Abstract
BACKGROUND: Delirium is a mental condition defined as fluctuating disturbances in attention, awareness, and cognition. It is often seen in older, hospitalized patients and is currently hard to predict, with long- and short-term outcomes being detrimental to patients. METHODS: We leveraged electronic health records (EHR) to identify 7492 UCSF patients and 19,417 UC health system patients with an inpatient delirium diagnosis and the same number of control patients without delirium. We used the Fisher's exact test with multiple corrections for the association studies and the Cox regression model for the longitudinal analyses. RESULTS: Here we show significant associations between comorbidities or laboratory values and an inpatient delirium diagnosis, including metabolic abnormalities and psychiatric diagnoses. Some associations are sex-specific, including dementia subtypes and infections. We further explore the associations with anemia and bipolar disorder by conducting longitudinal analyses from the time of first diagnosis to development of delirium, demonstrating a significant relationship across time. Finally, we show that an inpatient delirium diagnosis leads to increased risk of mortality. CONCLUSIONS: These results demonstrate the powerful application of the EHR to shed insights into prior diagnoses and laboratory values that could help predict development of inpatient delirium and the importance of sex when making these assessments.