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4 raisons identifiées
Plateau technique de référence
Assistance publique – Hôpitaux de Paris (APHP) — équipements et expertise pointus pour les cas complexes
Praticien-chercheur
8 articles scientifiques publiés — formation continue solide
Disponibilité géographique
4 lieux d'exercice — choisissez celui qui vous arrange
Délais de RDV courts dans la région
146.3 rhumatos / 100 000 hab. — département bien doté
✨ Génération du profil synthétique IA en cours…
Indicateurs publics agrégés sur 250 M+ d'œuvres scientifiques (OpenAlex, PubMed). Traduits ici en langage patient.
Influence scientifique
Données ANS publiques (Licence Ouverte 2.0) · Enrichissements MonRhumato 100 % opt-in · Toute personne référencée peut demander la suppression ou la rectification.
3
3 articles ont été cités au moins 3fois par d'autres chercheurs — preuve que ses travaux sont repris par la communauté médicale.
h-index
Total citations reçues
77
Nombre de fois où d'autres équipes ont mentionné ses publications dans leurs propres travaux.
Publications totales
12
Articles, revues et chapitres référencés dans les bases académiques internationales.
Articles influents
3
Publications ayant marqué leur domaine — chacune citée au moins 10 fois par d'autres chercheurs.
i10-index
Thématiques principales
Source : OpenAlex (CC0, OurResearch). Indicateurs académiques agrégés sur 250 M+ d'œuvres.
Articles déposés en accès libre sur l'archive ouverte des universités françaises (HAL) — gage d'activité de recherche en France.
Source : HAL — archive ouverte CCSD/CNRS (couvre articles, chapitres EMC, communications congrès, thèses).
CABINET DU DR AURELIEN HAY
44 RUE DES CARMES, 54000 NANCY
GHU APHP CUP SITE HOTEL DIEU
1 PL DU PARVIS DE NOTRE DAME, 75181 PARIS CEDEX 04
CLINIQUE SAINT ANDRE
102 AV JEAN JAURES, 54501 VANDOEUVRE LES NANCY CEDEX
Secteur de conventionnement non disponible (médecin hospitalier ou non présent dans l'Annuaire santé CNAM des libéraux conventionnés).
Lien Doctolib = recherche Google site:doctolib.fr (le 1er résultat est presque toujours le profil correct s'il existe).
Journal of medical Internet research · 2020
Background Web-based self-care interventions have the potential to reduce health inequalities by removing barriers to access to health care. However, there is a lack of evidence about the equalizing effects of these interventions on chronic conditions. Objective This study investigated the differences in the effectiveness of web-based behavioral change interventions for the self-care of high burden chronic health conditions (eg, asthma, chronic obstructive pulmonary disease [COPD], diabetes, and osteoarthritis) across socioeconomic and cultural groups. Methods A systematic review was conducted, following Cochrane review guidelines. We conducted searches in Ovid Medical Literature Analysis and Retrieval System Online and Cumulative Index to Nursing and Allied Health Literature databases. Studies with any quantitative design were included (published between January 1, 2006, and February 20, 2019) if they investigated web-based self-care interventions targeting asthma, COPD, diabetes, and osteoarthritis; were conducted in any high-income country; and reported variations in health, behavior, or psychosocial outcomes across social groups. Study outcomes were investigated for heterogeneity, and the possibility of a meta-analysis was explored. A narrative synthesis was provided together with a novel figure that was developed for this review, displaying heterogeneous outcomes. Results Overall, 7346 records were screened and 18 studies were included, most of which had a high or critical risk of bias. Important study features and essential data were often not reported. The meta-analysis was not possible due to the heterogeneity of outcomes. There was evidence that intervention effectiveness was modified by participants’ social characteristics. Minority ethnic groups were found to benefit more from interventions than majority ethnic groups. Single studies with variable quality showed that those with higher education, who were employed, and adolescents with divorced parents benefited more from interventions. The evidence for differences by age, gender, and health literacy was conflicting (eg, in some instances, older people benefited more, and in others, younger people benefited more). There was no evidence of differences in income, numeracy, or household size. Conclusions There was evidence that web-based self-care interventions for chronic conditions can be advantageous for some social groups (ie, minority ethnic groups, adolescents with divorced parents) and disadvantageous for other (ie, low education, unemployed) social groups who have historically experienced health inequity. However, these findings should be treated with caution as most of the evidence came from a small number of low-quality studies. The findings for gender and health literacy were mixed across studies on diabetes, and the findings for age were mixed across studies on asthma, COPD, and diabetes. There was no evidence that income, numeracy, or the number of people living in the household modified intervention effectiveness. We conclude that there appear to be interaction effects, which warrant exploration in future research, and recommend a priori consideration of the predicted interaction effects. Trial Registration PROSPERO CRD42017056163; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=56163
Health technology assessment (Winchester, England) · 2022
BackgroundCoeliac disease is an autoimmune disorder triggered by ingesting gluten. It affects approximately 1% of the UK population, but only one in three people is thought to have a diagnosis. Untreated coeliac disease may lead to malnutrition, anaemia, osteoporosis and lymphoma.ObjectivesThe objectives were to define at-risk groups and determine the cost-effectiveness of active case-finding strategies in primary care.Design(1) Systematic review of the accuracy of potential diagnostic indicators for coeliac disease. (2) Routine data analysis to develop prediction models for identification of people who may benefit from testing for coeliac disease. (3) Systematic review of the accuracy of diagnostic tests for coeliac disease. (4) Systematic review of the accuracy of genetic tests for coeliac disease (literature search conducted in April 2021). (5) Online survey to identify diagnostic thresholds for testing, starting treatment and referral for biopsy. (6) Economic modelling to identify the cost-effectiveness of different active case-finding strategies, informed by the findings from previous objectives.Data sourcesFor the first systematic review, the following databases were searched from 1997 to April 2021: MEDLINE®(National Library of Medicine, Bethesda, MD, USA), Embase®(Elsevier, Amsterdam, the Netherlands), Cochrane Library, Web of Science™ (Clarivate™, Philadelphia, PA, USA), the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) and the National Institutes of Health Clinical Trials database. For the second systematic review, the following databases were searched from January 1990 to August 2020: MEDLINE, Embase, Cochrane Library, Web of Science, Kleijnen Systematic Reviews (KSR) Evidence, WHO ICTRP and the National Institutes of Health Clinical Trials database. For prediction model development, Clinical Practice Research Datalink GOLD, Clinical Practice Research Datalink Aurum and a subcohort of the Avon Longitudinal Study of Parents and Children were used; for estimates for the economic models, Clinical Practice Research Datalink Aurum was used.Review methodsFor review 1, cohort and case–control studies reporting on a diagnostic indicator in a population with and a population without coeliac disease were eligible. For review 2, diagnostic cohort studies including patients presenting with coeliac disease symptoms who were tested with serological tests for coeliac disease and underwent a duodenal biopsy as reference standard were eligible. In both reviews, risk of bias was assessed using the quality assessment of diagnostic accuracy studies 2 tool. Bivariate random-effects meta-analyses were fitted, in which binomial likelihoods for the numbers of true positives and true negatives were assumed.ResultsPeople with dermatitis herpetiformis, a family history of coeliac disease, migraine, anaemia, type 1 diabetes, osteoporosis or chronic liver disease are 1.5–2 times more likely than the general population to have coeliac disease; individual gastrointestinal symptoms were not useful for identifying coeliac disease. For children, women and men, prediction models included 24, 24 and 21 indicators of coeliac disease, respectively. The models showed good discrimination between patients with and patients without coeliac disease, but performed less well when externally validated. Serological tests were found to have good diagnostic accuracy for coeliac disease. Immunoglobulin A tissue transglutaminase had the highest sensitivity and endomysial antibody the highest specificity. There was little improvement when tests were used in combination. Survey respondents (n = 472) wanted to be 66% certain of the diagnosis from a blood test before starting a gluten-free diet if symptomatic, and 90% certain if asymptomatic. Cost-effectiveness analyses found that, among adults, and using serological testing alone, immunoglobulin A tissue transglutaminase was most cost-effective at a 1% pre-test probability (equivalent to population screening). Strategies using immunoglobulin A endomysial antibody plus human leucocyte antigen or human leucocyte antigen plus immunoglobulin A tissue transglutaminase with any pre-test probability had similar cost-effectiveness results, which were also similar to the cost-effectiveness results of immunoglobulin A tissue transglutaminase at a 1% pre-test probability. The most practical alternative for implementation within the NHS is likely to be a combination of human leucocyte antigen and immunoglobulin A tissue transglutaminase testing among those with a pre-test probability above 1.5%. Among children, the most cost-effective strategy was a 10% pre-test probability with human leucocyte antigen plus immunoglobulin A tissue transglutaminase, but there was uncertainty around the most cost-effective pre-test probability. There was substantial uncertainty in economic model results, which means that there would be great value in conducting further research.LimitationsThe interpretation of meta-analyses was limited by the substantial heterogeneity between the included studies, and most included studies were judged to be at high risk of bias. The main limitations of the prediction models were that we were restricted to diagnostic indicators that were recorded by general practitioners and that, because coeliac disease is underdiagnosed, it is also under-reported in health-care data. The cost-effectiveness model is a simplification of coeliac disease and modelled an average cohort rather than individuals. Evidence was weak on the probability of routine coeliac disease diagnosis, the accuracy of serological and genetic tests and the utility of a gluten-free diet.ConclusionsPopulation screening with immunoglobulin A tissue transglutaminase (1% pre-test probability) and of immunoglobulin A endomysial antibody followed by human leucocyte antigen testing or human leucocyte antigen testing followed by immunoglobulin A tissue transglutaminase with any pre-test probability appear to have similar cost-effectiveness results. As decisions to implement population screening cannot be made based on our economic analysis alone, and given the practical challenges of identifying patients with higher pre-test probabilities, we recommend that human leucocyte antigen combined with immunoglobulin A tissue transglutaminase testing should be considered for adults with at least a 1.5% pre-test probability of coeliac disease, equivalent to having at least one predictor. A more targeted strategy of 10% pre-test probability is recommended for children (e.g. children with anaemia).Future workFuture work should consider whether or not population-based screening for coeliac disease could meet the UK National Screening Committee criteria and whether or not it necessitates a long-term randomised controlled trial of screening strategies. Large prospective cohort studies in which all participants receive accurate tests for coeliac disease are needed.Study registrationThis study is registered as PROSPERO CRD42019115506 and CRD42020170766.FundingThis project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full inHealth Technology Assessment; Vol. 26, No. 44. See the NIHR Journals Library website for further project information.
PloS one · 2021
Background The prevalence of coeliac disease (CD) is around 1%, but diagnosis is challenged by varied presentation and non-specific symptoms and signs. This study aimed to identify diagnostic indicators that may help identify patients at a higher risk of CD in whom further testing is warranted. Methods International guidance for systematic review methods were followed and the review was registered at PROSPERO (CRD42020170766). Six databases were searched until April 2021. Studies investigating diagnostic indicators, such as symptoms or risk conditions, in people with and without CD were eligible for inclusion. Risk of bias was assessed using the QUADAS-2 tool. Summary sensitivity, specificity, and positive predictive values were estimated for each diagnostic indicator by fitting bivariate random effects meta-analyses. Findings 191 studies reporting on 26 diagnostic indicators were included in the meta-analyses. We found large variation in diagnostic accuracy estimates between studies and most studies were at high risk of bias. We found strong evidence that people with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease are more likely than the general population to have CD. Symptoms, psoriasis, epilepsy, inflammatory bowel disease, systemic lupus erythematosus, fractures, type 2 diabetes, and multiple sclerosis showed poor diagnostic ability. A sensitivity analysis revealed a 3-fold higher risk of CD in first-degree relatives of CD patients. Conclusions Targeted testing of individuals with dermatitis herpetiformis, migraine, family history of CD, HLA DQ2/8 risk genotype, anaemia, type 1 diabetes, osteoporosis, or chronic liver disease could improve case-finding for CD, therefore expediting appropriate treatment and reducing adverse consequences. Migraine and chronic liver disease are not yet included as a risk factor in all CD guidelines, but it may be appropriate for these to be added. Future research should establish the diagnostic value of combining indicators.
Source PubMed · Recherche par auteur (homonymes possibles, vérifier l'affiliation).
Health technology assessment (Winchester, England) · 2022 · Systematic Review
Elwenspoek MM, Thom H, Sheppard AL, Keeney E, et al.
PloS one · 2021 · Journal Article
Elwenspoek MMC, Jackson J, O'Donnell R, Sinobas A, et al.
Journal of medical Internet research · 2020 · Journal Article
Turnbull S, Cabral C, Hay A, Lucas PJ
Health technology assessment (Winchester, England) · 2022 · Systematic Review
Elwenspoek MM, Thom H, Sheppard AL, Keeney E, et al.
PloS one · 2021 · Journal Article
Elwenspoek MMC, Jackson J, O'Donnell R, Sinobas A, et al.
Journal of medical Internet research · 2020 · Journal Article
Clinical immunology (Orlando, Fla.) · 2018 · Journal Article
Zhang Y, Gupta S, Ilstad-Minnihan A, Ayyangar S, et al.
Pediatric annals · 2012 · Journal Article
Hay AD, Ilowite NT
Sports health · 2024 · Journal Article
Hay AM, Rhoades MJ, Bangerter S, Ferguson SA, et al.
British medical journal · 1978 · Case Reports
Hay AM
Health technology assessment (Winchester, England) · 2022 · Systematic Review
Elwenspoek MM, Thom H, Sheppard AL, Keeney E, et al.
Journal of immunology (Baltimore, Md. : 1950) · 2020 · Journal Article
Zhu J, Hay AN, Potter AA, Richwine MW, et al.
Health technology assessment (Winchester, England) · 2022 · Systematic Review
Elwenspoek MM, Thom H, Sheppard AL, Keeney E, et al.
Journal of medical Internet research · 2020 · Journal Article
Turnbull S, Cabral C, Hay A, Lucas PJ
Turnbull S, Cabral C, Hay A, Lucas PJ