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System for High-Intensity Evaluation During Radiotherapy

NCT04277650 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 311

Last updated 2021-05-19

No results posted yet for this study

Summary

This quality improvement project will evaluate the implementation of a previously described intervention (twice per week on-treatment clinical evaluations) in a feasible fashion using a previously described machine learning algorithm identifying patients identified at high risk for an emergency visit or hospitalization during radiation therapy.

Conditions

  • Radiation Therapy Complication
  • Chemotherapeutic Toxicity

Interventions

OTHER

Machine learning algorithm

machine learning directed identification of radiotherapy or chemoradiotherapy patients at high-risk for emergency department acute care and/or hospitalization

Sponsors & Collaborators

Principal Investigators

  • Manisha Palta, MD · Duke Health

Study Design

Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2018-09-07
Primary Completion
2019-06-30
Completion
2019-06-30

Countries

  • United States

Study Locations

More Related Trials

Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04277650 on ClinicalTrials.gov