Empirical Mode Decomposition and Decision Tree in Sarcopenia

NCT05396404 | Unknown DMC

• 1 other identifier: CCH IRB 211235
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

Brief 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 and classification of sarcopenia in this retrospective study in order 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

Outcome Measures

Primary Outcomes (13)

• center of pressure (COP)

  Use computerized dynography to measure the postural sway displacement, velocity (etc., mm, mm/sec)

  baseline: subject was enrolled

• walking speed

  6m, patients can walk with foot orthosis and assistive devices

  baseline: subject was enrolled

• grip force

  Use a grip force meter (kg) to test both hands for test 3 times

  baseline: subject was enrolled

• step time

  Use computerized dynography to measure spatial gait parameter: step time (ms)

  baseline: subject was enrolled

• stance time

  Use computerized dynography to measure spatial gait parameter: stance time (ms)

  baseline: subject was enrolled

• swing time

  Use computerized dynography to measure spatial gait parameter: swing time (ms)

  baseline: subject was enrolled

• step / stance length

  Use computerized dynography to measure spatial gait parameter: step / stance distance (mm)

  baseline: subject was enrolled

• muscle thickness

  Use ultrasound to assess muscles morphological parameter: thickness (mm). Target muscles include quadriceps, hamstring, anterior tibialis, gastrocnemius.

  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.

  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.

  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.

  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

  baseline: subject was enrolled

• Body composition

  Dual energy x-ray absorptiometry (DEXA) measures bone mineral content (BMC), fat-free mass (FFM).

  baseline: subject was enrolled

Secondary Outcomes (13)

• concentration of CRP (C-Reactive Protein)

  baseline: subject was enrolled

• concentration of ALB (Serum albumin)

  baseline: subject was enrolled

• concentration of Glomerular Filtration Rate (GFR)

  baseline: subject was enrolled

• concentration of Hemoglobin (Hb)

  baseline: subject was enrolled

• concentration of Glucose SPOT

  baseline: subject was enrolled

Study Arms (1)

observation

all subject data were retrieved from databank which is stored in the e-medical chart system.

Eligibility Criteria

• Age: 40 Years - 90 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The subject's data were collected from the e-medical chart system.

You may qualify if:

• aged from 40 - 90
• DXA test performed
• blood sample tests were performed

You may not qualify if:

• stroke history
• amputation
• cancer related disease

Sponsors & Collaborators

• Changhua Christian Hospital: lead

Study Sites (1)

Changhua Christian Hospital

Changhua, 500, Taiwan

Location

MeSH Terms

Conditions

Sarcopenia; Gait Disorders, Neurologic

Condition Hierarchy (Ancestors)

Muscular Atrophy; Neuromuscular Manifestations; Neurologic Manifestations; Nervous System Diseases; Atrophy; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms; Signs and Symptoms

Study Officials

• TASEN WEI, MD

  Changhua Christian Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 26, 2022
• First Posted: May 31, 2022
• Study Start: March 1, 2022
• Primary Completion: January 31, 2024
• Study Completion: July 1, 2024
• Last Updated: September 8, 2022

Record last verified: 2022-02

Locations

TW (1)