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36 citation(s) found for "Asaad, Malke".

Telemedicine in International Cleft Care: A Systematic Review
Bedi, Gurbani , Vyas, Krishna S. , Chung, Michael T. , Morrison, Shane D. , Asaad, Malke , Mardini, Samir

Mayo Clinic

The Cleft Palate Craniofacial Journal | February 5, 2021 | Volume: 58 | Issue: 12 | Pages: 1547-1555

10.1177/1055665621989140 | PMID 33535816 Get It

Background: Cleft lip and cleft palate (CLP) are among the world’s most common congenital malformation and has a higher prevalence in developing nations due to environmental and genetic factors. Global efforts have been developed in order to prevent and treat the malformation. Telemedicine has been implemented in various humanitarian global missions with success and is currently the primary means of care due to COVID-19. Objective: To assess the benefits and barriers of telehealth in the care of patients with CLP through a global approach. Methods: Systematic review of the PubMed and Cochrane Review databases with relevant terms related to telemedicine in cleft lip and palate surgery. Results: Eight articles fit the inclusion criteria and suggested benefits with the use of telemedicine in regard to education, preoperative, and postoperative care as well as increased access to underserved populations. Barriers included connectivity and accessibility concerns. Conclusion: Telehealth is a beneficial way to evaluate patients with CLP in developing countries with proper care and follow-up to reduce complications and to improve health outcomes.
Plastic Surgery Lockdown Learning during Coronavirus Disease 2019: Are Adaptations in Education Here to Stay?
Mohan, Anita T. , Vyas, Krishna S. , Khajuria, Ankur , Asaad, Malke

Mayo Clinic

Plastic and Reconstructive Surgery - Global Open | January 26, 2021 | Volume: 8 | Issue: 7 | Pages: e3064

10.1097/gox.0000000000003064 | PMID 32802695 Get It

Summary: The novel coronavirus disease 2019 has had a major impact on human life and livelihood. The unprecedented challenges have expanded beyond just social and work life, and have grown to impact resident education. In this article, we review the structure of plastic surgery education before the pandemic, the different online learning opportunities for self-directed learning. A summary of the range of platforms and approaches of online remote access delivery of conferences and education that emerged or expanded as a result of the crisis has been reported. This article highlighted the rapid initiatives and efforts of programs and national and international societies to support continuing medical education in conjunction with the guidelines to “shelter at home” and maintain social distancing, and possible future for expanding the reach of online academic initiatives, in addition to the role of developing virtual technologies. The coronavirus disease 2019 crisis has created an opportunity to analyze and advance online learning options to overcome the associated challenges and continue as a reliable platform even following the resolution of the social distancing requirements.
Using Artificial Intelligence to Measure Facial Expression following Facial Reanimation Surgery
Boonipat, Thanapoom , Lin, Jason , Glass, Graeme E. , Stotland, Mitchell A. , Stotland, Mitchell, Asaad, Malke , Mardini, Samir

Mayo Clinic

Plastic & Reconstructive Surgery | October 23, 2020 | Volume: 146 | Issue: 5 | Pages: 1147-1150

10.1097/prs.0000000000007251 | PMID 33136962 Get It

Summary: Social interactions are largely dependent on the interpretation of information conveyed through facial expressions. Although facial reanimation seeks restoration of the facial expression of emotion, outcome measures have not addressed this directly. This study evaluates the use of a machine learning technology to directly measure facial expression before and after facial reanimation surgery. Fifteen study subjects with facial palsy were evaluated both before and after undergoing cross-facial nerve grafting and free gracilis muscle transfer. Eight healthy volunteers were assessed for control comparison. Video footage of subjects with their face in repose and with a posed, closed-lip smile was obtained. The video data were then analyzed using the Noldus FaceReader software application to measure the relative proportions of seven cardinal facial expressions detected within each clip. The facial expression recognition application detected a far greater happy signal in postoperative (42 percent) versus preoperative (13 percent) smile videos (p < 0.0001), compared to 53 percent in videos of control faces smiling. This increase in postoperative happy signal was achieved in exchange for a reduction in the sad signal (15 percent to 9 percent; p = 0.092) and the neutral signal (57 percent to 37 percent; p = 0.0012). For video clips of patients in repose, no significant difference in happy emotion was detected between preoperative (3.1 percent) and postoperative (1.4 percent) states (p = 0.5). This study provides the first proof of concept for the use of a machine learning software application to objectively quantify facial expression before and after surgical reanimation. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV.
Surgical and Patient-Reported Outcomes in Patients With PEEK Versus Titanium Cranioplasty Reconstruction
Taslakian, Editt N. , Banuelos, Joseph, Bite, Uldis, Sharaf, Basel , Abu-Ghname, Amjed, Sharaf, Basel A , Asaad, Malke , Abu‐Ghname, Amjed , Mardini, Samir , Gompel, Jamie J. Van

Mayo Clinic

Journal of Craniofacial Surgery | October 18, 2020 | Volume: 32 | Issue: 1 | Pages: 193-197

10.1097/scs.0000000000007192 | PMID 33074970 Get It

Background: Several materials are available for cranioplasty reconstruction and consensus regarding the ideal material is lacking. The goal of this study is to present surgical and patient-reported outcomes with PEEK versus Titanium alloplastic cranioplasty. Methods: A retrospective review of all patients who underwent alloplastic cranioplasty with PEEK or Titanium from 2010 to 2017 was conducted. Patient demographics and complications were abstracted and analyzed. Information regarding patient-reported outcomes was collected through a telephone survey. Results: A total of 72 patients (median age 55 years) who underwent 77 cranioplasties were identified (38% PEEK, n = 29; 62% Titanium, n = 48). Overall complication rates were similar between the PEEK (24%, n = 7) and Titanium groups (23%, n = 11), P = 0.902. Similarly, implant failure was similar between the 2 groups (7% in PEEK (n = 2), 13% in Titanium (n = 6), P = 0.703). History of radiation was associated with increased rate of infection in patients with Titanium mesh cranioplasty (38% in radiated patients (n = 3), 3% in nonradiated patients (n = 1), P = 0.012) but not PEEK implants (0% infection rate in radiated patients (n = 0), 15% in nonradiated patients (n = 4), P = 1.000). A total of 24 patients (33% response rate) participated in the telephone survey. All PEEK cranioplasty patients who responded to our survey (n = 13) reported good to excellent satisfaction, while 72% of our titanium mesh cohort (n = 8) described good or excellent satisfaction and 27% (n = 3) reported acceptable result. Conclusion: Cranial reconstruction is associated with high satisfaction among cranioplasty patients with PEEK or Titanium showing comparable complications, failure, and patient-reported satisfaction rates. Patients with history of radiotherapy demonstrated a higher infection rate when titanium mesh was used.
Estimating global injuries morbidity and mortality: methods and data used in the Global Burden of Disease 2017 study
James, Spencer L , Castle, Chris D, Dingels, Zachary V, Fox, Jack T, Hamilton, Erin B, Sylte, Dillon O , Bertolacci, Gregory J, Cunningham, Matthew , LeGrand, Kate E , Abdelalim, Ahmed , Abdulkader, Rizwan Suliankatchi , Abedi, Aidin , Abegaz, Kedir Hussein , Eshete, Akine , Abushouk, Abdelrahman Ibrahim , Adebayo, Oladimeji , Advani, Shailesh M, Agudelo‐Botero, Marcela , Ahmad, Tauseef , Aichour, Miloud Taki Eddine, Alahdab, Fares , Alanezi, Fahad , Alema, Niguse Meles , Wassihun, Biresaw , Ali, Beriwan Abdulqadir, Alipour, Vahid, Almasri, Nihad A. , Altirkawi, Khalid A , Amer, Yasser Sami , Andrei, Cătălina Liliana , Ansari-Moghaddam, Alireza, Antonio, Carl Abelardo T, Anvari, Davood , Appiah, Seth Christopher Yaw , Arabloo, Jalal , Arefi, Zohreh , Aremu, Olatunde , Ariani, Filippo , Arora, Amit , Quintanilla, Beatriz Paulina Ayala , Ayano, Getinet , Ayanore, Martin Amogre , Azarian, Ghasem , Badawi, Alaa, Badiye, Ashish , Baig, Atif Amin , Bairwa, Mohan , Bakhtiari, Ahad , Banerjee, Srikanta , Banik, Palash Chandra , Banstola, Amrit , Barker‐Collo, Suzanne , Bärnighausen, Till , Barzegar, Akbar , Belete, Habte , Bennett, Derrick , Berhe, Kidanemaryam , Bhagavathula, Akshaya Srikanth , Bhardwaj, Pankaj , Bhat, Anusha Ganapati , Bhattacharyya, Krittika , Bhutta, Zulfiqar A , Bibi, Sadia , Bijani, Ali , Borschmann, Rohan , Borzì, Antonio Maria , Braithwaite, Dejana , Брико, Н. И. , Brugha, Traolach , Budhathoki, Shyam Sundar , Car, Josip , Cárdenas, Rosario , Carvalho, Félix , Castaldelli-Maia, João Maurício , Castañeda-Orjuela, Carlos A , Castelpietra, Giulio , Catalá-López, Ferrán , Cerin, Ester , Chandan, Joht Singh , Chapman, Jens R. , Chattu, Vijay Kumar , Chattu, Soosanna Kumary , Chaudhary, Neha , Cho, Daniel , Choi, Jee-Young J, Chowdhury, Mohiuddin Ahsanul Kabir , Christopher, Devasahayam Jesudas , Chu, Dinh‐Toi , Costa, Vera Marisa , Dávila-Cervantes, Claudio Alberto , Leo, Diego De, Demoz, Gebre Teklemariam , Demsie, Desalegn Getnet , Deribe, Kebede , Desai, Rupak , Nasab, Mostafa Dianati, Silva, Diana Dias da , Forooshani, Zahra Sadat Dibaji, Doyle, Kerrie , Driscoll, Tim , Dubljanin, Eleonora , Adema, Bereket Duko , Eagan, Arielle Wilder , Elemineh, Demelash Abewa , El‐Khatib, Ziad , Ellingsen, Christian Lycke , Eyawo, Oghenowede , Faris, Pawan , Faro, André , Farzadfar, Farshad , Fereshtehnejad, Seyed-Mohammad , Fernandes, Eduarda , Ferrara, Pietro , Fischer, Florian , Foláyan, Morẹ́nikẹ́ Oluwátóyìn , Fomenkov, Artem Alekseevich , Francis, Joel M , Fukumoto, Takeshi , Geberemariyam, Biniyam Sahiledengle, Gebremariam, Hadush, Gebremedhin, Ketema Bizuwork , Gebremeskel, Leake , Gebremeskel, Gebreamlak Gebremedhn , Gebremichael, Berhe , Geta, Birhanu, Ghafourifard, Mansour , Ghamari, Farhad , Gheshlagh, Reza Ghanei , Gholamian, Asadollah , Gilani, Syed Amir , Gill, Tiffany K, Goulart, Alessandra C. , Grada, Ayman , Guo, Yuming , Haagsma, Juanita A. , Hall, Brian J. , Hamadeh, Randah R , Hassan, Shoaib, Hassen, Hamid Yimam , Havmoeller, Rasmus, Heydarpour, Fatemeh , Hı́jar, Martha , Ho, Hung Chak , Hoang, Chi Linh , Hole, Michael K., Hossain, Naznin , Hosseinzadeh, Mehdi , Hostiuc, Sorin , Ibitoye, Segun Emmanuel , Inbaraj, Leeberk Raja , Irvani, Seyed Sina Naghibi , Islam, M. Mofizul , Islam, Sheikh Mohammed Shariful , Ivers, Rebecca , Jahani, Mohammad Ali, Jakovljević, Mihajlo , Jayaraman, Sudha , Jha, Ravi Prakash , John-Akinola, Yetunde O. , Joseph, Nitin , Joukar, Farahnaz, Jürisson, Mikk , Kahsay, Amaha , Kalankesh, Leila R , Kalhor, Rohollah , Kamil, Teshome Abegaz, Kapoor, Neeti , Karami, Manoochehr , Kasaeian, Amir , Kassaye, Hagazi Gebremedhin, Kavetskyy, Taras , Kayode, Gbenga A , Keiyoro, Peter Njenga, Kelbore, Abraham Getachew , Khader, Yousef , Khafaie, Morteza Abdullatif , Khalid, Nauman , Khalil, Ibrahim A, Khalilov, Rovshan , Khan, Maseer , Khan, Ejaz Ahmad , Khan, Junaid , Khanna, Tripti, Khundkar, Roba , Kiirithio, Daniel N, Kim, Yun Jin , Kısa, Sezer , Kısa, Adnan , Komaki, Hamidreza , Kondlahalli, Shivakumar K M, Koolivand, Ali , Korshunov, Vladimir Andreevich , Kraemer, Moritz U. G. , Krishan, Kewal , Defo, Barthélémy Kuate , Biçer, Burcu Küçük , Kugbey, Nuworza , Kumar, Manasi , Kumar, Vivek , Kumar, Narinder , Kumaresh, Girikumar, Lami, Faris , Lasrado, Savita , Leasher, Janet L , Li, Shanshan , Liu, Xuefeng , Lyons, Ronan A , Machado, Daiane Borges , Madadin, Mohammed , Razek, Muhammed Magdy Abd El, Mahotra, Narayan Bahadur , Majdán, Marek , Majeed, Azeem , Maled, Venkatesh , Manafi, Navid , Manafi, Amir , Manda, Ana-Laura, Mansour-Ghanaei, Fariborz, Mason‐Jones, Amanda J. , Masoumi, Seyedeh Zahra , Massenburg, Benjamin B. , Maulik, Pallab K , Mehndiratta, Man Mohan, Melketsedik, Zeleke Aschalew , Memiah, Peter , Mendoza, Walter, Menezes, Ritesh G. , Mengesha, Melkamu Merid , Meretoja, Tuomo J , Meretoja, Atte , Merie, Hayimro Edemealem , Miazgowski, Bartosz , Miazgowski, Tomasz , Miller, Ted R. , Mini, GK , Мirrakhimov, Erkin М , Mithra, Prasanna , Moghadaszadeh, Masoud, Mohammad, Yousef , Mohammadian-Hafshejani, Abdollah , Mohammed, Shafiu , Mohammed, Jemal , Bandpei, Mohammad Ali Mohseni, Molokhia, Mariam , Monasta, Lorenzo , Moodley, Yoshan , Moradi, Masoud , Moradi, Ghobad , Morawska, Lídia , Velásquez, Ilais Moreno , Mossie, Tilahun Belete , Musa, Kamarul Imran , Mustafa, Ghulam , Naderi, Mehdi , Nagarajan, Ahamarshan Jayaraman , Naik, Gurudatta , Naimzada, Mukhammad David , Nangia, Vinay, Nascimento, Bruno Ramos , Naserbakht, Morteza , Ndwandwe, Duduzile , Negoi, Ionuţ , Ngunjiri, Josephine W, Nguyen, Cuong Tat , Nguyen, Diep Ngoc , Nikbakhsh, Rajan , Ningrum, Dina Nur Anggraini , Nnaji, Chukwudi A , Ofori‐Asenso, Richard , Ogbo, Felix Akpojene , Oghenetega, Onome Bright , Olagunju, Andrew T , Olagunju, Tinuke O , Bali, Ahmed Omar , Onwujekwe, Obinna , Orpana, Heather , Otstavnov, Nikita , Otstavnov, Stanislav S , Mahesh, P A , Padubidri, Jagadish Rao , Pakhalé, Smita , Pakshir, Keyvan , Panda‐Jonas, Songhomitra, Park, Eun‐Kee , Patel, Sangram Kishor , Pathak, Ashish , Pati, Sanghamitra , Paulos, Kebreab , Pepito, Veincent Christian Filipino , Полибин, Р. В. , Polinder, Suzanne, Pourmalek, Farshad , Pourshams, Akram , Poustchi, Hossein, Prakash, Swayam , Pribadi, Dimas Ria Angga , Puri, Parul , Syed, Zahiruddin Quazi, Rabiee, Navid , Radfar, Amir , Rafay, Anwar, Rafiee, Ata , Rafiei, Alireza , Rahim, Fakher , Rahman, Muhammad Aziz , Rajabpour-Sanati, Ali, Rajati, Fatemeh , Rakovac, Ivo , Rao, Sowmya J, Rashedi, Vahid , Rawal, Lal , Rawassizadeh, Reza , Renjith, Vishnu , Resnikoff, Serge , Rezapour, Aziz, Rickard, Jennifer , Saddik, Basema , Safdarian, Mahdi , Sajadi, S. Mohammad , Salamati, Payman, Salem, Marwa Rashad , Salem, Hosni , Salz, Inbal, Samy, Abdallah M , Sanabria, Juan , Sànchez-Riera, Lídia , Sarveazad, Arash , Sathian, Brijesh , Sawhney, Monika, Schwebel, David C. , Seedat, Soraya , Senthilkumaran, Subramanian , Seyedmousavi, Seyedmojtaba , Sha, Feng , Shaahmadi, Faramarz , Shaikh, Masood Ali , Shams-Beyranvand, Mehran , Shigematsu, Mika, Shin, Jae Il , Shiri, Rahman , Sigfúsdóttir, Inga Dóra, Singh, Pankaj Kumar , Sinha, Dhirendra Narain , Soriano, Joan B. , Soyiri, Ireneous N , Sufiyan, Mu’awiyyah Babale , Sykes, Bryan L. , Tabarés‐Seisdedos, Rafael , Tabb, Karen M. , Wogayehu, Biruk , Tefera, Yibekal Manaye , Tekulu, Gebretsadkan Hintsa , Kassie, Ayenew , Титова, М. В. , Tlaye, Kenean Getaneh , Tohidinik, Hamid Reza , Topór-Mądry, Roman , Tripathy, Jaya Prasad , Tsai, Alexander C. , Tsatsakis, Aristidis , Car, Lorainne Tudor , Ullah, Irfan , Ullah, Saif , Upadhyay, Era , Valdéz, Pascual , Violante, Francesco Saverio , Waheed, Yasir , Wang, Yuan‐Pang , Wiangkham, Taweewat , Wolde, Haileab Fekadu , Woldeyes, Dawit Habte , Wu, Ai-Min, Wyper, Grant M. A. , Yadav, Rajaram , Yadollahpour, Ali , Yano, Yuichiro , Yaya, Sanni , Yazdi‐Feyzabadi, Vahid , Ye, Pengpeng , Yisma, Engida , Yoon, Seok‐Jun , Youm, Yoosik , Younis, Mustafa Z , Yousefi, Zabihollah , Yu, Yong , Moghadam, Telma Zahirian , Zaman, Sojib Bin , Zarei, Fatemeh , Zhang, Zhi-Jiang, Zhang, Yunquan , Zodpey, Sanjay , Dandona, Rakhi , Dharmaratne, Samath Dhamminda , Hay, Simon I , Mokdad, Ali H. , Reiner, Robert C. , Vos, Theo , Topór‐Mądry, Roman , Feyissa, Garumma Tolu , Haghparast‐Bidgoli, Hassan , Kumar, G Anil , Zahiruddin, Quazi Syed , Dianatinasab, Mostafa , Sanati, Ali Rajabpour , Baig, Atif Amin , Kumar, Vivek , Castaldelli-Maia, João M , Farzadfar, Farshad , Shin, Jae I L , Islam, Sheikh Mohammed Shariful , Rahman, Muhammad Aziz , Bhagavathula, Akshaya Srikanth , Belete, T , Liu, Zichen , Roberts, Nicholas L S , Henry, Nathaniel J , Abdollahpour, Ibrahim , Adsuar, José Carmelo , Ahmed, Muktar Beshir , Ahmed, Rushdiá , Alghnam, Suliman Abdullah , Ali, Saqib , Alinia, Cyrus , Aljunid, Syed Mohamed , Almasi‐Hashiani, Amir , Antonio, Carl Abelardo T. , Arab-Zozani, Morteza , Asaad, Malke , Balachandran, Arun , Banach, Maciej , Bayati, Mohsen , Bazargan‐Hejazi, Shahrzad , Bedi, Neeraj , Behzadifar, Masoud , Benseñor, Isabela M. , Boloor, Archith , Borges, Guilherme , Boufous, Soufiane , Chatziralli, Irini , Cicuttini, Flavia , Coelho, João M, Dahlawi, Saad M A , Daryani, Ahmad , Demeke, Feleke Mekonnen , Forooshani, Zahra Sadat Dibaji, Do, Hoa , Duko, Bereket , El-Jaafary, Shaimaa I , Zaki, Maysaa El Sayed , Eskandarieh, Sharareh , Foroutan, Masoud , Franklin, Richard C. , Gebremariam, Hadush, Gedefaw, Getnet , Bante, Agegnehu , Gill, Tiffany K. , Goudarzian, Amir Hossein , Grivna, Michal , Guimarães, Rafael Alves , Gupta, Gaurav Kumar , Hamidi, Samer , Handiso, Demelash Woldeyohannes , Haro, Josep María , Hasanzadeh, Amir , Hassanipour, Soheil , Hassankhani, Hadi , Hendrie, Delia V. , Holla, Ramesh , Hu, Guoqing , Ilesanmi, Olayinka Stephen , Jalilian, Farzad , Jayatilleke, Achala Upendra , Jonas, Jost B , Jones, Kelly , Jozwiak, Jacek Jerzy , Jungari, Suresh Banayya , Kabir, Ali , Kanchan, Tanuj , Khalil, Ibrahim A, Khazaei, Salman , Khazaie, Habibolah , Kim, Young‐Eun , Kim, Daniel , Shivakumar, KM , Koyanagi, Ai , Kumar, Nithin , Lansingh, Van Charles , Latifi, Arman , Lauriola, Paolo , Vecchia, Carlo La , Lee, Shaun Wen Huey , Lopez, Alan D , Lotufo, Paulo A. , Malta, Déborah Carvalho , Manjunatha, Narayana , Mansour‐Ghanaei, Fariborz , Mansournia, Mohammad Alì , Maravilla, Joemer Calderon , Aschalew, Zeleke , Meštrović, Tomislav , Mirică, Andreea , Mirzaei-Alavijeh, Mehdi, Moazen, Babak , Mohamadi, Efat , Darwesh, Aso Mohammad , Mohammadpourhodki, Reza , Mohebi, Farnam , Moradi‐Lakeh, Maziar , Moradzadeh, Rahmatollah , Morrison, Shane D. , Muluneh, Atalay Goshu , Najafi, Farid , Nayak, Vinod C , Nazari, Javad , Nguyen, Trang Huyen , Nguyen, Huong Lan Thi , Oh, In‐Hwan , Ota, Erika , Peden, Amy E. , Pereira, Jeevan , Phillips, Michael , Rabiee, Mohammad , Rahimi, Siavash , Rastogi, Prateek , Rathi, Priya , Rawaf, Salman , Ribeiro, Ana Isabel , Ríos-González, Carlos Miguel , Roever, Leonardo , Ronfani, Luca , Roshandel, Gholamreza , Safarpour, Hamid , Salamati, Payman, Santric-Milicevic, Milena M , Sarker, Abdur Razzaque , Sayyah, Mehdi , Shahabi, Saeed , Sheikh, Aziz , Siabani, Soraya , Singh, Ambrish , Soheili, Amin , Sorrie, Muluken Bekele , Stokes, Mark Andrew , Tehrani‐Banihashemi, Arash , Tesfay, Berhe Etsay , Thapar, Rekha , Tran, Khanh Bao , Tran, Bach Xuan , Unnikrishnan, Bhaskaran , Uthman, Olalekan Abdulrahman , Vasankari, Tommi Juhani , Veisani, Yousef , Venketasubramanian, Narayanaswamy , Vlassov, Vasily , Wondmeneh, Temesgen Gebeyehu , Wondmieneh, Adam Belay , YIP, PAUL S. F. , Yonemoto, Naohiro , Yu, Chuanhua , Zaidi, Zoubida , Zamani, Mohammad , Zandian, Hamed , Zhang, Zhi‐Jiang , Ziapour, Arash , Pigott, David M. , Olagunju, Andrew T , Baig, Atif Amin , Desai, Rupak , Alahdab, Fares , Rahim, Fakher

Mayo Clinic

Injury Prevention | August 24, 2020 | Volume: 26 | Issue: Suppl 2 | Pages: i125-i153

10.1136/injuryprev-2019-043531 | PMID 32839249 Get It

Background While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. Methods In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. Results GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. Conclusions GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.
Audio Articles: The Future of Academic Publishing
Howell, Skyler, Rajesh, Aashish , Tran, Nho V. , Asaad, Malke

Mayo Clinic

Plastic & Reconstructive Surgery | July 10, 2020 | Volume: 146 | Issue: 4 | Pages: 521e-522e

10.1097/prs.0000000000007193 | PMID 32649598 Get It

Prophylactic Bronchial Stump Support With Intrathoracic Muscle Flap Transposition
Handel, Amelia Van, Akhavan, Arya , Huang, Tony Chieh‐Ting , Rajesh, Aashish , Shen, K. Robert , Allen, Mark A., Sharaf, Basel , Moran, Steven L. , Van Handel, Amelia, Akhavan, Arya A, Sharaf, Basel A , Asaad, Malke

Mayo Clinic

Annals of Plastic Surgery | July 5, 2020 | Volume: 86 | Issue: 3 | Pages: 317-322

10.1097/sap.0000000000002451 | PMID 33555686 Get It

Background Bronchopleural fistula (BPF) is a dreaded complication of pulmonary resection. For high-risk patients, bronchial stump coverage with vascularized tissue has been recommended. The goal of this study was to report our experience with intrathoracic muscle transposition for bronchial stump coverage. Methods A retrospective review of all patients who underwent intrathoracic muscle flap transposition as a prophylactic measure at our institution between 1990 and 2010 was conducted. Demographics, surgical characteristics, and complication rates were abstracted and analyzed. Results A total of 160 patients were identified. The most common lung resections performed were pneumonectomy (n = 69, 43%) and lobectomy (n = 60, 38%). A total of 168 flaps were used where serratus anterior was the most common flap (n = 136, 81%), followed by intercostal (n = 14, 8%), and latissimus dorsi (n = 12, 7%). Ten patients (6%) developed BPF, and empyema occurred in 13 patients (8%). Median survival was 20 months, and operative mortality occurred in 7 patients (4%). Conclusions Reinforcement of the bronchial closure with vascularized muscle is a viable option for potentially decreasing the incidence of BPF in high-risk patients. Further randomized studies are needed to determine the efficacy of this technique for BPF prevention.
The Evolving Trends in the Impact Factor of Plastic Surgery Journals
Shamoun, Feras, Rajesh, Aashish , Meaike, Jesse D. , Tran, Nho V. , Meaike, Jesse, Asaad, Malke

Mayo Clinic

Annals of Plastic Surgery | July 5, 2020 | Volume: 86 | Issue: 3 | Pages: 329-334

10.1097/sap.0000000000002452 | PMID 33555687 Get It

Background The journal impact factor (IF) is one of the most widely adopted metrics to assess journal value. We aimed to investigate the trends in the IF and ranking of plastic surgery journals (PSJs) over a 22-year period. Methods The Journal Citation Report 2018 was used to identify all journals within the field of plastic surgery from 1997 to 2018. We analyzed the IF of PSJs and that of the category surgery. Results A total of 34 PSJs were identified. The mean IF increased from 0.584 (median, 0.533) in 1997 to 1.58 (median, 1.399) in 2018 (P < 0.0001). Over the same time, the median IF of the journals in the category surgery increased from 0.914 to 1.883. The mean journal IF percentile of PSJs within surgery remained fairly stable (P = 0.999). A strong positive correlation was identified between the IF of PSJs and both the 5-year IF (r = 0.943, P < 0.0001) and the immediacy index (r = 0.736, P < 0.0001). The percentage of self-citations across the study period was fairly stable at a mean of 19.2%. A weak positive correlation was found between the IF and the percentage of self-citations (r = 0.171, P < 0.0001). Conclusions The mean journal IF in PSJs has been trending upward over the last 22 years. Ranking of PSJs IF within the category surgery has remained unchanged. The self-citation rate has been fairly stable and correlated weakly with the IF. A strong positive correlation exists between the IF and both the immediacy index and the 5-year IF.
Altmetrics in Plastic Surgery Journals: Does It Correlate With Citation Count?
Asaad, Malke , Howell, Skyler, Rajesh, Aashish , Meaike, Jesse D. , Tran, Nho V. , Meaike, Jesse

Mayo Clinic

Aesthetic Surgery Journal | June 7, 2020 | Volume: 40 | Issue: 11 | Pages: NP628-NP635

10.1093/asj/sjaa158 | PMID 32506129 Get It

Abstract Background Altmetrics (alternative metrics) have become one of the most commonly utilized metrics to track the impact of research articles across electronic and social media platforms. Objectives The goal of this study was to identify whether the Altmetric Attention Score (AAS) is a good proxy for citation counts and whether it can be employed as an accurate measure to complement the current gold standard. Methods The authors conducted a citation analysis of all articles published in 6 plastic surgery journals during the 2016 calendar year. Citation counts and AAS were abstracted and analyzed. Results A total of 1420 articles were identified. The mean AAS was 11 and the median AAS was 1. The journal with the highest mean AAS was Aesthetic Surgery Journal (31), followed by Plastic and Reconstructive Surgery (19). A weak positive correlation was identified (r = 0.33, P &lt; .0001) between AAS and citations. Articles in the top 1% in terms of citation counts showed strong positive correlation between AAS and citation counts (r = 0.64, P = .01). On the contrary, articles in the top 1% of AAS had no significant correlation with citation counts (r = −0.31, P = .29). Conclusions Overall correlation between citations and AAS was weak, and therefor AAS may not be an accurate early predictor of future citations. The 2 metrics seem to measure different aspects of the impact of scholarly work and should be utilized in tandem for determining the reach of a scientific article.
Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017
James, Spencer L , Castle, Chris D, Dingels, Zachary V, Fox, Jack T, Hamilton, Erin B, Sylte, Dillon O , Henry, Nathaniel J , LeGrand, Kate E , Abdelalim, Ahmed , Abdulkader, Rizwan Suliankatchi , Abedi, Aidin , Eshete, Akine , Abushouk, Abdelrahman Ibrahim , Adebayo, Oladimeji , Agudelo‐Botero, Marcela , Ahmad, Tauseef , Aichour, Miloud Taki Eddine, Alahdab, Fares , Alamene, Genet Melak, Alanezi, Fahad , Alebel, Animut , Alema, Niguse Meles , Ali, Beriwan Abdulqadir, Alikhani, Mahtab , Alipour, Vahid, Almasri, Nihad A. , Altirkawi, Khalid A , Amer, Yasser Sami , Amini, Saeed, Amit, Arianna Maever L. , Andrei, Cătălina Liliana , Ansari-Moghaddam, Alireza, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw , Arabloo, Jalal , Arefi, Zohreh , Aremu, Olatunde , Ariani, Filippo , Arora, Amit , Asghari, Babak , Awoke, Nefsu , Quintanilla, Beatriz Paulina Ayala , Ayano, Getinet , Ayanore, Martin Amogre , Azari, Samad , Azarian, Ghasem , Badawi, Alaa, Badiye, Ashish , Bagli, Eleni , Baig, Atif Amin , Bairwa, Mohan , Bakhtiari, Ahad , Banach, Maciej , Banerjee, Srikanta , Banik, Palash Chandra , Banstola, Amrit , Barker‐Collo, Suzanne , Bärnighausen, Till , Barrero, Lope H. , Barzegar, Akbar , Baye, Bayisa Abdissa , Bekuma, Tariku Tesfaye , Belete, Habte , Bennett, Derrick , Berhe, Kidanemaryam , Bhardwaj, Pankaj , Bhat, Anusha Ganapati , Bhattacharyya, Krittika , Bijani, Ali , Sayeed, Muhammad Shahdaat Bin , Borzì, Antonio Maria , Bražinová, Alexandra, Брико, Н. 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Mehedi , Hassen, Hamid Yimam , Havmoeller, Rasmus, Heydarpour, Fatemeh , Hı́jar, Martha , Ho, Hung Chak , Hoang, Chi Linh , Hole, Michael K., Hossain, Naznin , Hosseinzadeh, Mehdi , Hostiuc, Sorin , Ibitoye, Segun Emmanuel , Ilić, Irena , Ilić, Milena , Inbaraj, Leeberk Raja , Indriasih, Endang , Irvani, Seyed Sina Naghibi , Islam, Sheikh Mohammed Shariful , Islam, M. Mofizul , Ivers, Rebecca , Jacobsen, Kathryn H. , Jahani, Mohammad Ali, Jahanmehr, Nader , Jakovljević, Mihajlo , Jayaraman, Sudha , Jha, Ravi Prakash , John-Akinola, Yetunde O. , Joseph, Nitin , Joukar, Farahnaz, Jozwiak, Jacek Jerzy , Jürisson, Mikk , Kadel, Rajendra , Kahsay, Amaha , Kalankesh, Leila R , Kalhor, Rohollah , Kamil, Teshome Abegaz, Kapoor, Neeti , Karami, Manoochehr , Kasaeian, Amir , Kassaye, Hagazi Gebremedhin, Kavetskyy, Taras , Kebede, Hafte Kahsay , Keiyoro, Peter Njenga, Kelbore, Abraham Getachew , Kelkay, Bayew, Khader, Yousef , Khafaie, Morteza Abdullatif , Khalid, Nauman , Khalil, Ibrahim A, Khalilov, Rovshan , Khan, Ejaz Ahmad , Khan, Maseer , Khanna, Tripti, Shadmani, Fatemeh Khosravi , Khundkar, Roba , Kiirithio, Daniel N, Kim, Yun Jin , Kısa, Adnan , Kısa, Sezer , Komaki, Hamidreza , Kondlahalli, Shivakumar K M, Korshunov, Vladimir Andreevich , Kraemer, Moritz U. 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Dawit Zewdu , Wondmeneh, Temesgen Gebeyehu , Wondmieneh, Adam Belay , Wu, Aimin , YIP, PAUL S. F. , Yonemoto, Naohiro , Yu, Chuanhua , Zaidi, Zoubida , Zamani, Mohammad , Zandian, Hamed , Zarei, Ahmad , Zare, Fatemeh, Degenhardt, Louisa J , Dharmaratne, Samath Dhamminda , Olagunju, Andrew T , Baig, Atif Amin , Desai, Rupak , Alahdab, Fares , Rahim, Fakher

Mayo Clinic

Injury Prevention | April 24, 2020 | Volume: 26 | Issue: Suppl 2 | Pages: i96-i114

10.1136/injuryprev-2019-043494 | PMID 32332142 Get It

Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.