Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford
Oxford, Oxfordshire, OX3 9DU, United Kingdom
NCT Number: NCT06881797
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.
This study is active but is not currently recruiting participants.
18 year and older
All sexes
Observational
Oxford, Oxfordshire, OX3 9DU, United Kingdom
This is a multi-centre observational cohort study of adult patients admitted to acute hospitals. Data will be collected from hospital systems sourcing data from both hospital and primary care electronic health record systems. The study will then use retrospective data to develop and validate tools to identify patients with undiagnosed long-term conditions.
These diagnostic tools will be implemented into a real-time digital platform and further validated on prospectively collected data. Once developed and validated, the digital platform could be used to identify patients who likely have undiagnosed long-term conditions and should undergo further investigation and preventative intervention.
The investigators will initially focus on two long-term conditions (diabetes and atrial fibrillation) and aim to expand this to others within the study period.
Why Diabetes and Atrial Fibrillation? Diabetes Diabetes is a major contributor to multimorbidity. More than 4.3 million people in the UK are living with this condition, with a further one million thought to be undiagnosed. Diabetes increases cardiovascular risk and can lead to chronic kidney disease and debilitating neuropathy. Current diabetes screening occurs through the NHS Health Checks and when people seek healthcare for unrelated symptoms. Early intervention can reduce the risk of long-term complications, including myocardial infarctions and death. However, diagnosing diabetes can be challenging when people are asymptomatic yet already have complications from their diabetes.
There are a range of well-established risk factors including non-white ethnicity, obesity, hypertension, family history, socioeconomic deprivation and increasing age. Recent systematic reviews of existing diabetes screening tools highlight poor or limited external validation, methodological weaknesses, and heterogenous definitions of diabetes that limit comparison between tools.
Atrial Fibrillation (AF) Atrial fibrillation (AF) is a common cardiac arrythmia, affecting 2.5 million people in England alone. Of these, 30% are undiagnosed. AF increases the risk of stroke five-fold, leading to decreased mobility and vascular dementia. There is currently no UK screening programme.
AF is a common complication of critical illness, associated with prolonged intensive care treatment and higher mortality. Lifestyle factors, such as obesity, smoking and high alcohol consumption also increase AF risk. People with AF are often prescribed anticoagulation to reduce stroke risk. However, the benefits of anticoagulation must be carefully balanced with the risk of bleeding, emphasising the need for more accurate prognostic models.
Study Activities
The investigators will reach our objectives by completing the following study activities:
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: Primary timepoint Within five years of hospital discharge. Secondary timepoints • Within three years of hospital discharge • Within two years of hospital discharge • Within one year of hospital discharge • Within six months of hospital discharge
Measure #1 Discrimination (c-statistic) and calibration (intercept and slope) of model predicting diagnosis of a new chronic health problem Measure #2 Positive and negative predictive values, sensitivity, and specificity
Time frame: Up to five years post-hospital discharge
Statistical measures of association including odds ratio with 95% confidence intervals.
Time frame: Up to five years post-hospital discharge
Time frame: Up to five years post-hospital discharge
University of Oxford
Other
Unrecognised Comorbidity Detection in Hospitalised Patients (CODETECT)
Acronym: CODETECT
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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