Ce ´cile Delcourt
email: cecile.delcourt@isped.fr

Jean-Franc ¸ois Korobelnik

Gabrie ¨lle

H S Buitendijk

Paul J Foster

Christopher J Hammond

Stefano Piermarocchi

Tunde Peto

Nomdo Jansonius

Alireza Mirshahi

Ruth E Hogg

Lionel Bretillon

Fotis Topouzis

Gabor Deak

Jakob Grauslund

Rebecca Broe

Eric H Souied

Catherine Creuzot-Garcher

Jose ´sahel

Vincent Daien

Terho Lehtima ¨ki

Hans-Werner Hense

Elena Prokofyeva

Konrad Oexle

Jugnoo S Rahi

Phillippa M Cumberland

Steffen Schmitz-Valckenberg

Sascha Fauser

• Geir Bertelsen

Carel Hoyng

Arthur Bergen

Rufino Silva

Sebastian Wolf

Andrew Lotery

Usha Chakravarthy

Astrid Fletcher

Caroline C W Klaver

Ophthalmic epidemiology in Europe: the ''European Eye Epidemiology'' (E3) consortium

Keywords: Epidemiology, Ophthalmology, Eye diseases, Prevalence, Risk factors, Europe

The European Eye Epidemiology (E3) consortium is a recently formed consortium of 29 groups from 12 European countries. It already comprises 21 populationbased studies and 20 other studies (case-control, cases only, randomized trials), providing ophthalmological data on approximately 170,000 European participants. The aim of the consortium is to promote and sustain collaboration and sharing of data and knowledge in the field of ophthalmic epidemiology in Europe, with particular focus on the harmonization of methods for future research, estimation and projection of frequency and impact of visual On behalf of the European Eye Epidemiology (E3) consortium.

outcomes in European populations (including temporal trends and European subregions), identification of risk factors and pathways for eye diseases (lifestyle, vascular and metabolic factors, genetics, epigenetics and biomarkers) and development and validation of prediction models for eye diseases. Coordinating these existing data will allow a detailed study of the risk factors and consequences of eye diseases and visual impairment, including study of international geographical variation which is not possible in individual studies. It is expected that collaborative work on these existing data will provide additional knowledge, despite the fact that the risk factors and the methods for collecting them differ somewhat among the participating studies. Most studies also include biobanks of various biological samples, which will enable identification of biomarkers to detect and predict occurrence and progression of eye diseases. This article outlines the rationale of

Introduction

Visual impairment and blindness have profound human and socioeconomic consequences in all societies. People with vision loss experience a reduced quality of life [START_REF] Mckean-Cowdin | Longitudinal changes in visual acuity and health-related quality of life: the Los Angeles Latino Eye study[END_REF][START_REF] Seland | Visual impairment and quality of life in the older European population, the EUREYE study[END_REF], greater difficulty with daily living and social dependence [START_REF] Lam | longitudinal relationships among visual acuity and tasks of everyday life: the Salisbury Eye Evaluation study[END_REF][START_REF] Daien | Visual acuity thresholds associated with activity limitations in the elderly. The Pathologies Oculaires Liees a l'Age study[END_REF], higher rates of depression [START_REF] Carriere | A prospective study of the bi-directional association between vision loss and depression in the elderly[END_REF][START_REF] Lamoureux | Impact of the severity of distance and near-vision impairment on depression and visionspecific quality of life in older people living in residential care[END_REF], and an increased risk of falls and related hip fractures [START_REF] Patino | Central and peripheral visual impairment and the risk of falls and falls with injury[END_REF][START_REF] Yip | Visual acuity, selfreported vision and falls in the EPIC-Norfolk Eye study[END_REF]. The costs of lost productivity and of rehabilitation and education of the blind constitute a considerable economic burden for the individual, the family and society. Vision loss also incurs both direct health care costs and indirect costs of lost productivity, welfare and informal care. The global annual cost of visual impairment was recently estimated to be 3000 billion US dollars (563 billion US dollars for Europe) [START_REF] Gordois | An estimation of the worldwide economic and health burden of visual impairment[END_REF].

Worldwide and in Europe, the major causes of visual impairment in adults currently are age-related eye diseases (cataract, age-related macular degeneration (AMD), glaucoma and diabetic retinopathy), together with uncorrected refractive errors (myopia, hyperopia, astigmatism) and presbyopia [START_REF] Pascolini | Global estimates of visual impairment: 2010[END_REF][START_REF] He | Prevalence and correction of near vision impairment at seven sites in China, India, Nepal, Niger, South Africa, and the United States[END_REF]. Globally, 65 % of visually impaired subjects and 82 % of the blind are aged 50 years or more [START_REF] Pascolini | Global estimates of visual impairment: 2010[END_REF]. Thus, the number of visually impaired people will increase worldwide with the ongoing aging demographic, unless preventive and therapeutic strategies are implemented. Since 1999, prevention of visual impairment and blindness is a priority of the World Health Organization, through its joint program with the International Agency for the Prevention of Blindness, known as ''VISION2020-the Right to Sight'' [START_REF]Action plan for the prevention of avoidable blindness and vision impairment[END_REF]. In 2013, the World Health Assembly adopted a new global action plan for the prevention of avoidable blindness and visual impairment for the period 2014-2019 [START_REF]Universal eye health: a global action plan[END_REF].

Indeed, an increasing proportion of visual impairment is potentially avoidable, due to improvements in treatments for many blinding disorders. These include cataract surgery, intraocular (IOP) lowering therapies and surgical procedures, laser therapies, and development of anti-angiogenic intravitreal therapies. Together with the advances in retinal imaging, intravitreal therapies have revolutionized the management of retinal diseases in the clinical setting [START_REF] Drexler | State-of-the-art retinal optical coherence tomography[END_REF]. However, despite these improvements, visual impairment cannot always be prevented, due to late presentation of patients, variability in treatment responsiveness, or the development of untreatable complications.

In conjunction with medical progress in the management of eye diseases, the public has been informed on modifiable risk factors by the large epidemiological studies of recent decades. In particular, smoking is now recognized as a major risk factor for cataract [START_REF] Asbell | Age-related cataract[END_REF][START_REF] Leske | Risk factors for nuclear opalescence in a longitudinal study[END_REF][START_REF] Delcourt | Risk factors for cortical, nuclear, and posterior subcapsular cataracts: the POLA study. Pathologies Oculaires Liees a l'Age[END_REF][START_REF] Christen | Smoking cessation and risk of age-related cataract in men[END_REF][START_REF] Prokofyeva | Cataract prevalence and prevention in Europe: a literature review[END_REF], AMD [START_REF] Vingerling | Age-related macular degeneration and smoking. The Rotterdam Study[END_REF][START_REF] Delcourt | Smoking and age-related macular degeneration. The POLA Study. Pathologies Oculaires Liees a l'Age[END_REF][START_REF] Smith | Risk factors for age-related macular degeneration: pooled findings from three continents[END_REF][START_REF] Chakravarthy | Cigarette smoking and age-related macular degeneration in the EUREYE Study[END_REF][START_REF] Lim | Age-related macular degeneration[END_REF][START_REF] Erke | Cardiovascular risk factors associated with age-related macular degeneration: the Tromso Study[END_REF] and retinal vein occlusion [START_REF] Lim | Age-related macular degeneration[END_REF][START_REF] Klein | The epidemiology of retinal vein occlusion: the Beaver Dam Eye Study[END_REF]. Ultraviolet light exposure is a recognized risk factor for cataract [START_REF] Asbell | Age-related cataract[END_REF][START_REF] Cruickshanks | Ultraviolet light exposure and lens opacities: the Beaver Dam Eye Study[END_REF][START_REF] West | Sunlight exposure and risk of lens opacities in a population-based study: the Salisbury Eye Evaluation Project[END_REF][START_REF] Delcourt | Light exposure and the risk of cortical, nuclear, and posterior subcapsular cataracts: the Pathologies Oculaires Lie ´es a `l'Age (POLA) Study[END_REF][START_REF] Mccarty | A review of the epidemiologic evidence linking ultraviolet radiation and cataracts[END_REF][START_REF] Delcourt | Lifetime exposure to ambient ultraviolet radiation and the risk for cataract extraction and age-related macular degeneration: the Alienor Study[END_REF] and pterygium, [START_REF] Threlfall | Sun exposure and pterygium of the eye: a dose-response curve[END_REF][START_REF] Mccarty | Epidemiology of pterygium in Victoria, Australia[END_REF] and has been shown to be a risk factor for AMD in those with low blood level of key antioxidant vitamins [START_REF] Fletcher | Sunlight exposure, antioxidants, and age-related macular degeneration[END_REF]. Indeed, the role of dietary antioxidants (including lutein and zeaxanthin) has been investigated in many eye disorders [START_REF] Seddon | Dietary carotenoids, vitamins A, C, and E, and advanced age-related macular degeneration[END_REF][START_REF] Delcourt | Age-related macular degeneration and antioxidant status in the POLA study. POLA Study Group. Pathologies Oculaires Liees a l'Age[END_REF][START_REF] Van Leeuwen | Dietary intake of antioxidants and risk of age-related macular degeneration[END_REF][START_REF] Tan | Dietary antioxidants and the long-term incidence of age-related macular degeneration: the Blue Mountains Eye Study[END_REF][START_REF] Mares Perlman | Lutein and zeaxanthin in the diet and serum and their relation to age-related maculopathy in the third national health and nutrition examination survey[END_REF][START_REF] Delcourt | Plasma lutein and zeaxanthin and other carotenoids as modifiable risk factors for age-related maculopathy and cataract: the POLA Study[END_REF][START_REF] Ho | Reducing the genetic risk of age-related macular degeneration with dietary antioxidants, zinc, and x-3 fatty acids: the Rotterdam study[END_REF][START_REF] Lyle | Antioxidant intake and risk of incident age-related nuclear cataracts in the Beaver Dam Eye Study[END_REF][START_REF] Gale | Plasma antioxidant vitamins and carotenoids and age-related cataract[END_REF][START_REF] Christen | Dietary carotenoids, vitamins C and E, and risk of cataract in women: a prospective study[END_REF][START_REF] Fletcher | Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration[END_REF][START_REF] Areds | A randomized, placebo-controlled, clinical trial of highdose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8[END_REF]. There is also growing literature on the potential role of other nutritional factors (in particular omega 3 fatty acids) in the etiology of age-related eye diseases [START_REF] Ho | Reducing the genetic risk of age-related macular degeneration with dietary antioxidants, zinc, and x-3 fatty acids: the Rotterdam study[END_REF][START_REF] Smith | Dietary fat and fish intake and age-related maculopathy[END_REF][START_REF] Cho | Prospective study of dietary fat and the risk of age-related macular degeneration[END_REF][START_REF] Seddon | Dietary fat and risk for advanced age-related macular degeneration[END_REF][START_REF] Delcourt | Dietary fat and the risk of age-related maculopathy: the POLANUT study[END_REF][START_REF] Sangiovanni | Omega-3 long-chain polyunsaturated fatty acid intake inversely associated with 12-year progression to advanced age-related macular degeneration[END_REF][START_REF] Tan | Dietary Fatty acids and the 10-year incidence of age-related macular degeneration: the blue mountains eye study[END_REF][START_REF] Merle | Dietary omega-3 Fatty acids and the risk for age-related maculopathy: the alienor study[END_REF][START_REF] Merle | Circulating omega-3 fatty acids and neovascular age-related macular degeneration[END_REF][START_REF] Augood | Oily fish consumption, dietary docosahexaenoic acid and eicosapentaenoic acid intakes, and associations with neovascular age-related macular degeneration[END_REF][START_REF] Chiu | Dietary carbohydrate intake and glycemic index in relation to cortical and nuclear lens opacities in the age-related Eye Disease study[END_REF][START_REF] Chiu | Dietary carbohydrate in relation to cortical and nuclear lens opacities in the melbourne visual impairment project[END_REF][START_REF] Mares | Healthy diets and the subsequent prevalence of nuclear cataract in women[END_REF]. Diabetes is associated with specific retinal complications such as diabetic retinopathy and diabetic macular edema, and is independently associated with an increased risk for cataract [START_REF] Delcourt | Risk factors for cortical, nuclear, and posterior subcapsular cataracts: the POLA study. Pathologies Oculaires Liees a l'Age[END_REF][START_REF] Prokofyeva | Cataract prevalence and prevention in Europe: a literature review[END_REF][START_REF] Cheung | Diabetic retinopathy[END_REF]. Improved prevention and management of diabetes thus has important potential consequences for ocular health. These lifestyle risk factors (smoking, ultraviolet exposure, outdoor activity, nutrition, exercise, obesity, and diabetes) not only relate to eye disorders, they also bear a great risk of other major chronic diseases such as cardiovascular diseases and cancers. They have been a focus for national and international public health programs and the arousal of public awareness may have impacted the prevalence of age-related eye diseases in Europe, and the related visual impairment. However, detailed data on temporal trends in Europe are scarce.

Ophthalmic epidemiology in Europe

Understanding the population and the epidemiology of common diseases is essential for planning future healthcare provision [START_REF] Lim | A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study[END_REF]. As the European population ages and environmental risk factors change, thorough epidemiological research is necessary to ensure sufficient medical care, evidence-based public health screening and efficient use of medical resources.

In the past twenty years, ophthalmic epidemiology has successfully identified genetic and environmental risk factors for eye diseases and visual impairment. Before 2000, few specific studies were undertaken in Europe, limiting the knowledge on visual impairment and eye diseases. Since then, many studies on eye health involving multiple European countries and totaling more than 170,000 participants have been performed. Most recently, very large studies have been undertaken, such as the UK Biobank study, the largest prospective study of health and disease (118,000 subjects with detailed ophthalmic examination, http://www.ukbiobank.ac.uk/) or the Constances study in France (currently 41,000 with ophthalmological data, planned 200,000) [START_REF] Zins | The CONSTANCES cohort: an open epidemiological laboratory[END_REF].

Overall, these studies have provided estimates of the frequency of visual impairment and eye diseases in European countries, and have had a major role in the identification of their genetic and environmental risk factors. However, the epidemiological data provided by these numerous studies have not been related to the European continent as a whole. The E3 collaboration aims to provide robust and precise estimates of prevalence and risk factors for visually impairing diseases across Europe. We believe this will deliver a strong and coherent public health message to populations across Europe and national governments. It will also enable examination of temporal trends and differences in European sub-regions in prevalence of eye conditions. Projections of frequency of eye diseases and visual impairment will allow a better planning of their prevention and treatment in the future.

Aside from these general epidemiological issues, ophthalmic epidemiology has been faced with methodological challenges. The major technological advances in eye imaging, which have profoundly influenced clinical practice, have only been implemented in more recent epidemiological studies. In particular, optical coherence tomography (OCT) has changed eye epidemiology, for it allows for noninvasive cross-sectional imaging of retinal layers, facilitating the diagnosis of structural changes in diseases such as age-related macular degeneration, vascular occlusions and diabetic retinopathy. Innovative eye imaging techniques are now commonly used in clinical practice but international classification systems of procedures and interpretation of images to standardize epidemiological data collection is currently lacking. The E3 collaboration strives to develop such international classification systems for use in future epidemiological studies. It may also help identifying and validating novel markers based on these imaging techniques, which could predict occurrence of eye diseases, or represent surrogate endpoints in future clinical trials.

There have also been major advances in the understanding of the molecular pathophysiological pathways of the major eye diseases. Many genetic polymorphisms associated with age-related eye diseases have been identified in the last decade, mainly through genome-wide association studies. Large international consortia (such as AMD Genomics Consortium for AMD [START_REF] Fritsche | Seven new loci associated with age-related macular degeneration[END_REF], CREAM for refractive error and myopia [START_REF] Verhoeven | Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia[END_REF], and IGGC for glaucoma [START_REF] Hysi | Genome-wide analysis of multi-ancestry cohorts identifies new loci influencing intraocular pressure and susceptibility to glaucoma[END_REF]) identified numerous genetic risk variants for these diseases by meta-analysis of thousands of study subjects. These consortia included studies from US, Asia, Australia, and Europe. New genetic and statistical developments (1000 genome analysis, exome platforms and sequencing) are currently paving the way for more detailed analyses of the genetic loci and possible rare variants involved. The latter in particular are likely to be population-specific. The consorted action of E3 will provide the required statistical power which no individual studies have, given the generally small effect sizes. In addition, these comprehensive genetic analyses will improve current models for prediction of disease [START_REF] Buitendijk | Prediction of agerelated macular degeneration in the general population: the Three Continent AMD Consortium[END_REF] and enable development of prediction models specific for European populations.

Finally, although progress has been made in identification of lifestyle risk factors for ocular diseases, detection of specific biochemical biomarkers for diagnosis and prognosis has been less successful. Biomarkers may be circulating (plasma, serum, red blood cells, leukocytes) or tissue-specific (tears, aqueous humor, vitreous) and include inflammatory markers, lipid molecules, peptides or proteins. Recent developments in analytical tools such as metabolomics, proteomics or lipidomics have opened up new avenues. To be considered reliable surrogate endpoints, biomarkers must fulfill several criteria in terms of robustness, reliability, precision, reproducibility, sensitivity and specificity. Insufficient sample sizes have been barriers to identify subtle changes in biochemical markers, hampering valid comparisons between studies. Standardization of methodologies and pooling of biological samples across European studies may enable more rapid progress in this area.

Pooling of existing data from European epidemiological studies will provide a major research resource, integrating genetic and biochemical biomarkers. We aim to translate these data into novel epidemiological insights that convey important messages to the public, medical practitioners and policy makers for lifestyle modification and other preventive strategies, with the ultimate aim of preventing visual impairment and blindness. Finally, pooling of data from different European epidemiological datasets will facilitate powerful studies to predict future magnitude and impact of visual impairment in Europe.

Scope of the European Eye Epidemiology (E3) consortium

The aim of the consortium is to promote ophthalmic epidemiology in Europe, by exchange of scientific knowledge and methodology, in particular for: harmonization of methods (classification of ocular outcomes, measures of risk factors) estimation of frequency and impact of visual outcomes in European populations (visual impairment, quality of life, eye diseases) identification of geographic differences in the prevalence and incidence of ophthalmic diseases and conditions across Europe projections of frequency of visual impairment and eye diseases in European populations identification of risk factors and pathways for eye diseases (lifestyle, vascular and metabolic factors, genetics, biomarkers) development and validation of prediction models for eye diseases building capacity and expertise in ophthalmic and genetic epidemiology in Europe and translating expertise to young researchers communicating findings and recommendations to the medical community, policy makers and the public These aims will be supported by assembling background information from participating studies, developing a plan for harmonization of core exposure and outcome variables, and pooling of data, effectively increasing sample size to yield statistically powered and robust data analyses.

Currently participating studies

As of May 2015, 29 groups from 12 European countries are participating in the E3 consortium (Fig. 1). European research groups active in ophthalmic epidemiology have been considered eligible for membership of the Consortium. As seen on Fig. 1, the majority of participating studies originate from high income European countries; only one centre (from the EUREYE study) is situated within a former communist country. To our knowledge, few epidemiological studies have been performed in Eastern Europe [START_REF] Bourne | Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe: 1990-2010[END_REF].

Overall, the E3 Consortium includes 21 populationbased studies in ophthalmic epidemiology, of which 16 are prospective (Table 1), and 20 other studies, including case-control studies, case only studies and randomized clinical trials (Table 2). Overall, these studies collected ophthalmological data in [170,000 European subjects. As new studies are being performed in Europe, we anticipate that the number of studies will be growing in the next years. In particular, collaboration with the UK Biobank study (http://www.ukbiobank.ac.uk/) and the Constances study is being considered [START_REF] Zins | The CONSTANCES cohort: an open epidemiological laboratory[END_REF].

The age range of participants varied, but most studies included subjects older than 50 years, while few studies include young subjects. Phenotyping was performed between 1995 and 2015, and thus allow for the study of temporal trends in the prevalence of ocular disease. As shown in Table 3, a variety of ocular phenotypes have been collected in these studies. The vast majority of studies collected measurements of vision and refractive errors.

Most studies also collected data on intraocular pressure, AMD and retinal vessels. A smaller number of studies included visual field examinations and diagnosis of glaucoma.

As shown in Tables 4 and5, most of the participating studies also collected data on a variety of risk factors potentially related to ocular health, such as socio-demographic characteristics (educational level, socio-economic status), medical history and medications, quality of life and disability, lifestyle and environment (smoking, alcohol, body mass index, nutrition, physical activity), laboratory (glucose, lipids, biomarkers of inflammation, renal and liver function, nutritional biomarkers), cardiovascular (blood pressure, ankle brachial index, carotid arteries, aortic and cardiac measurements, pulsometry) and neuropsychiatric (cognitive and psychiatric testing, brain imaging) measurements, genetics and genomics determinations (specific genetic polymorphism, GWAS, ExomeCorechip or exome sequencing) as well as epigenetic determinations (microRNA and DNA methylation). Coordinating these existing data will allow an in-depth study of the risk factors and consequences of eye diseases and visual impairment, although the risk factors and the methods for collecting them somewhat differ among the participating studies. Most studies also include biobanks, which may allow measurement of new biomarkers to determine their validity in detecting and predicting occurrence and progression of eye diseases (Tables 4 and5).

Structure of the consortium

Collaboration within the E3 consortium is defined by a Memorandum of Understanding, which has been signed by all participating teams. It is managed by an Executive Committee (with one representative for each participating institution) and a Steering Committee (constituted of the leaders of the workgroups). As of May 2015, there are ten active workgroups (

Harmonization of data and first activities of the consortium

One of the difficulties encountered in meta-analyses is the heterogeneity of the collected data. Some of the heterogeneity may be overcome by standardizing data analysis (using similar definitions of endpoints and similar statistical methods), while in other cases, new methods for interpreting and collecting data are needed.

A number of ocular outcomes (refractive errors, visual impairment, AMD and diabetic retinopathy) have been collected in a standardized manner in E3 participating studies owing to long-established consensus in the methods of collection and classification. Using summary data from participating studies a number of meta-analyses on the prevalence of these outcomes have been undertaken. These analyses have formed the basis for the two reports on the prevalence of refractive errors and myopia in Europe [START_REF] Williams | Prevalence of refractive error in Europe: the European Eye Epidemiology (E3) consortium[END_REF][START_REF] Williams | Increasing prevalence of Myopia in Europe and the impact of education[END_REF]. Additional manuscripts are in preparation on the prevalence of visual impairment and AMD (including temporal trends and geographical variation), and an ongoing meta-analysis on the prevalence of diabetic retinopathy.

For other outcomes, a need for harmonization has been identified. In particular, standardization of macular SD-OCT examinations, and consensus on the interpretation and classification of macular diseases are needed. To address this, we have developed a new classification, for use in epidemiological studies. The manuscript describing this new classification is in preparation and has been distributed to E3 participants for use in their ongoing studies. Harmonized interpretation of SD-OCT examinations throughout European epidemiological studies should thus be soon available. Significant variability also exists among European studies with regard to the data collection and classification of glaucoma. Harmonization of existing data represents a challenge in this field.

With regard to the identification of risk factors, a metaanalysis has been conducted on the factors associated with intra-ocular pressure (including age, gender, BMI, height, blood pressure and refractive errors). Each study performed multivariate linear regression models, using a standardized statistical plan, and regression coefficients were then metaanalyzed. This paper is currently submitted.

The next step in the integration of European data will be undertaken within the Eye-Risk project, which is funded by the European Union's Horizon 2020 Research and Innovation Programme (www.eyerisk.eu). This project will explore the combined role of genetic and non-genetic risk factors for AMD. It plans to integrate individual data from E3 participating studies into a common E3 database, which will be used for data analysis. This will require harmonization of data on genetic and non-genetic risk factors (including lifestyle, nutrition, in-depth retinal imaging, circulating biomarkers). This represents a major challenge, since data on risk factors have been collected in a highly variable way in participating studies. Some additional, harmonized, data collection will most probably be necessary, in particular in the field of genetic polymorphisms and circulating biomarkers. In the future, we plan to further extend this database to other ocular endpoints, allowing for powerful, detailed analyses of risk factors of various eye diseases.

Fig. 1

 1 Fig. 1 Map of groups participating in the E3 consortium (May 2015)

Table 1

 1 Population-based studies participating in the E3 consortium

	Study name	Country	Period of first	Age	Number of subjects	Prospective
			eye examination	range	with eye examination	study?
	1958 British Birth cohort	UK	2002	44-45	9330	Yes
	Young Finns Study	Finland	2010	33-48	1684	Yes
	Rotterdam Study I	Netherlands	1990-1993	55?	6913	Yes
	Twins UK	UK	1992	18?	6247	Yes
	MRC Older People Study	UK	1995-1998	75?	14,593	For mortality
						outcomes
	POLA	France	1995-1998	60?	2584	Yes
	Tromsø Eye Study	Norway	2001	40?	6540	Yes
	Rotterdam Study II	Netherlands	2000-2001	55?	3011	Yes
	Eureye	Norway, Estonia, UK, France,	2001-2002	65?	4753	No
		Italy, Greece, Spain
	Thessaloniki Eye Study	Greece	2000-2005	60?	2554	Yes
	ERF	Netherlands	2002	18?	2940	Yes
	KORA	Germany	2004-2005	35?	3078	No
	PAMDI	Italy	2005-2006	60?	1162	No
	Epic-Norfolk	UK	2004-2011	45?	8623	No
	Alienor	France	2006-2008	73?	963	Yes
	Rotterdam Study III	Netherlands	2006-2008	45?	3682	Yes
	Gutenberg Health Study	Germany	2007-ongoing	35-74	14,700	Yes
	Coimbra Eye Study	Portugal	2009-2013	55?	6023	No
	Montrachet	France	2009-2012	75?	1153	Yes
	Generation R	Netherlands	Ongoing	0?	*6000	Yes
	NICOLA	UK	Ongoing	50?	*5500	Yes
	Total				*112,000

Table 2

 2 Other studies participating in the E3 consortium

	Study name	Country	Period of eye	Age	Number of	Type of study	Types of cases
			examination	range	subjects
	Danish cohort of pediatric diabetes 1987 Denmark	1995-2011	28-42	324	Longitudinal study	Diabetes
	AMRO-NL	Netherlands 1998-2005	55?	1194	Hospital based-cohort	Glaucoma AMD
	Belfast	UK	2001	50?	402	Case-control	AMD
	Guernsey AMD case cohort study	UK	2003	50?	371	Case-control	AMD
	Southampton Rod-cone Dystrophies	UK	2003	10?	143	Case only	Rod-cone
							dystrophy
	Southampton POAG	UK	2003	40?	1618	Case only	Glaucoma
	MARS	Germany	2003-2010	60-80	1060	Hospital-based cohort	AMD
	Fyns Diabetes Database	Denmark	2003-2015	0?	22,089	Case only	Diabetes
	Creteil Study	France	2005	55?	2081	Case-control	AMD
	CARMA	UK/Ireland	2005	55?	430	Randomized clinical trial AMD
	EUGENDA	Netherlands/	2006	50?	4800	Case-control	AMD
		Germany
	Southampton nystagmus	UK	2006	0?	244	Case-control	Nystagmus
	Early Observational Markers Study	UK/	2007	50?	105	Longitudinal study	AMD
		Italy/
		Portugal
	CIC XV XX	France	2008	55?	794	Case-control	AMD
	IVAN Study	UK	2008	50?	608	Longitudinal study	AMD
	Southampton paediatric eye diseases	UK	2008	0-16	474	Case-control	Paediatric eye
							diseases
	Southampton AMD/glaucoma	UK	2009	50?	56	Case-control	AMD/glaucoma
	case-control Study
	MYST	Netherlands 2009-2012	25?	1200	Case-control	High myopes
	Southampton Liver Transplant	UK	2010	50?	241	Cases only	Liver transplant
	Coimbra-RD	Portugal	2011-2012	40?	22,658	Cases only	Diabetes
	Total				60,892

Table 6 )

 6 . The E3 consortium is open to new members working in the field of eye epidemiology in Europe. All membership requests are examined by the Executive Committee. Meetings dedicated to the consortium to consolidate objectives and future plans are planned on a yearly basis, and have been held in Bordeaux in June 2011, 2012 and 2013, in Rome in June 2014 and in London in June 2015.

Table 3

 3 Ocular endpoints available in population-based studies

	Study name	Vision Visual fields Refractive errors IOP a AMD Glaucoma Retinal vessels OCT examinations
	1958 British Birth cohort	X	X
	Young Finns Study		X	X

INRA, UMR1324 Centre des Sciences du Gou ˆt et de l'Alimentation, 21000 Dijon, France

CNRS, UMR6265 Centre des Sciences du Gou ˆt et de l'Alimentation, 21000 Dijon, France

Universite ´de Bourgogne, Centre des Sciences du Gou ˆt et de l'Alimentation, 21000 Dijon, France

Rotterdam StudyI X X X X X X X X Twins UK X X X X X X MRC Older People Study X X X POLA X X X X X Tromsø Eye Study X X X X X Rotterdam Study II X X X X X X Eureye X X X Thessaloniki Eye Study X X X X X X X X ERF X X X X X X KORA X X PAMDI X X X X X Epic-Norfolk X X X X X X Alienor X X X X X X X Rotterdam Study III X X X X X X X X Gutenberg Health Study X X X X X X X X Coimbra Eye Study X X X X Montrachet X X X X X X X X Generation R X X X X NICOLA X X X X X X X a Intraocular pressureOphthalmic epidemiology in Europe: the ''European Eye Epidemiology'' (E3) consortium 203

X Rotterdam I X X X X X X X X X Twins UK X X X X X X X X X MRC Older People Study X X X X X X X POLA X X X X X X Tromsø Eye Study X X X X X X X X Rotterdam Study II X X X X X X X X X Eureye X X X X X X X X Thessaloniki Eye Study X X X X X ERF X X X X X X X X KORA X X X X X X X PAMDI X X X X X X Epic-Norfolk X X X X X X X X X Alienor X X X X X X X X X Rotterdam Study III X X X X X X X X X Gutenberg Health Study X X X X X X X X X Coimbra Eye Study X X X Montrachet X X X X X X X X X Generation R X X X X X X X NICOLA X X X X X X X X 204C. Delcourt et al.

X AMRO-NL X X X X X Belfast X X X X X X Guernsey AMD study X X X X Southampton Rod-cone Dystrophies X X X X Southampton POAG X X X X MARS X X X X X X X X Creteil Study X X X X X X CARMA EUGENDA X X X X X X Southampton nystagmus X X X Fyns Diabetes DataBase X X X X Early Observational Markers Study X IVAN Study X X X X Southampton paediatric eye diseases X X X Southampton AMD/glaucoma case-control Study CIC XV XX X X X X MYST X X X X X Southampton Liver Transplant X X X X Coimbra RDOphthalmic epidemiology in Europe: the ''European Eye Epidemiology'' (E3) consortium

Acknowledgments The E3 consortium thanks Ce ´cile Delcourt, Jean-Franc ¸ois Korobelnik, Marie-Be ´ne ´dicte Rougier and Marie-Noe ¨lle Delyfer for organizing the meetings in Bordeaux in 2011, 2012 and 2013, Stefano Piermarocchi for organizing the meeting in Rome in 2014 and Chris Hammond, Paul Foster and Tunde Peto for organizing the meeting in London in 2015. These workshops have received financial support from Carl Zeiss Meditec AG, Laboratoires The ´a, Novartis and OOgroup. Compliance with ethical standards


Daniel Balouek

Ismael Perez

Sam D Faulstich

Heather A Holmes

Ilkay Altintas

Manish Parashar

Daniel Balouek-Thomert
email: daniel.balouek-thomert@inria.fr

Keynote Talk: Leveraging the Edge-Cloud Continuum to Manage the Impact of Wildfires on Air Quality

Keywords: Urgent computing, Continuum computing, Edge-Cloud integration, Cyberinfrastructure, Uncertainty

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

I. INTRODUCTION

Widely-distributed (and pervasive) computing resources and data sources along with low latency connections are enabling new classes of distributed, driven applications, such as those involving urgent analysis of data streams to identify critical events, accelerate decision making, and trigger responses. For example, recent work on Earthquake Early Warning (EEW) builds on such a geographically distributed cyberinfrastructure to integrate data from different types of sensors to increase the accuracy of detection, with efficient and timely computations using a range of resources available along the data path, all while ensuring robustness to data uncertainties and partial infrastructure failures [START_REF] Fauvel | A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning[END_REF], [START_REF] Esposito | Recent advances in internet of things solutions for early warning systems: A review[END_REF].

Indeed, such a Computing Continuum, i.e., the spectrum of connected resources and services with heterogeneous capabilities, capacities, availabilities distributed across the logical extreme of the network and along the data path [START_REF] Balouek-Thomert | Towards a computing continuum: Enabling edge-to-cloud integration for data-driven workflows[END_REF], [START_REF] Beckman | Harnessing the computing continuum for programming our world[END_REF], provides an ideal platform for supporting urgent computing, i.e., computing under strict time and quality constraints to support decision making with the desired confidence within a defined time interval [START_REF] Balouek-Thomert | Towards a methodology for building dynamic urgent applications on continuum computing platforms[END_REF]- [START_REF] Alexander V Boukhanovsky | Urgent computing for decision support in critical situations[END_REF]. However, exploiting resources across this continuum can be challenging [START_REF] Balouek-Thomert | Harnessing the computing continuum for urgent science[END_REF].

Developing urgent computing applications requires developers and service providers to orchestrate data-driven workflows while considering not only the extreme heterogeneity of underlying cyberinfrastructure, but also the uncertainty related to the availability and quality of the data [START_REF] Sergey | Deadline-driven resource management within urgent computing cyberinfrastructure[END_REF]. Thus, the endto-end performance of such applications deployed across the continuum depends on programming abstractions to express application behaviors that can react to unforeseen events at runtime, and autonomic runtime mechanisms that support the adaptations of resources and execution paths between the across the continuum. Furthermore, the inherent resource and system dynamics further complicate the realization of urgent computing applications [START_REF] Gibb | The technologies required for fusing hpc and real-time data to support urgent computing[END_REF]. For example, application developers cannot make assumptions about the exact execution context, which is only know at runtime. As a result, in order to preserve a level of generality, it is essential the programming and runtime systems maintain a separation between the concerns of domain experts (acquainted with the applications) and those of resource managers (familiar with the infrastructure). Furthermore, when choosing resources or carrying out actuation, it is important to take the shared nature of the sensors and resources into consideration.

This paper explores these issues using an application workflow that monitors and manage the air quality impacts of remote wildfires as a driving usecase. It then illustrates how the programming abstractions and runtime mechanisms provided by the R-Pulsar programming system, along with services provided by the SAGE and WIFIRE platforms can be lever- aged potentially enable urgent computing across the computing continuum to support this usecase. This paper is organized as follows. The driving urgent application usecase scenario is presented in Section II. An overview of the R-Pulsar programming system as well as the SAGE and WIFIRE platforms are described in Section III. Section IV explores how R-Pulsar along with SAGE and WIFIRE can support the urgent application usecase across the continuum and discusses research challenges.

II. MOTIVATING URGENT USECASE: MONITORING AND MANAGING THE AIR QUALITY IMPACTS OF WILDFIRES

High-fidelity data streaming from multiple data sources, combined with highly-accurate computational models, can be effectively used to monitor and manage the impacts of both natural disasters and extreme events. This is illustrated in the wildfire scenario below.

Wildfires are among the most destructive natural disasters, destroying homes, wildlife habitat and timber, and the emissions pollute the air, which is harmful to human health. Among many others in recent times, California's Dixie Fire burned nearly a thousand square miles in August 2021 [START_REF]Shasta County, and Unified Command Fires. California statewide fire summary[END_REF]. The claims of increased air pollution in Utah as a direct effect of the wildfires in California served as the driver for our research [START_REF] Liji M David | Could the exception become the rule¿uncontrollable'air pollution events in the us due to wildland fires[END_REF]. The motivating scenario is predicated on the utilization of a large number of applied models for the purpose of following and responding to fire events across a variety of states and different data sources. These plugins track wildfire events, track smoke plumes, and model downwind air pollution concentrations associated with wildfire smoke.

These wildfire events might be recognized, predicted, and linked to better alerts and reactions using sensors spread over California, Oregon, and Utah1 . Through a three-step approach, we aim to realize this possibility, illustrated in Figure 1. First, the HPWREN network's field cameras2 are situated in California as a collaborative, networked cyberinfrastructure. To extract photos and increase trust in detecting smoke events, camera feeds are processed using smoke detection models. Second, a Fire Simulator (FS) gathers latitude/longitude data from the cameras and produces fire metrics relating to the intensity of a starting fire, as well as providing fire emissions as an output. Finally, the Air Quality (AQ) Model runs a Lagrangian transport model with inputs from gridded weather datasets and fire emissions from FS to produce a map of air pollution concentrations. The output is subsequently applied to decision-making or to initiate further sensing. Such a scenario's specification calls for expertise from several fields and interdisciplinary cooperation.

III. HARNESSING THE COMPUTING CONTINUUM FOR URGENT APPLICATIONS: BUILDING BLOCKS A. The SAGE Platform

The SAGE cyberinfrastructure platform offers large-scale infrastructure at the national level to enable artificial intelligence (AI) at the network edge. SAGE addresses the tremendous variability of system and service capacities and capabilities 3 . Extreme uncertainty regarding the availability and quality of data, resources, and services throughout the Edge/Cloud-HPC continuum adds to this heterogeneity. To address this heterogeneity, developers need application formulations that expose natural flexible configurations and scheduling/resource trade-offs as well as establish policies and mechanisms that might trigger runtime adaptations are necessary to address this heterogeneity -the SAGE platform enables the execution of such formulations at the edge [START_REF] Beckman | Harnessing the computing continuum for programming our world[END_REF].

The SAGE catalog of plugins offers applied models that can be deployed on any of their nodes for sensor-based processing such as motion detection using cameras or air quality using dust monitors. These plugins are currently developed regardless of the device or runtime scheduling context in which they are used.

B. The WIFIRE Project

The NSF-funded WIFIRE project [START_REF] Altintas | Towards an integrated cyberinfrastructure for scalable data-driven monitoring, dynamic prediction and resilience of wildfires[END_REF] develops an integrated system for wildfire monitoring, simulation, and re- sponse. WIFIRE provides an end-to-end management cyberinfrastructure (CI) with integrated data collection from many real-time data sources, and for modeling wildfire behavior.

Producers

C. The R-Pulsar Programming System: Enabling Data-driven Workflows across the Continuum R-Pulsar is a programming system for building data-todiscovery pipelines between the edge of the network and larger-scale HPC systems and cloud services. It provides middleware services that enables local analytics, messaging, data storage, and data querying capabilities on edge devices using a unified platform [START_REF] Renart | Online decision-making using edge resources for content-driven stream processing[END_REF], [START_REF] Gibert Renart | An edge-based framework for enabling data-driven pipelines for iot systems[END_REF]. Overall, R-Pulsar offers:

• Content-and location-based programming abstractions for specifying what data are collected and where the data are analyzed.

• Rule-based runtime mechanisms for specifying when and where to trigger data-processing tasks as well as actions based on data patterns (spatial and temporal). Figure 2 illustrates the key concepts of R-Pulsar. First, producers are in charge of collecting data from physical and virtual sensors. As IoT data often come with temporal and spatial information, R-Pulsar presents a location-aware overlay network to logically connect sensors. This overlay allows developers to specific interactions based on data content and location, rather than using names and/or addresses [START_REF] Jiang | Meteor: a middleware infrastructure for content-based decoupled interactions in pervasive grid environments[END_REF].

Second, R-Pulsar provides an event-driven programming model where rules are triggered using data filters that are based on the availability/content of data and/or the state of resources. Using this model, developers can use filters to specify IF-THEN rules to steer the execution of a workflow. In the context of infinite streams of data, the filters can be written to reason on streaming windows to act on specific and/or incomplete batches and may be based on statistical properties of the data in a window. Other types of filters and rules include contentdriven, context-aware, or spatial [START_REF] Gibert Renart | An edge-based framework for enabling data-driven pipelines for iot systems[END_REF].

Finally, actions are triggered when a rule is fired, and can include communications/notifications, further data acquisition/analysis, changing of system parameters or service configurations, and/or launching additional computations and the implementation of tradeoffs.

We recently deployed and evaluated a policy-driven adaptation of R-Pulsar over the Grid'5000 platform [START_REF] Balouek | Adding virtualization capabilities to the grid'5000 testbed[END_REF] by observing the behavior of the system with variability in data volumes, network bandwidth, and available CPU capacity. Results shows that dynamic policies adjust quickly to periodic variations allowing for the management of a large number of events and complex decisions in cloud-only, edge-only or hybrid setups, with deadline and quality constraints [START_REF] Balouek-Thomert | Evaluating policy-driven adaptation on the edge-to-cloud continuum[END_REF].

The latest version of R-Pulsar is available on GitHub 4 under Apache License 2.0. On-going work is focused on packaging R-Pulsar as lightweight Kubernetes containers for integration with Waggle and SAGE.

IV. IMPLEMENTING URGENT WORKFLOWS ACROSS THE COMPUTING CONTINUUM: APPROACH AND CHALLENGES

A key goal of the research described in this paper is to understand of data-driven feedback necessary to map, schedule, execute and adapt the data-to-discovery workflow from sensors to decision-making, by opportunistically combining heterogeneous and geographically distributed resources. A further goal is to use the presented application usecase to synthesize urgent application patterns underlying similar urgent application workflows, and to develop implementation architectures, based on the R-Pulsar programming system, that can be used to execute these patterns across the edgeto-HPC/cloud computing continuum and realize the desired quality and performance goals.

A. Architecture

In [START_REF] Balouek | Platforms for edge computing and internet of things applications: A survey[END_REF], the authors compared and contrasted the state of the art of components and middleware systems that operate between the edge and the cloud, in both academia and industry. The findings from this study highlight a set of common requirements and design goals, for example, for implementing data ingestion, as well as for programming models that allow https://http://rpulsar.sci.utah.edu/ for the processing of streaming data and runtime systems that support the management of resources across the continuum. Figure 3 presents a simplified schematics of a three-layer edge-based middleware architecture for supporting application workflows across the edge-cloud/HPC continuum that emerged from the study. The Resource Management Layer organizes the discovery, selection, and allocation of available resources across the heterogeneous and distributed set of available resources. The key design goals of this layer include achieving low overhead, distributed management and aggregating of resources. The Data Processing Layer consolidates data from multiple sources, and provides support for data indexing and discovery. The data processing components may need to be able to process data under near-real time constraint and on a range of resource types, including edge constrained devices such as Raspberry Pis or smartphones as well as cloud/HPC systems. The Service Layer provides a set of capabilities to support the implementation of application workflows, managing resources, and coordinating execution.

Resource Management Layer

Furthermore, satisfying application requirements and constraints in terms of response time, solution quality, data resolution, cost, energy, etc., during execution across a highly dynamic edge-cloud/HPC continuum warrants optimizations across all three layers. Such cross-layer optimizations must address cost/benefit tradeoffs at runtime in an autonomic manner and may require the reconfiguration of applications, resources, and services, including provisioning new resources and services, adapting scheduling strategies, and/or adjusting application parameters as necessary.

In the context of our driving usecase, i.e., detecting the impacts of wildfire on air quality, the need to reduce execution time and energy usage requires dynamic resource and service composition and configuration [START_REF] Altintas | Towards a dynamic composability approach for using heterogeneous systems in remote sensing[END_REF].

The on-demand composition of various services (e.g., SAGE plugins) across geographically dispersed resources while considering cross-cutting performance, quality, security or energy concerns is not, however, supported by programming systems or resource management runtimes. For our usecase, sensors are spread across California, Oregon, and Utah, and utilize various analytics plugins for tracking and responding to fire events across these states. The plugins used include, for example, cloud motion, wildfire smoke detection, and air pollution measurements. Composing these distributed sensors and services into data-driven workflows, in spite of the inherent uncertainties (e.g., availability of resources and data, data quality, etc.) remains a challenge -existing workflows require a workflow's control structure and data-flows to be statically defined. Furthermore, runtime mechanisms must optimize increasingly complex trade-offs between the costs associated with computations, data movement and analysis, etc., and satisfying application requirements for data quality and response times, in a very dynamic execution environment where the availability and status of resources is changing. Ongoing research continues to develop the R-Pulsar programming system and autonomic runtime to address these challenges toward the overarching goal of enabling urgent application workflows across the computing continuum.

V. CONCLUSION

In this paper, we explored how the emerging computing continuum composed of a spectrum of connected resources and services distributed across the logical extreme of the network and along the data path can enable new classes of dynamic data-driven urgent applications. Specifically, we illustrated how the programming abstractions and runtime mechanisms provided by the R-Pulsar programming system, along with services provided by the SAGE and WIFIRE platforms can potentially enable urgent computing across the computing continuum to support an application workflow that monitors and manage the air quality impacts of remote wildfires. We also discussed research challenges associated with programming urgent application workflows and managing resources in an autonomic manner.

Fig. 1 :

 1 Fig. 1: Monitoring and managing the air quality impact of wildfires -This driving urgent application usecase is designed using R-Pulsar to composed sensors provided by the SAGE platform align, wildfire data and model provided by the WIFIRE platform along with local pollution concentration maps, all distributed across the computing continuum.

Fig. 2 :

 2 Fig. 2: The R-Pulsar programming system provides content-and location-based abstractions for specifying (1) what data are collected and where the data are analyzed, (2) when to trigger data-processing tasks based on data patterns (spatial and temporal), and (3) what and where to invoke actions as a result of the triggers.

Fig. 3 :

 3 Fig. 3: A schematic overview of an edge-based middleware architecture to support application workflows across the edgecloud/HPC continuum.

https://www.anl.gov/article/new-sensing-platform-deployed-at-controlledburn-site-could-help-prevent-forest-fires

2 http://hpwren.ucsd.edu/cameras/

SAGE -Cyber Infrastructure for AI at the Edge -https://sagecontinuum. org/

Authorized licensed use limited to: IMT ATLANTIQUE. Downloaded on January 11,2024 at 10:34:28 UTC from IEEE Xplore. Restrictions apply.

Cloud2Things 2023: 3rd Workshop on From Cloud to Things: harnessing pervasive data in the Computing Continuum

ACKNOWLEDGEMENTS

This research is supported in part by the NSF under grant number OAC 2238064, OAC 1640834, OAC 1835692. The research was conducted as part of the SCI Institute at the University of Utah.


Georges Ha Van

Sophie Schuldiner

Ariane Sultan

Benjamin Bouillet

Jacques Martini

Julien Vouillarmet

Medhi Menai

Aurélie Foucher

Olivier Bourron

Agnes Hartemann

Georges Ha

Sophie Schuldiner2

Ariane Sultan3

| Benjamin

Jacques Martini8

Julien Vouillarmet9

| Medhi

| Aurélie Foucher10

| Olivier Bourron11

Agnes Hartemann11

Antoine Perrier1

Use of the SINBAD score as a predicting tool for major adverse foot events in patients with diabetic foot ulcer: A French multicentre study

Keywords: diabetic foot ulcer, major adverse foot event, SINBAD

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Results:

A low SINBAD score (from 0 to 3) was observed in 61% of patients and a high (from 4 to 6) in 39%. MAFE occurred in, respectively, 24% and 28% of these patients. Multivariate analyses showed a significant relationship between the SINBAD score and MAFE, with the continuous SINBAD score: odds ratio (OR) 1.72 [95% CI (1.51-1.97)] or dichotomic SINBAD score (values: 0-3 and 4-6): OR 3.71 [95% CI (2.54-5.42)]. The SINBAD score (continuous or dichotomic) at inclusion was also significantly associated with six out of the eight components of the MAFE.

Conclusions:

The SINBAD score is a useful tool for predicting major adverse foot events. Diabetic foot ulcer (DFU) is a huge public health problem, with an estimated cost of approximately $80 billion in 2017 in the United States.1 A multidisciplinary approach is recommended to resolve the variety of problems that arise in DFU management, often requiring offloading, infection treatment, septic surgery (SS), revascularisation, topical care, optimization of glycaemic control, and undernutrition prevention.2 Several studies have shown the effectiveness of this unified approach to diabetic foot care, which reduces amputation risk by 45%-55%. [START_REF] Edmonds | Improved survival of the diabetic foot: the role of the specialized foot clinic[END_REF][START_REF] Fusilli | Improvement of diabetic foot care after the implementation of the International Consensus on the Diabetic Foot (ICDF): result of 5-year prospective study[END_REF][START_REF] Krishnan | Reduction in diabetic amputations over 11 year in a defined UK population: benefits of multidisciplinary team work and continuous prospective audit[END_REF][START_REF] Canavan | Diabetes and nondiabetes related lower extremity amputation incidence before and after the introduction of better organized diabetes foot care: continuous longitudinal monitoring using a standard method[END_REF] The International Working Group of the Diabetic Foot (IWGDF) 2019 guidelines on DFUs concluded that key useful factors for scoring DFUs are of three types: patient-related (end-stage renal failure), limb-related (peripheral arterial disease (PAD) and loss of protective sensation), and ulcer-related (area, depth, site, single or multiple, and infection). [START_REF] Monteiro-Soares | Game F on behalf of the international working group on the diabetic foot (IWGDF). Guidelines on the classification of diabetic foot ulcers (IWGDF 2019)[END_REF] The site, ischaemia, neuropathy, bacterial infection, area, depth (SINBAD) scoring system (site, ischaemia, neuropathy, bacterial infection, area, depth), which includes six out of these eight factors, is an easy-to-use scoring system that can reach a maximum of six points (Supplemental Table 1) and is recommended by the IWGDF for the follow-up of patients with a DFU.7

The relationship between healing time and ulcer area, ulcer site, and PAD has been demonstrated. [START_REF] Ince | The association between baseline characteristics and the outcome of foot lesions in a UK population with diabetes[END_REF] The SINBAD score shows a clear step-up in time to healing between scores of 2 and 3, suggesting that DFUs with a score of 3 or greater are at particular risk of poor foot outcomes.9 The cut-off of the SINBAD severity score in relation to the prognosis for healing or amputation is around 3, and this scoring has been validated with good reliability and reproducibility for both ulcer healing and amputation prediction.7,10-23 However, the association between the SINBAD score and adverse events (AEs), such as the occurrence of infection, revascularisation, SS, hospitalisation, death, or ulcer recurrence, has never been studied.

The main objective of this study was to assess the relationship between the SINBAD score and the risk of occurrence of at least one major adverse foot event (MAFE), defined as a composite of eight AEs: hospitalisation, SS, revascularisation, minor amputation (MinA), major amputation (MajA), death, infection and ulcer recurrence. Our hypothesis was that a high score on the SINBAD, a system that is easy to use for non-specialists, would be a predictive factor for MAFE. The secondary objective was to assess the relationship between the SINBAD score and the occurrence of each of the eight AEs.

| METHODS

| Study design and data collection

This was an ancillary study of a retrospective study (COVIPIED) comparing DFU outcomes in terms of MAFE between two periods: period 1 from 1 February 2019 to 17 March 2019 with a follow-up period up to 1 August 2019 (cohort 1), and period 2: 1 from February 2020 to 17 March 2020 with a follow-up period up to 1 August 2020 (cohort 2). This second period included the COVID-19 lockdown, which lasted from 16 March to 11 May 2020, in France.

The data sources were the discharge databases and the medical records, and all collected data was anonymous. The patient data from the two cohorts were pooled for analysis.

The study received approval from the Ethics and Research Committee of Sorbonne University on 18 January 2021 (Protocol number CER-2020-99). Six French multidisciplinary diabetic foot care departments (DFCDs) participated in this multicenter study (Montpellier, Dijon, Nimes, Lyon, Toulouse, and Paris). The inclusion criteria were as follows: patients over 18 years old with a DFU evolving for fewer than 12 months. The exclusion criteria were as follows: leg or malleolar ulcer; a wound secondary to MinA of less than 4 weeks; missing data on age, gender, body mass index (BMI) and SINBAD score; and lost to followup on 1 August 2019 (cohort 1) or 1 August 2020 (cohort 2).

All successive outpatients attending a DFCD with these criteria were included. In the case of two DFUs, the oldest one was included. The DFUs were clinically checked during monthly consultations. All patients received DFU management in accordance with the guidance recommendations.24

The collected data included age, sex, history of DFU, duration of diabetes, BMI, HbA1c, insulin therapy, and end-stage renal disease. The SINBAD score was assessed at inclusion (arrival at the DFCD).

The SINBAD score9 was calculated with six factors graded from 0 to 1: site, ischaemia, neuropathy, bacterial infection, area, and depth (Supplemental Table 1). The ulcer site was scored as 0: for forefoot (distal to tarso-metatarsal joint) or 1: for midfoot or hind foot. Ischaemia was scored as 0: at least one pulse palpable (blood flow relatively intact on the affected foot) or 1: no pulse palpable with signs of poor perfusion (cold feet, skin discolouration, slower hair growth, swelling, cramping) with or without gangrene. Neuropathy, or loss of protective sensation on the basis of examination using 10-g nylon monofilaments, was scored as 0: absent or 1: present. Bacterial infection, defined as clinical signs of infection of either soft tissues or bone (as proposed by the infectious disease society of america (IDSA) and IWGDF), was scored as 0: absent or 1: present). Area, or the two maximum dimensions at right angles multiplied, was scored as 0: <1 cm2 or 1: >1 cm2. Last, depth was scored as 0: superficial or 1: deep-reaching muscle, tendon, joint capsule or bone. The SINBAD score was obtained by summing the components of the classification, creating a SINBAD score range of 0-69 (Supplemental Table 1).

Every AE was related to the original DFU.

| Definitions of outcomes

A MAFE was defined as a composite outcome consisting of the occurrence of at least one of these eight AEs in relation to the initial DFU: hospitalisation (H), SS, revascularisation (Rev), MinA, MajA, death (D), secondary infection (SI), and DFU recurrence (Rec).

Secondary infection of the initial DFU was defined as purulent discharge with two other local signs (warmth, erythema, lymphangitis, lymphadenopathy, oedema, or pain) or cellulitis during follow-up and was classified according to the IDSA-IWGDF classification: grade 2, 3 or 4.24 Hospitalisation (H) was defined as hospitalisation during followup in the case of a DFU that had become complicated with wet gangrene, abscess, fever, signs of sepsis, critical limb ischaemia and the need for revascularisation, SS (soft tissue and/or bone), or parenteral antibiotic therapy.

Septic surgery was defined as soft tissue infection surgical debridement of the initial DFU with or without bone resection during follow-up. This could range from minor bedside debridement or incision and drainage to major operative procedures including resection of deep infected tissue, drainage of abscesses or infected compartments, and resection of necrotic or infected bone in accordance with IWGDF 2019 recommendations.25 Revascularisation (Rev) was defined as percutaneous transluminal angioplasty or bypass during the follow-up provided to improve healing of the initial DFU. In accordance with IWGDF recommendations, we considered vascular imaging to assess the need for revascularisation in a patient with DFU and PAD, irrespective of the results of bedside tests, when the DFU had not healed within 4-6 weeks despite optimal management.26 Recurrence (Rec) of DFU was defined as recurrence at the same DFU localization. Amputation was defined as the complete loss in the transverse anatomical plane of any part of the lower limb. Minor amputation was defined as removal of a part of the foot distal to the transverse tarsal joint with preservation of the talus and calcaneus (Chopart, Lisfranc, total or partial transmetatarsal or toe amputations), whereas MajA was defined as above ankle amputation (transtibial or transfemoral).

| Statistical analyses

Continuous and categorical variables are summarised as means +/standard deviation (SD) and percentages, respectively.

Potentially co-founding factors (as listed in the baseline characteristics section) between MAFE and its component and SINBAD and its component were initially identified through bivariate analyses and selected for multivariate logistic analyses [expressed as odds ratios with 95% CI] if p < 0.2.

Multivariate logistic models were constructed independently for each MAFE component and for the occurrence of at least one of its components, meaning each model had a different set of covariables. Age, sex, and BMI were included in each model. All statistical analyses were performed using SAS version 9.4 software (SAS Institute, Cary, NC, USA).

| Baseline characteristics

Baseline characteristics of patients and SINBAD scores at inclusion are shown in Table 1. The average age was 69.0 +/-12.4 years with 75.8% men. SINBAD groups 0-3 and 4-6 did not differ for age (68.8 years old vs. 69.3, p = 0.64), diabetes duration (21.0 years vs. 21.6, p = 0.60), history of ulcers (72% vs. 65.8%, p = 0.14), insulin treatment (69.2% vs. 76.7%, p = 0.06) and HbA1c (8% vs. 7.9%, p = 0.45), but the SINBAD group 0-3 comprised less men (72.3% vs. 81.3%, p = 0.02), had higher BMI (29.1 vs. 27.6, p = 0.001) and had less haemodialysis (10.6% vs. 18.6%, p = 0.01).

No interaction was found between MAFE and the SINBAD score with patient characteristics.

The average SINBAD score was 3 +/-1.5. A low SINBAD score (from 0 to 3) was found for 61% (n = 329) of the patients and a high SINBAD score (from 4 to 6) for 39% (n = 208) (Table 1). Major adverse foot events occurred, respectively, in 24% (n = 130) and 28% occurred, respectively, in 24% (n = 130) and 28% (n = 149) of these patients (Table 2). Table 2 also shows every AE per SINBAD score and the SINBAD 0-3 and 4-6 subgroups.

| Association between SINBAD score and major adverse foot event risk

The mean rate of MAFE was 52% (n = 279). The mean rate of separate AEs within the follow-up period (with a range of patient data between 473 and 530) were as follows: hospitalisation: 27% (n = 143), SS: 8.8% (n = 46), revascularisation:15.2% (n = 78), MinA:15.6% (n = 82), MajA: 7% (n = 37), SI: 38.4% (n = 188), death: 4.5% (n = 23), and recurrence: 4.2% (n = 20).

Multivariate analysis showed a positive association between a continuous SINBAD score and MAFE. If the SINBAD score increased by one unit (e.g., when the patient moved from 2 to 3 or from 5 to 6), this one-unit increase was significantly associated with an increased risk of MAFE (1.72 CI [1.51-1.97] (Table 3). In addition, there was a significant association between a continuous SINBAD score and an increased risk of six out of eight separate AEs (except for death and DFU recurrence): hospitalisation (1.29; CI [1.12-1.47]), SS (1.46 3).

Furthermore, multivariate analysis also showed a positive association between a dichotomic SINBAD score and MAFE. The comparison of the two groups of SINBAD scores (0-3 and 4-6) showed that the 4-6 SINBAD group was significantly associated with an increased risk of MAFE (3.71 CI [2.54-5.42]) (Table 3) along with a positive association between the dichotomic SINBAD score and the risk of six out of eight separate AEs (except for death and DFU recurrence): hospitalisation (1.87 [1.24-2.80]), SS (2.89 [1.42-5.90]), revascularisation (5.21 [2.83-9.60]), MinA (2.89 [1.75-4.78]), MajA (7.98 [3.19-19.93]), and SI (5.56 [3.65-8.46]) (Table 3).

| Multivariate logistic association between SINBAD components and AEs of patients with DFU23

There were significant associations between four SINBAD score components and AE (Supplemental table 2).

-Site (score 1: midfoot/hindfoot) and major amputations (2.63 [1.19-5.82]).

-Ischaemia (score 1: signs of ischaemia) and MAFE (1.97 [1.31-2.98]), hospitalisation (2.03 [1.31-3.14]), revascularisation (9.19 [4.35-19.4]), MinA (2.01 [1.15-3.50]), MajA (3.67 [1.42-9.47]), and death (3.05 [1.12-8.36]).

-Bacterial infection (score 1: present) and MAFE (4.47 [2.70-7.41]), hospitalisation (1.91 [1.09-3.34]), SS (2.97 [1.07-8.26]), revascularisation (2.32 [1.00-5.37]), MinA (5.34 [2.38-11.98]), and SI (6.66 [3.75-11.81]).

-Area (score 1: >1 cm2) and revascularisation (2.21 [1.14-4.30]), MajA (3.17

| DISCUSSION

To our knowledge, this is the first multicenter study that has explored the association between the SINBAD score and secondary MAFE in patients with DFU. We highlighted a strong significant association between the SINBAD score (continuous or dichotomic: 0-3 and 4-6) at inclusion and MAFE risk. We defined this composite outcome including eight classic MAFE: hospitalisation, SS, SI, revascularisation, MinA, MajA, ulcer recurrence, and death.

Until now, the validity of the SINBAD score has relied on its association with the chance of ulcer healing and the risk of MajA.15 A SINBAD score <3 is associated with a healing rate of 60% at 12 weeks compared with 35% if the score is > 3, and a risk of MajA at 6 months of 2.7% versus 0.7%.23 A 2021 study27 found a 100% healing rate in patients with a SINBAD score of 0 versus 49% in patients with a SINBAD score of 6, with a stepwise decrease in the proportion of ulcers healing with each increase in the score. DFUs classified into SINBAD category 4 were 28%, SINBAD 0: 0.7% and SINBAD 1: 4.5%.27 Furthermore, Alasabeck et al. showed a median healing time of 14 weeks in patients with a SINBAD score ≥3 and 4 weeks in patients with a SINBAD score ≤ 2.28 Two recent studies found that a high SINBAD score was associated with the presence of DFU infection with extended-spectrum beta-lactamase (ESBL)-producing bacteria29 or Meti-R Staph aureus. [START_REF] Prompers | Prediction of outcome in individuals with diabetic foot ulcers: focus on the differences between individuals with and without peripheral arterial disease. The EURODIALE Study[END_REF] In 2019, the IWGDF issued a strong recommendation to use the SINBAD system for communications among health professionals on the characteristics of a foot ulcer in a person with diabetes. For this purpose, it is important to use the individual clinical descriptors and not merely the total score. This classification has been validated for both ulcer healing and amputation prediction. [START_REF] Monteiro-Soares | Game F on behalf of the international working group on the diabetic foot (IWGDF). Guidelines on the classification of diabetic foot ulcers (IWGDF 2019)[END_REF] Our results showed that the SINBAD score is also useful to predict relevant MAFE. We explored this association using a composite outcome MAFE. One unit of the score increased the risk of MAFE by 1.7. Patients with a SINBAD score of 4-6 had an increased risk of MAFE of 3.7 compared with patients with a SINBAD score 0-3. These data reinforce the usefulness of this score.

The population was representative of the usual patients seen in specialised DFU centres, who generally have a rather high average SINBAD score. Mortality rate and minor and MajA rates were similar to what is described in the literature. [START_REF] Van | Diabetic foot ulcer management in a multidisciplinary foot centre: one-year healing, amputation and mortality rate[END_REF][START_REF] Prompers | Prediction of outcome in individuals with diabetic foot ulcers: focus on the differences between individuals with and without peripheral arterial disease. The EURODIALE Study[END_REF][START_REF] Morbach | Long-term prognosis of diabetic foot patients and their limbs: amputation and death over the course of a decade[END_REF][START_REF] Jeffcoate | Assessing the outcome of the management of diabetic foot ulcers using ulcer-related and person-related measures[END_REF] The SINBAD score during follow-up was associated with a significant increased risk of hospitalisation, SI, revascularisation, SS, and, as already known, minor and major amputations. The short duration of follow-up probably explains the absence of an association with death and ulcer recurrence. Mortality is often associated with the presence of a DFU, but only after a long follow-up.33,34 A recent study with a median follow-up of 8 years demonstrated that the SINBAD score is a predictor of mortality.35 Although DFU is not the direct cause of death (which is instead due to associated comorbidities such as PAD, endstage renal disease, coronary heart disease, stroke), some authors consider that it is an independent risk factor for mortality.1

Our study also confirmed in more than 500 patients that the components of the SINBAD score were relevant. [START_REF]Fourth Annual Report[END_REF] Ischaemia and infection at DFU presentation were associated with MAFE and five of the components of MAFE. This showed the predominance of these two components of the SINBAD score in the prognosis of the severity in DFU management. We should note that one of the weaknesses of the SINBAD score is that it attributes the same scores for ischaemia and infection and neuropathy and area or depth. Site, ischaemia, and area predicted the risk of MajA. Surprisingly, we found no independent association of depth with MAFE or any of the MAFE components, whereas in one study, depth was the only common item among multiple centres to be associated with outcome.9

As specified by the IWGDF 2019 guidelines, the interest of the SINBAD score lies in its ability to provide indications of the prognosis of the DFU. The six items of the SINBAD score describe rather well the usual characteristics of the severity of DFUs. In 2008, the authors of one study concluded that the SINBAD score may offer a system for defining the DFU type that could be applied worldwide.9. The objective of the present study was to use SINBAD system, noted for its simplicity, to evaluate its relevance to predict outcomes, even in poorly equipped centres. For non-specialists, diabetes alone is often considered responsible for secondary AEs.

The International Diabetic Foot Care Group, in collaboration with DFoot International, developed the Fastrack Pathway (FTP), which proposes practical integrated treatment, spanning primary care and dedicated diabetic foot services. In the UK, the SINBAD score is used in the English version of the FTP. [START_REF] Meloni | Fast-track pathway: an easy-touse tool to reduce delayed referral and amputations in diabetic patients with foot ulceration[END_REF] The composite outcome MAFE might complete the usefulness of the SINBAD score, just as composite major adverse cardiovascular event (MACE) does in the chest pain of cardiovascular patients. [START_REF] Backus | A prospective validation of the Heart score for chest pain patients at the emergency department[END_REF] The limitations of our study included a short follow-up period, a retrospective design, and the absence of information on ulcer healing. Also, of the 713 cases, only 75% were included in the study and this may have resulted in selection bias. Further, recruitment was limited to specialised DFU centres, meaning that generalizations should be made with caution (particularly with regard to the checking of ischaemia, which can easily be much more precise than simple pulse taking and the clinical aspect in these six DFU specialised centres). The strengths of our study were the multicenter aspects, the large number of patients, and the variety of AEs studied. We showed that the SINBAD score could be used beyond the simple prognosis of healing and amputation to assess the risk of MAFE in a study where not only were the demographics consistent with the literature but also the SINBAD scores were rather high.

  [1.21-8.34]), and death(3.11 [1.08-8.98]).

The SINBAD scoring system is simple and quick to use, not requiring special equipment beyond clinical examination alone and containing the necessary information to allow for triage by a specialist team.

We showed that the SINBAD score can be used by clinicians beyond the simple prognosis of healing and amputation to assess the risk of MAFE, since each unit of SINBAD and a score > 4 were associated with an increased risk of MAFE and most of its components.

Furthermore, for DFU management, we propose to use a composite outcome MAFE, which is similar to MACE in patients with cardiovascular risk.

ACKNOWLEDGEMENTS

Georges Ha Van is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

ETHICS STATEMENT

The authors declare that they adhere to the recommendations of the Wiley Publishing ethics guidelines: Declare to your chosen journal that your manuscript is not published elsewhere. Check all co-authors meet criteria for authorship and ensure appropriate acknowledgements made in the manuscript. Include appropriate funding statements in the manuscript. Show informed consent and provide assurances that participants' rights are protected*. Register clinical trial: The study received approval from the Ethics and Research Committee of Sorbonne University on 18 January 2021 (Protocol number CER-2020-99). Be alert to bias and follow guidelines for accurate and complete reporting of research. Inform the journal if you subsequently find errors in your research. Sign a copyright agreement.

AUTHOR CONTRIBUTIONS

Georges Ha Van had full access to all the data in the study and wrote the article. Antoine Perrier, Medhi Menai independently extracted the related data information. Georges Ha Van, Antoine Perrier, Aurélie Foucher, Medhi Menai conceived the study concept and design. Georges Ha Van, Benjamin Bouillet, Ariane Sultan, Sophie Schuldiner, Jacques Martini, Julien Vouillarmet included patients of the study. Georges Ha Van, Sophie Schuldiner, Ariane Sultan, Jacques Martini, Julien Vouillarmet, Benjamin Bouillet, Olivier Bourron, Aurélie Foucher, Agnes Hartemann, Antoine Perrier, Medhi Menai contributed to the critical revision of the manuscript. All authors have read and approved the final manuscript.

CONFLICT OF INTEREST STATEMENT

The authors have declared no potential conflict of interest relevant to this article.


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