4research
StudyU: A Platform for Designing and Conducting Innovative Digital N-of-1 Trials.
Link: https://doi.org/10.2196/35884 Authors: Konigorski, Stefan; Wernicke, Sarah; Slosarek, Tamara; Zenner, Alexander M; Strelow, Nils; Ruether, Darius F; Henschel, Florian; Manaswini, Manisha; Pottbäcker, Fabian; Edelman, Jonathan A; Owoyele, Babajide; Danieletto, Matteo; Golden, Eddye; Zweig, Micol; Nadkarni, Girish N; Böttinger, Erwin Abstract: N-of-1 trials are the gold standard study design to evaluate individual treatment effects and derive…
Read MoreClinical predictors of response to methotrexate in patients with rheumatoid arthritis: a machine learning approach using clinical trial data.
Link: https://doi.org/10.1186/s13075-022-02851-5 Authors: Duong, Stephanie Q; Crowson, Cynthia S; Athreya, Arjun; Atkinson, Elizabeth J; Davis, John M; Warrington, Kenneth J; Matteson, Eric L; Weinshilboum, Richard; Wang, Liewei; Myasoedova, Elena Abstract: Methotrexate is the preferred initial disease-modifying antirheumatic drug (DMARD) for rheumatoid arthritis (RA). However, clinically useful tools for individualized prediction of response to methotrexate treatment…
Read MoreCOVID-19 Vaccine Uptake Among Patients With Systemic Lupus Erythematosus in the American Midwest: The Lupus Midwest Network (LUMEN).
Link: https://doi.org/10.3899/jrheum.220220 Authors: Chevet, Baptiste; Figueroa-Parra, Gabriel; Yang, Jeffrey X; Hulshizer, Cassondra A; Gunderson, Tina M; Duong, Stephanie Q; Putman, Michael S; Barbour, Kamil E; Crowson, Cynthia S; Duarte-García, Alí Abstract: Patients with systemic lupus erythematosus (SLE) are at higher risk of poor outcomes from coronavirus disease 2019 (COVID-19). The vaccination rate among such patients…
Read MoreIntegration of feature vectors from raw laboratory, medication and procedure names improves the precision and recall of models to predict postoperative mortality and acute kidney injury.
Link: https://doi.org/10.1038/s41598-022-13879-7 Authors: Hofer, Ira S; Kupina, Marina; Laddaran, Lori; Halperin, Eran Abstract: Manuscripts that have successfully used machine learning (ML) to predict a variety of perioperative outcomes often use only a limited number of features selected by a clinician. We hypothesized that techniques leveraging a broad set of features for patient laboratory results, medications,…
Read MoreEpigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease.
Link: https://doi.org/10.1038/s41588-022-01097-w Authors: Liu, Hongbo; Doke, Tomohito; Guo, Dong; Sheng, Xin; Ma, Ziyuan; Park, Joseph; Vy, Ha My T; Nadkarni, Girish N; Abedini, Amin; Miao, Zhen; Palmer, Matthew; Voight, Benjamin F; Li, Hongzhe; Brown, Christopher D; Ritchie, Marylyn D; Shu, Yan; Susztak, Katalin Abstract: More than 800 million people suffer from kidney disease, yet the…
Read MoreGenetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.
Link: https://doi.org/S0085-2538(22)00454-9 Authors: Gorski, Mathias; Rasheed, Humaira; Teumer, Alexander; Thomas, Laurent F; Graham, Sarah E; Sveinbjornsson, Gardar; Winkler, Thomas W; Günther, Felix; Stark, Klaus J; Chai, Jin-Fang; Tayo, Bamidele O; Wuttke, Matthias; Li, Yong; Tin, Adrienne; Ahluwalia, Tarunveer S; Ärnlöv, Johan; Åsvold, Bjørn Olav; Bakker, Stephan J L; Banas, Bernhard; Bansal, Nisha; Biggs, Mary L;…
Read MoreDifferential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.
Link: https://doi.org/10.1038/s42003-022-03448-z Authors: Winkler, Thomas W; Rasheed, Humaira; Teumer, Alexander; Gorski, Mathias; Rowan, Bryce X; Stanzick, Kira J; Thomas, Laurent F; Tin, Adrienne; Hoppmann, Anselm; Chu, Audrey Y; Tayo, Bamidele; Thio, Chris H L; Cusi, Daniele; Chai, Jin-Fang; Sieber, Karsten B; Horn, Katrin; Li, Man; Scholz, Markus; Cocca, Massimiliano; Wuttke, Matthias; van der Most, Peter…
Read MoreThe promise of artificial intelligence for kidney pathophysiology.
Link: https://doi.org/10.1097/MNH.0000000000000808 Authors: Jiang, Joy; Chan, Lili; Nadkarni, Girish N Abstract: We seek to determine recent advances in kidney pathophysiology that have been enabled or enhanced by artificial intelligence. We describe some of the challenges in the field as well as future directions. We first provide an overview of artificial intelligence terminologies and methodologies. We…
Read MoreAutomated Determination of Left Ventricular Function Using Electrocardiogram Data in Patients on Maintenance Hemodialysis.
Link: https://doi.org/10.2215/CJN.16481221 Authors: Vaid, Akhil; Jiang, Joy J; Sawant, Ashwin; Singh, Karandeep; Kovatch, Patricia; Charney, Alexander W; Charytan, David M; Divers, Jasmin; Glicksberg, Benjamin S; Chan, Lili; Nadkarni, Girish N Abstract: Left ventricular ejection fraction is disrupted in patients on maintenance hemodialysis and can be estimated using deep learning models on electrocardiograms. Smaller sample sizes…
Read MoreInsights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension.
Link: https://doi.org/10.1161/HYPERTENSIONAHA.122.19324 Authors: Kelly, Tanika N; Sun, Xiao; He, Karen Y; Brown, Michael R; Taliun, Sarah A Gagliano; Hellwege, Jacklyn N; Irvin, Marguerite R; Mi, Xuenan; Brody, Jennifer A; Franceschini, Nora; Guo, Xiuqing; Hwang, Shih-Jen; de Vries, Paul S; Gao, Yan; Moscati, Arden; Nadkarni, Girish N; Yanek, Lisa R; Elfassy, Tali; Smith, Jennifer A; Chung,…
Read More