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Construction and validation of a clinical prediction model for functional abdominal pain in children based on machine learning

Construction and validation of a clinical prediction model for functional abdominal pain in children based on machine learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117929
Enrollment
Unknown
Registered
2026-01-30
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-02-02

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Functional Abdominal Pain Disorders

Interventions

Chronic abdominal pain group of non-functional abdominal pain disease:NA
Functional abdominal pain disorders group:NA

Sponsors

Children's Hospital of Chongqing Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
4 Years to 18 Years

Inclusion criteria

Inclusion criteria: 1. Children who visited the pain Clinic of Children's Hospital Affiliated to Chongqing Medical University between June 2023 and December 2030; 2. Patients in the functional abdominal pain group were included: children diagnosed with functional abdominal pain; 3. Patients in the chronic abdominal pain control group of non-functional abdominal pain diseases were included: those diagnosed with the following diseases (gastric ulcer, duodenal ulcer, chronic gastritis, chronic enteritis, chronic cholecystitis, tuberculous peritonitis, Crohn's disease, ulcerative colitis, tumors of abdominal organs); 4. Age: 4 to 18 years old.

Exclusion criteria

Exclusion criteria: 1. The child has mental illness or cognitive impairment; 2. Within the past six months, the patient has received treatments that may affect the FAPD assessment, such as antacid and antispasmodic treatments; 3. Children with retrospective data missing more than 30% (more than 30% of the key variables to be collected and analyzed in this study were missing, inaccessible or poorly recorded); 4. Acute abdominal pain or acute or chronic pain diseases in other parts of the body (such as acute gastroenteritis, surgical acute abdomen or traumatic pain in the limbs, etc.); 5. Children with serious diseases in other systems, such as cardiovascular diseases, respiratory system diseases, hematological malignancies, diabetes, etc. 6. The family of the child refused.

Design outcomes

Primary

MeasureTime frame
Predict the risk of functional abdominal pain in children through machine learning models;

Secondary

MeasureTime frame
The specificity of the model;The sensitivity of the model;The predicted value of the model;The area under curve of the receiver operating characteristic;

Countries

China

Contacts

Public ContactTu Shengfen

Children's Hospital of Chongqing Medical University

519194496@qq.com+86 23 6848 6646

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026