Automated conduction velocity estimation based on isochronal activation of heart chambers.

BACKGROUND: Spatial differences in conduction velocity (CV) are critical for cardiac arrhythmias induction. We propose a method for an automated CV calculation to identify areas of slower conduction during cardiac arrhythmias and sinus rhythm. METHODS: Color-coded representations of the isochronal activation map using data coming from the RHYTHMIA™ Mapping System were reproduced by applying a temporal isochronal window at 20 ms. Geodesic distances of the 3D mesh were calculated using an algorithm selecting the minimum distance pathway (MDP). The CV estimation was performed considering points on the boundary of two spatially and temporally adjacent isochrones. For each of the boundary points of a given isochrone, the nearest boundary point of the consecutive isochrone was chosen, the MDP was evaluated, and a map of CV was created. The proposed method has been applied to a population of 29 patients. RESULTS: In all cases of perimitral atrial flutter (16 pts out of 29 (55%)), areas with significantly low CV (< 30 cm/s) were found. Half of the cases present regions with low CV located in the anterior wall. No case with low CV at the so-called LA isthmus was observed. Right atrial maps during common atrial flutters showed low CV areas mainly located in the inferior inter-atrial septum. No areas of low CV were observed in subjects without a history of atrial arrhythmia while pts affected by paroxysmal AF showed areas with a limited extension of low CV. CONCLUSIONS: The proposed software for automated CV estimation allows the identification of low CV areas, potentially helping electrophysiologists to plan the ablation strategy.

[Population segmentation as a tool for planning community healthcare networks: the key role of social and health information systems.] / La stratificazione della popolazione come strumento per rimodulare la rete assistenziale sul territorio: il ruolo determinante dei sistemi informativi socio-sanitari.

INTRODUCTION: Due to the ongoing demographic and epidemiological changes, today stakeholders need to have available information, based on population stratification, in order to plan the most suitable organizational model to meet the population health needs. METHODS: The legally adult population assisted and resident in Lazio Region on 31/12/2019 was equally and casually divided in two samples: the training sample (to define the model) and the validation sample (to measure model performances). On the base of the more complex model of Lazio Region, three population strata were defined: multi-chronic population, multi-chronic population with a high clinical complexity, multi-chronic population with socioeconomic vulnerability. Hospital discharge records were identified in the previous five years prior to 31/12/2019. Through appropriate classification models, it was evaluated the level with which the simplified system "from SDO" is able to approximate the more complex algorithm developed by the Lazio Region. RESULTS: Model performances, which has examined only information "from SDO", results inadequate. In fact, the Positive Predictive Value (PVV) results equal to 46.3%, 16.3% and 30.3%, respectively for the three analyzed strata. DISCUSSION: This study demonstrated that using the hospital system as the only Health Information System reduces the possibility to stratify and predict population health needs. For this reason, the improvement of the completeness and of the quality of data from different social and health information systems and their interconnection, represent the essential starting point. In addition, updating record track is needed to simplify the workload of compilers and improve data availability. These actions must also be accompanied by supportive interventions by central bodies for the regions that show the greatest weaknesses, as well as training actions that improve the level of knowledge of compilers.