Search

Your search keyword '"Rajani A"' showing total 22,324 results
Start Over Author "Rajani A"
22,324 results on '"Rajani A"'

1. AMR Sign - An Arthroscopic S-shaped Fold Signifying Adequate Medial Meniscus Repair

Author

Rajani AM, Shah UA, Mittal ARS, Gupta S, Garg R, Rajani AA, Punamiya M, and Singhal R

Subjects
amr sign, medial meniscus tear, arthroscopic repair, all inside, adequate repair, Orthopedic surgery, RD701-811
Abstract

Introduction: The preferred management of medial meniscus tears has notably moved from meniscectomies towards repair. With a higher volume of meniscal repairs being done all across the world with every passing day, the lack of an objective and definitive sign suggesting the adequacy of its repair is daunting. The purpose of our study was to introduce a unique and novel arthroscopic sign formed after adequate repair of the medial meniscus, the AMR (Adequacy of Medial meniscus Repair) sign. We hypothesised that it is not only the objective end point for repair, but can also form the indicator for excellent clinical, functional, and radiological outcome even in the long term. Materials and methods: This was a multicentric, prospective study initiated by the corresponding author, and the findings validated subsequently by the other authors. Overall, it included 804 patients of isolated medial meniscus tear operated with arthroscopic all-inside technique between January 2014 and December 2017. Patients were segregated into three groups based on whether an S-shaped curve in the free, inner edge of the medial meniscus sign was formed post-repair, lost after further tightening, or not formed upon subjective completion of repair. All the patients were followed-up and evaluated based of medial joint line tenderness, McMurray’s test for medial meniscus, IKDC score, WOMET score, and radiologically using an MRI at the terminal follow-up. Results: The mean terminal follow-up was 42.34±4.54 months. There was significant (p

Published
2023
Full Text
View/download PDF

2. Genetic control of grain amino acid composition in a UK soft wheat mapping population

Author

Joseph Oddy, Monika Chhetry, Rajani Awal, John Addy, Mark Wilkinson, Dan Smith, Robert King, Chris Hall, Rebecca Testa, Eve Murray, Sarah Raffan, Tanya Y. Curtis, Luzie Wingen, Simon Griffiths, Simon Berry, J. Stephen Elmore, Nicholas Cryer, Isabel Moreira de Almeida, and Nigel G. Halford

Subjects
Plant culture, SB1-1110, Genetics, QH426-470
Abstract

Abstract Wheat (Triticum aestivum L.) is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed identification of quantitative trait loci (QTL) controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programs.

Published
2023
Full Text
View/download PDF

3. Pregnant Women’s Experiences with Midwifery-Led Antenatal Care Services in Peri-Urban Communities in Karachi, Pakistan

Author

Yazdani NS, Haider KA, Khan A, Jaffar Zaidi SA, Rajani A, Nisar I, Jehan F, and Hoodbhoy Z

Subjects
antenatal care, patient satisfaction, respectful maternity care, pakistan., Medicine (General), R5-920
Abstract

Nida Salman Yazdani,1 Kaniz Amna Haider,2 Amna Khan,2 Syed Ali Jaffar Zaidi,2 Akbar Rajani,1 Imran Nisar,2 Fyezah Jehan,2 Zahra Hoodbhoy2 1Research and Programs, VITAL Pakistan Trust, Karachi, Pakistan; 2Department of Paediatrics and Child Health, the Aga Khan University, Karachi, PakistanCorrespondence: Zahra Hoodbhoy, Aga Khan University, Stadium Road PO Box 3500, Karachi, 74800, Pakistan, Tel +92-3343481179, Email zahra.hoodbhoy@aku.eduPurpose: To understand pregnant women’s experience with midwifery-led antenatal care services using the Respectful Maternity Care charter in primary health centers in Karachi, Pakistan.Methods: This cross-sectional study was at Rehri Goth and Ibrahim Hyderi, two peri-urban communities in Karachi, Pakistan, where women receive antenatal care services. All pregnant women in their third trimester who consented during the study period were included. The participants were asked about access to care, antenatal care experience, person-centered approach, and general satisfaction with the facility using a pre-designed questionnaire. These themes were mapped onto the universal Respectful Maternity Care charter. Descriptive statistics were used to summarize the findings in each of these themes. Multivariable logistic regression techniques to determine the relationship between the dependent and independent variables.Results: There were 904 women who agreed to participate in this study during January to December 2021. Majority of the women (94%, n=854) were satisfied with the operating hours and cleanliness. More than 90% of the women reported positive experiences regarding privacy, respectful treatment by midwives, and non-discriminatory care. However, 40% (n=362) of the women reported not receiving adequate information and informed consent before a medical procedure, while 65% (n=587) reported poor counseling for birth preparedness. Maternal age, women’s occupation, women’s education, and parity were found to be significantly associated with respect provided, satisfaction with counseling and the consent process.Conclusion: This study reported satisfaction of pregnant women with the facility’s ambiance, respect, and care; however, poor communication skills regarding consent and antenatal counseling were reported. The findings suggest the need for more efficient strategies, such as regular respectful maternity care and technical training to strengthen midwife-patient interactions and enhance overall satisfaction, thus improving maternal and newborn outcomes.Keywords: antenatal care, patient satisfaction, Respectful Maternity Care, Pakistan

Published
2023

4. Self-rationalization improves LLM as a fine-grained judge

Author

Trivedi, Prapti, Gulati, Aditya, Molenschot, Oliver, Rajeev, Meghana Arakkal, Ramamurthy, Rajkumar, Stevens, Keith, Chaudhery, Tanveesh Singh, Jambholkar, Jahnavi, Zou, James, and Rajani, Nazneen

Subjects
Computer Science - Computation and Language
Abstract

LLM-as-a-judge models have been used for evaluating both human and AI generated content, specifically by providing scores and rationales. Rationales, in addition to increasing transparency, help models learn to calibrate its judgments. Enhancing a model's rationale can therefore improve its calibration abilities and ultimately the ability to score content. We introduce Self-Rationalization, an iterative process of improving the rationales for the judge models, which consequently improves the score for fine-grained customizable scoring criteria (i.e., likert-scale scoring with arbitrary evaluation criteria). Self-rationalization works by having the model generate multiple judgments with rationales for the same input, curating a preference pair dataset from its own judgements, and iteratively fine-tuning the judge via DPO. Intuitively, this approach allows the judge model to self-improve by learning from its own rationales, leading to better alignment and evaluation accuracy. After just two iterations -- while only relying on examples in the training set -- human evaluation shows that our judge model learns to produce higher quality rationales, with a win rate of $62\%$ on average compared to models just trained via SFT on rationale . This judge model also achieves high scoring accuracy on BigGen Bench and Reward Bench, outperforming even bigger sized models trained using SFT with rationale, self-consistency or best-of-$N$ sampling by $3\%$ to $9\%$.

Published
2024

5. KodeXv0.1: A Family of State-of-the-Art Financial Large Language Models

Author

Rajani, Neel, Kiessling, Lilli, Ogaltsov, Aleksandr, and Lang, Claus

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Quantitative Finance - Computational Finance, I.2.7
Abstract

Although powerful, current cutting-edge LLMs may not fulfil the needs of highly specialised sectors. We introduce KodeXv0.1, a family of large language models that outclass GPT-4 in financial question answering. We utilise the base variants of Llama 3.1 8B and 70B and adapt them to the financial domain through a custom training regime. To this end, we collect and process a large number of publicly available financial documents such as earnings calls and business reports. These are used to generate a high-quality, synthetic dataset consisting of Context-Question-Answer triplets which closely mirror real-world financial tasks. Using the train split of this dataset, we perform RAG-aware 4bit LoRA instruction tuning runs of Llama 3.1 base variants to produce KodeX-8Bv0.1 and KodeX-70Bv0.1. We then complete extensive model evaluations using FinanceBench, FinQABench and the withheld test split of our dataset. Our results show that KodeX-8Bv0.1 is more reliable in financial contexts than cutting-edge instruct models in the same parameter regime, surpassing them by up to 9.24%. In addition, it is even capable of outperforming state-of-the-art proprietary models such as GPT-4 by up to 7.07%. KodeX-70Bv0.1 represents a further improvement upon this, exceeding GPT-4's performance on every tested benchmark., Comment: 11 pages, 8 figures

Published
2024

6. Disclosure of clinically actionable genetic variants to thoracic aortic dissection biobank participants

Author

Adelyn Beil, Whitney Hornsby, Wendy R. Uhlmann, Rajani Aatre, Patricia Arscott, Brooke Wolford, Kim A. Eagle, Bo Yang, Jennifer McNamara, Cristen Willer, and J. Scott Roberts

Subjects
Biobank, Communication, Genetic counseling, Pathogenic variants, Return of results, Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Background Disclosure of pathogenic variants to thoracic aortic dissection biobank participants was implemented. The impact and costs, including confirmatory genetic testing in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, were evaluated. Methods We exome sequenced 240 cases with thoracic aortic dissection and 258 controls, then examined 11 aortopathy genes. Pathogenic variants in 6 aortopathy genes (COL3A1, FBN1, LOX, PRKG1, SMAD3, and TGFBR2) were identified in 26 participants, representing 10.8% of the cohort (26/240). A second research sample was used to validate the initial findings. Mailed letters to participants disclosed that a potentially disease causing DNA alteration had been identified (neither the gene nor variant was disclosed). Participants were offered clinical genetic counseling and confirmatory genetic testing in a CLIA laboratory. Results Excluding 6 participants who were deceased or lost to follow-up, 20 participants received the disclosure letter, 10 of whom proceeded with genetic counseling, confirmatory genetic testing, and enrolled in a survey study. Participants reported satisfaction with the letter (4.2 ± 0.7) and genetic counseling (4.4 ± 0.4; [out of 5, respectively]). The psychosocial impact was characterized by low decisional regret (11.5 ± 11.6) and distress (16.0 ± 4.2, [out of 100, respectively]). The average cost for 26 participants was $400, including validation and sending letters. The average cost for those who received genetic counseling and CLIA laboratory confirmation was $605. Conclusions Participants were satisfied with the return of clinically significant biobank genetic results and CLIA laboratory testing; however, the process required significant time and resources. These findings illustrate the trade-offs involved for researchers considering returning research genetic results.

Published
2021
Full Text
View/download PDF

7. Neurologic Manifestations of Severe Acute Respiratory Syndrome Coronavirus 2 Infection in Hospitalized Patients During the First Year of the COVID-19 Pandemic

Author

Anna M. Cervantes-Arslanian, MD, Chakradhar Venkata, MD, Pria Anand, MD, Joseph D. Burns, MD, Charlene J. Ong, MD, Allison M. LeMahieu, MS, Phillip J. Schulte, PhD, Tarun D. Singh, MD, Alejandro A. Rabinstein, MD, Neha Deo, BS, Vikas Bansal, MBBS, MPH, Karen Boman, BS, Juan Pablo Domecq Garces, MD, Donna Lee Armaignac, PhD, APRN, Amy B. Christie, MD, Roman R. Melamed, MD, Yasir Tarabichi, MD, MSCR, Sreekanth R. Cheruku, MD, MPH, Ashish K. Khanna, MD, FCCP, FCCM, FASA, Joshua L. Denson, MD, MS, Valerie M. Banner-Goodspeed, MPH, Harry L. Anderson, III, MD, FACS, FICS, FCCM, FCCP, FAIM, Ognjen Gajic, MD, MS, Vishakha K. Kumar, MD, MBA, Allan Walkey, MD, Rahul Kashyap, MD, MBA, on behalf of the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS): COVID-19 Registry Investigator Group, Jean-Baptiste Mesland, Pierre Henin, Hélène Petre, Isabelle Buelens, Anne-Catherine Gerard, Philippe Clevenbergh, Rolando Claure-Del Granado, Jose A. Mercado, Esdenka Vega-Terrazas, Maria F. Iturricha-Caceres, Ruben Garza, Eric Chu, Victoria Chan, Oscar Y Gavidia, Felipe Pachon, Yeimy A Sanchez, Danijel knežević, Mohamed El Kassas, Mohamed Badr, Ahmed Tawheed, Hend Yahia, Dimitrios Kantas, Vasileios Koulouras, Estela Pineda, Gabina María Reyes Guillen, Helin Archaga Soto, Ana Karen Vallecillo Lizardo, Csaba Kopitkó, Ágnes Bencze, István Méhész, Zsófia Gerendai,, Girish Vadgaonkar, Rekha Ediga, Shilpa Basety, Shwetha Dammareddy, Phani Sreeharsha Kasumalla, Smitha S. Segu, Tuhin Chakraborty, Epcebha Joyce, Sridhar Papani, Mahesh Kamuram, Mradul Kumar Daga, Munisha Agarwal, Ishan Rohtagi, Anusha Cherian, Sreejith Parameswaran, Magesh Parthiban, Phaneendra Doddaga, Neethi Chandra, Puneet Rijhwani, Ashish Jain, Aviral Gupta, Ram Mohan Jaiswal, Ambika Tyagi, Nimish Mathur, Madhav Prabhu, Vishal Jakati, Mukur Petrolwala, Bharat Ladva, Surapaneni Krishna Mohan, Ekambaram Jyothisree, Umamaheswara Raju, Janaki Manduva, Naresh Kolakani, Shreeja Sripathi, Sheetal Chaitanya, Kamlesh Kumar Agrawal, Vijendra Baghel, Kirti Kumar Patel, Nooshin Dalili, Mohsen Nafa, Wataru Matsuda, Reina Suzuki, Michihito Kyo, Shu Tahara, Mineji Hayakawa, Kunihiko Maekawa, Masamitsu Sanui, Sho Horikita, Yuki Itagaki, Akira Kodate, Yuki Takahashi, Koyo Moriki, Takuya Shiga, Yudai Iwasaki, Hidenobu Shigemitsu, Yuka Mishima, Nobuyuki Nosaka, Michio Nagashima, Abdulrahman Al-Fares, Rene Rodriguez-Gutierrez, Jose Gerardo Gonzalez-Gonzalez, Alejandro Salcido-Montenegro, Adrian Camacho-Ortiz, Mariana Janeth Hermosillo Ulloa, Fatimah Hassan-Hanga, Hadiza Galadanci, Abubakar Shehu Gezawa, Halima M. S. Kabara, Taiwo Gboluwaga Amole, Halima Kabir, Dalha Gwarzo Haliru, Abdullahi S Ibrahim, Muhammad Sohaib Asghar, Mashaal Syed, Syed Anosh Ali Naqvi, Igor Borisovich Zabolotskikh,, Konstantin Dmitrievich Zybin, Sergey Vasilevich Sinkov, Tatiana Sergeevna Musaeva, Razan K Alamoudi, Hassan M. AlSharif, Sarah A. Almazwaghi, Mohammed S Elsakran, Mohamed A Aid, Mouaz A Darwich, Omnia M Hagag, Salah A Ali, Alona rocacorba, Kathrine Supeña, Efren Ray Juane, Jenalyn Medina, Jowany Baduria, Marwa Ridha Amer, Mohammed Abdullah, Bawazeer, Talal I. Dahhan, Eiad Kseibi, Abid Shahzad Butt, Syed Moazzum Khurshid, Muath Rabee, Mohammed Abujazar, Razan Alghunaim, Maal Abualkhair, Abeer Turki AlFirm, Yaseen M Arabi, Sheryl Ann Abdukahil, Mohammed A Almazyad, Mohammed I Alarifi, Jara M Macarambon, Ahmad Abdullah Bukhari, Hussain A. Albahrani, Kazi N Asfina, Kaltham M Aldossary, Marija Zdravkovic, Zoran Todorovic, Viseslav Popadic, Slobodan Klasnja, Ana Andrijevic, Srdjan Gavrilovic, Vladimir Carapic, Bojan Kovacevic, Jovana Bojicic, Stevanovic Predrag, Dejan S Stojakov, Duska K Ignjatovic, Suzana C Bojic, Marina M Bobos, Irina B Nenadic, Milica S Zaric, Marko D Djuric, Vladimir R Djukic, Santiago Y. Teruel, Belen C. Martin, Uluhan Sili, Huseyin Bilgin, Pinar Ay, Varsha P Gharpure, Usman Raheemi, Kenneth W. Dodd, Nicholas Goodmanson, Kathleen Hesse, Paige Bird, Chauncey Weinert, Nathan Schoenrade, Abdulrahman Altaher, Esmael Mayar, Matthew Aronson, Tyler Cooper, Monica Logan, Brianna Miner, Gisele Papo, Eric M. Siegal, Phyllis Runningen, Suzanne Barry, Christopher Woll, Gregory Wu, Erin Carrole, Kathryn Burke, Mustafa Mohammed, Roman R. Melamed, David M. Tierney, Love A. Patel, Vino S. Raj, Barite U. Dawud, Narayana Mazumder, Abbey Sidebottom, Alena M. Guenther, Benjamin D. Krehbiel, Nova J. Schmitz, Stacy L. Jepsen, Lynn Sipsey, Anna Schulte, Whitney Wunderlich, Cecely Hoyt, Abhijit A Raval, Andrea Franks, Katherine Irby, Ronald C. Sanders, Jr., Glenda Hefley, Jennifer M. Jarvis, Anmol Kharbanda, Sunil Jhajhria, Zachary Fyffe, Stephen Capizzi, Bethany Alicie, Martha Green, Lori Crockarell, Amelia Drennan, Kathleen Dubuque, Tonya Fambrough, Nikole Gasaway, Briana Krantz, Peiman Nebi, Jan Orga, Margaret Serfass, Alina Simion, Kimberly Warren, Cassie Wheeler, CJ Woolman, Amy B. Christie, Dennis W. Ashley, Rajani Adiga, Andrew S. Moyer, George M. Verghese, Andrea Sikora Newsome, Christy C. Forehand, Rebecca Bruning, Timothy W. Jones, Moldovan Sabov, Fatema Zaidi, Fiona Tissavirasingham, Dhatri Malipeddi, Jarrod M Mosier, Karen Lutrick, Beth Salvagio Campbell, Cathleen Wilson, Patrick Rivers, Jonathan Brinks, Mokenge Ndiva Mongoh, Boris Gilson, Donna Lee Armaignac, Don Parris, Maria Pilar Zuniga, Ilea Vargas, Viviana Boronat, Anneka Hutton, Navneet Kaur, Prashank Neupane, Nohemi Sadule-Rios, Lourdes M. Rojas, Aashish Neupane, Priscilla Rivera, Carlos Valle Carlos, Gregory Vincent, Mahesh Amin, Mary E Schelle, Amanda Steadham, Christopher M Howard, Cameron McBride, Jocelyn Abraham, Orlando Garner, Katherine Richards, Keegan Collins, Preethi Antony, Sindhu Mathew, Valerie C. Danesh, Gueorgui Dubrocq, Amber L. Davis, Marissa J Hammers, ill M. McGahey, Amanda C. Farris, Elisa Priest, Robyn Korsmo, Lorie Fares, Kathy Skiles, Susan M. Shor, Kenya Burns, Corrie A Dowell, Gabriela “Hope” Gonzales, Melody Flores, Lindsay Newman, Debora A Wilk, Jason Ettlinger, Jaccallene Bomar, Himani Darji, Alejandro Arroliga, Alejandro C Arroliga, Corrie A. Dowell, Gabriela Hope Conzales, Debora A. Wilk, Paras B. Khandhar, Elizabeth Kring, Valerie M. Banner-Goodspeed, Somnath Bose, Lauren E. Kelly, Melisa Joseph, Marie McGourty, Krystal Capers, Benjamin Hoenig, Maria C. Karamourtopoulos, Anica C. Law, Elias N. Baedorf Kassis, Allan J. Walkey, Sushrut S. Waikar, Michael A. Garcia, Mia Colona, Zoe Kibbelaar, Michael Leong, Daniel Wallman, Kanupriya Soni, Jennifer Maccarone, Joshua Gilman, Ycar Devis, Joseph Chung, Munizay Paracha, David N. Lumelsky, Madeline DiLorenzo, Najla Abdurrahman, Shelsey Johnson, Maj Andrew M. Hersh, CPT Stephanie L Wachs, Brittany S. Swigger, Stephanie L Wachs, Capt Lauren A. Sattler, Capt Michael N. Moulton, Kimberly Zammit, Patrick, J McGrath, William Loeffler, Maya, R. Chilbert, Aaron S. Miller, Edwin L. Anderson, Rosemary Nagy, Ravali R. Inja, Pooja A. Nawathe, Isabel Pedraza, Jennifer Tsing, Karen Carr, Anila Chaudhary, Kathleen Guglielmino, Raghavendra Tirupathi, Alymer Tang, Arshad Safi, Cindy Green, Jackie Newell, Rayan E. Ihle, Shelda A. Martin, Elaine A. Davis, Katja M. Gist, Imran A Sayed, John Brinton, Larisa Strom, Kathleen Chiotos, Allison M. Blatz, Giyoung Lee, Ryan H. Burnett, Guy I. Sydney, Danielle M. Traynor, Karissa Nauert, Annika Gonzalez, Mariel Bagley, Anita Santpurkar, Salim Surani, Joshua White, Aftab Khan, Rahul Dhahwal, Sreekanth Cheruku, Farzin Ahmed, Christopher Deonarine, Ashley Jones, Mohammad-Ali Shaikh, David Preston, Jeanette Chin, Vidula Vachharajani, Abhijit Duggal, Prabalini Rajendram, Omar Mehkri, Siddharth Dugar, Michelle Biehl, Gretchen Sacha, Stuart Houltham, Alexander King, Kiran Ashok, Bryan Poynter, Mary Beukemann, Richard Rice, Susan Gole, Valerie Shaner, Adarsh Conjeevaram, Michelle Ferrari, Narendrakumar Alappan, Steven Minear, Jaime Hernandez-Montfort, Syed Sohaib Nasim, Ravi Sunderkrishnan, Debasis Sahoo, Patrick S. Milligan, Sandeep K. Gupta, Joy M. Koglin, Regina Gibson, Lana Johnson, Felicia Preston, Crimson Scott, Bethany Nungester, Dana D Byrne, Christa A Schorr, Katie Grant, Katherine L Doktor, Maura C Porto, Olga Kaplan, James E. Siegler, III, Brian Schonewald, Ashley Woodford, Alan Tsai, Savina Reid, Kuntal Bhowmick, Saba Daneshpooy, Cyrus Mowdawalla, Trishna Akshay Dave, Wilhemina Kennedy, Connor Crudeli, Christopher Ferry, Long Nguyen, Sneha Modi, Niharika Padala, Pavan Jitendra Patel, Belle Lin, Lena Chatterjee, Jamie Qiuyun, Fan Mandi Liu, Rasagna Kota, Annesha Banerjee, Steven K. Daugherty, Sam Atkinson, Kelly Shrimpton, Sidney Ontai, Brian Contreras, Uzoma Obinwanko, Nneka Amamasi, Amir Sharafi, Sarah Lee, Zahia Esber, Chetna Jinjvadia, Raquel R Bartz, Vijay Krishnamoorthy, Bryan Kraft, Aaron Pulsipher, Eugene Friedman, Sachin Mehta, Margit Kaufman, Gregg Lobel, Nisha Gandhi, Amr Abdelaty, Elizabeth Shaji, Kiana Lim, Juan Marte, Dani Ashley Sosa, David P. Yamane, Ivy Benjenk, Nivedita Prasanna, Nicholas Perkins, Prera J. Roth, Banu Sivaraj, Haley Fulton, Madison G Herin, Marissa Crum, Morgan E. Fretwell, Emily-Rose Zhou, Christine Waller, Kara Kallies, Jonean Thorsen, Alec Fitzsimmons, Haley Olsen, Heda R. Dapul, Sourabh Verma, Alan Salas, Ariel Daube, Michelle Korn, Michelle Ramirez, Logi Rajagopalan, Laura Santos, Héctor Collazo Santiago, Ricardo Alan Hernandez, Norma Smalls, Asher G Bercow, Mark Shlomovich, Christine Crandall, Sasko Stojanovski, Kristin Johnson, Kelly Michienzi, Steven Q. Davis, Valentina Jovic, Max Masuda, Amanda Hayes, Katharine Nault, Michael Smith, William Snow, Riley Liptak, Hannah Durant, Valerie Pendleton, Alay Nanavati, Risa Mrozowsk, Namrata Nag, Jeff Brauer, Ashwin Dharmadhikari, Sahib Singh, Franco Laghi, Ghania Naeem, Andrew Wang, Kevin Bliden, Amit Rout, Jaime Barnes, Martin Gesheff, Asha Thomas, Melbin Thomas, Alicia R. Liendo, Jovan Milosavljevic, Kenan Abbasi, Nicholas B. Burley, Nicole Rapista, Samuel Amankwah, Sanjay K Poude, Saroj Timilsina, Sauradeep Sarkar, Oluwasayo Akinyosoye, Shashi K. Yalamanchili, Sheena Moorthy, Sonia Sugumar, Jonathan Ford, Martin C. Taylor, Charlotte Dunderdale, Alyssa Henshaw, Mary K. Brunk, Jessica Hagy, Shehryar Masood, Sushrutha Sridhar, Yuk Ming Liu, Sarah Zavala, Esther Shim, Ronald A. Reilkoff, Julia A. Heneghan, Sarah Eichen, Lexie Goertzen, Scott Rajala, Ghislaine Feussom, Ben Tang, Christine C. Junia, Robert Lichtenberg, Hasrat Sidhu, Diana Espinoza, Shelden Rodrigues, Maria Jose Zabala, Daniela Goyes, Ammu Susheela, Buddhi Hatharaliyadda, Naveen Rameshkumar, Amulya Kasireddy, Genessis Maldonado, Lisseth Beltran, Akshata Chaugule, Hassan Khan, Namrata Patil, Ruhi Patil, Rodrigo Cartin-Ceba, Ayan Sen, Fahimeh Talaei, Rahul Kashyap, Juan Pablo Domecq, Ognjen Gajic, Vikas Bansal, Aysun Tekin, Amos Lal, John C. O’Horo, Neha N. Deo, Mayank Sharma, Shahraz Qamar, Romil Singh, Diana J. Valencia Morales, Abigail T. La Nou, Marija Bogojevic, Simon Zec, Devang Sanghavi, Pramod Guru, Pablo Moreno Franco, Karthik Gnanapandithan, Hollie Saunders, Zachary Fleissner, Juan Garcia, Alejandra Yu Lee Mateus, Siva Naga Yarrarapu, Nirmaljot Kaur, Abhisekh Giri, Mohammed Mustafa Hasan, Ashrita Donepudi, Syed Anjum Khan, Nitesh Kumar Jain, Thoyaja Koritala, Alexander Bastidas, Gabriela Orellana, Adriana Briceno Bierwirth, Eliana Milazzo, Juan Guillermo Sierra, Thao Dang, Rahul S Nanchal, Paul A Bergl, Jennifer L Peterson, Jessica Timmer, Kimberly Welker, Travis Yamanaka, Nicholas A. Barreras, Michael Markos, Anita Fareeduddin, Rohan Mehta, Chakradhar Venkata, Miriam Engemann, Annamarie Mantese, Yasir Tarabichi, Adam Perzynski, Christine Wang, Dhatri Kotekal, Adriana C Briceno Bierwirth, Gabriela M Orellana, Gerardo Catalasan, Shohana Ahmed, Carlos F Matute, Ahmad Hamdan, Ivania Salinas, Genesis Del Nogal, Angel Tejada, Anna Eschler, Mary Hejna, Emily Lewandowski, Kristen Kusmierski, Clare Martin, Jen-Ting Chen, Aluko Hope, Zoe Tsagaris, Elise Ruen, Aram Hambardzumyan, Nasar A Siddiqi, Lesly Jurado, Lindsey Tincher, Carolyn Brown, Prithvi Sendi, Meghana Nadiger, Balagangadhar Totapally, Bhagat S. Aulakh, Sandeep Tripathi, Jennifer A. Bandy, Lisa M. Kreps, Dawn R. Bollinger, Neha Gupta, Brent R Brown, Tracy L Jones, Kassidy Malone, Lauren A Sinko, Amy B Harrell, Shonda C Ayers, Lisa M Settle, Taylor J Sears, Roger Scott Stienecker, Andre G. Melendez, Tressa A. Brunner, Sue M Budzon, Jessica L. Heffernan, Janelle M. Souder, Tracy L. Miller, Andrea G. Maisonneuve, Roberta E. Redfern, Jessica Shoemaker, Jennifer Micham, Lynn Kenney, Gabriel Naimy, Victoria Schauf, Sara Utley, Holly Balcer, Kerry P. J. Pulver, Jennifer Yehle, Alicia Weeks, Terra Inman, Majdi Hamarshi, Jeannette Ploetz, Nick Bennett, Kyle Klindworth, Moustafa Younis, Adham Mohamed, Brian L. Delmonaco, Anthony Franklin, Mitchell Heath, Diane Barkas, Antonia L. Vilella, Sara B. Kutner, Kacie Clark, Danielle Moore, Shina Menon, John K McGuire, Deana Rich, Harry L. Anderson, III, Dixy Rajkumar, Ali Abunayla, Jerrilyn Heiter, Howard A. Zaren, Stephanie J. Smith, Grant C. Lewis, Lauren Seames, Cheryl Farlow, Judy Miller, Gloria Broadstreet, John Lin, Cindy Terrill, Brock Montgomery, Sydney Reyes, Summer Reyes, Alex Plattner, Anthony Martinez, Micheal Allison, Aniket Mittal, Rafael Ruiz, Aleta Skaanland, Robert Ross, Umang Patel, Jordesha Hodge, Krunal Kumar Patel, Shivani Dalal, Himanshu Kavani, Sam Joseph, Michael A. Bernstein, Ian K. Goff, Matthew Naftilan, Amal Mathew, Deborah Williams, Sue Murdock, Maryanne Ducey, Kerianne Nelson, Jason Block, James Mitchel, Connor G O’Brien, Sylvan Cox, William Marx, Ioana Amzuta, Asad J. Choudhry, Mohammad T. Azam, Kristina L Carter, Michael A Olmos, Brittany M Parker, Julio Quintanilla, Tara A Craig, Brendon J Clough, Jeffrey T Jameson, Utpal S. Bhalala, Joshua Kuehne, Melinda Garcia, Morgan Beebe, Heather Herrera, Chris Fiack, Stephanie Guo, May Vawer, Beth Blackburn, Caleb Darby, Kristy Page, Amanda Brown, Jessie McAbee, Katherine A. Belden, Michael Baram, Devin M. Weber, Rosalie DePaola, Yuwei Xia, Hudson Carter, Aaron Tolley, Mary Barletta, Mark Steele, Laurie Kemble, Joshua L. Denson, A. Scott Gillet, Margo Brown, Rachael Stevens, Andrew Wetherbie, Kevin Tea, Mathew Moore, Abdurrahman Husain, Atul Malhotra, Qais Zawaydeh, Benjamin J Sines, Thomas J Bice, Emily A. Vail, Susannah Nicholson, Rachelle B. Jonas, AnnaRose E. Dement, William Tang, Mark DeRosa, Robert E. Villarreal, Rajany V. Dy, Alfredo Iardino, Jill Sharma, Richard Czieki, Julia Christopher, Ryan Lacey, Marwan Mashina, Kushal Patel, Erica C. Bjornstad, Nancy M. Tofil, Scott House, Isabella Aldana, Nikhil K. Meena, Jose D. Caceres, Nikhil K Meena, Sarenthia M. Epps, Harmeen Goraya, Kelsey R. Besett, Ryan James, Lana Y. Abusalem, Akash K. Patel, Lana S Hasan, Dina Gomaa, Michael Goodman, Devin Wakefield, Anthony Spuzzillo, John O. Shinn II, Robert MacLaren, Azra Bihorac, Tezcan Ozrazgat Baslanti, George Omalay, Haleh Hashemighouchani, Julie S. Cupka, Matthew M Ruppert, Patrick W. McGonagill, Colette Galet, Janice Hubbard, David Wang, Lauren Allan, Aditya Badheka, Madhuradhar Chegondi, Usman Nazir, Garrett Rampon, Jake Riggle, Nathan Dismang, Vicki Montgomery, Janice Sullivan, Sarah Morris, Jennifer Nason, Ozan Akca, Rainer Lenhardt, Rodrigo S. Cavallazzi, Ann Jerde, Alexa Black, Allison Polidori, Haily Griffey, Justin Winkler, Thomas Brenzel, Roger A. Alvarez, Amarilys Alarcon-Calderon, Marie Anne Sosa, Sunita K. Mahabir, Mausam J. Patel, Pauline Park, Andrew Admon, Sinan Hanna, Rishi Chanderraj, Maria Pliakas, Ann Wolski, Jennifer Cirino, Dima Dandachi, Hariharan Regunath, Maraya N. Camazine, Grant. E. Geiger, Abdoulie O. Njai, Baraa M. Saad, Faraaz Ali Shah, Byron Chuan, Sagar L. Rawal, Manal Piracha, Joseph E. Tonna, Nicholas M. Levin, Kayte Suslavich, Rachel Tsolinas, Zachary T. Fica, Chloe R. Skidmore, Renee D. Stapleton, Anne E. Dixon, Olivia Johnson, Sara S. Ardren, Stephanie Burns, Anna Raymond, Erika Gonyaw, Kevin Hodgdon, Chloe Housenger, Benjamin Lin, Karen McQuesten, Heidi Pecott-Grimm, Julie Sweet, Sebastian Ventrone, Nita Khandelwal, T. Eoin West, Ellen S. Caldwell, Lara Lovelace-Macon, Navya Garimella, Denisse B. Dow, Sreekanth R. Cheruku, Catherine Chen, Murtaza Akhter, Rania Abdul Rahman, Mary Mulrow, Erin M. Wilfong, Kelsi Vela, Ashish K. Khanna, Lynne Harris, Bruce Cusson, Jacob Fowler, David Vaneenenaam, Glen McKinney, Imoh Udoh, Kathleen Johnson, Patrick G. Lyons, Andrew P Michelson, Sara S. Haluf, Lauren M. Lynch, Nguyet M. Nguyen, Aaron Steinberg, Nicholas Braus, Vishwanath Pattan, Jessica Papke, Ismail Jimada, Nida Mhid, Samuel Chakola, Kevin Sheth, Abdalla Ammar, Mahmoud Ammar, Victor Torres Lopez, Charles Dela Cruz,, Akhil Khosla, and Samir Gautam

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

OBJECTIVES:. To describe the prevalence, associated risk factors, and outcomes of serious neurologic manifestations (encephalopathy, stroke, seizure, and meningitis/encephalitis) among patients hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. DESIGN:. Prospective observational study. SETTING:. One hundred seventy-nine hospitals in 24 countries within the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study COVID-19 Registry. PATIENTS:. Hospitalized adults with laboratory-confirmed SARS-CoV-2 infection. INTERVENTIONS:. None. RESULTS:. Of 16,225 patients enrolled in the registry with hospital discharge status available, 2,092 (12.9%) developed serious neurologic manifestations including 1,656 (10.2%) with encephalopathy at admission, 331 (2.0%) with stroke, 243 (1.5%) with seizure, and 73 (0.5%) with meningitis/encephalitis at admission or during hospitalization. Patients with serious neurologic manifestations of COVID-19 were older with median (interquartile range) age 72 years (61.0–81.0 yr) versus 61 years (48.0–72.0 yr) and had higher prevalence of chronic medical conditions, including vascular risk factors. Adjusting for age, sex, and time since the onset of the pandemic, serious neurologic manifestations were associated with more severe disease (odds ratio [OR], 1.49; p < 0.001) as defined by the World Health Organization ordinal disease severity scale for COVID-19 infection. Patients with neurologic manifestations were more likely to be admitted to the ICU (OR, 1.45; p < 0.001) and require critical care interventions (extracorporeal membrane oxygenation: OR, 1.78; p = 0.009 and renal replacement therapy: OR, 1.99; p < 0.001). Hospital, ICU, and 28-day mortality for patients with neurologic manifestations was higher (OR, 1.51, 1.37, and 1.58; p < 0.001), and patients had fewer ICU-free, hospital-free, and ventilator-free days (estimated difference in days, –0.84, –1.34, and –0.84; p < 0.001). CONCLUSIONS:. Encephalopathy at admission is common in hospitalized patients with SARS-CoV-2 infection and is associated with worse outcomes. While serious neurologic manifestations including stroke, seizure, and meningitis/encephalitis were less common, all were associated with increased ICU support utilization, more severe disease, and worse outcomes.

Published
2022
Full Text
View/download PDF

8. Hospital Variation in Management and Outcomes of Acute Respiratory Distress Syndrome Due to COVID-19

Author

Shelsey W. Johnson, MD, Michael A. Garcia, MD, Emily K. Q. Sisson, MA, Christopher R. Sheldrick, PhD, Vishakha K. Kumar, MD, MBA, Karen Boman, BA, Scott Bolesta, PharmD, Vikas Bansal, MBBS, MPH, Amos Lal, MBBS, J. P. Domecq, MD, MS, Roman R. Melamed, MD, Amy B. Christie, MD, Abdurrahman Husain, MD, Santiago Yus, MBBS, Ognjen Gajic, MD, MSc, Rahul Kashyap, MBBS, MBA, Allan J. Walkey, MD, MSc, from the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS): COVID-19 Registry Investigator Group, Oscar Y. Gavidia, Felipe Pachon, Yeimy A. Sanchez, Mohamed El Kassas, Mohamed Badr, Ahmed Tawheed, Hend Yahia, Wataru Matsuda, Reina Suzuki, Masamitsu Sanui, Sho Horikita, Yuki Itagaki, Akira Kodate, Yuki Takahashi, Koyo Moriki, Muhammad Sohaib, Asghar, Mashaal Syed, Syed Anosh, Ali Naqvi, Borisovich Zabolotskikh, Konstantin Dmitrievich Zybin, Sergey Vasilevich Sinkov, Tatiana Sergeevna Musaeva, Mohammed A. Almazyad, Mohammed I. Alarifi, Jara M. Macarambon, Ahmad Abdullah Bukhari, Hussain A. Albahrani, Kazi N. Asfina, Kaltham M. Aldossary, Marija Zdravkovic, Zoran Todorovic, Viseslav Popadic, Slobodan Klasnja, Predrag D. Stevanovic, Dejan S. Stojakov, Duska K. Ignjatovic, Suzana C. Bojic, Marina M. Bobos, Irina B. Nenadic, Milica S. Zaric, Marko D. Djuric, Vladimir R. Djukic, Santiago Yus, Belen C. Martin, Uluhan Sili, Huseyin Bilgin, Pinar Ay, Roman R. Melamed, David M. Tierney, Love A. Patel, Vino S. Raj, Barite U. Dawud, Narayana Mazumder, Abbey Sidebottom, Alena M. Guenther, Benjamin D. Krehbiel, Nova J. Schmitz, Stacy L. Jepsen, Lynn Sipsey, Anna Schulte, Whitney Wunderlich, Cecely Hoyt, Kenneth W. Dodd, Nicholas Goodmanson, Kathleen Hesse, Paige Bird, Chauncey Weinert, Nathan Schoenrade, Abdulrahman Altaher, Esmael Mayar, Matthew Aronson, Tyler Cooper, Monica Logan, Brianna Miner, Gisele Papo, Abdulrahman Al-Fares, Anmol Kharbanda, Sunil Jhajhria, Zachary Fyffe, Amy B. Christie, Dennis W. Ashley, Rajani Adiga, Andrea Sikora Newsome, Christy C. Forehand, Rebecca Bruning, Timothy W. Jones, Moldovan Sabov, Fatema Zaidi, Fiona Tissavirasingham, Dhatri Malipeddi, Valerie M. Banner-Goodspeed, Somnath Bose, Lauren E. Kelly, Melisa Joseph, Marie McGourty, Krystal Capers, Benjamin Hoenig, Maria C. Karamourtopoulos, Anica C. Law, Elias N. Baedorf Kassis, Allan J. Walkey, Sushrut S. Waikar, Michael A. Garcia, Mia Colona, Zoe Kibbelaar, Michael Leong, Daniel Wallman, Kanupriya Soni, Jennifer Maccarone, Joshua Gilman, Ycar Devis, Joseph Chung, Munizay Paracha, David N. Lumelsky, Madeline DiLorenzo, Najla Abdurrahman, Shelsey Johnson, Kimberly Zammit, Patrick J. McGrath, William Loeffler, Maya R. Chilbert, Jean-Baptiste Mesland, Pierre Henin, Hélène Petre, Isabelle Buelens, Anne-Catherine Gerard, Rayan E. Ihle, Shelda A. Martin, Elaine A. Davis, Salim Surani, Joshua White, Aftab Khan, Rahul Dhahwal, Sreekanth Cheruku, Farzin Ahmed, Christopher Deonarine, Ashley Jones, Mohammad-Ali Shaikh, David Preston, Jeanette Chin, Steven K. Daugherty, Sam Atkinson, Kelly Shrimpton, Raquel R. Bartz, Vijay Krishnamoorthy, Bryan Kraft, Aaron Pulsipher, Eugene Friedman, Sachin Mehta, David P. Yamane, Ivy Benjenk, Nivedita Prasanna, Katharine Nault, Ronald A. Reilkoff, Julia A. Heneghan, Sarah Eichen, Lexie Goertzen, Scott Rajala, Ghislaine Feussom, Ben Tang, Mayo Clinic Arizona, Rodrigo Cartin-Ceba, Ayan Sen, Amanda Palacios, Giyth M. Mahdi, Rahul Kashyap, Ognjen Gajic, Vikas Bansal, Aysun Tekin, Amos Lal, John C. O’Horo, Neha N. Deo, Mayank Sharma, Shahraz Qamar, Juan Pablo Domecq, Romil Singh, Alex Niven, Mayo Clinic, Eau Claire, Abigail T. La Nou, Marija Bogojevic, Barbara Mullen, Devang Sanghavi, Pramod Guru, Pablo Moreno Franco, Karthik Gnanapandithan, Hollie Saunders, Zachary Fleissner, Juan Garcia, Alejandra Yu Lee Mateus, Siva Naga Yarrarapu, Nirmaljot Kaur, Abhisekh Giri, Syed Anjum Khan, Nitesh Kumar Jain, Thoyaja Koritala, Chakradhar Venkata, Miriam Engemann, Annamarie Mantese, Yasir Tarabichi, Adam Perzynski, Christine Wang, Dhatri Kotekal, Bhagat S. Aulakh, Sandeep Tripathi, Jennifer A. Bandy, Lisa M. Kreps, Dawn R. Bollinger, Roger Scott Stienecker, Andre G. Melendez, Tressa A. Brunner, Sue M. Budzon, Jessica L. Heffernan, Janelle M. Souder, Tracy L. Miller, Andrea G. Maisonneuve, Antonia L. Vilella, Sara B. Kutner, Kacie Clark, Danielle Moore, Harry L. Anderson, III, Dixy Rajkumar, Ali Abunayla, Jerrilyn Heiter, Howard A. Zaren, Stephanie J. Smith, Grant C. Lewis, Lauren Seames, Cheryl Farlow, Judy Miller, Gloria Broadstreet, Anthony Martinez, Micheal Allison, Aniket Mittal, Rafael Ruiz, Aleta Skaanland, Robert Ross, Neha Gupta, Tracy L. Jones, Shonda C. Ayers, Amy B. Harrell, Dr. Brent R. Brown, Abdurrahman Husain, Atul Malhotra, Qais Zawaydeh, Dragana Markotić, Ivana Bošnjak, Emily A. Vail, Susannah Nicholson, Rachelle B. Jonas, AnnaRose E. Dement, William Tang, Mark DeRosa, Robert E. Villarreal, Patrick W. McGonagill, Colette Galet, Janice Hubbard, David Wang, Lauren Allan, Aditya Badheka, Madhuradhar Chegondi, Roger A. Alvarez, Amarilys Alarcon-Calderon, Marie Anne Sosa, Sunita K. Mahabir, Mausam J. Patel, Faraaz Ali Shah, Byron Chuan, Sagar L. Rawal, Manal Piracha, Joseph E. Tonna, Nicholas M. Levin, Kayte Suslavich, Rachel Tsolinas, Zachary T. Fica, Chloe R. Skidmore, Renee D. Stapleton, Anne E. Dixon, Olivia Johnson, Sara S. Ardren, Stephanie Burns, Anna Raymond, Erika Gonyaw, Kevin Hodgdon, Chloe Housenger, Benjamin Lin, Karen McQuesten, Heidi Pecott-Grimm, Julie Sweet, Sebastian Ventrone, Murtaza Akhter, Rania Abdul Rahman, Mary Mulrow, Ashish K. Khanna, Lynne Harris, Bruce Cusson, Jacob Fowler, David Vaneenenaam, Glen McKinney, Imoh Udoh, Kathleen Johnson, Vishwanath Pattan, Jessica Papke, Ismail Jimada, Nida Mhid, and Samuel Chakola

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

OBJECTIVES:. To describe hospital variation in use of “guideline-based care” for acute respiratory distress syndrome (ARDS) due to COVID-19. DESIGN:. Retrospective, observational study. SETTING:. The Society of Critical Care Medicine’s Discovery Viral Infection and RESPIRATORY ILLNESS UNIVERSAL STUDY COVID-19 REGISTRY. PATIENTS:. Adult patients with ARDS due to COVID-19 between February 15, 2020, and April 12, 2021. INTERVENTIONS:. Hospital-level use of “guideline-based care” for ARDS including low-tidal-volume ventilation, plateau pressure less than 30 cm H2O, and prone ventilation for a Pao2/Fio2 ratio less than 100. MEASUREMENTS AND MAIN RESULTS:. Among 1,495 adults with COVID-19 ARDS receiving care across 42 hospitals, 50.4% ever received care consistent with ARDS clinical practice guidelines. After adjusting for patient demographics and severity of illness, hospital characteristics, and pandemic timing, hospital of admission contributed to 14% of the risk-adjusted variation in “guideline-based care.” A patient treated at a randomly selected hospital with higher use of guideline-based care had a median odds ratio of 2.0 (95% CI, 1.1–3.4) for receipt of “guideline-based care” compared with a patient receiving treatment at a randomly selected hospital with low use of recommended therapies. Median-adjusted inhospital mortality was 53% (interquartile range, 47–62%), with a nonsignificantly decreased risk of mortality for patients admitted to hospitals in the highest use “guideline-based care” quartile (49%) compared with the lowest use quartile (60%) (odds ratio, 0.7; 95% CI, 0.3–1.9; p = 0.49). CONCLUSIONS:. During the first year of the COVID-19 pandemic, only half of patients received “guideline-based care” for ARDS management, with wide practice variation across hospitals. Strategies that improve adherence to recommended ARDS management strategies are needed.

Published
2022
Full Text
View/download PDF

9. Variation in Use of Repurposed Medications Among Patients With Coronavirus Disease 2019. From The Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study: Coronavirus Disease 2019 Registry Investigator Group

Author

Michael A. Garcia, MD, Shelsey W. Johnson, MD, Nicholas A. Bosch, MD, MSc, Emily K. Sisson, MA, Christopher R. Sheldrick, PhD, Vishakha K. Kumar, MD, MBA, Karen Boman, BS, Scott Bolesta, PharmD, Vikas Bansal, MBBS, MPH, Neha Deo, BS, J. P. Domecq, MD, Amos Lal, MD, Amy B. Christie, MD, Valerie M. Banner-Goodspeed, MPH, Devang Sanghavi, MD, MHA, Girish Vadgaonkar, MBBS, Ognjen Gajic, MD, MSc, Rahul Kashyap, MBBS, MBA, Allan J. Walkey, MD, MSc, for the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study Investigators, Jean-Baptiste Mesland, Pierre Henin, Hélène Petre, Isabelle Buelens, Anne-Catherine Gerard, Philippe Clevenbergh, Dragana Markotić, Ivana Bošnjak, Ruben Garza, Eric Chu, Victoria Chan, Oscar Y Gavidia, Felipe Pachon, Yeimy A Sanchez, Mohamed El Kassas, Mohamed Badr, Ahmed Tawheed, Hend Yahia, Jose Luis Ramos Coello, Guillermo Perez, Ana Karen Vallecillo Lizardo, Gabina María Reyes Guillen, Helin Archaga Soto, Smitha S. Segu, Tuhin Chakraborty, Epcebha Joyce, Girish Vadgaonkar, Rekha Ediga, Shilpa Basety, Shwetha Dammareddy, Phani Sreeharsha Kasumalla, Umamaheswara Raju, Janaki Manduva, Naresh Kolakani, Shreeja Sripathi, Sheetal Chaitanya, Mradul Kumar Daga, Munisha Agarwal, Ishan Rohtagi, Sridhar Papani, Mahesh Kamuram, Kamlesh Kumar Agrawal, Vijendra Baghel, Kirti Kumar Patel, Surapaneni Krishna Mohan, Ekambaram Jyothisree, Wataru Matsuda, Reina Suzuki, Michihito Kyo, Yuki Itagaki, Akira Kodate, Yuki Takahashi, Koyo Moriki, Fatimah Hassan-Hanga, Hadiza Galadanci, Abubakar Shehu Gezawa, Halima M. S. Kabara, Taiwo Gboluwaga Amole, Halima Kabir, Dalha Gwarzo Haliru, Abdullahi S Ibrahim, Muhammad Sohaib Asghar, Mashaal Syed, Syed Anosh Ali Naqvi, Igor Borisovich Zabolotskikh, Konstantin Dmitrievich Zybin, Sergey Vasilevich Sinkov, Tatiana Sergeevna Musaeva, Mohammed A Almazyad, Mohammed I Alarifi, Jara M Macarambon, Ahmad Abdullah Bukhari, Hussain A. Albahrani, Kazi N Asfina, Kaltham M Aldossary, Marija Zdravkovic, Zoran Todorovic, Viseslav Popadic, Slobodan Klasnja, Bojan Kovacevic, Jovana Bojicic, Predrag D Stevanovic, Dejan S Stojakov, Duska K Ignjatovic, Suzana C Bojic, Marina M Bobos, Irina B Nenadic, Milica S Zaric, Marko D Djuric, Vladimir R Djukic, Santiago Y. Teruel, Belen C. Martin, Uluhan Sili, Huseyin Bilgin, Pinar Ay, Abhijit A Raval, Andrea Franks, Anmol Kharbanda, Sunil Jhajhria, Zachary Fyffe, Stephen Capizzi, Bethany Alicie, Martha Green, Lori Crockarell, Amelia Drennan, Kathleen Dubuque, Tonya Fambrough, Nikole Gasaway, Briana Krantz, Peiman Nebi, Jan Orga, Margaret Serfass, Alina Simion, Kimberly Warren, Cassie Wheeler, CJ Woolman, Amy B. Christie, Dennis W. Ashley, Rajani Adiga, Andrew S. Moyer, George M. Verghese, Andrea Sikora Newsome, Christy C. Forehand, Rebecca Bruning, Timothy W. Jones, Moldovan Sabov, Fatema Zaidi, Fiona Tissavirasingham, Dhatri Malipeddi, Donna Lee Armaignac, Don Parris, Maria Pilar Zuniga, Ilea Vargas, Viviana Boronat, Anneka Hutton, Navneet Kaur, Prashank Neupane, Nohemi Sadule-Rios, Lourdes M. Rojas, Aashish Neupane, Priscilla Rivera, Carlos Valle Carlos, Gregory Vincent, Valerie M. Banner-Goodspeed, Somnath Bose, Lauren E. Kelly, Melisa Joseph, Marie McGourty, Krystal Capers, Benjamin Hoenig, Maria C. Karamourtopoulos, Anica C. Law, Elias N. Baedorf Kassis, Allan J. Walkey, Sushrut S. Waikar, Michael A. Garcia, Mia Colona, Zoe Kibbelaar, Michael Leong, Daniel Wallman, Kanupriya Soni, Jennifer Maccarone, Joshua Gilman, Ycar Devis, Joseph Chung, Munizay Paracha, David N. Lumelsky, Madeline DiLorenzo, Najla Abdurrahman, Shelsey Johnson, Kimberly Zammit, Patrick, J McGrath, William Loeffler, Maya, R Chilbert, Raghavendra Tirupathi, Alymer Tang, Arshad Safi, Cindy Green, Jackie Newell, Katja M. Gist, Imran A Sayed, John Brinton, Larisa Strom, Steven K. Daugherty, Sam Atkinson, Kelly Shrimpton, David P. Yamane, Ivy Benjenk, Nivedita Prasanna, Norma Smalls, Michael Smith, William Snow, Riley Liptak, Hannah Durant, Valerie Pendleton, Alay Nanavati, Risa Mrozowsk, Yuk Ming Liu, Sarah Zavala, Esther Shim, Ronald A. Reilkoff, Julia A. Heneghan, Sarah Eichen, Lexie Goertzen, Scott Rajala, Ghislaine Feussom, Ben Tang, Christine C. Junia, Robert Lichtenberg, Hasrat Sidhu, Diana Espinoza, Shelden Rodrigues, Maria Jose Zabala, Daniela Goyes, Ammu Susheela, Buddhi Hatharaliyadda, Naveen Rameshkumar, Amulya Kasireddy, Genessis Maldonado, Lisseth Beltran, Akshata Chaugule, Hassan Khan, Rodrigo Cartin-Ceba, Ayan Sen, Amanda Palacios, Giyth M. Mahdi, Rahul Kashyap, Ognjen Gajic, Vikas Bansal, Aysun Tekin, Amos Lal, John C. O’Horo, Neha N. Deo, Mayank Sharma, Shahraz Qamar, Juan Pablo Domecq, Romil Singh, Alex Niven, Abigail La Nou, Marija Bogojevic, Barbara Mullen, Devang Sanghavi, Pablo Moreno Franco, Pramod Guru, Karthik Gnanapandithan, Hollie Saunders, Zachary Fleissner, Juan Garcia, Alejandra Yu, Lee Mateus, Siva Naga Yarrarapu, Nirmaljot Kaur, Abhisekh Giri, Syed Anjum Khan, Nitesh Kumar Jain, Thoyaja Koritala, Jessica Timmer, Kimberly Welker, Chakradhar Venkata, Miriam Engemann, Annamarie Mantese, Anna Eschler, Mary Hejna, Emily Lewandowski, Kristen Kusmierski, Clare Martin, Bhagat S. Aulakh, Sandeep Tripathi, Jennifer A. Bandy, Lisa M. Kreps, Dawn R. Bollinger, Roger Scott Stienecker, Andre G. Melendez, Tressa A. Brunner, Sue M Budzon, Jessica L. Heffernan, Janelle M. Souder, Tracy L. Miller, Andrea G. Maisonneuve, Brian L. Delmonaco, Anthony Franklin, Mitchell Heath, Antonia L. Vilella, Sara B. Kutner, Kacie Clark, Danielle Moore, Harry L. Anderson, III, Dixy Rajkumar, Ali Abunayla, Jerrilyn Heiter, Howard A. Zaren, Stephanie J. Smith, Grant C. Lewis, Lauren Seames, Cheryl Farlow, Judy Miller, Gloria Broadstreet, Anthony Martinez, Micheal Allison, Aniket Mittal, Rafael Ruiz, Aleta Skaanland, Robert Ross, Paul K Mohabir, Connor G O’Brien, Komal Dasani, Neha Gupta, Tracy L Jones, Shonda C Ayers, Amy B Harrell, Brent R Brown, Megan Edwards, Caleb Darby, Kristy Page, Amanda Brown, Jessie McAbee, Katherine A. Belden, Michael Baram, Devin M. Weber, Rosalie DePaola, Yuwei Xia, Hudson Carter, Aaron Tolley, Mary Barletta, Mary Ferranti, Benjamin J Sines, Thomas J Bice, Patrick W. McGonagill, Colette Galet, Janice Hubbard, David Wang, Lauren Allan, Aditya Badheka, Madhuradhar Chegondi, Usman Nazir, Garrett Rampon, Jake Riggle, Nathan Dismang, Roger A. Alvarez, Amarilys Alarcon-Calderon, Marie Anne Sosa, Sunita K. Mahabir, Mausam J. Patel, Dima Dandachi, Hariharan Regunath, Maraya N. Camazine, Grant. E. Geiger, Abdoulie O. Njai, Baraa M. Saad, Renee D. Stapleton, Anne E. Dixon, Olivia Johnson, Sara S. Ardren, Stephanie Burns, Anna Raymond, Erika Gonyaw, Kevin Hodgdon, Chloe Housenger, Benjamin Lin, Karen McQuesten, Heidi Pecott-Grimm, Julie Sweet, Sebastian Ventrone, Ashish K. Khanna, Lynne Harris, Bruce Cusson, Jacob Fowler, David Vaneenenaam, Glen McKinney, Imoh Udoh, Kathleen Johnson, Vishwanath Pattan, Jessica Papke, Ismail Jimada, Nida Mhid, Samuel Chakola, Kevin Sheth, Abdalla Ammar, Mahmoud Ammar, Victor Torres Lopez, Charles Dela Cruz, Akhil Khosla, and Samir Gautam

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

IMPORTANCE:. At the start of the coronavirus disease 2019 pandemic, medications repurposed for management of coronavirus disease 2019 were used in the absence of clinical trial evidence. OBJECTIVES:. To describe the variation and evolution in use of repurposed medications for coronavirus disease 2019. DESIGN, SETTING, AND PARTICIPANTS:. Observational cohort study of adults hospitalized with coronavirus disease 2019 between February 15, 2020, and April 12, 2021, across 76 United States and international hospitals within the Society of Critical Care Medicine’s Discovery Viral Infection and Respiratory Illness Universal Study coronavirus disease 2019 registry. MAIN OUTCOMES AND MEASURES:. Hospital variation was quantified using multivariable adjusted random effects logistic regression models and unsupervised clustering. Repurposed medications included antivirals, corticosteroids, hydroxychloroquine, immunomodulators, and therapeutic dose anticoagulants. RESULTS:. Among 7,069 adults hospitalized with coronavirus disease 2019, 1,979 (28%) received antivirals, 2,876 (41%) received corticosteroids, 1,779 (25%) received hydroxychloroquine, 620 (9%) received immunomodulators, and 2,154 (31%) received therapeutic dose anticoagulants. Contribution of hospital site to risk-adjusted variation was 46% for antivirals, 30% for corticosteroids, 48% for hydroxychloroquine, 46% for immunomodulators, and 52% for therapeutic dose anticoagulants. Compared with the early pandemic, the later pandemic practice phenotypes converged with increased use of antivirals (odds ratio, 3.14; 95% CI, 2.40–4.10) and corticosteroids (odds ratio, 5.43; 95% CI, 4.23–6.97), with decreased use of hydroxychloroquine (odds ratio, 0.02; 95% CI, 0.01–0.04) and immunomodulators (odds ratio, 0.49; 95% CI, 0.34–0.70). There was no clinically significant change in the use of therapeutic dose anticoagulants (odds ratio, 1.01; 95% CI, 1.01–1.02). There were no differences in risk-adjusted mortality between hospitals with high rates of repurposed medication use compared with hospitals with low rates of use. CONCLUSIONS AND RELEVANCE:. Hospital variation in the use of repurposed medications varied widely across hospitals early in the pandemic and later converged with the emergence of randomized clinical trials. Platforms developed for rapid activation and enrollment in clinical trials of repurposed medications are needed prior to the next pandemic to expedite effective, evidence-based practice.

Published
2021
Full Text
View/download PDF

10. Risk Factors for Critical Coronavirus Disease 2019 and Mortality in Hospitalized Young Adults: An Analysis of the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) Coronavirus Disease 2019 Registry

Author

Sandeep Tripathi, MD, MS, Imran A. Sayed, MD, Heda Dapul, MD, Jeremy S. McGarvey, MS, Jennifer A. Bandy, RN, Karen Boman, BS, Vishakha K. Kumar, MD, MBA, Vikas Bansal, MBBS, MPH, Lynn Retford, CAE, Sreekanth Cheruku, MD, MPH, Margit Kaufman, MD, FASA, Smith F. Heavner, MS, RN, Valerie C. Danesh, PhD, RN, Catherine A. St. Hill, DVM, PhD, Ashish K. Khanna, MD, Utpal Bhalala, MD, Rahul Kashyap, MBBS, MBA, Ognjen Gajic, MD, MS, Allan J. Walkey, MD, MS, Katja M. Gist, DO, MSc, for The Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS): COVID-19 Registry Investigator Group, Jean-Baptiste Mesland, Pierre Henin, Hélène Petre, Isabelle Buelens, Anne-Catherine Gerard, Philippe Clevenbergh, Rolando Claure-Del Granado, Jose A. Mercado, Esdenka Vega-Terrazas, Maria F. Iturricha-Caceres, Ruben Garza, Eric Chu, Victoria Chan, Oscar Y Gavidia, Felipe Pachon, Yeimy A Sanchez, Mohamed El Kassas, Mohamed Badr, Ahmed Tawheed, Hend Yahia, Sierra-Hoffman, Fernando Valerio, Oscar Diaz, Jose Luis Ramos Coello, Guillermo Perez, Ana Karen Vallecillo Lizardo, Gabina María Reyes Guillen, Helin Archaga Soto, Mradul Kumar Daga, Munisha Agarwal, Ishan Rohtagi, Anusha Cherian, Sreejith Parameswaran, Magesh Parthiban, Menu Priya A., Girish Vadgaonkar, Rekha Ediga, Shilpa Basety, Shwetha Dammareddy, Phani Sreeharsha Kasumalla, Sridhar Papani, Mahesh Kamuram, Smitha S. Segu, Tuhin Chakraborty, Epcebha Joyce, Umamaheswara Raju, Janaki Manduva, Naresh Kolakani, Shreeja Sripathi, Sheetal Chaitanya, Surapaneni Krishna Mohan, Ekambaram Jyothisree, Kamlesh Kumar Agrawal, Vijendra Baghel, Kirti Kumar Patel, Nooshin Dalili, Mohsen Nafa, Sandeep Tripathi, Yuki Itagaki, Akira Kodate, Reina Suzuki, Yuki Takahashi, Koyo Moriki, Michihito Kyo, Masamitsu Sanui, Sho Horikita, Wataru Matsuda, Shu Tahara, Mineji Hayakawa, Kunihiko Maekawa, Takuya Shiga, Yudai Iwasaki, Abdulrahman AlFares, Rene Rodriguez-Gutierrez, Jose Gerardo Gonzalez-Gonzalez, Alejandro Salcido-Montenegro, Adrian Camacho-Ortiz, Fatimah Hassan-Hanga, Hadiza Galadanci, Abubakar Shehu Gezawa, Halima M. S. Kabara, Taiwo Gboluwaga Amole, Halima Kabir, Dalha Gwarzo, Haliru, Abdullahi S Ibrahim, Muhammad Sohaib Asghar, Mashaal Syed, Syed Anosh Ali Naqvi, Igor Borisovich Zabolotskikh, Konstantin Dmitrievich Zybin, Sergey Vasilevich Sinkov, Tatiana Sergeevna Musaeva, Marwa Ridha Amer, Mohammed Abdullah Bawazeer, Talal I. Dahhan, Eiad Kseibi, Abid Shahzad Butt, Syed Moazzum Khurshid, Muath Rabee, Mohammed Abujazar, Razan Alghunaim, Maal Abualkhair, Abeer Turki AlFirm, Razan K Alamoudi, Hassan M. AlSharif, Sarah A. Almazwaghi, Mohammed S Elsakran, Mohamed A Aid, Mouaz A Darwich, Omnia M Hagag, Salah A Ali, Alona rocacorba, Kathrine Supeña, Efren Ray Juane, Jenalyn Medina, Jowany Baduria, Mohammed A Almazyad, Mohammed I Alarifi, Jara M Macarambon, Ahmad Abdullah Bukhari, Hussain A. Albahrani, Kazi N Asfina, Kaltham M Aldossary, Predrag D Stevanovic, Dejan S Stojakov, Duska K Ignjatovic, Suzana C Bojic, Marina M Bobos, Irina B Nenadic, Milica S Zaric, Marko D Djuric, Vladimir R Djukic, Bojan Kovacevic, Jovana Bojicic, Marija Zdravkovic, Zoran Todorovic, Viseslav Popadic, Slobodan Klasnja, Santiago Y. Teruel, Belen C. Martin, Himat Sulaimonov, Firuza Khudonazarova, Nabi Bakhtibekov, Nekruz Jamshedov, Uluhan Sili, Huseyin Bilgin, Pinar Ay, Varsha P Gharpure, Usman Raheemi, Kenneth W. Dodd, Nicholas Goodmanson, Kathleen Hesse, Paige Bird, Chauncey Weinert, Nathan Schoenrade, Abdulrahman Altaher, Esmael Mayar, Matthew Aronson, Tyler Cooper, Monica Logan, Brianna Miner, Gisele Papo, Eric M. Siegal, Phyllis Runningen, Catherine A. St. Hill, Roman R. Melamed, David M. Tierney, Love A. Patel, Vino S. Raj, Barite U. Dawud, Narayana Mazumder, Abbey Sidebottom, Alena M. Guenther, Benjamin D. Krehbiel, Nova J. Schmitz, Stacy L. Jepsen, Abhijit A Raval, Andrea Franks, Katherine Irby, Ronald C. Sanders, Jr., Glenda Hefley, Anmol Kharbanda, Sunil Jhajhria, Zachary Fyffe, Stephen Capizzi, Bethany Alicie, Martha Green, Lori Crockarell, Amelia Drennan, Kathleen Dubuque, Tonya Fambrough, Nikole Gasaway, Briana Krantz, Peiman Nebi, Jan Orga, Margaret Serfass, Alina Simion, Kimberly Warren, Cassie Wheeler, CJ Woolman, Andrew S. Moyer, George M. Verghese, Andrea Sikora Newsome, Christy C. Forehand, Rebecca Bruning, Timothy W. Jones, Moldovan Sabov, Fatema Zaidi, Fiona Tissavirasingham, Dhatri Malipeddi, Jarrod M Mosier, Karen Lutrick, Beth Salvagio Campbell, Cathleen Wilson, Patrick Rivers, Jonathan Brinks, Mokenge Ndiva Mongoh, Boris Gilson, Donna Lee Armaignac, Don Parris, Maria Pilar Zuniga, Ilea Vargas, Viviana Boronat, Anneka Hutton, Navneet Kaur, Prashank Neupane, Nohemi Sadule-Rios, Lourdes M. Rojas, Aashish Neupane, Priscilla Rivera, Carlos Valle Carlos, Gregory Vincent, Mahesh Amin, Mary E Schelle, Amanda Steadham, Christopher M Howard, Cameron McBride, Jocelyn Abraham, Orlando Garner, Katherine Richards, Keegan Collins, Preethi Antony, Sindhu Mathew, Valerie C. Danesh, Gueorgui Dubrocq, Amber L. Davis, Marissa J Hammers, ill M. McGahey, Amanda C. Farris, Elisa Priest, Robyn Korsmo, Lorie Fares, Kathy Skiles, Susan M. Shor, Kenya Burns, Corrie A Dowell, Melody Flores, Lindsay Newman, Debora A Wilk, Jason Ettlinger, Jaccallene Bomar, Himani Darji, Alejandro Arroliga, Alejandro C Arroliga, Corrie A. Dowell, Gabriela Hope Conzales, Debora A. Wilk, Paras B. Khandhar, Elizabeth Kring, Valerie M. Banner-Goodspeed, Somnath Bose, Lauren E. Kelly, Melisa Joseph, Marie McGourty, Krystal Capers, Benjamin Hoenig, Maria C. Karamourtopoulos, Anica C. Law, Elias N. Baedorf Kassis, Allan J. Walkey, Sushrut S. Waikar, Michael A. Garcia, Mia Colona, Zoe Kibbelaar, Michael Leong, Daniel Wallman, Kanupriya Soni, Jennifer Maccarone, Joshua Gilman, Ycar Devis, Joseph Chung, Munizay Paracha, David N. Lumelsky, Madeline DiLorenzo, Najla Abdurrahman, Shelsey Johnson, Andrew M. Hersh, Stephanie L Wachs, Brittany S. Swigger, Lauren A. Sattler, Michael N. Moulton, Kimberly Zammit, J Patrick, William McGrath, Maya Loeffler, R Chilbert, Aaron S. Miller, Edwin L. Anderson, Rosemary Nagy, Ravali R. Inja, Raghavendra Tirupathi, Alymer Tang, Arshad Safi, Cindy Green, Jackie Newell, Rayan E. Ihle, Shelda A. Martin, Elaine A. Davis, Katja M. Gist, Imran A Sayed, John Brinton, Larisa Strom, Kathleen Chiotos, Allison M. Blatz, Giyoung Lee, Ryan H. Burnett, Guy I. Sydney, Danielle M. Traynor, Karissa Nauert, Annika Gonzalez, Mariel Bagley, Anita Santpurkar, Salim Surani, Joshua White, Aftab Khan, Rahul Dhahwal, Sreekanth Cheruku, Farzin Ahmed, Christopher Deonarine, Ashley Jones, Mohammad-Ali Shaikh, David Preston, Jeanette Chin, Vidula Vachharajani, Abhijit Duggal, Prabalini Rajendram, Omar Mehkri, Siddharth Dugar, Michelle Biehl, Gretchen Sacha, Stuart Houltham, Alexander King, Kiran Ashok, Bryan Poynter, Mary Beukemann, Richard Rice, Susan Gole, Valerie Shaner, Adarsh Conjeevaram, Michelle Ferrari, Narendrakumar Alappan, Steven Minear, Jaime Hernandez-Montfort, Syed Sohaib Nasim, Ravi Sunderkrishnan, Debasis Sahoo, Patrick S. Milligan, Sandeep K. Gupta, Joy M. Koglin, Regina Gibson, Lana Johnson, Felicia Preston, Crimson Scott, Bethany Nungester, Steven K. Daugherty, Sam Atkinson, Kelly Shrimpton, Sidney Ontai, Brian Contreras, Uzoma Obinwanko, Nneka Amamasi, Amir Sharafi, Sarah Lee, Zahia Esber, Chetna Jinjvadia, Kimberly Welker, Francis M. Maguire, Jessica Timmer, Raquel R Bartz, Vijay Krishnamoorthy, Bryan Kraft, Aaron Pulsipher, Eugene Friedman, Sachin Mehta, Margit Kaufman, Gregg Lobel, Nisha Gandhi, Amr Abdelaty, Elizabeth Shaji, Kiana Lim, Juan Marte, Dani Ashley Sosa, David P. Yamane, Ivy Benjenk, Nivedita Prasanna, Smith F. Heavner-Sullivan, Prera J. Roth, Banu Sivaraj, Haley Fulton, Madison G Herin, Marissa Crum, Morgan E. Fretwell, Emily-Rose Zhou, Christine Waller, Kara Kallies, Jonean Thorsen, Alec Fitzsimmons, Haley Olsen, Heda R. Dapul, Sourabh Verma, Alan Salas, Ariel Daube, Michelle Korn, Michelle Ramirez, Logi Rajagopalan, Laura Santos, Orma Smalls, Atul Malhotra, Abdurrahman Husain, Qais Zawaydeh, J.H. Steuernagle, Steven Q. Davis, Valentina Jovic, Max Masuda, Amanda Hayes, Katharine Nault, Michael Smith, William Snow, Riley Liptak, Hannah Durant, Valerie Pendleton, Alay Nanavati, Risa Mrozowsk, LiManoj K Gupta, Franscene E. Oulds, Akshay Nandavar, Yuk Ming Liu, Sarah Zavala, Esther Shim, Ronald A. Reilkoff, Julia A. Heneghan, Sarah Eichen, Lexie Goertzen, Scott Rajala, Ghislaine Feussom, Ben Tang, Christine C. Junia, Robert Lichtenberg, Hasrat Sidhu, Diana Espinoza, Shelden Rodrigues, Maria Jose Zabala, Daniela Goyes, Ammu Susheela, Buddhi Hatharaliyadda, Naveen Rameshkumar, Amulya Kasireddy, Genessis Maldonado, Lisseth Beltran, Akshata Chaugule, Hassan Khan, Namrata Patil, Ruhi Patil, Rodrigo Cartin-Ceba, Ayan Sen, Amanda Palacios, Giyth M. Mahdi, Rahul Kashyap, Ognjen Gajic, Vikas Bansal, Aysun Tekin, Amos Lal, John C. O’Horo, Neha N. Deo, Mayank Sharma, Shahraz Qamar, Cory J. Kudrna, Juan Pablo Domecq Garces, Abigail T. La Nou, Marija Bogojevic, Devang Sanghavi, Pramod Guru, Karthik Gnanapandithan, Hollie Saunders, Zachary Fleissner, Juan Garcia, Alejandra Yu Lee Mateus, Siva Naga Yarrarapu, Syed Anjum Khan, Juan Pablo Domecq, Nitesh Kumar Jain, Thoyaja Koritala, Alexander Bastidas, Gabriela Orellana, Adriana Briceno Bierwirth, Eliana Milazzo, Juan Guillermo Sierra, Thao Dang, Amy B. Christie, Dennis W. Ashley, Rajani Adiga, Rahul S Nanchal, Paul A Bergl, Jennifer L Peterson, Travis Yamanaka, Nicholas A. Barreras, Michael Markos, Anita Fareeduddin, Rohan Mehta, Chakradhar Venkata, Miriam Engemann, Annamarie Mantese, Yasir Tarabichi, Adam Perzynski, Christine Wang, Dhatri Kotekal, Adriana C Briceno Bierwirth, Gabriela M Orellana, Gerardo Catalasan, Shohana Ahmed, Carlos F Matute, Ahmad Hamdan, Ivania Salinas, Genesis Del Nogal, Angel Tejada, Anna Eschler, Mary Hejna, Emily Lewandowski, Kristen Kusmierski, Clare Martin, Jen-Ting Chen, Aluko Hope, Zoe Tsagaris, Elise Ruen, Aram Hambardzumyan, Prithvi Sendi, Meghana Nadiger, Balagangadhar Totapally, Bhagat S. Aulakh, Jennifer A. Bandy, Lisa M. Kreps, Dawn R. Bollinger, Roger Scott Stienecker, Andre G. Melendez, Tressa A. Brunner, Sue M Budzon, Jessica L. Heffernan, Janelle M. Souder, Tracy L. Miller, Andrea G. Maisonneuve, Roberta E. Redfern, Jessica Shoemaker, Jennifer Micham, Lynn Kenney, Gabriel Naimy, Sara Utley, Holly Balcer, Kerry P. J. Pulver, Jennifer Yehle, Alicia Weeks, Terra Inman, Brian L. Delmonaco, Anthony Franklin, Mitchell Heath, Antonia L. Vilella, Sara B. Kutner, Kacie Clark, Danielle Moore, Shina Menon, John K McGuire, Deana Rich, Harry L. Anderson, III, Dixy Rajkumar, Ali Abunayla, Jerrilyn Heiter, Howard A. Zaren, Stephanie J. Smith, Grant C. Lewis, Lauren Seames, Cheryl Farlow, Judy Miller, Gloria Broadstreet, John Lin, Cindy Terrill, Brock Montgomery, Sydney Reyes, Summer Reyes, Alex Plattner, Anthony Martinez, Micheal Allison, Aniket Mittal, Rafael Ruiz, Aleta Skaanland, Robert Ross, Umang Patel, Jordesha Hodge, KrunalKumar Patel, Shivani Dalal, Himanshu Kavani, Sam Joseph, Michael A. Bernstein, Ian K. Goff, Matthew Naftilan, Amal Mathew, Deborah Williams, Sue Murdock, Maryanne Ducey, Kerianne Nelson, Paul K Mohabir, Connor G O’Brien, Komal Dasani, William Marx, Ioana Amzuta, Asad J. Choudhry, Mohammad T. Azam, Kristina L Carter, Michael A Olmos, Brittany M Parker, Julio Quintanilla, Tara A Craig, Brendon J Clough, Jeffrey T Jameson, Neha Gupta, Tracy L Jones, Shonda C Ayers, Amy B Harrell, Dr.Brent R Brown, Utpal S. Bhalala, Joshua Kuehne, Melinda Garcia, Morgan Beebe, Heather Herrera, Chris Fiack, Stephanie Guo, May Vawer, Beth Blackburn, Megan Edwards, Caleb Darby, Kristy Page, Amanda Brown, Jessie McAbee, Katherine A. Belden, Michael Baram, Devin M. Weber, Rosalie DePaola, Yuwei Xia, Hudson Carter, Aaron Tolley, Mark Steele, Laurie Kemble, Joshua L. Denson, A. Scott Gillet, Margo Brown, Rachael Stevens, Andrew Wetherbie, Kevin Tea, Mathew Moore, Benjamin J Sines, Thomas J Bice, Emily A. Vail, Susannah Nicholson, Rachelle B. Jonas, AnnaRose E. Dement, William Tang, Mark DeRosa, Robert E. Villarreal, Rajany V. Dy, Alfredo Iardino, Jill Sharma, Richard Czieki, Julia Christopher, Ryan Lacey, Marwan Mashina, Kushal Patel, Erica C. Bjornstad, Nancy M. Tofil, Scott House, Isabella Aldana, Nikhil K. Meena, Jose D. Caceres, Nikhil K Meena, Sarenthia M. Epps, Harmeen Goraya, Kelsey R. Besett, Ryan James, Lana Y. Abusalem, Akash K. Patel, Lana S Hasan, Dina Gomaa, Michael Goodman, Devin Wakefield, Anthony Spuzzillo, John O. Shinn, II, Azra Bihorac, Tezcan Ozrazgat Baslanti, George Omalay, Haleh Hashemighouchani, Julie S. Cupka, Matthew M Ruppert, Patrick W. McGonagill, Colette Galet, Janice Hubbard, David Wang, Lauren Allan, Aditya Badheka, Madhuradhar Chegondi, Usman Nazir, Garrett Rampon, Jake Riggle, Nathan Dismang, Vicki Montgomery, Janice Sullivan, Sarah Morris, Jennifer Nason, Roger A. Alvarez, Amarilys Alarcon-Calderon, Marie Anne Sosa, Sunita K. Mahabir, Mausam J. Patel, Pauline Park, Andrew Admon, Sinan Hanna, Rishi Chanderraj, Maria Pliakas, Ann Wolski, Jennifer Cirino, Dima Dandachi, Hariharan Regunath, Maraya N. Camazine, Grant. E. Geiger, Abdoulie O. Njai, Baraa M. Saad, Faraaz Ali Shah, Byron Chuan, Sagar L. Rawal, Manal Piracha, Joseph E. Tonna, Nicholas M. Levin, Kayte Suslavich, Rachel Tsolinas, Zachary T. Fica, Chloe R. Skidmore, Renee D. Stapleton, Anne E. Dixon, Olivia Johnson, Sara S. Ardren, Stephanie Burns, Anna Raymond, Erika Gonyaw, Kevin Hodgdon, Chloe Housenger, Benjamin Lin, Karen McQuesten, Heidi Pecott-Grimm, Julie Sweet, Sebastian Ventrone, Nita Khandelwal, T. Eoin West, Ellen S. Caldwell, Lara Lovelace-Macon, Navya Garimella, Denisse B. Dow, Murtaza Akhter, Rania Abdul Rahman, Mary Mulrow, Erin M. Wilfong, Kelsi Vela, Ashish K. Khanna, Lynne Harris, Bruce Cusson, Jacob Fowler, David Vaneenenaam, Glen McKinney, Imoh Udoh, Kathleen Johnson, Patrick G. Lyons, Andrew P Michelson, Sara S. Haluf, Lauren M. Lynch, Nguyet M. Nguyen, Aaron Steinberg, Nicholas Braus, Vishwanath Pattan, Jessica Papke, Ismail Jimada, Nida Mhid, and Samuel Chakola

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

IMPORTANCE:. Even with its proclivity for older age, coronavirus disease 2019 has been shown to affect all age groups. However, there remains a lack of research focused primarily on the young adult population. OBJECTIVES:. To describe the epidemiology and outcomes of coronavirus disease 2019 and identify the risk factors associated with critical illness and mortality in hospitalized young adults. DESIGN, SETTINGS, AND PARTICIPANTS:. A retrospective cohort study of the Society of Critical Care Medicine’s Viral Infection and Respiratory Illness Universal Study registry. Patients 18–40 years old, hospitalized from coronavirus disease 2019 from March 2020 to April 2021, were included in the analysis. MAIN OUTCOMES AND MEASURES:. Critical illness was defined as a composite of mortality and 21 predefined interventions and complications. Multivariable logistic regression was used to assess associations with critical illness and mortality. RESULTS:. Data from 4,005 patients (152 centers, 19 countries, 18.6% non-U.S. patients) were analyzed. The median age was 32 years (interquartile range, 27–37 yr); 51% were female, 29.4% Hispanic, and 42.9% had obesity. Most patients (63.2%) had comorbidities, the most common being hypertension (14.5%) and diabetes (13.7%). Hospital and ICU mortality were 3.2% (129/4,005) and 8.3% (109/1,313), respectively. Critical illness occurred in 25% (n = 996), and 34.3% (n = 1,376) were admitted to the ICU. Older age (p = 0.03), male sex (adjusted odds ratio, 1.83 [95% CI, 1.2–2.6]), and obesity (adjusted odds ratio, 1.6 [95% CI, 1.1–2.4]) were associated with hospital mortality. In addition to the above factors, the presence of any comorbidity was associated with critical illness from coronavirus disease 2019. Multiple sensitivity analyses, including analysis with U.S. patients only and patients admitted to high-volume sites, showed similar risk factors. CONCLUSIONS:. Among hospitalized young adults, obese males with comorbidities are at higher risk of developing critical illness or dying from coronavirus disease 2019.

Published
2021
Full Text
View/download PDF

11. A Qualitative Review of Barriers and Facilitators Identified While Implementing the Native Students Together against Negative Decisions Curriculum in a Multisite Dissemination and Implementation Study

Author

Caitlin Donald, Kavita Rajani, Michelle Singer, Megan Skye, Stephanie Craig Rushing, Allyson Kelley, Brittany Morgan, Tosha Zaback, Thomas Becker, and William Lambert

Abstract

Culturally-adapted evidence-based programs (EBPs) are needed to promote healthy behaviors among Native teens and young adults. Little is known about the facilitators and barriers of implementing and sustaining EBPs in Native communities. This paper aims to identify those factors described by educators who implemented the Native Students Together Against Negative Decisions (STAND) curriculum. Methods: We conducted qualitative, semi-structured interviews with 44 Native STAND educators from 48 sites throughout the United States. We used a modified grounded theory approach to explore barriers, facilitators, and sustainability factors related to implementing Native STAND. Results: We learned that disruptions to staffing, coordination, and organizational factors were the most common barriers. Factors that improved implementation success included: tailoring the program to local needs/constraints, having a supportive Project Manager, improved fidelity due to check-in calls, and participation in summer training. Factors that improved sustainability included: access to needed infrastructure, administrative support, community support, and student interest. Discussion: The delivery of Native STAND was further improved by person-to-person communication and resource sharing across sites. Sustaining EBPs in AI/AN settings requires culturally-tailored technical assistance, sufficient implementation funds for materials and staffing, and a community of peer educators to inspire forward progress. Conclusion: EBPs that reflect the needs and experiences of American Indian and Alaska Native (AI/AN) youth are necessary to address systemic inequities in adolescent health outcomes. The Native STAND Dissemination and Implementation study is among the first to assess facilitators and barriers to program delivery in diverse AI/AN settings.

Published
2024
Full Text
View/download PDF

12. Goal-conditioned reinforcement learning for ultrasound navigation guidance

Author

Amadou, Abdoul Aziz, Singh, Vivek, Ghesu, Florin C., Kim, Young-Ho, Stanciulescu, Laura, Sai, Harshitha P., Sharma, Puneet, Young, Alistair, Rajani, Ronak, and Rhode, Kawal

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, I.4.0, I.5.0
Abstract

Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures. However, using it effectively requires extensive training due to the intricate nature of image acquisition and interpretation. To enhance the efficiency of novice sonographers and reduce variability in scan acquisitions, we propose a novel ultrasound (US) navigation assistance method based on contrastive learning as goal-conditioned reinforcement learning (GCRL). We augment the previous framework using a novel contrastive patient batching method (CPB) and a data-augmented contrastive loss, both of which we demonstrate are essential to ensure generalization to anatomical variations across patients. The proposed framework enables navigation to both standard diagnostic as well as intricate interventional views with a single model. Our method was developed with a large dataset of 789 patients and obtained an average error of 6.56 mm in position and 9.36 degrees in angle on a testing dataset of 140 patients, which is competitive or superior to models trained on individual views. Furthermore, we quantitatively validate our method's ability to navigate to interventional views such as the Left Atrial Appendage (LAA) view used in LAA closure. Our approach holds promise in providing valuable guidance during transesophageal ultrasound examinations, contributing to the advancement of skill acquisition for cardiac ultrasound practitioners., Comment: Accepted in MICCAI 2024; 11 pages, 3 figures

Published
2024

23. Cardiac ultrasound simulation for autonomous ultrasound navigation

Author

Amadou, Abdoul Aziz, Peralta, Laura, Dryburgh, Paul, Klein, Paul, Petkov, Kaloian, Housden, Richard James, Singh, Vivek, Liao, Rui, Kim, Young-Ho, Ghesu, Florin Christian, Mansi, Tommaso, Rajani, Ronak, Young, Alistair, and Rhode, Kawal

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, I.6.0, I.5.4, J.3
Abstract

Ultrasound is well-established as an imaging modality for diagnostic and interventional purposes. However, the image quality varies with operator skills as acquiring and interpreting ultrasound images requires extensive training due to the imaging artefacts, the range of acquisition parameters and the variability of patient anatomies. Automating the image acquisition task could improve acquisition reproducibility and quality but training such an algorithm requires large amounts of navigation data, not saved in routine examinations. Thus, we propose a method to generate large amounts of ultrasound images from other modalities and from arbitrary positions, such that this pipeline can later be used by learning algorithms for navigation. We present a novel simulation pipeline which uses segmentations from other modalities, an optimized volumetric data representation and GPU-accelerated Monte Carlo path tracing to generate view-dependent and patient-specific ultrasound images. We extensively validate the correctness of our pipeline with a phantom experiment, where structures' sizes, contrast and speckle noise properties are assessed. Furthermore, we demonstrate its usability to train neural networks for navigation in an echocardiography view classification experiment by generating synthetic images from more than 1000 patients. Networks pre-trained with our simulations achieve significantly superior performance in settings where large real datasets are not available, especially for under-represented classes. The proposed approach allows for fast and accurate patient-specific ultrasound image generation, and its usability for training networks for navigation-related tasks is demonstrated., Comment: 24 pages, 10 figures, 5 tables

Published
2024

24. What's documented in AI? Systematic Analysis of 32K AI Model Cards

Author

Liang, Weixin, Rajani, Nazneen, Yang, Xinyu, Ozoani, Ezinwanne, Wu, Eric, Chen, Yiqun, Smith, Daniel Scott, and Zou, James

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The rapid proliferation of AI models has underscored the importance of thorough documentation, as it enables users to understand, trust, and effectively utilize these models in various applications. Although developers are encouraged to produce model cards, it's not clear how much information or what information these cards contain. In this study, we conduct a comprehensive analysis of 32,111 AI model documentations on Hugging Face, a leading platform for distributing and deploying AI models. Our investigation sheds light on the prevailing model card documentation practices. Most of the AI models with substantial downloads provide model cards, though the cards have uneven informativeness. We find that sections addressing environmental impact, limitations, and evaluation exhibit the lowest filled-out rates, while the training section is the most consistently filled-out. We analyze the content of each section to characterize practitioners' priorities. Interestingly, there are substantial discussions of data, sometimes with equal or even greater emphasis than the model itself. To evaluate the impact of model cards, we conducted an intervention study by adding detailed model cards to 42 popular models which had no or sparse model cards previously. We find that adding model cards is moderately correlated with an increase weekly download rates. Our study opens up a new perspective for analyzing community norms and practices for model documentation through large-scale data science and linguistics analysis.

Published
2024

25. Biological effects of corticosteroids on pneumococcal pneumonia in Mice-translational significance.

Author

Taenaka, Hiroki, Wick, Katherine, Sarma, Aartik, Matsumoto, Shotaro, Ghale, Rajani, Fang, Xiaohui, Maishan, Mazharul, Gotts, Jeffrey, Langelier, Charles, Calfee, Carolyn, and Matthay, Michael

Subjects
Acute respiratory distress syndrome, Glucocorticoids, Pneumonia, Streptococcal infections, Animals, Pneumonia, Pneumococcal, Mice, Disease Models, Animal, Adrenal Cortex Hormones, Humans, Dexamethasone, Female, Male, Streptococcus pneumoniae
Abstract

BACKGROUND: Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The primary objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in a mouse model. A secondary objective was to identify shared transcriptomic features of pneumococcal pneumonia and steroid treatment in the mouse model and clinical samples. METHODS: We carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy. We also studied lower respiratory tract gene expression from a cohort of 15 mechanically ventilated patients (10 with Streptococcus pneumoniae and 5 controls) to compare with the transcriptional studies in the mice. RESULTS: In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden. Transcriptomic analyses identified effects of steroid therapy in mice that were also observed in the clinical samples. CONCLUSIONS: In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The transcriptional studies in patients suggest that the mouse model replicates some of the features of pneumonia in patients with Streptococcus pneumoniae and steroid treatment. Overall, these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Published
2024

26. Hippocampal hyperphosphorylated tau-induced deficiency is rescued by L-type calcium channel blockade

Author

Crossley, Chelsea A, Omoluabi, Tamunotonye, Torraville, Sarah E, Duraid, Sarah, Maziar, Aida, Hasan, Zia, Rajani, Vishaal, Ando, Kanae, Hell, Johannes W, and Yuan, Qi

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Acquired Cognitive Impairment, Aging, Brain Disorders, Dementia, Alzheimer's Disease, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurological, tau, hippocampus, Alzheimer's disease, spatial learning, L-type calcium channel, Alzheimer’s disease, Clinical sciences, Biological psychology
Abstract

Aging and Alzheimer's disease are associated with chronic elevations in neuronal calcium influx via L-type calcium channels. The hippocampus, a primary memory encoding structure in the brain, is more vulnerable to calcium dysregulation in Alzheimer's disease. Recent research has suggested a link between L-type calcium channels and tau hyperphosphorylation. However, the precise mechanism of L-type calcium channel-mediated tau toxicity is not understood. In this study, we seeded a human tau pseudophosphorylated at 14 amino acid sites in rat hippocampal cornu ammonis 1 region to mimic soluble pretangle tau. Impaired spatial learning was observed in human tau pseudophosphorylated at 14 amino acid sites-infused rats as early as 1-3 months and worsened at 9-10 months post-infusion. Rats infused with wild-type human tau exhibited milder behavioural deficiency only at 9-10 months post-infusion. No tangles or plaques were observed in all time points examined in both human tau pseudophosphorylated at 14 amino acid sites and human tau-infused brains. However, human tau pseudophosphorylated at 14 amino acid sites-infused hippocampus exhibited a higher amount of tau phosphorylation at S262 and S356 than the human tau-infused rats at 3 months post-infusion, paralleling the behavioural deficiency observed in human tau pseudophosphorylated at 14 amino acid sites-infused rats. Neuroinflammation indexed by increased Iba1 in the cornu ammonis 1 was observed in human tau pseudophosphorylated at 14 amino acid sites-infused rats at 1-3 but not 9 months post-infusion. Spatial learning deficiency in human tau pseudophosphorylated at 14 amino acid sites-infused rats at 1-3 months post-infusion was paralleled by decreased neuronal excitability, impaired NMDA receptor-dependent long-term potentiation and augmented L-type calcium channel-dependent long-term potentiation at the cornu ammonis 1 synapses. L-type calcium channel expression was elevated in the soma of the cornu ammonis 1 neurons in human tau pseudophosphorylated at 14 amino acid sites-infused rats. Chronic L-type calcium channel blockade with nimodipine injections for 6 weeks normalized neuronal excitability and synaptic plasticity and rescued spatial learning deficiency in human tau pseudophosphorylated at 14 amino acid sites-infused rats. The early onset of L-type calcium channel-mediated pretangle tau pathology and rectification by nimodipine in our model have significant implications for preclinical Alzheimer's disease prevention and intervention.

Published
2024

27. Laboratory Experiments of Model-based Reinforcement Learning for Adaptive Optics Control

Author

Nousiainen, Jalo, Engler, Byron, Kasper, Markus, Rajani, Chang, Helin, Tapio, Heritier, Cédric T., Quanz, Sascha P., and Glauser, Adrian M.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, Computer Science - Robotics
Abstract

Direct imaging of Earth-like exoplanets is one of the most prominent scientific drivers of the next generation of ground-based telescopes. Typically, Earth-like exoplanets are located at small angular separations from their host stars, making their detection difficult. Consequently, the adaptive optics (AO) system's control algorithm must be carefully designed to distinguish the exoplanet from the residual light produced by the host star. A new promising avenue of research to improve AO control builds on data-driven control methods such as Reinforcement Learning (RL). RL is an active branch of the machine learning research field, where control of a system is learned through interaction with the environment. Thus, RL can be seen as an automated approach to AO control, where its usage is entirely a turnkey operation. In particular, model-based reinforcement learning (MBRL) has been shown to cope with both temporal and misregistration errors. Similarly, it has been demonstrated to adapt to non-linear wavefront sensing while being efficient in training and execution. In this work, we implement and adapt an RL method called Policy Optimization for AO (PO4AO) to the GHOST test bench at ESO headquarters, where we demonstrate a strong performance of the method in a laboratory environment. Our implementation allows the training to be performed parallel to inference, which is crucial for on-sky operation. In particular, we study the predictive and self-calibrating aspects of the method. The new implementation on GHOST running PyTorch introduces only around 700 microseconds in addition to hardware, pipeline, and Python interface latency. We open-source well-documented code for the implementation and specify the requirements for the RTC pipeline. We also discuss the important hyperparameters of the method, the source of the latency, and the possible paths for a lower latency implementation., Comment: Accepted for publication in JATIS

Published
2023

28. Harnessing landrace diversity empowers wheat breeding

Author

Cheng, Shifeng, Feng, Cong, Wingen, Luzie U., Cheng, Hong, Riche, Andrew B., Jiang, Mei, Leverington-Waite, Michelle, Huang, Zejian, Collier, Sarah, Orford, Simon, Wang, Xiaoming, Awal, Rajani, Barker, Gary, O’Hara, Tom, Lister, Clare, Siluveru, Ajay, Quiroz-Chávez, Jesús, Ramírez-González, Ricardo H., Bryant, Ruth, Berry, Simon, Bansal, Urmil, Bariana, Harbans S., Bennett, Malcolm J., Bicego, Breno, Bilham, Lorelei, Brown, James K. M., Burridge, Amanda, Burt, Chris, Buurman, Milika, Castle, March, Chartrain, Laetitia, Chen, Baizhi, Denbel, Worku, Elkot, Ahmed F., Fenwick, Paul, Feuerhelm, David, Foulkes, John, Gaju, Oorbessy, Gauley, Adam, Gaurav, Kumar, Hafeez, Amber N., Han, Ruirui, Horler, Richard, Hou, Junliang, Iqbal, Muhammad S., Kerton, Matthew, Kondic-Spica, Ankica, Kowalski, Ania, Lage, Jacob, Li, Xiaolong, Liu, Hongbing, Liu, Shiyan, Lovegrove, Alison, Ma, Lingling, Mumford, Cathy, Parmar, Saroj, Philp, Charlie, Playford, Darryl, Przewieslik-Allen, Alexandra M., Sarfraz, Zareen, Schafer, David, Shewry, Peter R., Shi, Yan, Slafer, Gustavo A., Song, Baoxing, Song, Bo, Steele, David, Steuernagel, Burkhard, Tailby, Phillip, Tyrrell, Simon, Waheed, Abdul, Wamalwa, Mercy N., Wang, Xingwei, Wei, Yanping, Winfield, Mark, Wu, Shishi, Wu, Yubing, Wulff, Brande B. H., Xian, Wenfei, Xu, Yawen, Xu, Yunfeng, Yuan, Quan, Zhang, Xin, Edwards, Keith J., Dixon, Laura, Nicholson, Paul, Chayut, Noam, Hawkesford, Malcolm J., Uauy, Cristobal, Sanders, Dale, Huang, Sanwen, and Griffiths, Simon

Published
2024
Full Text
View/download PDF

35. Zephyr: Direct Distillation of LM Alignment

Author

Tunstall, Lewis, Beeching, Edward, Lambert, Nathan, Rajani, Nazneen, Rasul, Kashif, Belkada, Younes, Huang, Shengyi, von Werra, Leandro, Fourrier, Clémentine, Habib, Nathan, Sarrazin, Nathan, Sanseviero, Omar, Rush, Alexander M., and Wolf, Thomas

Subjects
Computer Science - Machine Learning, Computer Science - Computation and Language
Abstract

We aim to produce a smaller language model that is aligned to user intent. Previous research has shown that applying distilled supervised fine-tuning (dSFT) on larger models significantly improves task accuracy; however, these models are unaligned, i.e. they do not respond well to natural prompts. To distill this property, we experiment with the use of preference data from AI Feedback (AIF). Starting from a dataset of outputs ranked by a teacher model, we apply distilled direct preference optimization (dDPO) to learn a chat model with significantly improved intent alignment. The approach requires only a few hours of training without any additional sampling during fine-tuning. The final result, Zephyr-7B, sets the state-of-the-art on chat benchmarks for 7B parameter models, and requires no human annotation. In particular, results on MT-Bench show that Zephyr-7B surpasses Llama2-Chat-70B, the best open-access RLHF-based model. Code, models, data, and tutorials for the system are available at https://github.com/huggingface/alignment-handbook.

Published
2023

36. Bifractal behavior of Solar supergranulation and magnetic activity

Author

Rajani, G., Sowmya, G. M., Paniveni, U., and Srikanth, R.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

We study the complexity and scale of the supergranular network across the 23rd solar cycle, using the Ca II K digitized intensitygrams from the Kodaikanal Solar Observatory (KSO). Enhancing our previous data and refining our data analysis, we study supergranular fractal dimension as a function of cell size. We find that across the cycle phases, the cells show a bifractal behavior, with approximately half the larger cells in the studied scale range showing a slightly greater fractal dimension than the smaller cells. We also study the discrepancy between supergranular scale as determined by direct inspection methods (around 17 Mm) and autocorrelation (around 30 Mm), and attribute this to a preferential selection of well defined cells in the former case., Comment: 10 pages, 2 figures; Accepted for publication in Acta Astron

Published
2023

37. Dependence of Solar supergranular lifetime on surface magnetic activity and rotation

Author

M., Sowmya G., G., Rajani, Paniveni, U., and Srikanth, R.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

The lifetimes and length-scales for supergranular cells in active and quiescent regions of the Solar chromosphere, and the relation between the two, were studied using a time series of Ca II K filtergrams. The lifetimes, in contrast to supergranular length scale and fractal dimension, show no significant dependence on Solar latitude, suggesting that cell lifetimes are independent of the differential rotation and a possible supergranular super-rotation. The functional form of the relation was obtained guided by a comparison of the distributions of the two supergranular parameters. We infer a linear dependence of cell lifetime on area, which can be understood by the assumption of the network's evolution via a diffusion of the magnetic field. Our analysis suggests that the diffusion rate in quiet regions is about 10% greater than in active regions., Comment: 15 pages, 10 figures; Accepted for publication in the Astrophysical Bulletin

Published
2023

38. Improving patient retention of medical information: lessons from the contact dermatitis clinic

Author

Li-Wang, Jennifer and Katta, Rajani

Subjects
communication, counseling, dermatitis, retention
Abstract

Medical communication skills are widely recognized as important, especially for situations in which providers must present complex and detailed information. Although much research focuses on how providers can improve their delivery of medical information, an equally important part of communication is supporting patient retention of the information. We present several methods to improve patient retention of medical information that we have found successful in an allergic contact dermatitis clinic. Some recommendations address information transfer (follow effective structure, teach to different learning styles, provide written instructions, employ the teach-back method). Other methods are effective, focusing on the patient's emotional, social, and relational needs (include storytelling, metaphor, and analogy, allay negative emotions, listen deeply/know your patient). This list is not exhaustive, but we have found these methods effective when counseling patients with allergic contact dermatitis. Patient retention of medical information is an important part of effective health care, benefits both the provider and the patient, and is applicable to every medical practice.

Published
2024

40. Challenging University Complicity and Majoritarian Narratives: Counter-Storytelling from Black Working-Class Students

Author

Mukovhe Masutha, Rajani Naidoo, and Jürgen Enders

Abstract

Low completion rates amongst students from Black working-class backgrounds remain a persistent challenge to post-apartheid university transformation in South Africa. Notions of universities as colour-blind, meritocratic, and post-racial have developed around a deficit and victim-blaming majoritarian narrative that individualises educational under-achievement, blaming victims and downplaying the complicity of universities in reproducing inequity. This article analyses the narratives of a group of Black working-class students, and academics on their in-depth experiences of educational success and failure in post-apartheid South African universities. Counter-storytelling is employed to foreground and promote the voice and lived experiences of those who often go unheard; and to highlight their narratives as valuable and critical in understanding persistent inequity in higher education. This article looks beyond the fixation on what students from marginalised communities are perceived to lack to reassert a place for institutional context in studying their experiences, to minimise the de-contextualisation of such experiences; and to illuminate areas of universities' complicity in reproducing untenable educational experiences and outcomes for those already in the margins. Participants' counter-stories are presented to deepen our understanding and theorisation of Black working-class students' lived experiences in a manner that enriches the work of researchers, policy makers and practitioners.

Published
2024
Full Text
View/download PDF

41. Treatment of Insomnia by Pranic Healing

Author

RAJANI AITHAL, SRIKANTH NAGARAJA JOIS, and PRABHU PRASAD MAHADEVAIAH

Subjects
complementary therapy, prana, sleep, wellbeing, Medicine
Abstract

Insomnia is a sleep disorder where people have trouble sleeping. This case pertains to a working, married female, aged 27 years with insomnia, complaining of irritability, low energy, daytime sleepiness and depressed mood. Pranic Healing (PH) is a natural healing technique that uses prana to treat illness. It is a non-touch, drugless, complementary therapy that corrects imbalances in the body’s energy field. Insomnia was measured using the Athens Insomnia Scale (AIS). On self-assessment before PH, AIS score was 16, indicating insomnia condition in the subject. A total of six pranic healing sessions, of 20 minutes each were applied on the subject. After six PH sessions AIS score was two, indicating a normal sleeping pattern. During the healing sessions, the subject expressed unique experiences of tingling sensation in hands, heavy energy moving out of the body and lightness of the body. At the end of the healing process, the subject experienced a sense of calmness, well-being and being energetic.

Published
2018
Full Text
View/download PDF

42. Role of Thrombopoietin in the Diagnosis of Ovarian Cancer: A Brief Review

Author

Amar Ranjan, Rajani Anand, Iffat Jamal, Amrendra Kumar, and Ritesh Kumar

Subjects
cancer antigen 125, ovarian tumour, platelets, Medicine
Abstract

Ovarian Cancer (OC) is the most fatal condition among all gynaecologic malignancies. The survival rate of early and advance stage of OC is 80-90% and 15-20% respectively. This data constitutes the need of a novel biomarker for early diagnosis, which may distinguish malignant tumours from benign ovarian cysts. Presently in practice there are three screening techniques: bimanual pelvic examination, serum Cancer Antigen (CA) 125 and transvaginal ultrasound. Bimanual pelvic examination can detect only 1 in 10,000 ovarian cancers in women presenting to the clinic. CA 125 is raised in 80% of cases of ovarian carcinoma; however, if the carcinoma is limited to ovary, the raised value is seen only in 50% of women. It is mainly useful in postmenopausal women. Ultrasonography also lacks specificity and sensitivity, apart from being costly as a screening test. Studies are going on for search of a biomarker, which may complement CA 125. Most common among these are Human Epididymis Protein 4 (HE4), Thrombopoietin (TPO), CA19-9, human kallikrein 10, human kallikrein 6, osteopontin, claudin 3, DF3 (murine monoclonal antibody), vascular endothelial growth factor, MUC1, mesothelin etc. In 2008, FDA approved the use of HE4 assay for monitoring of progressive disease in patients with epithelial ovarian cancer. Similarly TPO also holds the promise of being a biomarker to complement CA125 and many studies are indeed available to support the association of TPO and OC. In this review article we have summarised and analysed such studies.

Published
2018
Full Text
View/download PDF

44. Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices

Author

Rajani, Samir, Dematties, Dario, Hudson, Nathaniel, Chard, Kyle, Ferrier, Nicola, Sankaran, Rajesh, and Beckman, Peter

Subjects
Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Federated learning (FL) is increasingly becoming the default approach for training machine learning models across decentralized Internet-of-Things (IoT) devices. A key advantage of FL is that no raw data are communicated across the network, providing an immediate layer of privacy. Despite this, recent works have demonstrated that data reconstruction can be done with the locally trained model updates which are communicated across the network. However, many of these works have limitations with regard to how the gradients are computed in backpropagation. In this work, we demonstrate that the model weights shared in FL can expose revealing information about the local data distributions of IoT devices. This leakage could expose sensitive information to malicious actors in a distributed system. We further discuss results which show that injecting noise into model weights is ineffective at preventing data leakage without seriously harming the global model accuracy., Comment: 6 pages, 6 figures, accepted for publication through 2023 IEEE World Forum on Internet of Things

Published
2023

45. Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings

Author

Shoker, Sarah, Reddie, Andrew, Barrington, Sarah, Booth, Ruby, Brundage, Miles, Chahal, Husanjot, Depp, Michael, Drexel, Bill, Gupta, Ritwik, Favaro, Marina, Hecla, Jake, Hickey, Alan, Konaev, Margarita, Kumar, Kirthi, Lambert, Nathan, Lohn, Andrew, O'Keefe, Cullen, Rajani, Nazneen, Sellitto, Michael, Trager, Robert, Walker, Leah, Wehsener, Alexa, and Young, Jessica

Subjects
Computer Science - Computers and Society
Abstract

Foundation models could eventually introduce several pathways for undermining state security: accidents, inadvertent escalation, unintentional conflict, the proliferation of weapons, and the interference with human diplomacy are just a few on a long list. The Confidence-Building Measures for Artificial Intelligence workshop hosted by the Geopolitics Team at OpenAI and the Berkeley Risk and Security Lab at the University of California brought together a multistakeholder group to think through the tools and strategies to mitigate the potential risks introduced by foundation models to international security. Originating in the Cold War, confidence-building measures (CBMs) are actions that reduce hostility, prevent conflict escalation, and improve trust between parties. The flexibility of CBMs make them a key instrument for navigating the rapid changes in the foundation model landscape. Participants identified the following CBMs that directly apply to foundation models and which are further explained in this conference proceedings: 1. crisis hotlines 2. incident sharing 3. model, transparency, and system cards 4. content provenance and watermarks 5. collaborative red teaming and table-top exercises and 6. dataset and evaluation sharing. Because most foundation model developers are non-government entities, many CBMs will need to involve a wider stakeholder community. These measures can be implemented either by AI labs or by relevant government actors.

Published
2023

46. Clinical characteristics, racial inequities, and outcomes in patients with breast cancer and COVID-19: A COVID-19 and cancer consortium (CCC19) cohort study

Author

Nagaraj, Gayathri, Vinayak, Shaveta, Khaki, Ali Raza, Sun, Tianyi, Kuderer, Nicole M, Aboulafia, David M, Acoba, Jared D, Awosika, Joy, Bakouny, Ziad, Balmaceda, Nicole B, Bao, Ting, Bashir, Babar, Berg, Stephanie, Bilen, Mehmet A, Bindal, Poorva, Blau, Sibel, Bodin, Brianne E, Borno, Hala T, Castellano, Cecilia, Choi, Horyun, Deeken, John, Desai, Aakash, Edwin, Natasha, Feldman, Lawrence E, Flora, Daniel B, Friese, Christopher R, Galsky, Matthew D, Gonzalez, Cyndi J, Grivas, Petros, Gupta, Shilpa, Haynam, Marcy, Heilman, Hannah, Hershman, Dawn L, Hwang, Clara, Jani, Chinmay, Jhawar, Sachin R, Joshi, Monika, Kaklamani, Virginia, Klein, Elizabeth J, Knox, Natalie, Koshkin, Vadim S, Kulkarni, Amit A, Kwon, Daniel H, Labaki, Chris, Lammers, Philip E, Lathrop, Kate I, Lewis, Mark A, Li, Xuanyi, de Lima Lopes, Gilbert, Lyman, Gary H, Makower, Della F, Mansoor, Abdul-Hai, Markham, Merry-Jennifer, Mashru, Sandeep H, McKay, Rana R, Messing, Ian, Mico, Vasil, Nadkarni, Rajani, Namburi, Swathi, Nguyen, Ryan H, Nonato, Taylor Kristian, O'Connor, Tracey Lynn, Panagiotou, Orestis A, Park, Kyu, Patel, Jaymin M, Patel, Kanishka GopikaBimal, Peppercorn, Jeffrey, Polimera, Hyma, Puc, Matthew, Rao, Yuan James, Razavi, Pedram, Reid, Sonya A, Riess, Jonathan W, Rivera, Donna R, Robson, Mark, Rose, Suzanne J, Russ, Atlantis D, Schapira, Lidia, Shah, Pankil K, Shanahan, M Kelly, Shapiro, Lauren C, Smits, Melissa, Stover, Daniel G, Streckfuss, Mitrianna, Tachiki, Lisa, Thompson, Michael A, Tolaney, Sara M, Weissmann, Lisa B, Wilson, Grace, Wotman, Michael T, Wulff-Burchfield, Elizabeth M, Mishra, Sanjay, French, Benjamin, Warner, Jeremy L, Lustberg, Maryam B, Accordino, Melissa K, and Shah, Dimpy P

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Clinical Research, Cancer, Infectious Diseases, Women's Health, Coronaviruses, Lung, Emerging Infectious Diseases, Breast Cancer, Good Health and Well Being, United States, Humans, Female, Middle Aged, COVID-19, SARS-CoV-2, Cohort Studies, Breast Neoplasms, Retrospective Studies, COVID-19 and Cancer Consortium, breast cancer, epidemiology, global health, human, oncology, pandemic, racial inequities, Biochemistry and Cell Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundLimited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations.MethodsThis is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity.Results1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status.ConclusionsUsing one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients.FundingThis study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication.Clinical trial numberCCC19 registry is registered on ClinicalTrials.gov, NCT04354701.

Published
2023

47. A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling

Author

Hackney, Jason A, Shivram, Haridha, Vander Heiden, Jason, Overall, Chris, Orozco, Luz, Gao, Xia, Kim, Eugene, West, Nathan, Qamra, Aditi, Chang, Diana, Chakrabarti, Arindam, Choy, David F, Combes, Alexis J, Courau, Tristan, Fragiadakis, Gabriela K, Rao, Arjun Arkal, Ray, Arja, Tsui, Jessica, Hu, Kenneth, Kuhn, Nicholas F, Krummel, Matthew F, Erle, David J, Kangelaris, Kirsten, Sarma, Aartik, Lyon, Zoe, Calfee, Carolyn S, Woodruff, Prescott G, Ghale, Rajani, Mick, Eran, Byrne, Ashley, Zha, Beth Shoshana, Langelier, Charles, Hendrickson, Carolyn M, van der Wijst, Monique GP, Hartoularos, George C, Grant, Tianna, Bueno, Raymund, Lee, David S, Greenland, John R, Sun, Yang, Perez, Richard, Ogorodnikov, Anton, Ward, Alyssa, Ye, Chun Jimmie, Consortium, UCSF COMET, Abe-Jones, Yumiko, Adkisson, Michael, Ansel, K Mark, Asthana, Saurabh, Beagle, Alexander, Bhide, Sharvari, Cai, Cathy, Caldera, Saharai, Calvo, Maria, Carrillo, Sidney A, Chak, Suzanna, Christenson, Stephanie, Collins, Zachary, Darmanis, Spyros, Detweiler, Angela, DeVoe, Catherine, Eckalbar, Walter, Giberson, Jeremy, Gonzalez, Ana, Gordon, Gracie, Serpa, Paula Hayakawa, Jauregui, Alejandra, Jones, Chayse, Ke, Serena, Kushnoor, Divya, Lea, Tasha, Lee, Deanna, Leligdowicz, Aleksandra, Liu, Yale, Mahboob, Salman, Maliskova, Lenka, Matthay, Michael, McCarthy, Elizabeth, Muñoz-Sandoval, Priscila, Neff, Norma, Nguyen, Viet, Nigam, Nishita, Parada, Randy, Phelps, Maira, Pierce, Logan, Prasad, Priya, Rashid, Sadeed, Reeder, Gabriella, Rodriguez, Nicklaus, Samad, Bushra, Schroeder, Andrew, Shaw, Cole, Shen, Alan, Sigman, Austin, Sinha, Pratik, Spitzer, Matthew, Sunshine, Sara, Tang, Kevin, Altamirano, Luz Torres, and Tsitsiklis, Alexandra

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Immunology, Lung, Coronaviruses, Emerging Infectious Diseases, Infectious Diseases, Acute Respiratory Distress Syndrome, Rare Diseases, Clinical Research, 2.1 Biological and endogenous factors, Good Health and Well Being, UCSF COMET Consortium, Clinical genetics, Immune response, Molecular medicine
Abstract

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

Published
2023

50. Zinc finger nuclease-mediated gene editing in hematopoietic stem cells results in reactivation of fetal hemoglobin in sickle cell disease

Author

Lessard, Samuel, Rimmelé, Pauline, Ling, Hui, Moran, Kevin, Vieira, Benjamin, Lin, Yi-Dong, Rajani, Gaurav Manohar, Hong, Vu, Reik, Andreas, Boismenu, Richard, Hsu, Ben, Chen, Michael, Cockroft, Bettina M., Uchida, Naoya, Tisdale, John, Alavi, Asif, Krishnamurti, Lakshmanan, Abedi, Mehrdad, Galeon, Isobelle, Reiner, David, Wang, Lin, Ramezi, Anne, Rendo, Pablo, Walters, Mark C., Levasseur, Dana, Peters, Robert, Harris, Timothy, and Hicks, Alexandra

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results