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219 citation(s) found for "Yu, Qing".

Comparison of Factors Associated With 30‐Day and 90‐Day Readmission Among a Global Cohort of Patients Hospitalised With Cirrhosis
Haktanıyan, Büşra, Choudhury, Ashok , Wong, Florence , Kamath, Patrick S. , Topazian, Mark , Hayes, P C, Álvares‐da‐Silva, Mário Reis , Torre, Aldo , Silvey, Scott, Bajaj, Jasmohan S. , Investigators, CLEARED, Barutçu, Sezgin , Fisseha, Henok , Idilman, Ramazan , Haktaniyan, Busra , Chaudhary, Ashok , Wong, Florence , Kamath, Patrick S , Xie, Qing , Topazian, Mark D , Alvares-da-Silva, Mario Reis , Torre, Aldo , George, Jacob , Seto, Wai-Kay , BUSH, BRIAN J. , Thacker, Leroy R , Bajaj, Jasmohan S , Fisseha, Henok , Idılman, Ramazan , George, Jacob , Seto, Wai‐Kay , Silvey, Scott , Thacker, Leroy R.

Liver International | July 29, 2026 | Volume: 46 | Issue: 9 | Pages: No page available

10.1111/liv.70804 | PMID 42522657 Get It

ABSTRACT Background and Aims It remains unclear whether different factors influence 30‐ and 90‐day readmission rates. We identified predictors of 90‐day mortality in a global cohort of hospitalised patients with cirrhosis. Methods Variables associated with 30‐ and 90‐day post‐discharge readmission, liver transplantation (LT), and mortality were compared in prospectively enrolled, non‐electively hospitalised adult patients with cirrhosis. Results We enrolled 4208 patients from 125 centres across 37 countries. Alcohol‐related liver disease was the most common aetiology of cirrhosis (40%), followed by hepatitis B virus infection (21%); 47% were readmitted, 8% received liver transplantation (LT), and 23% died within 90 days post‐discharge. In multivariable analysis, country income was significantly associated with both 30‐ and 90‐day readmission rates, the receipt of LT, and mortality within 30 and 90 days post‐discharge (all p ‐values < 0.001). Independent predictors of higher rates of 30‐ and 90‐day readmissions, respectively, were disease severity ( p < 0.001, p = 0.003), prior ascites ( p = 0.025, p = 0.016), prior hospitalisation ( p < 0.001), hyponatremia ( p < 0.001, p = 0.008), and in‐hospital vasopressor use ( p = 0.002, p = 0.011). Prior variceal bleeding independently predicted higher 90‐day readmission rates, whereas age, disease severity, mechanical ventilation, and in‐hospital vasopressor use (all, p < 0.001) increased odds of 30‐ and 90‐day post‐discharge death. Additionally, admission ( p = 0.011) and nosocomial ( p = 0.022) infections increased the odds of 90‐day post‐discharge death. Conclusion In a global cohort of hospitalised patients with cirrhosis, patients in high‐income countries exhibited the highest rates of 30‐ and 90‐day readmission, alongside lower mortality rates and a higher incidence of LT. Variables that predict 30‐day readmission also predicted 90‐day readmission. Understanding these disparities is essential for achieving health equity.
Primary Aldosteronism Medical Treatment Outcomes (PAMO) Beyond 12 Months
Yang, Jun , Goi, Jessica , Burrello, Jacopo , Reincke, Martín , Adolf, Christian, Brüdgam, Denise , Li, Qifu , Song, Ying , Hu, Jinbo , Yang, Shumin , Satoh, Fumitoshi , Ono, Yoshikiyo , Libianto, Renata , Nayak, Drishya , Vaidya, Anand , O’Toole, Samuel , Larose, Stéphanie , Nakai, Kazuki , Nishikawa, Tetsuo , Ladygina, D. O. , Fardella, Carlos , Mulatero, Paolo , Drake, William M., Varsani, Chetna, Wu, Xilin , Stowasser, Michael , Li, Nanfang , Zhu, Qing , Hong, Namki , Nayak, Drishya , Puar, Troy H , Wu, Vin-Cent , Vaidya, Anand , Araujo-Castro, Marta , Kocjan, Tomaz , O'Toole, Samuel Matthew , Hundemer, Gregory L , Ragnarsson, Oskar , Lacroix, Andre , Larose, Stephanie , Nakai, Kazuki , Nishikawa, Tetsuo , Ladygina, Daria , Turcu, Adina F , Fardella, Carlos E , Uslar, Thomas , Quinkler, Marcus , Mulatero, Paolo , Pintus, Giovanni , Rossi, Gian Paolo , Hahner, Stefanie , Amar, Laurence , Brown, Morris Jonathan , Wu, Xilin , Young, W F , Williams, Tracy Ann , Fuller, Peter J , Yang, Jun , Stowasser, Michael , Hong, Namki , Wu, Vin‐Cent , Araujo‐Castro, Marta , Kocjan, Tomaž , Lacroix, André , Turcu, Adina F. , Vibhatavata, Peeradon , Quinkler, Marcus , Rossi, Gian Paolo , Hahner, Stefanie , Drake, William, Young, William F. , Williams, Tracy Ann

Hypertension | July 22, 2026 | Volume: 83 | Issue: 9 | Pages: No page available

10.1161/hypertensionaha.126.27431 | PMID 42483794 Get It

BACKGROUND: Primary aldosteronism (PA) is a common and treatable cause of hypertension, yet data on the durability of medical treatment response beyond the first year are limited. Using the PA medical treatment outcomes framework, we evaluated long-term biochemical and clinical outcomes and factors associated with treatment response. METHODS: We conducted an international, multicenter, observational cohort study across 27 centers on 4 continents. Adults with PA treated with mineralocorticoid receptor antagonists and/or epithelial sodium channel blockers between 2016 and 2021 were included if follow-up data were available at ≥12 months. Biochemical and clinical responses were classified as complete, partial, or absent using PA medical treatment outcomes criteria. Ordinal logistic regression identified determinants of a favorable treatment response. RESULTS: The cohort included 1292 patients (47.5% women, mean age 52 years) with a median follow-up of 34 months (interquartile range, 21–51). At ≥12 months, 58.3% achieved a complete biochemical response, and 20.8% achieved a complete clinical response, with only 5% showing no response. Determinants of a favorable biochemical response included lower aldosterone and lateralization index, and higher renin and potassium levels at baseline. In those taking spironolactone, a higher daily dose was also associated with a favorable biochemical response. Determinants of a favorable clinical response included female sex, lower body mass index, shorter duration of hypertension, and absence of hypertension-mediated organ damage. CONCLUSIONS: Targeted medical therapy for PA can deliver sustained biochemical and clinical benefits. Early disease detection and adequate dose titration are highly actionable determinants of long-term treatment success.
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Blackwell, Thomas W., Kachuri, Linda , Castaldi, Peter J. , Cho, Michael H. , Christenson, Stephanie A. , Durda, Peter , Gabriel, Stacey , Hersh, Craig P. , Huntsman, Scott , Hwang, S.-J., Joehanes, Roby, Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching‐Ti , Liu, Yongmei , Mak, Angel C. Y. , Manichaikul, Ani , Paik, David T. , Saferali, Aabida , Smith, Joshua D. , Taylor, Kent D. , Wang, Jiongming , Weinstock, Joshua S. , Weiss, Jeffrey, Wheeler, Heather E. , Zhou, Ying , Zoellner, Sebastian, Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R.G. , Ortega, Victor E. , Johnson, Craig , Gan, Weiniu , Abecasis, Gonçalo , Nickerson, Deborah A. , Ardlie, Kristin G., Woodruff, Prescott G. , Bowler, Russell P. , Meyers, Deborah A. , Reiner, Alex, Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S. , Silverman, Edwin K. , Rich, Stephen S., Heard‐Costa, Nancy L. , Tang, Hua, Rotter, Jerome I. , Smith, Albert V. , Aguet, François, Scott, Laura J. , Raffield, Laura M. , Parker, Stephen C.J. , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. Charles, Guan, Yue, Hall, Michael, Han, Yi, Harris, Daniel, Heavner, Ben, Herrington, David, Hobbs, Brian, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Jackson, Rebecca, Jain, Deepti, Johnsen, Jill, Johnston, Rich, Jones, Kimberly, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Kramer, Holly, Lange, Christoph, Lange, Ethan, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Sandra, Lee, Wen-Jane, Levine, David, Lewis, Joshua, Li, Yun, Lin, Xihong, Liu, Simin, Liu, Yu, Make, Barry, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGoldrick, Daniel, McHugh, Caitlin, Mei, Hao, Meigs, James, Menon, Vipin, Min, Nancy, Moll, Matt, Momin, Zeineen, Montasser, May, Mychaleckyj, Josyf C, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nkechinyere, Osuji, O'Connell, Jeff, O’Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pankow, James, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Phillips, Lawrence S, Pollin, Toni, Becker, Julia Powers, Boorgula, Meher Preethi, Psaty, Bruce, Qiao, Dandi, Rafaels, Nicholas, Rajendran, Mahitha, Rasmussen-Torvik, Laura, Ratan, Aakrosh, Reed, Robert, Regan, Elizabeth, Reupena, Muagututi‘a Sefuiva, Robillard, Rebecca, Roselli, Carolina, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ryan, Kathleen, Sabino, Ester Cerdeira, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Santibanez, Jireh, Schwander, Karen, Sciurba, Frank, Sériès, Frédéric, Shetty, Amol, Shetty, Aniket, Silver, Brian, Skomro, Robert, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taub, Margaret, Taylor, Simeon, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tong, Catherine, Tsai, Michael, Vaidya, Dhananjay, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Watson, Karol, Watt, Jennifer, Weng, Lu-Chen, Wessel, Jennifer, Williams, Kayleen, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Zekavat, Seyedeh Maryam, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Rich, Stephen S. , Pankow, James S. , Reiner, Alex P. , Aguet, François , Johnson, W. Craig , Ardlie, Kristin , Orchard, Peter , Kachuri, Linda , Castaldi, Peter J , Cho, Michael H , Christenson, Stephanie A , Durda, Peter , Hersh, Craig P , Huntsman, Scott , Hwang, Seungyong , Joehanes, Roby , Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching-Ti , Liu, Yongmei , Mak, Angel C Y , Manichaikul, Ani W , Paik, David T , Smith, Joshua D , Taylor, Kent D , Tracy, Russell P , Wang, Jiongming , Wang, Mingqiang , Weinstock, Joshua S , Weiss, Jeffrey , Wheeler, Heather E , Zhou, Ying , Zöllner, Sebastian , Wu, Joseph C , Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R G , Ortega, Victor E , Johnson, W Craig , Gan, Weiniu , Gupta, Namrata , Ardlie, Kristin , Woodruff, Prescott G , Bowler, Russell P , Reiner, Alexander P , Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S , Silverman, Edwin K , Rich, Stephen S , Heard-Costa, Nancy , Tang, Hua , Rotter, Jerome I , Smith, Albert V , Levy, Daniel , Aguet, François , Scott, Laura J , Raffield, Laura M , Parker, Stephen C J , Pankow, James S , Tracy, Russell P. , Wu, Joseph C. , Larson, Martin G. , Cupples, L. Adrienne , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan , Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. Charles, Guan, Yue, Hall, Michael, Han, Yi, Harris, Daniel, Heavner, Ben, Herrington, David, Hobbs, Brian, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Jackson, Rebecca, Jain, Deepti, Johnsen, Jill, Johnston, Rich, Jones, Kimberly, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Kramer, Holly, Lange, Christoph, Lange, Ethan, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Sandra, Lee, Wen-Jane, Levine, David, Lewis, Joshua, Li, Yun, Lin, Xihong, Liu, Simin, Liu, Yu, Make, Barry, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGoldrick, Daniel, McHugh, Caitlin, Mei, Hao, Meigs, James, Menon, Vipin, Min, Nancy, Moll, Matt, Momin, Zeineen, Montasser, May, Mychaleckyj, Josyf C, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nkechinyere, Osuji, O'Connell, Jeff, O’Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Phillips, Lawrence S, Pollin, Toni, Becker, Julia Powers, Boorgula, Meher Preethi, Psaty, Bruce, Qiao, Dandi, Rafaels, Nicholas, Rajendran, Mahitha, Rasmussen-Torvik, Laura, Ratan, Aakrosh, Reed, Robert, Regan, Elizabeth, Reupena, Muagututi‘a Sefuiva, Robillard, Rebecca, Roselli, Carolina, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ryan, Kathleen, Sabino, Ester Cerdeira, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Santibanez, Jireh, Schwander, Karen, Sciurba, Frank, Sériès, Frédéric , Shetty, Amol, Shetty, Aniket, Silver, Brian, Skomro, Robert, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taub, Margaret, Taylor, Simeon, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tong, Catherine, Tsai, Michael, Vaidya, Dhananjay, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Watson, Karol, Watt, Jennifer, Weng, Lu-Chen, Wessel, Jennifer, Williams, Kayleen, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Zekavat, Seyedeh Maryam, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng

Science | July 16, 2026 | Volume: 393 | Issue: 6808 | Pages: No page available

10.1126/science.adx2989 | PMID 42462027 Get It

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.
Beyond Breathing: Lung as a Sensory Organ A Report from the NHLBI Workshop on Lung Sensing and its Implication in Diseases
Jendzjowsky, Nicholas, Kuo, Christin S. , Chen, Zhijian, Li, Peng, Prescott, Sara , Liu, Yin, Seeholzer, Laura, Tschumperlin, Daniel J. , Taylor‐Clark, Thomas E. , Rajagopal, Jay, Haber, Adam L, Noel, A, Kotas, Maya, Drake, M G, Pabelick, C M, Rosenblatt, Jody , Mouradian, Gary, Su, Yujuan, Gomez, Christian, Lin, Q. , Lu, Qing , Mongodin, Emmanuel F. , Vuga, Louis, Zhou, Guofei , Prakash, Y S, Sun, X, Pabelick, Christina, Jendzjowsky, Nicholas Gregory , Reznikov, Leah R. , Li, Peng, Prescott, Sara, Seeholzer, Laura F. , Rajagopal, Jayaraj , Haber, Adam L., Kotas, Maya E. , Pabelick, Christina M. , Mouradian, Gary Charles , Gómez, Christian R. , Vuga, Louis J., Prakash, Y. S.

American Journal of Respiratory Cell and Molecular Biology | June 8, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1093/ajrcmb/aanag111 | PMID 42265991 Get It

Abstract The lung, one the largest branching organs in our body and vital for survival at first breath, is commonly known as the gas-exchange organ. Recent novel findings on lung sensing cells, molecules, and lung-brain crosstalk in the emerging discipline of interoception have highlighted the consideration of the lung as a sensory organ. Acknowledging the central importance of lung sensing to human health and disease, NHLBI convened a workshop to synthesize the past, current, and future of lung sensing research, with in-person presentations by ∼20 interdisciplinary experts and a large virtual audience. Here, we highlight the key topics discussed and summarize a blueprint for the future in this important field.
Mean Arterial Pressure at Admission Predicts 28-day Mortality in Patients With Severe Alcohol-Associated Hepatitis
Ventura-Cots, Meritxell, Clemente, Ana, Alvarado-Tapias, Edilmar, Ravi, Sujan, Cuyàs, Berta , Tanguy, M, Poca, Maria, Jäger, Marion , Arteel, Gavin E. , Villagrasa, Ares, Aguilar-Amorós, Anna, Argemí, Josepmaria , Abraldes, Juan G., Bosques, Francisco, Brown, R, Garcia-Taso, Guadalupe, Genesca, Juan, Schanbl, Bernd, Mathurin, P., Louvet, Alexander, Lucey, Michael R., Shawcross, Debbie L., Verna, Elisabeth, Dasarathy, S, Tu, Wanzhu, Kamath, Patrick S, Chalasani, Naga P, McClain, Craig J, Szabo, Gyongyi, Tang, Qing, Barton, Bruce, Nagy, Laura E. , Shah, Vijay H, Sanyal, Arun J, Singal, Ashwani K, Soriano, Germà, Rautou, Pierre Emmanuel, Shawcross, Debbie L. , Ventura Cots, Meritxell , Bataller, Ramon A , Shawcross, Debbie Lindsay , Cuyas, Berta , Ventura‐Cots, Meritxell , Alvarado‐Tápias, Edilmar , Ravi, Sujan, Tanguy, Marion , Poca, María , Fernández‐Carrillo, Carlos , Villagrasa, Ares , Abraldeṣ, Juan G. , Genescà, Joan , Mathurin, Philippe , Lucey, Michael R., Gawrieh, Samer , Tu, Wanzhu , Kamath, Patrick S. , Chalasani, Naga , McClain, Craig J. , Tang, Qing , Shah, Vijay H. , Sanyal, Arun J. , Mitchell, Mack , Singal, Ashwani K. , Rautou, Pierre-Emmanuel

Clinical and Translational Gastroenterology | June 4, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.14309/ctg.0000000000001053 | PMID 42235929 Get It

INTRODUCTION: Alcohol-associated hepatitis (AH) is a severe condition with high short-term mortality. Identifying key predictors of poor outcomes is critical for guiding therapeutic strategies. Mean arterial pressure (MAP), a key determinant of tissue perfusion and systemic hemodynamics, may play a pivotal role in prognosis. METHODS: We analyzed a multicenter, prospective cohort of 323 patients hospitalized with AH, with validation in an independent cohort of 290 patients. Survival was evaluated using Kaplan-Meier curves and compared with the log-rank (Mantel-Cox) test. Cox proportional hazards models were used to estimate hazard ratios for mortality, adjusted for Model for end stage liver disease score. Mechanistic insights were explored through assessment of cardiovascular biomarkers. RESULTS: A baseline MAP <80 mm Hg was associated with significantly higher mortality at both 28 days (27.3% vs 8.0%) and 90 days (40.3% vs 15.6%; P < 0.001 for both). This association persisted after adjusting for Model for end stage liver disease score, age, and baseline hepatic encephalopathy. The incidence of infections during follow-up was similar across MAP groups (27.6% vs 22.8%), but acute kidney injury occurred more frequently in the MAP <80 mm Hg group (62% vs 38%, P < 0.001). In the validation cohort, patients with MAP <80 mm Hg also demonstrated significantly lower 28-day transplant-free survival. Although B-type natriuretic peptide and plasma renin levels were altered in patients with AH, they did not correlate with MAP values. DISCUSSION: A baseline MAP <80 mm Hg is an independent predictor of short-term and mid-term mortality in patients with AH. Strategies aimed at restoring hemodynamic stability may improve outcomes in this high-risk population.
Cross‐Vendor Validation of Proton Density Fat Fraction and T 1 Mapping Using a Combined Proton Density Fat Fraction—
Starekova, Jitka , Weingärtner, Sebastian , Rutkowski, David , Fullerton, Garrett , Bae, Won C. , Do, Hung P. , Madhuranthakam, Ananth J. , Lin, S. , Serai, Suraj D., Brittain, Jean H. , Hernando, D, Rutkowski, David R , Fullerton, Garrett C , Lin, Sheng Qing , Serai, Suraj D , Yokoo, Takeshi , Reeder, Scott B. , Brittain, Jean H , Hernando, Diego , Do, Hung Phi , Malis, Vadim , Serai, Suraj D. , Yokoo, Takeshi

Journal of Magnetic Resonance Imaging | May 20, 2026 | Volume: 64 | Issue: 2 | Pages: 482-492

10.1002/jmri.70344 | PMID 42159302 Get It

ABSTRACT Background In chronic liver disease, fat and fibroinflammatory changes often coexist. However, their biomarkers, proton density fat fraction (PDFF) and T 1 , are typically assessed separately. Their reproducibility under mutual confounding remains unclear. Purpose To assess multicenter, multi‐vendor reproducibility of confounder‐corrected chemical shift‐encoded (CSE)‐MRI‐based PDFF mapping and MOLLI‐based T 1 mapping using a combined PDFF‐T 1 phantom. Study Type Prospective phantom study. Phantom Commercial PDFF‐T 1 Phantom (Model 725) with varying PDFF (0%–30%) and T 1 (200–1400 ms) values. Field Strength/Sequence 1.5 T and 3 T multi‐echo, three‐dimensional spoiled‐gradient‐echo (SGRE) sequence for PDFF mapping, and MOLLI sequence (5(3)3 acquisition scheme) using two‐dimensional SGRE readouts for T 1 mapping across four centers and vendors. Assessment PDFF and T 1 maps were acquired using standardized protocols. PDFF maps were reconstructed locally, while T 1 maps were generated using a centralized algorithm. All maps were quantitatively analyzed by a single radiologist using standardized region‐of‐interest placement. Phantom temporal stability was assessed at one center across five sessions over 9 months (baseline, retest, 1 week, 6 and 9 months). Statistical Tests Intraclass correlation coefficients (ICC), reproducibility coefficients (RDC), and linear regression analysis were used. A p value < 0.05 was considered statistically significant. Results PDFF showed overall excellent reproducibility (ICC = 0.987, RDC = 3.7%), with increased variability at higher T 1 values (RDC up to 7.9% at T 1 = 1400 ms). T 1 mapping showed good reproducibility in the absence of fat (RDC 16–161 ms at PDFF = 0%), but moderate to poor reproducibility in the presence of fat, with RDC increasing up to 1553 ms at PDFF 30%. Temporal stability was excellent ICC ≥ 0.998 for both PDFF and T 1 , and RDC of 1.1%–1.3% for PDFF and 52–57 ms for T 1 . Data Conclusion This phantom study demonstrated high reproducibility of PDFF, whereas T 1 reproducibility deteriorated at higher fat and T 1 levels, underscoring the need for fat‐corrected T 1 mapping for reliable assessment of fibroinflammatory changes. Evidence Level N/A. Technical Efficacy Stage 1.
Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort
Silvey, Scott , Choudhury, Ashok , Kamath, Patrick S. , Wong, Florence , Hayes, P C, Seto, Wai‐Kay , Singhal, Garima, Jothimani, Dinesh , Asrani, Sumeet, Gadano, Adrián , Dinçer, Dinc , Adebayo, Daneille, Doyle, Adam, Debzi, Nabil , Shaw, Jawaid , Barutçu, Sezgin , Lah, Ponan Claude Regis, Duarte‐Rojo, Andrés , Turan, Dilara , Wang, Lei, Velazquez, René Malé, Aghayaeva, Sevda, Córdova-Gallardo, J, Xu, Bin, Gao, Haibing , Elangovan, Harendran, Fung, James, Rajorya, Neil, Wang, X I A O Y U, Katchman, Helena , Jiang, Yongfang, Thanapirom, Kessarin , Eapen, CE, Dhiman, Radha K. , Lu, Mingqin, Su, Minghua , Hueso, Sarai Gonzalez, Aberra, Hanna , Fisseha, Henok , Tan, Hiang Keat , Zhao, Caiyan , Zhang, Ningping, MacQuillan, Gerry, Pereira, Gustavo, Reddy, K. Rajender , Topazian, Mark, Torre, A Ullate De La, Silva, Mario, Bush, Brian J., Bajaj, Jasmohan S. , Chaudhary, Ashok , Xie, Qing , Wong, Florence , Arora, Umang , Gadano, Adrian , Dincer, Dinc , Velarde-Ruiz Velasco, José Antonio , Kulkarni, Anand V , Shaw, Jawaid , Desalgn, Hailemicheal , Bettinger, Dominik , Regis Lah, Ponan Claude , Duarte-Rojo, Andres , Turan, Dilara , Zheng, Xin , Demirtas, Coskun , Liu, Chenghai , Cordova-Gallardo, Jacqueline , Nagral, Aabha , Gao, Haibing , Katchmann, Helena , Praharaj, Dibyalochan , Mahadeva, Sanjiv , Eapen, C E , Dhiman, Radha K , Lu, Mingqin , Arrese, Marco , Su, Minghua , Hueso, Sarai Gonzalez , Aberra, Hanna , Fisseha, Henok , Tan, Hiang Keat , Zhao, Caiyan , Zhang, Ningping , Taneja, Sunil , Sonavane, Amey , Saraya, Anoop , Gofton, Cameron , Pereira, Gustavo , Rajender Reddy, K , Sarin, Shiv Kumar , Cao, Zhujun , Topazian, Mark D , Idilman, Ramazan , Torre, Aldo , George, Jacob , BUSH, BRIAN J. , Bajaj, Jasmohan S , Seto, Wai-Kay , Singhal, Garima, Asrani, Sumeet K. , Farias, Alberto Queiróz , Velasco, J.A. Velarde-Ruiz , Kulkarni, Anand V. , Desalegn, Hailemichael , Karasu, Zeki A. , Fung, James , Rajoriya, Neil , Zheng, Katina , Arrese, Marco , Zhu, Chuanwu , Taneja, Sunil , Aravinthan, Aloysious Dominic , MacQuillan, Gerry C., Idılman, Ramazan , George, Jacob , Alvares-da-Silva, Mario Reis

American Journal of Gastroenterology | April 27, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.14309/ajg.0000000000004031 | PMID 42043180 Get It

INTRODUCTION: Nosocomial infections (NIs) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, 3 ML approaches (random forest [RF], extreme gradient boosting, and neural networks [NNs]) were used to predict NI. Data were split 80:20 for training and testing stratified by the outcome. Models were compared using area under the receiver operating characteristic curve (AUC). RESULTS: In total, 8,263 patients (55.90 ± 13.34 years; 64.1% men) from 127 centers in 37 countries were included. NI developed in 869 (10.5%), a median of 6 (4–11) days of postadmission. Major NIs were respiratory (29.6%) and urinary tract infection (15.7%), and spontaneous bacterial peritonitis (13.5%). NIs occurred more frequently in patients from low/low-middle income countries and those with severe liver disease, alcohol etiology, and admission infections. NIs were associated with inpatient mortality (31.9% vs 8.1%, P < 0.001) and liver transplantation (4.8% vs 1.9%, P < 0.001). Although the RF model (AUC 0.69) showed good calibration (Brier score 0.09), outperforming extreme gradient boosting, neural network, and LR models (AUC 0.66 for all; LR comparison P = 0.043), no model achieved AUC ≥0.80 for clinical utility. At 10% predicted probability threshold, the RF model demonstrated only 75.4% sensitivity, 52.9% specificity, and 15.9% positive predictive value (PPV). DISCUSSION: NIs cannot be accurately predicted from day-of-admission data using ML models, even in a large, prospective, global cirrhosis cohort. Every hospitalized patient with cirrhosis should receive protocolized infection control measures.
Abstract LB196: Fluorinated cuban-1-yl biguanides overcome hormone therapy resistance to standard of care fulvestrant, and palbociclib
Guo, Zhijun , Lei, Jianxun, Wells, Christian T., Makovec, Allison M., Yates, Andrew C., Hawse, John R. , McCarra, Joshua, Cao, Qing, Pryzbilla, Michael J., Koniar, Brenda, Norris, Beverly, Florey, Craig M., Schumacher, Robert J., Schwertfeger, Kaylee L., Ambrose, Elizabeth A., Wong, Henry, D'Assoro, Antonino, Goetz, Matthew P., Makovec, Allison , Jayaraman, Swaathi , Cao, Qing , Farrar, Michael A. , Schwertfeger, Kaylee, Ambrose, Elizabeth A. , Georg, Gunda I. , D’Assoro, Antonino B. , Goetz, Matthew P. , Potter, David A.

Cancer Research | April 17, 2026 | Volume: 86 | Issue: 8_Supplement | Pages: LB196-LB196

10.1158/1538-7445.am2026-lb196 Get It

Abstract Introduction: Epoxy fatty acid (EpFA) mechanisms of hormone therapy resistance (HTR) in ER+HER2- breast cancer (BC) are poorly understood. EETs are EpFAs that contribute to BC progression and HTR by promoting oxidative phosphorylation (OXPHOS). However, it remains unclear how EETs contribute to HTR. In this study, two fulvestrant resistant (FR) subclones of the letrozole resistant (LR) MCF-7AC1 line were isolated (termed LR/FR) and were incidentally resistant to the CDKi palbociclib (PR) (termed MCF-7AC1 LR/FR/PR or multiply resistant - MCF-7AC1 MR). These HTR cell lines exhibited CYP3A4 upregulation (2.3- to 4.3-fold) and increased cellular (±)14,15-EET levels, which were suppressed by biguanide treatment (P&lt;0.05). Structure activity studies led to the design of hexyl cuban-1-yl biguanide (HCB) and fluorinated HCB derivatives C5F2-HCB and C6F3-HCB, which inhibited CYP3A4-mediated EET biosynthesis and growth of the HTR lines. HCB fluorination improved pharmacokinetics (PK) and toxicity. Methods: HCB and fluorinated HCBs were tested for impact on EET biosynthesis, OXPHOS, PK, and growth inhibition and reversal of hypoxia in the MCF-7AC1 MR tumor model. Results: Fulvestrant selection for MCF-7AC1 MR cell lines resulted in undetectable cyclin D1 and estrogen receptor (ERα) expression, while cyclin E1, CDK4, CDK6, CYP3A4, and c-MYC were upregulated (P&lt;0.001). MCF-7 MR cells demonstrated 1.8, 1.4, and 1.2- fold higher levels of (±)8,9, (±)11,12, and (±)14,15-EET compared to parental MCF-7 cells (P&lt;0.05). The most potent fluorinated HCB, C6F3-HCB, suppressed cellular levels of (±)8,9-EET, (±)11,12-EET, and (±)14,15-EET by 53-60% (P&lt;0.029). The MCF-7AC1 MR cells were more potently inhibited by HCBs and fluorinated derivatives compared to the MCF-7 cell line. Comparing an MCF-7 MR line vs. MCF-7, HCB exhibited IC50 values of 4.1 vs. 7.0 uM, C5F2-HCB 10 vs. 25 uM, and C6F3-HCB 5.4 vs. 12 uM (P values all &lt;0.05). C5F2-HCB exhibited the best PK and treatment of the MCF-7AC1 MR xenograft model showed reversal of hypoxia (P&lt;0.05) and transient inhibition by C5F2-HCB (P=0.025 at 20 days). P/F also transiently inhibited this model (P=0.006 at 20 days). C5F2-HCB and P/F showed synergy in vitro (CI=0.46) leading to testing of C5F2-HCB/P/F in vivo enabled by acceptable toxicity of the triplet in mice. This combination showed synergy in vivo vs. standard of care palbociclib/fulvestrant by nonparametric statistical tests (Mann Whitney; P=0.0389; Kolmogorov-Smirnov; P=0.0473), providing a pathway for possible clinical development of the combination. Conclusions: MR BC cell lines exhibit upregulation of CYP3A4 and biosynthesis of EETs, indicating a role for EETs in HTR. The C5F2-HCB/P/F exhibits activity against the highly resistant MCF-7 MR xenograft with acceptable toxicity indicating an avenue for clinical development. Citation Format: Zhijun Guo, Jianxun Lei, Christian T. Wells, Allison M. Makovec, Andrew C. Yates, Swaathi Jayaraman, John R. Hawse, Joshua A. McCarra, Qing Cao, Michael J. Pryzbilla, Brenda L. Koniar, Beverly J. Norris, Craig M. Florey, Robert J. Schumacher, Michael A. Farrar, Kaylee L. Schwertfeger, Elizabeth A. Ambrose, Henry Wong, Gunda I. Georg, Antonino D'Assoro, Matthew P. Goetz, David A. Potter. Fluorinated cuban-1-yl biguanides overcome hormone therapy resistance to standard of care fulvestrant, and palbociclib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB196.
Lack of association between rifaximin and drug-resistant infections: a global multicenter inpatient cirrhosis cohort
Bajaj, Jasmohan S, Kamath, Patrick S, Wong, Florence, Xie, Qing, Topazian, Mark, Seto, Wai-Kay, Torre, Aldo, Hayes, PC, Silva, Mario, Bush, Brian J., Choudhury, Ashok, Investigators, On behalf of the EXPLANTORREDO-TAVR Registry, Fisseha, Henok , Fisseha, Henok , Bajaj, Jasmohan S. , Kamath, Patrick S. , Wong, Florence , Xie, Qing , Idılman, Ramazan , Seto, Wai‐Kay , George, Jacob , Alvares-da-Silva, Mario, BUSH, BRIAN J. , Silvey, Scott , Choudhury, Ashok

Clinical and Molecular Hepatology | April 15, 2026 | Volume: 32 | Issue: 3 | Pages: 1321-1332

10.3350/cmh.2026.0228 | PMID 42120075 Get It

Background/Aims: Infections with drug-resistant organisms (DROs) are associated with poor outcomes in cirrhosis. Rifaximin, widely used for hepatic encephalopathy (HE), could promote cross-resistance, but data regarding clinical impact are conflicting. Aim: Determine predictors of DROs in a global cirrhosis inpatient cohort focusing on preadmission rifaximin use.Methods: From the global CLEARED consortium, we focused on cirrhosis inpatients with infections on/during admission. Clinical/demographic/medication, especially rifaximin details were recorded. The primary outcome was DRO development. Multivariable regression for DRO including clinical, medications, and country income was performed.Results: 2,949 infected inpatients (55.3 years, 62.9% male) were included. 12.2% of all and 24.4% of culture-positive infections developed DROs; these patients had higher HE (39 vs. 31%, <i>P</i>=0.003), hepatorenal syndrome (25 vs. 19%, <i>P</i>=0.006), lactulose (55 vs. 47%, <i>P</i>=0.008) and rifaximin use (34 vs. 27%, <i>P</i>=0.006) on crude comparisons but country-income distributions were similar. 29.7% were on pre-admission rifaximin, mostly HE-related; they had more advanced cirrhosis and from low/low-middle-income countries. Daptomycin was used in 1.5%, linked with DROs (5.0 vs. 1.0%, <i>P</i><0.0001) without a difference in rifaximin use (1.4 vs.1.7%, <i>P</i>=0.61). On adjusted analysis, MELD-Na (1.03, 95% CI 1.02–1.04, <i>P</i><0.001) increased, whereas male sex (0.73, 95% CI 0.58–0.92, <i>P</i>=0.008) and hepatitis-B (0.65, 95% CI 0.45–0.92, <i>P</i>=0.020) decreased DRO. Rifaximin was not associated with DROs overall (OR 1.07, 95% CI 0.80–1.43, <i>P</i>=0.65) or within income strata (high: 1.07, 95% CI 0.59–1.92, <i>P</i>=0.82, upper-middle: 1.18, 95% CI 0.74–1.85, <i>P</i>=0.49, low/low-middle: 1.04, 95% CI 0.60–1.81, <i>P</i>=0.90) despite sensitivity analyses.Conclusions: In this large global cohort of hospitalized patients with cirrhosis and infections, 12% developed infections involving DROs. 30% had pre-admission rifaximin use which was not linked with daptomycin use or with DRO development on adjusted analysis overall or across country income groups.
A phase 1/1b study of the BCMA-targeting bispecific T-cell engager pavurutamab for relapsed/refractory multiple myeloma
Lee, Hans C. , Plattel, Wouter J. , Sborov, Douglas W, Lentzsch, Suzanne , Spencer, Andrew, Niesvizky, Rubén, Trudel, Suzanne , Vij, Ravi, Rasche, Leo , Talpes, Mihaela , Eggert, Tobias , Kapoor, Prashant , Ailawadhi, Sikander, Harrison, Simon J , Lentzsch, Suzanne , Minnema, Monique C , Rasche, Leo , Upreti, Vijay V , Xia, Qing , Lee, Hans C , Sborov, Douglas W. , Spencer, Andrew , Mollee, Peter , Vij, Ravi , Zhou, Di , Ailawadhi, Sikander

Blood | April 8, 2026 | Volume: 148 | Issue: 2 | Pages: 199-212

10.1182/blood.2025032044 | PMID 41950113 Get It

Abstract The B-cell maturation antigen (BCMA)–targeting bispecific T-cell engager pavurutamab (AMG 701) directs the cytotoxic T-cell response toward multiple myeloma (MM) cells. This phase 1/1b, open-label, dose-exploration and dose-expansion study evaluated the safety, tolerability, and efficacy of pavurutamab monotherapy in patients with triple-class relapsed/refractory MM (RRMM). Pavurutamab (5-18 000 μg) was administered IV weekly with step-up dosing in week 1. Overall, 172 patients received at least 1 dose of pavurutamab; 73 received the recommended phase 2 dose (RP2D; 18 000 μg), with 2 different step-up dosing regimens in phase 1b. Twelve patients had dose-limiting toxicities, which included cytokine release syndrome (CRS) and increased transaminases; none of which occurred at the RP2D. The most frequently reported treatment-emergent adverse events included CRS (74.4%), anemia (61.0%), neutropenia (47.1%), and hypophosphatemia (45.3%). Grade ≥3 infections were noted in 60 patients (34.9%). The overall response rate (ORR) was 46.5% among all patients and 65.8% (very good partial response [VGPR] or better, 60.3%) among 73 patients treated at the RP2D. At median follow-up of 17.2 months, median duration of response (DOR) was 36.6 months (95% confidence interval [CI], 22.3 to not estimable). Median progression-free survival (PFS) for all patients was 5.5 months (95% CI, 2.8-10.1) and 16.8 months (95% CI, 5.0 to not estimable) with the RP2D. Pavurutamab exposure generally increased in a dose-proportional manner, with high soluble BCMA levels correlating with lower exposure level. The acceptable safety profile, pharmacokinetics, and preliminary efficacy of pavurutamab supports anti-BCMA T-cell engager therapy in heavily pretreated patients with RRMM. This trial was registered at www.clinicaltrials.gov as NCT03287908.