Eugene Tang on Clinical Prediction Rules for Cognitive Outcomes Post-Stroke
Eugene Tang, NIHR RRDN NENC Primary Care Settings Lead at NIHR Research Delivery Network, shared on LinkedIn:
”New Publication Alert!
Thrilled to share my very first output from my NIHR (National Institute for Health and Care Research) Advanced Fellowship as I near the end of year 1!
Just published in eClinicalMedicine – The Lancet Discovery Science
Key insights from our systematic review and meta-analysis:
- Prediction models are improving for cognitive impairment.
- Machine learning approaches are emerging
- However! Most models rely on small datasets and lack robust external validation or real-world testing
- Overall certainty of evidence is still low, highlighting an urgent need for larger, pooled datasets, ensuring model development follows best practice guidance and real-world validation
A special additional personal highlight: this review also provided opportunities for me to mentor early career researchers to get involved, develop skills, and allow me to help with Capacity Building for the future of Stroke and Dementia research!
Thanks to Dr Serena Sabatini, Linda Errington, Claire Burley, Jennifer Dunne, Dr Leanne Greene, Ram Bajpai, Nele Demeyere, Blossom Stephan, Terry Quinn and other authors not on LinkedIn.”
Read the full article here.
Article: Clinical prediction rules for cognitive outcomes post-stroke: an updated systematic review and meta-analysis
Authors: Eugene Yee Hing Tang, Jacob Brain, Rhiannon De Ivey, Serena Sabatini, Felicity Mills, Emma Jackson, Linda Errington, Claire Burley, Jennifer Dunne, Leanne Greene, Ram Bajpai, Christopher Price, Louise Robinson, Nele Demeyere, Blossom Christa Maree Stephan, Maree Stephan, Terry Quinn
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