precautions. As with all stroke patients, health workers should be aware of symptoms of depression, anxiety, insomnia, and/or distress developing in their patients and caregivers. Postdischarge outpatient care currently includes continued secondary prevention measures. Although hoping a COVID-19 stroke patient can be considered cured of the virus, those concerned for contact safety can take comfort in the increasing use of telemedicine, which is itself a growing source of patient-physician contacts. Many online resources are available to patients and physicians. Like prior challenges, stroke care teams will also overcome this one. Key Messages: Evidence-based stroke management should continue to be provided throughout the patient care journey, while strict infection control measures are enforced.
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- 2021
70. Cortical and phase rim lesions on 7 T MRI as markers of multiple sclerosis disease progression.
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Treaba, Constantina, Conti, Allegra, Klawiter, Eric, Barletta, Valeria, Herranz, Elena, Mehndiratta, Ambica, Russo, Andrew, Sloane, Jacob, Kinkel, Revere, Toschi, Nicola, and Mainero, Caterina
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MRI ,cortical lesions ,machine learning ,multiple sclerosis ,phase rim lesions - Abstract
In multiple sclerosis, individual lesion-type patterns on magnetic resonance imaging might be valuable for predicting clinical outcome and monitoring treatment effects. Neuropathological and imaging studies consistently show that cortical lesions contribute to disease progression. The presence of chronic active white matter lesions harbouring a paramagnetic rim on susceptibility-weighted magnetic resonance imaging has also been associated with an aggressive form of multiple sclerosis. It is, however, still uncertain how these two types of lesions relate to each other, or which one plays a greater role in disability progression. In this prospective, longitudinal study in 100 multiple sclerosis patients (74 relapsing-remitting, 26 secondary progressive), we used ultra-high field 7-T susceptibility imaging to characterize cortical and rim lesion presence and evolution. Clinical evaluations were obtained over a mean period of 3.2 years in 71 patients, 46 of which had a follow-up magnetic resonance imaging. At baseline, cortical and rim lesions were identified in 96% and 63% of patients, respectively. Rim lesion prevalence was similar across disease stages. Patients with rim lesions had higher cortical and overall white matter lesion load than subjects without rim lesions (P = 0.018-0.05). Altogether, cortical lesions increased by both count and volume (P = 0.004) over time, while rim lesions expanded their volume (P = 0.023) whilst lacking new rim lesions; rimless white matter lesions increased their count but decreased their volume (P = 0.016). We used a modern machine learning algorithm based on extreme gradient boosting techniques to assess the cumulative power as well as the individual importance of cortical and rim lesion types in predicting disease stage and disability progression, alongside with more traditional imaging markers. The most influential imaging features that discriminated between multiple sclerosis stages (area under the curve±standard deviation = 0.82 ± 0.08) included, as expected, the normalized white matter and thalamic volume, white matter lesion volume, but also leukocortical lesion volume. Subarachnoid cerebrospinal fluid and leukocortical lesion volumes, along with rim lesion volume were the most important predictors of Expanded Disability Status Scale progression (area under the curve±standard deviation = 0.69 ± 0.12). Taken together, these results indicate that while cortical lesions are extremely frequent in multiple sclerosis, rim lesion development occurs only in a subset of patients. Both, however, persist over time and relate to disease progression. Their combined assessment is needed to improve the ability of identifying multiple sclerosis patients at risk of progressing disease.
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- 2021
71. Maternal Serum Vitamin E Levels and its Association with Cord Blood Telomere Length and Mitochondrial DNA Copy Number in Preterm Premature Rupture of Membranes
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Kumari, Rupa, Suneja, Amita, Mehndiratta, Mohit, Guleria, Kiran, and Malik, Rashmi
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- 2023
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72. Peripheral Nerve Ultrasound: from Clinic to Operating Room
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Rangarajan, Aadithya, Bathala, Lokesh, Gururajrao, Madhusudan, Mahesh, M. S., and Mehndiratta, Man Mohan
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- 2023
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73. Recent Advancements in Biomedical Sciences and Their Healthcare Applications
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Sharma, Reena, primary and Mehndiratta, Samir, additional
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- 2023
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74. Validating the rigour of adaptive methods of economic evaluation
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Nidhi Gupta, Shankar Prinja, Abha Mehndiratta, Akashdeep Singh Chauhan, Deepshikha Sharma, Basant Garg, and Amneet P Kumar
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Medicine (General) ,R5-920 ,Infectious and parasitic diseases ,RC109-216 - Abstract
Background There has been a lot of debate on how to ‘generalise’ or ‘translate’ findings of economic evaluation (EE) or health technology assessment (HTA) to other country contexts. Researchers have used various adaptive HTA (aHTA) methods like model-adaptation, price-benchmarking, scorecard-approach, etc., for transferring evidence from one country to other. This study was undertaken to assess the degree of accuracy in results generated from aHTA approaches specifically for EE.Methods By applying selected aHTA approaches, we adapted findings of globally published EE to Indian context. The first-step required identifying two interventions for which Indian EE (referred to as the ‘Indian reference study’) has been conducted. The next-step involved identification of globally published EE. The third-step required undertaking quality and transferability check. In the fourth step, outcomes of EE meeting transferability standards, were adapted using selected aHTA approaches. Lastly, adapted results were compared with findings of the Indian reference study.Results The adapted cost estimates varied considerably, while adapted quality-adjusted life-years did not differ much, when matched with the Indian reference study. For intervention I (trastuzumab), adapted absolute costs were 11 and 6 times higher than the costs reported in the Indian reference study for control and intervention arms, respectively. Likewise, adapted incremental cost and incremental cost-effectiveness ratio (ICER) were around 3.5–8 times higher than the values reported in the Indian reference study. For intervention II (intensity-modulated radiation therapy), adapted absolute cost was 35% and 12% lower for the comparator and intervention arms, respectively, than the values reported in the Indian reference study. The mean incremental cost and ICER were 2.5 times and 1.5 times higher, respectively, than the Indian reference study values.Conclusion We conclude that findings from aHTA methods should be interpreted with caution. There is a need to develop more robust aHTA approaches for cost adjustment. aHTA may be used for ‘topic prioritisation’ within the overall HTA process, whereby interventions which are highly cost-ineffective, can be directly ruled out, thus saving time and resources for conducting full HTA for interventions that are not well studied or where evidence is inconclusive.
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- 2023
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75. Improving Academic Performance of Medical Undergraduates: Impediments and Solutions
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Archana Nimesh, Mohit Mehndiratta, Seema Garg, Rajarshi Kar, Dinesh Puri
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Not available ,Medicine - Abstract
Introduction: Medical undergraduates selected for studying medicine through exceedingly competitive pre- medical entrance tests are highly intellectual and hardworking, yet many students perform poorly in internal examinations perhaps because the initial exposure to medical education is tense and uninteresting. This study aims to find out probable reasons that could affect optimalacademic performance of first year medical students. Methodology: First year medical students of 3 consecutive academic batches were asked to fill a feedback form comprising of questions (regarding their opinion for inclusion of clinically oriented teaching and how often they read a topic prior to and after a lecture). Students were also asked to mention the problems affecting their academic performance. Results: 95.6-98.1% of students wanted clinically oriented teaching. 1.9-10.3% of students read a topic in advance (either always or most of the times) but the percentage of students who never or sometimes read the topic in advance was alarmingly very high (89.7-98.1%). 20.8-25.4% of students read the topic for lecture (either always or most of the times) on the same day after the lecture but the percentage of students who never or sometimes read the topic on the same day after the lecture was quite high(74.6-79.2%). Conclusion: Inclusion of clinically oriented classes and integration of clinical and non-c1inica1 subjects might enhance students' academic performance by evoking interest in subjects to read a topic before and after lecture. Provision for adequate hostels, personal counselling and repeated motivation which is frequently ignored by educators might also help.
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- 2023
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76. PINK1 and oxidative stress in lean and obese patients with type 2 diabetes mellitus
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Almeida, Edelbert Anthonio, Mehndiratta, Mohit, Madhu, S.V., Kar, Rajarshi, and Puri, Dinesh
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- 2023
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77. Knowledge and risk perception towards human immunodeficiency virus and hepatitis B infections among medical students
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M. Mehndiratta, R. Kar, E. A. Almeida, A. Goel, and R. Mehndiratta
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hiv, hepatitis b, awareness, medical students, clinical exposure ,Infectious and parasitic diseases ,RC109-216 - Abstract
Background and objectives: Nosocomial human immunodeficiency virus (HIV) and hepatitis B virus (HBV) infections are common occupational hazards transmitted through infected needle-stick injuries. Younger medical students are at a higher risk of exposure mainly because of their inexperience and ignorance. Both these infections are preventable if standard precautions and protocols for post-exposure prophylaxis are followed. The present study assesses the knowledge, and risk perception among medical students and interns towards HIV and HBV infections, to guide instructors in planning appropriate training programmes. Methods: Following approval of the institutional ethics committee of University College of Medical Sciences, Delhi, India, (UCMS) undergraduate medical students and interns were invited to respond to an indigenously designed questionnaire regarding HIV and HBV infections. Participation was voluntary and anonymous. The students were assessed vertically. Results: There was a gradual increase in the awareness regarding HIV and HBV infection with each passing academic year. The percentage of total questions answered correctly was highest (91.1%) in internship and lowest (71.5%) in the first semester. Awareness regarding HIV was greater as compared to HBV infection in all the groups. Interns had maximum awareness of post exposure prophylaxis available for both HIV and HBV infections. Ninth semester students scored the highest on pre-exposure prophylaxis for HBV infection. Overall, the interns were the most aware. Conclusion: Students’ knowledge on HIV and HBV infections improves as these areas are covered in greater detail during exposure to clinical disciplines. An early clinical exposure module for first year medical students in the Competency Based Medical Education curriculum may provide an opportunity to improve awareness, to reduce infection and subsequent morbidity. The students have greater awareness of HIV than HBV, though the risk of transmission is higher for the latter. Thus, shortcomings in imparting knowledge about hepatitis B must be identified and rectified.
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- 2022
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78. Global, regional, and national burden of low back pain, 1990–2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021
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Ferreira, Manuela L, de Luca, Katie, Haile, Lydia M, Steinmetz, Jaimie D, Culbreth, Garland T, Cross, Marita, Kopec, Jacek A, Ferreira, Paulo H, Blyth, Fiona M, Buchbinder, Rachelle, Hartvigsen, Jan, Wu, Ai-Min, Safiri, Saeid, Woolf, Anthony D, Collins, Gary S, Ong, Kanyin Liane, Vollset, Stein Emil, Smith, Amanda E, Cruz, Jessica A, Fukutaki, Kai Glenn, Abate, Semagn Mekonnen, Abbasifard, Mitra, Abbasi-Kangevari, Mohsen, Abbasi-Kangevari, Zeinab, Abdelalim, Ahmed, Abedi, Aidin, Abidi, Hassan, Adnani, Qorinah Estiningtyas Sakilah, Ahmadi, Ali, Akinyemi, Rufus Olusola, Alamer, Abayneh Tadesse, Alem, Adugnaw Zeleke, Alimohamadi, Yousef, Alshehri, Mansour Abdullah, Alshehri, Mohammed Mansour, Alzahrani, Hosam, Amini, Saeed, Amiri, Sohrab, Amu, Hubert, Andrei, Catalina Liliana, Andrei, Tudorel, Antony, Benny, Arabloo, Jalal, Arulappan, Judie, Arumugam, Ashokan, Ashraf, Tahira, Athari, Seyyed Shamsadin, Awoke, Nefsu, Azadnajafabad, Sina, Bärnighausen, Till Winfried, Barrero, Lope H, Barrow, Amadou, Barzegar, Akbar, Bearne, Lindsay M, Bensenor, Isabela M, Berhie, Alemshet Yirga, Bhandari, Bharti Bhandari, Bhojaraja, Vijayalakshmi S, Bijani, Ali, Bodicha, Belay Boda Abule, Bolla, Srinivasa Rao, Brazo-Sayavera, Javier, Briggs, Andrew M, Cao, Chao, Charalampous, Periklis, Chattu, Vijay Kumar, Cicuttini, Flavia M, Clarsen, Benjamin, Cuschieri, Sarah, Dadras, Omid, Dai, Xiaochen, Dandona, Lalit, Dandona, Rakhi, Dehghan, Azizallah, Demie, Takele Gezahegn G, Denova-Gutiérrez, Edgar, Dewan, Syed Masudur Rahman, Dharmaratne, Samath Dhamminda, Dhimal, Mandira Lamichhane, Dhimal, Meghnath, Diaz, Daniel, Didehdar, Mojtaba, Digesa, Lankamo Ena, Diress, Mengistie, Do, Hoa Thi, Doan, Linh Phuong, Ekholuenetale, Michael, Elhadi, Muhammed, Eskandarieh, Sharareh, Faghani, Shahriar, Fares, Jawad, Fatehizadeh, Ali, Fetensa, Getahun, Filip, Irina, Fischer, Florian, Franklin, Richard Charles, Ganesan, Balasankar, Gemeda, Belete Negese Belete, Getachew, Motuma Erena, Ghashghaee, Ahmad, Gill, Tiffany K, Golechha, Mahaveer, Goleij, Pouya, Gupta, Bhawna, Hafezi-Nejad, Nima, Haj-Mirzaian, Arvin, Hamal, Pawan Kumar, Hanif, Asif, Harlianto, Netanja I, Hasani, Hamidreza, Hay, Simon I, Hebert, Jeffrey J, Heidari, Golnaz, Heidari, Mohammad, Heidari-Soureshjani, Reza, Hlongwa, Mbuzeleni Mbuzeleni, Hosseini, Mohammad-Salar, Hsiao, Alexander Kevin, Iavicoli, Ivo, Ibitoye, Segun Emmanuel, Ilic, Irena M, Ilic, Milena D, Islam, Sheikh Mohammed Shariful, Janodia, Manthan Dilipkumar, Jha, Ravi Prakash, Jindal, Har Ashish, Jonas, Jost B, Kabito, Gebisa Guyasa, Kandel, Himal, Kaur, Rimple Jeet, Keshri, Vikash Ranjan, Khader, Yousef Saleh, Khan, Ejaz Ahmad, Khan, Md Jobair, Khan, Moien AB, Khayat Kashani, Hamid Reza, Khubchandani, Jagdish, Kim, Yun Jin, Kisa, Adnan, Klugarová, Jitka, Kolahi, Ali-Asghar, Koohestani, Hamid Reza, Koyanagi, Ai, Kumar, G Anil, Kumar, Narinder, Lallukka, Tea, Lasrado, Savita, Lee, Wei-Chen, Lee, Yo Han, Mahmoodpoor, Ata, Malagón-Rojas, Jeadran N, Malekpour, Mohammad-Reza, Malekzadeh, Reza, Malih, Narges, Mehndiratta, Man Mohan, Mehrabi Nasab, Entezar, Menezes, Ritesh G, Mentis, Alexios-Fotios A, Mesregah, Mohamed Kamal, Miller, Ted R, Mirza-Aghazadeh-Attari, Mohammad, Mobarakabadi, Maryam, Mohammad, Yousef, Mohammadi, Esmaeil, Mohammed, Shafiu, Mokdad, Ali H, Momtazmanesh, Sara, Monasta, Lorenzo, Moni, Mohammad Ali, Mostafavi, Ebrahim, Murray, Christopher J L, Nair, Tapas Sadasivan, Nazari, Javad, Nejadghaderi, Seyed Aria, Neupane, Subas, Neupane Kandel, Sandhya, Nguyen, Cuong Tat, Nowroozi, Ali, Okati-Aliabad, Hassan, Omer, Emad, Oulhaj, Abderrahim, Owolabi, Mayowa O, Panda-Jonas, Songhomitra, Pandey, Anamika, Park, Eun-Kee, Pawar, Shrikant, Pedersini, Paolo, Pereira, Jeevan, Peres, Mario F P, Petcu, Ionela-Roxana, Pourahmadi, Mohammadreza, Radfar, Amir, Rahimi-Dehgolan, Shahram, Rahimi-Movaghar, Vafa, Rahman, Mosiur, Rahmani, Amir Masoud, Rajai, Nazanin, Rao, Chythra R, Rashedi, Vahid, Rashidi, Mohammad-Mahdi, Ratan, Zubair Ahmed, Rawaf, David Laith, Rawaf, Salman, Renzaho, Andre M N, Rezaei, Negar, Rezaei, Zahed, Roever, Leonardo, Ruela, Guilherme de Andrade, Saddik, Basema, Sahebkar, Amirhossein, Salehi, Sana, Sanmarchi, Francesco, Sepanlou, Sadaf G, Shahabi, Saeed, Shahrokhi, Shayan, Shaker, Elaheh, Shamsi, MohammadBagher, Shannawaz, Mohammed, Sharma, Saurab, Shaygan, Maryam, Sheikhi, Rahim Ali, Shetty, Jeevan K, Shiri, Rahman, Shivalli, Siddharudha, Shobeiri, Parnian, Sibhat, Migbar Mekonnen, Singh, Ambrish, Singh, Jasvinder A, Slater, Helen, Solmi, Marco, Somayaji, Ranjani, Tan, Ker-Kan, Thapar, Rekha, Tohidast, Seyed Abolfazl, Valadan Tahbaz, Sahel, Valizadeh, Rohollah, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Vlassov, Vasily, Vo, Bay, Wang, Yuan-Pang, Wiangkham, Taweewat, Yadav, Lalit, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yang, Lin, Yazdanpanah, Fereshteh, Yonemoto, Naohiro, Younis, Mustafa Z, Zare, Iman, Zarrintan, Armin, Zoladl, Mohammad, Vos, Theo, and March, Lyn M
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- 2023
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79. Suppression of perioperative stress response in elective abdominal surgery: A randomized comparison between dexmedetomidine and epidural block
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Rashmi Salhotra, Vishal Kamal, Asha Tyagi, Mohit Mehndiratta, Rajesh S Rautela, and Edelbert A Almeida
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anesthesia technique ,cortisol ,dexmedetomidine ,stress response ,surgery ,Anesthesiology ,RD78.3-87.3 ,Pharmacy and materia medica ,RS1-441 - Abstract
Background and Aims: Stress response after surgery induces local and systemic inflammation which may be detrimental if it goes unchecked. Blockade of afferent neurons or inhibition of hypothalamic function may mitigate the stress response. Material and Methods: A total of 50 consenting adult ASA I/II patients undergoing elective abdominal surgery were randomized to receive either dexmedetomidine (Group D) or epidural bupivacaine (Group E) in addition to balanced general anesthesia. Laparoscopic surgery, contraindications to epidural administration, history of psychiatric disorders, obesity (BMI >30 kg/m2), on beta blockers or continuous steroid therapy for >5 days over last 1 year, and known case of endocrine abnormalities or malignancy were excluded. Serum cortisol, blood glucose, and blood urea were estimated. Hemodynamic parameters, total dose of dexmedetomidine, bupivacaine, emergence characteristics, and analgesic consumption over 24 h postoperatively were recorded. Statistical comparisons were done using Student's t-test, repeated measure analysis of variance followed by Dunnett's test, generalized linear model and Chi-square/Fisher's exact test. A P value
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- 2023
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80. Non-invasive intravoxel incoherent motion MRI in prediction of histopathological response to neoadjuvant chemotherapy and survival outcome in osteosarcoma at the time of diagnosis
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Esha Baidya Kayal, Sameer Bakhshi, Devasenathipathy Kandasamy, Mehar Chand Sharma, Shah Alam Khan, Venkatesan Sampath Kumar, Kedar Khare, Raju Sharma, and Amit Mehndiratta
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Intravoxel incoherent motion ,Diffusion weighted imaging ,Biomarkers ,Chemotherapy response evaluation ,Survival outcome ,Osteosarcoma ,Medicine - Abstract
Abstract Background Early prediction of response to neoadjuvant chemotherapy (NACT) is important to aid personalized treatment in osteosarcoma. Diffusion-weighted Intravoxel Incoherent Motion (IVIM) MRI was used to evaluate the predictive value for response to NACT and survival outcome in osteosarcoma. Methods Total fifty-five patients with biopsy-proven osteosarcoma were recruited prospectively, among them 35 patients were further analysed. Patients underwent 3 cycles of NACT (Cisplatin + Doxorubicin) followed by surgery and response adapted adjuvant chemotherapy. Treatment outcomes were histopathological response to NACT (good-response ≥ 50% necrosis and poor-response
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- 2022
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81. Quantification of prostate tumour diameter and volume from MR images using 3D ellipsoid model and its impact on PI-RADS v2.1 assessment
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Dharmesh Singh, Chandan J. Das, Virendra Kumar, Anup Singh, and Amit Mehndiratta
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Medicine ,Science - Abstract
Abstract Maximum diameter and volume of the tumour provide important clinical information and are decision-making parameters for patients suspected with prostate cancer (PCa). The objectives of this study were to develop an automated method for 3D tumour measurement and compare it with the radiologist’s manual assessment, as well as to investigate the impact of 3D tumour measurement on Prostate Imaging-Reporting and Data System version-2.1 (PI-RADS v2.1) scoring of prostate cancer. Tumour maximum diameter and volume were calculated using automated ellipsoid-fit method. For all PI-RADS scores, mean ± standard deviation range of tumour maximum diameter and volume measured using ellipsoid-fit method were 1.36 ± 0.28 to 1.97 ± 0.67 cm and 0.49 ± 0.31 to 1.05 ± 0.78 cc and manual assessment were in range of 0.73 ± 0.12 to 1.14 ± 0.25 cm and 0.36 ± 0.21 to 0.93 ± 0.39 cc, respectively. Ellipsoid-fit method showed significantly (p
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- 2022
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82. IVIM-DKI with parametric reconstruction method for lymph node evaluation and characterization in lymphoma: A preliminary study comparison with FDG-PET/CT
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Malagi, Archana Vadiraj, Kandasamy, Devasenathipathy, Pushpam, Deepam, Khare, Kedar, Sharma, Raju, Kumar, Rakesh, Bakhshi, Sameer, and Mehndiratta, Amit
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- 2023
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83. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Steinmetz, J, Seeher, K, Schiess, N, Nichols, E, Cao, B, Servili, C, Cavallera, V, Cousin, E, Hagins, H, Moberg, M, Mehlman, M, Abate, Y, Abbas, J, Abbasi, M, Abbasian, M, Abbastabar, H, Abdelmasseh, M, Abdollahi, M, Abdollahifar, M, Abd-Rabu, R, Abdulah, D, Abdullahi, A, Abedi, A, Abedi, V, Abeldano Zuniga, R, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Aboyans, V, Abrha, W, Abualhasan, A, Abu-Gharbieh, E, Aburuz, S, Adamu, L, Addo, I, Adebayo, O, Adekanmbi, V, Adekiya, T, Adikusuma, W, Adnani, Q, Adra, S, Afework, T, Afolabi, A, Afraz, A, Afzal, S, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, J, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akade, S, Akbari, M, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemi, R, Akonde, M, Al Hasan, S, Alahdab, F, Al-Ahdal, T, Al-Amer, R, Albashtawy, M, Albataineh, M, Aldawsari, K, Alemi, H, Alemi, S, Algammal, A, Al-Gheethi, A, Alhalaiqa, F, Alhassan, R, Ali, A, Ali, E, Ali, L, Ali, M, Ali, R, Ali, S, Shujait Ali, S, Ali, Z, Alif, S, Alimohamadi, Y, Aliyi, A, Aljofan, M, Aljunid, S, Alladi, S, Almazan, J, Almustanyir, S, Al-Omari, B, Alqahtani, J, Alqasmi, I, Alqutaibi, A, Al-Shahi Salman, R, Altaany, Z, Al-Tawfiq, J, Altirkawi, K, Alvis-Guzman, N, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Amusa, G, Amzat, J, Ancuceanu, R, Anderlini, D, Anderson, D, Andrei, C, Androudi, S, Angappan, D, Angesom, T, Anil, A, Ansari-Moghaddam, A, Anwer, R, Arafat, M, Aravkin, A, Areda, D, Ariffin, H, Arifin, H, Arkew, M, Arnlov, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, R, Asadi-Pooya, A, Asena, T, Asghari-Jafarabadi, M, Ashraf, M, Ashraf, T, Atalell, K, Athari, S, Atinafu, B, Atorkey, P, Atout, M, Atreya, A, Aujayeb, A, Avan, A, Ayala Quintanilla, B, Ayatollahi, H, Ayinde, O, Mohammad Ayyoubzadeh, S, Azadnajafabad, S, Azizi, Z, Azizian, K, Azzam, A, Babaei, 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K., Khanmohammadi S., Khanna T., Khatab K., Khatatbeh H., Khatatbeh M. M., Khateri S., Khatib M. N., Khayat Kashani H. R., Khonji M. S., Khorashadizadeh F., Khormali M., Khubchandani J., Kian S., Kim G., Kim J., Kim M. S., Kim Y. J., Kimokoti R. W., Kisa A., Kisa S., Kivimaki M., Kochhar S., Kolahi A. -A., Koly K. N., Kompani F., Koroshetz W. J., Kosen S., Kourosh Arami M., Koyanagi A., Kravchenko M. A., Krishan K., Krishnamoorthy V., Defo B. K., Kuddus M. A., Kumar A., Kumar G. A., Kumar M., Kumar N., Kumsa N. B., Kundu S., Kurniasari M. D., Kusuma D., Kuttikkattu A., Kyu H. H., La Vecchia C., Ladan M. A., Lahariya C., Laksono T., Lal D. K., Lallukka T., Lam J., Lami F. H., Landires I., Langguth B., Lasrado S., Latief K., Latifinaibin K., Lau K. M. -M., Laurens M. B., Lawal B. K., Le L. K. D., Le T. T. T., Ledda C., Lee M., Lee S. -W., Lee S. W., Lee W. -C., Lee Y. H., Leonardi M., Lerango T. L., Li M. -C., Li W., Ligade V. S., Lim S. 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N., Mirfakhraie R., Mirica A., Mirrakhimov E. M., Mirzaei M., Misganaw A., Misra S., Mithra P., Mizana B. A., Mohamadkhani A., Mohamed N. S., Mohammadi E., Mohammadi H., Mohammadi S., Mohammadshahi M., Mohammed M., Mohammed S., Mohan S., Mojiri-Forushani H., Moka N., Mokdad A. H., Molinaro S., Moller H., Monasta L., Moniruzzaman M., Montazeri F., Moradi M., Moradi Y., Moradi-Lakeh M., Moraga P., Morovatdar N., Morrison S. D., Mosapour A., Mosser J. F., Mossialos E., Motaghinejad M., Mousavi P., Ehsan Mousavi S., Mubarik S., Muccioli L., Mughal F., Mukoro G. D., Mulita A., Mulita F., Musaigwa F., Mustafa A., Mustafa G., Muthu S., Nagarajan A. J., Naghavi P., Naik G. R., Nainu F., Nair T. S., Najmuldeen H. H. R., Nakhostin Ansari N., Nambi G., Namdar Areshtanab H., Nargus S., Nascimento B. R., Naser A. Y., Nashwan A. J. J., Nasoori H., Nasreldein A., Natto Z. S., Nauman J., Nayak B. P., Nazri-Panjaki A., Negaresh M., Negash H., Negoi I., Negoi R. I., Negru S. M., Nejadghaderi S. A., Nematollahi M. H., Nesbit O. D., Newton C. R. J., Nguyen D. H., Nguyen H. T. H., Nguyen H. Q., Nguyen N. -T. T., Nguyen P. T., Nguyen V. T., Niazi R. K., Nikolouzakis T. K., Niranjan V., Nnyanzi L. A., Noman E. A., Noroozi N., Norrving B., Noubiap J. J., Nri-Ezedi C. A., Ntaios G., Nunez-Samudio V., Nurrika D., Oancea B., Odetokun I. A., O'Donnell M. J., Ogunsakin R. E., Oguta J. O., Oh I. -H., Okati-Aliabad H., Okeke S. R., Okekunle A. P., Okonji O. C., Okwute P. G., Olagunju A. T., Olaiya M. T., Olana M. D., Olatubi M. I., Oliveira G. M. M., Olufadewa I. I., Olusanya B. O., Bali A. O., Ong S., Onwujekwe O. E., Ordak M., Orji A. U., Ortega-Altamirano D. V., Osuagwu U. L., Otstavnov N., Otstavnov S. S., Ouyahia A., Owolabi M. O., Mahesh Padukudru P. A., Pacheco-Barrios K., Padubidri J. R., Pal P. K., Palange P. N., Palladino C., Palladino R., Palma-Alvarez R. F., Pan F., Panagiotakos D., Panda-Jonas S., Pandey A., Pandian J. D., Pangaribuan H. 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- Abstract
Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous s
- Published
- 2024
84. Children with Severe Acute Malnutrition Have High Rates of Bone Resorption: A Cross-sectional Comparative Study
- Author
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Das, Sreetama, Meena, Rajesh Kumar, Shah, Dheeraj, Almeida, Edelbert Anthonio, Mehndiratta, Mohit, and Gupta, Piyush
- Published
- 2023
- Full Text
- View/download PDF
85. GAD-65-associated limbic encephalitis - Early diagnosis and course of disease, treated with IV methylprednisolone
- Author
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Vegda, Monalisa and Mehndiratta, Manmohan
- Subjects
Methylprednisolone ,Corticosteroids ,Encephalitis -- Diagnosis ,Hospitals -- Emergency service ,Health - Abstract
Byline: Monalisa. Vegda, Manmohan. Mehndiratta An 80-year-old male was brought to the emergency room complaining of being confused for a few hours. The patient went to the toilet and came [...]
- Published
- 2023
86. A proposed methodology for detecting the malignant potential of pulmonary nodules in sarcoma using computed tomographic imaging and artificial intelligence-based models
- Author
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Esha Baidya Kayal, Shuvadeep Ganguly, Archana Sasi, Swetambri Sharma, Dheeksha DS, Manish Saini, Krithika Rangarajan, Devasenathipathy Kandasamy, Sameer Bakhshi, and Amit Mehndiratta
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sarcoma ,lung metastases ,machine learning ,deep learning ,artificial intelligence ,malignancy ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
The presence of lung metastases in patients with primary malignancies is an important criterion for treatment management and prognostication. Computed tomography (CT) of the chest is the preferred method to detect lung metastasis. However, CT has limited efficacy in differentiating metastatic nodules from benign nodules (e.g., granulomas due to tuberculosis) especially at early stages (
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- 2023
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87. WED-443-YI Usability and acceptability of blood-based hepatitis C virus selftesting (HCVST) among the urban slum population in northern India
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Bhadoria, Ajeet, primary, Selv, Kathirvel, additional, Somvanshi, Rajesh, additional, and Mehndiratta, Amrita, additional
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- 2024
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88. Understanding the extent of economic evidence usage for informing policy decisions in the context of India’s national health insurance scheme: Ayushman Bharat Pradhan Mantri Jan Aarogya Yojana (PM-JAY)
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Sharma, Deepshikha, primary, Chauhan, Akashdeep Singh, additional, Guinness, Lorna, additional, Mehndiratta, Abha, additional, Dhiman, Anamika, additional, Singh, Malkeet, additional, and Prinja, Shankar, additional
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- 2024
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89. IVIM–DKI for differentiation between prostate cancer and benign prostatic hyperplasia: comparison of 1.5 T vs. 3 T MRI
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Malagi, Archana Vadiraj, Netaji, Arjunlokesh, Kumar, Virendra, Baidya Kayal, Esha, Khare, Kedar, Das, Chandan Jyoti, Calamante, Fernando, and Mehndiratta, Amit
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- 2022
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90. Oxidative Stress, Mitochondrial Dysfunction, and Premature Ageing in Severe Acute Malnutrition in Under-Five Children
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Saha, Dipanwita, Mehndiratta, Mohit, Aaradhana, Shah, Dheeraj, and Gupta, Piyush
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- 2022
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91. Trends in age and sex-specific prevalence of cancer and cancer subtypes in acute ischemic stroke from 2007-2019
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Otite, Fadar Oliver, Somani, Sana, Aneni, Ehimen, Akano, Emmanuel, Patel, Smit D., Anikpezie, Nnabuchi, Lamikanra, Olaoluwatomi, Masoud, Hesham, Latorre, Julius Gene, Chaturvedi, Seemant, and Mehndiratta, Prachi
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- 2022
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92. GAD-65-associated limbic encephalitis – Early diagnosis and course of disease, treated with IV methylprednisolone
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Monalisa Vegda and Manmohan Mehndiratta
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Neurology. Diseases of the nervous system ,RC346-429 - Published
- 2023
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93. Salute to Venky for cinematic mark on organ donation and euthanasia
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Amrita Mehndiratta, G Adarsh, and Pooja Bhadoria
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Medicine - Published
- 2023
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94. Consolidation of Layered Soils with Variable Compressibility
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Singh, Deepak Kumar, primary, Kumawat, Chitranshu, additional, and Mehndiratta, Siddharth, additional
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- 2022
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95. Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000–18: a geospatial modelling study
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Frostad, Joseph Jon, Nguyen, QuynhAnh P, Baumann, Mathew M, Blacker, Brigette F, Marczak, Laurie B, Deshpande, Aniruddha, Wiens, Kirsten E, LeGrand, Kate E, Johnson, Kimberly B, Abbasi-Kangevari, Mohsen, Abdoli, Amir, Abolhassani, Hassan, Abreu, Lucas Guimarães, Abrigo, Michael R M, Abu-Rmeileh, Niveen ME, Adekanmbi, Victor, Agrawal, Anurag, Ahmed, Muktar Beshir, Al-Aly, Ziyad, Alanezi, Fahad Mashhour, Alcalde-Rabanal, Jacqueline Elizabeth, Alipour, Vahid, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Alvis-Zakzuk, Nelson J, Amegah, Adeladza Kofi, Amini, Saeed, Amiri, Fatemeh, Amugsi, Dickson A, Ancuceanu, Robert, Andrei, Catalina Liliana, Andrei, Tudorel, Antriyandarti, Ernoiz, Anvari, Davood, Arabloo, Jalal, Arab-Zozani, Morteza, Athari, Seyyed Shamsadin, Ausloos, Marcel, Ayano, Getinet, Aynalem, Yared Asmare, Azari, Samad, Badiye, Ashish D, Baig, Atif Amin, Balakrishnan, Kalpana, Banach, Maciej, Basu, Sanjay, Bedi, Neeraj, Bell, Michelle L, Bennett, Derrick A, Bhattacharyya, Krittika, Bhutta, Zulfiqar A, Bibi, Sadia, Bohlouli, Somayeh, Boufous, Soufiane, Bragazzi, Nicola Luigi, Braithwaite, Dejana, Burugina Nagaraja, Sharath, Butt, Zahid A, Caetano dos Santos, Florentino Luciano, Car, Josip, Cárdenas, Rosario, Carvalho, Felix, Castaldelli-Maia, Joao Mauricio, Castañeda-Orjuela, Carlos A, Cerin, Ester, Chattu, Soosanna Kumary, Chattu, Vijay Kumar, Chaturvedi, Pankaj, Chaturvedi, Sarika, Chen, Simiao, Chu, Dinh-Toi, Chung, Sheng-Chia, Dahlawi, Saad M A, Damiani, Giovanni, Dandona, Lalit, Dandona, Rakhi, Darwesh, Aso Mohammad, Das, Jai K, Dash, Aditya Prasad, Dávila-Cervantes, Claudio Alberto, De Leo, Diego, De Neve, Jan-Walter, Demissie, Getu Debalkie, Denova-Gutiérrez, Edgar, Dey, Sagnik, Dharmaratne, Samath Dhamminda, Dhimal, Meghnath, Dhungana, Govinda Prasad, Diaz, Daniel, Dipeolu, Isaac Oluwafemi, Dorostkar, Fariba, Doshmangir, Leila, Duraes, Andre Rodrigues, Edinur, Hisham Atan, Efendi, Ferry, El Tantawi, Maha, Eskandarieh, Sharareh, Fadhil, Ibtihal, Fattahi, Nazir, Fauk, Nelsensius Klau, Fereshtehnejad, Seyed-Mohammad, Folayan, Morenike Oluwatoyin, Foroutan, Masoud, Fukumoto, Takeshi, Gaidhane, Abhay Motiramji, Ghafourifard, Mansour, Ghashghaee, Ahmad, Gilani, Syed Amir, Gill, Tiffany K, Goulart, Alessandra C, Goulart, Bárbara Niegia Garcia, Grada, Ayman, Gubari, Mohammed Ibrahim Mohialdeen, Guido, Davide, Guo, Yuming, Gupta, Rajat Das, Gupta, Rajeev, Gutiérrez, Reyna Alma, Hafezi-Nejad, Nima, Hamadeh, Randah R, Hasaballah, Ahmed I, Hassanipour, Soheil, Hayat, Khezar, Heibati, Behzad, Heidari-Soureshjani, Reza, Henry, Nathaniel J, Herteliu, Claudiu, Hosseinzadeh, Mehdi, Hsairi, Mohamed, Hu, Guoqing, Ibitoye, Segun Emmanuel, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Irvani, Seyed Sina Naghibi, Islam, Sheikh Mohammed Shariful, Iwu, Chidozie C D, Jaafari, Jalil, Jakovljevic, Mihajlo, Javaheri, Tahereh, Jha, Ravi Prakash, Ji, John S, Jonas, Jost B, Kabir, Ali, Kabir, Zubair, Kalhor, Rohollah, Kamyari, Naser, Kanchan, Tanuj, Kapil, Umesh, Kapoor, Neeti, Kayode, Gbenga A, Keiyoro, Peter Njenga, Khader, Yousef Saleh, Khalid, Nauman, Khan, Ejaz Ahmad, Khan, Maseer, Khan, Md Nuruzzaman, Khatab, Khaled, Khater, Mona M, Khatib, Mahalaqua Nazli, Khayamzadeh, Maryam, Khubchandani, Jagdish, Kim, Gyu Ri, Kim, Yun Jin, Kimokoti, Ruth W, Kisa, Adnan, Kisa, Sezer, Knibbs, Luke D, Koul, Parvaiz A, Koyanagi, Ai, Krishan, Kewal, Kumar, G Anil, Kumar, Manasi, Kusuma, Dian, La Vecchia, Carlo, Lacey, Ben, Lami, Faris Hasan, Lan, Qing, Lasrado, Savita, Lauriola, Paolo, Lee, Paul H, Lewycka, Sonia, Li, Shanshan, Machado, Daiane Borges, Mahasha, Phetole Walter, Maheri, Mina, Majeed, Azeem, Maleki, Afshin, Malekzadeh, Reza, Malta, Deborah Carvalho, Mansouri, Borhan, Mansournia, Mohammad Ali, Martinez, Natalie Maria, Martini, Santi, Martins-Melo, Francisco Rogerlândio, Mayala, Benjamin K, Mehndiratta, Man Mohan, Mendoza, Walter, Menezes, Ritesh G, Mengesha, Endalkachew Worku, Meretoja, Tuomo J, Mestrovic, Tomislav, Michalek, Irmina Maria, Mirrakhimov, Erkin M, Mirzaei, Maryam, Mirzaei, Roya, Moazen, Babak, Mohammad, Yousef, Mohammadian-Hafshejani, Abdollah, Mohammed, Shafiu, Mokdad, Ali H, Monasta, Lorenzo, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Mosapour, Abbas, Mouodi, Simin, Mousavi Khaneghah, Amin, Mukhopadhyay, Satinath, Munro, Sandra B, Murray, Christopher J L, Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Nair, Sanjeev, Nangia, Vinay, Nascimento, Bruno Ramos, Nazari, Javad, Negoi, Ionut, Netsere, Henok Biresaw, Ngunjiri, Josephine W, Nguyen, Huong Lan Thi, Noubiap, Jean Jacques, Oancea, Bogdan, Ogbo, Felix Akpojene, Oh, In-Hwan, Olagunju, Andrew T, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Omar Bali, Ahmed, Onwujekwe, Obinna E, Otstavnov, Nikita, Otstavnov, Stanislav S, Owolabi, Mayowa O, P A, Mahesh, Pandey, Anamika, Park, Eun-Cheol, Park, Eun-Kee, Patel, Sangram Kishor, Pham, Hai Quang, Pilgrim, Thomas, Pirsaheb, Meghdad, Pokhrel, Khem Narayan, Postma, Maarten J, Quazi Syed, Zahiruddin, Rabiee, Navid, Radfar, Amir, Rahim, Fakher, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahmani, Amir Masoud, Ranabhat, Chhabi Lal, Rao, Sowmya J, Rasella, Davide, Rastogi, Prateek, Rath, Goura Kishor, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Rawassizadeh, Reza, Renzaho, Andre M N, Reshmi, Bhageerathy, Rezaei, Negar, Rezaei, Nima, Rezapour, Aziz, Rickard, Jennifer, Roever, Leonardo, Ronfani, Luca, Rostamian, Morteza, Rubagotti, Enrico, Rwegerera, Godfrey M, Saddik, Basema, Sadeghi, Ehsan, Saeedi Moghaddam, Sahar, Sagar, Rajesh, Sahebkar, Amirhossein, Sahiledengle, Biniyam, Salem, Marwa Rashad, Samy, Abdallah M, Santric-Milicevic, Milena M, Saraswathy, Sivan Yegnanarayana Iyer, Sathian, Brijesh, Sathish, Thirunavukkarasu, Schwebel, David C, Sepanlou, Sadaf G, Shahabi, Saeed, Shaheen, Amira A, Shahid, Izza, Shaikh, Masood Ali, Shalash, Ali S, Shams-Beyranvand, Mehran, Shannawaz, Mohammed, Sharafi, Kiomars, Sheikh, Aziz, Sheikhbahaei, Sara, Shetty, Ranjitha S, Shiferaw, Wondimeneh Shibabaw, Shigematsu, Mika, Shin, Jae Il, Shivakumar, K M, Siabani, Soraya, Siddiqi, Tariq Jamal, Singh, Balbir Bagicha, Singh, Jasvinder A, Sintayehu, Yitagesu, Sorrie, Muluken Bekele, Soyiri, Ireneous N, Spurlock, Emma Elizabeth, Sreeramareddy, Chandrashekhar T, Stockfelt, Leo, Sufiyan, Mu'awiyyah Babale, Suliankatchi Abdulkader, Rizwan, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Taherkhani, Amir, Temsah, Mohamad-Hani, Thankappan, Kavumpurathu Raman, Tovani-Palone, Marcos Roberto, Traini, Eugenio, Ullah, Saif, Unnikrishnan, Bhaskaran, Upadhyay, Era, Valadan Tahbaz, Sahel, Varughese, Santosh, Violante, Francesco S, Vo, Bay, Vu, Giang Thu, Waheed, Yasir, Wang, Yuan-Pang, Welgan, Catherine A, Werdecker, Andrea, Yahyazadeh Jabbari, Seyed Hossein, Yaya, Sanni, Yazdi-Feyzabadi, Vahid, Yilma, Mekdes Tigistu, Yonemoto, Naohiro, Younis, Mustafa Z, Yousefinezhadi, Taraneh, Yu, Chuanhua, Yu, Yong, Zaman, Sojib Bin, Zhang, Yunquan, Zhang, Zhi-Jiang, Brauer, Michael, Hay, Simon I, and Reiner, Robert C, Jr
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- 2022
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96. Machine learning based reanalysis of clinical scores for distinguishing between ischemic and hemorrhagic stroke in low resource setting
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Bhardwaj, Aman, Srivastava, MV Padma, Wilson, Pulikottil Vinny, Mehndiratta, Amit, Vishnu, Venugopalan Y, and Garg, Rahul
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- 2022
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97. Individualized closed-loop TMS synchronized with exoskeleton for modulation of cortical-excitability in patients with stroke: a proof-of-concept study
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Neha Singh, Megha Saini, Nand Kumar, M. V. Padma Srivastava, and Amit Mehndiratta
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stroke ,transcranial magnetic stimulation ,exoskeleton ,closed-loop brain stimulation ,neuro-rehabilitation ,motor evoked potential ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
BackgroundRepetitive TMS is used in stroke rehabilitation with predefined passive low and high-frequency stimulation. Brain State-Dependent Stimulation (BSDS)/Activity-Dependent Stimulation (ADS) using bio-signal has been observed to strengthen synaptic connections. Without the personalization of brain-stimulation protocols, we risk a one-size-fits-all approach.MethodsWe attempted to close the ADS loop via intrinsic-proprioceptive (via exoskeleton-movement) and extrinsic-visual-feedback to the brain. We developed a patient-specific brain stimulation platform with a two-way feedback system, to synchronize single-pulse TMS with exoskeleton along with adaptive performance visual feedback, in real-time, for a focused neurorehabilitation strategy to voluntarily engage the patient in the brain stimulation process.ResultsThe novel TMS Synchronized Exoskeleton Feedback (TSEF) platform, controlled by the patient’s residual Electromyogram, simultaneously triggered exoskeleton movement and single-pulse TMS, once in 10 s, implying 0.1 Hz frequency. The TSEF platform was tested for a demonstration on three patients (n = 3) with different spasticity on the Modified Ashworth Scale (MAS = 1, 1+, 2) for one session each. Three patients completed their session in their own timing; patients with (more) spasticity tend to take (more) inter-trial intervals. A proof-of-concept study on two groups—TSEF-group and a physiotherapy control-group was performed for 45 min/day for 20-sessions. Dose-matched Physiotherapy was given to control-group. Post 20 sessions, an increase in ipsilesional cortical-excitability was observed; Motor Evoked Potential increased by ~48.5 μV at a decreased Resting Motor Threshold by ~15.6%, with improvement in clinical scales relevant to the Fugl-Mayer Wrist/Hand joint (involved in training) by 2.6 units, an effect not found in control-group. This strategy could voluntarily engage the patient.ConclusionA brain stimulation platform with a real-time two-way feedback system was developed to voluntarily engage the patients during the brain stimulation process and a proof-of-concept study on three patients indicates clinical gains with increased cortical excitability, an effect not observed in the control-group; and the encouraging results nudge for further investigations on a larger cohort.
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- 2023
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98. IVIM-DKI with parametric reconstruction method for lymph node evaluation and characterization in lymphoma: A preliminary study comparison with FDG-PET/CT
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Archana Vadiraj Malagi, Devasenathipathy Kandasamy, Deepam Pushpam, Kedar Khare, Raju Sharma, Rakesh Kumar, Sameer Bakhshi, and Amit Mehndiratta
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Diffusion kurtosis imaging ,Diffusion-weighted imaging ,Hodgkin lymphoma ,Intravoxel incoherent motion ,Non-hodgkin lymphoma ,Total variation penalty function ,Technology - Abstract
To investigate IVIM-DKI in diagnosing benign and malignant lymph nodes in lymphoma and its subtypes in comparison to FDG-PET/CT. A total of twenty-one (n = 21) patients diagnosed with biopsy-proven Hodgkin lymphoma(HL: n = 13) and non-Hodgkin lymphoma (NHL: n = 8) were prospectively evaluated. All patients underwent MRI(T1-weighted, Short-Tau-Inversion-Recovery (STIR)), and IVIM-DKI was acquired with 9b-values (0–2000s/mm2) at 1.5T and whole-body FDG-PET/CT. The maximum and average standard uptake values (SUVmax and SUVmean) were calculated using PET images. IVIM-DKI parameters (diffusion coefficient(D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and kurtosis (k)) were estimated using IVIM-DKI model with total variation (TV) method (IDTV model). Area-under-curve from receiver-operating-curve (ROC) analysis was used to examine diagnostic value of IVIM-DKI parameters in differentiation between benign and malignant lymph nodes and HL from NHL. Machine learning-based classification of histogram features were performed using linear classifier model. For malignant vs. benign lymph nodes, apparent diffusion coefficient (ADC), f, and k were significantly (p
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- 2023
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99. Black-white Differences in Left Ventricular Hypertrophy Rates Among Young Adults with Ischemic Stroke
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Hou, Yan, Ryan, Kathleen A., Cronin, Carolyn A., Aradine, Elizabeth M., Cole, John W., Chaturvedi, Seemant, Wozniak, Marcella A., Mehndiratta, Prachi, Phipps, Michael S., Yarbrough, Karen L., Yousaf, Mohammad, and Kittner, Steven J.
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- 2022
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100. SARS-CoV-2-associated haemorrhagic encephalitis mimicking Herpes encephalitis
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Handa, Rahul, Nanda, Satyan, Prasad, Atul, Anand, Rajiv, Mehndiratta, Man Mohan, Zutshi, Dhruv, Pahuja, Aarti, Pandey, Rajesh Kumar, Mittal, Payal, Sharma, Sachal, Dass, Sujata K, Bedi, Prabhjeet Kaur, Shah, Pankaj Kumar, Sharma, Bipan, and Malhotra, Nalin
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- 2022
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