Artificial Intelligence-based Models for Spine Malalignment Auto-analysis
NCT ID: NCT06711757
Last Updated: 2024-12-02
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
3015 participants
OBSERVATIONAL
2022-01-05
2024-11-05
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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QMH&DKCH cohort
A total of 1,950 whole spine posteroanterior X-rays collected from two local hospitals (QMH and DKCH) were utilized for the development and internal validation of our model.
No interventions assigned to this group
PUMCH cohort
314 whole spine posteroanterior X-rays from Peking Union Medical College Hospital, Beijing, China
No interventions assigned to this group
NFH cohort
94 whole spine posteroanterior X-rays from Nanfang Hospital, Guangzhou, China
No interventions assigned to this group
JSTH cohort
187 whole spine posteroanterior X-rays from Jishuitan Hospital, Beijing, China
No interventions assigned to this group
RJH cohort
294 whole spine posteroanterior X-rays from Ruijin Hospital, Shanghai, China
No interventions assigned to this group
HSH cohort
176 whole spine posteroanterior X-rays from Huashan Hospital, Shanghai, China
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
* A pathological confirmation of the presence or absence of AIS
Exclusion Criteria
* Patients with skin diseases, such as acne, psoriasis, skin pigmentation and rash that can affect imaging
* Individuals that cannot stand up
* Cases where standing imaging was not feasible or other conditions that could impair image acquisition.
10 Years
18 Years
ALL
No
Sponsors
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Peking Union Medical College Hospital
OTHER
Queen Mary Hospital, Hong Kong
OTHER
The Duchess of Kent Children's Hospital at Sandy Bay
UNKNOWN
Ruijin Hospital
OTHER
Huashan Hospital
OTHER
Beijing Jishuitan Hospital
OTHER
Nanfang Hospital, Southern Medical University
OTHER
The University of Hong Kong
OTHER
Responsible Party
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Locations
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Digital Health Laboratory, Li Ka Shing Faculty of Medicine, The University of Hong Kong
Hong Kong, , Hong Kong
Countries
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Other Identifiers
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UW 24-350
Identifier Type: -
Identifier Source: org_study_id