Actively Recruiting
Avoidance of Insulin-induced Lipohypertophy in People With Diabetes Using Ultrasound Scanning Within Diabetes Clinics
Led by Imperial College London · Updated on 2026-02-13
50
Participants Needed
1
Research Sites
73 weeks
Total Duration
On this page
Sponsors
I
Imperial College London
Lead Sponsor
I
Imperial College Healthcare NHS Trust
Collaborating Sponsor
AI-Summary
What this Trial Is About
Diabetes is a common long-term health condition globally. Type 1 diabetes requires insulin treatment right from diagnosis. Similarly, many living with type 2 diabetes eventually require insulin injections as the condition progresses. A common but often underappreciated complication associated with insulin use is the formation of fatty tissue at injection sites, known as "Lipos," a shorthand for "Lipohypertrophy." These Lipos can interfere with insulin absorption, leading to an altered insulin action profile. This results in glucose fluctuations increasing the risk of both high and low glucose levels. In current medical practice, Lipos are assessed through clinical examination, specifically by physically palpating the injection sites. Research indicates that approximately 40% of insulin-treated individuals may have Lipos. However, manual palpation can often overlook these fatty deposits. Ultrasound scanning (USS) presents a more effective method for detecting Lipos. Studies that have employed ultrasound scanning have reported a much higher prevalence, reaching up to 86%. The primary goal of this study is to ascertain whether the avoidance of ultrasound-identified Lipos can improve glucose regulation. The focus will be on individuals using continuous glucose monitoring who exhibit high glucose fluctuations and less time within their target range. By focusing on this population, the chances of identifying those with Lipos will increase. Participants will undergo a clinical examination followed by an ultrasound scan. Those found to have Lipos will receive guidance on avoiding those sites and education on insulin injection techniques. Glucose data will be collected periodically over the next 24 weeks. After this period, participants will return for a follow-up ultrasound scan. Additionally, members of the diabetes care team will be trained to conduct the ultrasound scans. Data from this study may also be utilized to develop artificial intelligence algorithms aimed at identifying Lipos in future ultrasound scans.
CONDITIONS
Official Title
Avoidance of Insulin-induced Lipohypertophy in People With Diabetes Using Ultrasound Scanning Within Diabetes Clinics
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age 18 years and above
- Diagnosis of any type of diabetes for at least 1 year managed with multiple daily insulin injections or insulin pump therapy
- Currently using continuous glucose monitoring (CGM) with more than 70% use in the last 4 weeks
- No expected changes to diabetes treatment in the next 6 months
- Coefficient of variation of CGM glucose above 36% and time in range between 3.9 to 10.0 mmol/l below 70%
- Willing and able to undergo two ultrasound scans of insulin injection sites
- Able to understand English sufficiently for safe participation
You will not qualify if you...
- Any other physical disease or severe mental illness that could interfere with study conduct or results as judged by the investigator
- Known lipodystrophy disorders, primary or secondary
- Dercum's disease
- Women who are pregnant or planning pregnancy
- Active life-threatening illness limiting life expectancy to less than 6 months
- Estimated Glomerular Filtration Rate (e-GFR) less than 25
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Imperial College Healthcare NHS Trust
London, United Kingdom, M13 9WL
Actively Recruiting
Research Team
L
Lalantha Leelarathna, PhD FRCP (UK)
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NA
Model
SINGLE_GROUP
Primary Purpose
DIAGNOSTIC
Number of Arms
1
Not the Right Trial for You?
Explore thousands of other clinical trials that might be a better match.
Sign up to get personalized trial recommendations delivered to your inbox.
Already have an account? Log in here