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Retrospective study for the diagnosis of acute pulmonary embolism on non-contrast chest CT via deep learning

Retrospective study for the diagnosis of acute pulmonary embolism on non-contrast chest CT via deep learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400092347
Enrollment
Unknown
Registered
2024-11-14
Start date
2024-12-01
Completion date
Unknown
Last updated
2024-11-18

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

Conditions

Pulmonary embolism

Interventions

Gold Standard:CTPA of the patients lungs may show a low-density filling defect in the pulmonary artery, which is partially or completely surrounded by opaque blood flow (track sign), or a complete fil
or accompanied by indirect signs, including wedge-shaped high-density areas or discoid atelectasis in the lung field, dilation of the central pulmonary artery, and reduced or absent distal blood vesse
Index test:Lung CT images, electrocardiogram, D-dimer, blood gas analysis, blood routine, lower limb venous ultrasound, body temperature, respiration, blood pressure, heart rate, and blood oxygen satu

Sponsors

the First Affiliated Hospital of Harbin Medical University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients who have undergone lung CT scan and pulmonary angiography; 2. Patients suspected of pulmonary thromboembolism;

Exclusion criteria

Exclusion criteria: None

Design outcomes

Primary

MeasureTime frame
Diagnostic accuracy compared with CTPA;

Secondary

MeasureTime frame
Diagnostic accuracy compared with Wells and Geneva scores;

Countries

China

Contacts

Public ContactMeng xianglin

the First Affiliated Hospital of Harbin Medical University

mengzi98@163.com+86 139 3668 3621

Outcome results

None listed

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