3,382 results on '"Kirchner, H"'
Search Results
2. Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder
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Walsh, Colin G., Ripperger, Michael A., Hu, Yirui, Sheu, Yi-han, Lee, Hyunjoon, Wilimitis, Drew, Zheutlin, Amanda B., Rocha, Daniel, Choi, Karmel W., Castro, Victor M., Kirchner, H. Lester, Chabris, Christopher F., Davis, Lea K., and Smoller, Jordan W.
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- 2024
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3. Limitations of Noninvasive Tests-Based Population-Level Risk Stratification Strategy for Nonalcoholic Fatty Liver Disease
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Behari, Jaideep, Bradley, Allison, Townsend, Kevin, Becich, Michael J., Cappella, Nickie, Chuang, Cynthia H., Fernandez, Soledad A., Ford, Daniel E., Kirchner, H. Lester, Morgan, Richard, Paranjape, Anuradha, Silverstein, Jonathan C., Williams, David A., Donahoo, W. Troy, Asrani, Sumeet K., Ntanios, Fady, Ateya, Mohammad, Hegeman-Dingle, Rozelle, McLeod, Euan, and McTigue, Kathleen
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- 2024
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4. Exploring Social Cognition Tests to Differentiate Frontotemporal Dementia from Depression
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Lichtenstein, Maya L, Stewart, Peter V, Kirchner, H Lester, Finney, Glen, and Feldman, Howard H
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Biological Psychology ,Psychology ,Clinical Research ,Mental Health ,Brain Disorders ,Aging ,Behavioral and Social Science ,Alzheimer's Disease ,Frontotemporal Dementia (FTD) ,Rare Diseases ,Depression ,Acquired Cognitive Impairment ,Neurodegenerative ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,Neurosciences ,Mental health ,Neurological ,Humans ,Frontotemporal Dementia ,Pilot Projects ,Social Cognition ,Neuropsychological Tests ,Cognition ,Clinical Sciences ,Cognitive Sciences ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
Behavioral-variant frontotemporal dementia (bvFTD) is challenging to recognize, and often misdiagnosed as depression (DEP). Evidence suggests changes in social cognition (SoCog) precede general cognitive decline in bvFTD. Currently, there are no screening measures of social cognition. 17 bvFTD, 16 DEP, and 18 control participants underwent 6 SoCog tests measuring: emotion recognition; theory of mind; empathy; insight. We used χ 2 , Wilcoxon rank sum, Kruskal-Wallis tests to compare groups, with decision tree analysis to identify items that best differentiated bvFTD from DEP. bvFTD performed significantly worse on all SoCog tasks compared with other groups. Decision tree analysis yielded a 5-item test with ROC area under the curve of 0.973 (95% CI: 0.928, 1.0) for differentiating bvFTD versus depression. These results suggest that it may be feasible to develop a screening measure of social cognition.
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- 2023
5. Associations between obstructive sleep apnea and sleep characteristics with chronic kidney disease in rural Pennsylvania
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Sanders, Alison P., Saconi, Bruno, Politis, Maria D., Manus, J. Neil, and Kirchner, H. Lester
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- 2024
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6. “Faith and a sunny day”: Association of patient frailty with strain experienced by informal caregivers of older adults with non-muscle-invasive bladder cancer
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Garg, Tullika, Maheshwari, Charu, Frank, Katie, Johns, Alicia, Rabinowitz, Kirstin, Danella, John F., Becker, Halle, Kirchner, H. Lester, Nielsen, Matthew E., Cohen, Harvey J., Murphy, Terrence E., and McMullen, Carmit K.
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- 2024
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7. IMPACT-FH Study for Implementing Innovative Family Communication and Cascade Testing Strategies for Familial Hypercholesterolemia
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Jones, Laney K., Campbell-Salome, Gemme, Walters, Nicole L., Brangan, Andrew, Morgan, Kelly M., Tricou, Eric P., Lindsey Mills, Zoe T., McGowan, Mary P., Gidding, Samuel S., Johns, Alicia M., Kirchner, H. Lester, Rahm, Alanna Kulchak, and Sturm, Amy C.
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- 2024
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8. Performance of a stool-based quantitative PCR assay for the diagnosis of tuberculosis in adolescents and adults: a multinational, prospective diagnostic accuracy study
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Kay, Alexander, Vasiliu, Anca, Carratala-Castro, Lucia, Mtafya, Bariki, Mendez Reyes, Jose Euberto, Maphalala, Nontobeko, Munguambe, Shilzia, Mulengwa, Durbbin, Ness, Tara, Saavedra, Belen, Bacha, Jason, Maphalala, Gugu, Mejia, Rojelio, Mtetwa, Godwin, Acacio, Sozinho, Manjate, Patricia, Mambuque, Edson, Shiba, Nosisa, Kota, Nokwanda, Ziyane, Mangaliso, Ntinginya, Nyanda Elias, Lange, Christoph, Kirchner, H Lester, DiNardo, Andrew R, Garcia-Basteiro, Alberto L, and Mandalakas, Anna Maria
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- 2024
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9. Using implementation science to develop a familial hypercholesterolemia screening program in primary care: The CARE-FH study
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Jones, Laney K., Romagnoli, Katrina M., Schubert, Tyler J., Clegg, Katarina, Kirchner, H. Lester, Hu, Yirui, Cawley, Dylan, Norelli, Victoria, Williams, Marc S., Gidding, Samuel S., and Rahm, Alanna K.
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- 2024
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10. Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
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Raghunath, Sushravya, Cerna, Alvaro E. Ulloa, Jing, Linyuan, vanMaanen, David P., Stough, Joshua, Hartzel, Dustin N., Leader, Joseph B., Kirchner, H. Lester, Good, Christopher W., Patel, Aalpen A., Delisle, Brian P., Alsaid, Amro, Beer, Dominik, Haggerty, Christopher M., and Fornwalt, Brandon K.
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Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
The electrocardiogram (ECG) is a widely-used medical test, typically consisting of 12 voltage versus time traces collected from surface recordings over the heart. Here we hypothesize that a deep neural network can predict an important future clinical event (one-year all-cause mortality) from ECG voltage-time traces. We show good performance for predicting one-year mortality with an average AUC of 0.85 from a model cross-validated on 1,775,926 12-lead resting ECGs, that were collected over a 34-year period in a large regional health system. Even within the large subset of ECGs interpreted as 'normal' by a physician (n=297,548), the model performance to predict one-year mortality remained high (AUC=0.84), and Cox Proportional Hazard model revealed a hazard ratio of 6.6 (p<0.005) for the two predicted groups (dead vs alive one year after ECG) over a 30-year follow-up period. A blinded survey of three cardiologists suggested that the patterns captured by the model were generally not visually apparent to cardiologists even after being shown 240 paired examples of labeled true positives (dead) and true negatives (alive). In summary, deep learning can add significant prognostic information to the interpretation of 12-lead resting ECGs, even in cases that are interpreted as 'normal' by physicians., Comment: An updated version of this paper is now published with Nature Medicine (2020)
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- 2019
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11. The risk of tuberculosis in children after close exposure: a systematic review and individual-participant meta-analysis
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Martinez, Leonardo, Cords, Olivia, Horsburgh, C Robert, Andrews, Jason R, Consortium, Pediatric TB Contact Studies, Acuna-Villaorduna, Carlos, Ahuja, Shama Desai, Altet, Neus, Augusto, Orvalho, Baliashvili, Davit, Basu, Sanjay, Becerra, Mercedes, Bonnet, Maryline, Boom, W Henry, Borgdorff, Martien, Boulahbal, Fadila, Carvalho, Anna Cristina C, Cayla, Joan A, Chakhaia, Tsira, Chan, Pei-Chun, Cohen, Ted, Croda, Julio, Datta, Sumona, del Corral, Helena, Denholm, Justin T, Dietze, Reynaldo, Dobler, Claudia C, Donkor, Simon, Egere, Uzochukwu, Ellner, Jerrold J, Espinal, Marcos, Evans, Carlton A, Fang, Chi-Tai, Fielding, Katherine, Fox, Greg J, García, Luis F, García-Basteiro, Alberto L, Geis, Steffen, Graham, Stephen M, Grandjean, Louis, Hannoun, Djohar, Hatherill, Mark, Hauri, Anja M, Hesseling, Anneke C, Hill, Philip C, Huang, Li-Min, Huerga, Helena, Hussain, Rabia, Jarlsberg, Leah, Jones-López, Edward C, Kato, Seiya, Kato-Maeda, Midori, Kampmann, Beate, Kirchner, H Lester, Kritski, Afrânio, Lange, Christoph, Lee, Chih-Hsin, Lee, Li-Na, Lee, Meng-Rui, Lemos, Antonio Carlos, Lienhardt, Christian, Ling, Du-Lin, Liu, Qiao, Lo, Nathan C, Long, Richard, Lopez-Varela, Elisa, Lu, Peng, Magee, Matthew, Malone, LaShaunda L, Mandalakas, Anna M, Martinson, Neil A, Mazahir, Rufaida, Murray, Megan B, Netto, Eduardo Martins, Otero, Larissa, Parsonnet, Julie, Reingold, Arthur, Schaaf, H Simon, Seddon, James A, Sharma, Surendra, Singh, Jitendra, Singh, Sarman, Sloot, Rosa, Sotgiu, Giovanni, Stein, Catherine M, Iqbal, Najeeha Talat, Triasih, Rina, Trieu, Lisa, van der Loeff, Maarten F Schim, Van der Stuyft, Patrick, van Schalkwyk, Cari, Vashishtha, Richa, Verhagen, Lilly M, Villalba, Julian A, Wang, Jann-Yuan, Whalen, Christopher C, Yoshiyama, Takashi, Zar, Heather J, Zellweger, Jean-Pierre, and Zhu, Limei
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Biomedical and Clinical Sciences ,Clinical Sciences ,Health Sciences ,Tuberculosis ,Prevention ,Rare Diseases ,Pediatric ,Infectious Diseases ,Emerging Infectious Diseases ,Infection ,Good Health and Well Being ,Adolescent ,Age Factors ,Child ,Child ,Preschool ,Contact Tracing ,Disease Transmission ,Infectious ,Family Characteristics ,Female ,Global Health ,Humans ,Incidence ,Male ,Mycobacterium tuberculosis ,Risk Assessment ,Sex Factors ,Tuberculosis ,Pulmonary ,Pediatric TB Contact Studies Consortium ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
BackgroundTens of millions of children are exposed to Mycobacterium tuberculosis globally every year; however, there are no contemporary estimates of the risk of developing tuberculosis in exposed children. The effectiveness of contact investigations and preventive therapy remains poorly understood.MethodsIn this systematic review and meta-analysis, we investigated the development of tuberculosis in children closely exposed to a tuberculosis case and followed for incident disease. We restricted our search to cohort studies published between Jan 1, 1998, and April 6, 2018, in MEDLINE, Web of Science, BIOSIS, and Embase electronic databases. Individual-participant data and a pre-specified list of variables were requested from authors of all eligible studies. These included characteristics of the exposed child, the index case, and environmental characteristics. To be eligible for inclusion in the final analysis, a dataset needed to include: (1) individuals below 19 years of age; (2) follow-up for tuberculosis for a minimum of 6 months; (3) individuals with household or close exposure to an individual with tuberculosis; (4) information on the age and sex of the child; and (5) start and end follow-up dates. Studies assessing incident tuberculosis but without dates or time of follow-up were excluded. Our analysis had two primary aims: (1) estimating the risk of developing tuberculosis by time-period of follow-up, demographics (age, region), and clinical attributes (HIV, tuberculosis infection status, previous tuberculosis); and (2) estimating the effectiveness of preventive therapy and BCG vaccination on the risk of developing tuberculosis. We estimated the odds of prevalent tuberculosis with mixed-effects logistic models and estimated adjusted hazard ratios (HRs) for incident tuberculosis with mixed-effects Poisson regression models. The effectiveness of preventive therapy against incident tuberculosis was estimated through propensity score matching. The study protocol is registered with PROSPERO (CRD42018087022).FindingsIn total, study groups from 46 cohort studies in 34 countries-29 (63%) prospective studies and 17 (37%) retrospective-agreed to share their data and were included in the final analysis. 137 647 tuberculosis-exposed children were evaluated at baseline and 130 512 children were followed for 429 538 person-years, during which 1299 prevalent and 999 incident tuberculosis cases were diagnosed. Children not receiving preventive therapy with a positive result for tuberculosis infection had significantly higher 2-year cumulative tuberculosis incidence than children with a negative result for tuberculosis infection, and this incidence was greatest among children below 5 years of age (19·0% [95% CI 8·4-37·4]). The effectiveness of preventive therapy was 63% (adjusted HR 0·37 [95% CI 0·30-0·47]) among all exposed children, and 91% (adjusted HR 0·09 [0·05-0·15]) among those with a positive result for tuberculosis infection. Among all children
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- 2020
12. Mean Square Strains Caused by Dislocations
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Kirchner, H. O. K., primary
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- 2023
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13. The Line Tension of <111> Screw Dislocations Is Isotropic
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Kirchner, H. O. K., primary
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- 2023
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14. Abstract 17509: Gender-Specific Differences in Patients Undergoing Coronary Artery Bypass Grafting
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Morland, Thomas, Abbas, Mostafa, Shuhaiber, Jeffrey, Hall, Eric S, Kirchner, H Lester, and El-Manzalawy, Yasser
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- 2023
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15. Abstract 17465: Analysis of Intra-Operative Heart Rates Reveals a Novel Sub-Phenotype in Coronary Artery Bypass Grafting Patients
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Abbas, Mostafa, Morland, Thomas, Kirchner, H Lester, Hall, Eric S, Shuhaiber, Jeffrey, and El-Manzalawy, Yasser
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- 2023
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16. Abstract 11930: Using Implementation Science to Develop a Familial Hypercholesterolemia Screening Program in Primary Care: The CARE-FH Study
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Jones, Laney K, Romagnoli, Katrina M, Schubert, Tyler J, Clegg, Katarina, Kirchner, H Lester, Hu, Yirui, Cawley, Dylan, Norelli, Victoria, Williams, Marc S, Gidding, Sam S, and Kulchak Rahm, Alanna
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- 2023
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17. A deep neural network to enhance prediction of 1-year mortality using echocardiographic videos of the heart
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Ulloa, Alvaro, Jing, Linyuan, Good, Christopher W, vanMaanen, David P, Raghunath, Sushravya, Suever, Jonathan D, Nevius, Christopher D, Wehner, Gregory J, Hartzel, Dustin, Leader, Joseph B, Alsaid, Amro, Patel, Aalpen A, Kirchner, H Lester, Pattichis, Marios S, Haggerty, Christopher M, and Fornwalt, Brandon K
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition ,Quantitative Biology - Quantitative Methods - Abstract
Predicting future clinical events helps physicians guide appropriate intervention. Machine learning has tremendous promise to assist physicians with predictions based on the discovery of complex patterns from historical data, such as large, longitudinal electronic health records (EHR). This study is a first attempt to demonstrate such capabilities using raw echocardiographic videos of the heart. We show that a large dataset of 723,754 clinically-acquired echocardiographic videos (~45 million images) linked to longitudinal follow-up data in 27,028 patients can be used to train a deep neural network to predict 1-year mortality with good accuracy (area under the curve (AUC) in an independent test set = 0.839). Prediction accuracy was further improved by adding EHR data (AUC = 0.858). Finally, we demonstrate that the trained neural network was more accurate in mortality prediction than two expert cardiologists. These results highlight the potential of neural networks to add new power to clinical predictions., Comment: We updated results with improved performance after dropout bug in tensorflow v1.12. We also added learning curves showing promise in video model with more samples
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- 2018
18. Relationship of Estimated GFR and Albuminuria to Concurrent Laboratory Abnormalities: An Individual Participant Data Meta-analysis in a Global Consortium
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Inker, Lesley A, Grams, Morgan E, Levey, Andrew S, Coresh, Josef, Cirillo, Massimo, Collins, John F, Gansevoort, Ron T, Gutierrez, Orlando M, Hamano, Takayuki, Heine, Gunnar H, Ishikawa, Shizukiyo, Jee, Sun Ha, Kronenberg, Florian, Landray, Martin J, Miura, Katsuyuki, Nadkarni, Girish N, Peralta, Carmen A, Rothenbacher, Dietrich, Schaeffner, Elke, Sedaghat, Sanaz, Shlipak, Michael G, Zhang, Luxia, van Zuilen, Arjan D, Hallan, Stein I, Kovesdy, Csaba P, Woodward, Mark, Levin, Adeera, Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Yatsuya, Hiroshi, Tamakoshi, Koji, Li, Yuanying, Hirakawa, Yoshihisa, Matsushita, Kunihiro, Grams, Morgan, Sang, Yingying, Polkinghorne, Kevan, Chadban, Steven, Atkins, Robert, Djurdjev, Ognjenka, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Ebert, Natalie, Martus, Peter, Tang, Mila, Heine, Gunnar, Emrich, Insa, Seiler, Sarah, Zawada, Adam, Nally, Joseph, Navaneethan, Sankar, Schold, Jesse, Shlipak, Michael, Sarnak, Mark, Katz, Ronit, Hiramoto, Jade, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hasegawa, Takeshi, Fujii, Naohiko, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Brenner, Hermann, Schöttker, Ben, Saum, Kai-Uwe, Fox, Caroline, Hwang, Shih-Jen, Köttgen, Anna, Schneider, Markus P, Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, and Chang, Alex R
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Biomedical and Clinical Sciences ,Clinical Sciences ,Kidney Disease ,Women's Health ,Clinical Research ,Renal and urogenital ,Good Health and Well Being ,Aged ,Albuminuria ,Blood Chemical Analysis ,Creatinine ,Cross-Sectional Studies ,Disease Progression ,Female ,Global Health ,Glomerular Filtration Rate ,Humans ,Hypertension ,Renal ,Internationality ,Kidney Function Tests ,Male ,Middle Aged ,Predictive Value of Tests ,Renal Insufficiency ,Chronic ,Retrospective Studies ,Sensitivity and Specificity ,Severity of Illness Index ,Urinalysis ,CKD Prognosis Consortium ,CKD stage ,Chronic kidney disease ,albuminuria ,anemia ,diabetes ,glomerular filtration rate ,hematocrit ,hemoglobin ,hyperparathyroidism ,hypertension ,individual-level meta-analysis ,kidney function ,laboratory abnormality ,laboratory tests ,meta-analysis ,serum bicarbonate ,serum calcium ,serum intact parathyroid hormone ,serum phosphorus ,serum potassium ,staging system ,Public Health and Health Services ,Urology & Nephrology ,Clinical sciences - Abstract
Rationale & objectiveChronic kidney disease (CKD) is complicated by abnormalities that reflect disruption in filtration, tubular, and endocrine functions of the kidney. Our aim was to explore the relationship of specific laboratory result abnormalities and hypertension with the estimated glomerular filtration rate (eGFR) and albuminuria CKD staging framework.Study designCross-sectional individual participant-level analyses in a global consortium.Setting & study populations17 CKD and 38 general population and high-risk cohorts.Selection criteria for studiesCohorts in the CKD Prognosis Consortium with data for eGFR and albuminuria, as well as a measurement of hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, or calcium, or hypertension.Data extractionData were obtained and analyzed between July 2015 and January 2018.Analytical approachWe modeled the association of eGFR and albuminuria with hemoglobin, bicarbonate, phosphorus, parathyroid hormone, potassium, and calcium values using linear regression and with hypertension and categorical definitions of each abnormality using logistic regression. Results were pooled using random-effects meta-analyses.ResultsThe CKD cohorts (n=254,666 participants) were 27% women and 10% black, with a mean age of 69 (SD, 12) years. The general population/high-risk cohorts (n=1,758,334) were 50% women and 2% black, with a mean age of 50 (16) years. There was a strong graded association between lower eGFR and all laboratory result abnormalities (ORs ranging from 3.27 [95% CI, 2.68-3.97] to 8.91 [95% CI, 7.22-10.99] comparing eGFRs of 15 to 29 with eGFRs of 45 to 59mL/min/1.73m2), whereas albuminuria had equivocal or weak associations with abnormalities (ORs ranging from 0.77 [95% CI, 0.60-0.99] to 1.92 [95% CI, 1.65-2.24] comparing urinary albumin-creatinine ratio > 300 vs < 30mg/g).LimitationsVariations in study era, health care delivery system, typical diet, and laboratory assays.ConclusionsLower eGFR was strongly associated with higher odds of multiple laboratory result abnormalities. Knowledge of risk associations might help guide management in the heterogeneous group of patients with CKD.
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- 2019
19. Adiposity and risk of decline in glomerular filtration rate: meta-analysis of individual participant data in a global consortium
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Chang, Alex R, Grams, Morgan E, Ballew, Shoshana H, Bilo, Henk, Correa, Adolfo, Evans, Marie, Gutierrez, Orlando M, Hosseinpanah, Farhad, Iseki, Kunitoshi, Kenealy, Timothy, Klein, Barbara, Kronenberg, Florian, Lee, Brian J, Li, Yuanying, Miura, Katsuyuki, Navaneethan, Sankar D, Roderick, Paul J, Valdivielso, Jose M, Visseren, Frank LJ, Zhang, Luxia, Gansevoort, Ron T, Hallan, Stein I, Levey, Andrew S, Matsushita, Kunihiro, Shalev, Varda, Woodward, Mark, Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Yatsuya, Hiroshi, Tamakoshi, Koji, Hirakawa, Yoshihisa, Coresh, Josef, Sang, Yingying, Polkinghorne, Kevan, Chadban, Steven, Atkins, Robert, Levin, Adeera, Djurdjev, Ognjenka, Klein, Ron, Lee, Kristine, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Tang, Mila, Heine, Gunnar, Emrich, Insa, Zawada, Adam, Bauer, Lucie, Nally, Joseph, Schold, Jesse, Shlipak, Michael, Sarnak, Mark, Katz, Ronit, Hiramoto, Jade, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hamano, Takayuki, Hasegawa, Takeshi, Fujii, Naohiko, Jafar, Tazeen, Hatcher, Juanita, Poulter, Neil, Chaturvedi, Nish, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Brenner, Hermann, Schöttker, Ben, Saum, Kai-Uwe, Rothenbacher, Dietrich, Fox, Caroline, Hwang, Shih-Jen, Köttgen, Anna, Schneider, Markus P, Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, Ito, Sadayoshi, Miyazaki, Mariko, Nakayama, Masaaki, Yamada, Cirillo, Massimo, Romundstad, Solfrid, Øvrehus, Marius, Langlo, Knut Asbjørn, Irie, Fujiko, Sairenchi, Toshimi, Rebholz, Casey M, and Young, Bessie
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Epidemiology ,Health Sciences ,Obesity ,Kidney Disease ,Cardiovascular ,Aging ,Prevention ,Nutrition ,Clinical Research ,Good Health and Well Being ,Adiposity ,Adult ,Aged ,Aged ,80 and over ,Body Height ,Body Mass Index ,Cohort Studies ,Female ,Glomerular Filtration Rate ,Humans ,Kidney Failure ,Chronic ,Male ,Middle Aged ,Mortality ,Risk Factors ,Waist Circumference ,CKD Prognosis Consortium ,Clinical Sciences ,Public Health and Health Services ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences ,Psychology - Abstract
ObjectiveTo evaluate the associations between adiposity measures (body mass index, waist circumference, and waist-to-height ratio) with decline in glomerular filtration rate (GFR) and with all cause mortality.DesignIndividual participant data meta-analysis.SettingCohorts from 40 countries with data collected between 1970 and 2017.ParticipantsAdults in 39 general population cohorts (n=5 459 014), of which 21 (n=594 496) had data on waist circumference; six cohorts with high cardiovascular risk (n=84 417); and 18 cohorts with chronic kidney disease (n=91 607).Main outcome measuresGFR decline (estimated GFR decline ≥40%, initiation of kidney replacement therapy or estimated GFR
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- 2019
20. Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442–1451
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Astor, Brad, Appel, Lawrence J, Levin, Adeera, Tang, Mila, Djurdjev, Ognjenka, Navaneethan, Sankar D, Jolly, Stacey E, Schold, Jesse D, Nally, Joseph V, Wheeler, David C, Emberson, Jonathan, Townend, John, Landray, Martin, Feldman, Harold I, Hsu, Chi-yuan, Lash, James P, Kalra, Philip A, Ritchie, James P, Maharajan, Raman, Middleton, Rachel J, O’Donoghue, Donal J, Eckardt, Kai-Uwe, Schneider, Markus P, Köttgen, Anna, Kronenberg, Florian, Bärthlein, Barbara, Chang, Alex R, Green, Jamie A, Kirchner, H Lester, Ho, Kevin, Marks, Angharad, Black, Corri, Prescott, Gordon J, Fluck, Nick, Nakayama, Masaaki, Miyazaki, Mariko, Yamamoto, Tae, Yamada, Wang, Angela Yee-Moon, Cheung, Sharon, Wong, Sharon, Chu, Jessie, Wu, Henry, Garg, Amit X, McArthur, Eric, Nash, Danielle M, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Wetzels, Jack FM, van Zuilen, Arjan D, van den Brand, Jan A, Levey, Andrew S, Inker, Lesley A, Sarnak, Mark J, Tighiouart, Hocine, Zhang, Haitao, Stengel, Benedicte, Metzger, Marie, Flamant, Martin, Houillier, Pascal, Haymann, Jean-Philippe, Rios, Pablo G, Mazzuchi, Nelson, Gadola, Liliana, Lamadrid, Verónica, Sola, Laura, Collins, John F, Elley, C Raina, Kenealy, Timothy, Moranne, Olivier, Couchoud, Cecile, Vigneau, Cecile, Brunskill, Nigel J, Major, Rupert W, Shepherd, David, Medcalf, James F, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, Molnar, Miklos Z, Sumida, Keiichi, Potukuchi, Praveen K, Heerspink, Hiddo JL, de Zeeuw, Dick, Brenner, Barry, Carrero, Juan Jesus, Gasparini, Alessandro, Qureshi, Abdul Rashid, Elinder, Carl-Gustaf, Visseren, Frank LJ, van der Graaf, Yolanda, Evans, Marie, Stendahl, Maria, Schön, Staffan, Segelmark, Mårten, Prütz, Karl-Göran, Naimark, David M, Tangri, Navdeep, and Mark, Patrick B
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Renal and urogenital ,Chronic Kidney Disease Prognosis Consortium ,Clinical Sciences ,Urology & Nephrology - Abstract
The Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: • African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr.; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Rachel J. Middleton, Donal J. O'Donoghue; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Köttgen, Florian Kronenberg, Barbara Bärthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Ontario Institute for Clinical Evaluative Sciences, Provincial Kidney, Dialysis and Transplantation program (ICES KDT): Amit X. Garg, Eric McArthur, Danielle M. Nash; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study (NephroTest): Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, Verónica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agées (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Alessandro Gasparini, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schön, Mårten Segelmark, Karl-Göran Prütz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.• CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.• CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).• Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director).
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- 2018
21. Evans M, Grams ME, Sang Y, et al., for the Chronic Kidney Disease Prognosis Consortium. Risk factors for prognosis in patients with severely decreased GFR. Kidney Int Rep. 2018;3:625–637
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Astor, Brad, Appel, Lawrence J, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Navaneethan, Sankar D, Jolly, Stacey E, Schold, Jesse D, Nally, Joseph V, Wheeler, David C, Emberson, Jonathan, Townend, John, Landray, Martin, Feldman, Harold I, Hsu, Chi-yuan, Lash, James P, Kalra, Philip A, Ritchie, James P, Maharajan, Raman, Alderson, Helen, Lane, Beverly, Eckardt, Kai-Uwe, Schneider, Markus P, Köttgen, Anna, Kronenberg, Florian, Bärthlein, Barbara, Chang, Alex R, Green, Jamie A, Kirchner, H Lester, Ho, Kevin, Marks, Angharad, Black, Corri, Prescott, Gordon J, Fluck, Nick, Nakayama, Masaaki, Miyazaki, Mariko, Yamamoto, Tae, Yamada, Wang, Angela Yee-Moon, Cheung, Sharon, Wong, Sharon, Chu, Jessie, Wu, Henry, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Wetzels, Jack FM, van Zuilen, Arjan D, van den Brand, Jan A, Levey, Andrew S, Inker, Lesley A, Sarnak, Mark J, Tighiouart, Hocine, Zhang, Haitao, Stengel, Benedicte, Rios, Pablo G, Mazzuchi, Nelson, Gadola, Liliana, Lamadrid, Verónica, Sola, Laura, Collins, John F, Elley, C Raina, Kenealy, Timothy, Moranne, Olivier, Couchoud, Cecile, Vigneau, Cecile, Brunskill, Nigel J, Major, Rupert W, Shepherd, David, Medcalf, James F, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, Molnar, Miklos Z, Sumida, Keiichi, Potukuchi, Praveen K, Heerspink, Hiddo JL, de Zeeuw, Dick, Brenner, Barry, Carrero, Juan Jesus, Barany, Peter, Qureshi, Abdul Rashid, Elinder, Carl-Gustaf, Visseren, Frank LJ, van der Graaf, Yolanda, Evans, Marie, Stendahl, Maria, Schön, Staffan, Segelmark, Mårten, Prütz, Karl-Göran, Naimark, David M, Tangri, Navdeep, Mark, Patrick B, Traynor, Jamie P, Geddes, Colin C, Thomson, Peter C, and Coresh, Josef
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Biomedical and Clinical Sciences ,Clinical Sciences ,Renal and urogenital ,Good Health and Well Being ,Chronic Kidney Disease Prognosis Consortium ,Biomedical and clinical sciences ,Health sciences - Abstract
[This corrects the article DOI: 10.1016/j.ekir.2018.01.002.].
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- 2018
22. Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis.
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Kovesdy, Csaba P, Matsushita, Kunihiro, Sang, Yingying, Brunskill, Nigel J, Carrero, Juan J, Chodick, Gabriel, Hasegawa, Takeshi, Heerspink, Hiddo L, Hirayama, Atsushi, Landman, Gijs WD, Levin, Adeera, Nitsch, Dorothea, Wheeler, David C, Coresh, Josef, Hallan, Stein I, Shalev, Varda, Grams, Morgan E, Astor, Brad, Appel, Larry, Greene, Tom, Chen, Teresa, Chalmers, John, Woodward, Mark, Arima, Hisatomi, Perkovic, Vlado, Djurdjev, Ognjenka, Zhang, Luxia, Liu, Lisheng, Zhao, Minghui, Wang, Fang, Wang, Jinwei, Tang, Mila, Iso, Hiroyasu, Yamagishi, Kazumasa, Umesawa, Mitsumasa, Muraki, Isao, Fukagawa, Masafumi, Maruyama, Shoichi, Hamano, Takayuki, Fujii, Naohiko, Wheeler, David, Emberson, John, Townend, John, Landray, Martin, Green, Jamie, Kirchner, H Lester, Chang, Alex R, Cirillo, Massimo, Jee, Sun Ha, Kimm, Heejin, Mok, Yejin, Wetzels, Jack FM, Blankestijn, Peter J, van Zuilen, Arjan D, Bots, M, Sarnak, Mark, Inker, Lesley, Roderick, Paul, Fletcher, Astrid, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen B, Nadukuru, Rajiv, Brunskill, Nigel, Major, Rupert, Shepherd, David, Medcalf, James, Gansevoort, Ron T, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, Jassal, Simerjot K, Bergstrom, Jaclyn, Ix, Joachim H, Barrett-Connor, Elizabeth, Kovesdy, Csaba, Kalantar-Zadeh, Kamyar, de Zeeuw, Dick, Brenner, Barry, Gasparini, Alessandro, Elinder, Carl-Gustaf, Barany, Peter, Evans, Marie, Segelmark, Mårten, Stendahl, Maria, Schön, Staffan, Tangri, Navdeep, Sud, Maneesh, Naimark, David, Wen, Chi-Pang, and Tsao, Chwen-Keng
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Kidney Disease ,Prevention ,Clinical Research ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Renal and urogenital ,Cardiovascular ,Good Health and Well Being ,Adult ,Aged ,Albuminuria ,Cardiovascular Diseases ,Cause of Death ,Comorbidity ,Glomerular Filtration Rate ,Humans ,Hyperkalemia ,Hypokalemia ,Kidney Failure ,Chronic ,Middle Aged ,Prognosis ,Renal Insufficiency ,Chronic ,Risk Factors ,Potassium ,Estimated glomerular filtration rate ,End-stage renal disease ,Mortality ,CKD Prognosis Consortium ,Cardiorespiratory Medicine and Haematology ,Clinical Sciences ,Cardiovascular System & Hematology - Abstract
AimsBoth hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium.Methods and resultsWe performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 ± 16 years, average eGFR was 83 ± 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 ± 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts.ConclusionsOutpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria.
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- 2018
23. Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes
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Gusarova, Viktoria, O’Dushlaine, Colm, Teslovich, Tanya M, Benotti, Peter N, Mirshahi, Tooraj, Gottesman, Omri, Van Hout, Cristopher V, Murray, Michael F, Mahajan, Anubha, Nielsen, Jonas B, Fritsche, Lars, Wulff, Anders Berg, Gudbjartsson, Daniel F, Sjögren, Marketa, Emdin, Connor A, Scott, Robert A, Lee, Wen-Jane, Small, Aeron, Kwee, Lydia C, Dwivedi, Om Prakash, Prasad, Rashmi B, Bruse, Shannon, Lopez, Alexander E, Penn, John, Marcketta, Anthony, Leader, Joseph B, Still, Christopher D, Kirchner, H Lester, Mirshahi, Uyenlinh L, Wardeh, Amr H, Hartle, Cassandra M, Habegger, Lukas, Fetterolf, Samantha N, Tusie-Luna, Teresa, Morris, Andrew P, Holm, Hilma, Steinthorsdottir, Valgerdur, Sulem, Patrick, Thorsteinsdottir, Unnur, Rotter, Jerome I, Chuang, Lee-Ming, Damrauer, Scott, Birtwell, David, Brummett, Chad M, Khera, Amit V, Natarajan, Pradeep, Orho-Melander, Marju, Flannick, Jason, Lotta, Luca A, Willer, Cristen J, Holmen, Oddgeir L, Ritchie, Marylyn D, Ledbetter, David H, Murphy, Andrew J, Borecki, Ingrid B, Reid, Jeffrey G, Overton, John D, Hansson, Ola, Groop, Leif, Shah, Svati H, Kraus, William E, Rader, Daniel J, Chen, Yii-Der I, Hveem, Kristian, Wareham, Nicholas J, Kathiresan, Sekar, Melander, Olle, Stefansson, Kari, Nordestgaard, Børge G, Tybjærg-Hansen, Anne, Abecasis, Goncalo R, Altshuler, David, Florez, Jose C, Boehnke, Michael, McCarthy, Mark I, Yancopoulos, George D, Carey, David J, Shuldiner, Alan R, Baras, Aris, Dewey, Frederick E, and Gromada, Jesper
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Diabetes ,Atherosclerosis ,Cardiovascular ,Metabolic and endocrine ,Amino Acid Substitution ,Angiopoietin-Like Protein 4 ,Animals ,Blood Glucose ,Case-Control Studies ,Diabetes Mellitus ,Type 2 ,Female ,Gene Silencing ,Genetic Association Studies ,Genetic Variation ,Heterozygote ,Homeostasis ,Humans ,Insulin Resistance ,Lipoprotein Lipase ,Male ,Mice ,Mice ,Inbred C57BL ,Mice ,Knockout ,Risk Factors ,Exome Sequencing - Abstract
Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85-0.92, p = 6.3 × 10-10), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49-0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D.
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- 2018
24. Comparing enhancements to well-child visits in the prevention of obesity: ENCIRCLE cluster-randomized controlled trial
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Bailey-Davis, Lisa, Moore, Amy M., Poulsen, Melissa N., Dzewaltowski, David A., Cummings, Stacey, DeCriscio, Laina R., Hosterman, Jennifer Franceschelli, Huston, Daniel, Kirchner, H. Lester, Lutcher, Shawnee, McCabe, Carolyn, Welk, Gregory J., and Savage, Jennifer S.
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- 2022
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25. Genotype-first analysis in an unselected health system-based population reveals variable phenotypic severity of COL4A5 variants
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Zellers, McKenzie, primary, Solanki, Kaushal, additional, Retterer, Kyle, additional, Murphy, Karyn M, additional, Kelly, Melissa A, additional, Kirchner, H. Les, additional, Bucaloiu, Ion Dan, additional, Mirshahi, Tooraj, additional, Moore, Bryn, additional, and Chang, Alexander R, additional
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- 2024
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26. Retrospective Comparison of Outcomes and Cost of a Virtual vs. Center-Based Cardiac Rehabilitation Program
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Shah, Neil D, primary, Banta, Conor W, additional, Berger, Andrea L, additional, Hattenberger, Andrea, additional, Zimmerman, Alex, additional, Martin, Bryan E, additional, Wu, Edward, additional, Majumdar, Usnish, additional, Kirchner, H Lester, additional, and Matsumura, Martin E, additional
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- 2024
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27. Genomic Screening for Pathogenic Transthyretin Variants Finds Evidence of Underdiagnosed Amyloid Cardiomyopathy From Health Records
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Carry, Brendan J., Young, Katelyn, Fielden, Samuel, Kelly, Melissa A., Sturm, Amy C., Avila, J. David, Martin, Christa L., Kirchner, H. Lester, Fornwalt, Brandon K., and Haggerty, Christopher M.
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- 2021
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28. Geriatric conditions and treatment burden following diagnosis of non-muscle- invasive bladder cancer in older adults: A population-based analysis
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Garg, Tullika, Johns, Alicia, Young, Amanda J., Nielsen, Matthew E., Tan, Hung-Jui, McMullen, Carmit K., Kirchner, H. Lester, Cohen, Harvey J., and Murphy, Terrence E.
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- 2021
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29. Measures of chronic kidney disease and risk of incident peripheral artery disease: a collaborative meta-analysis of individual participant data
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Matsushita, Kunihiro, Ballew, Shoshana H, Coresh, Josef, Arima, Hisatomi, Ärnlöv, Johan, Cirillo, Massimo, Ebert, Natalie, Hiramoto, Jade S, Kimm, Heejin, Shlipak, Michael G, Visseren, Frank LJ, Gansevoort, Ron T, Kovesdy, Csaba P, Shalev, Varda, Woodward, Mark, Kronenberg, Florian, Chalmers, John, Perkovic, Vlado, Grams, Morgan E, Sang, Yingying, Schaeffner, Elke, Martus, Peter, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Heine, Gunnar, Seiler, Sarah, Zawada, Adam, Emrich, Insa, Sarnak, Mark, Katz, Ronit, Brenner, Hermann, Schöttker, Ben, Rothenbacher, Dietrich, Saum, Kai-Uwe, Köttgen, Anna, Schneider, Markus, Eckardt, Kai-Uwe, Green, Jamie, Kirchner, H Lester, Chang, Alex R, Black, Corri, Marks, Angharad, Prescott, Gordon, Clark, Laura, Fluck, Nick, Jee, Sun Ha, Mok, Yejin, Chodick, Gabriel, Wetzels, Jack FM, Blankestijn, Peter J, van Zuilen, Arjan D, Bots, M, Peralta, Carmen, Hiromoto, Jade, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen B, Nadukuru, Rajiv, Kenealy, Timothy, Elley, C Raina, Collins, John F, Drury, Paul L, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, Jassal, Simerjot K, Bergstrom, Jaclyn, Ix, Joachim H, Barrett-Connor, Elizabeth, Kalantar-Zadeh, Kamyar, Carrero, Juan J, Gasparini, Alessandro, Qureshi, Abdul Rashid, Barany, Peter, Algra, Ale, van der Graaf, Yolanda, Evans, Marie, Segelmark, Mårten, Stendahl, Maria, Schön, Staffan, Tangri, Navdeep, Sud, Maneesh, Naimark, David, Lannfelt, Lars, Larsson, Anders, Hallan, Stein, Levey, Andrew S, Chen, Jingsha, and Kwak, Lucia
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Clinical Research ,Kidney Disease ,Prevention ,Renal and urogenital ,Good Health and Well Being ,Adult ,Aged ,Albuminuria ,Creatinine ,Databases ,Factual ,Female ,Glomerular Filtration Rate ,Humans ,Incidence ,Male ,Middle Aged ,Peripheral Arterial Disease ,Renal Insufficiency ,Chronic ,Risk Factors ,Chronic Kidney Disease Prognosis Consortium ,Medical Biochemistry and Metabolomics ,Clinical Sciences ,Public Health and Health Services - Abstract
BackgroundSome evidence suggests that chronic kidney disease is a risk factor for lower-extremity peripheral artery disease. We aimed to quantify the independent and joint associations of two measures of chronic kidney disease (estimated glomerular filtration rate [eGFR] and albuminuria) with the incidence of peripheral artery disease.MethodsIn this collaborative meta-analysis of international cohorts included in the Chronic Kidney Disease Prognosis Consortium (baseline measurements obtained between 1972 and 2014) with baseline measurements of eGFR and albuminuria, at least 1000 participants (this criterion not applied to cohorts exclusively enrolling patients with chronic kidney disease), and at least 50 peripheral artery disease events, we analysed adult participants without peripheral artery disease at baseline at the individual patient level with Cox proportional hazards models to quantify associations of creatinine-based eGFR, urine albumin-to-creatinine ratio (ACR), and dipstick proteinuria with the incidence of peripheral artery disease (including hospitalisation with a diagnosis of peripheral artery disease, intermittent claudication, leg revascularisation, and leg amputation). We assessed discrimination improvement through c-statistics.FindingsWe analysed 817 084 individuals without a history of peripheral artery disease at baseline from 21 cohorts. 18 261 cases of peripheral artery disease were recorded during follow-up across cohorts (median follow-up was 7·4 years [IQR 5·7-8·9], range 2·0-15·8 years across cohorts). Both chronic kidney disease measures were independently associated with the incidence of peripheral artery disease. Compared with an eGFR of 95 mL/min per 1·73 m2, adjusted hazard ratios (HRs) for incident study-specific peripheral artery disease was 1·22 (95% CI 1·14-1·30) at an eGFR of 45 mL/min per 1·73 m2 and 2·06 (1·70-2·48) at an eGFR of 15 mL/min per 1·73 m2. Compared with an ACR of 5 mg/g, the adjusted HR for incident study-specific peripheral artery disease was 1·50 (1·41-1·59) at an ACR of 30 mg/g and 2·28 (2·12-2·44) at an ACR of 300 mg/g. The adjusted HR at an ACR of 300 mg/g versus 5 mg/g was 3·68 (95% CI 3·00-4·52) for leg amputation. eGFR and albuminuria contributed multiplicatively (eg, adjusted HR 5·76 [4·90-6·77] for incident peripheral artery disease and 10·61 [5·70-19·77] for amputation in eGFR
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- 2017
30. Genetic and Pharmacologic Inactivation of ANGPTL3 and Cardiovascular Disease
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Dewey, Frederick E, Gusarova, Viktoria, Dunbar, Richard L, O'Dushlaine, Colm, Schurmann, Claudia, Gottesman, Omri, McCarthy, Shane, Van Hout, Cristopher V, Bruse, Shannon, Dansky, Hayes M, Leader, Joseph B, Murray, Michael F, Ritchie, Marylyn D, Kirchner, H Lester, Habegger, Lukas, Lopez, Alex, Penn, John, Zhao, An, Shao, Weiping, Stahl, Neil, Murphy, Andrew J, Hamon, Sara, Bouzelmat, Aurelie, Zhang, Rick, Shumel, Brad, Pordy, Robert, Gipe, Daniel, Herman, Gary A, Sheu, Wayne HH, Lee, I-Te, Liang, Kae-Woei, Guo, Xiuqing, Rotter, Jerome I, Chen, Yii-Der I, Kraus, William E, Shah, Svati H, Damrauer, Scott, Small, Aeron, Rader, Daniel J, Wulff, Anders Berg, Nordestgaard, Børge G, Tybjærg-Hansen, Anne, van den Hoek, Anita M, Princen, Hans MG, Ledbetter, David H, Carey, David J, Overton, John D, Reid, Jeffrey G, Sasiela, William J, Banerjee, Poulabi, Shuldiner, Alan R, Borecki, Ingrid B, Teslovich, Tanya M, Yancopoulos, George D, Mellis, Scott J, Gromada, Jesper, and Baras, Aris
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Genetics ,Heart Disease ,Clinical Research ,Atherosclerosis ,Heart Disease - Coronary Heart Disease ,Cardiovascular ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Aged ,Angiopoietin-Like Protein 3 ,Angiopoietin-like Proteins ,Angiopoietins ,Animals ,Antibodies ,Monoclonal ,Cardiovascular Diseases ,Coronary Artery Disease ,Disease Models ,Animal ,Dose-Response Relationship ,Drug ,Double-Blind Method ,Dyslipidemias ,Female ,Humans ,Lipid Metabolism ,Lipids ,Male ,Mice ,Mice ,Inbred Strains ,Middle Aged ,Mutation ,Medical and Health Sciences ,General & Internal Medicine - Abstract
BackgroundLoss-of-function variants in the angiopoietin-like 3 gene (ANGPTL3) have been associated with decreased plasma levels of triglycerides, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. It is not known whether such variants or therapeutic antagonism of ANGPTL3 are associated with a reduced risk of atherosclerotic cardiovascular disease.MethodsWe sequenced the exons of ANGPTL3 in 58,335 participants in the DiscovEHR human genetics study. We performed tests of association for loss-of-function variants in ANGPTL3 with lipid levels and with coronary artery disease in 13,102 case patients and 40,430 controls from the DiscovEHR study, with follow-up studies involving 23,317 case patients and 107,166 controls from four population studies. We also tested the effects of a human monoclonal antibody, evinacumab, against Angptl3 in dyslipidemic mice and against ANGPTL3 in healthy human volunteers with elevated levels of triglycerides or LDL cholesterol.ResultsIn the DiscovEHR study, participants with heterozygous loss-of-function variants in ANGPTL3 had significantly lower serum levels of triglycerides, HDL cholesterol, and LDL cholesterol than participants without these variants. Loss-of-function variants were found in 0.33% of case patients with coronary artery disease and in 0.45% of controls (adjusted odds ratio, 0.59; 95% confidence interval, 0.41 to 0.85; P=0.004). These results were confirmed in the follow-up studies. In dyslipidemic mice, inhibition of Angptl3 with evinacumab resulted in a greater decrease in atherosclerotic lesion area and necrotic content than a control antibody. In humans, evinacumab caused a dose-dependent placebo-adjusted reduction in fasting triglyceride levels of up to 76% and LDL cholesterol levels of up to 23%.ConclusionsGenetic and therapeutic antagonism of ANGPTL3 in humans and of Angptl3 in mice was associated with decreased levels of all three major lipid fractions and decreased odds of atherosclerotic cardiovascular disease. (Funded by Regeneron Pharmaceuticals and others; ClinicalTrials.gov number, NCT01749878 .).
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- 2017
31. Protein-Truncating Variants at the Cholesteryl Ester Transfer Protein Gene and Risk for Coronary Heart Disease
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Nomura, Akihiro, Won, Hong-Hee, Khera, Amit V, Takeuchi, Fumihiko, Ito, Kaoru, McCarthy, Shane, Emdin, Connor A, Klarin, Derek, Natarajan, Pradeep, Zekavat, Seyedeh M, Gupta, Namrata, Peloso, Gina M, Borecki, Ingrid B, Teslovich, Tanya M, Asselta, Rosanna, Duga, Stefano, Merlini, Piera A, Correa, Adolfo, Kessler, Thorsten, Wilson, James G, Bown, Matthew J, Hall, Alistair S, Braund, Peter S, Carey, David J, Murray, Michael F, Kirchner, H Lester, Leader, Joseph B, Lavage, Daniel R, Manus, J Neil, Hartze, Dustin N, Samani, Nilesh J, Schunkert, Heribert, Marrugat, Jaume, Elosua, Roberto, McPherson, Ruth, Farrall, Martin, Watkins, Hugh, Juang, Jyh-Ming J, Hsiung, Chao A, Lin, Shih-Yi, Wang, Jun-Sing, Tada, Hayato, Kawashiri, Masa-Aki, Inazu, Akihiro, Yamagishi, Masakazu, Katsuya, Tomohiro, Nakashima, Eitaro, Nakatochi, Masahiro, Yamamoto, Ken, Yokota, Mitsuhiro, Momozawa, Yukihide, Rotter, Jerome I, Lander, Eric S, Rader, Daniel J, Danesh, John, Ardissino, Diego, Gabriel, Stacey, Willer, Cristen J, Abecasis, Goncalo R, Saleheen, Danish, Kubo, Michiaki, Kato, Norihiro, Ida Chen, Yii-Der, Dewey, Frederick E, and Kathiresan, Sekar
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Clinical Sciences ,Genetics ,Cardiovascular ,Heart Disease ,Atherosclerosis ,Heart Disease - Coronary Heart Disease ,Adult ,Aged ,Case-Control Studies ,Cholesterol Ester Transfer Proteins ,Coronary Disease ,Female ,Genetic Variation ,Humans ,Male ,Middle Aged ,Risk Factors ,case-control studies ,cholesteryl ester transfer protein ,coronary disease ,lipids ,Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology ,Clinical sciences - Abstract
RationaleTherapies that inhibit CETP (cholesteryl ester transfer protein) have failed to demonstrate a reduction in risk for coronary heart disease (CHD). Human DNA sequence variants that truncate the CETP gene may provide insight into the efficacy of CETP inhibition.ObjectiveTo test whether protein-truncating variants (PTVs) at the CETP gene were associated with plasma lipid levels and CHD.Methods and resultsWe sequenced the exons of the CETP gene in 58 469 participants from 12 case-control studies (18 817 CHD cases, 39 652 CHD-free controls). We defined PTV as those that lead to a premature stop, disrupt canonical splice sites, or lead to insertions/deletions that shift frame. We also genotyped 1 Japanese-specific PTV in 27561 participants from 3 case-control studies (14 286 CHD cases, 13 275 CHD-free controls). We tested association of CETP PTV carrier status with both plasma lipids and CHD. Among 58 469 participants with CETP gene-sequencing data available, average age was 51.5 years and 43% were women; 1 in 975 participants carried a PTV at the CETP gene. Compared with noncarriers, carriers of PTV at CETP had higher high-density lipoprotein cholesterol (effect size, 22.6 mg/dL; 95% confidence interval, 18-27; P
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- 2017
32. Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity
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Liu, Yaowu, Zhang, Xiaoyu, Lee, Jiwon, Smelser, Diane, Cade, Brian, Chen, Han, Zhou, Hufeng, Kirchner, H. Lester, Lin, Xihong, Mukherjee, Sutapa, Hillman, David, Liu, Ching-Ti, Redline, Susan, and Sofer, Tamar
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- 2021
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33. Abstract 13914: Additional ASCVD Risk Factors for Patients With Diabetes: FIB-4 Score and NLR Are Higher in Adults With Diabetes and Current Risk Enhancers vs No Risk Enhancers in Real-World Evidence
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Chapagain, Himal, Alish, Yousef, Becich, Michael, Bradley, Alison, Fernandez, Soledad, Ford, Dan, Hwang, Wenke, Jeong, Jong, Jurczak, Martha, Kirchner, H Lester, McTigue, Kathleen M, Morgan, Richard, Paranjape, Anuradha, Thomas, Neena, Williams, David, and Arnold, Jonathan
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- 2022
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34. Abstract 13909: Use of Advanced Lipoprotein Testing in Real-World Data: A Cross Sectional Study Across Multiple Health Systems
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Boricha, Hetal, Alish, Yousef, Becich, Michael, Bradley, Alison, Fernandez, Soledad, Ford, Dan, Hwang, Wenke, Jeong, Jong, Jurczak, Martha, Kirchner, H Lester, McTigue, Kathleen M, Morgan, Richard, Paranjape, Anuradha, Thomas, Neena, Williams, David, and Arnold, Jonathan
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- 2022
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35. Abstract 12482: Practical Adherence to AHA/ACC 2018 Guidelines Among Secondary Prevention Patients
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Kainat, Aleesha, Alish, Yousef, Ateya, Mohammad, Becich, Michael J, Bradley, Alison, Demicco, David A, Fernandez, Soledad, Ford, Dan, Hegeman-Dingle, Rozelle, Hwang, Wenke, Jeong, Jong, Jurczak, Martha O, Kirchner, H Lester, McLeod, Euan, McTigue, Kathleen M, Morgan, Richard S, Paranjape, Anuradha, Saccone, Phillip, Thomas, Neena, Townsend, Kevin A, Williams, David A, and Arnold, Jonathan
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- 2022
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36. Abstract 9822: Yield of a Familial Hypercholesterolemia Genetic Diagnosis After Electronic Health Record and Genomic Data Screening
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Gidding, Sam S, Kirchner, H Lester, Brangan, Andrew, HOWARD, WILLIAM, Kelly, Melissa A, Myers, Kelly, Morgan, Kelly, Shuey, Timothy C, Staszak, David, Strande, Natasha T, Walters, Nicole, Yu, Kristen D, Wilemon, Katherine A, Williams, Marc S, Jones, Laney K, and Sturm, Amy C
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- 2022
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37. Deep-learning-assisted analysis of echocardiographic videos improves predictions of all-cause mortality
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Ulloa Cerna, Alvaro E., Jing, Linyuan, Good, Christopher W., vanMaanen, David P., Raghunath, Sushravya, Suever, Jonathan D., Nevius, Christopher D., Wehner, Gregory J., Hartzel, Dustin N., Leader, Joseph B., Alsaid, Amro, Patel, Aalpen A., Kirchner, H. Lester, Pfeifer, John M., Carry, Brendan J., Pattichis, Marios S., Haggerty, Christopher M., and Fornwalt, Brandon K.
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- 2021
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38. Innovative Implementation Strategies for Familial Hypercholesterolemia Cascade Testing: The Impact of Genetic Counseling.
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Morgan, Kelly M., Campbell-Salome, Gemme, Walters, Nicole L., Betts, Megan N., Brangan, Andrew, Johns, Alicia, Kirchner, H. Lester, Lindsey-Mills, Zoe, McGowan, Mary P., Tricou, Eric P., Rahm, Alanna Kulchak, Sturm, Amy C., and Jones, Laney K.
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GENETIC counseling ,FAMILIAL hypercholesterolemia ,POISSON regression ,CHATBOTS ,GENETIC testing - Abstract
The IMPACT-FH study implemented strategies (packet, chatbot, direct contact) to promote family member cascade testing for familial hypercholesterolemia (FH). We evaluated the impact of genetic counseling (GC) on medical outcomes, strategy selection, and cascade testing. Probands (i.e., patients with FH) were recommended to complete GC and select sharing strategies. Comparisons were performed for both medical outcomes and strategy selection between probands with or without GC. GEE models for Poisson regression were used to examine the relationship between proband GC completion and first-degree relative (FDR) cascade testing. Overall, 46.3% (81/175) of probands completed GC. Probands with GC had a median LDL-C reduction of −13.0 mg/dL (−61.0, 4.0) versus −1.0 mg/dL (−16.0, 17.0) in probands without GC (p = 0.0054). Probands with and without GC selected sharing strategies for 65.3% and 40.3% of FDRs, respectively (p < 0.0001). Similarly, 27.1% of FDRs of probands with GC completed cascade testing, while 12.0% of FDRs of probands without GC completed testing (p = 0.0043). Direct contact was selected for 47 relatives in total and completed for 39, leading to the detection of 18 relatives with FH. Proband GC was associated with improved medical outcomes and increased FDR cascade testing. Direct contact effectively identified FH cases for the subset who participated. [ABSTRACT FROM AUTHOR]
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- 2024
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39. Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality
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Ofoma, Uchenna R., Montoya, Juan, Saha, Debdoot, Berger, Andrea, Kirchner, H. Lester, McIlwaine, John K., and Kethireddy, Shravan
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- 2020
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40. A Machine Learning Approach to Management of Heart Failure Populations
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Jing, Linyuan, Ulloa Cerna, Alvaro E., Good, Christopher W., Sauers, Nathan M., Schneider, Gargi, Hartzel, Dustin N., Leader, Joseph B., Kirchner, H. Lester, Hu, Yirui, Riviello, David M., Stough, Joshua V., Gazes, Seth, Haggerty, Allyson, Raghunath, Sushravya, Carry, Brendan J., Haggerty, Christopher M., and Fornwalt, Brandon K.
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- 2020
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41. Structural assessment of an ASR-affected reinforced concrete bridge
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Kirchner, H, primary, van Rooyen, J, additional, van der Spuy, P F, additional, and van Zijl, G P A G, additional
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- 2024
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42. The Relationship Between Integrated Pediatric Psychology and Primary Care Visit Length, Revenue, Content Over 24 Months
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Gormley, Matthew J., Meadows, Tawnya J., Hostermans, Shelley J., Kettlewell, Paul W., Kirchner, H. Lester, and O'Dell, Sean M.
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Childhood mental disorders -- Care and treatment ,Child psychiatric services -- Economic aspects ,Health care teams -- Methods -- Economic aspects ,Primary health care -- Methods -- Economic aspects ,Family and marriage ,Health ,Psychology and mental health - Abstract
Introduction: Integrating behavioral health providers into pediatric primary care to provide behavioral health (BH) services is both effective and efficient; however, the impact of pediatric integrated services on the operational and financial outcomes of primary care provider (PCP) visits has not been thoroughly investigated. The present study examined whether length of practice integration predicts the relationship between BH content addressed in a PCP visit, visit length, and revenue generation. Method: A total of 1,209 pediatric encounters with 25 PCPs across 7 primary care offices in a predominantly rural health system were abstracted for the presence or absence of BH content, visit length, duration of integration, and revenue. [x.sup.2] analyses and the generalized linear model framework were used to address the study objectives. Results: Integration was associated with more PCP visits with a BH topic discussed at 6-11 months of integration but not at 14-24 months. Visits with a BH topic were longer than medical-only visits and shorter when a practice was integrated for 6-11 months but not at 14-24 months of integration. Public insurance and integration were associated with lower revenue generation per minute. Visit content was not associated with PCP revenue. Discussion: Results suggest a relationship between integration and the operational and financial outcomes of PCP visits. This study shows that initial efficiencies or improvements (e.g., time, cost, content) associated with integrating BH may be lost over time. Future studies should evaluate sustainability in relation to program impact. Keywords: behavioral health, primary care, integrated care, pediatric, Greater than 20% of children and adolescents meet diagnostic criteria for at least one behavioral health (BH) disorder, and greater than 40% experience clinically significant impairment because of subclinical presentations [...]
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- 2020
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43. Clinical outcomes of a genomic screening program for actionable genetic conditions
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Buchanan, Adam H., Lester Kirchner, H., Schwartz, Marci L. B., Kelly, Melissa A., Schmidlen, Tara, Jones, Laney K., Hallquist, Miranda L. G., Rocha, Heather, Betts, Megan, Schwiter, Rachel, Butry, Loren, Lazzeri, Amanda L., Frisbie, Lauren R., Rahm, Alanna Kulchak, Hao, Jing, Willard, Huntington F., Martin, Christa L., Ledbetter, David H., Williams, Marc S., and Sturm, Amy C.
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- 2020
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44. Positive impact of genetic counseling assistants on genetic counseling efficiency, patient volume, and cost in a cancer genetics clinic
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Hallquist, Miranda L. G., Tricou, Eric P., Hallquist, Michael N., Savatt, Juliann M., Rocha, Heather, Evans, Alyson E., Deckard, Nicole, Hu, Yirui, Kirchner, H. Lester, Pervola, Josie, Rahm, Alanna Kulchak, Rashkin, Misha, Schmidlen, Tara J., Schwartz, Marci L. B., Williams, Janet L., Williams, Marc S., and Buchanan, Adam H.
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- 2020
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45. Prediction of mortality from 12-lead electrocardiogram voltage data using a deep neural network
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Raghunath, Sushravya, Ulloa Cerna, Alvaro E., Jing, Linyuan, vanMaanen, David P., Stough, Joshua, Hartzel, Dustin N., Leader, Joseph B., Kirchner, H. Lester, Stumpe, Martin C., Hafez, Ashraf, Nemani, Arun, Carbonati, Tanner, Johnson, Kipp W., Young, Katelyn, Good, Christopher W., Pfeifer, John M., Patel, Aalpen A., Delisle, Brian P., Alsaid, Amro, Beer, Dominik, Haggerty, Christopher M., and Fornwalt, Brandon K.
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- 2020
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46. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Diabetes Mellitus, and Hypertension With Acute Kidney Injury
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James, Matthew T, Grams, Morgan E, Woodward, Mark, Elley, C Raina, Green, Jamie A, Wheeler, David C, de Jong, Paul, Gansevoort, Ron T, Levey, Andrew S, Warnock, David G, Sarnak, Mark J, Tonelli, Marcello, Hemmelgarn, Brenda R, Turin, Tanvir Chowdhury, Coresh, Josef, Matsushita, Kunihiro, Grams, Morgan, Sang, Yingying, Shlipak, Michael, Katz, Ronit, Emberson, Jonathan, Landray, Martin J, Townend, Jonathan N, Green, Jamie, Kirchner, H Les, Perkins, Robert, Chang, Alex R, Romundstad, Solfrid, Aasarød, Knut, Øien, Cecilia M, Hallan, Stein, Smith, David H, Thorp, Micah L, Johnson, Eric S, Chodick, Gabriel, Herzel, Esma, Katz, Rachel, Shalev, Varda, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, van der Harst, Pim, Jee, Sun Ha, Kimm, Heejin, Mok, Yejin, Tangri, Navdeep, Naimark, David, Ärnlöv, Johan, Larsson, Anders, Lannfelt, Lars, Kovesdy, Csaba P, Kalantar-Zadeh, Kamyar, de Jong, Paul E, Iseki, Kunitoshi, Stengel, Benedicte, Warnock, David, and Ballew, Shoshana H
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Nutrition ,Kidney Disease ,Clinical Research ,Diabetes ,4.2 Evaluation of markers and technologies ,Detection ,screening and diagnosis ,Metabolic and endocrine ,Renal and urogenital ,Acute Kidney Injury ,Adult ,Aged ,Comorbidity ,Diabetes Mellitus ,Disease Progression ,Female ,Glomerular Filtration Rate ,Humans ,Hypertension ,Incidence ,Kidney Failure ,Chronic ,Male ,Middle Aged ,Prognosis ,Renal Insufficiency ,Chronic ,Estimated glomerular filtration rate ,renal function ,albuminuria ,albumin-creatine ratio ,diabetes ,hypertension ,acute kidney injury ,acute renal failure ,Chronic Kidney Disease Prognosis Consortium ,meta-analysis ,CKD Prognosis Consortium ,Clinical Sciences ,Public Health and Health Services ,Urology & Nephrology - Abstract
BackgroundDiabetes mellitus and hypertension are risk factors for acute kidney injury (AKI). Whether estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (ACR) remain risk factors for AKI in the presence and absence of these conditions is uncertain.Study designMeta-analysis of cohort studies.Setting & population8 general-population (1,285,045 participants) and 5 chronic kidney disease (CKD; 79,519 participants) cohorts.Selection criteria for studiesCohorts participating in the CKD Prognosis Consortium.PredictorsDiabetes and hypertension status, eGFR by the 2009 CKD Epidemiology Collaboration creatinine equation, urine ACR, and interactions.OutcomeHospitalization with AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results.ResultsDuring a mean follow-up of 4 years, there were 16,480 episodes of AKI in the general-population and 2,087 episodes in the CKD cohorts. Low eGFRs and high ACRs were associated with higher risks of AKI in individuals with or without diabetes and with or without hypertension. When compared to a common reference of eGFR of 80mL/min/1.73m(2) in nondiabetic patients, HRs for AKI were generally higher in diabetic patients at any level of eGFR. The same was true for diabetic patients at all levels of ACR compared with nondiabetic patients. The risk gradient for AKI with lower eGFRs was greater in those without diabetes than with diabetes, but similar with higher ACRs in those without versus with diabetes. Those with hypertension had a higher risk of AKI at eGFRs>60mL/min/1.73m(2) than those without hypertension. However, risk gradients for AKI with both lower eGFRs and higher ACRs were greater for those without than with hypertension.LimitationsAKI identified by diagnostic code.ConclusionsLower eGFRs and higher ACRs are associated with higher risks of AKI among individuals with or without either diabetes or hypertension.
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- 2015
47. A Meta-analysis of the Association of Estimated GFR, Albuminuria, Age, Race, and Sex With Acute Kidney Injury
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Grams, Morgan E, Sang, Yingying, Ballew, Shoshana H, Gansevoort, Ron T, Kimm, Heejin, Kovesdy, Csaba P, Naimark, David, Oien, Cecilia, Smith, David H, Coresh, Josef, Sarnak, Mark J, Stengel, Benedicte, Tonelli, Marcello, Hemmelgarn, Brenda R, James, Matthew T, Turin, Tanvir Chowdhury, Matsushita, Kunihiro, Grams, Morgan, Shlipak, Michael, Katz, Ronit, Wheeler, David C, Emberson, Jonathan, Landray, Martin J, Townend, Jonathan N, Green, Jamie, Kirchner, H Les, Perkins, Robert, Chang, Alex R, Romundstad, Solfrid, Aasarød, Knut, Øien, Cecilia M, Hallan, Stein, Thorp, Micah L, Johnson, Eric S, Chodick, Gabriel, Herzel, Esma, Katz, Rachel, Shalev, Varda, Bakker, Stephan JL, Heerspink, Hiddo J Lambers, van der Harst, Pim, Jee, Sun Ha, Mok, Yejin, Tangri, Navdeep, Ärnlöv, Johan, Larsson, Anders, Lannfelt, Lars, Kalantar-Zadeh, Kamyar, de Jong, Paul E, Iseki, Kunitoshi, Levey, Andrew S, Warnock, David, and Woodward, Mark
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Clinical Research ,Prevention ,Kidney Disease ,Renal and urogenital ,Acute Kidney Injury ,Adolescent ,Adult ,African Americans ,Age Distribution ,Aged ,Albuminuria ,Female ,Glomerular Filtration Rate ,Humans ,Incidence ,Male ,Middle Aged ,Predictive Value of Tests ,Prognosis ,Racial Groups ,Severity of Illness Index ,Sex Distribution ,Whites ,Young Adult ,Estimated glomerular filtration rate ,renal function ,albuminuria ,albumin-creatinine ratio ,proteinuria ,age ,race/ethnicity ,sex ,acute kidney injury ,acute renal failure ,Chronic Kidney Disease Prognosis Consortium ,meta-analysis ,CKD Prognosis Consortium ,White People ,Black or African American ,Clinical Sciences ,Public Health and Health Services ,Urology & Nephrology - Abstract
BackgroundAcute kidney injury (AKI) is a serious global public health problem. We aimed to quantify the risk of AKI associated with estimated glomerular filtration rate (eGFR), albuminuria (albumin-creatinine ratio [ACR]), age, sex, and race (African American and white).Study designCollaborative meta-analysis.Setting & population8 general-population cohorts (1,285,049 participants) and 5 chronic kidney disease (CKD) cohorts (79,519 participants).Selection criteria for studiesAvailable eGFR, ACR, and 50 or more AKI events.PredictorsAge, sex, race, eGFR, urine ACR, and interactions.OutcomeHospitalized with or for AKI, using Cox proportional hazards models to estimate HRs of AKI and random-effects meta-analysis to pool results.Results16,480 (1.3%) general-population cohort participants had AKI over a mean follow-up of 4 years; 2,087 (2.6%) CKD participants had AKI over a mean follow-up of 1 year. Lower eGFR and higher ACR were strongly associated with AKI. Compared with eGFR of 80mL/min/1.73m(2), the adjusted HR of AKI at eGFR of 45mL/min/1.73m(2) was 3.35 (95% CI, 2.75-4.07). Compared with ACR of 5mg/g, the risk of AKI at ACR of 300mg/g was 2.73 (95% CI, 2.18-3.43). Older age was associated with higher risk of AKI, but this effect was attenuated with lower eGFR or higher ACR. Male sex was associated with higher risk of AKI, with a slight attenuation in lower eGFR but not in higher ACR. African Americans had higher AKI risk at higher levels of eGFR and most levels of ACR.LimitationsOnly 2 general-population cohorts could contribute to analyses by race; AKI identified by diagnostic code.ConclusionsReduced eGFR and increased ACR are consistent strong risk factors for AKI, whereas associations of AKI with age, sex, and race may be weaker in more advanced stages of CKD.
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- 2015
48. Risk and protective factors associated with mental health among female military veterans: results from the veterans’ health study
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Adams, Richard E., Hu, Yirui, Figley, Charles R., Urosevich, Thomas G., Hoffman, Stuart N., Kirchner, H. Lester, Dugan, Ryan J., Boscarino, Joseph J., Withey, Carrie A., and Boscarino, Joseph A.
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- 2021
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49. Change in albuminuria and subsequent risk of end-stage kidney disease: an individual participant-level consortium meta-analysis of observational studies
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Appel, Lawrence J, Greene, Tom, Chen, Teresa K, Chalmers, John, Arima, Hisatomi, Perkovic, Vlado, Levin, Adeera, Djurdjev, Ognjenka, Tang, Mila, Nally, Joseph, Navaneethan, Sankar D, Schold, Jesse D, Weldegiorgis, Misghina, Herrington, William G, Smith, Margaret, Hsu, C Yenchih, Hwang, Shih-Jen, Chang, Alex R, Kirchner, H. Lester, Green, Jamie A, Ho, Kevin, Marks, Angharad, Prescott, Gordon, Clark, Laura E, Fluck, Nick, Shalev, Varda, Chodick, Gabriel, Blankestijn, Peter J, Van Zuilen, Arjan, Van den Brand, Jan A, Sarnak, Mark J, Bottinger, Erwin, Nadkarni, Girish N, Ellis, Stephen G, Nadukuru, Rajiv, Metzger, Marie, Flamant, Martin, Houillier, Pascal, Haymann, Jean-Philippe, Froissart, Marc, Kenealy, Timothy, Elley, Raina C, Collins, John F, Drury, Paul L, Cuddeback, John K, Ciemins, Elizabeth L, Stempniewicz, Rich, Nelson, Robert G, Knowler, William C, Bakker, Stephen J, Major, Rupert W, Medcalf, James F, Shepherd, David, Barrett-Connor, Elizabeth, Bergstrom, Jaclyn, Ix, Joachim H, Molnar, Miklos Z, Sumida, Keiichi, de Zeeuw, Dick, Brenner, Barry, Qureshi, Abdul R, Elinder, Carl-Gustaf, Runesson, Bjorn, Evans, Marie, Segelmark, Marten, Stendahl, Maria, Schön, Staffan, Naimark, David M, Tangri, Navdeep, Sud, Maneesh, Hirayama, Atsushi, Ichikawa, Kazunobu, Bilo, Henk JG, Landman, Gijs WD, Van Hateren, Kornelis JJ, Kleefstra, Nanne, Hallan, Stein I, Ballew, Shoshana H, Chen, Jingsha, Kwak, Lucia, Surapaneni, Aditya, Parving, Hans-Henrik, Rodby, Roger A., Rohde, Richard D, Lewis, Julia B, Lewis, Edmund, Perrone, Ronald D, Abebe, Kaleab Z, Hou, Fan F, Xie, Di, Hunsicker, Lawrence G, Imai, Enyu, Kobayashi, Fumiaki, Makino, Hirofumi, Ito, Sadayoshi, Remuzzi, Giuseppe, Ruggenenti, Piero, Eckardt, Kai-Uwe, Gudmundsdottir, Hrefna, Maciulaitis, Romaldas, Manley, Tom, Smith, Kimberly, Stockbridge, Norman, Thompson, Aliza, Vetter, Thorsten, Willis, Kerry, Zhang, Luxia, Coresh, Josef, Heerspink, Hiddo J L, Sang, Yingying, Matsushita, Kunihiro, Arnlov, Johan, Astor, Brad C, Black, Corri, Brunskill, Nigel J, Carrero, Juan-Jesus, Feldman, Harold I, Fox, Caroline S, Inker, Lesley A, Ishani, Areef, Jassal, Simerjot, Konta, Tsuneo, Polkinghorne, Kevan, Romundstad, Solfrid, Solbu, Marit D, Stempniewicz, Nikita, Stengel, Benedicte, Tonelli, Marcello, Umesawa, Mitsumasa, Waikar, Sushrut S, Wen, Chi-Pang, Wetzels, Jack F M, Woodward, Mark, Grams, Morgan E, Kovesdy, Csaba P, Levey, Andrew S, and Gansevoort, Ron T
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- 2019
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50. Limitations of Noninvasive Tests-Based Population-Level Risk Stratification Strategy for Nonalcoholic Fatty Liver Disease
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Behari, Jaideep, primary, Bradley, Allison, additional, Townsend, Kevin, additional, Becich, Michael J., additional, Cappella, Nickie, additional, Chuang, Cynthia H., additional, Fernandez, Soledad A., additional, Ford, Daniel E., additional, Kirchner, H. Lester, additional, Morgan, Richard, additional, Paranjape, Anuradha, additional, Silverstein, Jonathan C., additional, Williams, David A., additional, Donahoo, W. Troy, additional, Asrani, Sumeet K., additional, Ntanios, Fady, additional, Ateya, Mohammad, additional, Hegeman-Dingle, Rozelle, additional, McLeod, Euan, additional, and McTigue, Kathleen, additional
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- 2023
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