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Artificial intelligence electrocardiogram to predict blood glucose levels-A multicenter cohort study

Artificial intelligence electrocardiogram to predict blood glucose levels-A multicenter cohort study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500096931
Enrollment
Unknown
Registered
2025-02-10
Start date
2025-02-11
Completion date
Unknown
Last updated
2025-02-17

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

Conditions

Diabetes

Interventions

Observation group:None

Sponsors

Jiangsu Province Hospital(The First Affiliated Hospital with Nanjing Medical University)
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Age > = 18 and < = 80 years; hospitalized diabetic versus non-diabetic patients; Patient is willing to sign an informed consent form; Patient is willing to undergo long-term follow-up.

Exclusion criteria

Exclusion criteria: severe hyperkalaemia versus hypokalemia (K+=5.5 mmol/L); Long-term use or ongoing intravenous use of anti-arrhythmic drugs (except ß blockers); Patients with pacemaker or CRT implantation; Patients with various sustained arrhythmias include patients with persistent atrial fibrillation, patients with sustained atrial flutter tachycardia, patients with ventricular tachycardia, etc.; patients with fever and severe infection; Patients with cognitive impairment or unconsciousness; Patients with skin allergies who cannot tolerate long-term electrode sticking; Patients with positive infection indicators such as HIV, syphilis, and hepatitis B.

Design outcomes

Primary

MeasureTime frame
Electrocardiogram;Blood Sugar;

Countries

China

Contacts

Public ContactLiu Yun

Jiangsu Province Hospital(The First Affiliated Hospital with Nanjing Medical University)

yanggang201301@163.com+86 186 0140 6982

Outcome results

None listed

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