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Congratulations to our student, Dina Farran
May 22, 2024
View Dina's Abstract
We are delighted to share that one of our EPSRC DRIVE-Health CDT students and PhD candidate at the IoPPN, Dina Farran, has been awarded 1st prize presentation at the recent Royal College of Psychiatrists Faculty of Liaison Psychiatry annual conference earlier this month. Dina is working under the supervision of Professor Fiona Gaughran and Professor Mark Ashworth and is about to submit her thesis at the end of this month.
In the presentation, Dina summarised her PhD project consisting of a literature review, 2 observational studies, an intervention and 2 qualitative studies. Dina provides further detail below.
Background
Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness.
Methods
(a) Conducted a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population.
(b) Evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital.
(c) Identified the recorded rates of OAC prescription among people with AF and various mental illnesses and evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust.
(d) Implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Record to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM.
(e) Assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspective of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention).
Results
(a) People with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors.
(b) Among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI patients to be prescribed any OAC, particularly warfarin (but not DOACs). However, there was no evidence of a significant difference between the two groups since 2019.
(c) Adjusting for age, sex, stroke and bleeding risk scores, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders or common mental disorders. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions and activities of daily living impairment.
(d) Clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes and refer patients at high risk of stroke to OAC clinics.
(e) Clinicians reported that the eCDSS saved time, prompted them towards guidelines, boosted their confidence, and identified patients at risk. Perceived barriers to using the tool included low admission rate of AF cases, low or insufficient visibility of the alert/awareness of the tool, and impact of the eCDSS on workload.
Conclusions
This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes, using electronic health records. This has the potential to improve health outcomes and therefore patients' quality of life.
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We’re thrilled to announce that John Jumper, PhD , will kick-off our 2024/2025 Seminar Series with his talk, "Extending AlphaFold to make predictions across the universe of biomolecular interactions" . John is one of the key pioneers behind the development of Google’s DeepMind AlphaFold - an artificial intelligence model to predict protein structures from their amino acid sequence with high accuracy. This in-person event promises to be an incredible opportunity to hear from one of the foremost innovators in AI and biology. Seminar Series Event: Extending AlphaFold to make predictions across the universe of biomolecular interactions Date and Time: 14:00 – 15.00, Thursday 10 October 2024 Location: The Council Room, 2nd floor, The King’s Building, Strand Campus Registration: Limited to EPSRC DRIVE-Health students in the first instance. Please email drive-health-cdt@kcl.ac.uk to check availability. Abstract: The high accuracy of AlphaFold 2 in predicting protein structures and protein-protein interactions raises the question of how to extend the success of AlphaFold to general biomolecular modeling, including protein-nucleic and protein-small molecule structure predictions as well as the effects of post-translational modification. In this talk, I will discuss our latest work on AlphaFold 3 to develop a single deep learning system that makes accurate predictions across these interaction types, as well as examine some of the remaining challenges in predicting the universe of biologically-relevant protein interactions.
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