Key result
Adding heart rate variability parameters to a basic clinical model significantly improved the prediction of intradialytic hypotension, achieving an area under the curve of 0.804 (p=0.049 vs basic model).
Why the study?
It was unknown whether a new method using heart rate variability could predict intradialytic hypotension one month in advance in patients undergoing prevalent hemodialysis.
Does heart rate variability measurement predict intradialytic hypotension in patients on prevalent hemodialysis?
Population
71 patients undergoing prevalent hemodialysis
Comparison
Prediction model combining HRV parameters and basic clinical factors vs basic clinical model alone
Design
Observational cohort study
Follow-up
One month
Authors
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May enhance intradialytic hypotension prediction in hemodialysis; hypothesis-generating and requires prospective validation before clinical use.
Observational (n=71)
No
Does heart rate variability measurement predict intradialytic hypotension in patients on prevalent hemodialysis?
Effect estimate: AUC 0.804
p-value: p=<0.001
Adding heart rate variability parameters to a basic clinical model significantly improves the prediction of intradialytic hypotension in patients undergoing hemodialysis.
Park et al. (2019) conducted an observational in End-stage renal disease on hemodialysis (n=71). Heart rate variability (HRV) parameters vs. Basic clinical model was evaluated on Prediction of intradialytic hypotension (IDH) (AUC 0.804, p=<0.001). Adding heart rate variability parameters to a basic clinical model significantly improved the prediction of intradialytic hypotension, achieving an area under the curve of 0.804 (p=0.049 vs basic model).
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