SarcopeniaNCT05396404
Empirical Mode Decomposition and Decision Tree in Sarcopenia
An observational study of Sarcopenia and Fall, run by Changhua Christian Hospital at 1 site in Taiwan.
Trial summary
Sarcopenia is quickly becoming a major global public health issue. Falls are the leading cause of mortality among the elderly, and they must be addressed. The investigators will use machine learning techniques such as empirical mode decomposition technology and decision tree algorithms to extract the characteristics… Read more about this study
- Who is it for?
- Ages 40 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Sarcopenia, Fall, Gait, Unsteady
- How many people
- 200 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Mar 2022to 1 Jul 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 40 to 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: The subject's data were collected from the e-medical chart system.
Who may be able to join
- aged from 40 - 90
- DXA test performed
- blood sample tests were performed
Who cannot join
- stroke history
- amputation
- cancer related disease
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Using Empirical Mode Decomposition and Decision Tree to Extract the Balance and Gait Features and Classification in Sarcopenia
Sarcopenia is quickly becoming a major global public health issue. Falls are the leading cause of mortality among the elderly, and they must be addressed. The investigators will use machine learning techniques such as empirical mode decomposition technology and decision tree algorithms to extract the characteristics and classification of sarcopenia in this retrospective study in order to offer clinically proven and effective interventional strategies to prevent, stabilize, and reverse sarcopenia.
Read the detailed description
Sarcopenia is becoming a severe global public health concern as the world's elderly population grows. Sarcopenia is characterized by muscular mass and strength loss, as well as impaired physical performance, and it is frequently connected with negative health outcomes such as falls. Falls are a primary cause of death in older individuals and must be addressed. Sarcopenia is currently diagnosed clinically using three primary technologies: imaging technology, precision medicine, and machine learning. In this study, the investigators will use previously collected data from nearly 200 community-dwelling subjects, including medical history, biochemistry, body composition, balance and gait, electromyography, and functional performance, to extract the characteristics and classification of sarcopenia using machine learning techniques such as empirical mode decomposition technology and decision tree algorithms. The investigators intend to offer clinically proven and effective interventional strategies to prevent, stabilize, and reverse sarcopenia.
- Conditions
- Sarcopenia, Fall, Gait, Unsteady, Balance; Distorted
- Keywords
- empirical mode decomposition, machine learning, decision tree
- Medical subject headings
- Sarcopenia, Gait Disorders, Neurologic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| observation | all subject data were retrieved from databank which is stored in the e-medical chart system. |
What is being measured
The primary outcome is the main question the study is designed to answer.
center of pressure (COP)
Use computerized dynography to measure the postural sway displacement, velocity (etc., mm, mm/sec)
Measured: baseline: subject was enrolled
walking speed
6m, patients can walk with foot orthosis and assistive devices
Measured: baseline: subject was enrolled
grip force
Use a grip force meter (kg) to test both hands for test 3 times
Measured: baseline: subject was enrolled
step time
Use computerized dynography to measure spatial gait parameter: step time (ms)
Measured: baseline: subject was enrolled
stance time
Use computerized dynography to measure spatial gait parameter: stance time (ms)
Measured: baseline: subject was enrolled
swing time
Use computerized dynography to measure spatial gait parameter: swing time (ms)
Measured: baseline: subject was enrolled
step / stance length
Use computerized dynography to measure spatial gait parameter: step / stance distance (mm)
Measured: baseline: subject was enrolled
muscle thickness
Use ultrasound to assess muscles morphological parameter: thickness (mm). Target muscles include quadriceps, hamstring, anterior tibialis, gastrocnemius.
Measured: baseline: subject was enrolled
international Quality of Life Assessment Short Form -36 (SF-36)
including 8 health concepts: (1) physical functioning, (2) role limitations because of physical health problems; (3) bodily pain, (4) social functioning, (5) general mental health (psychological distress and psychological wellbeing), (6) role limitations because of emotional problems, (7) vitality (energy/fatigue), (8) general health perceptions.
Scoring: answers to each question are scored which are then summed and transformed to a 0 - 100 scale.
The lower the score the more disability. The higher the score the less disability i.e., a score of zero is equivalent to maximum disability and a score of 100 is equivalent to no disability.
Measured: baseline: subject was enrolled
amplitude of Muscle activity
use electromyography to measure the muscles activity in microvolts (uv) included quadriceps, hamstrings, tibialis anterior, gastrocnemius during subject walking in self-selected speed in 6 meters.
Measured: baseline: subject was enrolled
Fear of fall scale
A 15-item self-report questionnaire for measuring fear of falling. Each item is rated on a Likert-type scale from 1 (strongly disagree) to 4 (strongly agree). The total possible score ranges from 15-60, with higher scores indicating greater fear of falling.
Measured: baseline: subject was enrolled
Bone density
A bone density test, DEXA, measures the mineral content of the bones in certain areas of the skeleton. A DEXA scan is a type of medical imaging test. It uses very low levels of x-rays to measure how dense participants' bones are. DEXA stands for "dual-energy X-ray absorptiometry." The bone density area includes: Hip and Spine
Measured: baseline: subject was enrolled
Body composition
Dual energy x-ray absorptiometry (DEXA) measures bone mineral content (BMC), fat-free mass (FFM).
Measured: baseline: subject was enrolled
Secondary outcomes (13)
concentration of CRP (C-Reactive Protein)
The concentration of CRP in the blood test. CRP is used mainly as a marker of inflammation.
Measured: baseline: subject was enrolled
concentration of ALB (Serum albumin)
The concentration of ALB in the blood test. Albumin is the most important contributor to the maintenance of plasma colloid oncotic pressure; deficiency results in edema.
Measured: baseline: subject was enrolled
concentration of Glomerular Filtration Rate (GFR)
The concentration of GFR in the blood test. The glomerular filtration rate is the best test to measure the patient's level of kidney function and determine the stage of kidney disease. It can calculate it from the results of the blood creatinine test.
Measured: baseline: subject was enrolled
concentration of Hemoglobin (Hb)
The concentration of Hb in the blood test.
Measured: baseline: subject was enrolled
concentration of Glucose SPOT
The concentration of Glucose SPOT in the blood test. TheSpot glucose measurement in epidermal interstitial fluid appears to be a promising alternative to capillary blood glucose estimation
Measured: baseline: subject was enrolled
concentration of Cholesterol
The concentration of Cholesterol in the blood test.
Measured: baseline: subject was enrolled
concentration of Triglyceride
The concentration of Triglyceride in the blood test.
Measured: baseline: subject was enrolled
concentration of Transferrin
The concentration of Transferrin in the blood test.
Measured: baseline: subject was enrolled
Berg balance test (BBS)
including 14 items which are scored on a 5 points scale (0-4). The degree of success in achieving each task is given a score of zero (unable) to four (independent), and the final measure is the sum of all of the scores.
The item scores are summed, minimum score =0, maximum score = 56
Measured: baseline: subject was enrolled
Body Mass Index (BMI)
(body weight) kg/(height) m*(height)m
Measured: baseline: subject was enrolled
Mini-mental state examination (MMSE)
It is an 11-question measure that tests five areas of cognitive function:
orientation, registration, attention and calculation, recall, and language. The maximum score is 30. A score of 23 or lower is indicative of cognitive impairment.
Measured: baseline: subject was enrolled
calf muscle circumference
Use ruler to measure the bilateral calf muscle circumference, It is an anthropometric parameter commonly used in clinical practice.
Measured: baseline: subject was enrolled
Timed up and go
To determine fall risk and measure the progress of balance, sit to stand and walking. Patients wear their regular footwear and can use a walking aid, if needed. The patient starts in a seated position. The patient stands up upon therapist's command: walks 3 meters, turns around, walks back to the chair and sits down. The time stops when the patient is seated. To document if the assistive device used. Stopwatch to record the whole task duration.
Measured: baseline: subject was enrolled
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 May 2022
- Study start1 Mar 2022
- Primary completion31 Jan 2024 (estimated)
- Study completion1 Jul 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for SarcopeniaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Changhua Christian Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- TASEN WEI, MD, Principal investigator, Changhua Christian Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05396404
- Sponsor's protocol ID
- CCH IRB 211235
- Status last verified
- Feb 2022
- First submitted
- 26 May 2022
- Last updated
- 8 Sep 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 Sep 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using Empirical Mode Decomposition and Decision Tree to Extract the Balance and Gait Features and Classification in Sarcopenia
- ClinicalTrials.gov ID
- NCT05396404
- Acronym / sponsor ID
- CCH IRB 211235
- Conditions
- Sarcopenia, Fall, Gait, Unsteady, Balance; Distorted
- Keywords
- empirical mode decomposition, machine learning, decision tree
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Changhua Christian HospitalUniversity, hospital or other
- Study start
- 1 Mar 2022 (actual)
- Primary completion
- 31 Jan 2024 (estimated)
- Study completion
- 1 Jul 2024 (estimated)
- First posted
- 31 May 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Sarcopenia is quickly becoming a major global public health issue. Falls are the leading cause of mortality among the elderly, and they must be addressed. The investigators will use machine learning techniques such as empirical mode decomposition technology and decision tree algorithms to extract the characteristics and classification of sarcopenia in this retrospective study in order to offer clinically proven and effective interventional strategies to prevent, stabilize, and reverse sarcopenia.
Detailed description
Sarcopenia is becoming a severe global public health concern as the world's elderly population grows. Sarcopenia is characterized by muscular mass and strength loss, as well as impaired physical performance, and it is frequently connected with negative health outcomes such as falls. Falls are a primary cause of death in older individuals and must be addressed. Sarcopenia is currently diagnosed clinically using three primary technologies: imaging technology, precision medicine, and machine learning. In this study, the investigators will use previously collected data from nearly 200 community-dwelling subjects, including medical history, biochemistry, body composition, balance and gait, electromyography, and functional performance, to extract the characteristics and classification of sarcopenia using machine learning techniques such as empirical mode decomposition technology and decision tree algorithms. The investigators intend to offer clinically proven and effective interventional strategies to prevent, stabilize, and reverse sarcopenia.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| observation | – | –all subject data were retrieved from databank which is stored in the e-medical chart system. |
Who may qualify
- Ages
- 40 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- The subject's data were collected from the e-medical chart system.
Key inclusion criteria (3 listed)
- aged from 40 - 90
- DXA test performed
- blood sample tests were performed
Key exclusion criteria (3 listed)
- stroke history
- amputation
- cancer related disease
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
center of pressure (COP)
Time frame: baseline: subject was enrolled
Use computerized dynography to measure the postural sway displacement, velocity (etc., mm, mm/sec)
walking speed
Time frame: baseline: subject was enrolled
6m, patients can walk with foot orthosis and assistive devices
grip force
Time frame: baseline: subject was enrolled
Use a grip force meter (kg) to test both hands for test 3 times
step time
Time frame: baseline: subject was enrolled
Use computerized dynography to measure spatial gait parameter: step time (ms)
stance time
Time frame: baseline: subject was enrolled
Use computerized dynography to measure spatial gait parameter: stance time (ms)
swing time
Time frame: baseline: subject was enrolled
Use computerized dynography to measure spatial gait parameter: swing time (ms)
step / stance length
Time frame: baseline: subject was enrolled
Use computerized dynography to measure spatial gait parameter: step / stance distance (mm)
muscle thickness
Time frame: baseline: subject was enrolled
Use ultrasound to assess muscles morphological parameter: thickness (mm). Target muscles include quadriceps, hamstring, anterior tibialis, gastrocnemius.
international Quality of Life Assessment Short Form -36 (SF-36)
Time frame: baseline: subject was enrolled
including 8 health concepts: (1) physical functioning, (2) role limitations because of physical health problems; (3) bodily pain, (4) social functioning, (5) general mental health (psychological distress and psychological wellbeing), (6) role limitations because of emotional problems, (7) vitality (energy/fatigue), (8) general health perceptions. Scoring: answers to each question are scored which are then summed and transformed to a 0 - 100 scale. The lower the score the more disability. The higher the score the less disability i.e., a score of zero is equivalent to maximum disability and a score of 100 is equivalent to no disability.
amplitude of Muscle activity
Time frame: baseline: subject was enrolled
use electromyography to measure the muscles activity in microvolts (uv) included quadriceps, hamstrings, tibialis anterior, gastrocnemius during subject walking in self-selected speed in 6 meters.
Fear of fall scale
Time frame: baseline: subject was enrolled
A 15-item self-report questionnaire for measuring fear of falling. Each item is rated on a Likert-type scale from 1 (strongly disagree) to 4 (strongly agree). The total possible score ranges from 15-60, with higher scores indicating greater fear of falling.
Bone density
Time frame: baseline: subject was enrolled
A bone density test, DEXA, measures the mineral content of the bones in certain areas of the skeleton. A DEXA scan is a type of medical imaging test. It uses very low levels of x-rays to measure how dense participants' bones are. DEXA stands for "dual-energy X-ray absorptiometry." The bone density area includes: Hip and Spine
Body composition
Time frame: baseline: subject was enrolled
Dual energy x-ray absorptiometry (DEXA) measures bone mineral content (BMC), fat-free mass (FFM).
13 secondary outcomes
concentration of CRP (C-Reactive Protein)
Time frame: baseline: subject was enrolled
concentration of ALB (Serum albumin)
Time frame: baseline: subject was enrolled
concentration of Glomerular Filtration Rate (GFR)
Time frame: baseline: subject was enrolled
concentration of Hemoglobin (Hb)
Time frame: baseline: subject was enrolled
concentration of Glucose SPOT
Time frame: baseline: subject was enrolled
concentration of Cholesterol
Time frame: baseline: subject was enrolled
concentration of Triglyceride
Time frame: baseline: subject was enrolled
concentration of Transferrin
Time frame: baseline: subject was enrolled
Berg balance test (BBS)
Time frame: baseline: subject was enrolled
Body Mass Index (BMI)
Time frame: baseline: subject was enrolled
Mini-mental state examination (MMSE)
Time frame: baseline: subject was enrolled
calf muscle circumference
Time frame: baseline: subject was enrolled
Timed up and go
Time frame: baseline: subject was enrolled
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 Sep 2022.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
TASEN WEI, MD principal investigator
Changhua Christian Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sarcopenia and Fall, run by Changhua Christian Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 Sep 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
center of pressure (COP) (time frame: baseline: subject was enrolled). The study lists 13 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 Sep 2022.