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Intra-Session recurrence in intradialytic hypotension prediction: evaluation implications and recurrence-aware
Siun Kim1, Jiwon Ryu2,3, Sejoong Kim3
1Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.
Frontiers in Digital Health
|July 22, 2026
Summary
Predicting intradialytic hypotension (IDH) improves by accounting for recurrent events. New models analyzing IDH recurrence patterns enhance accuracy and reliability in hemodialysis care.
Area of Science:
- Nephrology
- Artificial Intelligence
- Biomedical Engineering
Background:
- Deep learning models show high accuracy in predicting intradialytic hypotension (IDH).
- Existing models often treat initial and recurrent IDH events uniformly, overlooking distinct physiological and clinical differences.
- This approach may limit the clinical applicability and reliability of IDH prediction.
Purpose of the Study:
- To systematically examine intradialytic hypotension recurrence patterns.
- To evaluate the impact of recurrence on deep learning model performance.
- To identify methodological improvements for more accurate and robust IDH prediction.
Main Methods:
- Retrospective analysis of 12,767 hemodialysis sessions from 66 patients.
- Definition of recurrent IDH as an event occurring ≥30 minutes after the initial IDH.
- Comparison of deep learning models (ConvMixer, TCN, LSTM) with a rule-based baseline, incorporating recurrence-aware features and adversarial training.
Main Results:
- The probability of IDH significantly increased after initial events (11.7-65.7%).
- Conventional aggregated evaluation overestimated model performance, showing large gaps between initial and recurrent IDH predictions.
- Incorporating recurrence information improved AUROC by up to 8.0 percentage points; adversarial training enhanced robustness.
Conclusions:
- Accounting for IDH recurrence patterns significantly improves prediction model accuracy, robustness, and comparability.
- Standardized evaluation protocols that include recurrence are recommended for enhanced clinical applicability.
- Methodological advancements in IDH prediction can lead to more reliable patient care during hemodialysis.
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