16,657 results on '"Spratt AN"'
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2. Influence of magmatic and magmatic-hydrothermal processes on the lithium endowment of micas in the Cornubian Batholith (SW England)
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Putzolu, F., Seltmann, R., Dolgopolova, A., Armstrong, R. N., Shail, R. K., Spratt, J., Buret, Y., Broderick, C., and Brownscombe, W.
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- 2024
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3. Expert Perspectives on Controversies in Metastatic Castration-Resistant Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 2.
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Bryce, Alan, Crawford, E, Agarwal, Neeraj, Hussain, Maha, Beltran, Himisha, Cooperberg, Matthew, Petrylak, Daniel, Shore, Neal, Spratt, Daniel, Tagawa, Scott, Antonarakis, Emmanuel, Aparicio, Ana, Armstrong, Andrew, Boike, Thomas, Calais, Jeremie, Carducci, Michael, Chapin, Brian, Cookson, Michael, Davis, John, Dorff, Tanya, Eggener, Scott, Feng, Felix, Gleave, Martin, Higano, Celestia, Iagaru, Andrei, Morgans, Alicia, Morris, Michael, Murray, Katie, Poage, Wendy, Rettig, Matthew, Sartor, Oliver, Scher, Howard, Sieber, Paul, Small, Eric, Srinivas, Sandy, Yu, Evan, Zhang, Tian, and Koo, Phillip
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androgen antagonists ,biomarkers ,precision medicine ,prostatic neoplasms ,radiotherapy - Abstract
BACKGROUND: Management strategies for metastatic castration-resistant prostate cancer (mCRPC) have rapidly shifted in recent years. As novel imaging and therapeutic approaches have made their way to the clinic, providers are encountering increasingly challenging clinical scenarios, with limited guidance from the current literature. MATERIALS AND METHODS: The US Prostate Cancer Conference (USPCC) is a multidisciplinary meeting of prostate cancer experts intended to address the many challenges of prostate cancer management. At the first annual USPCC meeting, areas of controversy and consensus were identified during a 2-day meeting that included expert presentations, full-panel discussions, and postdiscussion responses to questions developed by the USPCC cochairs and session moderators. RESULTS: This narrative review covers the USPCC expert discussion and perspectives relevant to mCRPC, including neuroendocrine/aggressive-variant prostate cancer (NEPC/AVPC). Areas of broad agreement identified among USPCC experts include the benefits of poly (ADP-ribose) polymerase (PARP) inhibitors for patients with BRCA1/2 mutations, the use of radioligand therapy in patients with prostate-specific membrane antigen (PSMA)-positive mCRPC, and the need for clinical trials that address real-world clinical questions, including the performance of novel therapies when compared with modern standard-of-care treatment. Ongoing areas of controversy and uncertainty included the appropriateness of PARP inhibitors in patients with non-BRCA1/2 mutations, the optimal definition of PSMA positivity, and systemic therapies for patients with NEPC/AVPC after progression on platinum-based therapies. CONCLUSIONS: The first annual USPCC meeting identified several areas of controversy in the management of mCRPC, highlighting the urgent need for clinical trials designed to facilitate treatment selection and sequencing in this heterogeneous disease state.
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- 2024
4. Expert Perspectives on Controversies in Castration-Sensitive Prostate Cancer Management: Narrative Review and Report of the First US Prostate Cancer Conference Part 1.
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Crawford, E, Bryce, Alan, Hussain, Maha, Agarwal, Neeraj, Beltran, Himisha, Cooperberg, Matthew, Petrylak, Daniel, Shore, Neal, Spratt, Daniel, Tagawa, Scott, Antonarakis, Emmanuel, Aparicio, Ana, Armstrong, Andrew, Boike, Thomas, Calais, Jeremie, Carducci, Michael, Chapin, Brian, Cookson, Michael, Davis, John, Dorff, Tanya, Eggener, Scott, Feng, Felix, Gleave, Martin, Higano, Celestia, Iagaru, Andrei, Morgans, Alicia, Morris, Michael, Murray, Katie, Poage, Wendy, Rettig, Matthew, Sartor, Oliver, Scher, Howard, Sieber, Paul, Small, Eric, Srinivas, Sandy, Yu, Evan, Zhang, Tian, and Koo, Phillip
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biomarkers ,ndrogen antagonists ,precision medicine ,prostatic neoplasms ,radiotherapy - Abstract
PURPOSE: Castration-sensitive prostate cancer (CSPC) is a complex and heterogeneous condition encompassing a range of clinical presentations. As new approaches have expanded management options, clinicians are left with myriad questions and controversies regarding the optimal individualized management of CSPC. MATERIALS AND METHODS: The US Prostate Cancer Conference (USPCC) multidisciplinary panel was assembled to address the challenges of prostate cancer management. The first annual USPCC meeting included experts in urology, medical oncology, radiation oncology, and nuclear medicine. USPCC co-chairs and session moderators identified key areas of controversy and uncertainty in prostate cancer management and organized the sessions with multidisciplinary presentations and discussion. Throughout the meeting, experts responded to questions prepared by chairs and moderators to identify areas of agreement and controversy. RESULTS: The USPCC panel discussion and question responses for CSPC-related topics are presented. Key advances in CSPC management endorsed by USPCC experts included the development and clinical utilization of gene expression classifiers and artificial intelligence (AI) models for risk stratification and treatment selection in specific patient populations, the use of advanced imaging modalities in patients with clinically localized unfavorable intermediate or high-risk disease and those with biochemical recurrence, recommendations of doublet or triplet therapy for metastatic CSPC (mCSPC), and consideration of prostate and/or metastasis-directed radiation therapy in select patients with mCSPC. CONCLUSIONS: CSPC is a diverse disease with many therapeutic options and the potential for adverse outcomes associated with either undertreatment or overtreatment. Future studies are needed to validate and clinically integrate novel technologies, including genomics, AI, and advanced imaging, to optimize outcomes among patients with CSPC.
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- 2024
5. Distinct Challenges of Eruptive and Non-Eruptive Calcified Nodules in Percutaneous Coronary Intervention
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Galougahi, Keyvan Karimi, Shin, Doosup, Dakroub, Ali, Sakai, Koshiro, Singh, Mandeep, Malik, Sarah, Maehara, Akiko, Matsumura, Mitsuaki, Mintz, Gary, Spratt, James C., Khalique, Omar, Shlofmitz, Evan, Jeremias, Allen, Shlofmitz, Richard, and Ali, Ziad A.
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- 2024
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6. Assembling Comparison: Understanding Education Policy through Mobilities and Assemblage
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Lewis, Steven, author, Spratt, Rebecca, author, Lewis, Steven, and Spratt, Rebecca
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- 2024
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7. Biochemical Recurrence Surrogacy for Clinical Outcomes After Radiotherapy for Adenocarcinoma of the Prostate.
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Roy, Soumyajit, Romero, Tahmineh, Michalski, Jeff, Feng, Felix, Efstathiou, Jason, Lawton, Colleen, Bolla, Michel, Maingon, Philippe, de Reijke, Theo, Joseph, David, Ong, Wee, Sydes, Matthew, Dearnaley, David, Tree, Alison, Carrier, Nathalie, Nabid, Abdenour, Souhami, Luis, Incrocci, Luca, Heemsbergen, Wilma, Pos, Floris, Zapatero, Almudena, Guerrero, Araceli, Alvarez, Ana, San-Segundo, Carmen, Maldonado, Xavier, Reiter, Robert, Nickols, Nicholas, Ma, T, Farrell, Matthew, Neilsen, Beth, Juarez, Jesus, Deng, Jie, Vangala, Sitaram, Avril, Norbert, Jia, Angela, Zaorsky, Nicholas, Sun, Yilun, Spratt, Daniel, Kishan, Amar, Rettig, Matthew, Steinberg, Michael, and Valle, Luca
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Male ,Humans ,Prostate ,Prostatic Neoplasms ,Androgen Antagonists ,Prostate-Specific Antigen ,Adenocarcinoma - Abstract
PURPOSE: The surrogacy of biochemical recurrence (BCR) for overall survival (OS) in localized prostate cancer remains controversial. Herein, we evaluate the surrogacy of BCR using different surrogacy analytic methods. MATERIALS AND METHODS: Individual patient data from 11 trials evaluating radiotherapy dose escalation, androgen deprivation therapy (ADT) use, and ADT prolongation were obtained. Surrogate candidacy was assessed using the Prentice criteria (including landmark analyses) and the two-stage meta-analytic approach (estimating Kendalls tau and the R2). Biochemical recurrence-free survival (BCRFS, time from random assignment to BCR or any death) and time to BCR (TTBCR, time from random assignment to BCR or cancer-specific deaths censoring for noncancer-related deaths) were assessed. RESULTS: Overall, 10,741 patients were included. Dose escalation, addition of short-term ADT, and prolongation of ADT duration significantly improved BCR (hazard ratio [HR], 0.71 [95% CI, 0.63 to 0.79]; HR, 0.53 [95% CI, 0.48 to 0.59]; and HR, 0.54 [95% CI, 0.48 to 0.61], respectively). Adding short-term ADT (HR, 0.91 [95% CI, 0.84 to 0.99]) and prolonging ADT (HR, 0.86 [95% CI, 0.78 to 0.94]) significantly improved OS, whereas dose escalation did not (HR, 0.98 [95% CI, 0.87 to 1.11]). BCR at 48 months was associated with inferior OS in all three groups (HR, 2.46 [95% CI, 2.08 to 2.92]; HR, 1.51 [95% CI, 1.35 to 1.70]; and HR, 2.31 [95% CI, 2.04 to 2.61], respectively). However, after adjusting for BCR at 48 months, there was no significant treatment effect on OS (HR, 1.10 [95% CI, 0.96 to 1.27]; HR, 0.96 [95% CI, 0.87 to 1.06] and 1.00 [95% CI, 0.90 to 1.12], respectively). The patient-level correlation (Kendalls tau) for BCRFS and OS ranged between 0.59 and 0.69, and that for TTBCR and OS ranged between 0.23 and 0.41. The R2 values for trial-level correlation of the treatment effect on BCRFS and TTBCR with that on OS were 0.563 and 0.160, respectively. CONCLUSION: BCRFS and TTBCR are prognostic but failed to satisfy all surrogacy criteria. Strength of correlation was greater when noncancer-related deaths were considered events.
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- 2023
8. Method for portable, scalable, and performant GPU-accelerated simulation of multiphase compressible flow
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Radhakrishnan, Anand, Berre, Henry Le, Wilfong, Benjamin, Spratt, Jean-Sebastien, Rodriguez Jr., Mauro, Colonius, Tim, and Bryngelson, Spencer H.
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Physics - Fluid Dynamics ,Physics - Computational Physics - Abstract
Multiphase compressible flows are often characterized by a broad range of space and time scales. Thus entailing large grids and small time steps, simulations of these flows on CPU-based clusters can thus take several wall-clock days. Offloading the compute kernels to GPUs appears attractive but is memory-bound for standard finite-volume and -difference methods, damping speed-ups. Even when realized, faster GPU-based kernels lead to more intrusive communication and I/O times. We present a portable strategy for GPU acceleration of multiphase compressible flow solvers that addresses these challenges and obtains large speedups at scale. We use OpenACC for portable offloading of all compute kernels while maintaining low-level control when needed. An established Fortran preprocessor and metaprogramming tool, Fypp, enables otherwise hidden compile-time optimizations. This strategy exposes compile-time optimizations and high memory reuse while retaining readable, maintainable, and compact code. Remote direct memory access, realized via CUDA-aware MPI, reduces communication times. We implement this approach in the open-source solver MFC. Metaprogramming-based preprocessing results in an 8-times speedup of the most expensive kernels, 46% of peak FLOPs on NVIDIA GPUs, and high arithmetic intensity (about 10 FLOPs/byte). In representative simulations, a single A100 GPU is 300-times faster than an Intel Xeon CPU core, corresponding to a 9-times speedup for a single A100 compared to the entire CPU die. At the same time, near-ideal (97%) weak scaling is observed for at least 13824 GPUs on Summit. A strong scaling efficiency of 84% is retained for an 8-times increase in GPU count. Collective I/O, implemented via MPI3, helps ensure negligible contribution of data transfers. Large many-GPU simulations of compressible (solid-)liquid-gas flows demonstrate the practical utility of this strategy., Comment: 22 pages, 8 figures, 4 tables
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- 2023
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9. Use of the Decipher genomic classifier among men with prostate cancer in the United States.
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Zaorsky, Nicholas, Proudfoot, James, Jia, Angela, Zuhour, Raed, Vince, Randy, Liu, Yang, Zhao, Xin, Hu, Jim, Schussler, Nicola, Stevens, Jennifer, Bentler, Suzanne, Cress, Rosemary, Doherty, Jennifer, Durbin, Eric, Gershman, Susan, Cheng, Iona, Gonsalves, Lou, Hernandez, Brenda, Liu, Lihua, Morawski, Bożena, Schymura, Maria, Schwartz, Stephen, Ward, Kevin, Wiggins, Charles, Wu, Xiao-Cheng, Shoag, Jonathan, Ponsky, Lee, Dal Pra, Alan, Schaeffer, Edward, Ross, Ashley, Sun, Yilun, Davicioni, Elai, Petkov, Valentina, and Spratt, Daniel
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Male ,Humans ,United States ,Risk Assessment ,Prostatic Neoplasms ,Prostate-Specific Antigen ,Prostate ,Genomics - Abstract
BACKGROUND: Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer. METHODS: Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy. RESULTS: A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P
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- 2023
10. Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.
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Spratt, Daniel, Tang, Siyi, Sun, Yilun, Huang, Huei-Chung, Chen, Emmalyn, Mohamad, Osama, Armstrong, Andrew, Tward, Jonathan, Nguyen, Paul, Lang, Joshua, Zhang, Jingbin, Mitani, Akinori, Simko, Jeffry, DeVries, Sandy, van der Wal, Douwe, Pinckaers, Hans, Monson, Jedidiah, Campbell, Holly, Wallace, James, Ferguson, Michelle, Bahary, Jean-Paul, Schaeffer, Edward, Sandler, Howard, Tran, Phuoc, Rodgers, Joseph, Esteva, Andre, Yamashita, Rikiya, and Feng, Felix
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Male ,Humans ,Prostatic Neoplasms ,Androgen Antagonists ,Prostate-Specific Antigen ,Artificial Intelligence ,Hormones - Abstract
BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized prostate cancer. However, ADT can negatively impact quality of life, and there remain no validated predictive models to guide its use. METHODS: We used digital pathology images from pretreatment prostate tissue and clinical data from 5727 patients enrolled in five phase 3 randomized trials, in which treatment was radiotherapy with or without ADT, as our data source to develop and validate an artificial intelligence (AI)–derived predictive patient-specific model that would determine which patients would develop the primary end point of distant metastasis. The model used baseline data to provide a binary output that a given patient will likely benefit from ADT or not. After the model was locked, validation was performed using data from NRG Oncology/Radiation Therapy Oncology Group (RTOG) 9408 (n=1594), a trial that randomly assigned men to radiotherapy plus or minus 4 months of ADT. Fine–Gray regression and restricted mean survival times were used to assess the interaction between treatment and the predictive model and within predictive model–positive, i.e., benefited from ADT, and –negative subgroup treatment effects. RESULTS: Overall, in the NRG/RTOG 9408 validation cohort (14.9 years of median follow-up), ADT significantly improved time to distant metastasis. Of these enrolled patients, 543 (34%) were model positive, and ADT significantly reduced the risk of distant metastasis compared with radiotherapy alone. Of 1051 patients who were model negative, ADT did not provide benefit. CONCLUSIONS: Our AI-based predictive model was able to identify patients with a predominantly intermediate risk for prostate cancer likely to benefit from short-term ADT. (Supported by a grant [U10CA180822] from NRG Oncology Statistical and Data Management Center, a grant [UG1CA189867] from NCI Community Oncology Research Program, a grant [U10CA180868] from NRG Oncology Operations, and a grant [U24CA196067] from NRG Specimen Bank from the National Cancer Institute and by Artera, Inc. ClinicalTrials.gov numbers NCT00767286, NCT00002597, NCT00769548, NCT00005044, and NCT00033631.)
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- 2023
11. Expect the unexpected: An insight into museum programming
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Wyatt-Spratt, Neridah
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- 2024
12. Artificial intelligence applications in prostate cancer
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Baydoun, Atallah, Jia, Angela Y., Zaorsky, Nicholas G., Kashani, Rojano, Rao, Santosh, Shoag, Jonathan E., Vince, Jr, Randy A., Bittencourt, Leonardo Kayat, Zuhour, Raed, Price, Alex T., Arsenault, Theodore H., and Spratt, Daniel E.
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- 2024
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13. Multivalent insulin receptor activation using insulin–DNA origami nanostructures
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Spratt, Joel, Dias, José M., Kolonelou, Christina, Kiriako, Georges, Engström, Enya, Petrova, Ekaterina, Karampelias, Christos, Cervenka, Igor, Papanicolaou, Natali, Lentini, Antonio, Reinius, Björn, Andersson, Olov, Ambrosetti, Elena, Ruas, Jorge L., and Teixeira, Ana I.
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- 2024
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14. A novel prostate cancer subtyping classifier based on luminal and basal phenotypes
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Weiner, Adam B, Liu, Yang, Hakansson, Alex, Zhao, Xin, Proudfoot, James A, Ho, Julian, Zhang, Jj H, Li, Eric V, Karnes, R Jeffrey, Den, Robert B, Kishan, Amar U, Reiter, Robert E, Hamid, Anis A, Ross, Ashely E, Tran, Phuoc T, Davicioni, Elai, Spratt, Daniel E, Attard, Gerhardt, Lotan, Tamara L, Lee Kiang Chua, Melvin, Sweeney, Christopher J, and Schaeffer, Edward M
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Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Prostate Cancer ,Aging ,Genetics ,Clinical Research ,Urologic Diseases ,2.1 Biological and endogenous factors ,Aetiology ,Humans ,Male ,Prostatic Neoplasms ,Receptors ,Androgen ,Docetaxel ,Androgen Antagonists ,Gene Expression Profiling ,Phenotype ,Biomarkers ,Tumor ,Prognosis ,biomarkers ,gene expression ,gene expression profiling ,genetics ,humans ,pathology ,prognosis ,prostatic neoplasms ,tumor ,Public Health and Health Services ,Oncology & Carcinogenesis ,Oncology and carcinogenesis ,Public health - Abstract
BackgroundProstate cancer (PCa) is a clinically heterogeneous disease. The creation of an expression-based subtyping model based on prostate-specific biological processes was sought.MethodsUnsupervised machine learning of gene expression profiles from prospectively collected primary prostate tumors (training, n = 32,000; evaluation, n = 68,547) was used to create a prostate subtyping classifier (PSC) based on basal versus luminal cell expression patterns and other gene signatures relevant to PCa biology. Subtype molecular pathways and clinical characteristics were explored in five other clinical cohorts.ResultsClustering derived four subtypes: luminal differentiated (LD), luminal proliferating (LP), basal immune (BI), and basal neuroendocrine (BN). LP and LD tumors both had higher androgen receptor activity. LP tumors also had a higher expression of cell proliferation genes, MYC activity, and characteristics of homologous recombination deficiency. BI tumors possessed significant interferon γactivity and immune infiltration on immunohistochemistry. BN tumors were characterized by lower androgen receptor activity expression, lower immune infiltration, and enrichment with neuroendocrine expression patterns. Patients with LD tumors had less aggressive tumor characteristics and the longest time to metastasis after surgery. Only patients with BI tumors derived benefit from radiotherapy after surgery in terms of time to metastasis (hazard ratio [HR], 0.09; 95% CI, 0.01-0.71; n = 855). In a phase 3 trial that randomized patients with metastatic PCa to androgen deprivation with or without docetaxel (n = 108), only patients with LP tumors derived survival benefit from docetaxel (HR, 0.21; 95% CI, 0.09-0.51).ConclusionsWith the use of expression profiles from over 100,000 tumors, a PSC was developed that identified four subtypes with distinct biological and clinical features.Plain language summaryProstate cancer can behave in an indolent or aggressive manner and vary in how it responds to certain treatments. To differentiate prostate cancer on the basis of biological features, we developed a novel RNA signature by using data from over 100,000 prostate tumors-the largest data set of its kind. This signature can inform patients and physicians on tumor aggressiveness and susceptibilities to treatments to help personalize cancer management.
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- 2023
15. Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort CollaborativeResearch in context
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Timothy Bergquist, Johanna Loomba, Emily Pfaff, Fangfang Xia, Zixuan Zhao, Yitan Zhu, Elliot Mitchell, Biplab Bhattacharya, Gaurav Shetty, Tamanna Munia, Grant Delong, Adbul Tariq, Zachary Butzin-Dozier, Yunwen Ji, Haodong Li, Jeremy Coyle, Seraphina Shi, Rachael V. Philips, Andrew Mertens, Romain Pirracchio, Mark van der Laan, John M. Colford, Jr., Alan Hubbard, Jifan Gao, Guanhua Chen, Neelay Velingker, Ziyang Li, Yinjun Wu, Adam Stein, Jiani Huang, Zongyu Dai, Qi Long, Mayur Naik, John Holmes, Danielle Mowery, Eric Wong, Ravi Parekh, Emily Getzen, Jake Hightower, Jennifer Blase, Ataes Aggarwal, Joseph Agor, Amera Al-Amery, Oluwatobiloba Aminu, Adit Anand, Corneliu Antonescu, Mehak Arora, Sayed Asaduzzaman, Tanner Asmussen, Mahdi Baghbanzadeh, Frazier Baker, Bridget Bangert, Laila Bekhet, Jenny Blase, Brian Caffo, Hao Chang, Zeyuan Chen, Jiandong Chen, Jeffrey Chiang, Peter Cho, Robert Cockrell, Parker Combs, Ciara Crosby, Ran Dai, Anseh Danesharasteh, Elif Yildirim, Ryan Demilt, Kaiwen Deng, Sanjoy Dey, Rohan Dhamdhere, Andrew Dickson, Phoebe Dijour, Dong Dinh, Richard Dixon, Albi Domi, Souradeep Dutta, Mirna Elizondo, Zeynep Ertem, Solomon Feuerwerker, Danica Fliss, Jennifer Fowler, Sunyang Fu, Kelly Gardner, Neil Getty, Mohamed Ghalwash, Logan Gloster, Phil Greer, Yuanfang Guan, Colby Ham, Samer Hanoudi, Jeremy Harper, Nathaniel Hendrix, Leeor Hershkovich, Junjie Hu, Yu Huang, Tongtong Huang, Junguk Hur, Monica Isgut, Hamid Ismail, Grant Izmirlian, Kuk Jang, Christianah Jemiyo, Hayoung Jeong, Xiayan Ji, Ming Jiang, Sihang Jiang, Xiaoqian Jiang, Yuye Jiang, Akin Johnson, Zach Analyst, Saarthak Kapse, Uri Kartoun, Dukka KC, Zahra Fard, Tim Kosfeld, Spencer Krichevsky, Mike Kuo, Dale Larie, Lauren Lederer, Shan Leng, Hongyang Li, Jianfu Li, Tiantian Li, Xinwen Liang, Hengyue Liang, Feifan Liu, Daniel Liu, Gang Luo, Ravi Madduri, Vithal Madhira, Shivali Mani, Farzaneh Mansourifard, Robert Matson, Vangelis Metsis, Pablo Meyer, Catherine Mikhailova, Dante Miller, Christopher Milo, Gourav Modanwal, Ronald Moore, David Morgenthaler, Rasim Musal, Vinit Nalawade, Rohan Narain, Saideep Narendrula, Alena Obiri, Satoshi Okawa, Chima Okechukwu, Toluwanimi Olorunnisola, Tim Ossowski, Harsh Parekh, Jean Park, Saaya Patel, Jason Patterson, Chetan Paul, Le Peng, Diana Perkins, Suresh Pokharel, Dmytro Poplavskiy, Zach Pryor, Sarah Pungitore, Hong Qin, Salahaldeen Rababa, Mahbubur Rahman, Elior Rahmani, Gholamali Rahnavard, Md Raihan, Suraj Rajendran, Sarangan Ravichandran, Chandan Reddy, Abel Reyes, Ali Roghanizad, Sean Rouffa, Xiaoyang Ruan, Arpita Saha, Sahil Sawant, Melody Schiaffino, Diego Seira, Saurav Sengupta, Ruslan Shalaev, Linh Shinguyen, Karnika Singh, Soumya Sinha, Damien Socia, Halen Stalians, Charalambos Stavropoulos, Jan Strube, Devika Subramanian, Jiehuan Sun, Ju Sun, Chengkun Sun, Prathic Sundararajan, Salmonn Talebi, Edward Tawiah, Jelena Tesic, Mikaela Thiess, Raymond Tian, Luke Torre-Healy; Ming-Tse Tsai, David Tyus, Madhurima Vardhan, Benjamin Walzer, Jacob Walzer, Junda Wang, Lu Wang, Will Wang, Jonathan Wang, Yisen Wang, Chad Weatherly, Fanyou Wu, Yifeng Wu, Hao Yan, Zhichao Yang, Biao Ye, Rui Yin, Changyu Yin, Yun Yoo, Albert You, June Yu, Martin Zanaj, Zachary Zaiman, Kai Zhang, Xiaoyi Zhang, Tianmai Zhang, Degui Zhi, Yishan Zhong, Huixue Zhou, Andrea Zhou, Yuanda Zhu, Sophie Zhu, Meredith Adams, Caleb Alexander, Benjamin Amor, Alfred Anzalone, Benjamin Bates, Will Beasley, Tellen Bennett, Mark Bissell, Eilis Boudreau, Samuel Bozzette, Katie Bradwell, Carolyn Bramante, Don Brown, Penny Burgoon, John Buse, Tiffany Callahan, Kenrick Cato, Scott Chapman, Christopher Chute, Jaylyn Clark, Marshall Clark, Will Cooper, Lesley Cottrell, Karen Crowley, Mariam Deacy, Christopher Dillon, David Eichmann, Mary Emmett, Rebecca Erwin-Cohen, Patricia Francis, Evan French, Rafael Fuentes, Davera Gabriel, Joel Gagnier, Nicole Garbarini, Jin Ge, Kenneth Gersing, Andrew Girvin, Valery Gordon, Alexis Graves, Justin Guinney, Melissa Haendel, J.W. Hayanga, Brian Hendricks, Wenndy Hernandez, Elaine Hill, William Hillegass, Stephanie Hong, Dan Housman, Robert Hurley, Jessica Islam, Randeep Jawa, Steve Johnson, Rishi Kamaleswaran, Warren Kibbe, Farrukh Koraishy, Kristin Kostka, Michael Kurilla, Adam Lee, Harold Lehmann, Hongfang Liu, Charisse Madlock-Brown; Sandeep Mallipattu, Amin Manna, Federico Mariona, Emily Marti, Greg Martin, Jomol Mathew, Diego Mazzotti, Julie McMurry, Hemalkumar Mehta, Sam Michael, Robert Miller, Leonie Misquitta, Richard Moffitt, Michele Morris, Kimberly Murray, Lavance Northington, Shawn O’Neil, Amy Olex, Matvey Palchuk, Brijesh Patel, Rena Patel, Philip Payne, Jami Pincavitch, Lili Portilla, Fred Prior, Saiju Pyarajan, Lee Pyles, Nabeel Qureshi, Peter Robinson, Joni Rutter, Ofer Sadan, Nasia Safdar, Amit Saha, Joel Saltz, Mary Saltz, Clare Schmitt, Soko Setoguchi, Noha Sharafeldin, Anjali Sharathkumar, Usman Sheikh, Hythem Sidky, George Sokos, Andrew Southerland, Heidi Spratt, Justin Starren, Vignesh Subbian, Christine Suver, Cliff Takemoto, Meredith Temple-O'Connor, Umit Topaloglu, Satyanarayana Vedula, Anita Walden, Kellie Walters, Cavin Ward-Caviness, Adam Wilcox, Ken Wilkins, Andrew Williams, Chunlei Wu, Elizabeth Zampino, Xiaohan Zhang, and Richard Zhu
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Long COVID ,PASC ,Machine learning ,COVID-19 ,Evaluation ,Community challenge ,Medicine ,Medicine (General) ,R5-920 - Abstract
Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.
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- 2024
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16. Impact of Anatomical and Viability-Guided Completeness of Revascularization on Clinical Outcomes in Ischemic Cardiomyopathy
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Perera, Divaka, Chiribiri, Amedeo, Carr-White, Gerry, Pavlidis, Antonis, Redwood, Simon, Clapp, Brian, Rinaldi, Aldo, Rahman, Haseeb, Briceno, Natalia, Arnold, Sophie, Raynsford, Amy, Petrie, Mark, McEntegart, Margaret, Watkins, Stuart, Shaukat, Aadil, Rocchiccioli, Paul, Cowan, Louise, Weerackody, Roshan, Davies, Ceri, Smith, Elliot, Modi, Bhavik, O’Kane, Peter, Din, Jehangir, Hinton, Jonathon, Greenwood, John, Blaxill, Jonathan, Mozid, Abdul, Anderson, Michelle, Dixon, Lana, Walsh, Simon, Spence, Mark, Glover, Patricia, Edwards, Richard, McDiarmid, Adam, Egred, Mohaned, Stevenson, Hannah, Amin-Youssef, George, Shah, Ajay, McDonagh, Theresa, Byrne, Jonathan, Pareek, Nilesh, Breeze, Jonathan, Gershlick, Anthony, McCann, Gerald, Ladwiniec, Andrew, Squire, Iain, Alexander, Donna, De Silva, Kalpa, Strange, Julian, Johnson, Tom, Nightingale, Angus, Gallego, Laura, Spratt, James, Cosgrove, Claudia, Willia, Rupert, Firoozi, Sam, Lim, Pitt, Conway, Dwayne, Swoboda, Peter, Brooksby, Paul, Cotton, James, Horton, Richard, Metherell, Stella, Hogrefe, Kai, Cheng, Adrian, Sidgwick, Sian, Lockie, Tim, Patel, Niket, Rakhit, Roby, Ahmed, Fozia, Hendry, Cara, Fath-Odoubadi, Farzin, Fraser, Douglas, Mamas, Mamas, Behan, Miles, Japp, Alan, Jenkins, Nicholas, McClure, Sam, Martin, Karen, Abdelaal, Eltigani, Sarma, Jaydeep, Sastry, Sanjay, Riley, Jo, Magapu, Pradeep, Stables, Rod, Wright, David, Mahmoudi, Michael, Flett, Andrew, Curzen, Nick, Gough, Sam, Nicholas, Zoe, Ludman, Andrew, Kurdi, Hibba, Keenan, Sam, Thorpe, Kevin, Banerjee, Prithwish, Tapp, Luke, Panicker, Abeesh, de Belder, Mark, Thambyrajah, Jeet, Swanson, Neil, Kukreja, Neville, Lynch, Mary, Viswanathan, Girish, Jones, Elaine, Norman, Sarah, Routledge, Helen, Trevelyan, Jasper, Pegge, Nick, Dhamrait, Sukhbir, Wells, Tim, Sinha, Manas, Galasko, Gavin, Cassidy, Christopher, Edwards, Tim, Iqbal, Javed, Witherow, Fraser, Lee, Kaeng, Beattie, James, Pitt, Mike, Gunn, Julian, Al-Mohammad, Abdallah, Denney, Helen, Griffiths, Huw, Kalra, Paul, Gray, Tim, Sobolewska, Jolanta, Ramcharitar, Steve, McCafferty, Laura, Martin, Thomas, Irving, John, Iskandar, Zaid, Glover, Jason, Beynon, James, Pye, Maurice, Megarry, Simon, Das, Paul, Bellamy, Chris, Ezad, Saad M., Dodd, Matthew, Didagelos, Matthaios, Sidik, Novalia, Li Kam Wa, Matthew, Morgan, Holly P., Walsh, Simon J., Spratt, James C., Ludman, Peter, Clayton, Tim, and Petrie, Mark C.
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- 2024
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17. Symptoms as a Predictor of the Placebo-Controlled Efficacy of PCI in Stable Coronary Artery Disease
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Rajkumar, Christopher, Foley, Michael, Ahmed-Jushuf, Fiyyaz, Simader, Florentina, Ganesananthan, Sashiananthan, Wang, Danqi, Mohsin, Muhammad, Pathimagaraj, Rachel, Macierzanka, Krzysztof, Petraco, Ricardo, Khamis, Ramzi, Cole, Graham, Howard, James, Mayet, Jamil, Francis, Darrel, Kokhar, Arif, Gohar, Aisha, Lampadakis, Ioannis, Seligman, Henry, Kaura, Amit, Nijjer, Sukhjinder, Sen, Sayan, Ramrakha, Punit, Kaprielian, Raffi, Malik, Iqbal, Khan, Masood, Sethi, Amarjit, Foale, Rodney, Keeble, Thomas, Tang, Kare, Davies, John, Gamma, Reto, Clesham, Gerald, Dungu, Jason, Kabir, Alamgir, Nazri, Shah Mohd, O’Kane, Peter, Hinton, Jonathan, Din, Jehangir, Nowbar, Alexandra, Kotecha, Tushar, Haworth, Peter, Spratt, James, Williams, Rupert, Cosgrove, Claudia, Lim, Pitt, Routledge, Helen, Mughal, Lal, Trevelyan, Jasper, Sinha, Manas, Curzen, Nick, Wilkinson, James, Sirohi, Rohit, Calver, Alison, Rawlins, John, Jabbour, Richard, Ruparelia, Neil, Sehmi, Joban, Kinnaird, Tim, Abdul, Fairoz, Panoulas, Vasileios, Collier, David, Thornton, George, Sohaib, Afzal, Al-Lamee, Rasha K., Simader, Florentina A., Rajkumar, Christopher A., Foley, Michael J., Chotai, Shayna, Bual, Nina, Khokhar, Arif, Pathimagaraj, Rachel H., Davies, John R., Keeble, Tom R., O’Kane, Peter D., Spratt, James C., Nijjer, Sukhjinder S., Howard, James P., Harrell, Frank E., Jr., Francis, Darrel P., and Shun-Shin, Matthew J.
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- 2024
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18. A Synoptic-Scale Comparison of Satellite Yukon River Mouth Temperature to In-Situ and Reanalysis Data During 2003-2020.
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Rachel Spratt, Jorge Vazquez-Cuervo, and Dustin Carroll
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- 2024
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19. Venoarterial Extracorporeal Membrane Oxygenation for 'Protected' Percutaneous Coronary Intervention Secondary to Refractory Polymorphic Ventricular Tachycardia and Cardiac Arrest
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Jordan D. Phillips, John R. Spratt, Calvin Y. Choi, Salvatore T. Scali, and Marc O. Maybauer
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extracorporeal cardiopulmonary resuscitation (ecpr) ,extracorporeal life support (ecls) ,mechanical circulatory support (mcs) ,protected percutaneous coronary intervention (pci) ,refractory polymorphic ventricular tachycardia (pvt) ,venoarterial extracorporeal membrane oxygenation (v-a ecmo) ,Anesthesiology ,RD78.3-87.3 ,Diseases of the circulatory (Cardiovascular) system ,RC666-701 - Abstract
We present a case of cardiogenic shock secondary to refractory polymorphic ventricular tachycardia associated with coronary ischemia resulting in cardiac arrest. Following the return of spontaneous circulation, the patient was cannulated for peripheral venoarterial extracorporeal membrane oxygenation (V-A ECMO) in anticipation of high-risk “protected” percutaneous coronary intervention (PCI). Under full V-A ECMO support, inotropes and vasopressors were weaned off, and the patient underwent uneventful PCI of left circumflex and obtuse marginal lesions. After 48 hours, the patient was decannulated and could be discharged home alive 16 days after his initial cardiac arrest.
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- 2024
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20. Effects of Aerobic Exercise in the Intensive Care Unit on Patient-Reported Physical Function and Mental Health Outcomes in Severely Burned Children-A Multicenter Prospective Randomized Trial.
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Palackic, Alen, Rego, Andrea, Parry, Ingrid, Sen, Soman, Branski, Ludwik, Hallman, Taylor, Spratt, Heidi, Lee, Jong, Herndon, David, Wolf, Steven, and Suman, Oscar
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burns ,exercising ,intensive care unit ,rehabilitation - Abstract
UNLABELLED: Severe burns are life-altering and can have lasting effects on patients physical and mental health. Alterations in physical function, changes in appearance, and psychological disturbances resulting from severe burns are especially concerning in children, as they are still in the early stages of identity formation. Exercise in the nonburn population has been shown to improve quality of life and result in better physical and mental status. However, the effect of early exercise on the quality of life in pediatric burn patients requires more research. METHODS: Forty-eight children between the ages of seven and seventeen with ≥30% total body surface area (TBSA) burn were randomized in a 1:2 fashion to receive treatment with standard-of-care (SOC) or standard-of-care plus exercise (SOC+Ex). Surveys administered at admission and discharge collected patient-reported information regarding physical and mental health outcomes. The results are given as means +/- standard deviation. Significance was set at p < 0.05. RESULTS: The average age of the SOC and SOC+Ex groups were 12 ± 3 and 13 ± 4 years, respectively. The average %TBSA burned in the SOC and SOC+Ex groups were 54 ± 17 and 48 ± 14, respectively. The SOC+Ex group averaged 10 ± 9 exercise sessions (range of 1 to 38 sessions) with an attendance rate of 25% (10 sessions out of 40 BICU days). Both groups demonstrated significant improvement in patient-reported physical and mental outcomes during hospital admission (p < 0.05) However, additional exercise did not exhibit any additional benefits for measured levels. CONCLUSIONS: Our recommendation is for all pediatric patients in the BICU to continue with the SOC and consult with their physician over the benefits of additional aerobic exercise. This study suggests that perhaps there is potential for increasing the amount of exercise that can be administered to pediatric burn survivors beyond SOC as we did not find aerobic exercise to be of any harm to any patients if it is performed properly and under supervision.
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- 2023
21. Sequencing of Androgen-Deprivation Therapy of Short Duration With Radiotherapy for Nonmetastatic Prostate Cancer (SANDSTORM): A Pooled Analysis of 12 Randomized Trials
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Martin, Ting, Sun, Yilun, Malone, Shawn, Roach, Mack, Dearnaley, David, Pisansky, Thomas M, Feng, Felix Y, Sandler, Howard M, Efstathiou, Jason A, Syndikus, Isabel, Hall, Emma C, Tree, Alison C, Sydes, Matthew R, Cruickshank, Claire, Roy, Soumyajit, Bolla, Michel, Maingon, Philippe, De Reijke, Theo, Nabid, Abdenour, Carrier, Nathalie, Souhami, Luis, Zapatero, Almudena, Guerrero, Araceli, Alvarez, Ana, San-Segundo, Carmen Gonzalez, Maldonado, Xavier, Romero, Tahmineh, Steinberg, Michael L, Valle, Luca F, Rettig, Matthew B, Nickols, Nicholas G, Shoag, Jonathan E, Reiter, Robert E, Zaorsky, Nicholas G, Jia, Angela Y, Garcia, Jorge A, Spratt, Daniel E, Kishan, Amar U, and Investigators, on behalf of the Meta-Analysis of Randomized Trials in Cancer of the Prostate Consortium
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Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Aging ,Clinical Research ,Patient Safety ,Urologic Diseases ,Cancer ,Prostate Cancer ,Evaluation of treatments and therapeutic interventions ,6.4 Surgery ,Good Health and Well Being ,Male ,Humans ,Prostatic Neoplasms ,Androgen Antagonists ,Androgens ,Randomized Controlled Trials as Topic ,Prostate-Specific Antigen ,Meta-Analysis of Randomized Trials in Cancer of the Prostate (MARCAP) Consortium Investigators ,Oncology & Carcinogenesis ,Oncology and carcinogenesis - Abstract
PurposeThe sequencing of androgen-deprivation therapy (ADT) with radiotherapy (RT) may affect outcomes for prostate cancer in an RT-field size-dependent manner. Herein, we investigate the impact of ADT sequencing for men receiving ADT with prostate-only RT (PORT) or whole-pelvis RT (WPRT).Materials and methodsIndividual patient data from 12 randomized trials that included patients receiving neoadjuvant/concurrent or concurrent/adjuvant short-term ADT (4-6 months) with RT for localized disease were obtained from the Meta-Analysis of Randomized trials in Cancer of the Prostate consortium. Inverse probability of treatment weighting (IPTW) was performed with propensity scores derived from age, initial prostate-specific antigen, Gleason score, T stage, RT dose, and mid-trial enrollment year. Metastasis-free survival (primary end point) and overall survival (OS) were assessed by IPTW-adjusted Cox regression models, analyzed independently for men receiving PORT versus WPRT. IPTW-adjusted Fine and Gray competing risk models were built to evaluate distant metastasis (DM) and prostate cancer-specific mortality.ResultsOverall, 7,409 patients were included (6,325 neoadjuvant/concurrent and 1,084 concurrent/adjuvant) with a median follow-up of 10.2 years (interquartile range, 7.2-14.9 years). A significant interaction between ADT sequencing and RT field size was observed for all end points (P interaction < .02 for all) except OS. With PORT (n = 4,355), compared with neoadjuvant/concurrent ADT, concurrent/adjuvant ADT was associated with improved metastasis-free survival (10-year benefit 8.0%, hazard ratio [HR], 0.65; 95% CI, 0.54 to 0.79; P < .0001), DM (subdistribution HR, 0.52; 95% CI, 0.33 to 0.82; P = .0046), prostate cancer-specific mortality (subdistribution HR, 0.30; 95% CI, 0.16 to 0.54; P < .0001), and OS (HR, 0.69; 95% CI, 0.57 to 0.83; P = .0001). However, in patients receiving WPRT (n = 3,049), no significant difference in any end point was observed in regard to ADT sequencing except for worse DM (HR, 1.57; 95% CI, 1.20 to 2.05; P = .0009) with concurrent/adjuvant ADT.ConclusionADT sequencing exhibits a significant impact on clinical outcomes with a significant interaction with field size. Concurrent/adjuvant ADT should be the standard of care where short-term ADT is indicated in combination with PORT.
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- 2023
22. The magnetic structure and field dependence of the cycloid phase mediating the spin reorientation transition in Ca$_3$Ru$_2$O$_7$
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Faure, Q., Dashwood, C. D., Colin, C. V., Johnson, R. D., Ressouche, E., Stenning, G. B. G., Spratt, J., McMorrow, D. F., and Perry, R. S.
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Condensed Matter - Strongly Correlated Electrons - Abstract
We report a comprehensive experimental investigation of the magnetic structure of the cycloidal phase in Ca$_3$Ru$_2$O$_7$, which mediates the spin reorientation transition, and establishes its magnetic phase diagram. In zero applied field, single-crystal neutron diffraction data confirms the scenario deduced from an earlier resonant x-ray scattering study: between $46.7$~K $< T < 49.0$~K the magnetic moments form a cycloid in the $a-b$ plane with a propagation wavevector of $(\delta,0,1)$ with $\delta \simeq 0.025$ and an ordered moment of about 1 $\mu_{\rm{B}}$, with the eccentricity of the cycloid evolving with temperature. In an applied magnetic field applied parallel to the $b$-axis, the intensity of the $(\delta,0,1)$ satellite peaks decreases continuously up to about $\mu_0 H \simeq 5$ T, above which field the system becomes field polarised. Both the eccentricity of the cycloid and the wavevector increase with field, the latter suggesting an enhancement of the anti$-$symmetric Dzyaloshinskii$-$Moriya interaction via magnetostriction effects. Transitions between the various low-temperature magnetic phases have been carefully mapped out using magnetometry and resistivity. The resulting phase diagram reveals that the cycloid phase exists in a temperature window that expands rapidly with increasing field, before transitioning to a polarised paramagnetic state at 5 T. High-field magnetoresistance measurements show that below $T\simeq 70$ K the resistivity increases continuously with decreasing temperature, indicating the inherent insulating nature at low temperatures of our high-quality, untwinned, single-crystals. We discuss our results with reference to previous reports of the magnetic phase diagram of Ca$_3$Ru$_2$O$_7$ that utilised samples which were more metallic and/or poly-domain., Comment: 12 pages, 11 figures
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- 2022
23. Impact of sequencing of androgen receptor-signaling inhibition and radiotherapy in prostate cancer: importance of homologous recombination disruption
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Allen, Steven G., Zhang, Chao, Malone, Shawn, Roy, Soumyajit, Dess, Robert T., Jackson, William C., Mehra, Rohit, Speers, Corey, Chinnaiyan, Arul M., Sun, Yilun, and Spratt, Daniel E.
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- 2023
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24. Association of PSA kinetics after testosterone recovery with subsequent recurrence: secondary analysis of a phase III randomized controlled trial
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Roy, Soumyajit, Kishan, Amar U., Morgan, Scott C., Martinka, Levi, Spratt, Daniel E., Sun, Yilun, Malone, Julia, Grimes, Scott, Citrin, Deborah E., and Malone, Shawn
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- 2023
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25. Generalisable long COVID subtypes: Findings from the NIH N3C and RECOVER programmes
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Reese, Justin T, Blau, Hannah, Casiraghi, Elena, Bergquist, Timothy, Loomba, Johanna J, Callahan, Tiffany J, Laraway, Bryan, Antonescu, Corneliu, Coleman, Ben, Gargano, Michael, Wilkins, Kenneth J, Cappelletti, Luca, Fontana, Tommaso, Ammar, Nariman, Antony, Blessy, Murali, TM, Caufield, J Harry, Karlebach, Guy, McMurry, Julie A, Williams, Andrew, Moffitt, Richard, Banerjee, Jineta, Solomonides, Anthony E, Davis, Hannah, Kostka, Kristin, Valentini, Giorgio, Sahner, David, Chute, Christopher G, Madlock-Brown, Charisse, Haendel, Melissa A, Robinson, Peter N, Consortium, N3C, Spratt, Heidi, Visweswaran, Shyam, Flack, Joseph Eugene, Yoo, Yun Jae, Gabriel, Davera, Alexander, G Caleb, Mehta, Hemalkumar B, Liu, Feifan, Miller, Robert T, Wong, Rachel, Hill, Elaine L, Consortium, RECOVER, Thorpe, Lorna E, and Divers, Jasmin
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Biomedical and Clinical Sciences ,Clinical Sciences ,Coronaviruses ,Emerging Infectious Diseases ,Networking and Information Technology R&D (NITRD) ,Infectious Diseases ,Precision Medicine ,Machine Learning and Artificial Intelligence ,Good Health and Well Being ,Humans ,COVID-19 ,Disease Progression ,Post-Acute COVID-19 Syndrome ,SARS-CoV-2 ,N3C Consortium ,RECOVER Consortium ,Human Phenotype Ontology ,Long COVID ,Machine learning ,Precision medicine ,Semantic similarity ,Public Health and Health Services ,Clinical sciences ,Epidemiology - Abstract
BackgroundStratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.MethodsWe present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.FindingsWe found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.InterpretationSemantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.FundingNIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.
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- 2023
26. Epidermodysplasia Verruciformis in CADINS Disease: Expanding the Phenotype
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Aggarwal, Ridhima, Spratt, Alison R., Snow, Andrew L., and Vignesh, Pandiarajan
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- 2024
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27. NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study
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Reese, Justin T, Coleman, Ben, Chan, Lauren, Blau, Hannah, Callahan, Tiffany J, Cappelletti, Luca, Fontana, Tommaso, Bradwell, Katie R, Harris, Nomi L, Casiraghi, Elena, Valentini, Giorgio, Karlebach, Guy, Deer, Rachel, McMurry, Julie A, Haendel, Melissa A, Chute, Christopher G, Pfaff, Emily, Moffitt, Richard, Spratt, Heidi, Singh, Jasvinder A, Mungall, Christopher J, Williams, Andrew E, and Robinson, Peter N
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Microbiology ,Biological Sciences ,Emerging Infectious Diseases ,Coronaviruses ,Lung ,Infectious Diseases ,Kidney Disease ,Good Health and Well Being ,Acute Kidney Injury ,Anti-Inflammatory Agents ,Non-Steroidal ,COVID-19 ,COVID-19 Testing ,Cohort Studies ,Humans ,Pandemics ,Retrospective Studies ,NSAIDs ,Cyclooxygenase inhibitors ,Observational study ,Medical Microbiology ,Virology - Abstract
BackgroundNon-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use.MethodsA 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis.ResultsLogistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations.ConclusionsStudy interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.
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- 2022
28. Why Policy, Why Comparison?
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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29. Why Is Policy?
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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30. Policy Mobilities and Assemblage Theory: A Conjoined Approach
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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31. (Re)Assembling Comparison
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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32. Front Matter
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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33. References
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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34. Notes
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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35. How to Research Policy?
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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36. Policy Mobilities and Assemblage Theory: Key Concepts
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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37. Index
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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38. Where (and When) Is Policy?
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Lewis, Steven, primary and Spratt, Rebecca, additional
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- 2024
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39. Focused Shear Wave Beam Propagation in Tissue-Mimicking Phantoms.
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John M. Cormack, Yu-Hsuan Chao, Branch T. Archer, Kang Kim, Kyle S. Spratt, and Mark F. Hamilton
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- 2024
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40. Rollout of a statewide Australian telestroke network including virtual reality training is associated with improved hyperacute stroke workflow metrics and thrombolysis rate
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Carlos Garcia-Esperon, Steven Maltby, Ken Butcher, Md Golam Hasnain, Beng Lim Alvin Chew, William O'Brien, James W. Evans, Timothy Ang, Leon Edwards, Christopher Blair, Candice Delcourt, Mark W. Parsons, Ferdinand Miteff, Jason Dizon, David Lambkin, Daniel Barker, Murielle G. Kluge, John H. Wiggers, Christopher R. Levi, Neil J. Spratt, Frederick Rohan Walker, The Virtual Reality NSW Telestroke Group, Chris Oldmeadow, Rachel Peake, Jaclyn Birnie, Amanda Buzio, Jennifer Steel, Kim Parrey, Emma McCartney, Thembelihle Mathe, Matthew Shepherd, Lisa Dark, James Hughes, Kate Jackson, Claire Gill, Courtney Dixon, Skye Russell, and Natalie Wilson
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telestroke ,virtual reality ,medical education ,stroke workflow ,thrombolysis ,Medicine - Abstract
BackgroundTelestroke networks aim to address variability in both quality and access to stroke care in rural areas, by providing remote access to expert stroke neurologists. Implementation of telestroke requires adaptation of workflow processes and education. We previously developed virtual reality (VR) workflow training and documented acceptability, utility and feasibility. The effects on acute stroke treatment metrics have not been previously described.AimsThe overall aim was to improve hyperacute stroke metrics and shorten the time-to-reperfusion therapy administration in rural settings.MethodsThis study applies a natural experiment approach, collecting stroke metric data during transition from a pre-existing pilot to a statewide telestroke service at five rural hospitals. Pre- and post-intervention data included baseline patient demographics and assessment, diagnosis, and treatment delivery metrics. The primary study outcome was door-to-decision time (thrombolysis and endovascular thrombectomy). Secondary outcomes included door-to-computerized tomography time, door-to-thrombolysis time and proportion of patients receiving thrombolysis or thrombectomy treatment. Usage data relating to the VR stroke workflow training of interprofessional healthcare professionals was automatically captured via Wi-Fi. Statistical comparisons of clinical metrics between the pre- and post-intervention time periods, defined as the timeframes before and after VR deployment, were performed.ResultsA total of 2,683 patients were included (April 2013–December 2022); 1910 pre- and 773 post-intervention. All acute stroke time metrics significantly improved post-intervention. The primary outcome, door-to-decision time, decreased from 80 min [56–118] to 54 min [40–76; P < 0.001]. Secondary outcomes also improved, including door-to-thrombolysis time (90 min [68–114] vs. 68.5 min [54–90]; P < 0.001) and proportion of patients thrombolysed (11 vs. 16%; P < 0.001). The proportion of patients transferred for thrombectomy was unchanged (6 vs. 7%; P = 0.69). Seventy VR sessions totaling 15 h 39 min of training time were logged. VR training usage varied across sites (3–31 sessions per site).ConclusionsDelivery of a multi-factorial intervention including infrastructure, funding, education and training (with VR workflow training) as part of a state-wide telestroke rollout was associated with improved acute stroke treatment metrics. Additional work is required to identify the contribution of each intervention component on clinical outcomes and to increase training uptake and sustainment.
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- 2024
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41. A unique mission: Remembering Operation Jaywick, 80 years on
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Smith, Stirling and Wyatt-Spratt, Neridah
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- 2023
42. Personalised Emails in First-Year Mathematics: Exploring a Scalable Strategy for Improving Student Experiences and Outcomes
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Dart, Sarah and Spratt, Belinda
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Widening participation initiatives in higher education have grown overall student numbers while also increasing the diversity of student cohorts. Consequently, enhancing student experiences and outcomes has become increasingly challenging. This study implemented personalised emails in two first-year mathematics courses as a scalable strategy for supporting students with diverse needs. Impact on student experience and outcomes was assessed through surveying and statistical comparisons to previous cohorts. It was found that students perceived the personalised emails favourably and believed the intervention would contribute to them achieving better grades. This translated to a statistically significant improvement in both student experience and academic performance in one of the courses. The results imply that personalised emails are well-suited to courses taken in students' first semesters of university study, aiding those transitioning to the higher education environment by fostering feelings of belonging, supporting effective engagement, and easing navigation of university systems and processes.
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- 2021
43. Comparison of Six-Minute Walk Test and Modified Bruce Treadmill Test in Paediatric Patients With Severe Burns: A Cross-Over Study.
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Palackic, Alen, Abazie, Stephanie, Parry, Ingrid, Mlcak, Ronald, Lee, Jong, Herndon, David, Branski, Ludwik, Wolf, Steven, Spratt, Heidi, Suman, Oscar, and Sen, Soman
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Humans ,Child ,Walk Test ,Exercise Test ,Cross-Over Studies ,Walking ,Oxygen ,Burns ,Oxygen Consumption - Abstract
OBJECTIVE: To compare the six-minute walk test and the Modified Bruce treadmill test in paediatric patients with severe burns. SUBJECTS: A total of 67 children, aged 7-17 years, with severe burns. METHODS: Participants were assigned to perform the six-minute walk test and the Modified Bruce treadmill test in randomized order on discharge from acute burn care. Primary outcome measure was heart rate. Secondary outcome measures were distance walked, Borgs CR-10 rate of perceived exertion, and maximal oxygen uptake (VO2). RESULTS: A total of 67 participants were enrolled. Thirty-eight patients completed both tests. The mean six-minute walk test maximum heart rate was 135 ± 19 bpm (range 97-180 bpm) and the mean Modified Bruce treadmill test maximum heart rate was 148 ± 24 bpm (range 100-197 bpm; p ≤ 0.05), with a weak positive correlation of R² = 0.14. The mean six-minute walk test maximum distance was 294 ± 124 m (range 55 to 522 m) while the mean Modified Bruce treadmill test maximum distance was 439 ± 181 m (range 53 to 976 m; p ≤ 0.05), with no correlation of R² = 0.006. The mean RPE CR-10 score for the six-minute walk test was 3 ± 2.5 (range 0-10) vs a mean RPE CR-10 score of 10 ± 0 for the Modified Bruce treadmill test. CONCLUSION: The Modified Bruce treadmill test challenges the cardiorespiratory system significantly more than the six-minute walk test, as reflected by maximum heart rate measurements, and the perception of effort (i.e. rate of perceived exertion) by the patient. When possible, the Modified Bruce treadmill test should be used to assess cardiovascular functional capacity. However, the six-minute walk test may be more clinically feasible for use with paediatric patients with burns, and provides information about submaximal functional exercise capacity.
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- 2022
44. The effects of short bouts of ergometric exercise for severely burned children in intensive care: A randomized controlled trial.
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Chao, Tony, Parry, Ingrid, Palackic, Alen, Spratt, Heidi, Mlcak, Ronald, Lee, Jong, Herndon, David, Wolf, Steven, Branski, Ludwik, Suman, Oscar, and Sen, Soman
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burns ,exercise ,intensive care ,pediatric ,Adolescent ,Child ,Critical Care ,Exercise ,Exercise Therapy ,Humans ,Intensive Care Units ,Muscle Strength - Abstract
OBJECTIVE: To determine the effects of short bouts of ergometric exercises on the number of days in the burn intensive care unit (ICU), body mass, and functional ambulation. DESIGN: Multi-center, randomized controlled trial. SETTING: Burn intensive care unit. PARTICIPANTS: Children ages 7-17 with severe burns covering over 30% total body surface area (TBSA). INTERVENTION: All patients received standard of care (Control) with the experimental group receiving additional exercise with a cycle ergometer (Exercise). MAIN MEASURES: The number of days in the ICU, total weight, lean body mass (LBM), and functional ambulation were taken shortly after randomization and again within one week of the scheduled hospital discharge. Results of outcomes are expressed as median ± interquartile range (IQR), unless otherwise noted (e.g. demographics). RESULTS: Fifty-four severely burned children (n = 18 Control, n = 36 Exercise) were included. The average ± standard deviation for age was 12 ± 3 years and TBSA was 48 ± 16%. The median ± IQR ICU days for Control was 46 ± 51 days vs 31 ± 29 days for Exercise. The median total weight loss for Control was 2.2 ± 1.2 kg vs 1.8 ± 1.4 kg in Exercise. Control lost 0.75 ± 0.8 kg of LBM vs 0.46 ± 0.43 kg in Exercise. Both groups showed significant improvement in functional ambulation (p
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- 2022
45. Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative
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Aggarwal, Ataes, Agor, Joseph, Al-Amery, Amera, Aminu, Oluwatobiloba, Anand, Adit, Antonescu, Corneliu, Arora, Mehak, Asaduzzaman, Sayed, Asmussen, Tanner, Baghbanzadeh, Mahdi, Baker, Frazier, Bangert, Bridget, Bekhet, Laila, Bhattacharya, Biplab, Blase, Jenny, Butzin-Dozier, Zachary, Caffo, Brian, Chang, Hao, Chen, Zeyuan, Chen, Jiandong, Chiang, Jeffrey, Cho, Peter, Cockrell, Robert, Combs, Parker, Coyle, Jeremy, Crosby, Ciara, Dai, Zongyu, Dai, Ran, Danesharasteh, Anseh, Yildirim, Elif, Delong, Grant, Demilt, Ryan, Deng, Kaiwen, Dey, Sanjoy, Dhamdhere, Rohan, Dickson, Andrew, Dijour, Phoebe, Dinh, Dong, Dixon, Richard, Domi, Albi, Dutta, Souradeep, Elizondo, Mirna, Ertem, Zeynep, Feuerwerker, Solomon, Fliss, Danica, Fowler, Jennifer, Fu, Sunyang, Gardner, Kelly, Getty, Neil, Ghalwash, Mohamed, Gloster, Logan, Greer, Phil, Guan, Yuanfang, Ham, Colby, Hanoudi, Samer, Harper, Jeremy, Hendrix, Nathaniel, Hershkovich, Leeor, Hightower, Jake, Hu, Junjie, Huang, Jiani, Huang, Yu, Huang, Tongtong, Hur, Junguk, Isgut, Monica, Ismail, Hamid, Izmirlian, Grant, Jang, Kuk, Jemiyo, Christianah, Jeong, Hayoung, Ji, Yunwen, Ji, Xiayan, Jiang, Ming, Jiang, Sihang, Jiang, Xiaoqian, Jiang, Yuye, Johnson, Akin, Analyst, Zach, Kapse, Saarthak, Kartoun, Uri, KC, Dukka, Fard, Zahra, Kosfeld, Tim, Krichevsky, Spencer, Kuo, Mike, Larie, Dale, Lederer, Lauren, Leng, Shan, Li, Ziyang, Li, Hongyang, Li, Haodong, Li, Jianfu, Li, Tiantian, Liang, Xinwen, Liang, Hengyue, Liu, Feifan, Liu, Daniel, Luo, Gang, Munia, Tamanna, Madduri, Ravi, Madhira, Vithal, Mani, Shivali, Mansourifard, Farzaneh, Matson, Robert, Mertens, Andrew, Metsis, Vangelis, Meyer, Pablo, Mikhailova, Catherine, Miller, Dante, Milo, Christopher, Mitchell, Elliot, Modanwal, Gourav, Moore, Ronald, Morgenthaler, David, Musal, Rasim, Naik, Mayur, Nalawade, Vinit, Narain, Rohan, Narendrula, Saideep, Obiri, Alena, Okawa, Satoshi, Okechukwu, Chima, Olorunnisola, Toluwanimi, Ossowski, Tim, Parekh, Harsh, Park, Jean, Patel, Saaya, Patterson, Jason, Paul, Chetan, Peng, Le, Perkins, Diana, Pokharel, Suresh, Poplavskiy, Dmytro, Pryor, Zach, Pungitore, Sarah, Qin, Hong, Rababa, Salahaldeen, Rahman, Mahbubur, Rahmani, Elior, Rahnavard, Gholamali, Raihan, Md, Rajendran, Suraj, Ravichandran, Sarangan, Reddy, Chandan, Reyes, Abel, Roghanizad, Ali, Rouffa, Sean, Ruan, Xiaoyang, Saha, Arpita, Sawant, Sahil, Schiaffino, Melody, Seira, Diego, Sengupta, Saurav, Shalaev, Ruslan, Shetty, Gaurav, Shi, Seraphina, Shinguyen, Linh, Singh, Karnika, Sinha, Soumya, Socia, Damien, Stalians, Halen, Stavropoulos, Charalambos, Strube, Jan, Subramanian, Devika, Sun, Jiehuan, Sun, Ju, Sun, Chengkun, Sundararajan, Prathic, Talebi, Salmonn, Tawiah, Edward, Tesic, Jelena, Thiess, Mikaela, Tian, Raymond, Torre-Healy; Ming-Tse Tsai, Luke, Tyus, David, Vardhan, Madhurima, Velingker, Neelay, Walzer, Benjamin, Walzer, Jacob, Wang, Junda, Wang, Lu, Wang, Will, Wang, Jonathan, Wang, Yisen, Weatherly, Chad, Wu, Fanyou, Wu, Yifeng, Wu, Yinjun, Xia, Fangfang, Yan, Hao, Yang, Zhichao, Ye, Biao, Yin, Rui, Yin, Changyu, Yoo, Yun, You, Albert, Yu, June, Zanaj, Martin, Zaiman, Zachary, Zhang, Kai, Zhang, Xiaoyi, Zhang, Tianmai, Zhao, Zixuan, Zhi, Degui, Zhong, Yishan, Zhou, Huixue, Zhou, Andrea, Zhu, Yuanda, Zhu, Yitan, Zhu, Sophie, Adams, Meredith, Alexander, Caleb, Amor, Benjamin, Anzalone, Alfred, Bates, Benjamin, Beasley, Will, Bennett, Tellen, Bissell, Mark, Boudreau, Eilis, Bozzette, Samuel, Bradwell, Katie, Bramante, Carolyn, Brown, Don, Burgoon, Penny, Buse, John, Callahan, Tiffany, Cato, Kenrick, Chapman, Scott, Chute, Christopher, Clark, Jaylyn, Clark, Marshall, Cooper, Will, Cottrell, Lesley, Crowley, Karen, Deacy, Mariam, Dillon, Christopher, Eichmann, David, Emmett, Mary, Erwin-Cohen, Rebecca, Francis, Patricia, French, Evan, Fuentes, Rafael, Gabriel, Davera, Gagnier, Joel, Garbarini, Nicole, Ge, Jin, Gersing, Kenneth, Girvin, Andrew, Gordon, Valery, Graves, Alexis, Guinney, Justin, Haendel, Melissa, Hayanga, J.W., Hendricks, Brian, Hernandez, Wenndy, Hill, Elaine, Hillegass, William, Hong, Stephanie, Housman, Dan, Hurley, Robert, Islam, Jessica, Jawa, Randeep, Johnson, Steve, Kamaleswaran, Rishi, Kibbe, Warren, Koraishy, Farrukh, Kostka, Kristin, Kurilla, Michael, Lee, Adam, Lehmann, Harold, Liu, Hongfang, Loomba, Johanna, Madlock-Brown; Sandeep Mallipattu, Charisse, Manna, Amin, Mariona, Federico, Marti, Emily, Martin, Greg, Mathew, Jomol, Mazzotti, Diego, McMurry, Julie, Mehta, Hemalkumar, Michael, Sam, Miller, Robert, Misquitta, Leonie, Moffitt, Richard, Morris, Michele, Murray, Kimberly, Northington, Lavance, O’Neil, Shawn, Olex, Amy, Palchuk, Matvey, Patel, Brijesh, Patel, Rena, Payne, Philip, Pfaff, Emily, Pincavitch, Jami, Portilla, Lili, Prior, Fred, Pyarajan, Saiju, Pyles, Lee, Qureshi, Nabeel, Robinson, Peter, Rutter, Joni, Sadan, Ofer, Safdar, Nasia, Saha, Amit, Saltz, Joel, Saltz, Mary, Schmitt, Clare, Setoguchi, Soko, Sharafeldin, Noha, Sharathkumar, Anjali, Sheikh, Usman, Sidky, Hythem, Sokos, George, Southerland, Andrew, Spratt, Heidi, Starren, Justin, Subbian, Vignesh, Suver, Christine, Takemoto, Cliff, Temple-O'Connor, Meredith, Topaloglu, Umit, Vedula, Satyanarayana, Walden, Anita, Walters, Kellie, Ward-Caviness, Cavin, Wilcox, Adam, Wilkins, Ken, Williams, Andrew, Wu, Chunlei, Zampino, Elizabeth, Zhang, Xiaohan, Zhu, Richard, Bergquist, Timothy, Tariq, Adbul, Philips, Rachael V., Pirracchio, Romain, van der Laan, Mark, Colford, John M., Jr., Hubbard, Alan, Gao, Jifan, Chen, Guanhua, Stein, Adam, Long, Qi, Holmes, John, Mowery, Danielle, Wong, Eric, Parekh, Ravi, Getzen, Emily, and Blase, Jennifer
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- 2024
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46. External Validation of a Digital Pathology-based Multimodal Artificial Intelligence Architecture in the NRG/RTOG 9902 Phase 3 Trial
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Ross, Ashley E., Zhang, Jingbin, Huang, Huei-Chung, Yamashita, Rikiya, Keim-Malpass, Jessica, Simko, Jeffry P., DeVries, Sandy, Morgan, Todd M., Souhami, Luis, Dobelbower, Michael C., McGinnis, L. Scott, Jones, Christopher U., Dess, Robert T., Zeitzer, Kenneth L., Choi, Kwang, Hartford, Alan C., Michalski, Jeff M., Raben, Adam, Gomella, Leonard G., Sartor, A. Oliver, Rosenthal, Seth A., Sandler, Howard M., Spratt, Daniel E., Pugh, Stephanie L., Mohamad, Osama, Esteva, Andre, Chen, Emmalyn, Schaeffer, Edward M., Tran, Phuoc T., and Feng, Felix Y.
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- 2024
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47. The effect of nitroglycerin treatment on cerebral ischaemia: A systematic review and meta-analysis of animal studies
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Litman, Magdalena, Spratt, Neil J., and Beard, Daniel J.
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- 2024
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48. Addressing cost barriers to healthy eating with Eat Well, a prescription produce subsidy, for patients with diabetes and at risk for food insecurity: Study protocol for a type 1 hybrid effectiveness-implementation pragmatic randomized controlled trial
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Drake, Connor, Granados, Isa, Rader, Abigail, Brucker, Amanda, Hoeffler, Sam, Goldstein, Benjamin A., Chamorro, Ceci, Johnson, Fred, Hinz, Eugenia McPeek, Bedoya, Armando D., German, Jashalynn C., Hauser, Jillian, Thacker, Connie, and Spratt, Susan E.
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- 2024
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49. From Alpha to Omicron and Beyond: Associations Between SARS-CoV-2 Variants and Surgical Outcomes
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Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred, Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Verhagen, Nathaniel B., Geissler, Thomas, SenthilKumar, Gopika, Gehl, Carson, Shaik, Tahseen, Flitcroft, Madelyn A., Yang, Xin, Taylor, Bradley W., Ghaferi, Amir A., Gould, Jon C., and Kothari, Anai N.
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- 2024
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50. Carbonatite research: The African Legacy
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Zaitsev, Anatoly N. and Spratt, John
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- 2024
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