Evidence map›Paper›PMID 41215784›Full record

ArticleClinical kidney journal2025

Continuous measurement of pulse arrival time for identification of blood pressure changes in patients undergoing hemodialysis-a feasibility study.

Michael Wunderle, Martin Bachler, David Stadler, Bernhard Hametner, Stefan Orter, Claudius Küchle, Simon Krenn, Uwe Heemann, Siegfried Wassertheurer, Christoph Schmaderer and 1 more

Abstract read
In one paragraph

Article in Clinical kidney journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Michael WunderleTechnical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Nephrology, Munich, Germany.
Martin BachlerAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.
David StadlerTechnical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Nephrology, Munich, Germany.
Bernhard HametnerAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.ORCID https://orcid.org/0000-0003-2048-1019
Stefan OrterAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.
Claudius KüchleTechnical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Nephrology, Munich, Germany.
Simon KrennAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.
Uwe HeemannTechnical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Nephrology, Munich, Germany.
Siegfried WassertheurerAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.
Christoph SchmadererTechnical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Nephrology, Munich, Germany.ORCID https://orcid.org/0000-0002-5803-2190
Christopher C MayerAIT Austrian Institute of Technology GmbH, Center for Health & Bioresources, Medical Signal Analysis, Vienna, Austria.ORCID https://orcid.org/0000-0002-5612-5481

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and hypothesis: Intradialytic hypotension (IDH) is a common complication during hemodialysis, associated with immediate and long-term risks. Current monitoring methods lack timely warning signals for preemptive intervention. Continuous non-invasive measurement of blood pressure providing real-time insights into hemodynamic changes might enable the early detection of impending IDH. Pulse arrival time (PAT), which can be measured non-invasively and continuously by electrocardiogram (ECG) and photoplethysmography (PPG), is inversely correlated with blood pressure and might serve as such. Thus, this study explores the feasibility of using PAT to track blood pressure changes in end-stage renal disease patients undergoing hemodialysis. Methods: A feasibility study was conducted with 44 patients [mean age 64.9 (18.1 SD) years] undergoing hemodialysis, collecting data at the Klinikum rechts der Isar of the Technical University of Munich, School of Medicine. The PAT was determined by an algorithm for detecting the R-wave in the ECG and the beginning of the pulse curve in the PPG. The study focused on changes in PAT and blood pressure during three predefined time periods of 1 hour during dialysis. Statistical analysis included equivalence testing using the TOST (two one-sided Results: Patients' mean systolic blood pressure (BP) was 137 (30.1 SD) mmHg, diastolic BP 68.4 (18.4 SD) mmHg and PAT 233 (42.3 SD) ms. The study revealed an inverse association between PAT and BP changes, demonstrating significant correlations [systolic/diastolic blood pressures (SBP/DBP) Conclusions: The study demonstrates that tracking BP changes using PAT as a non-invasive method in hemodialysis patients is feasible. However, the reliability of PAT measurements appears to vary among patients, indicating that this method may not be universally applicable. The observed inverse association between PAT and BP changes, especially during the start to middle phase of dialysis, highlights the potential of this technique to complement traditional monitoring methods. These exploratory findings open avenues for further research to validate the utility of PAT, particularly in predicting IDH episodes and assessing its behavior in scenarios of low BP or minimal variations.

Indexed as

continuous blood pressure changesfeasibilityhemodialysisintradialytic hypotensionpulse arrival time

Identifiers

PMID41215784
PMCPMC12596194

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.