Key Points Question How does an artificial intelligence (AI)–enabled decision aid generated using patient-reported outcome measurements compare with education only on decision quality, patient satisfaction, and functional outcomes among individuals with knee osteoarthritis considering total knee replacement? Findings This randomized clinical trial of 129 patients demonstrated statistically significant improvement in decision quality, level of shared decision-making, patient satisfaction, and functional outcomes in patients using an AI-enabled decision aid. Meaning These findings suggest that AI-enabled decision aids incorporating patient-reported outcome measurement data provide a personalized, data-driven approach to shared decision-making for the surgical management of knee osteoarthritis.

Cerebrospinal fluid (CSF) measures of Ab and tau, Pittsburgh Compound B (PIB) imaging and hippocampal atrophy are promising Alzheimer’s disease biomarkers yet the associations between them are not known. We applied a validated, automated hippocampal labeling method and 3D radial distance mapping to the 1.5T structural magnetic resonance imaging (MRI) data of 388 ADNI subjects with baseline CSF Ab42, total tau (t-tau) and phosphorylated tau (p-tau181) and 98 subjects with positron emission tomography (PET) imaging using PIB. We used linear regression to investigate associations between hippocampal atrophy and average cortical, parietal and precuneal PIB standardized uptake value ratio (SUVR) and CSF Ab42, t-tau, p-tau181, t-tau/Ab42 and p-tau181/Ab42. All CSF measures showed significant associations with hippocampal volume and radial distance in the pooled sample. Strongest correlations were seen for p-tau181, followed by p-tau181/Ab42 ratio, t-tau/Ab42 ratio, t-tau and Ab42. p-tau181 showed stronger correlation in ApoE4 carriers, while t-tau showed stronger correlation in ApoE4 noncarriers. Of the 3 PIB measures the precuneal SUVR showed strongest associations with hippocampal atrophy.

Level II, prognostic study.