ABSTRACT
Background: The integrated approach to electrical cardioversion (EC) in atrial fibrillation (AF) is complex; candidates can resolve spontaneously while waiting for EC, and post-cardioversion recurrence is high. Thus, it is especially interesting to avoid the programming of EC in patients who would restore sinus rhythm (SR) spontaneously or present early recurrence. We have analyzed the whole elective EC of the AF process using machine-learning (ML) in order to enable a more realistic and detailed simulation of the patient flow for decision making purposes. Methods: The dataset consisted of electronic health records (EHRs) from 429 consecutive AF patients referred for EC. For analysis of the patient outcome, we considered five pathways according to restoring and maintaining SR: (i) spontaneous SR restoration, (ii) pharmacologic-cardioversion, (iii) direct-current cardioversion, (iv) 6-month AF recurrence, and (v) 6-month rhythm control. We applied ML classifiers for predicting outcomes at each pathway and compared them with the CHA2DS2-VASc and HATCH scores. Results: With the exception of pathway (iii), all ML models achieved improvements in comparison with CHA2DS2-VASc or HATCH scores (p < 0.01). Compared to the most competitive score, the area under the ROC curve (AUC-ROC) was: 0.80 vs. 0.66 for predicting (i); 0.71 vs. 0.55 for (ii); 0.64 vs. 0.52 for (iv); and 0.66 vs. 0.51 for (v). For a threshold considered optimal, the empirical net reclassification index was: +7.8%, +47.2%, +28.2%, and +34.3% in favor of our ML models for predicting outcomes for pathways (i), (ii), (iv), and (v), respectively. As an example tool of generalizability of ML models, we deployed our algorithms in an open-source calculator, where the model would personalize predictions. Conclusions: An ML model improves the accuracy of restoring and maintaining SR predictions over current discriminators. The proposed approach enables a detailed simulation of the patient flow through personalized predictions.
ABSTRACT
BACKGROUND: Macitentan is the latest endothelin-receptor antagonist (ERA) approved for the treatment of pulmonary arterial hypertension (PAH), presenting enhanced properties over previous ERAs. OBJECTIVE: We describe the clinical and echocardiographic evolution of patients with PAH who started macitentan after discontinuing bosentan/ambrisentan. METHODS: This was a retrospective series of patients with different etiologies who started macitentan after the suspension of other ERAs under routine clinical practice at five Spanish hospitals. World Health Organization functional class (WHO-FC), 6-min walk distance (6MWD), levels of N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and cardiac imaging data were collected and described at baseline (before macitentan initiation) and after 3, 6, and 12 months, when available. RESULTS: In total, 12 patients (ten women; mean age 65.63 ± 13.27 years) were observed. At baseline, most patients were receiving concomitant PAH medications, and five patients were classed as WHO-FC III. After 3 months of macitentan treatment, WHO-FC had improved in four patients, 6MWD increased in eight patients, and NT-proBNP levels and right atrial area were lowered in seven and eight patients, respectively. Similar results were observed after 6 and 12 months. Macitentan was well-tolerated, with no PAH hospitalizations, septostomies, transplants, or deaths registered. CONCLUSIONS: Our results suggest that switching to macitentan in patients with PAH who discontinued bosentan/ambrisentan was well-tolerated and effective. Further studies are needed to confirm these observations.
