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Development and Demonstration of a Cloud-edge Collaborative Platform for Prediction of Postpartum Pelvic Floor Dysfunction Based on 5G+AI

Development and Demonstration of a Cloud-edge Collaborative Platform for Prediction of Postpartum Pelvic Floor Dysfunction Based on 5G+AI

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400082079
Enrollment
Unknown
Registered
2024-03-20
Start date
2023-08-15
Completion date
Unknown
Last updated
2024-03-25

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

Conditions

pelvic floor dysfunction

Interventions

Trail group :No

Sponsors

The Third Affiliated Hospital of Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to 55 Years

Inclusion criteria

Inclusion criteria: 1) Age =18 years old; 2) Single full-term postpartum women.

Exclusion criteria

Exclusion criteria: 1) Pelvic mass >3cm detected by routine ultrasound; 2) History of pelvic surgery; 3) History of estrogen use; 4) History of neurological disorders and lumbosacral trauma; 5) Patients with systemic connective tissue diseases; 6) Inability to complete the study procedures as required; 7) Patients with incomplete medical history and pelvic floor ultrasound images that do not meet the modeling criteria.

Design outcomes

Primary

MeasureTime frame
Bladder position;Uterine position;Bladder neck mobility;Area of levator hiatus;ICIQ-SF;IIQ-7;PFDI-20;area under the receiver operating characteristic curve;sensitivity;specificity;accuracy;

Countries

China

Contacts

Public ContactXinling Zhang

The Third Affiliated Hospital of Sun Yat-sen University

zhxinl@mail.sysu.edu.cn+86 20 8525 3030

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026