Cardiovasc Diabetol

Lower-extremity arterial disease (LEAD) is a major endemic disease with an alarming increased prevalence worldwide. It is a common and severe condition with excess risk of major cardiovascular events and death. It also leads to a high rate of lower-limb adverse events and non-traumatic amputation. The American Diabetes Association recommends a widespread medical history and clinical examination to screen for LEAD. The ankle brachial index (ABI) is the first non-invasive tool recommended to diagnose LEAD although its variable performance in patients with diabetes. The performance of ABI is particularly affected by the presence of peripheral neuropathy, medial arterial calcification, and incompressible arteries. There is no strong evidence today to support an alternative test for LEAD diagnosis in these conditions. The management of LEAD requires a strict control of cardiovascular risk factors including diabetes, hypertension, and dyslipidaemia. The benefit of intensive versus standard glucose control on the risk of LEAD has not been clearly established. Antihypertensive, lipid-lowering, and antiplatelet agents are obviously worthfull to reduce major cardiovascular adverse events, but few randomised controlled trials (RCTs) have evaluated the benefits of these treatments in terms of LEAD and its related adverse events. Smoking cessation, physical activity, supervised walking rehabilitation and healthy diet are also crucial in LEAD management. Several advances have been achieved in endovascular and surgical revascularization procedures, with obvious improvement in LEAD management. The revascularization strategy should take into account several factors including anatomical localizations of lesions, medical history of each patients and operator experience. Further studies, especially RCTs, are needed to evaluate the interest of different therapeutic strategies on the occurrence and progression of LEAD and its related adverse events in patients with diabetes

Spatial investigation of congenital malformations in Reunion Island (2008-2012)

International audienceBackground: Reunion Island is a French territory located in the south- western Indian Ocean. The Reunion Registry of congenital malformations is in charge of monitoring cases. Overall prevalence (289 cases per 10,000 births) is close to the average reported by mainland French registries (315 cases). However, the prevalence of spina bifida is almost twice (10 cases per 10,000 births) the one reported in mainland France (5 cases). This study aims to describe the spatial distribution of different birth defects and identifying clusters.Methods: The analysis specifically tackles three groups being potentially related to environmental exposure. Each case recorded between 2008 and 2012 was geolocated according to its home address: 492 cases of congenital heart defects, 108 cases of cleft lip and palate and 69 cases of spina bifida. Four statistical methods were applied at different administrative scales: Standardized Prevalence Ratio (SPR), Hierarchical Clus- ter Analysis (HCA), Kulldorff method and Geographic epicenter method.Results: The resulting clusters differ depending on the method. Combining the observation at different administrative scales helps to identify the most affected areas for each pathology.Conclusions: These initial observations allow considering case-control studies to identify exposure factors in the most affected areas, including environmental, socio-economic and healthcare factors

Mise en place d'une surveillance spatialisée des malformations congénitales à La Réunion : choix méthodologiques

International audienceIntroduction – The Registry of Congenital Malformations (CM) in Reunion Island (REMACOR) oversees the surveillance of CM for public health and research purposes. This surveillance consists of the exhaustive collec- tion of cases, and temporal analysis of CM. Since 2013, REMACOR has retrospectively geolocalized the data to allow their spatial analysis and the detection of health signals the methodology of which is presented hereunder.Materials and methods – Each case is geolocated according to the mother’s address, using the reference address databases. Birth-related prevalence is then calculated by aggregating cases according to the different administrative scales. The choice of the suitable scale is determined using a Poisson test that estimates the minimum number of births required to perform the analysis in a statistically signi cant manner, and then a compromise between this representativeness of information, data completeness and spatial resolution.Results – 95% of the cases could be geolocalized. Different cluster detection methods are used to identify the most affected areas. Finally, clusters detected at different scales are nally intersected to calculate an index of belonging to 1, 2 or 3 scales.Discussion and conclusion – The spatialized database set up now allows REMACOR to consider the spatial heterogeneity of the distribution of the most frequent CM in order to inform public health stakeholders.Introduction: Le Registre des malformations congénitales de La Réunion (Remacor) assure la surveillance de ces pathologies à des fins de santé publique et de recherche. Cette surveillance consiste en un recueil exhaustif des cas et en l'analyse temporelle de leur survenue. Afin de permettre leur analyse spatiale et la détection de signaux sanitaires, le Remacor a géocodé rétroactivement les données et mis en place une surveillance spatialisée, dont les choix méthodologiques sont présentés ici.Matériel et méthodes: Chaque cas est géolocalisé conformément à l'adresse de la mère. Les prévalences relatives aux naissances sont ensuite calculées par agrégation des cas selon les différentes échelles administratives. Le choix de l'échelle est déterminé à l'aide d'un test de Poisson qui permet d'estimer le nombre de naissances minimum nécessaire pour réaliser l'analyse de manière statistiquement significative, puis d'un compromis entre cette significativité de l'information, la complétude des données et la résolution spatiale.Résultats: Il a été possible de géolocaliser 95% des cas. Différentes méthodes de détection d'agrégats de cas ont été utilisées afin de repérer les zones les plus touchées. Enfin, les agrégats détectés à différentes échelles ont été intersectés pour calculer un indice d'appartenance à 1, 2 ou 3 échelles.Discussion et conclusion: La base de données spatialisée mise en place permet aujourd'hui au Remacor de prendre en compte l'hétérogénéité spatiale de la distribution des malformations congénitales les plus fréquentes pour informer les acteurs de la santé publique