Incremental Dialysis Decision Model Based on Expert-Guided Machine Learning

Machine Learning Based on Expert Knowledge to Build and Validate a Decision Model for Incremental Dialysis

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06775067

Enrollment

175

Registered

2025-01-14

Start date

2010-04-12

Completion date

2024-06-28

Last updated

2025-01-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

End-stage Renal Disease

Keywords

Machine Learning, Expert Knowledge, Interpretability, Incremental Hemodialysis, Decision Model

Brief summary

This observational prospective study combined clinical expert knowledge with machine learning to develop and validate a predictive model for incremental hemodialysis decision-making. The aim of the predictive model is to assist clinicians in developing individualized incremental dialysis treatment plans to optimize patient outcomes.

Detailed description

By collecting patients' clinical and biochemical parameters and combining them with experts' judgments of dialysis timing and frequency, the model can dynamically assess patients' risk of needing to increase the frequency of dialysis, thus assisting physicians in formulating individualized incremental dialysis regimens to optimize dialysis outcomes and improve patients' prognosis.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

1. New hemodialysis patients (Apr 2010-Jun 2024), started within 3 months, including transfers. 2. Age ≥18, stable hemodialysis \>6 months.

Exclusion criteria

1. Incomplete/unreliable data. 2. Twice-weekly palliative dialysis. 3. No baseline urine output or ≤200 mL/24h. 4. Liver disease, heart failure, or severe comorbidities.

Design outcomes

Primary

Measure	Time frame	Description
Number (Proportion) of Participants Who Experience an Incremental Dialysis Event, Assessed Monthly	Baseline and monthly visits from enrollment until incremental dialysis event, death, transfer, or up to 5 years (whichever occurs first)	An incremental dialysis event is defined as an increase in a patient's dialysis frequency (e.g., from 1 session per week to 2 sessions per week, or from 2 to 3 sessions per week, etc.) due to clinical considerations such as decreased residual renal function, fluid overload, or other physician-determined criteria. At each monthly visit (up to 5 years from enrollment), investigators will record whether each participant experiences an incremental event. We will quantify the primary outcome as the number and proportion of participants who transition to a higher dialysis frequency per month, as well as the cumulative incidence over time.

Countries

China

Outcome results