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NCT06881797: CODETECT
Unrecognised Comorbidity Detection in Hospitalised Patients
trial in Diabetes in 4,500,000 participants. Participants enrolled and being followed up; not accepting new ones.
30 November 2027
Quick facts
| Lead sponsor | University of Oxford |
|---|---|
| Status | Active, enrolled |
| Study type | OBSERVATIONAL |
| Enrollment | 4,500,000 |
| Start date | 1 July 2024 |
| Primary completion | 30 November 2027 |
| Estimated completion | 30 November 2027 |
| Sites | 1 location across United Kingdom |
Conditions studied
- Diabetes — all drugs for Diabetes →
- Atrial Fibrillation (AF) — all drugs for Atrial Fibrillation (AF) →
- Cardiac Disease — all drugs for Cardiac Disease →
Sponsor
University of Oxford
Who can join
18 and older, any sex, with Diabetes or Atrial Fibrillation (AF). Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
Over two million people in the UK are unaware that they're living with a long-term (chronic) health condition, such as diabetes or a heart problem. These chronic conditions can lead to serious complications such as heart attacks, strokes, and kidney problems. By diagnosing these conditions earlier, effective treatments can be started sooner which will reduce the risk of harm. However, diagnosis relies on people having symptoms and contacting their doctor or attending NHS Health Checks. There are over 16 million admissions to English hospitals each year. Hospitals collect a lot of information during a hospital stay including patients' age, blood test results and blood pressure measurements. Research has shown that this information can be helpful in spotting people with chronic conditions. This study aims to design and test a digital platform to find the patients in hospital who are most likely to have a chronic disease or develop one in the near future. To do this, the investigators will: * Use information from earlier research studies and experts to pinpoint which patient information (for example, certain blood tests) would be most useful to spot people with chronic conditions. * Extract relevant information from historical patient records, looking at who has these risk factors and which patients developed chronic conditions. The investigators will use information from hospital and general practitioner records. * Build tools to combine this information to predict which people have, or will develop, chronic conditions. * Implement these tools into a "real-time" digital platform that could be used to find which people should undergo further testing for a chronic condition. * Test the platform usability with clinical stake holders.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06881797
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06881797 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by University of Oxford
- Last refreshed: 18 March 2025
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06881797.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing