Atrial Fibrillation Risk Assessment after Embolic Stroke of Undetermined Source.

OBJECTIVE: Approximately 20% of strokes are embolic strokes of undetermined source (ESUS). Undetected atrial fibrillation (AF) remains an important cause. Yet, oral anticoagulation in unselected ESUS patients failed in secondary stroke prevention. Guidance on effective AF detection is lacking. Here, we introduce a novel, non-invasive AF risk assessment after ESUS. METHODS: Catch-Up ESUS is an investigator-initiated, observational cohort study conducted between 2018 and 2019 at the Munich University Hospital. Besides clinical characteristics, patients received ≥72 h digital electrocardiogram recordings to generate the rhythm irregularity burden. Uni- and multivariable regression models predicted the primary endpoint of incident AF, ascertained by standardized follow-up including implantable cardiac monitors. Predictors included the novel rhythm irregularity burden constructed from digital electrocardiogram recordings. We independently validated our model in ESUS patients from the University Hospital Tübingen, Germany. RESULTS: A total of 297 ESUS patients were followed for 15.6 ± 7.6 months. Incident AF (46 patients, 15.4%) occurred after a median of 105 days (25th to 75th percentile 31-33 days). Secondary outcomes were recurrent stroke in 7.7% and death in 6.1%. Multivariable-adjusted analyses identified the rhythm irregularity burden as the strongest AF-predictor (hazard ratio 3.12, 95% confidence interval 1.62-5.80, p < 0001) while accounting for the known risk factors age, CHA2 DS2 -VASc-Score, and NT-proBNP. Independent validation confirmed the rhythm irregularity burden as the most significant AF-predictor (hazard ratio 2.20, 95% confidence interval 1.45-3.33, p < 0001). INTERPRETATION: The novel, non-invasive, electrocardiogram-based rhythm irregularity burden may help adjudicating AF risk after ESUS, and subsequently guide AF-detection after ESUS. Clinical trials need to clarify if high-AF risk patients benefit from tailored secondary stroke prevention. ANN NEUROL 2023;93:479-488.

Neuronal injury biomarkers for assessment of the individual cognitive reserve in clinically suspected Alzheimer's disease.

OBJECTIVES: Many predictive or influencing factors have emerged in investigations of the cognitive reserve model of patients with Alzheimer's disease (AD). For example, neuronal injury, which correlates with cognitive decline in AD, can be assessed by [18F]-fluorodeoxyglucose positron-emission-tomography (FDG-PET), structural magnetic resonance imaging (MRI) and total tau in cerebrospinal fluid (CSFt-tau), all according to the A/T/N-classification. The aim of this study was to calculate residual cognitive performance based on neuronal injury biomarkers as a surrogate of cognitive reserve, and to test the predictive value of this index for the individual clinical course. METHODS: 110 initially mild cognitive impaired and demented subjects (age 71 ±â€¯8 years) with a final diagnosis of AD dementia were assessed at baseline by clinical mini-mental-state-examination (MMSE), FDG-PET, MRI and CSFt-tau. All neuronal injury markers were tested for an association with clinical MMSE and the resulting residuals were correlated with years of education. We used multiple regression analysis to calculate the expected MMSE score based on neuronal injury biomarkers and covariates. The residuals of the partial correlation for each biomarker and the predicted residualized memory function were correlated with individual cognitive changes measured during clinical follow-up (27 ±â€¯13 months). RESULTS: FDG-PET correlated highly with clinical MMSE (R = -0.49, p < .01), whereas hippocampal atrophy to MRI (R = -0.15, p = .14) and CSFt-tau (R = -0.12, p = .22) showed only weak correlations. Residuals of all neuronal injury biomarker regressions correlated significantly with education level, indicating them to be surrogates of cognitive reserve. A positive residual was associated with faster cognitive deterioration at follow-up for the residuals of stand-alone FDG-PET (R = -0.36, p = .01) and the combined residualized memory function model (R = -0.35, p = .02). CONCLUSIONS: These findings suggest that subjects with higher cognitive reserve had accumulated more pathology, which subsequently caused a faster cognitive decline over time. Together with previous findings suggesting that higher reserve is associated with slower cognitive decline, we propose a biphasic reserve effect, with an initially protective phase followed by more rapid decompensation once the protection is overwhelmed.