NCT05735288

Brief Summary

This is a prospective, single-arm observational study that aims to assess the validity and reproducibility of an algorithm for assessing fluid status in a cohort of dialysis patients. The study will externally validate an existing algorithm for dry weight prediction in real-time in a cohort of dialysis patients.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
24

participants targeted

Target at below P25 for all trials

Timeline
Completed

Started Feb 2023

Shorter than P25 for all trials

Geographic Reach
1 country

2 active sites

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

November 30, 2022

Completed
3 months until next milestone

Study Start

First participant enrolled

February 14, 2023

Completed
7 days until next milestone

First Posted

Study publicly available on registry

February 21, 2023

Completed
2 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

April 27, 2023

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

April 27, 2023

Completed
Last Updated

May 19, 2023

Status Verified

November 1, 2022

Enrollment Period

2 months

First QC Date

November 30, 2022

Last Update Submit

May 18, 2023

Conditions

Volume OverloadDialysis

Keywords

DialysisVolume OverloadMachine LearningBioimpedance

Outcome Measures

Primary Outcomes (1)

  • The primary objective is to determine the validity of the machine learning model in estimating bioimpedance-determined dry weight in haemodialysis patients.

    Dry weight (kg) estimated by the machine learning estimation model will be compared with the bioimpedance normohydration weight in kg.

    8 weeks

Secondary Outcomes (1)

  • Acceptability

    8 weeks

Study Arms (1)

Haemodialysis patients

Haemodialysis patients attending haemodialysis in an outpatient setting in Beaumont Hospital, Ireland.

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Patients requiring maintenance haemodialysis in an ambulatory care setting.

You may qualify if:

  • Receiving maintenance haemodialysis in an ambulatory care setting
  • Aged at least 18 years
  • Demonstrates understanding of the study requirements.
  • Willing to give written informed consent.

You may not qualify if:

  • Conditions precluding accurate use of bioimpedance (e.g. limb amputations,severe malnourishment, pregnancy, cardiac resynchronisation devices, pacemakers).
  • Significant confusion or any concomitant medical condition, which would limit the ability of the patient to record symptoms or other parameters.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (2)

Beaumont Hospital

Dublin, Leinster, 9, Ireland

Location

Beaumont Hospital

Dublin, Leinster, D09V2N0, Ireland

Location

Related Publications (5)

  • Guo X, Zhou W, Lu Q, Du A, Cai Y, Ding Y. Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L2,1-Norm. Biomed Res Int. 2021 Feb 4;2021:6627650. doi: 10.1155/2021/6627650. eCollection 2021.

    PMID: 33628794BACKGROUND

  • Collins AJ, Foley RN, Herzog C, Chavers BM, Gilbertson D, Ishani A, Kasiske BL, Liu J, Mau LW, McBean M, Murray A, St Peter W, Guo H, Li Q, Li S, Li S, Peng Y, Qiu Y, Roberts T, Skeans M, Snyder J, Solid C, Wang C, Weinhandl E, Zaun D, Arko C, Chen SC, Dalleska F, Daniels F, Dunning S, Ebben J, Frazier E, Hanzlik C, Johnson R, Sheets D, Wang X, Forrest B, Constantini E, Everson S, Eggers PW, Agodoa L. Excerpts from the US Renal Data System 2009 Annual Data Report. Am J Kidney Dis. 2010 Jan;55(1 Suppl 1):S1-420, A6-7. doi: 10.1053/j.ajkd.2009.10.009. No abstract available.

    PMID: 20082919BACKGROUND

  • Flythe JE, Chang TI, Gallagher MP, Lindley E, Madero M, Sarafidis PA, Unruh ML, Wang AY, Weiner DE, Cheung M, Jadoul M, Winkelmayer WC, Polkinghorne KR; Conference Participants. Blood pressure and volume management in dialysis: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2020 May;97(5):861-876. doi: 10.1016/j.kint.2020.01.046. Epub 2020 Mar 8.

    PMID: 32278617BACKGROUND

  • Tomasev N, Glorot X, Rae JW, Zielinski M, Askham H, Saraiva A, Mottram A, Meyer C, Ravuri S, Protsyuk I, Connell A, Hughes CO, Karthikesalingam A, Cornebise J, Montgomery H, Rees G, Laing C, Baker CR, Peterson K, Reeves R, Hassabis D, King D, Suleyman M, Back T, Nielson C, Ledsam JR, Mohamed S. A clinically applicable approach to continuous prediction of future acute kidney injury. Nature. 2019 Aug;572(7767):116-119. doi: 10.1038/s41586-019-1390-1. Epub 2019 Jul 31.

    PMID: 31367026BACKGROUND

  • Lee H, Yun D, Yoo J, Yoo K, Kim YC, Kim DK, Oh KH, Joo KW, Kim YS, Kwak N, Han SS. Deep Learning Model for Real-Time Prediction of Intradialytic Hypotension. Clin J Am Soc Nephrol. 2021 Mar 8;16(3):396-406. doi: 10.2215/CJN.09280620. Epub 2021 Feb 11.

    PMID: 33574056BACKGROUND

MeSH Terms

Conditions

Edema

Condition Hierarchy (Ancestors)

Signs and SymptomsPathological Conditions, Signs and Symptoms

Study Officials

  • O'Seaghdha

    Royal College of Surgeons in Ireland

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
COHORT
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

November 30, 2022

First Posted

February 21, 2023

Study Start

February 14, 2023

Primary Completion

April 27, 2023

Study Completion

April 27, 2023

Last Updated

May 19, 2023

Record last verified: 2022-11

Data Sharing

IPD Sharing
Will not share

Locations

IE(2)