Vision-based Assessment of Joint Extensibility in Ehlers Danlos Syndrome

NCT05366114 | Unknown

• 1 other identifier: 22-5073
• Study Type: observational
• Target: 225
• Locations: 1 country
• Sites: 1

Brief Summary

Ehlers Danlos Syndrome (EDS) is a heterogenous group of genetic disorders with 13 identified subtypes. Hypermobile EDS (hEDS), although the most common subtype of EDS, does not yet have an identified genetic mutation for diagnostic confirmation. Generalized joint hypermobility (GJH) is one of the hallmark features of hEDS. The scoring system used in measurement of GJH was described by Beighton. The Beighton score is calculated using a dichotomous scoring system to assess the extensibility of nine joints. Each joint is scored as either hypermobile (score = 1) or not hypermobile (score = 0). The total score (Beighton score) can vary between a minimum of 0 and a maximum of 9, with higher scores indicating greater joint laxity. While there is moderate validity and inter-rater variability in using the Beighton score, there continue to be several challenges with its widespread and consistent application by clinicians. Some of the barriers reported in the literature include: i) In open, non-standardized systems there can be significant variation in the method to perform these joint extensibility tests including assessing baseline measurements, ii) Determining consistent and standard measurement tools/methodology e.g. goniometer use can vary widely iii) Assessing the reliability of the cut off values and, iv) Performing full assessment prior to informing patients of possible classification of GJH positivity (low specificity and low positive predictive). Inappropriate implementation of tests to assess GJH results in inaccurate identification of GJH and potentially unintended negative consequences of making the wrong diagnosis of EDS. The objective of this study is to create a more robust and valid method of joint mobility measurement and reduce error in the screening of EDS through use of a smartphone-based machine learning application systems for measurement of joint extensibility. The project will: i) Create a smart-phone enabled visual imaging app to assess the measurement of joint extensibility, ii) Assess the feasibility of using the smart-phone app in a clinical setting to screen potential EDS patients, iii) Determine the validity of the application in comparison to in person clinical assessment in a tertiary care academic EDS program. If successful, the smart-phone application could help standardize the care of potential EDS patients in an efficient and cost-effective manner.

Conditions

Ehlers-Danlos Syndrome

Keywords

Ehlers-Danlos Syndrome; Computer-vision; Video; Smartphone; Beighton Score; Joint Range of Motion

Outcome Measures

Primary Outcomes (3)

• Comparison of agreement in predicted angle by pose-estimation library

  The performance of the developed machine learning models for predicting the range of motion will be analyzed by the pose-estimation library used. This analysis will be performed on the subset of the data collected during the first 2 months of data collection. This information will be used to select the pose-estimation libraries to proceed with when refining the machine learning models.

  4 months

• Comparison of agreement in predicted angle by joint

  The performance of the developed machine learning models for predicting the range of motion at each joint (spine, knee, ankle, elbow, shoulder, thumb, fifth finger) will be analyzed independently for each joint. This will provide insight with respect to which joints the system is more accurate at predicting from video.

  1 year

• Assess the accuracy of range of motion prediction using vision-based data

  Machine learning models trained on videos of individuals performing the joint hypermobility maneuvers will be developed. Their performance will be compared to the range of motion measured by an expert clinician using a goniometer.

  1 year

Study Arms (1)

New patients at the GoodHope EDS clinic at Toronto General Hospital

All patients seen in the EDS clinic are eligible for inclusion, regardless of their presenting diagnosis or the results of their assessments.

Other: No intervention, additional video data collection only

Interventions

No intervention, additional video data collection only OTHER

No intervention will be used. Consenting participants will have video recordings taken during their exam of joint hypermobility which will be analyzed at a later time

New patients at the GoodHope EDS clinic at Toronto General Hospital

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The population being studied includes all patients referred to or seen in the GoodHope EDS clinic. The clinic accepts referrals from symptomatic adult patients (age \> 18 years), with EDS, or suspected EDS. EDS is a connective tissue disorder with 100% penetrance, but variable in phenotypic expression, suspected cases of EDS or G-HSD may therefore include other hereditary or acquired connective tissue diseases/disorder, and/or complex chronic illnesses characterized by, or that feature, joint hypermobility, pain, and fatigue.

You may not qualify if:

• Patients who do not consent to participate will not be included (participants may withdraw consent at any time)

Sponsors & Collaborators

• University Health Network, Toronto: lead

Study Sites (1)

GoodHope EDS - Toronto General Hospital

Toronto, Ontario, M5G 2C4, Canada

Location

Related Publications (21)

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  BACKGROUND

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  BACKGROUND

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  BACKGROUND

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  BACKGROUND

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  BACKGROUND

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• Shi B, Brentari D, Shakhnarovich G, Livescu K. Fingerspelling Detection in American Sign Language. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021. p. 4166-75

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  BACKGROUND

• Hakim A. Hypermobile Ehlers-Danlos Syndrome. 2004 Oct 22 [updated 2024 Feb 22]. In: Adam MP, Bick S, Mirzaa GM, Pagon RA, Wallace SE, Amemiya A, editors. GeneReviews(R) [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2026. Available from http://www.ncbi.nlm.nih.gov/books/NBK1279/

  PMID: 20301456 BACKGROUND

• Mittal N, Sabo A, Deshpande A, Clarke H, Taati B. Feasibility of video-based joint hypermobility assessment in individuals with suspected Ehlers-Danlos syndromes/generalised hypermobility spectrum disorders: a single-site observational study protocol. BMJ Open. 2022 Dec 16;12(12):e068098. doi: 10.1136/bmjopen-2022-068098.

  PMID: 36526308 DERIVED

MeSH Terms

Conditions

Ehlers-Danlos Syndrome

Condition Hierarchy (Ancestors)

Hemostatic Disorders; Vascular Diseases; Cardiovascular Diseases; Hemorrhagic Disorders; Hematologic Diseases; Hemic and Lymphatic Diseases; Skin Abnormalities; Congenital Abnormalities; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Skin Diseases, Genetic; Genetic Diseases, Inborn; Collagen Diseases; Connective Tissue Diseases; Skin and Connective Tissue Diseases; Skin Diseases

Study Officials

• Nimish Mittal, MD

  GoodHope Ehlers Danlos Syndrome Clinic, Toronto General Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Medical Director - GoodHope Ehlers Danlos Syndrome Clinic

Study Record Dates

• First Submitted: May 4, 2022
• First Posted: May 9, 2022
• Study Start: April 26, 2022
• Primary Completion: June 1, 2024
• Study Completion: December 1, 2024
• Last Updated: November 28, 2023

Record last verified: 2023-11

Data Sharing

• IPD Sharing: Will not share

Locations

CA (1)