Prescribed Physical Activity in Improving Sleep and Physical Performance in Patients Undergoing Stem Cell Transplant
- Conditions
- Cell Transplantation
- Interventions
- Other: Medical Chart ReviewDevice: Monitoring DeviceProcedure: Physical Therapy
- Registration Number
- NCT02796196
- Lead Sponsor
- Stanford University
- Brief Summary
This research trial studies prescribed physical activity in improving sleep and physical performance in patients undergoing stem cell transplant. A wearable physical activity monitor can be used to record minutes of activity and sleep. Gathering data over time using a physical activity monitor may help doctors learn if prescribed physical activity helps improve sleep and physical performance in patients undergoing stem cell transplant.
- Detailed Description
PRIMARY OBJECTIVES:
I. Evaluate whether prescribed physical activity, as part of standard care, improves sleep and functional outcomes in hematopoietic cell transplantation (HCT) (stem cell transplantation) patients during a typical 30-day hospitalization period.
OUTLINE:
Data including demographics, type of HCT (e.g., allogeneic or autologous), preexisting physical conditions (e.g., chronic joint injury), chronic renal failure (CRF), steroid use data, Eastern Cooperative Oncology Group (ECOG) and Karnofsky performance status (KPS) scores are collected from patients' medical charts at time of enrollment. Patients are prescribed participation in a primarily self-directed physical activity program which encourages them to spend 6 hours out of bed daily and to perform 30 minutes of light-to-moderate daily aerobic activity. Patients who are able to maintain independent mobility undergo physical therapist assessment 2 times a week until hospital discharge. Patients wear a physical activity monitoring device and daily activity and sleep data are collected continuously during hospital length of stay (LOS).
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 75
- Admitted to Stanford Hospital for HCT
- Able to provide informed consent
- Speaks language supported by interpretative services
- Able to operate and take care of a physical activity monitor
- Does not meet inclusion criteria
- Unable to wear a physical activity monitor throughout hospital stay
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description Supportive care (monitoring device, medical chart review) Monitoring Device Data including demographics, type of HCT (e.g., allogeneic or autologous), preexisting physical conditions (e.g., chronic joint injury), CRF, steroid use data, ECOG and KPS scores are collected from patients' medical charts at time of enrollment. Patients are prescribed participation in a primarily self-directed physical activity program which encourages them to spend 6 hours out of bed daily and to perform 30 minutes of light-to-moderate daily aerobic activity. Patients who are able to maintain independent mobility undergo physical therapist assessment 2 times a week until hospital discharge. Patients wear a physical activity monitoring device and daily activity and sleep data are collected continuously during hospital LOS. Supportive care (monitoring device, medical chart review) Medical Chart Review Data including demographics, type of HCT (e.g., allogeneic or autologous), preexisting physical conditions (e.g., chronic joint injury), CRF, steroid use data, ECOG and KPS scores are collected from patients' medical charts at time of enrollment. Patients are prescribed participation in a primarily self-directed physical activity program which encourages them to spend 6 hours out of bed daily and to perform 30 minutes of light-to-moderate daily aerobic activity. Patients who are able to maintain independent mobility undergo physical therapist assessment 2 times a week until hospital discharge. Patients wear a physical activity monitoring device and daily activity and sleep data are collected continuously during hospital LOS. Supportive care (monitoring device, medical chart review) Physical Therapy Data including demographics, type of HCT (e.g., allogeneic or autologous), preexisting physical conditions (e.g., chronic joint injury), CRF, steroid use data, ECOG and KPS scores are collected from patients' medical charts at time of enrollment. Patients are prescribed participation in a primarily self-directed physical activity program which encourages them to spend 6 hours out of bed daily and to perform 30 minutes of light-to-moderate daily aerobic activity. Patients who are able to maintain independent mobility undergo physical therapist assessment 2 times a week until hospital discharge. Patients wear a physical activity monitoring device and daily activity and sleep data are collected continuously during hospital LOS.
- Primary Outcome Measures
Name Time Method ECOG performance scores At baseline Will focus on trends in scores between patients with different durations of activity and sleep. Results, from both descriptive and inferential analyses, will be presented in table and/or graphical format.
KPS performance scores At baseline Will focus on trends in scores between patients with different durations of activity and sleep. Results, from both descriptive and inferential analyses, will be presented in table and/or graphical format.
Minutes of aerobic activity per day Up to time of hospital discharge, or 29 days Will use interval-censored regression to estimate distributions of activity from one day to the next. This repeated-measures analysis with a polynomial model will generate average curves for activity, each spanning average LOS (i.e., activity duration plotted on day one, day two, day three, etc.). Will also run diagnostics to verify the assumptions of a linear model (e.g., statistical independence of observations and lack of undue influence of outliers on model fit).
Minutes of sleep per day Up to time of hospital discharge, or 29 days Will use interval-censored regression to estimate distributions of sleep from one day to the next. This repeated-measures analysis with a polynomial model will generate average curves for sleep, each spanning average LOS (i.e., sleep duration plotted on day one, day two, day three, etc.). Will use multiple linear regressions to control for potential confounders in predicting sleep duration. Will also run diagnostics to verify the assumptions of a linear model (e.g., statistical independence of observations and lack of undue influence of outliers on model fit).
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Stanford University, School of Medicine
🇺🇸Palo Alto, California, United States