An observational study in Metabolic Syndrome, Obesity and Sarcopenia, sponsored by Zhangzhou Municipal Hospital. Recruiting at 1 site in China. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-09-23.
Sponsored by Zhangzhou Municipal Hospital · Observational
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.
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.
2,116 studies on the registry are indexed under Metabolic Syndrome; 347 are open to participants now.
This study's planned enrollment of 320 is above the median of 197 across 496 observational studies indexed under Metabolic Syndrome.
Browse Metabolic Syndrome studies →Zhangzhou Municipal Hospital is the lead sponsor of 6 studies on the registry; 5 are open to participants now.
Counted across the registry records on this site, refreshed daily.
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.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
A condition in which the immune system attacks the body’s own tissues, such as rheumatoid arthritis, lupus, psoriasis, type 1 diabetes or inflammatory bowel disease.
Immunotherapy studies often leave out active autoimmune disease, and some name exceptions, such as thyroid disease on replacement hormone. Check the exceptions this study lists.
BMI (body mass index)
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Cancer (malignancy)
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Corticosteroids (steroids)
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Autoimmune disease
A condition in which the immune system attacks the body’s own tissues, such as rheumatoid arthritis, lupus, psoriasis, type 1 diabetes or inflammatory bowel disease.
Immunotherapy studies often leave out active autoimmune disease, and some name exceptions, such as thyroid disease on replacement hormone. Check the exceptions this study lists.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
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.
Participants diagnosed with type 2 diabetes according to the ADA 2023 diagnostic criteria, with disease duration of at least 1 year.
Participants with BMI ≥ 28 kg/m², without hypertension, hyperglycemia, dyslipidemia, or other metabolic abnormalities.
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.
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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 12 months
Plan to share: 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.
No publications or documents are linked to this record.
Started Jul 2023 (actual). Primary completion is estimated for Aug 2027, 49 months after the start.
Of 149 non-industry observational studies under Metabolic Syndrome, half reached primary completion within 43 months of starting (the median), counting those still running; a quarter within 18 and three quarters within 106. This study's planned 49 months is above that.
Counting every sponsor, half of 160 studies reached it within 42 months; a quarter within 18 and three quarters within 106.
How these figures are worked out, and which studies are left out of them.
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Zhangzhou Municipal Hospital