Posts Tagged ‘Nephrology’
Assessment of prescribed vs. achieved fluid balance during continuous renal replacement therapy and mortality outcome.
Link: https://doi.org/10.1371/journal.pone.0272913 Authors: Neyra, Javier A; Lambert, Joshua; Ortiz-Soriano, Victor; Cleland, Daniel; Colquitt, Jon; Adams, Paul; Bissell, Brittany D; Chan, Lili; Nadkarni, Girish N; Tolwani, Ashita; Goldstein, Stuart L Abstract: Fluid management during continuous renal replacement therapy (CRRT) requires accuracy in the prescription of desired patient fluid balance (FBGoal) and precision in the attainable patient…
Read MoreMachine learning for risk stratification in kidney disease.
Link: https://doi.org/10.1097/MNH.0000000000000832 Authors: Gulamali, Faris F; Sawant, Ashwin S; Nadkarni, Girish N Abstract: Risk stratification for chronic kidney is becoming increasingly important as a clinical tool for both treatment and prevention measures. The goal of this review is to identify how machine learning tools contribute and facilitate risk stratification in the clinical setting. The two…
Read MoreFederated Learning in Risk Prediction: A Primer and Application to COVID-19-Associated Acute Kidney Injury.
Link: https://doi.org/10.1159/000525645 Authors: Gulamali, Faris F; Nadkarni, Girish N Abstract: Modern machine learning and deep learning algorithms require large amounts of data; however, data sharing between multiple healthcare institutions is limited by privacy and security concerns. Federated learning provides a functional alternative to the single-institution approach while avoiding the pitfalls of data sharing. In cross-silo…
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 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 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 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 MoreDesign and rationale of GUARDD-US: A pragmatic, randomized trial of genetic testing for APOL1 and pharmacogenomic predictors of antihypertensive efficacy in patients with hypertension.
Link: https://doi.org/S1551-7144(22)00139-2 Authors: Eadon, Michael T; Cavanaugh, Kerri L; Orlando, Lori A; Christian, David; Chakraborty, Hrishikesh; Steen-Burrell, Kady-Ann; Merrill, Peter; Seo, Janet; Hauser, Diane; Singh, Rajbir; Beasley, Cherry Maynor; Fuloria, Jyotsna; Kitzman, Heather; Parker, Alexander S; Ramos, Michelle; Ong, Henry H; Elwood, Erica N; Lynch, Sheryl E; Clermont, Sabrina; Cicali, Emily J; Starostik, Petr; Pratt,…
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