Clinical trial NCT06314594: The Individualized Stepwise Treatment Mode of Adolescent Idiopathic Scoliosis
Official title: The Individualized Stepwise Treatment Mode of Adolescent Idiopathic Scoliosis Based on Transformer Learning Algorithm
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Adolescent Scoliosis
Lead sponsor: Hangzhou Medical College
Sponsor class: OTHER
First posted: 2024-03-18
Enrollment: 76
Sex: ALL
Minimum age (years): 3
Maximum age (years): 18
Standard ages: CHILD
ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: Based on the risk factors affecting adolescent scoliosis found in the previous social survey, this project adopts the paradigm based on transfer learning and semi-supervised learning, and uses mathematical methods such as multiple learning methods and Transformer image classification algorithms to develop and verify the early warning model and stepped treatment model of adolescent scoliosis, and conducts cost-effect analysis.

Detailed description: This study intends to build a standard system for the prevention and treatment of scoliosis in adolescents, do a good job in school health education and prevention and control work in school, comprehensively strengthen the construction of the prevention and control system of spondylosis, improve the ability of professionals in medical institutions, and give full play to the role of home-school-medical in the prevention and control of abnormal spinal curvature in children Firstly, relying on the investigation report, we independently develop the software platform and physical device for measuring, preventing and correcting scoliosis. Secondly, we use a series of prevention and control advantages to change from passive to active. Based on the Internet and big data technology, we integrate Western medicine data management and monitoring technology to establish the characteristics of the disease General disease information (personal history, family history, solar terms, climate and environment detection indicators, etc.) as one of the health management platform, the management platform set up health archives disease risk early warning health intervention and health promotion education follow-up management system management data quality control review data analysis and visualization 9 modules, respectively set up a management platform patient-side physician side and management background 3 parts through sampling investigation clinical research, break the medical school barriers, to build a personalized step treatment model for adolescent scoliosis.

Eligibility criteria: Inclusion Criteria:

1. The diagnosis of moderate and mild AIS, with a Cobb angle measuring less than 45°;
2. The age range of 12 to 16 years old;
3. Participants are required to have no history of mental illness, possess normal communication skills, and be proficient in reading and writing;
4. Signed informed consent by the patient or their family.

Exclusion Criteria:

Patients who fulfill any of the following conditions will be excluded a clear history of inducement, such as diseases caused by trauma, surgery, cognitive impairment, severe dysfunction of heart, liver, kidney and other organs, and malignant tumors, immune diseases and other malignant diseases.

Primary outcomes:
measure: Number of Cobb angles
timeFrame: 4 months before the intervention and 4 months after the intervention
measure: Accuracy of new screening modalities
timeFrame: 4 months before and after the intervention, 4 months after the end of the intervention, and 8 months after the end of the intervention
measure: Hamilton Depression Volume
timeFrame: 4 months before and after the intervention, 4 months after the end of the intervention, and 8 months after the end of the intervention
Secondary outcomes:
Other outcomes:
Locations:
city: Hangzhou
country: China
facility: the Affiliated Zhejiang Provincial People's Hospital to Hangzhou Medical College.
state: Zhejiang
Study officials:
affiliation: hangzhou medical colleage
name: Xinyun Dr Li, doctor
role: PRINCIPAL_INVESTIGATOR
References: