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Development of an Artificial Intelligence Model to Guide the Management of Blood Pressure, Fluid Volume, and Dialysis Dose in End-Stage Kidney Disease Patients: Proof of Concept and First Clinical Assessment
- Source :
- Kidney diseases, Kidney diseases, Karger, 2019, 5 (1), pp.28-33. ⟨10.1159/000493479⟩
- Publication Year :
- 2018
- Publisher :
- S. Karger AG, 2018.
-
Abstract
- Background: Fluid volume and blood pressure (BP) management are crucial endpoints for end-stage kidney disease patients. BP control in clinical practice mainly relies on reducing extracellular fluid volume overload by diminishing targeted postdialysis weight. This approach exposes dialysis patients to intradialytic hypotensive episodes. Summary: Both chronic hypertension and intradialytic hypotension lead to adverse long-term outcomes. Achieving the optimal trade-off between adequate fluid removal and the risk of intradialytic adverse events is a complex task in clinical practice given the multiple patient-related and dialysis-related factors affecting the hemodynamic response to treatment. State-of-the-art artificial intelligence has been adopted in other complex decision-making tasks for dialysis patients and may help personalize the multiple dialysis-related prescriptions affecting patients’ intradialytic hemodynamics. As a proof of concept, we developed a multiple-endpoint model predicting session-specific Kt/V, fluid volume removal, heart rate, and BP based on patient characteristics, historic hemodynamic responses, and dialysis-related prescriptions. Key Messages: The accuracy and precision of this preliminary model is extremely encouraging. Such analytic tools may be used to anticipate patients’ reactions through simulation so that the best strategy can be chosen based on clinical judgment or formal utility functions.
- Subjects :
- Dialysis adequacy
Artificial intelligence
medicine.medical_treatment
Heart rate
Hemodynamics
Review Article
Intradialytic hypotension
[SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Extracellular fluid
medicine
Adverse effect
Dialysis
business.industry
Medical decision-making
medicine.disease
Personalized medicine
Blood pressure
Hemodialysis
Fluid overload
business
Kidney disease
Subjects
Details
- ISSN :
- 22969357 and 22969381
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- Kidney Diseases
- Accession number :
- edsair.doi.dedup.....fc77aa248b360ec34e0be93552100a13