Model Development and Temporal Validation of the Predictive Factors for Return to Work After Stroke Rehabilitation

February 19, 2025 updated by: Changi General Hospital
The purpose of the study is to develop a predictive model for return to work after stroke rehabilitation.

Study Overview

Status

Enrolling by invitation

Conditions

Detailed Description

Background Return to work post stroke is a key milestone for many survivors of stroke; however, many cannot achieve this goal. Based on the previous work by Tay et al, independent predictive factors were identified for return to work post inpatient stroke rehabilitation. In further works by Koh and Tay with the same dataset put through different models such as LASSO-Full, Lasso-Routine, ElasticNet-Full, etc suggests that the good discrimination performance of the return-to-work prediction models during internal validation supports a multisite, external validation study. Performing a temporal validation study is the interim step. A smaller part of the dataset could be used to further train the development model.

Significant economic costs are incurred because of stroke, which do not include further economic costs from the downstream loss of earnings and caregiver burden. Existing prediction models of return-to-work have area under the receiver operating characteristic curves (AUROCs) between 0.65 and 0.80. However, these models have not been assessed for calibration or clinical utility. No externally validated prediction model exists for return-to-work after stroke. There are advantages to having a prediction model. One of the concerns of patients and their families involve the loss of income as a result of stroke. The prediction model would help to prognosticate, as well as assist to set appropriate rehabilitation goals for the patient. Suitable patients can be directed to return to work services, if necessary.

Health is related to one's employment and financial position. Being able to return to gainful employment can result in better general and mental health5. People with disabilities employed in the past year reported better general and mental health than their peers with the same disabilities who were unemployed.

This study could be completed in 1 to 2 years and a prospective study involving external validation can be simultaneously performed with NUHS collaborators over 2 to 2.5 years. Both projects could be published in the next 2 to 3 years upon obtaining the grant for the temporal validation study. Thereafter, a Return to work calculator could be designed and launched in the next 4 years.

Hypothesis This study seeks to collect 1375 patient data who had completed inpatient stroke rehabilitation between the time periods of 2018-2025. We seek to further train our development model and to perform a temporal validation on this model.

Study Type

Observational

Enrollment (Estimated)

1375

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Singapore, Singapore, 529889
        • Changi General Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

The criteria for recruitment is first-ever stroke and premorbid work.

Description

Inclusion Criteria:

  1. Completed inpatient stroke rehabilitation in CGH
  2. Diagnosis of a first ever stroke
  3. Patients who were working prior to stroke
  4. Consent given

Exclusion Criteria:

  1. Not first ever stroke
  2. Did not require inpatient stroke rehabilitation
  3. Not working prior to stroke
  4. No consent obtained

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Stroke patients who had completed inpatient stroke rehabilitation between 2018-2025

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Return to work
Time Frame: 1 year and 2 years
Return to work at 1 year and 2 years post stroke
1 year and 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 5, 2023

Primary Completion (Estimated)

March 31, 2026

Study Completion (Estimated)

March 31, 2026

Study Registration Dates

First Submitted

February 13, 2025

First Submitted That Met QC Criteria

February 19, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

February 19, 2025

Last Verified

February 1, 2025

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Data is protected under the SingHealth Data Protection Policy which is compliant to the Singapore Personal Data Protection Act 2012

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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