Metabolic SyndromeNCT07836088
A Clinical Study on Using Multimodal Ultrasound to Assess Muscle Mass in Metabolic Diseases
An observational study of Metabolic Syndrome and Obesity, run by Zhangzhou Municipal Hospital at 1 site in China.
Trial summary
This study aims to evaluate the clinical value of multimodal ultrasound for assessing muscle mass in patients with metabolic diseases, including metabolic syndrome, type 2 diabetes, and simple obesity. Skeletal muscle is the largest metabolic organ in the human body and plays a critical role in glucose metabolism. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Metabolic Syndrome, Obesity, Sarcopenia
- How many people
- 320 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2023to 31 Dec 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Adult patients diagnosed with metabolic syndrome, type 2 diabetes, or simple obesity, as well as healthy volunteers, recruited from the Endocrinology Department and Physical Examination Center of Zhangzhou Hospital, Fujian Medical University. All participants must meet the specified inclusion and exclusion criteria. The three metabolic disease groups will be matched with healthy controls by age and sex. A total of 320 participants (80 per group) will be enrolled.
Who may be able to join
- Diagnosis of metabolic syndrome according to the Chinese Consensus on Diagnosis and Management of Metabolic Syndrome (2020 edition), meeting at least 3 of the following 5 criteria: abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-C.
- Diagnosis of type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year.
- Body mass index (BMI) >= 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities.
- Healthy volunteers without metabolic diseases, muscle diseases, chronic liver or kidney dysfunction, malignancies, cardiovascular diseases, or neurological disorders, and without long-term use of corticosteroids or other medications affecting muscle metabolism.
- Age and sex matched across all four groups.
- Willing and able to provide written informed consent and comply with all study procedures including ultrasound examination, DXA scan, and follow-up visits.
Who cannot join
- Severe hepatic or renal failure, malignancy, stroke, severe cardiovascular disease, or autoimmune diseases.
- Long-term use of corticosteroids, muscle relaxants, or other medications affecting muscle metabolism.
- Presence of movement disorders, joint diseases, muscle injury, muscular dystrophy, or other conditions affecting muscle function.
- Pregnancy or lactation.
- Inability to cooperate with ultrasound examination, DXA scanning, or follow-up assessments.
- Any other condition that, in the opinion of the investigator, would interfere with the study objectives or participant safety.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Zhangzhou Hospital, Fujian Medical University
Zhangzhou, Fujian, 363000
Fahui Lu, Master's, 0596-2082027, 18750745115@163.com
Wenting Jiang, Master's, 13625926205, 120722807@163.com
About this study
This study aims to evaluate the clinical value of multimodal ultrasound for assessing muscle mass in patients with metabolic diseases, including metabolic syndrome, type 2 diabetes, and simple obesity. Skeletal muscle is the largest metabolic organ in the human body and plays a critical role in glucose metabolism. Muscle mass reduction is common in patients with metabolic diseases and is associated with insulin resistance, poor disease control, and increased risk of complications. Currently available methods for muscle assessment, such as dual-energy X-ray absorptiometry (DXA), computed tomography (CT), and magnetic resonance imaging (MRI), have limitations including high cost, radiation exposure, or poor portability, making them unsuitable for routine bedside monitoring.
Multimodal ultrasound combines B-mode imaging, shear-wave elastography, superb microvascular imaging, and artificial intelligence analysis to provide a comprehensive evaluation of muscle morphology, stiffness, microcirculation, and quality. This non-invasive, radiation-free, and portable technique may serve as an ideal tool for muscle assessment in clinical practice.
Read more
This prospective observational study will enroll 320 participants divided into four groups: metabolic syndrome (n=80), type 2 diabetes (n=80), simple obesity (n=80), and healthy controls (n=80). All participants will undergo baseline assessments including clinical data collection, biochemical tests, muscle function tests (handgrip strength, gait speed, Short Physical Performance Battery [SPPB]), multimodal ultrasound examination (muscle thickness, cross-sectional area, echo intensity, shear wave velocity, Young's modulus, microvascular density), and DXA measurement as the reference standard. The three metabolic disease groups will be followed prospectively for 12 months with repeat assessments at 6 and 12 months.
The primary objectives are to determine diagnostic thresholds of multimodal ultrasound parameters for detecting metabolic sarcopenia; to establish correlation between ultrasound parameters and metabolic indicators (blood glucose, glycated hemoglobin [HbA1c], homeostatic model assessment of insulin resistance [HOMA-IR], lipids); to develop a combined diagnostic model integrating ultrasound and clinical parameters; and to evaluate the predictive value of baseline ultrasound parameters for 12-month disease progression and complications. The findings will provide a non-invasive, convenient, and widely applicable tool for early screening, risk stratification, and therapeutic monitoring of muscle abnormalities in patients with metabolic diseases.
Read the detailed description
This study will be conducted at Zhangzhou Hospital, Fujian Medical University. Participants in the four groups will be matched for age and sex to ensure comparability. Multimodal ultrasound examinations will be performed by two trained sonographers using a high-end musculoskeletal ultrasound system (GE Logiq E9 or Philips EPIQ 7) with a 10-15 MHz linear array probe. Parameters assessed include B-mode imaging (muscle thickness, fascicle length, pennation angle, cross-sectional area, and echo intensity); shear-wave elastography (shear wave velocity and Young's modulus measured at rest and during isometric contraction); and artificial intelligence (automated region of interest [ROI] segmentation and texture analysis for quantification of muscle fat infiltration).
Clinical and biochemical assessments include fasting blood glucose, HbA1c, lipid profile, insulin, HOMA-IR, and liver/kidney function. Muscle function is assessed by handgrip strength, 6-meter gait speed, and SPPB. All assessments follow standardized protocols with quality control measures including inter-observer reproducibility testing (intraclass correlation coefficient [ICC] > 0.85).
Statistical analyses will be performed using SPSS 26.0. Group comparisons will use analysis of variance (ANOVA) or Kruskal-Wallis tests. Correlation analyses will use Pearson or Spearman methods. Receiver operating characteristic (ROC) curve analysis will determine diagnostic thresholds. Logistic regression will be used to construct combined diagnostic models. Cox proportional hazards models and Kaplan-Meier analysis will evaluate prognostic value. A p-value < 0.05 will be considered statistically significant.
The study is expected to yield diagnostic thresholds of multimodal ultrasound parameters for metabolic sarcopenia; a combined ultrasound-clinical diagnostic model; prognostic prediction models for disease progression and complications; and a standardized protocol for clinical application of multimodal ultrasound in metabolic disease management.
- Conditions
- Metabolic Syndrome, Obesity, Sarcopenia, Type 2 Diabetes
- Keywords
- Multimodal Ultrasound, Muscle Mass, Metabolic Syndrome, Type 2 Diabetes, Obesity, Sarcopenia, Shear-Wave Elastography, Skeletal Muscle, Diagnostic Accuracy, Insulin Resistance, Prospective Study, DXA
- Medical subject headings
- Metabolic Syndrome, Obesity, Sarcopenia, Diabetes Mellitus, Type 2, Insulin Resistance
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 |
|---|---|---|
| Metabolic Syndrome Group | Participants diagnosed with metabolic syndrome according to the Chinese Consensus on Diagnosis and Management of Metabolic Syndrome (2020 edition). Inclusion criteria: meeting at least 3 of the following 5 criteria: abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-C. | |
| Type 2 Diabetes Group | Participants diagnosed with type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year. | |
| Simple Obesity Group | Participants with BMI ≥ 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities. | |
| Healthy Control Group | Healthy volunteers without metabolic diseases, muscle diseases, chronic liver/kidney diseases, malignancies, cardiovascular diseases, or neurological disorders. Age and sex matched to the other three groups. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area under the ROC curve (AUC) of multimodal ultrasound for detecting metabolic sarcopenia
Area under the receiver operating characteristic curve (AUC) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Measured: At baseline assessment
Sensitivity of multimodal ultrasound for detecting metabolic sarcopenia
Sensitivity (true positive rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Measured: At baseline assessment
Specificity of multimodal ultrasound for detecting metabolic sarcopenia
Specificity (true negative rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Measured: At baseline assessment
Positive predictive value of multimodal ultrasound for detecting metabolic sarcopenia
Positive predictive value of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Measured: At baseline assessment
Negative predictive value of multimodal ultrasound for detecting metabolic sarcopenia
Negative predictive value of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Measured: At baseline assessment
Correlation between ultrasound parameters and metabolic indicators
Correlation coefficients (Pearson or Spearman) between multimodal ultrasound parameters (muscle thickness, cross-sectional area [CSA], echo intensity, shear wave velocity [SWV], Young's modulus [Emean], microvascular density) and metabolic indicators including fasting blood glucose, glycated hemoglobin (HbA1c), homeostatic model assessment of insulin resistance (HOMA-IR), triglycerides, high-density lipoprotein cholesterol (HDL-C), and systemic inflammatory markers.
Measured: At baseline assessment
Combined diagnostic model for metabolic sarcopenia
Development and validation of a combined diagnostic model integrating multimodal ultrasound parameters and clinical indicators (age, BMI, metabolic components) for diagnosing metabolic sarcopenia, with model performance evaluated by area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis.
Measured: At baseline assessment
Predictive value of baseline ultrasound for 12-month outcomes
Hazard ratios (HRs) from Cox proportional hazards regression models for baseline multimodal ultrasound parameters as predictors of metabolic disease progression, incident sarcopenia, and cardiovascular complications during the 12-month prospective follow-up period. Kaplan-Meier survival curves will be generated to compare complication rates across different ultrasound parameter levels.
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Sep 2026
- Study start1 Jul 2023
- Primary completion31 Aug 2027 (estimated)
- Study completion31 Dec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Metabolic SyndromeStudies 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
- Prospective
- Enrolment
- 320 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Zhangzhou Municipal Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Wenting Jiang, Master's, Principal investigator, Department of Ultrasound Medicine, Zhangzhou Hospital Affiliated to Fujian Medical University, China
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07836088
- Sponsor's protocol ID
- lufahui
- Status last verified
- Sep 2026
- First submitted
- 14 Sep 2026
- Last updated
- 23 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: This is a single-center observational diagnostic study and doesn't involve the need for multi-center data sharing. The protocol doesn't mention plans to share data with other researchers. The study data will mainly be used for internal publications and building a database, and won't involve providing raw individual patient data (IPD) to external researchers.
Study at a glance
From the registry record, last updated by the sponsor on 23 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Clinical Study on Using Multimodal Ultrasound to Assess Muscle Mass in Metabolic Diseases
- ClinicalTrials.gov ID
- NCT07836088
- Acronym / sponsor ID
- lufahui
- Conditions
- Metabolic Syndrome, Obesity, Sarcopenia, Type 2 Diabetes
- Keywords
- Multimodal Ultrasound, Muscle Mass, Metabolic Syndrome, Type 2 Diabetes, Obesity, Sarcopenia, Shear-Wave Elastography, Skeletal Muscle
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 320 participants (estimated)
- Lead sponsor
- Zhangzhou Municipal HospitalUniversity, hospital or other
- Study start
- 1 Jul 2023 (actual)
- Primary completion
- 31 Aug 2027 (estimated)
- Study completion
- 31 Dec 2027 (estimated)
- First posted
- 23 Sep 2026 (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.
This study aims to evaluate the clinical value of multimodal ultrasound for assessing muscle mass in patients with metabolic diseases, including metabolic syndrome, type 2 diabetes, and simple obesity. Skeletal muscle is the largest metabolic organ in the human body and plays a critical role in glucose metabolism. Muscle mass reduction is common in patients with metabolic diseases and is associated with insulin resistance, poor disease control, and increased risk of complications. Currently available methods for muscle assessment, such as dual-energy X-ray absorptiometry (DXA), computed tomography (CT), and magnetic resonance imaging (MRI), have limitations including high cost, radiation exposure, or poor portability, making them unsuitable for routine bedside monitoring.
Multimodal ultrasound combines B-mode imaging, shear-wave elastography, superb microvascular imaging, and artificial intelligence analysis to provide a comprehensive evaluation of muscle morphology, stiffness, microcirculation, and quality. This non-invasive, radiation-free, and portable technique may serve as an ideal tool for muscle assessment in clinical practice.
This prospective observational study will enroll 320 participants divided into four groups: metabolic syndrome (n=80), type 2 diabetes (n=80), simple obesity (n=80), and healthy controls (n=80). All participants will undergo baseline assessments including clinical data collection, biochemical tests, muscle function tests (handgrip strength, gait speed, Short Physical Performance Battery [SPPB]), multimodal ultrasound examination (muscle thickness, cross-sectional area, echo intensity, shear wave velocity, Young's modulus, microvascular density), and DXA measurement as the reference standard. The three metabolic disease groups will be followed prospectively for 12 months with repeat assessments at 6 and 12 months.
The primary objectives are to determine diagnostic thresholds of multimodal ultrasound parameters for detecting metabolic sarcopenia; to establish correlation between ultrasound parameters and metabolic indicators (blood glucose, glycated hemoglobin [HbA1c], homeostatic model assessment of insulin resistance [HOMA-IR], lipids); to develop a combined diagnostic model integrating ultrasound and clinical parameters; and to evaluate the predictive value of baseline ultrasound parameters for 12-month disease progression and complications. The findings will provide a non-invasive, convenient, and widely applicable tool for early screening, risk stratification, and therapeutic monitoring of muscle abnormalities in patients with metabolic diseases.
Detailed description
This study will be conducted at Zhangzhou Hospital, Fujian Medical University. Participants in the four groups will be matched for age and sex to ensure comparability. Multimodal ultrasound examinations will be performed by two trained sonographers using a high-end musculoskeletal ultrasound system (GE Logiq E9 or Philips EPIQ 7) with a 10-15 MHz linear array probe. Parameters assessed include B-mode imaging (muscle thickness, fascicle length, pennation angle, cross-sectional area, and echo intensity); shear-wave elastography (shear wave velocity and Young's modulus measured at rest and during isometric contraction); and artificial intelligence (automated region of interest [ROI] segmentation and texture analysis for quantification of muscle fat infiltration).
Clinical and biochemical assessments include fasting blood glucose, HbA1c, lipid profile, insulin, HOMA-IR, and liver/kidney function. Muscle function is assessed by handgrip strength, 6-meter gait speed, and SPPB. All assessments follow standardized protocols with quality control measures including inter-observer reproducibility testing (intraclass correlation coefficient [ICC] > 0.85).
Statistical analyses will be performed using SPSS 26.0. Group comparisons will use analysis of variance (ANOVA) or Kruskal-Wallis tests. Correlation analyses will use Pearson or Spearman methods. Receiver operating characteristic (ROC) curve analysis will determine diagnostic thresholds. Logistic regression will be used to construct combined diagnostic models. Cox proportional hazards models and Kaplan-Meier analysis will evaluate prognostic value. A p-value < 0.05 will be considered statistically significant.
The study is expected to yield diagnostic thresholds of multimodal ultrasound parameters for metabolic sarcopenia; a combined ultrasound-clinical diagnostic model; prognostic prediction models for disease progression and complications; and a standardized protocol for clinical application of multimodal ultrasound in metabolic disease management.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 4
| Arm | Type | Receives |
|---|---|---|
| Metabolic Syndrome Group | – | –Participants diagnosed with metabolic syndrome according to the Chinese Consensus on Diagnosis and Management of Metabolic Syndrome (2020 edition). Inclusion criteria: meeting at least 3 of the following 5 criteria: abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-C. |
| Type 2 Diabetes Group | – | –Participants diagnosed with type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year. |
| Simple Obesity Group | – | –Participants with BMI ≥ 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities. |
| Healthy Control Group | – | –Healthy volunteers without metabolic diseases, muscle diseases, chronic liver/kidney diseases, malignancies, cardiovascular diseases, or neurological disorders. Age and sex matched to the other three groups. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Adult patients diagnosed with metabolic syndrome, type 2 diabetes, or simple obesity, as well as healthy volunteers, recruited from the Endocrinology Department and Physical Examination Center of Zhangzhou Hospital, Fujian Medical University. All participants must meet the specified inclusion and exclusion criteria. The three metabolic disease groups will be matched with healthy controls by age and sex. A total of 320 participants (80 per group) will be enrolled.
Key inclusion criteria (6 listed)
- Diagnosis of metabolic syndrome according to the Chinese Consensus on Diagnosis and Management of Metabolic Syndrome (2020 edition), meeting at least 3 of the following 5 criteria: abdominal obesity, hypertension, hyperglycemia, hypertriglyceridemia, and low HDL-C.
- Diagnosis of type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year.
- Body mass index (BMI) >= 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities.
- Healthy volunteers without metabolic diseases, muscle diseases, chronic liver or kidney dysfunction, malignancies, cardiovascular diseases, or neurological disorders, and without long-term use of corticosteroids or other medications affecting muscle metabolism.
- Age and sex matched across all four groups.
Key exclusion criteria (6 listed)
- Severe hepatic or renal failure, malignancy, stroke, severe cardiovascular disease, or autoimmune diseases.
- Long-term use of corticosteroids, muscle relaxants, or other medications affecting muscle metabolism.
- Presence of movement disorders, joint diseases, muscle injury, muscular dystrophy, or other conditions affecting muscle function.
- Pregnancy or lactation.
- Inability to cooperate with ultrasound examination, DXA scanning, or follow-up assessments.
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
Area under the ROC curve (AUC) of multimodal ultrasound for detecting metabolic sarcopenia
Time frame: At baseline assessment
Area under the receiver operating characteristic curve (AUC) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Sensitivity of multimodal ultrasound for detecting metabolic sarcopenia
Time frame: At baseline assessment
Sensitivity (true positive rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Specificity of multimodal ultrasound for detecting metabolic sarcopenia
Time frame: At baseline assessment
Specificity (true negative rate) of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Positive predictive value of multimodal ultrasound for detecting metabolic sarcopenia
Time frame: At baseline assessment
Positive predictive value of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Negative predictive value of multimodal ultrasound for detecting metabolic sarcopenia
Time frame: At baseline assessment
Negative predictive value of ultrasound parameters including muscle thickness, cross-sectional area, echo intensity, shear wave velocity (SWV), and Young's modulus (Emean) for detecting metabolic sarcopenia, using dual-energy X-ray absorptiometry (DXA)-measured appendicular skeletal muscle mass (ASM) as the reference standard.
Correlation between ultrasound parameters and metabolic indicators
Time frame: At baseline assessment
Correlation coefficients (Pearson or Spearman) between multimodal ultrasound parameters (muscle thickness, cross-sectional area [CSA], echo intensity, shear wave velocity [SWV], Young's modulus [Emean], microvascular density) and metabolic indicators including fasting blood glucose, glycated hemoglobin (HbA1c), homeostatic model assessment of insulin resistance (HOMA-IR), triglycerides, high-density lipoprotein cholesterol (HDL-C), and systemic inflammatory markers.
Combined diagnostic model for metabolic sarcopenia
Time frame: At baseline assessment
Development and validation of a combined diagnostic model integrating multimodal ultrasound parameters and clinical indicators (age, BMI, metabolic components) for diagnosing metabolic sarcopenia, with model performance evaluated by area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis.
Predictive value of baseline ultrasound for 12-month outcomes
Time frame: 12 months
Hazard ratios (HRs) from Cox proportional hazards regression models for baseline multimodal ultrasound parameters as predictors of metabolic disease progression, incident sarcopenia, and cardiovascular complications during the 12-month prospective follow-up period. Kaplan-Meier survival curves will be generated to compare complication rates across different ultrasound parameter levels.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Sep 2026.
- Individual participant dataSharing planned: No. This is a single-center observational diagnostic study and doesn't involve the need for multi-center data sharing. The protocol doesn't mention plans to share data with other researchers. The study data will mainly be used for internal publications and building a database, and won't involve providing raw individual patient data (IPD) to external researchers.
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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.
Wenting Jiang, Master's principal investigator
Department of Ultrasound Medicine, Zhangzhou Hospital Affiliated to Fujian Medical University, China
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 Metabolic Syndrome and Obesity, run by Zhangzhou Municipal Hospital at 1 site in China.
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 6 inclusion and 6 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: looking for participants now, as of the sponsor's last update on 23 Sep 2026. 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 China. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Fahui Lu, Master's (0596-2082027, 18750745115@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Area under the ROC curve (AUC) of multimodal ultrasound for detecting metabolic sarcopenia (time frame: At baseline assessment). The study lists 8 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 23 Sep 2026.