The study, funded by the National Institute for Health and Care research (NIHR), and led by researchers at the Nuffield Department of Clinical Neurosciences was published in the Lancet Health Longevity.

Many people experience changes in thinking after stroke. This can include difficulties with memory, attention, language, planning, or decision-making. For some, these problems improve over time. For others, they can last much longer and affect day-to-day life, work, relationships, and independence.

There is no single typical recovery pattern for cognition after stroke and families have reported feeling unprepared for these “invisible” effects when someone leaves hospital.

If clinicians can make an earlier and more informed estimate of who is more likely to have longer-term thinking problems, this could help plan more effective support for patients and families.

A team led by Professor Nele Demeyere have created a prediction tool that uses information already collected during a typical hospital stay, including age, gender, severity of the stroke. alongside results from the Oxford Cognitive Screen (OCS), a short bedside test of thinking skills carried out soon after the stroke and now widely used across the NHS.

Data was collected on an initial 430 participants in Oxford, with the accuracy of the predictions tested by looking at the development data of the same group after six months.

The Stroke Cognition Calculator was 76% accurate in predicting a patient’s cognitive difficulties six months after their stroke, whereas other tools that have been published for the same purpose had a 53%-66% accuracy rate. These previous tools have focused on predicting a decline in thinking skills, whereas the Stroke Cognition Calculator allows for the fact that after stroke cognition can improve or stay stable, giving a more accurate result.

Further testing on an additional 264 participants recruited from 37 hospitals across England looked at how the calculator would apply to patients in different healthcare settings and showed that accuracy of predictions remained similar at 74%.

This research is a major step toward more personalised care post-stroke. By using routinely available data, the tool would be easy and equitable to implement across different health systems. Used appropriately, a Stroke Cognition Calculator could eventually support clinician’s decision making about a patient’s needs following discharge. This could help patients and families understand what to expect, and help services plan the right support at the right time, while recognising that every recovery is different.

The team hope that this study will pave the way for further testing in a wider range of stroke services and patient groups, ultimately looking at whether use of the calculator can improve care and outcomes for patients and families.

First author Andrea Kusec says: ‘The Cognition Calculator has a lot of potential for everyday clinical use because it uses predictors and risk factors that should be in every stroke patient’s medical records, making it affordable and easy to implement. I hope it will lead to more conversations on supporting long-term cognitive outcomes and dealing with uncertainty about future change in thinking skills in people with stroke and their loved ones.’

Professor Nele Demeyere says: ‘Cognitive difficulties after stroke are common and highly varied but predicting who will continue to struggle has been challenging. What makes this model different is that it incorporates information already collected in routine care using the Oxford Cognitive Screen, which is widely adopted within NHS clinical practice. The next step is to test how these predictions can be used responsibly to improve follow-up and support for patients and families.’

The paper, ‘Multidomain post-stroke cognitive impairment: Development and validation of a clinical prediction model’ is published in the Lancet Healthy Longevity.