# Predictive Analytics in Hemodialysis: Enabling Precision Care for Patient with ESKD

> **NIH NIH R01** · DUKE UNIVERSITY · 2022 · $512,937

## Abstract

ABSTRACT
End stage kidney disease (ESKD) is a complex disease with individuals having variable life-
expectancies, with 25% dying within 1 year and 41% surviving at least 5 years. While providers
recognize that patients are different – and ought to be differently – there are no tools to reliably
forecast individual life expectancy and aid in treatment individualization. Instead, providers are
left with often unclear or incomplete guidelines on how best to manage patients. In order to
provide precision care for patients on hemodialysis (HD), there is a critical need to be able to (1)
dynamically assess life expectancy for medical decision-making; and (2) identify distinct clinical
phenotypes to enhance clinical monitoring and care planning. Our central hypothesis is that
there is heterogeneity in patient survivorship and disease trajectory that, when known, can be
used to provide more personalized and effective care. By coupling novel machine learning
approaches for survival prediction with granular clinical data on HD patients, we will be able to
develop the analytic tools necessary to support precision care. At the completion of this
proposal we will have tools to dynamically assess a patient's life expectancy and insights into
heterogeneous disease phenotypes for patients with ESKD. These tools will allow providers to
make informed treatment decisions as well as lay the groundwork for further precision research
into optimized patient care.

## Key facts

- **NIH application ID:** 10414814
- **Project number:** 5R01DK123062-03
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Benjamin Alan Goldstein
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $512,937
- **Award type:** 5
- **Project period:** 2020-07-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10414814

## Citation

> US National Institutes of Health, RePORTER application 10414814, Predictive Analytics in Hemodialysis: Enabling Precision Care for Patient with ESKD (5R01DK123062-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10414814. Licensed CC0.

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