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Predicting hip fractures using machine learning based on femoral geometry

Predicting Femoral Fractures Using Femoral Geometry via Machine Learning: A Study Based on the Chinese Population Incorporating Multiple Mixed Factors

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600123191
Enrollment
Unknown
Registered
2026-04-22
Start date
2026-04-22
Completion date
Unknown
Last updated
2026-04-27

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

Conditions

Hip fracture

Interventions

Trochanteric fracture group, femoral neck fracture group, normal pelvis group:None

Sponsors

Xuzhou Mining Group General Hospita
Lead Sponsor

Eligibility

Sex/Gender
All
Age
65 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Age >= 65 years. 2. Diagnosed by imaging (X-ray or CT) as an initial, unilateral, low-energy trauma-induced femoral neck fracture or intertrochanteric fracture. 3. Undergoing surgical treatment at this hospital. 4. Possession of complete preoperative hip imaging data (DICOM format) and accessible clinical medical records.

Exclusion criteria

Exclusion criteria: 1. Fractures resulting from high-energy trauma (e.g., road traffic accidents, falls from height). 2. Conditions severely affecting bone metabolism (e.g., hyperparathyroidism, Paget's disease, bone tumours). 3. Long-term use (over 6 months prior to study) of medications affecting bone metabolism (e.g., glucocorticoids, bisphosphonates, SERMs, teriparatide). 4. Occurrence of bilateral hip fractures. 5. Poor imaging quality rendering key anatomical structures unidentifiable or unmeasurable.

Design outcomes

Primary

MeasureTime frame
Neck length (NL);hip axis length;femoral neck axis length;femoral neck-shaft angle;femoral head diameter;femoral eccentricity;femoral neck diameter;Wiberg angle (CEA);

Countries

China

Contacts

Public ContactZhu Ziqiang

Xuzhou Mining Group General Hospital

zhuziq@163.com+86 130 5620 7205

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 1, 2026