Improving scientific rigour in conservation evaluations and a plea deal for transparency on potential biases

The delivery of rigorous and unbiased evidence on the effects of interventions lay at the heart of the scientific method. Here we examine scientific papers evaluating agri-environment schemes, the principal instrument to mitigate farmland biodiversity declines worldwide. Despite previous warnings about rudimentary study designs in this field, we found that the majority of studies published between 2008 and 2017 still lack robust study designs to strictly evaluate intervention effects. Potential sources of bias that arise from the correlative nature are rarely mentioned, and results are still promoted by using a causal language. This lack of robust study designs likely results from poor integration of research and policy, while the erroneous use of causal language and an unwillingness to discuss bias may stem from publication pressures. We conclude that scientific reporting and discussion of study limitations in intervention research must improve and propose some practices toward this goal

Validation of a Whole Heart Segmentation from Computed Tomography Imaging Using a Deep-Learning Approach

International audienceThe aim of this study is to develop an automated deep-learning-based whole heart segmentation of ECG-gated computed tomography data. After 21 exclusions, CT acquired before transcatheter aortic valve implantation in 71 patients were reviewed and randomly split in a training (n = 55 patients), validation (n = 8 patients), and a test set (n = 8 patients). A fully automatic deep-learning method combining two convolutional neural networks performed segmentation of 10 cardiovascular structures, which was compared with the manually segmented reference by the Dice index. Correlations and agreement between myocardial volumes and mass were assessed. The algorithm demonstrated high accuracy (Dice score = 0.920; interquartile range: 0.906-0.925) and a low computing time (13.4 s, range 11.9-14.9). Correlations and agreement of volumes and mass were satisfactory for most structures. Six of ten structures were well segmented. Deep-learning-based method allowed automated WHS from ECG-gated CT data with a high accuracy. Challenges remain to improve right-sided structures segmentation and achieve daily clinical application

Management of aortic valve replacement according to the Gradient across symptomatic aortic valve stenosis and its prognostic impact

International audienceBackground - Treatment strategy for low-gradient (LG) aortic stenosis (AS) remains an unresolved issue. The presence of a low aortic gradient and preserved left ventricular ejection fraction (LVEF) might lead toward the underestimation of aortic stenosis severity and a more conservative management. We sought (a) to describe the nature and timing of intervention according to flow/gradient subgroups in patibents with LG-AS, (2) to determine the factors associated with the decision to intervene, and (c) to describe prognosis. Methods and results - One hundred and ten patients prospectively included in this study underwent a standardized clinical and imaging evaluation at inclusion and at 1-year follow-up. According to aortic flow, gradient and LVEF, patients were divided into 4 groups: LG-normal flow [n = 27], LG-low flow-low LVEF [n = 27], LG-low flow-normal LVEF [n = 16], and high gradient (HG) [n = 40]). 73% of patients underwent AVR 86 ± 59 days after the initial assessment. The HG subgroup had significantly higher intervention rates (P < .001). In multivariable analysis, four parameters were associated with the AVR: aortic gradient (HR 1.52 [1.10-2.11], P = .012), LVEF (HR 0.58 [0.40-0.85], P = .006), atrial fibrillation (HR 0.43 [0.021-0.87], P = .019), and NT-proBNP (HR 0.92[0.86-0.98), P = .008]. Patients operated earlier had better outcomes than those having a delayed AVR (P = .042). LG-AS patients had worse outcomes than HG-AS patients (P < .001). Conclusion - Compared to HG-AS, LG-AS is less likely to benefit from an AVR and had a significantly worse outcome. Further interventional studies are needed to investigate the timing of AVR in these patients

Therapie

Les Ateliers de Giens avaient consacré en 2018 une table ronde à l’intelligence artificielle (IA) et conduit ses experts à confirmer l’apport potentiel et le bénéfice théorique que représente l’IA en recherche clinique et en matière d’amélioration de l’efficience de soins. La table ronde de 2022 s’inscrit dans la continuité de cette réflexion sur l’IA et l’automatisation intelligente (AI) en la ciblant sur son apport en pharmacovigilance et les applications et tâches qu’elles pourraient optimiser afin de préserver et de renforcer l’expertise médicale et pharmacologique en pharmacovigilance. En effet, l’évolution du travail en pharmacovigilance est caractérisée par de nombreuses tâches à faible valeur ajoutée, une volumétrie croissante des déclarations de pharmacovigilance, la rareté des personnels médicaux ayant une expertise en pharmacologique clinique et en pharmacovigilance et des ressources humaines qui ne sont pas et ne seront pas en adéquation avec l’évolution constatée. Tous ces paramètres concourent à une embolisation du système de pharmacovigilance avec le risque de passer à côté de sa mission première qui est d’identifier et de caractériser un risque, voire une alerte sanitaire, sur un médicament. Les participants de la table ronde (représentants des centres régionaux de pharmacovigilance (CRPV), de l’Agence nationale de sécurité du médicament et des produits de santé (ANSM), des patients, de l’industrie du médicament ou encore de start-ups travaillant dans le développement de l’IA dans le domaine du médicament) ont partagé leurs expériences, leurs projets pilotes et leurs attentes sur les potentialités attendues, théoriques ou avérées, de l’IA et l’AI. Ce travail a permis de dégager les besoins et les enjeux réels que représentent, ou pas, l’IA ou l’AI dans les modes d’organisation actuelles ou futures de la pharmacovigilance. Cette démarche a permis l’élaboration d’une matrice SWOT (forces, faiblesses, opportunités, menaces), socle de réflexion pour identifier des points critiques et envisager quatre principales recommandations : (1) préserver et développer l’expertise métier en pharmacovigilance (incluant la partie recherche et développement en méthodes) avec l’intégration de nouvelles technologies ; (2) améliorer la qualité des déclarations en pharmacovigilance ; (3) adapter les moyens techniques et réglementaires ; (4) implémenter une stratégie de développements des outils AI et IA au service de l’expertise

Early Ventricular Arrhythmias After LVAD Implantation Is the Strongest Predictor of 30-Day Post-Operative Mortality

International audienceObjectives - This study aimed to evaluate incidence, clinical significance, and predictors of early ventricular arrhythmias (VAs) in left ventricular assist device (LVAD) recipients. Background - LVAD implantation is increasingly used in patients with end-stage heart failure. Early VAs may occur during the 30-day post-operative period, but many questions remain unanswered regarding their incidence and clinical impact. Methods - This observational study was conducted in 19 centers between 2006 and 2016. Early VAs were defined as sustained ventricular tachycardia and/or ventricular fibrillation occurring <30 days post-LVAD implantation and requiring appropriate implantable cardioverter-defibrillator therapy, external electrical shock, or medical therapy. Results - A total of 652 patients (median age: 59.8 years; left ventricular ejection fraction: 20.7 ± 7.4%; HeartMate 2: 72.8%; HeartWare: 19.5%; Jarvik 2000: 7.7%) were included in the analysis. Early VAs occurred in 162 patients (24.8%), most frequently during the first week after LVAD implantation. Multivariable analysis identified history of VAs prior to LVAD and any combined surgery with LVAD as 2 predictors of early VAs. The occurrence of early VAs with electrical storm was the strongest predictor of 30-day post-operative mortality, associated with a 7-fold increase of 30-day mortality. However, in patients discharged alive from hospital, occurrence of early VAs did not influence long-term survival. Conclusions - Early VAs are common after LVAD implantation and increase 30-day post-operative mortality, without affecting long-term survival. Further studies will be needed to analyze whether pre- or pre-operative ablation of VAs may improve post-operative outcomes. (Determination of Risk Factors of Ventricular Arrhythmias After Implantation of Continuous Flow Left Ventricular Assist Device With Continuous Flow Left Ventricular Assist Device [ASSIST-ICD]; NCT02873169)

Temporal Trends in Transcatheter Aortic Valve Replacement in France: FRANCE 2 to FRANCE TAVI

International audienceBackground - Transcatheter aortic valve replacement (TAVR) is standard therapy for patients with severe aortic stenosis who are at high surgical risk. However, national data regarding procedural characteristics and clinical outcomes over time are limited. Objectives - The aim of this study was to assess nationwide performance trends and clinical outcomes of TAVR during a 6-year period. Methods - TAVRs performed in 48 centers across France between January 2013 and December 2015 were prospectively included in the FRANCE TAVI (French Transcatheter Aortic Valve Implantation) registry. Findings were further compared with those reported from the FRANCE 2 (French Aortic National CoreValve and Edwards 2) registry, which captured all TAVRs performed from January 2010 to January 2012 across 34 centers. Results - A total of 12,804 patients from FRANCE TAVI and 4,165 patients from FRANCE 2 were included in this analysis. The median age of patients was 84.6 years, and 49.7% were men. FRANCE TAVI participants were older but at lower surgical risk (median logistic European System for Cardiac Operative Risk Evaluation [EuroSCORE]: 15.0% vs. 18.4%; p < 0.001). More than 80% of patients in FRANCE TAVI underwent transfemoral TAVR. Transesophageal echocardiography guidance decreased from 60.7% to 32.3% of cases, whereas more recent procedures were increasingly performed in hybrid operating rooms (15.8% vs. 35.7%). Rates of Valve Academic Research Consortium-defined device success increased from 95.3% in FRANCE 2 to 96.8% in FRANCE TAVI (p < 0.001). In-hospital and 30-day mortality rates were 4.4% and 5.4%, respectively, in FRANCE TAVI compared with 8.2% and 10.1%, respectively, in FRANCE 2 (p < 0.001 for both). Stroke and potentially life-threatening complications, such as annulus rupture or aortic dissection, remained stable over time, whereas rates of cardiac tamponade and pacemaker implantation significantly increased. Conclusions - The FRANCE TAVI registry provided reassuring data regarding trends in TAVR performance in an all-comers population on a national scale. Nonetheless, given that TAVR indications are likely to expand to patients at lower surgical risk, concerns remain regarding potentially life-threatening complications and pacemaker implantation. (Registry of Aortic Valve Bioprostheses Established by Catheter [FRANCE TAVI]; NCT01777828)