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Use of Artificial intelligence Enhanced Electrocardiogram Analysis for Detection of Left Ventricular Systolic Dysfunction in Hypotensive Critically ill Patients

Use of Artificial intelligence Enhanced Electrocardiogram Analysis for Detection of Left Ventricular Systolic Dysfunction in Hypotensive Critically ill Patients

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
PACTR
Registry ID
PACTR202511779912747
Enrollment
70
Registered
2025-11-21
Start date
2025-09-15
Completion date
Unknown
Last updated
2026-09-14

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

Conditions

Circulatory System Cardiology

Interventions

Baseline ECG Assesment by ECGBuddy and Echocardiographic Assesment of Left Ventrcular Function

Sponsors

Mohamed Eltokhy
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: • Age =18 years. • Admission to ICU with documented hypotension (systolic blood pressure < 90 mmHg or MAP < 65 mmHg).

Exclusion criteria

Exclusion criteria: • Paced cardiac rhythm • Bundle branch blocks or significant arrhythmias that interfere with ECG interpretation. • Poor-quality ECG recordings or missing data • Poor echogenic window • Contraindications to transthoracic echocardiography.

Design outcomes

Primary

MeasureTime frame
Assessing the diagnostic accuracy of ECGBuddy in detecting LVSD (EF = 40%) compared to Transthoracic Echocardiography.

Secondary

MeasureTime frame
Correlation of ECGBuddy-predicted LVSD with: ? ICU length of stay ? Mechanical ventilation duration ? Need for inotropic support ? 7-day mortality.

Countries

Egypt

Contacts

Public ContactMohamed Eltokhy

ICU Resident at National Heart Institute of Egypt

mohamed.hossam.eltokhy@gmail.com+201007233869

Outcome results

None listed

Source: PACTR (via WHO ICTRP) · Data processed: Sep 19, 2026