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Development and verification of intraoperative blood electrolyte concentration prediction technology based on ECG using deep learning models

Development and verification of intraoperative blood electrolyte concentration prediction technology based on ECG using deep learning models

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2300077172
Enrollment
Unknown
Registered
2023-11-01
Start date
2023-11-01
Completion date
Unknown
Last updated
2023-11-06

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

Conditions

Blood gas analysis

Interventions

Case series:None

Sponsors

West China Second Hospital of Sichuan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 100 Years

Inclusion criteria

Inclusion criteria: Patients who are scheduled to undergo blood gas analysis during surgery

Exclusion criteria

Exclusion criteria: 1. Patients who are scheduled to undergo extracorporeal bypass during surgery (cardiac arrest, inability to collect effective ECG waveforms); 2. Patients with pacemakers placed; 3. Preoperative diagnosis of patients with atrial fibrillation, atrial flutter, conduction block, ventricular tachycardia, ventricular fibrillation, or pre-excitation syndrome affecting the electrical conduction disorder of the heart.

Design outcomes

Primary

MeasureTime frame
Blood gas analysis indicators;—

Secondary

MeasureTime frame
Infection;Pulmonary complication;Acute kidney injury;Frailty;Sarcopenia;—

Countries

China

Contacts

Public ContactDongxu Chen

West China Second Hospital of Sichuan University

scucdx@foxmail.com+86 158 8173 0901

Outcome results

None listed

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