Inflammation, mitochondrial dysfunction and physical performance: a possible association in older patients with persistent atrial fibrillation-the results of a preliminary study.

BACKGROUND: Atrial fibrillation (AF) is associated with chronic inflammation, a hallmark of ageing process. The aim of this study was to determine interleukin-6 (IL-6)-associated variables, also exploring acylcarnitines, expression of mitochondrial abnormalities. METHODS: We evaluated 22 controls and 50 patients with persistent AF. IL-6 and acylcarnitines were measured with ELISA kits and mass spectrometry techniques. RESULTS: IL-6 concentration (mean: 3.9 ± 3.1 pg/mL) was lower in controls and increased in AF patients, especially with heart failure. The CHA2DS2-VASc, the MMSE and the SPPB scores were 3.8 ± 1.6, 28 ± 2 and 9.4 ± 2.1. Thirteen acylcanitines correlated with IL-6. At multivariable analysis, IL-6 was directly associated with C4-OH-a short-chain acylcarnitine, fibrinogen and alanine aminotransferase values, and with hyperuricemia. An inverse association existed with calcium concentration and SPPB score. CONCLUSIONS: In older AF patients, IL-6 correlated with acylcarnitines and lower physical performance. Alterations in energy production, reduced physical function and inflammation could contribute to frailty development.

Atrial fibrillation in older patients and artificial intelligence: a quantitative demonstration of a link with some of the geriatric multidimensional assessment tools-a preliminary report.

Atrial fibrillation (AF) associates with disability and frailty. Aim of this study was to evaluate in older AF patients, using artificial intelligence (AI), the relations between geriatric tools and daily standing and resting periods. We enrolled thirty-one > 65 years patients undergoing electrical cardioversion of AF (age: 79 ± 6 years; women: 41.9%; CHA2DS2-VASc: 3.7 ± 1.2; MMSE: 27.7 ± 2.7; GDS: 3.0 ± 2.8). The data of the first day following the procedure were analyzed using machine-learning techniques in a specifically designed cloud platform. Standing, activity, time (582 ± 139 min) was directly associated with MMSE and inversely with GDS. Sleep length was 472 ± 230 min. Light sleep, the longer resting phase, was inversely related to GDS. The Chest Effort Index, a measure of obstructive sleep apnea, grew with GDS. In conclusion, AI devices can be routinely used in improving older subjects' evaluation. A correlation exists between standing time, MMSE, and depressive symptoms. GDS associates to length and quality of sleep.