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Epigenetics Biomarker of Post Operative Delirium and Long Term Cognitive Decline among Elderly Dementia Patients

Dr. Gen Shinozaki from Stanford Psychiatry has received a grant from the National Institute on Aging to investigate epigenetic biomarkers related to post-operative delirium and long-term cognitive decline in elderly patients, both with and without dementia. Delirium, particularly common after surgery in elderly patients, is a serious condition that can lead to cognitive deterioration and even death, especially for those with Alzheimer’s or dementia. Despite its severity, predicting and detecting delirium remains a major challenge.

The focus of this study is on understanding how epigenetic changes, particularly through DNA methylation, contribute to delirium. DNA methylation is an epigenetic modification that can be influenced by environmental factors and aging, impacting how genes are expressed. The study will examine these molecular changes to explore how they might be linked to the onset of delirium after surgery. The research involves a large cohort of elderly patients undergoing hip fracture surgery, which carries a high risk of delirium. By comparing the DNA methylation profiles of patients who develop delirium with those who do not, the team aims to identify specific epigenetic markers that could serve as early indicators of delirium risk.

The project is a collaboration with Dr. Michael Snyder (Genetics), Dr. VJ Periyakoil (Geriatrics), Dr. Katrin Andreasson (Neurology), and Dr. Brice Gaudilliere (Anesthesiology) at Stanford, along with colleagues from Vanderbilt University and the University of Iowa.

According to Dr. Shinozaki, understanding these epigenetic changes could offer new ways to predict, prevent, and treat delirium, improving outcomes for elderly patients, especially those with dementia.

Dr. Shinozaki’s broader work includes developing biomarkers and a bispectral EEG device proven effective in detecting delirium in over 1,000 inpatients. He recently received the Wayne Katon Research Award from Academy of Consultation Liaison Psychaitry for these accomplishments. His recent publications, such as studies on epigenetic signals and immune-related DNA methylation changes associated with delirium, further support his ongoing research.

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Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding"

Julia Adler-Milstein, PhD1; Jonathan H. Chen, MD, PhD; Gurpreet Dhaliwal, MD

Improving the diagnostic process is a quality and safety priority.With the digitization of health records and rapid expansion of health data, the cognitive demand on the diagnostician has increased. The use of artificial intelligence (AI) to assist human cognition has the potential to reduce this demand and associated diagnostic errors. However, current AI tools have not realized this potential, due in part to the long-standing focus of these tools on predicting final diagnostic labels instead of helping clinicians navigate the dynamic refinement process of diagnosis. This Viewpoint highlights the importance of shifting the role of diagnostic AI from predicting labels to “wayfinding” (interpreting context and providing cues that guide the diagnostician).