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5. Phi-3 Safety Post-Training: Aligning Language Models with a 'Break-Fix' Cycle

Author

Haider, Emman, Perez-Becker, Daniel, Portet, Thomas, Madan, Piyush, Garg, Amit, Ashfaq, Atabak, Majercak, David, Wen, Wen, Kim, Dongwoo, Yang, Ziyi, Zhang, Jianwen, Sharma, Hiteshi, Bullwinkel, Blake, Pouliot, Martin, Minnich, Amanda, Chawla, Shiven, Herrera, Solianna, Warreth, Shahed, Engler, Maggie, Lopez, Gary, Chikanov, Nina, Dheekonda, Raja Sekhar Rao, Jagdagdorj, Bolor-Erdene, Lutz, Roman, Lundeen, Richard, Westerhoff, Tori, Bryan, Pete, Seifert, Christian, Kumar, Ram Shankar Siva, Berkley, Andrew, and Kessler, Alex

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Recent innovations in language model training have demonstrated that it is possible to create highly performant models that are small enough to run on a smartphone. As these models are deployed in an increasing number of domains, it is critical to ensure that they are aligned with human preferences and safety considerations. In this report, we present our methodology for safety aligning the Phi-3 series of language models. We utilized a "break-fix" cycle, performing multiple rounds of dataset curation, safety post-training, benchmarking, red teaming, and vulnerability identification to cover a variety of harm areas in both single and multi-turn scenarios. Our results indicate that this approach iteratively improved the performance of the Phi-3 models across a wide range of responsible AI benchmarks. Finally, we include additional red teaming strategies and evaluations that were used to test the safety behavior of Phi-3.5-mini and Phi-3.5-MoE, which were optimized for multilingual capabilities.

Published
2024

6. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Author

Abdin, Marah, Aneja, Jyoti, Awadalla, Hany, Awadallah, Ahmed, Awan, Ammar Ahmad, Bach, Nguyen, Bahree, Amit, Bakhtiari, Arash, Bao, Jianmin, Behl, Harkirat, Benhaim, Alon, Bilenko, Misha, Bjorck, Johan, Bubeck, Sébastien, Cai, Martin, Cai, Qin, Chaudhary, Vishrav, Chen, Dong, Chen, Dongdong, Chen, Weizhu, Chen, Yen-Chun, Chen, Yi-Ling, Cheng, Hao, Chopra, Parul, Dai, Xiyang, Dixon, Matthew, Eldan, Ronen, Fragoso, Victor, Gao, Jianfeng, Gao, Mei, Gao, Min, Garg, Amit, Del Giorno, Allie, Goswami, Abhishek, Gunasekar, Suriya, Haider, Emman, Hao, Junheng, Hewett, Russell J., Hu, Wenxiang, Huynh, Jamie, Iter, Dan, Jacobs, Sam Ade, Javaheripi, Mojan, Jin, Xin, Karampatziakis, Nikos, Kauffmann, Piero, Khademi, Mahoud, Kim, Dongwoo, Kim, Young Jin, Kurilenko, Lev, Lee, James R., Lee, Yin Tat, Li, Yuanzhi, Li, Yunsheng, Liang, Chen, Liden, Lars, Lin, Xihui, Lin, Zeqi, Liu, Ce, Liu, Liyuan, Liu, Mengchen, Liu, Weishung, Liu, Xiaodong, Luo, Chong, Madan, Piyush, Mahmoudzadeh, Ali, Majercak, David, Mazzola, Matt, Mendes, Caio César Teodoro, Mitra, Arindam, Modi, Hardik, Nguyen, Anh, Norick, Brandon, Patra, Barun, Perez-Becker, Daniel, Portet, Thomas, Pryzant, Reid, Qin, Heyang, Radmilac, Marko, Ren, Liliang, de Rosa, Gustavo, Rosset, Corby, Roy, Sambudha, Ruwase, Olatunji, Saarikivi, Olli, Saied, Amin, Salim, Adil, Santacroce, Michael, Shah, Shital, Shang, Ning, Sharma, Hiteshi, Shen, Yelong, Shukla, Swadheen, Song, Xia, Tanaka, Masahiro, Tupini, Andrea, Vaddamanu, Praneetha, Wang, Chunyu, Wang, Guanhua, Wang, Lijuan, Wang, Shuohang, Wang, Xin, Wang, Yu, Ward, Rachel, Wen, Wen, Witte, Philipp, Wu, Haiping, Wu, Xiaoxia, Wyatt, Michael, Xiao, Bin, Xu, Can, Xu, Jiahang, Xu, Weijian, Xue, Jilong, Yadav, Sonali, Yang, Fan, Yang, Jianwei, Yang, Yifan, Yang, Ziyi, Yu, Donghan, Yuan, Lu, Zhang, Chenruidong, Zhang, Cyril, Zhang, Jianwen, Zhang, Li Lyna, Zhang, Yi, Zhang, Yue, Zhang, Yunan, and Zhou, Xiren

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3.5 (e.g., phi-3-mini achieves 69% on MMLU and 8.38 on MT-bench), despite being small enough to be deployed on a phone. Our training dataset is a scaled-up version of the one used for phi-2, composed of heavily filtered publicly available web data and synthetic data. The model is also further aligned for robustness, safety, and chat format. We also provide parameter-scaling results with a 7B, 14B models trained for 4.8T tokens, called phi-3-small, phi-3-medium, both significantly more capable than phi-3-mini (e.g., respectively 75%, 78% on MMLU, and 8.7, 8.9 on MT-bench). To enhance multilingual, multimodal, and long-context capabilities, we introduce three models in the phi-3.5 series: phi-3.5-mini, phi-3.5-MoE, and phi-3.5-Vision. The phi-3.5-MoE, a 16 x 3.8B MoE model with 6.6 billion active parameters, achieves superior performance in language reasoning, math, and code tasks compared to other open-source models of similar scale, such as Llama 3.1 and the Mixtral series, and on par with Gemini-1.5-Flash and GPT-4o-mini. Meanwhile, phi-3.5-Vision, a 4.2 billion parameter model derived from phi-3.5-mini, excels in reasoning tasks and is adept at handling both single-image and text prompts, as well as multi-image and text prompts., Comment: 24 pages

Published
2024

15. Machine Learning Model for Traffic Prediction and Pattern Extraction in High-Speed Optical Networks

Author

Rai, Saloni, Garg, Amit Kumar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Fortino, Giancarlo, editor, Kumar, Akshi, editor, Swaroop, Abhishek, editor, and Shukla, Pancham, editor

Published
2024
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16. Deep Convolutional Encoder–Decoder Models for Road Extraction from Aerial Imagery

Author

Kumar, Ashish, Izharul Hasan Ansari, M., Garg, Amit, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Joshi, Amit, editor, Mahmud, Mufti, editor, Ragel, Roshan G., editor, and Karthik, S., editor

Published
2024
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17. Traffic Optimization and Optimal Routing in 5G SDN Networks Using Deep Learning

Author

Kulshreshtha, Piyush, Garg, Amit Kumar, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Shaw, Rabindra Nath, editor, Siano, Pierluigi, editor, Makhilef, Saad, editor, Ghosh, Ankush, editor, and Shimi, S. L., editor

Published
2024
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21. Plasma Soluble Tumor Necrosis Factor Receptor Concentrations and Clinical Events After Hospitalization: Findings From the ASSESS-AKI and ARID Studies.

Author

Coca, Steven, Vasquez-Rios, George, Mansour, Sherry, Moledina, Dennis, Thiessen-Philbrook, Heather, Wurfel, Mark, Bhatraju, Pavan, Himmelfarb, Jonathan, Siew, Eddie, Garg, Amit, Hsu, Chi-Yuan, Kimmel, Paul, Chinchilli, Vernon, Kaufman, James, Wilson, Michelle, Banks, Rosamonde, Packington, Rebecca, McCole, Eibhlin, Kurth, Mary, Richardson, Ciaran, Go, Alan, Selby, Nicholas, Parikh, Chirag, and Liu, Kathleen

Subjects
AKI follow-up, Acute kidney injury (AKI), biomarker, end-stage kidney disease (ESKD), heart failure, hospitalization, kidney disease progression, mortality, prognosis, risk stratification, sTNFR2, soluble tumor necrosis factor receptor 1 (sTNFR1), Humans, Prospective Studies, Receptors, Tumor Necrosis Factor, Acute Kidney Injury, Hospitalization, Biomarkers, Heart Failure
Abstract

RATIONALE & OBJECTIVE: The role of plasma soluble tumor necrosis factor receptor 1 (sTNFR1) and sTNFR2 in the prognosis of clinical events after hospitalization with or without acute kidney injury (AKI) is unknown. STUDY DESIGN: Prospective cohort. SETTING & PARTICIPANTS: Hospital survivors from the ASSESS-AKI (Assessment, Serial Evaluation, and Subsequent Sequelae of Acute Kidney Injury) and ARID (AKI Risk in Derby) studies with and without AKI during the index hospitalization who had baseline serum samples for biomarker measurements. PREDICTORS: We measured sTNFR1 and sTNFR2 from plasma samples obtained 3 months after discharge. OUTCOMES: The associations of biomarkers with longitudinal kidney disease incidence and progression, heart failure, and death were evaluated. ANALYTICAL APPROACH: Cox proportional hazard models. RESULTS: Among 1,474 participants with plasma biomarker measurements, 19% had kidney disease progression, 14% had later heart failure, and 21% died during a median follow-up of 4.4 years. For the kidney outcome, the adjusted HRs (AHRs) per doubling in concentration were 2.9 (95% CI, 2.2-3.9) for sTNFR1 and 1.9 (95% CI, 1.5-2.5) for sTNFR2. AKI during the index hospitalization did not modify the association between biomarkers and kidney events. For heart failure, the AHRs per doubling in concentration were 1.9 (95% CI, 1.4-2.5) for sTNFR1 and 1.5 (95% CI, 1.2-2.0) for sTNFR2. For mortality, the AHRs were 3.3 (95% CI, 2.5-4.3) for sTNFR1 and 2.5 (95% CI, 2.0-3.1) for sTNFR2. The findings in ARID were qualitatively similar in terms of the magnitude of association between biomarkers and outcomes. LIMITATIONS: Different biomarker platforms and AKI definitions; limited generalizability to other ethnic groups. CONCLUSIONS: Plasma sTNFR1 and sTNFR2 measured 3 months after hospital discharge were independently associated with clinical events regardless of AKI status during the index admission. sTNFR1 and sTNFR2 may assist with the risk stratification of patients during follow-up.

Published
2023

22. Methodological innovations and stakeholder involvement in core outcome sets for skin diseases: a survey of the C3 working groups

Author

Ahmed, Areeba, Koza, Eric, Shi, Victoria, Ma, Melissa, Haq, Misha, Kottner, Jan, Garg, Amit, Ingram, John R., Ezzedine, Khaled, Spuls, Phyllis I., Beeckman, Dimitri, Wolkenstein, Pierre, Fransen, Frederike, Noe, Megan H., Langbroek, Ginger Beau, Bauer, Andrea, Thorlacius, Linnea, Horbach, Sophie E. R., Layton, Alison, Apfelbacher, Christian, Cahn, Brian A., Pearlman, Ross, Schlessinger, Daniel I., and Alam, Murad

Published
2024
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23. Clinical relevance and uptake of core outcome sets in dermatology

Author

Ahmed, Areeba, Koza, Eric, Shi, Victoria, Ma, Melissa, Haq, Misha, Kottner, Jan, Garg, Amit, Ingram, John R., Ezzedine, Khaled, Spuls, Phyllis I., Beeckman, Dimitri, Wolkenstein, Pierre, Fransen, Frederike, Noe, Megan H., Langbroek, Ginger Beau, Bauer, Andrea, Thorlacius, Linnea, Horbach, Sophie E. R., Layton, Alison, Apfelbacher, Christian, Cahn, Brian A., Pearlman, Ross, Schlessinger, Daniel I., and Alam, Murad

Published
2024
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24. Quantifiable Assurance: From IPs to Platforms

Author

Ahmed, Bulbul, Bepary, Md Kawser, Pundir, Nitin, Borza, Mike, Raikhman, Oleg, Garg, Amit, Donchin, Dale, Cron, Adam, Abdel-moneum, Mohamed A, Farahmandi, Farimah, Rahman, Fahim, and Tehranipoor, Mark

Subjects
Computer Science - Cryptography and Security
Abstract

Hardware vulnerabilities are generally considered more difficult to fix than software ones because they are persistent after fabrication. Thus, it is crucial to assess the security and fix the vulnerabilities at earlier design phases, such as Register Transfer Level (RTL) and gate level. The focus of the existing security assessment techniques is mainly twofold. First, they check the security of Intellectual Property (IP) blocks separately. Second, they aim to assess the security against individual threats considering the threats are orthogonal. We argue that IP-level security assessment is not sufficient. Eventually, the IPs are placed in a platform, such as a system-on-chip (SoC), where each IP is surrounded by other IPs connected through glue logic and shared/private buses. Hence, we must develop a methodology to assess the platform-level security by considering both the IP-level security and the impact of the additional parameters introduced during platform integration. Another important factor to consider is that the threats are not always orthogonal. Improving security against one threat may affect the security against other threats. Hence, to build a secure platform, we must first answer the following questions: What additional parameters are introduced during the platform integration? How do we define and characterize the impact of these parameters on security? How do the mitigation techniques of one threat impact others? This paper aims to answer these important questions and proposes techniques for quantifiable assurance by quantitatively estimating and measuring the security of a platform at the pre-silicon stages. We also touch upon the term security optimization and present the challenges for future research directions.

Published
2022

26. Retrieving Clinical Evidence: A Comparison of PubMed and Google Scholar for Quick Clinical Searches

Author

Shariff, Salimah Z, Bejaimal, Shayna AD, Sontrop, Jessica M, Iansavichus, Arthur V, Haynes, R Brian, Weir, Matthew A, and Garg, Amit X

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundPhysicians frequently search PubMed for information to guide patient care. More recently, Google Scholar has gained popularity as another freely accessible bibliographic database. ObjectiveTo compare the performance of searches in PubMed and Google Scholar. MethodsWe surveyed nephrologists (kidney specialists) and provided each with a unique clinical question derived from 100 renal therapy systematic reviews. Each physician provided the search terms they would type into a bibliographic database to locate evidence to answer the clinical question. We executed each of these searches in PubMed and Google Scholar and compared results for the first 40 records retrieved (equivalent to 2 default search pages in PubMed). We evaluated the recall (proportion of relevant articles found) and precision (ratio of relevant to nonrelevant articles) of the searches performed in PubMed and Google Scholar. Primary studies included in the systematic reviews served as the reference standard for relevant articles. We further documented whether relevant articles were available as free full-texts. ResultsCompared with PubMed, the average search in Google Scholar retrieved twice as many relevant articles (PubMed: 11%; Google Scholar: 22%; P

Published
2013
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28. Wound drainage measurements: a narrative review

Author

Shih, Terri, Park, Sarah, Thorlacius, Linnea R., Daveluy, Steven, Garg, Amit, Goegji, Susanne D., Kirby, Joslyn S., McGrath, Barry M., Riis, Peter T., Villumsen, Bente, Zalik, Kari, Jemec, Gregor B. E., and Hsiao, Jennifer L.

Published
2023
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32. Efficacy and safety of bimekizumab in patients with moderate-to-severe hidradenitis suppurativa (BE HEARD I and BE HEARD II): two 48-week, randomised, double-blind, placebo-controlled, multicentre phase 3 trials

Author

Kimball, Alexa B, Jemec, Gregor B E, Sayed, Christopher J, Kirby, Joslyn S, Prens, Errol, Ingram, John R, Garg, Amit, Gottlieb, Alice B, Szepietowski, Jacek C, Bechara, Falk G, Giamarellos-Bourboulis, Evangelos J, Fujita, Hideki, Rolleri, Robert, Joshi, Paulatsya, Dokhe, Pratiksha, Muller, Edward, Peterson, Luke, Madden, Cynthia, Bari, Muhammad, and Zouboulis, Christos C

Published
2024
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33. Vaccination recommendations for adults receiving biologics and oral therapies for psoriasis and psoriatic arthritis: Delphi consensus from the medical board of the National Psoriasis Foundation

Author

Chat, Vipawee S., Ellebrecht, Christoph T., Kingston, Paige, Gondo, George, Bell, Stacie, Cordoro, Kelly M., Desai, Seemal R., Duffin, Kristina C., Feldman, Steven R., Garg, Amit, Gelfand, Joel M., Gladman, Dafna, Green, Lawrence J., Gudjonsson, Johann, Han, George, Hawkes, Jason E., Kircik, Leon, Koo, John, Langley, Richard, Lebwohl, Mark, Michael Lewitt, G., Liao, Wilson, Martin, George, Orbai, Ana-Maria, Reddy, Soumya M., Richardson, Veronica, Ritchlin, Christopher T., Schwartzman, Sergio, Siegel, Evan L., Van Voorhees, Abby S., Wallace, Elizabeth B., Weinberg, Jeffrey M., Winthrop, Kevin L., Yamauchi, Paul, and Armstrong, April W.

Published
2024
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35. Comorbidity screening in hidradenitis suppurativa: Evidence-based recommendations from the US and Canadian Hidradenitis Suppurativa Foundations

Author

Garg, Amit, Malviya, Neeta, Strunk, Andrew, Wright, Shari, Alavi, Afsaneh, Alhusayen, Raed, Alikhan, Ali, Daveluy, Steven D, Delorme, Isabelle, Goldfarb, Noah, Gulliver, Wayne, Hamzavi, Iltefat, Jaleel, Tarannum, Kimball, Alexa B, Kirby, Joslyn S, Kirchhof, Mark G, Lester, Janice, Lev-Tov, Hadar, Lowes, Michelle A, Micheletti, Robert, Orenstein, Lauren A, Piguet, Vincent, Sayed, Christopher, Tan, Jerry, and Naik, Haley B

Subjects
Clinical Research, Health Services, Obesity, Prevention, Digestive Diseases, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Good Health and Well Being, Canada, Comorbidity, Female, Hidradenitis Suppurativa, Humans, Metabolic Syndrome, Pyoderma Gangrenosum, acne, cardiovascular disease, comorbidity, Crohn's disease, depression, dermatologist, diabetes mellitus, dissecting cellulitis of the scalp, down syndrome, dyslipidemia, generalized anxiety disorder, guidelines, herpes zoster, hidradenitis suppurativa, hypertension, inflammatory bowel disease, lymphoma, metabolic syndrome, North America, obesity, pilonidal disease, polycystic ovary syndrome, pyoderma gangrenosum, screening, sexual dysfunction, smoking, spondyloarthritis, substance use, suicide, systemic, ulcerative colitis, Clinical Sciences, Dermatology & Venereal Diseases
Abstract

BackgroundHidradenitis suppurativa (HS) is associated with comorbidities that contribute to poor health, impaired life quality, and mortality risk.ObjectiveTo provide evidence-based screening recommendations for comorbidities linked to HS.MethodsSystematic reviews were performed to summarize evidence on the prevalence and incidence of 30 comorbidities in patients with HS relative to the general population. The screening recommendation for each comorbidity was informed by the consistency and quality of existing studies, disease prevalence, and magnitude of association, as well as benefits, harms, and feasibility of screening. The level of evidence and strength of corresponding screening recommendation were graded by using the Strength of Recommendation Taxonomy (SORT) criteria.ResultsScreening is recommended for the following comorbidities: acne, dissecting cellulitis of the scalp, pilonidal disease, pyoderma gangrenosum, depression, generalized anxiety disorder, suicide, smoking, substance use disorder, polycystic ovary syndrome, obesity, dyslipidemia, diabetes mellitus, metabolic syndrome, hypertension, cardiovascular disease, inflammatory bowel disease, spondyloarthritis, and sexual dysfunction. It is also recommended to screen patients with Down syndrome for HS. The decision to screen for specific comorbidities may vary with patient risk factors. The role of the dermatologist in screening varies according to comorbidity.LimitationsScreening recommendations represent one component of a comprehensive care strategy.ConclusionsDermatologists should support screening efforts to identify comorbid conditions in HS.

Published
2022

38. Implementation and Efficacy of a Large-Scale Radiation Oncology Case-Based Peer-Review Quality Program across a Multinational Cancer Network

Author

Ludmir, Ethan B., Hoffman, Karen E., Jhingran, Anuja, Kouzy, Ramez, Ip, Mee-chung Puscilla, Sturdevant, Laurie, Ning, Matthew S., Minsky, Bruce D., McAleer, Mary Frances, Chronowski, Gregory M., Arzu, Isidora Y., Reed, Valerie Klairisa, Garg, Amit K., Roberts, Terence, Eastwick, Gary A., Olson, Michael R., Selek, Ugur, Gabel, Molly, Koong, Albert C., Kupferman, Michael E., and Kuban, Deborah A.

Published
2024
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39. Ring-Based Hybrid GPON Network with Inter-oNU Transmission Capability

Author

Khare, Shalini, Garg, Amit Kumar, Phophaliya, Aditi, Janyani, Vijay, Singh, Ghanshyam, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nguyen, Thi Dieu Linh, editor, Verdú, Elena, editor, Le, Anh Ngoc, editor, and Ganzha, Maria, editor

Published
2023
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43. The “Understanding Pyoderma Gangrenosum, Review and Assessment of Disease Effects (UPGRADE)” Project: a protocol for the development of the core outcome domain set for trials in pyoderma gangrenosum

Author

Rick, Jonathan, Gould, Lisa J., Marzano, Angelo Valerio, Garg, Amit, Chen, Diana, Oakes, Debbie L., Dissemond, Joachim, Herfarth, Hans, Friedman, Marcia A., Alavi, Afsaneh, Yamamoto, Toshiyuki, Gerbens, Louise A. A., Thomas, Kim S., and Ortega-Loayza, Alex G.

Published
2023
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44. Achieved blood pressure post-acute kidney injury and risk of adverse outcomes after AKI: A prospective parallel cohort study.

Author

McCoy, Ian, Brar, Sandeep, Liu, Kathleen D, Go, Alan S, Hsu, Raymond K, Chinchilli, Vernon M, Coca, Steven G, Garg, Amit X, Himmelfarb, Jonathan, Ikizler, T Alp, Kaufman, James, Kimmel, Paul L, Lewis, Julie B, Parikh, Chirag R, Siew, Edward D, Ware, Lorraine B, Zeng, Hui, Hsu, Chi-Yuan, and Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study investigators

Subjects
Assessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) study investigators, AKI, blood pressure, hypertension, Kidney Disease, Cardiovascular, Clinical Research, Patient Safety, 2.1 Biological and endogenous factors, 2.4 Surveillance and distribution, Renal and urogenital, Urology & Nephrology, Clinical Sciences
Abstract

BackgroundThere has recently been considerable interest in better understanding how blood pressure should be managed after an episode of hospitalized AKI, but there are scant data regarding the associations between blood pressure measured after AKI and subsequent adverse outcomes. We hypothesized that among AKI survivors, higher blood pressure measured three months after hospital discharge would be associated with worse outcomes. We also hypothesized these associations between blood pressure and outcomes would be similar among those who survived non-AKI hospitalizations.MethodsWe quantified how systolic blood pressure (SBP) observed three months after hospital discharge was associated with risks of subsequent hospitalized AKI, loss of kidney function, mortality, and heart failure events among 769 patients in the prospective ASSESS-AKI cohort study who had hospitalized AKI. We repeated this analysis among the 769 matched non-AKI ASSESS-AKI enrollees. We then formally tested for AKI interaction in the full cohort of 1538 patients to determine if these associations differed among those who did and did not experience AKI during the index hospitalization.ResultsAmong 769 patients with AKI, 42 % had subsequent AKI, 13 % had loss of kidney function, 27 % died, and 18 % had heart failure events. SBP 3 months post-hospitalization did not have a stepwise association with the risk of subsequent AKI, loss of kidney function, mortality, or heart failure events. Among the 769 without AKI, there was also no stepwise association with these risks. In formal interaction testing using the full cohort of 1538 patients, hospitalized AKI did not modify the association between post-discharge SBP and subsequent risks of adverse clinical outcomes.ConclusionsContrary to our first hypothesis, we did not observe that higher stepwise blood pressure measured three months after hospital discharge with AKI was associated with worse outcomes. Our data were consistent with our second hypothesis that the association between blood pressure measured three months after hospital discharge and outcomes among AKI survivors is similar to that observed among those who survived non-AKI hospitalizations.

Published
2021

45. The ASSESS-AKI Study found urinary epidermal growth factor is associated with reduced risk of major adverse kidney events

Author

Menez, Steven, Wen, Yumeng, Xu, Leyuan, Moledina, Dennis G., Thiessen-Philbrook, Heather, Hu, David, Obeid, Wassim, Bhatraju, Pavan K., Ikizler, T. Alp, Siew, Edward D., Chinchilli, Vernon M., Garg, Amit X., Go, Alan S., Liu, Kathleen D., Kaufman, James S., Kimmel, Paul L., Himmelfarb, Jonathan, Coca, Steven G., Cantley, Lloyd G., and Parikh, Chirag R.

Published
2023
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47. Regional Practice Variation and Outcomes in the Standard Versus Accelerated Initiation of Renal Replacement Therapy in Acute Kidney Injury (STARRT-AKI) Trial: A Post Hoc Secondary Analysis

Author

Vaara, Suvi T., Serpa Neto, Ary, Bellomo, Rinaldo, Adhikari, Neill K. J., Dreyfuss, Didier, Gallagher, Martin, Gaudry, Stephane, Hoste, Eric, Joannidis, Michael, Pettilä, Ville, Wang, Amanda Y., Kashani, Kianoush, Wald, Ron, Bagshaw, Sean M., Ostermann, Marlies, Bagshaw, Sean M, Wald, Ron, Adhikari, Neill K.J., Bellomo, Rinaldo, Dreyfuss, Didier, Du, Bin, Gallagher, Martin P., Gaudry, Stéphane, Hoste, Eric A., Lamontagne, François, Joannidis, Michael, Liu, Kathleen D., McAuley, Daniel F., McGuinness, Shay P., Nichol, Alistair D., Ostermann, Marlies, Palevsky, Paul M., Qiu, Haibo, Pettilä, Ville, Schneider, Antoine G., Smith, Orla M., Vaara, Suvi T., Weir, Matthew, Bellomo, Rinaldo, Eastwood, Glenn M., Peck, Leah, Young, Helen, Kruger, Peter, Laurie, Gordon, Saylor, Emma, Meyer, Jason, Venz, Ellen, Wetzig, Krista, French, Craig, McGain, Forbes, Mulder, John, Fennessy, Gerard, Koottayi, Sathyajith, Bates, Samantha, Towns, Miriam, Morgan, Rebecca, Tippett, Anna, Udy, Andrew, Mason, Chris, Licari, Elisa, Gantner, Dashiell, McClure, Jason, Nichol, Alistair, McCracken, Phoebe, Board, Jasmin, Martin, Emma, Vallance, Shirley, Young, Meredith, Vladic, Chelsey, McGloughlin, Steve, Gattas, David, Buhr, Heidi, Coles, Jennifer, Hutch, Debra, Wun, James, Cole, Louise, Whitehead, Christina, Lowrey, Julie, Masters, Kristy, Gresham, Rebecca, Campbell, Victoria, Gutierrez, David, Brailsford, Jane, Forbes, Loretta, Murray, Lauren, Maguire, Teena, NiChonghaile, Martina, Orford, Neil, Bone, Allison, Elderkin, Tania, Salerno, Tania, Chimunda, Tim, Fletcher, Jason, Broadfield, Emma, Porwal, Sanjay, Knott, Cameron, Boschert, Catherine, Smith, Julie, Richardson, Angus, Hill, Dianne, Duke, Graeme, Oziemski, Peter, Cegarra, Santiago, Chan, Peter, Welsh, Deborah, Hunter, Stephanie, Roodenburg, Owen, Dyett, John, Kokotsis, Nicos, Moser, Max, Yang, Yang, Padayachee, Laven, Vetro, Joseph, Gangopadhyay, Himangsu, Kaufman, Melissa, Ghosh, Angaj, Said, Simone, Patel, Alpesh, Bihari, Shailesh, Matheson, Elisha, Jin, Xia, Shrestha, Tapaswi, Schwartz, Kate, Gallagher, Martin P., Cross, Rosalba, Cheung, Winston, Wong, Helen, Kol, Mark, Shah, Asim, Wang, Amanda Y., Endre, Zoltan, Bradford, Celia, Janin, Pierre, Finfer, Simon, Diel, Naomi, Gatward, Jonathan, Hammond, Naomi, Delaney, Anthony, Bass, Frances, Yarad, Elizabeth, Buscher, Hergen, Reynolds, Claire, Baker, Nerilee, Joannidis, Michael, Bellmann, Romuald, Peer, Andreas, Hasslacher, Julia, Koglberger, Paul, Klein, Sebastian, Zotter, Klemens, Brandtner, Anna, Finkenstedt, Armin, Ditlbacher, Adelheid, Hartig, Frank, Fries, Dietmar, Bachler, Mirjam, Schenk, Bettina, Wagner, Martin, Staudinger, Thomas, Tiller, Esther, Schellongowski, Peter, Bojic, Andja, Hoste, Eric A., Bracke, Stephanie, De Crop, Luc, Vermeiren, Daisy, Thome, Fernando, Chiella, Bianca, Fendt, Lucia, Antunes, Veronica, Maisonneuve-Rosemont, Lafrance, Jean-Philippe, Lamontagne, François, D’Aragon, Frédérick, St-Arnaud, Charles, Mayette, Michael, Carbonnaeu, Élaine, Marchand, Joannie, Masse, Marie-Hélène, Ladouceur, Marilène, Turgeon, Alexis F., Lauzier, François, Bellemare, David, Langis Francoeur, Charles, LeBlanc, Guillaume, Guilbault, Gabrielle, Grenier, Stéphanie, Cloutier, Eve, Boivin, Annick, Delisle-Thibault, Charles, Giannakouros, Panagiota, Costerousse, Olivier, Cailhier, Jean-François, Carrier, François-Martin, Ghamraoui, Ali, Lebrasseur, Martine, Benettaib, Fatna, Salamé, Maya, Boumahni, Dounia, Tung Sia, Ying, Naud, Jean-François, Roy, Isabelle, Stelfox, Henry T., Ruddell, Stacey, Manns, Braden J., Duggan, Shelley, Carney, Dominic, Barchard, Jennifer, Whitlock, Richard P., Belley-Cote, Emilie, Savija, Nevena, Sabev, Alexandra, Campbell, Troy, Creary, Thais, Devereaux, Kelson, Brodutch, Shira, Rigatto, Claudio, Paunovic, Bojan, Mooney, Owen, Glybina, Anna, Harasemiw, Oksana, Di Nella, Michelle, Harmon, John, Mehta, Navdeep, Lakatos, Louis, Haslam, Nicole, Lellouche, Francois, Simon, Mathieu, Tung, Ying, Lizotte, Patricia, Bourchard, Pierre-Alexandre, Rochwerg, Bram, Karachi, Tim, Millen, Tina, Muscedere, John, Maslove, David, Gordon Boyd, J., Sibley, Stephanie, Drover, John, Hunt, Miranda, Georgescu, Ilinca, Wax, Randy, Lenga, Ilan, Sridhar, Kavita, Steele, Andrew, Fusco, Kelly, Ghate, Taneera, Tolibas, Michael, Robinson, Holly, Weir, Matthew A., Taneja, Ravi, Ball, Ian M., Garg, Amit, Campbell, Eileen, Ovsenek, Athena, Bagshaw, Sean M., van Diepen, Sean, Baig, Nadia, Magder, Sheldon, Yao, Han, Alam, Ahsan, Campisi, Josie, MacIntyre, Erika, Rokosh, Ella, Scherr, Kimberly, Lapinsky, Stephen, Mehta, Sangeeta, Shah, Sumesh, Niven, Daniel J., Stelfox, Henry T., Ruddell, Stacey, Russell, Michael, Jim, Kym, Brown, Gillian, Oxtoby, Kerry, Hall, Adam, Benoit, Luc, Sokolowski, Colleen, Prasad, Bhanu, Rao, Jag, Giebel, Shelley, Kutsogiannis, Demetrios J., Thompson, Patricia, Thompson, Tayne, Cirone, Robert, Kavikondala, Kanthi, Soth, Mark, Clarke, France, Takaoka, Alyson, Wald, Ron, Mazer, David, Burns, Karen, Friedrich, Jan, Klein, David, Sandhu, Gyan, Santos, Marlene, Khalid, Imrana, Hodder, Jennifer, Dodek, Peter, Ayas, Najib, Alcuaz, Victoria, Suen, Gabriel, Rewa, Oleksa, Singh, Gurmeet, Norris, Sean, Gibson, Neil, Arias, Castro, Shami, Aysha, Pelletier, Celine, Adhikari, Neill K.J., Zahirieh, Alireza, Amaral, Andre, Marinoff, Nicole, Kaur, Navjot, Perez, Adic, Wang, Jane, Haljan, Gregory, Condin, Christopher, McIntyre, Lauralyn, Gomes, Brigette, Porteous, Rebecca, Watpool, Irene, Hiremath, Swapnil, Clark, Edward, Herridge, Margaret S., Backhouse, Felicity, Elizabeth Wilcox, M., Walczak, Karolina, Ki, Vincent, Sharman, Asheer, Romano, Martin, Bagshaw, Sean M., Noel Gibney, R.T., Romanovsky, Adam S., Rewa, Oleksa, McCoshen, Lorena, Baig, Nadia, Wood, Gordon, Ovakim, Daniel, Auld, Fiona, Carney, Gayle, Duan, Meili, Ji, Xiaojun, Guo, Dongchen, Qi, Zhili, Lin, Jin, Zhang, Meng, Dong, Lei, Liu, Jingfeng, Liu, Pei, Zhi, Deyuan, Bai, Guoqiang, Qiu, Yu, Yang, Ziqi, Bai, Jing, Liu, Zhuang, Zhuang, Haizhou, Wang, Haiman, Li, Jian, Zhao, Mengya, Zhou, Xiao, Shi, Xianqing, Ye, Baning, Liu, Manli, Wu, Jing, Fu, Yongjian, Long, Dali, Pan, Yu, Wang, Jinlong, Mei, Huaxian, Zhang, Songsong, Wen, Mingxiang, Yang, Enyu, Mu, Sijie, Li, Jianquan, Hu, Tingting, Qin, Bingyu, Li, Min, Wang, Cunzhen, Dong, Xin, Wang, Kaiwu, Wang, Haibo, Yang, Jianxu, Du, Bin, Wang, Chuanyao, Wang, Dongxin, Li, Nan, Yu, Zhui, Xu, Song, Yao, Lan, Hou, Guo, Liu, Zhou, Lu, Liping, Lian, Yingtao, Wang, Chunting, Zhang, Jichen, Ding, Ruiqi, Qi, Guoqing, Wang, Qizhi, Wang, Peng, Meng, Zhaoli, Chen, Man, Hu, Xiaobo, He, Xiandi, Zhao, Shibing, Hang, Lele, Li, Rui, Qin, Suhui, Lu, Kun, Dun, Shijuan, Liu, Cheng, Zhou, Qi, Chen, Zhenzhen, Mei, Jing, Zhang, Minwei, Xu, Hao, Lin, Jincan, Shi, Qindong, Fu, Lijuan, Zeng, Qinjing, Ma, Hongye, Yan, Jinqi, Gao, Lan, Liu, Hongjuan, Zhang, Lei, Li, Hao, He, Xiaona, Fan, Jingqun, Guo, Litao, Liu, Yu, Wang, Xue, Sun, Jingjing, Liu, Zhongmin, Yang, Juan, Ding, Lili, Sheng, Lulu, Liu, Xingang, Yan, Jie, Wang, Quihui, Wang, Yifeng, Zhao, Dan, Zhao, Shuangping, Hu, Chenghuan, Li, Jing, Deng, Fuxing, Qiu, Haibo, Yang, Yi, Mo, Min, Pan, Chun, Wu, Changde, Huang, Yingzi, Huang, Lili, Liu, Airan, Pettilä, Ville, Vaara, Suvi T., Korhonen, Anna-Maija, Törnblom, Sanna, Sutinen, Sari, Pettilä, Leena, Heinonen, Jonna, Lappi, Eliria, Suhonen, Taria, Karlsson, Sari, Hoppu, Sanna, Jalkanen, Ville, Kuitunen, Anne, Levoranta, Markus, Långsjö, Jaakko, Ristimäki, Sanna, Malila, Kaisa, Wootten, Anna, Varila, Simo, Järvisalo, Mikko J, Inkinen, Outi, Kentala, Satu, Leivo, Keijo, Haltia, Paivi, Dreyfuss, Didier, Ricard, Jean-Damien, Messika, Jonathan, Tiagarajah, Abirami, Emery, Malo, Dechanet, Aline, Gernez, Coralie, Roux, Damien, Martin-Lefevre, Laurent, Fiancette, Maud, Vinatier, Isabelle, Claude Lacherade, Jean, Colin, Gwenhaël, Lebert, Christine, Azais, Marie-Ange, Yehia, Aihem, Pouplet, Caroline, Henry- Lagarrigue, Matthieu, Seguin, Amélie, Crosby, Laura, Maizel, Julien, Titeca-Beauport, Dimitri, Combes, Alain, Nieszkowska, Ania, Masi, Paul, Demoule, Alexandre, Mayaux, Julien, Dres, Martin, Morawiec, Elise, Decalvele, Maxens, Demiri, Suela, Faure, Morgane, Marios, Clémence, Mallet, Maxime, Amélie Ordon, Marie, Morizot, Laura, Cantien, Marie, Pousset, François, Gaudry, Stéphane, Poirson, Florent, Cohen, Yves, Argaud, Laurent, Cour, Martin, Bitker, Laurent, Simon, Marie, Hernu, Romain, Baudry, Thomas, De La Salle, Sylvie, Robine, Adrien, Sedillot, Nicholas, Tchenio, Xavier, Bouisse, Camille, Roux, Sylvie, Barbar, Davide, Trusson, Rémi, Tamion, Fabienne, Grangé, Steven, Carpentier, Dorothée, Chevrel, Guillaume, Ensenyat-Martin, Luis, Marque, Sophie, Quenot, Jean-Pierre, Andreu, Pascal, Dargent, Auguste, Large, Audrey, Chudeau, Nicolas, Landais, Mickael, Derrien, Benoit, Christophe Callahan, Jean, Guitton, Christophe, Le Moal, Charlène, Robert, Alain, Asehnoune, Karim, Cinotti, Raphaël, Grillot, Nicolas, Demeure, Dominique, Vinsonneau, Christophe, Rahmani, Imen, Marzouk, Mehdi, Dekeyser, Thibault, Sejourne, Caroline, Verlay, Mélanie, Thevenin, Fabienne, Delecolle, Lucie, Didier Thevenin, Lens, Souweine, Bertrand, Coupez, Elisabeth, Adda, Mireille, Eraldi, Jean-Pierre, Marchalot, Antoine, De Prost, Nicolas, Mekontso Dessap, Armand, Razazi, Keyvan, Meziani, Ferhat, Boisrame-Helms, Julie, Clere-Jehl, Raphael, Delabranche, Xavier, Kummerlen, Christine, Merdji, Hamid, Monnier, Alexandra, Rabouel, Yannick, Rahmani, Hassene, Allam, Hayat, Chenaf, Samir, Franja, Vincenta, Pons, Bertrand, Carles, Michel, Martino, Frédéric, Richard, Régine, Zuber, Benjamin, Lacave, Guillaume, Lakhal, Karim, Rozec, Bertrand, Dang Van, Hoa, Boulet, Éric, Dubos, René, Fadel, Fouad, Cleophax, Cedric, Dufour, Nicolas, Grant, Caroline, Thuong, Marie, Reignier, Jean, Canet, Emmanuel, Nicolet, Laurent, Boulain, Thierry, Nay, Mai-Anh, Benzekri, Dalila, Barbier, François, Bretagnol, Anne, Kamel, Toufik, Mathonnet, Armelle, Muller, Grégoire, Skarzynski, Marie, Rossi, Julie, Pradet, Amandine, Dos Santos, Sandra, Guery, Aurore, Muller, Lucie, Felix, Luis, Bohé, Julien, Thiéry, Guillaume, Aissaoui, Nadia, Vimpere, Damien, Commeureuc, Morgane, Diehl, Jean-Luc, Guerot, Emmanuel, Liangos, Orfeas, Wittig, Monika, Zarbock, Alexander, Küllmar, Mira, van Waegeningh, Thomas, Rosenow, Nadine, Nichol, Alistair D., Brickell, Kathy, Doran, Peter, Murray, Patrick T., Landoni, Giovanni, Lembo, Rosalba, Zangrillo, Alberto, Monti, Giacomo, Tozzi, Margherita, Marzaroli, Matteo, Lombardi, Gaetano, Paternoster, Gianluca, Vitiello, Michelangelo, McGuinness, Shay, Parke, Rachael, Butler, Magdalena, Gilder, Eileen, Cowdrey, Keri-Anne, Wallace, Samantha, Hallion, Jane, Woolett, Melissa, Neal, Philippa, Duffy, Karina, Long, Stephanie, McArthur, Colin, Simmonds, Catherine, Chen, Yan, McConnochie, Rachael, Newby, Lynette, Knight, David, Henderson, Seton, Mehrtens, Jan, Morgan, Stacey, Morris, Anna, Vander Hayden, Kymbalee, Burke, Tara, Bailey, Matthew, Freebairn, Ross, Chadwick, Lesley, Park, Penelope, Rolls, Christine, Thomas, Liz, Buehner, Ulrike, Williams, Erin, Albrett, Jonathan, Kirkham, Simon, Jackson, Carolyn, Browne, Troy, Goodson, Jennifer, Jackson, David, Houghton, James, Callender, Owen, Higson, Vicki, Keet, Owen, Dominy, Clive, Young, Paul, Hunt, Anna, Judd, Harriet, Lawrence, Cassie, Olatunji, Shaanti, Robertson, Yvonne, Latimer-Bell, Charlotte, Hendry, Deborah, Mckay-Vucago, Agnes, Beehre, Nina, Lesona, Eden, Navarra, Leanlove, Robinson, Chelsea, Jang, Ryan, Junge, Andrea, Lambert, Bridget, Schneider, Antoine G., Thibault, Michel, Eckert, Philippe, Kissling, Sébastien, Polychronopoulos, Erietta, Poli, Elettra, Altarelli, Marco, Schnorf, Madeleine, Abed Mallaird, Samia, Heidegger, Claudia, Perret, Aurelie, Montillier, Philippe, Sangla, Frederic, Neils, Seigenthaller, De Watteville, Aude, Phull, Mandeep-Kaur, George, Aparna, Hussain, Nauman, Pogreban, Tatiana, Lobaz, Steve, Daniels, Alison, Cunningham, Mishell, Kerr, Deborah, Nicholson, Alice, Shanmugasundaram, Pradeep, Abrams, Judith, Manso, Katarina, Hambrook, Geraldine, McKerrow, Elizabeth, Salva, Juvy, Foulkes, Stephen, Wise, Matthew, Morgan, Matt, Brooks, Jenny, Cole, Jade, Michelle Davies, Tracy, Hill, Helen, Thomas, Emma, Vizcaychipi, Marcela, Baharlo, Behrad, Carungcong, Jaime, Costa, Patricia, Martins, Laura, Kapoor, Ritoo, Hazelton, Tracy, Moon, Angela, Musselwhite, Janine, Shelley, Ben, McCall, Philip, Ostermann, Marlies, Arbane, Gill, Bociek, Aneta, Marotti, Martina, Lim, Rosario, Campos, Sara, Grau Novellas, Neus, Cennamo, Armando, Slack, Andrew, Wyncoll, Duncan, Camporota, Luigi, Sparkes, Simon, Tilley, Rosalinde, Rattray, Austin, Moreland, Gayle, Duffy, Jane, McGonigal, Elizabeth, Hopkins, Philip, Finney, Clare, Smith, John, Noble, Harriet, Watson, Hayley, Harris, Claire-Louise, Clarey, Emma, Corcoran, Eleanor, Beck, James, Howcroft, Clare, Youngs, Nora, Wilby, Elizabeth, Ogg, Bethan, Wolverson, Adam, Lee, Sandra, Butler, Susie, Okubanjo, Maryanne, Hindle, Julia, Welters, Ingeborg, Williams, Karen, Johnson, Emily, Patrick-Heselton, Julie, Shaw, David, Waugh, Victoria, Stewart, Richard, Mwaura, Esther, Wren, Lynn, Mew, Louise, Sutherland, Sara-Beth, Adderley, Jane, Ruddy, Jim, Harkins, Margaret, Kaye, Callum, Scott, Teresa, Mitchell, Wendy, Anderson, Felicity, Willox, Fiona, Jagannathan, Vijay, Clark, Michele, Purv, Sarah, Sharman, Andrew, Meredith, Megan, Ryan, Lucy, Conner, Louise, Peters, Cecilia, Harvey, Dan, Roshdy, Ashraf, Collins, Amy, Sim, Malcolm, Henderson, Steven, Chee, Nigel, Pitts, Sally, Bowman, Katie, Dilawershah, Maria, Vamplew, Luke, Howe, Elizabeth, Rogers, Paula, Hernandez, Clara, Prendergast, Clara, Benton, Jane, Rosenberg, Alex, Forni, Lui G., Grant, Alice, Carvelli, Paula, Raithatha, Ajay, Bird, Sarah, Richardson, Max, Needham, Matthew, Hirst, Claire, Ball, Jonathan, Leaver, Susannah, Howlett, Luisa, Castro Delgado, Carlos, Farnell-Ward, Sarah, Farrah, Helen, Gray, Geraldine, Joseph, Gipsy, Robinson, Francesca, Tridente, Ascanio, Harrop, Clare, Shuker, Karen, McLaughlan, Derek, Ramsey, Judith, Meehan, Sharon, Oliver Rose, Bernd, Reece-Anthony, Rosie, Gurung, Babita, Whitehouse, Tony, Snelson, Catherine, Veenith, Tonny, Johnston, Andy, Cooper, Lauren, Carrera, Ron, Ellis, Karen, Fellows, Emma, Harkett, Samanth, Bergin, Colin, Spruce, Elaine, Despy, Liesl, Goundry, Stephanie, Dooley, Natalie, Mason, Tracy, Clark, Amy, Dignam, Gemma, Ward, Geraldine, Attwood, Ben, Parsons, Penny, Mason, Sophie, Margarson, Michael, Lord, Jenny, McGlone, Philip, Hodgson, Luke E., Chadbourn, Indra, Gomez, Raquel, Margalef, Jordi, Pretorius, Rinus, Hamshere, Alexandra, Carter, Joseph, Cahill, Hazel, Grainger, Lia, Howard, Kate, Forshaw, Greg, Guy, Zoe, Kashani, Kianoush B., Albright, Robert C., Amsbaugh, Amy, Stoltenberg, Anita, Niven, Alexander S., Lynch, Matthew, O’Mara, AnnMarie, Naeem, Syed, Sharif, Sairah, McKenney Goulart, Joyce, Lynch, Matthew, O’Mara, AnnMarie, Naeem, Syed, Sharif, Sairah, McKenney Goulart, Joyce, Tolwani, Ashita, Lyas, Claretha, Latta, Laura, Bihorac, Azra, Hashemighouchani, Haleh, Efron, Philip, Ruppert, Matthew, Cupka, Julie, Kiley, Sean, Carson, Joshua, White, Peggy, Omalay, George, Brown, Sherry, Velez, Laura, Marceron, Alina, Neyra, Javier A., Carlos Aycinena, Juan, Elias, Madona, Ortiz-Soriano, Victor M., Hauschild, Caroline, and Dorfman, Robert

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2024
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48. One-year Outcomes after Discharge from Noncardiac Surgery and Association between Predischarge Complications and Death after Discharge: Analysis of the VISION Prospective Cohort Study

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Roshanov, Pavel S., Chan, Matthew T. V., Borges, Flavia K., Conen, David, Wang, C. Y., Xavier, Denis, Berwanger, Otavio, Marcucci, Maura, Sessler, Daniel I., Szczeklik, Wojciech, Spence, Jessica, Alonso-Coello, Pablo, Fernández, Carmen, Pearse, Rupert M., Malaga, German, Garg, Amit X., Srinathan, Sadeesh K., Jacka, Michael J., Tandon, Vikas, McGillion, Michael, Popova, Ekaterine, Sigamani, Alben, Abraham, Valsa, Biccard, Bruce M., Villar, Juan Carlos, Chow, Clara K., Polanczyk, Carísi A., Tiboni, Maria, Whitlock, Richard, Ackland, Gareth L., Panju, Mohamed, Lamy, André, Sapsford, Robert, Williams, Colin, Wu, William Ka Kei, Cortés, Olga L., MacNeil, S. Danielle, Patel, Ameen, Belley-Côté, Emilie P., Ofori, Sandra, McIntyre, William F., Leong, Darryl P., Heels-Ansdell, Diane, Gregus, Krysten, and Devereaux, P. J.

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2024
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