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- Anselmino, Matteo, et al.
(författare)
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Atrial fibrillation ablation long-term ESC-EHRA EORP AFA LT registry : in-hospital and 1-year follow-up findings in Italy
- 2020
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Ingår i: Journal of Cardiovascular Medicine. - : Ovid Technologies (Wolters Kluwer Health). - 1558-2027 .- 1558-2035. ; 21:10, s. 740-748
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To report the Italian data deriving from the European Society of Cardiology-EURObservational Research Program atrial fibrillation ablation long-term registry.Methods and results: Ten Italian centers enrolled up to 50 consecutive patients undergoing atrial fibrillation ablation. Of the 318 patients included, 5 (1.6%) did not undergo catheter ablation, 1 had ablation partially done and 62 were lost at 1-year follow-up. Women were less represented (23.6%) and the median age was 60.0 years. A total of 195 patients (62.3%) suffered paroxysmal atrial fibrillation, whereas only 9 (2.9%) had long-standing persistent atrial fibrillation. Most Italian patients (92.3%) were symptomatic but suffering fewer symptomatic events than patients enrolled in other countries (median of two events in the month preceding the ablation vs. three, respectively; P<0.0001). The main finding of the study is that the success rate at 1 year, with and without antiarrhythmic drugs, was 76.4%, consistently with other participating countries (73.4%). This result was obtained however, with a significantly lower prevalence of 1-year adverse events (7.3 vs. 16.6%, P<0.0001). Procedure duration and fluoroscopy total time resulted as being shorter in Italy (145 vs. 160, P=0.0005 and 16.9 vs. 20.0 min, P=0.0018, respectively); however, the radiation dose per BSA was greater (37.5 vs. 26.0mGy/cm(2), P=0.0022).Conclusion: The demographic characteristics of patients undergoing atrial fibrillation ablation are similar to those reported in other countries. The success rate in Italy is consistent with those in other countries, whereas the complications rate is lower.
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| 2. |
- D'Ascenzo, Fabrizio, et al.
(författare)
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Incidence and predictors of coronary stent thrombosis : Evidence from an international collaborative meta-analysis including 30 studies, 221,066 patients, and 4276 thromboses
- 2013
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Ingår i: International Journal of Cardiology. - : Elsevier BV. - 0167-5273 .- 1874-1754. ; 167:2, s. 575-584
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND:Stent thrombosis remains among the most feared complications of percutaneous coronary intervention (PCI) with stenting. However, data on its incidence and predictors are sparse and conflicting. We thus aimed to perform a collaborative systematic review on incidence and predictors of stent thrombosis.METHODS: PubMed was systematically searched for eligible studies from the drug-eluting stent (DES) era (1/2002-12/2010). Studies were selected if including ≥2000 patients undergoing stenting or reporting on ≥25 thromboses. Study features, patient characteristics, and incidence of stent thrombosis were abstracted and pooled, when appropriate, with random-effect methods (point estimate [95% confidence intervals]), and consistency of predictors was formally appraised.RESULTS:A total of 30 studies were identified (221,066 patients, 4276 thromboses), with DES used in 87%. After a median of 22months, definite, probable, or possible stent thrombosis had occurred in 2.4% (2.0%; 2.9%), with acute in 0.4% (0.2%; 0.6%), subacute in 1.1% (1.0%; 1.3%), late in 0.5% (0.4%; 0.6%), and very late in 0.6% (0.4%; 0.8%). Similar figures were computed for studies reporting only on DES. From a total of 47 candidate variables, definite/probable stent thrombosis was more commonly and consistently predicted by early antiplatelet therapy discontinuation, extent of coronary disease, and stent number/length, with acute coronary syndrome at admission, diabetes, smoking status, and bifurcation/ostial disease also proving frequent predictors, but less consistently.CONCLUSIONS:Despite numerous possible risk factors, the most common and consistent predictors of stent thrombosis are early antiplatelet therapy discontinuation, extent of coronary disease, and stent number/length.
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| 3. |
- Raposeiras-Roubin, Sergio, et al.
(författare)
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Development and external validation of a post-discharge bleeding risk score in patients with acute coronary syndrome : The BleeMACS score
- 2018
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Ingår i: International Journal of Cardiology. - : ELSEVIER IRELAND LTD. - 0167-5273 .- 1874-1754. ; 254, s. 10-15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Accurate 1-year bleeding risk estimation after hospital discharge for acute coronary syndrome(ACS) may help clinicians guide the type and duration of antithrombotic therapy. Currently there are no predictive models for this purpose. The aim of this study was to derive and validate a simple clinical tool for bedside risk estimation of 1-year post-discharge serious bleeding in ACS patients.Methods: The risk score was derived and internally validated in the BleeMACS (Bleeding complications in a Multicenter registry of patients discharged with diagnosis of Acute Coronary Syndrome) registry, an observational international registry involving 15,401 patients surviving admission for ACS and undergoing percutaneous coronary intervention (PCI) from 2003 to 2014, engaging 15 hospitals from 10 countries located in America, Europe and Asia. External validation was conducted in the SWEDEHEART population, with 96,239 ACS patients underwent PCI and 93,150 without PCI.Results: Seven independent predictors of bleeding were identified and included in the BleeMACS score: age, hypertension, vascular disease, history of bleeding, malignancy, creatinine and hemoglobin. The BleeMACS risk score exhibited a C-statistic value of 0.71 (95% CI 0.68-0.74) in the derivation cohort and 0.72 (95% CI 0.67-0.76) in the internal validation sample. In the SWEDEHEART external validation cohort, the C-statistic was 0.65 (95% CI 0.64-0.66) for PCI patients and 0.63 (95% CI 0.62-0.64) for non-PCI patients. The calibration was excellent in the derivation and validation cohorts.Conclusions: The BleeMACS bleeding risk score is a simple tool useful for identifying those ACS patients at higher risk of serious 1-year post-discharge bleeding.
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| 4. |
- Saglietto, Andrea, et al.
(författare)
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AFA-Recur : an ESC EORP AFA-LT registry machine-learning web calculator predicting atrial fibrillation recurrence after ablation
- 2023
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Ingår i: Europace. - : Oxford University Press. - 1099-5129 .- 1532-2092. ; 25:1, s. 92-100
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Tidskriftsartikel (refereegranskat)abstract
- Aims: Atrial fibrillation (AF) recurrence during the first year after catheter ablation remains common. Patient-specific prediction of arrhythmic recurrence would improve patient selection, and, potentially, avoid futile interventions. Available prediction algorithms, however, achieve unsatisfactory performance. Aim of the present study was to derive from ESC-EHRA Atrial Fibrillation Ablation Long-Term Registry (AFA-LT) a machine-learning scoring system based on pre-procedural, easily accessible clinical variables to predict the probability of 1-year arrhythmic recurrence after catheter ablation.Methods and results: Patients were randomly split into a training (80%) and a testing cohort (20%). Four different supervised machine-learning models (decision tree, random forest, AdaBoost, and k-nearest neighbour) were developed on the training cohort and hyperparameters were tuned using 10-fold cross validation. The model with the best discriminative performance on the testing cohort (area under the curve-AUC) was selected and underwent further optimization, including re-calibration. A total of 3128 patients were included. The random forest model showed the best performance on the testing cohort; a 19-variable version achieved good discriminative performance [AUC 0.721, 95% confidence interval (CI) 0.680-0.764], outperforming existing scores (e.g. APPLE score: AUC 0.557, 95% CI 0.506-0.607). Platt scaling was used to calibrate the model. The final calibrated model was implemented in a web calculator, freely available at http://afarec.hpc4ai.unito.ti/.Conclusion: AFA-Recur, a machine-learning-based probability score predicting 1-year risk of recurrent atrial arrhythmia after AF ablation, achieved good predictive performance, significantly better than currently available tools. The calculator, freely available online, allows patient-specific predictions, favouring tailored therapeutic approaches for the individual patient.
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