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  • Clinical Research Article
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Intradialytic hypotension and hemodynamic phenotypes in children following continuous renal replacement therapy initiation

Abstract

Background

Intradialytic hypotension (IDH) leads to inadequate organ perfusion and occurs frequently after continuous renal replacement therapy (CRRT) connection. Unsupervised learning can enhance our understanding of how clinical trajectories impact outcomes. We aim to investigate the association between IDH during CRRT connection and outcomes, while also identifying hemodynamic trajectory-based phenotypes.

Methods

A single center retrospective observational study of children (<18 years) undergoing CRRT from 9/2016 to 10/2018. IDH was defined as a sustained >20% decrease in mean arterial pressure (MAP) from baseline for ≥2 consecutive minutes. IDH burden was calculated by dividing connections with IDH by total observed connections. The primary outcome was major adverse kidney events at 30 days (MAKE30). K-means clustering was used to identify MAP trajectory-based phenotypes.

Results

59 patients, 232 connections, and 13,920 minutes were included. Median age was 59 months (IQR 8-152). In multivariable analysis, higher IDH burden [β 4.35 (CI: 0.01–8.70)] was associated with MAKE30. Two distinct MAP trajectories phenotypes were identified, with differing incidence of MAKE30 [21 (100%) vs. 29 (76%), p < 0.01].

Conclusions

IDH within the first hour of CRRT connection is associated with poor outcomes, and time-series clustering is feasible and could improve our understanding of the impact of CRRT in children.

Impact

  • Repeated episodes of intradialytic hypotension within the first hour of continuous renal replacement therapy connection are associated with increased morbidity and mortality.

  • Our findings suggest that intradialytic hypotension in the hour following CRRT connection in children is associated with poor outcomes.

  • Unsupervised machine learning, an underutilized approach in pediatric research, identified two significantly different mean arterial pressure trajectory-based phenotypes with differing anthropometric features and outcomes.

  • Leveraging unsupervised machine learning, we can identify trajectory-based subgroups that can provide insights into the impact of continuous renal replacement therapy in critically ill children.

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Fig. 1: This figure depicts the silhouette score using K-means clustering for each subgroup as well as the average silhouette score.
Fig. 2: Two distinct hemodynamic trajectories (blue and grey) were identified using unsupervised clustering.

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Data availability

Due to the small size of the cohort, the data are not publicly available as individual participants could be easily identifiable, posing a risk to patient privacy.

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Funding

No extramural financial assistance was provided for this study.

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Contributions

S.T., C.S., P.S., T.F., A.A.A., J.C., J.A.N.: Substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data. S.T., C.S., C.H., P.S., A.A.A., J.C., J.A.N.: Drafting the article or revising it critically for important intellectual content. S.T., C.S., C.H., K.D., P.S., T.F., A.A.A., J.C., J.A.N.: Final approval of the version to be published.

Corresponding author

Correspondence to Sameer Thadani.

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Given the retrospective nature of the study, the Institutional Review Board approved the protocol and waived the requirement for informed patient consent.

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Thadani, S., Silos, C., Horvat, C. et al. Intradialytic hypotension and hemodynamic phenotypes in children following continuous renal replacement therapy initiation. Pediatr Res (2025). https://doi.org/10.1038/s41390-025-04368-4

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