SEARCH FOR DECOMPENSATION RISK FACTORS WITHIN THE EGPRN MULTIMORBIDITY'S DEFINITION THEMES. COHORT PILOT STUDY, FOLLOW UP AT 18 MONTHS IN NURSING HOME

Background :

Chronic diseases are widely expanding, notably because of ageing population. Actual practice guidelines basing on a disease approach are not suitable anymore. Multimorbidity and its outcomes heavily matter, especially in Nursing Homes (NH) residents. Management of multimorbidity has become a daily challenge for General Practitioners (GPs). This study's objective was to highlight some risk factors of decompensation of multimorbidity.

Methods :

A prospective cohort study was carried out in Lanmeur's NH from July 2014 to December 2015. Patients matching the European General Practitioners Research Network (EGPRN)'s definition of multimorbidity were included. Decompensation corresponded to death or a hospitalization lasting at least seven successive days. Eighteen months after inclusion, patients were classified in two groups, "Decompensation" ("D") or "Nothing to Report" ("NTR"), depending on their status. A logistic regression following a Cox model was performed to identify potential risk factors.

Results :

64 patients were included. After eighteen months, 31 belonged to the group "D" and 33 to the group "NTR". The multivariate analysis using a Cox's model, brought out two variables statistically significant : pain (Hazard Ratio (HR) = 2.18; 95% CI [1.07-4.44], p-value= 0.012) and unhealthy lifestyle (no healthy diet, physical activity nor correct hygiene) (HR= 2.53 ;], p=0.033).

Conclusion:

Pain and unhealthy way of life were suggested to increase the risk of death or hospitalization among the multimorbid elderly living in nursing homes. More powerful studies are needed to confirm these findings after some methodological adjustments.

REMERCIEMENTS

A Monsieur le Professeur Jean-Yves Le Reste, merci de m'avoir guidée, accompagnée et soutenue dans cette nouvelle aventure de recherche. Merci pour votre patience et votre gentillesse, merci d'avoir résisté à notre névrose obsessionnelle à Brest et sur les routes de France et de Navarre. Et encore merci de me faire l'honneur de présider ce jury. Soyez assuré de ma profonde considération et de mon amitié.

A Monsieur le Professeur Bernard Le Floc'h, merci de me faire l'honneur de faire partie de ce jury. Merci de nous avoir initiées à la recherche en médecine générale, de nous avoir fait découvrir les villes de Tours et Nice, d'avoir cru en nous. Soyez assuré de ma reconnaissance et de mon profond respect.

A Monsieur le Docteur Benoît Chiron, merci aussi de nous avoir initiées à la recherche en médecine générale. Merci de nous avoir accompagnées à Nice et fait partager ces bons moments. Merci d'avoir été mon tuteur tout au long de cet internat. Merci enfin de me faire l'honneur de faire partie de ce jury. Sois assuré de ma sincère reconnaissance et de mon profond respect.

A Madame le Docteur Delphine Le Goff, merci pour votre présence au sein de ce jury. Merci pour votre implication dans la formation des étudiants. Soyez assurée de ma grande considération.

A Madame Florence Gatineau, merci pour ce remarquable travail statistique accompli au pied levé. Merci pour les tous efforts que vous avez fournis pour nous, pour avoir répondu à nos innombrables questions et pour votre aide précieuse. Soyez assurée de ma profonde reconnaissance.

A Véro, la plus belle rencontre de mes études. Merci pour tous nos moments, les bons comme les moins bons, les fous rires, les larmes, la joie, le stress, le travail, les soirées, le binge drinking, nos appels interminables, ton soutien indéfectible, ta motivation communicative, ton énergie, tes précieux conseils et tout ce que nous partageons depuis ces années. Que tu sois ma co-thésarde n'était qu'une évidence, merci d'être toi.

A Alain, merci d'être à mes côtés, de m'apporter tant d'amour, de me soutenir dans tout ce que j'entreprends, de me faire progresser toujours un peu plus, de m'épauler dans les moments difficiles, d'illuminer ma vie de jour en jour. Avec tout mon amour.

A Aloïs, le deuxième homme de ma vie, ton arrivée a bouleversé ma vie et me donne envie de me surpasser. Merci pour l'infini bonheur que tu nous apportes.

A mes parents, merci d'avoir cru en moi et mes capacités, de m'avoir aidée à réaliser ce rêve, d'être toujours là pour moi en toutes circonstances.

A mon frère, ma soeur et Aude, merci pour votre soutien tout au long de ces études, pour m'avoir poussé à m'aérer l'esprit quand il le fallait et pour tout l'amour qui unit notre famille.

A Mamie, merci pour nos innombrables cafés, nos longues discussions, ta présence et ton soutien. Avec mon profond amour.

A Papy et Grand-mère, je sais que vous n'êtes pas loin, avec mon profond amour.

A ma belle-famille, merci pour votre soutien, la confiance que vous me portez et tous les bons moments passés ensemble.

A mes oncles et tantes, mes cousins et mes cousines, vous tous qui formez ma grande famille, merci.

A mes amis, merci pour les joies partagées ensemble, les soirées, les séances de papotage, de shopping et les bons moments à venir. Merci à toi Laure, particulièrement, pour m'avoir aidée à améliorer mon anglais et me faire divaguer vers d'autres sphères. Au Docteur Beyssey, merci Alain de m'avoir illustré ce qu'est l'humanité dans notre métier, merci pour tes encouragements et pour ton réconfort dans les moments de doute.

Merci à vous

A mes maîtres de stage et collègues, merci de m'avoir transmis vos savoirs et fait partager votre expérience, merci de m'avoir donné une formation de qualité.

A Buffy, Docteur House, Grey's Anatomy, Clark Kent, merci de m'avoir fait rêver ou souffler sans trop culpabiliser. Au handball, à Jean-Jacques Goldman et Patrick Bruel, au FCLP, parce qu'il n'y pas que la médecine dans la vie !

TABLE OF CONTENTS

Introduction :

Les pathologies chroniques sont en pleine expansion, notamment du fait du vieillissement de la population. Les recommandations de bonnes pratiques actuelles basées sur l'approche par maladie ne sont plus adaptées. La multimorbidité et ses conséquences négatives ont de lourdes répercussions, en particulier dans les Etablissements d'Hébergement des Personnes Agées Dépendantes (EHPAD). La prise en charge de la multimorbidité est devenue un challenge quotidien pour les médecins généralistes. L'objectif de cette étude était d'identifier des facteurs de risque de décompensation de la multimorbidité.

Méthode :

Une étude de cohorte prospective a été menée à l'EHPAD de Lanmeur de juillet 2014 à décembre 2015. Les patients correspondant à la définition de la multimorbidité de l' European General Practitioners Research Network (EGPRN) ont été inclus. La décompensation était définie par le décès ou une hospitalisation durant au moins 7 jours consécutifs. Dix-huit mois après l'inclusion, les patients étaient répartis selon leur statut en deux groupes, "Décompensés" ("D") ou "Rien à Signaler" ("RAS"). Une régression logistique suivant le modèle de Cox était réalisée pour identifier les facteurs de risque potentiels.

Résultats

Conclusion :

La douleur et la mauvaise hygiène de vie semblent augmenter le risque de décès ou d'hospitalisation chez les personnes âgées multimorbides résidant en EHPAD. Des études plus puissantes menées à plus grande échelle sont nécessaires avec quelques ajustements méthodologiques pour confirmer ces résultats.

INTRODUCTION

Diseases are called chronic when they are permanent, caused by irreversible pathological alteration or if they required rehabilitation or a long duration of care. Prevention and control of chronic diseases, sometimes also designed as Non Communicable Diseases (NCDs), have become a high priority for the World Health Organization (WHO) since 2000 [START_REF]Global strategy for the prevention and control of noncommunicable diseases[END_REF].

Their management is an integral part of General Practice. Although clinical practice guidelines aimed to improve the quality of health care, numerous publications demonstrated that they weren't appropriate for patients suffering for several chronic diseases (2-8). To deliver the best possible care, those patients need a person-focused approach rather than a disease-focused approach. This holistic perspective is one of the six fundamental competences of the European definition of the family medicine set by the World Organization of National Colleges, Academies and Academic Associations of General Practitioners/Family Physicians (WONCA) (9).

In this context, the concept of multimorbidity became more and more pertinent. It arose in Germany in 1976 [START_REF] Brandlmeier | Multimorbidity among elderly patients in an urban general practice[END_REF] and was recognized on the international scale in 1990 [START_REF] Heuft | Future research perspectives of a psychoanalytical gerontopsychophysiology-personality and the aging process[END_REF]. In 2008, the WHO defined multimorbidity as people suffering from two or more chronic conditions [START_REF]The World Health Report 2008. Primary Health Care-Now more than ever[END_REF]. But it lacked of precision according to the variable prevalence of multimorbidity found in several systematic reviews of studies on the subject [START_REF] Violan | Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies[END_REF][START_REF] Fortin | A systematic review of prevalence studies on multimorbidity: toward a more uniform methodology[END_REF][START_REF] Marengoni | Aging with multimorbidity: a systematic review of the literature[END_REF]. In 2012, the European General Practitioners Research Network (EGPRN) brought the following comprehensive definition of multimorbidity after a systematic review of literature: « Multimorbidity is defined as any combination of chronic disease with at least one other disease (acute or chronic) or biopsychosocial factor (associated or not) or somatic risk factor.

Any biopsychosocial factor, any risk factor, the social network, the burden of diseases, the health care consumption, and the patient's coping strategies may function as modifiers (of the effects of multimorbidity). Multimorbidity may modify the health outcomes and lead to an increased disability or a decreased quality of life or frailty. » [START_REF] Reste | The European General Practice Research Network Presents a Comprehensive Definition of Multimorbidity in Family Medicine and Long Term Care, Following a Systematic Review of Relevant Literature[END_REF] The EGPRN aimed to help the European family doctors to finger on the multimorbid patients they take care of so they translated the definition into ten European languages then [START_REF] Reste | The European General Practice Research Network Presents the Translations of Its Comprehensive Definition of Multimorbidity in Family Medicine in Ten European Languages[END_REF].

Multimorbidity heavily matters because it leads to reduced quality of life, higher mortality, increases disability and dependence, polypharmacy and high treatment burden. It increases significantly the healthcare cost by augmenting the use of health services, the emergency hospital admission rate and the postoperative complications rate [START_REF] Glynn | The prevalence of multimorbidity in primary care and its effect on health care utilization and cost[END_REF][START_REF] Wolff | Prevalence, expenditures, and complications of multiple chronic conditions in the elderly[END_REF][START_REF] Prince | The burden of disease in older people and implications for health policy and practice[END_REF][START_REF] France | Multimorbidity in primary care: a systematic review of prospective cohort studies[END_REF][START_REF] Fortin | Multimorbidity and quality of life in primary care: a systematic review[END_REF][START_REF] Rizzuto | Effect of Chronic Diseases and Multimorbidity on Survival and Functioning in Elderly Adults[END_REF]. Management of multimorbidity appears thus as a crucial health challenge [START_REF] Violan | Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies[END_REF][START_REF] Starfield | Global health, equity, and primary care[END_REF][START_REF] Moffat | Challenges of managing people with multimorbidity in today's healthcare systems[END_REF][START_REF]Multimorbidity: clinical assessment and management. Multimorbidity: assessment, prioritisation and management of care for people with commonly occurring multimorbidity[END_REF].

Better socio-sanitary conditions associated with medical and technologic advancements have conducted to a lifespan extension. Combined with the decline of the fecundity rate (25), population is ageing. On 1 January 2017, 66.991 million people lived in France. 19.2% of them were 65 years old or more. According to the projections, a person over four would be 65 or more in 2040 [START_REF]Population par âge[END_REF]. The prevalence of multimorbidity increases considerably with age and most of people aged 65 or more are multimorbid [START_REF] Violan | Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies[END_REF][START_REF] Marengoni | Aging with multimorbidity: a systematic review of the literature[END_REF][START_REF] Barnett | Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study[END_REF][START_REF] Marengoni | Prevalence of chronic diseases and multimorbidity among the elderly population in Swedern[END_REF]. Hence, detect the key determinants of multimorbidity is necessary for the development of effective strategies for the early identification of patients at risk and for the prevention of future health condition.

From 2010 to 2014, several medical theses carried out by students in Brest aimed to highlight the factors of multimorbidity and then gather them in themes from the EGPRN's definition [START_REF] Bodin | Critères de définition de la multi-morbidité en médecine générale: étude qualitative par entretiens individuels semi-dirigés avec les maîtres de stage des universités brestois[END_REF][START_REF] Derrienic | Quels sont les critères de multi-morbidité reconnus par les médecins généralistes ? Diffèrent-ils de la littérature ?[END_REF][START_REF] Daraban | La multimorbidité -les différences entre la théorie et le vécu des médecins généralistes[END_REF][START_REF] Franck | Quels sont les critères de la définition de la multi-morbidité pour les médecins généralistes ?[END_REF][START_REF] Vince | Quels sont les critères de la définition de la multi-morbidité pour les médecins généralistes ?[END_REF][START_REF] Lometti | Quels sont les critères de multimorbidité reconnus par les médecins généralistes ? Diffèrent-ils de ceux de la revue de la littérature ?[END_REF][START_REF] Hemidy | Quels sont les critères de la définition de la multi-morbidité pour les médecins généralistes ?[END_REF][START_REF] Mao | Critères de la définition de la multi-morbidité en médecine générale[END_REF]. 13 themes were identified. Basing on these qualitative works, a quantitative study was carried out to find out the risk factors of decompensation among the multimorbidity's themes.

Considering the important prevalence of multimorbidity in the aged patients, a cohort of persons living in nursing home (NH) seemed appropriate and was chosen for the study.

A pilot study was first performed in 2015 to check the feasibility of the cohort study in NH [START_REF] Colleter | Etude pilote de faisabilité d'une étude de cohorte en soins primaires en établissement d'hébergement pour personnes âgées dépendantes (EHPAD) à la recherche de facteurs de risque de fragilité parmi les différents thèmes de la définition de la multi-morbidité[END_REF]. The objective was also to highlight the significant predictors of decompensation on multimorbid patients. This study focused on the same cohort after eighteen months of follow-up.

The research hypothesis supposed that most of institutionalized patients responded to the EGPRN's definition of multimorbidity. And among the factors of multimorbidity brought out of the previous theses, some would be risk factors of decompensation. If those factors are known, they could be quickly recorded and properly managed to prevent decompensation (hospitalization or death).

The main objective of this study was to highlight the risk factors of decompensation within the multimorbid EGPRN's definition themes. The second objective was to relate the difficulties faced during the study.

METHODS

Study design

A feasibility pilot study was led at the outset with the patients residing in Lanmeur's nursing home. It was developed into a prospective study with a contemporary, fixed and specific cohort.

The setting alpha level was of 5% and the beta level was of 20% using a non-symmetrical sample (75% -25%). With the expected difference on the significant variables of 20% it required 127 subjects.

Recruitment lasted six months. 64 patients were enrolled on the 127 expected. Patients were monitored over time every three months. This survey handles the following of the same cohort at eighteen months.

Study population

It was the same population as in the feasibility pilot study. It comprised all the multimorbid patients (according to the EGPRN definition of the multimorbidity), residing in Lanmeur's nursing home. Moreover, their GP had to work in the university primary care center of Lanmeur.

Patients could be included if they matched the criteria of the definition of multimorbidity according to the EGPRN definition: any combination of chronic disease with at least one other disease (acute or chronic) or a bio psychosocial factor (associated or not) or a somatic risk factor. For the research team, bio psychological factors took into account psychological risk factors, psychosocial risk factors, lifestyle, demographics (age, gender), psychological distress, socio-demographic characteristics, aging, beliefs and expectations of patients, physiology, pathophysiology [START_REF] Reste | The European General Practice Research Network Presents a Comprehensive Definition of Multimorbidity in Family Medicine and Long Term Care, Following a Systematic Review of Relevant Literature[END_REF].

Patients not meeting the criteria of the definition of multimorbidity, patients who should not be followed up over time during the study, patients for whom prognosis vital was committed or life expectancy was estimated less than three months and patients undergoing legal protection were excluded.

Study conduct

The team contacted the GPs practicing in the university center of Lanmeur to participate in the study by email. If they agreed they became investigators.

Inclusion criteria were checked by the team to select patients. Then, they had a conversation with each patient about the study.

Potential risk factors of decompensation were gathered by filling a questionnaire. This one was pre-filled by the team after accessing to the medical record and then was completed by the GPs.

Data were anonymous: a number was given to each patient corresponding to the inclusion order in the cohort. The patient's status was examined every three months and they were categorized in the group "decompensation" ("D") or "nothing to report" ("NTR"). Death or a hospitalization seven successive days or more defined a decompensation.

Then, the team analysed the patients' characteristics from multimorbidity themes and subthemes and compared the two groups in order to identify some risk factors of decompensation. A questionnaire and a guide for its filling (Appendix 1) were written to collect these variables basing on the axial and thematic coding used to develop the definition of multimorbidity [START_REF] Daraban | La multimorbidité -les différences entre la théorie et le vécu des médecins généralistes[END_REF].

The qualitative notions extracted from the multimorbidity themes and sub-themes were turned into quantitative factors to help the data collection after the fulfilment of the questionnaire and to limit confusion.

The variables « cardiovascular risk factor », « fall risk factor », « assessment of hygiene », « assessment of feeding » and « assessment of physical activity » extracted from the coding book were used to assess the concept of somatic risk factor. The fall risk was calculated using the CETAF score [START_REF] Prince | The burden of disease in older people and implications for health policy and practice[END_REF].

The variables « chronic condition, cost of care, disability, quality of life, health outcome, frailty, physiology, disease and assessment, demography and aging » were redundant or impossible to evaluate. So they were crushed.

This questionnaire was validated by peer group.

Judgment criteria

The primary endpoint was decompensation during the eighteen-months follow up. The definition of decompensation was established in peer group including doctors, residents and researchers in primary care on multimorbidity. It was death or a hospitalization lasting at least seven successive days.

The secondary criterion was the difficulties experienced during the study process.

Data cleaning

Data were saved using Microsoft Excel. Two distinct groups were identified: one group "Decompensation" ("D") and a second group "Nothing To Report" ("NTR"). The team preferred those denominations to "frail" and "not frail" because of the risk of confusion with the concept "frailty". Indeed, the definition of "frailty" wasn't approved unanimously between the Fried's physical approach and the Rockwood's frailty concept.

A data cleaning was operated before statistical analysis to homogenize data. A "dictionary" (Appendix 2) gathering all the modifications and the meaning of the abbreviations was established. Some diseases were assembled into one entity such as osteoarticular diseases. Some were effaced and some others such as transient ischemic attack or osteopenia were reconsidered as a risk factor and not a disease.

Statistical analysis a. Clustering and classification

Firstly, some significance tests variables were performed to compare the "D" and "NTR" groups. For qualitative variables, a Fischer's exact test or a Chi 2 test, depending on the number of patients concerned, was fulfilled with an alpha level at 5% and a beta level at 20%. For quantitative variables, a Student test or a Wilcoxon/Man Whitney test was achieved with the same risk levels to compare means or medians between the two groups.

Secondly, a clustering was performed to describe the multimorbid population: patients sharing common characteristics were gathered in homogenous groups without taking into account their status at eighteen months. The first stage of the clustering consisted in a dissimilarity measure with Euclidian distance calculation and a hierarchical clustering using the Ward method. The result appeared as a cluster dendrogram (i.e a classification tree to observe the hierarchy of groups).

Then, a Multiple Correspondence Analysis (MCA) was used to select among all the variables, the significant variables to describe each group (active variables) by transforming categorical variables into a set of few continuous variables. It removed the non-discriminating ones and the one related to the quality of care for the multimorbidity and the GPs' self-evaluation. Illustrative variables assisted in the interpretation of active variables after their projection onto the dimensions. It allowed to assess the differences and the resemblances between the individuals, to group the variables, and assess the differences and the resemblances between modalities. At the end, some profiles emerged.

Finally, clusters were obtained thanks to the Hierarchical Clustering on Principal Components (HCPC) approach and could be projected onto a MCA factor map.

b. Survival analysis and multivariate regression

For the survival analysis, time must be considered because the follow up was not the same for all patients as they did not decompensate at the same moment. A logistic regression following the Cox's model was the most suitable for this analysis. It assessed the supplementary risk bring by the exposition to a risk factor while considering the probability of occurrence of decompensation at all times of the follow up.

The Kaplan-Meir method, a non-parametric estimation assessing the survival function from the data, gave the survival curves of the "D" and "NTR" groups.

To find out if the two groups were significantly different, a univariate analysis consisting in a log-rank test with a p-value level of 0,05 was performed.

Then, a semi parametric assessment using the Cox's method gave unrefined Hazard Ratios (HR)

and their 95% confidence intervals (CI) (univariate analysis). They corresponded to the association between a variable and the decompensation risk factor, taking account of the time.

And after, a second Cox model was applied to obtain the adjusted HR (multivariate analysis)

and their 95% CI. The adjusted HR corresponded to the association between a variable and the decompensation risk factor after adjusting some others variables (age, sex…). The interest was to avoid confusion factors.

At the end, a check of the final model was carried out thanks to a Chi 2 test to control the hypothesis of proportional hazards set by the Cox's model.

Ethics

The study was approved by Ethics Committee of the "Université de Bretagne Occidentale" Faculty of Medicine.

RESULTS

Study population

The first inclusion period took place from July to December 2014. 64 patients were enrolled on the 127 expected. None of the patients were lost to follow-up so the status at eighteen months could be collected for every patient.

A second inclusion period happened from July to December 2015. It enrolled 54 other patients.

The cohort counted 118 persons. The follow-up of these new patients was too short to include them in any statistical analysis. That's why another thesis will study the data after eighteen months of follow-up for the 118 patients.

Status at eighteen months

Eighteen months after inclusion, 31 patients belonged to the group « D » and 33 to the group « NTR ». In the group « D », 13 were hospitalized seven days or more and 18 were dead.

Characteristics of the two groups are exposed on the table 2. The analysis did not bring out any statistically significant variable, qualitative nor quantitative,

i.e with a p-value < 0.05.

Cleaning and recoding data

The results of the recoding work were reported in the dictionary. ( Appendix2) The answer for several variables was the same for the 64 patients. So they were not discriminant and had been erased. It concerned: the presence of pharmacological treatment (yes), material available to the patient (yes), human aid available to the patient (yes), life in institution (yes), unemployment (no), suicide risk (not), stress at work (no), family history of cardiovascular diseases (no).

The useless variables were eliminated, namely patient identification number and date of inclusion.

Date of birth was transformed into age.

The goal was to compare the groups according to their characteristics. That's why the variables relating to the quality of care of the multimorbidity and the general practitioner's self-evaluation (intuition, good communication with others carers, coordination procedures etc) were also removed from the analysis (questions 26, 29, 30, 34, 45 to 52).

Clustering and classification : describing the study population

The multidimensional analysis started with an ascendant hierarchical classification. Every patient was initially taken individually. Some criterions were selected to group the patients.

Then, patients who were the closest according to the Euclidian distances where gathered. The process continued iteratively and on every step, individuals then groups were fused until obtained hierarchy. The hierarchy was represented on a cluster dendrogram. (Figure 1) Most of people belonging to the cluster 1 had a healthy diet and no psychological risk factor (addiction, risk behaviour or suicide risk) (96.67%). They had a good hygiene and their conditions, acute as well as chronic, were not complicated. They suffered rather from hypercholesterolemia.

They took less medication than the cohort study (8.90 vs 9.97).

b. Cluster 2

The patients composing the cluster 2 were women (86.96%), whose hygiene was not correct and they had children (91.3%). None of them had a healthy diet. They were not immunosuppressed. They didn't present psychological risk factor or addictions. They took more medication and underwent less biology exams per year than the population study.

c. Cluster 3

The cluster 3 is defined only by qualitative variables. It was characterized by a majority of men (81.82%) and workers (54.55%). None of them had a correct hygiene. They were under risk treatment and had psychological risk factors (addictions and risk behaviours). They did not suffer from osteo-articular diseases, postural instability and were immune-supressed.

b. Multivariate analysis : Cox's models

The Cox's model was applied to take the follow-up duration into account. The univariate analysis resulted in the unrefined Hazard Ratio (HR), which corresponded to the association between a variable and the risk of decompensation. The HR and their confidence interval figured on the table 3. decompensation. On the contrary, existing entourage emerged as a protective factor of decompensation.

The Cox's model was applied a second time in a multivariate analysis to obtain the adjusted Hazard Ratio. First, the significant and pertinent variables that could be incorporated in the model had to be selected. They are chosen thanks to an expert consensus among the variables obtained from the univariate analysis.

The adjusted HR were issued from this final model. They are presented on the table 4.

c. Checking of the final model

A Chi 2 test assessed the validity of the final model, testing the hypothesis of proportional hazards of the Cox's model. The p-value is 0.401 so the decompensation risk stayed proportional over time among painful patients and patients having an unhealthy way of life. In conclusion, the model was valid.

Experienced difficulties

The principal difficulty was the recruitment of only 64 patients on the 127 expected. It resulted in a lack of power of the study.

The questionnaire to complete comprised 52 questions so its filling was time-consuming.

Because it was the same than used in the primary care studies, some questions were not suitable for the nursing home population.

Certain formulation of questions seemed not precise enough so answering was more complicated. Moreover, some questions led to subjective answers. Hence their analyse and interpretation could not be performed.

Classification of several diseases as acute or chronic diseases or risk factors was difficult.

The number of variables increased owing to the repetition of some variables. The statistical analysis was thus complicated and required a selection of variables.

DISCUSSION 1. Main findings

Pain appeared as a risk factor of decompensation for the nursing home residents. The risk of death or hospitalization was 2.53 higher in painful patients.

Pain is known to be a frequent problem, concerning from 27 % to 83% nursing homes residents according to Fox and al. [START_REF] Fox | Prevalence and treatment of pain in older adults in nursing homes and other long-term care institutions: a systematic review[END_REF] Despite it is underestimated and undertreated (39-44): 40 % of the painful residents are not given any pain killer, especially those with a low cognitive status.

Persistent pain has yet numerous negative consequences : decreased quality of life, worsened mood and depression [START_REF] Zanocchi | Chronic pain in a sample of nursing home residents: Prevalence, characteristics, influence on quality of life (QoL)[END_REF][START_REF] Erdal | Associations between pain and depression in nursing home patients at different stages of dementia[END_REF][START_REF] Kenefick | Pain treatment and quality of life: reducing depression and improving cognitive impairment[END_REF][START_REF] Achterberg | Pain in European long-term care facilities: Cross-national study in Finland, Italy and the Netherlands[END_REF], increased dependency in activities of daily living [START_REF] Tarakci | Chronic pain, depression symptoms and daily living independency level among geriatrics in nursing home[END_REF], impaired social activities, impaired posture and mobility, impaired appetite, cognitive deterioration and behavioural symptoms, sleep troubles and anxiety [START_REF] Zanocchi | Chronic pain in a sample of nursing home residents: Prevalence, characteristics, influence on quality of life (QoL)[END_REF][START_REF] Cowan | The assessment and management of pain among older people in care homes: current status and future directions[END_REF][START_REF] Kenefick | Pain treatment and quality of life: reducing depression and improving cognitive impairment[END_REF][START_REF] Ferrell | Pain in the nursing home[END_REF][START_REF] Tse | Health-Related Profile and Quality of Life Among Nursing Home Residents: Does Pain Matter?[END_REF].

Several elements may highlight the inadequate management of pain in NH : first, pain is sometimes considered as a part of the ageing process by both patients and carers [START_REF] Cowan | The assessment and management of pain among older people in care homes: current status and future directions[END_REF][START_REF] Boerlage | Pain prevalence and characteristics in three Dutch residential homes[END_REF][START_REF] Lansbury | Chronic pain management: a qualitative study of elderly people's preferred coping strategies and barriers to management[END_REF][START_REF] Vaismoradi | Normalizing suffering: A metasynthesis of experiences of and perspectives on pain and pain management in nursing homes[END_REF].

Older people can also hide they feel painful because they worry about being a burden (52), because they feel not being taken seriously [START_REF] Brockopp | Elderly people's knowledge of and attitudes to pain management[END_REF] or because they are afraid of medication [START_REF] Schofield | Pain management of older people in care homes: a pilot study[END_REF].

Pain evaluation scales are multiple and self-reporting is often considered as a « gold-standard » assessment even though it is not always reliable, particularly when cognitive troubles exist [START_REF] Reynolds | Disparities in Pain Management Between Cognitively Intact and Cognitively Impaired Nursing Home Residents[END_REF][START_REF] Horgas | Pain assessment in persons with dementia: relationship between self-report and behavioral observation[END_REF][START_REF] Malara | Pain Assessment in Elderly with Behavioral and Psychological Symptoms of Dementia[END_REF] and ECPA [START_REF] Dosquet | Évaluation Et Prise En Charge Thérapeutique De La Douleur Chez Les Personnes Agées Ayant Des Troubles De La Communication Verbale[END_REF].

In this study, only 29.7 % of patients were painful. Reporting pain was achieved by GPs, whose evaluation was based on their patient's knowledge and the medical record data (pain assessment and/or treatment and/or the nurses' annotations). However Sengstaken and al demonstrated that GPs failed frequently to detect pain in nursing home users (in 34 % of the patients of the study) [START_REF] Sengstaken | The problems of pain and its detection among geriatric nursing home residents[END_REF]. Other studies put forward that nurses could misestimate the intensity of pain [START_REF] Bergh | A comparative study of nurses' and elderly patients' ratings of pain and pain tolerance[END_REF][START_REF] Duignan | Congruence of pain assessment between nurses and emergency department patients: A replication[END_REF]. The association of these elements with the caregivers' misconceptions about analgesics [START_REF] Herr | Chronic pain: challenges and assessment strategies[END_REF][START_REF] Lander | Fallacies and phobias about addiction and pain[END_REF][START_REF] Closs | Pain and elderly patients: a survey of nurses' knowledge and experiences[END_REF] contributes to the under-treated pain [START_REF] Cowan | The assessment and management of pain among older people in care homes: current status and future directions[END_REF].

Using a combined strategy consisting in direct questioning and evaluation scales (auto and/or hetero-evaluation) could have been more appropriate to confirm the prevalence of pain in the cohort.

Improving the management of pain is a challenge for caregivers, especially for multimorbid old people. Some researches suggest that chronic pain increases mortality, particularly from cardiovascular diseases and cancer [START_REF] Mcbeth | Musculoskeletal pain is associated with a long-term increased risk of cancer and cardiovascular-related mortality[END_REF][START_REF] Smith | Chronic Pain and Mortality: A Systematic Review[END_REF][START_REF] Macfarlane | Persons with chronic widespread pain experience excess mortality: longitudinal results from UK Biobank and meta-analysis[END_REF]. However, further studies are needed to precise the relation between pain and the risk of decompensation among multimorbid patients.

A second risk factor of decompensation arose from the study: adverse lifestyle factors, i.e not having a healthy diet, physical activity or good hygiene. The risk was 2.18 times higher.

Having a healthy lifestyle is recognized as a preventive factor of developing various chronic diseases in older adults. [START_REF] Chodzko-Zajko | Exercise and Physical Activity for Older Adults[END_REF][START_REF] Nelson | Physical Activity and Public Health in Older Adults[END_REF] Promotion of physical activity and healthy diet appears in the priority interventions proposed by The Lancet NCD Action Group and the NCD Alliance to curb the increasing burden of Non Communicable diseases (NCDs) [START_REF] Beaglehole | Priority actions for the non-communicable disease crisis[END_REF]. French health authorities have adopted a similar approach during the updating of the French National Nutrition and Health Program (PNNS), by revising guideline daily amounts and establishing recommendations to increase physical activity and reduce sedentary lifestyle [START_REF]Haut Conseil de la Santé Publique. Avis relatif à la révision des repères alimentaires pour les adultes du futur Programme national nutrition santé 2017-2021[END_REF][START_REF]ANSES de février 2016 sur l'activité physique et la sédentarité[END_REF].

The relation existing between multimorbidity and lifestyle has already been highlighted in other studies [START_REF] Wikström | Clinical and lifestylerelated risk factors for incident multimorbidity: 10-year follow-up of Finnish populationbased cohorts 1982-2012[END_REF][START_REF] Barnes | Mechanisms of development of multimorbidity in the elderly[END_REF]. Multimorbidity is contrarily associated with the physical activity level according to Loprinzi and al. ( 75) and Autenrieth and al [START_REF] Autenrieth | Physical activity is inversely associated with multimorbidity in elderly men: Results from the KORA-Age Augsburg Study[END_REF]. Booth and al. affirm that lack of exercise is a predominant cause of most chronic conditions and explain through which physiopathological mechanisms [START_REF] Booth | Lack of exercise is a major cause of chronic diseases[END_REF]. Sedentary behaviours even increase the risk of death in general population [START_REF] Gulsvik | Ageing, physical activity and mortality-a 42-year follow-up study[END_REF][START_REF] Mokdad | Actual Causes of Death in the United States, 2000[END_REF][START_REF] Koster | Association of Sedentary Time with Mortality Independent of Moderate to Vigorous Physical Activity[END_REF] as well as in the elderly [START_REF] De Groot | Lifestyle, nutritional status, health, and mortality in elderly people across Europe: a review of the longitudinal results of the SENECA study. The journals of gerontology[END_REF]. In the same way, unhealthy food habits have an important impact on health. In 2000 in the USA, sedentarity and low-quality diet were responsible for 365.000 deaths [START_REF] Mokdad | Actual Causes of Death in the United States, 2000[END_REF]. According to Lock and al. up to 2.635 million deaths per year worldwide would result from an insufficient consumption of fruits and vegetables ! (82)

These numbers point out the urgent need to change lifestyle habits. Policies promoting the Mediterranean diet ; a regimen giving priority to fish, mono-unsaturated fats from olive oil, fruits, vegetables, whole grains, legumes/nuts, and moderate alcohol consumption, should be privileged. Indeed, Mediterranean diet reduces mortality [START_REF] Mcnaughton | Diet Quality Is Associated with All-Cause Mortality in Adults Aged 65 Years and Older[END_REF][START_REF] Pérez-López | Effects of the Mediterranean diet on longevity and age-related morbid conditions[END_REF] and the risk of developing numerous diseases, often reported as multimorbidity patterns [START_REF] Violan | Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies[END_REF][START_REF] Kirchberger | Patterns of Multimorbidity in the Aged Population. Results from the KORA-Age Study[END_REF][START_REF] Prados-Torres | Multimorbidity patterns: a systematic review[END_REF][START_REF] Forouzanfar | Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015[END_REF][START_REF] Van Den Bussche | Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany[END_REF], such as cardiovascular and metabolic diseases, cancer, rheumatoid pathologies [START_REF] Pérez-López | Effects of the Mediterranean diet on longevity and age-related morbid conditions[END_REF].

About personal hygiene, there is no specific study focusing on the relation between it and multimorbidity or mortality. Through the increasing risk of contracting infection, it can be hypothesized that incorrect personal hygiene might negatively influence multimorbidity.

In the study, only half of residents were supposed to have a healthy diet. Interview of patients, variations of their weight and personal opinion may have influenced GPs' answers. It is difficult to assess if this result meshes with literature due to the lack of consensual definition of malnutrition and the obtained wide range of its prevalence in nursing home (from 1.5% to 66.5%) [START_REF] Bell | Malnutrition in the nursing home[END_REF]. Several leads to optimize nutritional care of NH's patients exist [START_REF] Labossiere | Nutritional considerations in institutionalized elders[END_REF]: an exhaustive physical evaluation, regular monitoring of weight and meal intake, improvement of meal environment, evaluation of the feeding dependency and adaptation of the available staff needed to assist residents with meals. A document providing technical and practical advice to improve dietary intake for older people living in long-term care has been produced by the French Department of Health [START_REF]Recueil d'actions pour l'amélioration de l'alimentation en établissements hébergeant des personnes âgées[END_REF] and insists on the requirement to get patients involved in meal times.

93% of patients from the cohort did not practice physical activity. Increasing age is associated with decreasing physical activity (69) while potential benefits in functional abilities [START_REF] Nelson | The effects of multidimensional home-based exercise on functional performance in elderly people. The journals of gerontology[END_REF][START_REF] Keysor | Does late-life physical activity or exercise prevent or minimize disablement? A critical review of the scientific evidence[END_REF][START_REF] Vries | Effects of physical exercise therapy on mobility, physical functioning, physical activity and quality of life in community-dwelling older adults with impaired mobility, physical disability and/or multi-morbidity: A meta-analysis[END_REF] and various diseases are extensive [START_REF] Bassuk | Epidemiological evidence for the role of physical activity in reducing risk of type 2 diabetes and cardiovascular disease[END_REF]. The American College of Sports Medicine and the American Heart Association have recommended in 2007 to develop a individualized activity plan for each old person suffering from chronic conditions [START_REF] Nelson | Physical Activity and Public Health in Older Adults[END_REF]. Interventions on physical activity showed their positive effects in nursing home [START_REF] Jansen | Effects of interventions on physical activity in nursing home residents[END_REF] and are worthy of being developed in the Lanmeur's one.

They resulted in qualitative data which were hardly to convert in quantitative data for the statistical analysis. Besides, GPs had only two possible choices of response available, « Yes » or « No ». Thus, data which would have been extracted may be limited. For further studies, proposing semi-quantitative answers such as « yes completely, yes overall, yes a little, not at all » and ask indirect questions appears a suitable alternative.

d. Choice of chronic conditions

No In the study, the team considered all the diseases reported by GPs. A correction was applied for redundant and wrong-classified ones. Their number rather than their type was used in the analysis.

e. Statistical analysis

The high number of variables complexified the statistical analysis. Because of the small number of patients, the used statistical tests reached their limits. For example, a Yates's correction needed to be applied to the Chi 2 test for the comparison of the characteristics of the « D » and « NTR » groups when the number of patients was between 2.5 and 5.

For the clustering, the 20% difference threshold was empirically fixed to define the clusters which have to be studied. In fact, a difference of 20% corresponds to the limit from which GPs estimates that a difference matters in daily practice.

Study limitations a. Selection bias

• A legal protection measure prevented patients to be enrolled. But those who were not able to consent and were not under such a measure could be enrolled. Though, for some people, family consent's was asked. Among the 28 requested families, 24 agreed and 4 refused. So, these four persons were not included even though they matched the inclusion criteria.

• Life threatening situation or estimated life expectancy lower than three months also prevented the inclusion. This criteria was left to the discretion of GPs and its evaluation was necessarily subjective, based on doctor's intuition and experience and on the medical data.

But taking into account such situations was essential to avoid distortion of the results by including almost dying people.

• Given the length of the questionnaire and the time needed to fill it out, even though the team had pre-filled it, a longer inclusion period or a multicentric design would have led to a higher number of residents.

• GPs recruiters came only from the medical university center of Lanmeur. More people may have been enrolled if recruitement had been extended to all neighbouring GPs, independently of their workplace. But working in a university medical center made GPs familiar with research projects and objectives and had possibly increase GPs' investment.

The cohort's residents were not comparable with the residents of French nursing homes, according to the 12 months follow-up study (105). It was due to a monocentric recruitment in Lanmeur's NH. A multicentric study would enhance the statistical power and improve representativity.

b. Information bias

Some inconsistencies appeared in the results during analysis.

• No resident had a family history of cardiovascular conditions (question 8). Such antecedents may not have been exhaustively reported in the medical files.

• Because it was too difficult to evaluate in NH, the annual number of paramedical helps (question 22) was arbitrarily fixed to three a day and was the same for every resident.

• It was reported that two patients accepted screening tests while they were not proposed them (questions 37 and 38). Questions should be combined and modified for "Does the patient receive a personal or organized screen test ?"

• The pain-related question (question 40) generated subjective answers based on medical data available and the GP's knowledge of patient. Using a pain evaluation scale should be prefered.

c. Confusion bias

• Multimorbidity's themes and subthemes had been written in English. They had to be translate in French to build the questionnaire. Some translations may be incorrect.

• The qualitative data had been converted into quantitative data for the statistical analysis. Some transformations may be inexact.

• Considering the high number of variables to analyze compared with the small size of the cohort, a selection was required. It enabled to remove the redundant and the nondiscriminating variables according to an expert's consensus. Another selection was performed to chose which variables to include in the multivariate analysis after the univariate analysis, respecting the following rule : 1 variable for 10 events (decompensation in the study). The choice was made by clinical experts. Results might have been different

hence if the removed variables had been kept.

Future prospects

For further studies, a new questionnaire, more suitable for nursing homes' residents, shorter and more precise, had been proposed (Appendix 3). All changes were grouped in the table 5.

However, it must be validated by a consensus procedure before being used. A question concerning pain killer consumption was added.

Statistical tests will probably need to be changed because their limits have been reached.

Despite these methodological shortcomings, pain and unhealthy lifestyle were suggested to be risk factors of decompensation. Pain matters especially as it had already been highlighted in the previous 6-month, 9-month, 12-month and 15-month studies (105-108) .

A complementary analysis at 21-month on the same cohort is the next stage of the study.

Perhaps it will permit to confirm the obtained results.

A study analyzing the cohort of 118 patients after 18 months of following-up will be performed.

Its power will be higher. It needs to be demonstrated if pain and adverse lifestyle will remain as decompensation risk factors and if other variables emerge.

CONCLUSION

  Pauline et Aude, les BD, pour notre épopée à Nice, nos soirées mémorables et notre amitié. A nos futures retrouvailles réunionnaises.

METHODS 1 .RESULTS 1 .DISCUSSION 1 .

 111 Study design ..................................................................................................................... 2. Study population .............................................................................................................. 3. Study conduct ................................................................................................................... 4. Judgment criteria .............................................................................................................. 5. Data cleaning .................................................................................................................... 6. Statistical analysis ............................................................................................................ a. Clustering and classification ......................................................................................... b. Survival analysis and multivariate regression ............................................................... 7. Ethics ................................................................................................................................ Study population .............................................................................................................. 2. Status at eighteen months ................................................................................................. 3. Cleaning and recoding data .............................................................................................. 4. Clustering and classification : describing the study population ....................................... a. Cluster 1 ........................................................................................................................ b. Cluster 2 ........................................................................................................................ c. Cluster 3 ........................................................................................................................ 5. Survival analysis : investigate the decompensation risk factors ...................................... a. Univariate analysis : the Kaplan-Meier method ............................................................ b. Multivariate analysis : Cox's models ............................................................................ c. Checking of the final model .......................................................................................... 6. Experienced difficulties .................................................................................................... Main findings ................................................................................................................... 2. Analysis of experienced difficulties ................................................................................. a. Small sample size .......................................................................................................... b. Pertinence of some questions ........................................................................................ c. Subjectivity of the « Expertise of the GP » assessment ................................................ d. Choice of chronic conditions ......................................................................................... e. Statistical analysis ......................................................................................................... 3. Study limitations .............................................................................................................. a. Selection bias ................................................................................................................. b. Information bias ............................................................................................................ c. Confusion bias ............................................................................................................... 4. Future prospects ............................................................................................................... DE RISQUE DE DECOMPENSATION PARMI LES THEMES DE LA DEFINITION DE LA MULTIMORBIDITE SELON EGPRN. ETUDE PILOTE DE COHORTE, A 18 MOIS DE SUIVI EN EHPAD.

:

  64 patients ont été inclus. Après dix-huit mois de suivi, 31 appartenaient au groupe "D" et 33 au groupe "RAS". L'analyse multivariée selon un modèle de Cox faisait émerger deux variables statistiquement significatives : la douleur (Hazard Ratio (HR) = 2.18 ; 95% IC [1.07-4.44], p= 0.012) et la mauvaise hygiène de vie (pas d'alimentation saine, d'activité physique ni d'hygiène correcte) (HR= 2.53 ; 95% IC [1.23-5.19], p=0.033).

Table 1 :

 1 Themes and subthemes of the multimorbidity

Figure 1 :

 1 Figure 1 : cluster dendrogram

Figure 2 :

 2 Figure 2 : HCPC on three clusters

Figure

  Figure : Unhealthy way of life

Figure 6 :

 6 Figure 6 : Absence of entourage

  classified list of diseases like ICD 10 (International Classification of Diseases, Tenth version) or ICPC2 (International Classification of Primary Care, Second Edition), was used by GPs to list patients'diseases. There is no consensus in the literature about the number and the type of diseases to retain to define multimorbidity. The systematic review of literature performed by Violan and al in 2014 (2) found out that selected studies comprised from 2 to 335 conditions in their multimorbidity's definition. Heterogenous measurement methods of the prevalence of multimorbidity explained thus the wide range of estimations. And it supported the EGPRN's process to develop a comprehensive definition of multimorbidity (15).

57 19) 51 ) 1 Non 2 « 3 » = supérieur ou égal à 3 Modification des réponses de la question 37 PropositionAppendix 3 : 4 -. 5 - 6 - 8 - 67 􀀀 12 - 16 - 21 -▪

 57511233373456867121621 17) Situation familiale En couple  Célibataire  Enfant(s) vivant ou non au domicile (cocher si oui) 18) Le patient met-il en place au moins une stratégie adaptative parmi les suivantes ? (En entendant par stratégies adaptatives les moyens que le patient met en oeuvre pour essayer d'aller mieux : mise en place de règles hygiéno-diététiques, planification, soutien instrumental, soutien émotionnel, expression des sentiments, réinterprétation positive, acceptation, déni, blâme, humour, religion, distraction, utilisation de substances)  Oui  Non Le patient présente-il des complications de ses pathologies ? (En entendant par complication une décompensation aiguë de ses pathologies chroniques, une situation de fin de vie ou de la iatrogénie (aléa thérapeutique et donc non imputable au médecin)) Oui  Non20) Quel est le nombre annuel de consultations ou visites du patient au généraliste ? 21) Quel est le nombre annuel de consultations de patient aux spécialistes ? 22) Quel est le nombre de recours annuel du patient aux paramédicaux (IDE à domicile, kinésithérapeute, podologue...) 23) Le patient bénéficie-t-il de traitements pharmacologiques ?  Oui  Non 24) Bénéficie-t-il de traitement à risque ? (AVK, chimiothérapie, insuline, traitement chirurgical lourd…)  Oui  Non 25) Utilisation quotidienne de traitements psychotropes (aide au calcul du score de chute)  Oui  Non 26) Mettez-vous en oeuvre des procédures de coordinations de soins pour ce patient ? (Réseaux, interaction avec des correspondants multiples : spécialistes, psychologues...)  Oui  Non 27) A combien d'EXAMENS BIOLOGIQUES votre patient a-t-il recourt annuellement ? (En entendant examens réalisés EN DEHORS de la surveillance thérapeutique habituelle (HbA1c, INR, pré chimiothérapie ?) et EN DEHORS du suivi de ses pathologies chroniques (cirrhose, insuffisance rénale, diabète) exemple de diagnostic de pathologie aigue : sérologie IST...) 58 28) A combien d'EXAMENS D'IMAGERIE votre patient a-t-il recourt annuellement ? (En entendant les examens réalisés EN DEHORS de la surveillance thérapeutique habituelle et EN DEHORS du suivi de ses pathologies chroniques (cirrhose et échographie abdominale) exemple de pathologie aigue : Fracture) 29) Pensez-vous qu'en ce qui concerne votre patient, la communication avec les autres intervenants de santé est bonne ?  Oui  Non 30) Pensez-vous avoir déjà été négligent envers la santé de votre patient ?  Oui  Non 31) Votre patient a-t-il été victime de iatrogénie suite à un traitement inadapté (surdosage ou mésusage) ?  Oui  Non 32) Votre patient bénéficie-t-il de matériel à disposition (lit médicalisé, Montauban, télé alarme)  Oui  Non 33) Votre patient bénéficie-t-il d'aides humaines (IDE, AS, aides ménagères, assistante sociale)  Oui  Non 34) Avez-vous une impression de manque de temps ou de rémunération pour une prise en charge optimale de votre patient ?  Oui  Non 35) Pensez-vous que votre patient a des antécédents médicaux ou chirurgicaux lourds et/ou complexes ?  Oui  Non 36) Votre patient a-t-il bénéficié des vaccinations recommandées (selon le calendrier vaccinal 2014)  Oui  Non 37) Avez-vous proposé à votre patient les dépistages systématiques organisés (cancer colorectal avec le test Hemoccult, cancer du sein avec la mammographie) ?  Oui  Non  Patient rentrant dans le cadre d'un dépistage personnalisé 38) Votre patient a-t-il accepté les dépistages systématiques organisés ou personnalisés ?  Oui  Non 39) Avez-vous proposé une éducation thérapeutique à votre patient ? (Réseau diabète, AVK...)  Oui  Non 40) Votre patient est-il douloureux ?  Oui  Non 41) Votre patient vit-il en institution ? (EHPAD, foyer logement, hébergement temporaire)  Oui  Non 42) Votre patient présente-il des plaintes multiples ? (Patient toujours dans la plainte, vivant mal sa multimorbidité entrainant une consommation de soins importante) ?  Oui  Non 43) Combien de traitement prend-t-il ? (Chiffre du nombre de traitements actif et chronique) 44) Caractéristiques de l'entourage de votre patient :  Existence de l'entourage (cocher si oui)  Entourage soutenant (cocher si oui)  Dépendance de l'entourage (dépendance = maintien à domicile impossible en absence de l'entourage) (cocher si oui)  Mise en place de stratégies adaptatives  Absence d'entourage 45) Pensez-vous que bien connaître le système de santé vous a aidé à mieux suivre ou détecter la multimorbidité de votre patient ?  Oui  Non 46) Pensez-vous que l'habitude à résoudre des problèmes complexes (combinant maladies et facteurs psycho-sociaux) vous a aidé à mieux suivre ou détecter la multimorbidité de votre patient ?  Oui  Non 47) Pensez-vous qu'avoir une vision globale de toutes les maladies de votre patient vous a aidé à mieux suivre ou à détecter sa multimorbidité ?  Oui  Non 48) Pensez-vous que pratiquer des soins centrés sur les attentes et les besoins de votre patient vous a aidé à mieux suivre ou détecter sa multimorbidité ?  Oui  Non 49) Pensez-vous qu'avoir une relation de long terme attentive sur l'ensemble des facteurs biopsycho-sociaux vous a aidé à mieux suivre ou détecter la multimorbidité de votre patient ?  Oui  Non 50) Est-ce que le fait d'avoir l'intuition que quelque chose n'allait pas vous a aidé à le détecter ? Une communication de bonne qualité et le fait que le patient puisse s'ouvrir à vous, vous semble-t-il important pour détecter sa multi morbidité ?  Oui  Non 52) Pensez-vous que la multi morbidité de votre patient influe sur la qualité de votre suivi ?  Oui  Non DMLA : dégénérescence maculaire liée à l'âge AIT : accident ischémique transitoire AVC : accident vasculaire cérébral SAS : syndrome d'apnée du sommeil PTH : prothèse totale de hanche PATHOLOGIES CHRONIQUES Pathologies ostéoarticulaires Englobe « fracture », « ostéoporose », « prothèse articulaire », « tassement », « arthrose », « arthrotomie », « ostéotomie », « luxation », « arthroplastie », « algodystrophie ». Si une de ces réponses à la question « pathologie chronique » et « non » répondu à la question « pathologie ostéoarticulaire » : modification par « oui » à la question « pathologie ostéoarticulaire » et mise entre parenthèse du nom de ces pathologies. Nombre de pathologies chroniques Addition des pathologies de la question 1 (pathologies ostéoarticulaires, hypertension artérielle, hypercholestérolémie et diabète) et du nombre de pathologies de la question 2 (autres pathologies chroniques) Absence de pathologie ostéoarticulaire = 0 Présence d'une ou plusieurs pathologies ostéoarticulaires = cognitifs = « Alzheimer » + « leucoaraïose » Troubles cognitifs = « troubles cognitifs » + « leucoaraïose » Cécité oeil gauche = « rétinopathie diabétique » + « cécité oeil gauche » Insuffisance respiratoire chronique = « Insuffisance respiratoire chronique » + « BPCO » et/ou « dilatation des bronches » et/ou « fibrose » et/ou « asthme » Plaies chroniques « Escarres » +/-« pied du diabétique » +/de dépistage organisé ou personnalisé : réponse oui/non/perso  modification des 4 réponses « perso » par « oui » New Autres pathologies chroniques en cours (à lister, cf. dictionnaire des maladies) : ……………………………………………………………………………………………… ………………………………………………………………………………………………Existence de caractéristiques complexes des pathologies chroniques (Ex : diabète déséquilibré, risque élevé de décompensation cardiaque...) : Antécédents médicaux et chirurgicaux (= pathologies terminées, exemple fracture du col du fémur, cholécystectomie, pneumopathie…) A lister ………………………………………………………………………………………….. 7-Jugez-vous ces antécédents médicaux lourds et/ou complexes ? Le motif de consultation du jour/ dernier motif de consultation est (cochez et précisez le motif) : 􀀀 Pathologie aigue simple (ex : cystite) : ………. 􀀀 Complication d'une pathologie chronique (ex : OEdème pulmonaire aigu sur insuffisance cardiaque chronique) : ………. Complication d'une pathologie aigue (ex : détresse respiratoire sur pneumopathie) : ………… 􀀀 Autre (renouvellement d'ordonnance / administratif / suivi) : …………. 9-Le patient (cochez la ou les propositions) : 􀀀 Présente ou a présenté une pathologie psychosomatique 􀀀 Est multi plaintif 􀀀 Aucune des propositions 10-Le patient présente un trouble de l'adaptation à un stress (au moindre stress / nouvelle pathologie / mauvaise nouvelle) de type : anxiété majeure, dépression réactionnelle, idées suicidaires : 􀀀 Oui 􀀀 Non 􀀀 Je ne sais pas 11-Le patient est capable de mettre en place une stratégie adaptative (règles hygiénodiététiques, planification, soutien émotionnel, expression des sentiments, réinterprétation positive, acceptation, déni, blâme, humour, religion, distraction, utilisation de substance) : Nombre annuel de recours (si aucun : notez « 0 », si ne sait pas : notez « ? ») : Au généraliste : … Aux spécialistes : … 13-Procédures de coordinations de soins mises en place pour ce patient ? (Réseaux, interaction avec des correspondants multiples : spécialistes, psychologues...) DEHORS DE LA SURVEILLANCE THERAPEUTIQUE ET DU SUIVI HABITUEL DES MALADIES CHRONIQUES, Nombre d'examens : ▪ Biologiques par an : 􀀀 <1 􀀀 1 à 3 􀀀 4 à 6 􀀀 7 à 12 􀀀 >12 ▪ Radiologiques par an : 􀀀 <1 􀀀 1 à 3 􀀀 >3 15-Le patient est-il douloureux ? 􀀀Oui 􀀀Non Si oui, quel(s) traitement(s) prend-t-il ? … Traitements médicamenteux (si aucun : notez « 0 », si ne sait pas : notez « ? ») Nombre de traitements en cours : … Nombre de traitements à risque (AVK, insuline, chimio…) : … Utilisation quotidienne de psychotrope : 􀀀 oui 􀀀 non 􀀀 je ne sais pas 17-Nombre de chutes ces 12 derniers mois : 􀀀 0 􀀀 1 􀀀 2 􀀀 3 ou plus Instabilité posturale (=incapable de tenir en appui monopodal plus de 5 secondes sans bouger les bras) : 􀀀 oui 􀀀 non 18-Le patient présente (cochez la ou les propositions) : 􀀀 Des conduites à risque 􀀀 Un risque suicidaire 􀀀 Une addiction 􀀀 Aucune des propositions 19-Le patient : ▪ Réalise les dépistages organisés : 􀀀 oui 􀀀 non 􀀀pas d'indication au dépistage 􀀀 je ne sais pas  ▪ Est à jour de ses vaccins : 􀀀 oui 􀀀 non 􀀀 je ne sais pas ▪ A bénéficié d'une éducation thérapeutique (AVK/diabète…) : 􀀀 oui 􀀀 non 􀀀 je ne sais pas 20-Quels sont ses facteurs de risque psychosociaux ? (cochez la ou les propositions justes) : 􀀀 Conjugopathie 􀀀 Divorce 􀀀 Problèmes familiaux 􀀀 Décès d'un ou plusieurs proches 􀀀 Précarité financière et sociale 69 Catégorie socio professionnelle (selon INSEE), cocher la profession prédominante exercée avant le passage à la retraite (cochez la proposition) : 􀀀 Agriculteur / exploitant agricole 􀀀 Artisan, commerçant, chef d'entreprise 􀀀 Cadre et professions intellectuelles supérieures 􀀀 Professions intermédiaires 􀀀 Employés 􀀀 Ouvriers 􀀀 Sans activité (ex : femme au foyer) 22-Caractéristiques de l'entourage : 􀀀 Entourage aidant et soutenant (stratégie adaptative : aide le patient dans ses démarches administratives, peuvent alerter quand ça ne va…) 􀀀 Entourage existant mais non soutenant 􀀀 Absence d'entourage 23-Ces compétences vous aident-elles à appréhender la multimorbidité de votre patient ? La connaissance du système de santé 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ L'habitude à résoudre des problèmes complexes 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ La vision globale des maladies de votre patient 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ Les soins centrés sur les attentes et besoins du patient 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ L'attention portée aux facteurs bio-psycho-sociaux 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ L'intuition 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non ▪ Une communication de bonne qualité 􀀀oui complètement 􀀀oui dans l'ensemble 􀀀oui un peu 􀀀non

Table 2 :

 2 Characteristics of the study population

		Study Population N=64 (100%)	Decompensation (D) N= 31 (48.43%)	Nothing to Report (51.56%) (NTR) N= 33	P value
	Qualitative variables	N	%	N	%	N	%	Chi2/Fisher
	Men	24	37.50%	11	35.48%	13	39.49%	0.949
	Women	40	62.50%	20	64.52%	20	60.61%	0.949
	Somatic risk factors and
	disease
	Ostearticular disease	42	65.63%	21	67.74%	21	63.64%	0.934
	Hypertension	47	73.44%	24	77.42%	23	69.70%	0.677
	Hypercholesterolemia	10	15.63%	3	9.68%	7	21.21%	0.355
	Diabetes	7	10.94%	2	6.45%	5	15.15%	0.475

Table legend : Sd = Standard deviation ; Q1 = First quartile ; Q3= Third quartile ; NI= not interpretable

Mean in the cluster Mean in the cohort Standard deviation in the cluster Standard deviation in the cohort p

						% in the cluster
			% in the cluster % in the cohort	relative to % in	p
						the cohort
	Cluster 1
	q13_alimsaine=q13_alimsaine_Yes			96,67	50,00	90,63	0,000
	q13_aucun=q13_aucun_No			100,00	57,81	81,08	0,000
	q13_hygieneOK=q13_hygieneOK_Yes			70,00	37,50	87,50	0,000
	q11_FR_psy_aucun=q11_FR_psy_aucun_Yes			96,67	84,38	53,70	0,012
	q1_hypercholest=q1_hypercholest_Yes			26,67	15,63	80,00	0,028
	q7_complicationPA=q7_complicationPA_No			76,67	62,50	57,50	0,032
	q19_complications=q19_complications_No			70,00	56,25	58,33	0,042
	q11_FR_psy_addictions=q11_FR_psy_addictions_No		96,67	87,50	51,79	0,045
	q11_FR_psy_addictions=q11_FR_psy_addictions_Yes		3,33	12,50	12,50	0,045
	q19_complications=q19_complications_Yes			30,00	43,75	32,14	0,042
	q7_complicationPA=q7_complicationPA_Yes			23,33	37,50	29,17	0,032
	q1_hypercholest=q1_hypercholest_No			73,33	84,38	40,74	0,028
	q11_FR_psy_aucun=q11_FR_psy_aucun_No			3,33	15,63	10,00	0,012
	q13_hygieneOK=q13_hygieneOK_No			30,00	62,50	22,50	0,000
	q13_aucun=q13_aucun_Yes			-	42,19	-	0,000
	q13_alimsaine=q13_alimsaine_No			3,33	50,00	3,13	0,000
	Cluster 1
	q43_Ntraitements	8,90	9,97	3,32	3,89 0,039

Mean in the cluster Mean in the cohort Standard deviation in the cluster Standard deviation in the cohort p

						% in the
						cluster
			% in the cluster	% in the cohort	relative to % in	p
						the
						cohort
	Cluster 2
	q13_alimsaine=q13_alimsaine_No		100,00	50,00	71,88	0,000
	q13_aucun=q13_aucun_Yes		86,96	42,19	74,07	0,000
	q14_sex_H=Women		86,96	62,50	50,00	0,002
	q13_hygieneOK=q13_hygieneOK_No		86,96	62,50	50,00	0,002
	q11_FR_psy_aucun=q11_FR_psy_aucun_Yes	100,00	84,38	42,59	0,007
	q11_FR_psy_addictions=q11_FR_psy_addictions_No	100,00	87,50	41,07	0,022
	q8_FR_immunodep=q8_FR_immunodep_No	95,65	81,25	42,31	0,027
	q17_enfant=q17_enfant_Yes		91,30	76,56	42,86	0,039
	q17_enfant=q17_enfant_No		8,70	23,44	13,33	0,039
	q8_FR_immunodep=q8_FR_immunodep_Yes	4,35	18,75	8,33	0,027
	q11_FR_psy_addictions=q11_FR_psy_addictions_Yes	-		12,50	-	0,022
	CSP=CSP6-Ouvriers		8,70	26,56	11,76	0,015
	q11_FR_psy_aucun=q11_FR_psy_aucun_No	-		15,63	-	0,007
	q14_sex_H=Men		13,04	37,50	12,50	0,002
	q13_hygieneOK=q13_hygieneOK_Yes		13,04	37,50	12,50	0,002
	q13_aucun=q13_aucun_No		13,04	57,81	8,11	0,000
	q13_alimsaine=q13_alimsaine_Yes		-		50,00	-	0,000
	5.
	Cluster 2
	q43_Ntraitements	11,52	9,97	4,33	3,89 0,017
	q27_Nbiologie	2,96	4,70	2,88	5,27 0,047

Survival analysis : investigate the decompensation risk factors a. Univariate analysis : the Kaplan-Meier method

				% in the
		% in the cluster	% in the cohort	cluster % in the relative to	p
				cohort
	Cluster 3
	q11_FR_psy_aucun=q11_FR_psy_aucun_No	81,82	15,63	90,00	0,000
	q11_FR_psy_addictions=q11_FR_psy_addictions_Yes	63,64	12,50	87,50	0,000
	q14_sex_H=Men	81,82	37,50	37,50	0,002
	q13_hygieneOK=q13_hygieneOK_No	100,00	62,50	27,50	0,003
	q8_FR_immunodep=q8_FR_immunodep_Yes	54,55	18,75	50,00	0,004
	q11_FR_psy_conduiteRisQ=q11_FR_psy_conduiteRisQ_Yes	27,27	4,69	100,00	0,004
	q24_trait_risQ=q24_trait_risQ_Yes	72,73	40,63	30,77	0,024
	CSP=CSP6-Ouvriers	54,55	26,56	35,29	0,036
	q9_insta_posturale=q9_insta_posturale_No	54,55	26,56	35,29	0,036
	q1_patho_osteo=q1_patho_osteo_No	63,64	34,38	31,82	0,037
	q1_patho_osteo=q1_patho_osteo_Yes	36,36	65,63	9,52	0,037
	q9_insta_posturale=q9_insta_posturale_Yes	45,45	73,44	10,64	0,036
	q24_trait_risQ=q24_trait_risQ_No	27,27	59,38	7,89	0,024
	score_CETAF_3cl=Risque élevé	-	29,69	-	0,014
	q11_FR_psy_conduiteRisQ=q11_FR_psy_conduiteRisQ_No	72,73	95,31	13,11	0,004
	q8_FR_immunodep=q8_FR_immunodep_No	45,45	81,25	9,62	0,004
	q13_hygieneOK=q13_hygieneOK_Yes	-	37,50	-	0,003
	q14_sex_H=Women	18,18	62,50	5,00	0,002
	q11_FR_psy_addictions=q11_FR_psy_addictions_No	36,36	87,50	7,14	0,000
	q11_FR_psy_aucun=q11_FR_psy_aucun_Yes	18,18	84,38	3,70	0,000
	Several variables came out with a significative p-value < 0.05 after the comparison between the
	groups "D" and "NTR" using the Kaplan-Meier method. It was unhealthy way of life
	(corresponding to the patients that didn't have a healthy diet nor physical activity nor a correct
	hygiene), pain, existing entourage and absence of entourage. Curves are shown on the figures
	3, 4, 5 and 6.

Table 3 :

 3 Unrefined Hazard RatioIt showed that painful patients as well as patients having an unhealthy way of life had a higher risk of decompensation. The absence of entourage seemed also to increase the risk of

	Variable	HR	IC95%	p
	Unhealthy lifestyle	2,09 [ 1,03 ; 4,24 ] 0,042
	Pain	2,42 [ 1,18 ; 4,96 ] 0,015
	Existing entourage	0,10 [ 0,01 ; 0,77 ] 0,028
	Absence of entourage	10,20 [ 1,29 ; 80,63 ] 0,028

Table 4 :

 4 Adjusted Hazard Ratio

Two variables appeared significant, i.e with a p-value less than 0.05 and a confidence interval not containing 1. According to this final model, a unhealthy way of life (no healthy diet, physical activity nor correct hygiene) was a risk factor of decompensation (HR= 2.53 ; 95%CI

[1.23-5.19]

) as well as pain (HR=2.18 ; 95%CI

[1.07-4.44]

).

  . Among them, Numeric Rating Scales (NRS), Visual Analogue Scales (VAS),

	Verbal Rating Scales (VRS) and Facial Pain Scales (FPS) should be cited. Hetero-evaluation
	scales, such as DOLOPLUS-2, Pain Assessment IN Advanced Dementia Scale (PAINAD),
	Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC),

Echelle Comportementale pour Personnes Agées (ECPA), are used for people suffering from severe cognitive impairments or unable to communicate. Although no pain scale is validated with the elderly (58), the HAS (Haute Autorité de Santé) recommends using DOLOPLUS-2

Table 5 :

 5 Difficulties and propositions for further studies

	Difficulties	Propositions
	Small cohort	A second period of inclusion from July to
		December 2015 included 54 additional patients
		in the cohort.
	Same answers for each patient for question	Questions were removed in the new
	q13, 22, 23, 32, 33, 41	questionnaire
	Important number of variables

  Instabilité posturale (Est-ce que le patient est capable de tenir sur une jambe sans bouger les bras pendant les 5 premières secondes // A ne tester que chez les patients marchant, l'expertise du médecin sera considérée comme valable pour les patients alités) Catégories socioprofessionnelle (selon INSEE) A noter que la notion de chômage est recueillie par ailleurs. Ainsi en cas de recherche d'emploi noter la profession recherchée.

	7) Existence de complication(s) des pathologies aigues (exemple : OAP secondaire à un IDM,
	détresse respiratoire sur bronchite aigue...) 13) Mode de vie (cocher l'item si oui sinon cocher la dernière case)
	 Oui  Hygiène correcte  Non  Activité physique
	 Alimentation saine
	8) Quels sont les facteurs de risque somatiques du patient ?  Aucune de ces réponses
	 Antécédents familiaux cardio-vasculaires
	 Surpoids 14) Sexe
	 Immunodépression (cancer, alcoolisme, traitement immunosuppresseur)  Homme  Aucune de ces réponses  Femme
	15) Date de naissance 9)  Oui  Non 16)  Agriculteur / exploitant agricole 10) Nombre de chutes au cours des douze derniers mois  Artisan, commerçant, chef d'entreprise
	 0  Cadre et professions intellectuelles supérieures
	 1  Professions intermédiaires
	 2  Employés
	 3 et plus  Ouvriers
	 Sans activité (ex: femme au foyer)
	11) Quels sont ses facteurs de risque psychologiques ?
	 Conduites à risque (sports extrêmes, relations sexuelles à risque, conduite
	automobile...)
	 Risque suicidaire
	 Addiction(s)
	 Aucune de ces réponses ou aucun facteur de risque
	Multimorbidity concerns a higher number of people with increasing age, especially in nursing 12) Quels sont ses facteurs de risque psychosociaux ?
	homes. Its consequences weigh heavily both at the individual and societal scales. This study  Chômage
	suggests pain and adverse lifestyle factors as risk factors of decompensation among people  Conjugopathie
	 Stress au travail residing in long-term facilities.  Problèmes familiaux
	More powerful studies are needed to confirm these findings. They may assist in developing  Précarité financière et sociale
	 Décès d'un ou plusieurs proche(s) clinical tools to better prevent multimorbidity's outcomes and improve quality of care in  Divorce
	nursing homes.  Aucune de ces réponses
	56

patients were expected but only 64 were included. It could have been higher :

SERMENT D'HIPPOCRATE

« Au moment d'être admis à exercer la médecine, je promets et je jure d'être fidèle aux lois de l'honneur et de la probité.

Mon premier souci sera de rétablir, de préserver ou de promouvoir la santé dans tous ses éléments, physiques et mentaux, individuels et sociaux.

Je respecterai toutes les personnes, leur autonomie et leur volonté, sans aucune discrimination selon leur état ou leurs convictions. J'interviendrai pour les protéger si elles sont affaiblies, vulnérables ou menacées dans leur intégrité ou leur dignité. Même sous la contrainte, je ne ferai pas usage de mes connaissances contre les lois de l'humanité. J'informerai les patients des décisions envisagées, de leurs raisons et de leurs conséquences. Je ne tromperai jamais leur confiance et n'exploiterai pas le pouvoir hérité des circonstances pour forcer les consciences.

Je donnerai mes soins à l'indigent et à quiconque me le demandera. Je ne me laisserai pas influencer par la soif du gain ou la recherche de la gloire.

Admis dans l'intimité des personnes, je tairai les secrets qui me seront confiés. Reçu à l'intérieur des maisons, je respecterai les secrets des foyers et ma conduite ne servira pas à corrompre les moeurs.

Je ferai tout pour soulager les souffrances. Je ne prolongerai pas abusivement les agonies. Je ne provoquerai jamais la mort délibérément.

Je préserverai l'indépendance nécessaire à l'accomplissement de ma mission. Je n'entreprendrai rien qui dépasse mes compétences. Je les entretiendrai et les perfectionnerai pour assurer au mieux les services qui me seront demandés. J'apporterai mon aide à mes confrères ainsi qu'à leurs familles dans l'adversité.

Que les hommes et mes confrères m'accordent leur estime si je suis fidèle à mes promesses ; que je sois déshonoré et méprisé si j'y manque. »

Preserving and/or enhancing elderly's diet and physical activity can significantly ameliorate health status and quality of life and delay death or hospitalization.

Analysis of experienced difficulties a. Small sample size

Only 64 patients on the 127 expected were enrolled in the cohort. Length of the questionnaire may hindered GPs motivation, because its filling was time-consuming whereas their workload is already heavy. Time constraints, the additional administrative task brought by research projects, concern about medical data utilization and lack of recognition are reported by several authors as GPs'reluctances to get involved in primary health care research [START_REF] Hummers-Pradier | Simply no time? Barriers to GPs' participation in primary health care research[END_REF][START_REF] Rossi | Research interest by general practitioners: a survey[END_REF][START_REF] Rosemann | General practitioners' attitudes towards research in primary care: qualitative results of a cross sectional study[END_REF]. However, Supper and al pointed out that 30% of 85 family physicians wished take part in a research project (100). Motivation is higher when GPs judge the research topic relevant for daily practice and when they can ameliorate quality of their care from it [START_REF] Rossi | Research interest by general practitioners: a survey[END_REF][START_REF] Rosemann | General practitioners' attitudes towards research in primary care: qualitative results of a cross sectional study[END_REF].

Visiting GPs in person and proposing financial incentives could have improved GPs participation as suggested by some authors [START_REF] Rosemann | General practitioners' attitudes towards research in primary care: qualitative results of a cross sectional study[END_REF](101)(102)(103). To overcome forgetfulness of some investigators, reminders were sent.

The second period of inclusion enrolled 54 other patients, what resulted in a global cohort of 118 patients. A further thesis will analyze all the patients at eighteen months.

b. Pertinence of some questions

Since the questionnaire was also used for another study concerning a outpatient cohort some propositions were not suitable for nursing home residents. It was those about unemployment, stress at work (question 12), material available to the patient (question 32), human aid available (question 33) and life in institution (question 41).

c. Subjectivity of the « Expertise of the GP » assessment

The initial EGPRN's definition of multimorbidity [START_REF] Reste | The European General Practice Research Network Presents a Comprehensive Definition of Multimorbidity in Family Medicine and Long Term Care, Following a Systematic Review of Relevant Literature[END_REF] was detailed in eleven themes and subthemes thanks to several qualitative works. Submission of the definition to GPs coming from different European countries added two supplementary themes (104): the use of Wonca's core competencies of general practice, also said GP's expertise, and the dynamics of the doctorpatient relationship. The eight last questions of the questionnaire explored these themes.

Though GPs' self-criticism is not evident to respond them and answers can only be subjective.

APPENDIX


Cédric Julien

François-Xavier Irisarri

Dimitri Bettebghor

Florian Lavelle

Kévin Mathis

Optimisation of sandwich composite structures for spatial applications

Optimisation of sandwich composite structures for spatial applications

Cédric JULIEN, François-Xavier IRISARRI, Dimitri BETTEBGHOR ONERA

Florian LAVELLE, Kevin MATHIS CNES Context

With the increasing use of advanced composite materials in aerospace structures, comes the matter of the optimal design of composite structures. Indeed, even after several decades of experience, the aeronautic industry is still looking for the best practice for designing composite structures. The most advanced methods that are currently used are either very computationally expensive, or require massive and costly experimental validations, thus limiting the use of these methods to the most critical parts only.

For the more common parts, design is conducted with the traditional approach which relies on very conservative guidelines that hamper the development of design tools that would really take advantage of the freedom-of-design offered by composite structures. The consequence is the oversizing of the structures, as a mean to compensate for their lack of sound physical basis. As a result, the specificities and advantages of the composite materials are not fully exploited, and composite solutions are often undervalued compared to metallic solutions, much more readily available. This issue is just as critical for the spatial industry, and in particular for CNES, the French space Agency, which design tools have proven to be outdated with regard to the design of the Ariane VI launcher.

Indeed, as the aerospace industry always require lighter, reusable and cheaper launchers, research effort is needed to devise new design tools for launchers structures. As in the aeronautic industry, the use of CFRP materials has always been seen as a key driver to maximize payload while maintaining high structural integrity. However, unlike aircraft industry where use of composite has been driven by aeroelastic issues in addition to weight savings, there is no part of the launcher where unconventional mechanical couplings have been seen as useful as, for instance, the shear/tension coupling in a composite wing. Nevertheless, composites have naturally been integrated into launchers as their use has always been reported beneficial for bending-dominated and prone-tobuckling structures, which launchers typically are.

(Figure 1, view of the Ariane V SYLDA).

Historically, and very similarly to aircraft structures, design approach for buckling of composite structures in launchers rely on the former NASA Technical Note from 1968 (NASA SP-8007) that considers the laminate as a kind of special metal and rely on traditional design approaches for metallic structures. In particular, the stacking sequence is often considered fixed and is not a full design variable. This traditional approach, so-called 'black metal' by its simplicity and proximity to metallic structures has often been the only design approach for space structures. The drawback of this method is once again that it does not fully benefit from the use of composites.

Over the recent years, the space industry has been experiencing a revolution with the arrival of SpaceX and their reusable launchers that will dramatically decrease the cost of launch. As a result, the competition between launcher manufacturers, with respect to the performance/cost ratio of these structures, has probably never been as fierce. It is expected that the massive use of new materials and new manufacturing processes will lead to a leap in those performances. According to the European Space Agency, the Future Launcher Preparatory Program will integrate many new CFRP components, both in unpressurised and pressurised (cryogenic propellant) structures.

In this context, in order to face the increasingly complex design of composite structures, and owing to the relative absence of integrated design composite tools, CNES and ONERA have decided to join their efforts in developing a novel tool for the optimal design of composite structures, which aims to cover the whole design process of a structure, from the search for the structural concept to the prediction of damage and failure in the most critical areas. This tool would take into account a large number of the specificities of these materialsanisotropic nonlinear behaviour, manufacturing constraints,… --and would be applicable to a large range of structures, from cylindrical shells to lattice structures, and of processes (e.g. draping, fibre placement, thermomoulding, etc…). This article presents the outcome of the first step of this large project which has taken place from 2015 to 2017, and has resulted in the development of a prototype tool implemented in Python 3. This prototype carries out a new global design strategy that allows to size large-scale composite sandwich structures. In the following we describe how this tool interacts with commercial FE software (MSC Nastran), and demonstrate its efficiency on the testcase of the SYLDA payload adapter (see Figure 1).

Overview of the optimisation strategy (Figure 2, workflow of the XComp optimisation tool)

Figure 2 shows the principle of the global design strategy used in this work. It follows in essence the indirect two-step approach described in the literature [ref], where the material is first seen as an homogenised equivalent material, characterized by its total thickness and a set of stiffness parameters that fully define the elastic behaviour of the material. These continuous parameters are then used as design variables for a first optimisation step of mass minimisation, where the mechanical specifications of the structure are enforced as the optimisation constraints. Then, the continuous thickness distribution and stiffness distribution are used as the target for a second optimization problem, where the variables are the number and the orientations of the layers that define the composite lay-ups. The outcome of the second optimisation step is a fullydefined composite structure.

The major advantage of the two-step approach is to deal separately with structural analysis and laminate combinatorial optimisation which enables to optimize complex composite structures within practical computational time. Indeed, the first step combines computationally expensive finite element analysis of the structures with efficient gradient-based optimisation while the second step combines computationally expensive laminate lay-up combinatorial optimisation with analytic evaluation of the homogenised shell stiffness. Nonetheless, this strategy comes with a significant disadvantage. Since no structural analysis is performed at the second optimisation step, it falls to the designers to check that the design fulfils its specifications and then to repair the solution as needed. To overcome this limitation and adapt the tool for composite sandwich materials our approach differs from the general twostep scheme in several ways. First, the material here is a composite sandwich, that is to say a thick shell made of two identical thin monolithic composite skins, and a thick NIDA core in between them. However, for any given material for the NIDA core, a sandwich shell can be treated as a homogeneous shell, whose behaviour is fully described by the thicknesses of both the skin and the core, and the stiffness properties of the skin. These properties are thus the variables of the first optimisation step. Indeed, the membrane and bending stiffness matrices of the sandwich panels are parameterised using the stiffness of the skins, the thickness of the core material as well as the thickness of the skins. Additionally, for thick sandwich shells, transverse shear stiffness cannot be neglected. In the present work, the transverse shear stiffness matrix of the sandwich material is evaluated as a function of the design variables, using a dedicated response surface.

In the second optimisation stepstacking sequence retrievalthe composite skins are not represented as the usual lay-up of unidirectional layers. Rather, we use the Stacking Sequence Table (thereafter SST) representation.

(Figure 3, view of a Stacking Sequence

Table),

This representation allows us, among other things, to enforce manufacturing constraints related to the blending of the composite panels, in a variable thickness structure (for instance, the proper spacing of ply-drops). The corresponding stacking sequence retrieval problem is solved using a dedicated evolutionary algorithm [REF].

Finally, we introduce a third optimisation step, which goal is to restore the feasibility of the final result, with respect to the mechanical constraints. Indeed, when optimising the composite lay-ups, the thickness of the structure at any given location is rounded to a discrete number of layers. It is then very likely that at least one of the mechanical constraints will be violated in the process. This last step allows the design to evolve slightly (adding or substracting at most one layer) in order to ensure that the final solution remains within the feasible domain. As a final note, the first and third optimisation steps are run with the FE optimization software MSC Nastran SOL 200, while the second step (Layup optimisation) is performed through the use of an in-house code.

Optimisation of Ariane 5 SYLDA.

The application case showed here is derived from a typical aerospace structure : the Ariane 5 SYLDA payload adapter.

(Figure 4, geometry of the A5 SYLDA).

Let us note however that we do not intend to reproduce or elaborate on the actual design process of this part. Rather, we use its mechanical specifications to define an optimization problem that will be solved using our global design strategy. The results should thus not be interpreted as potential gains on the real structure, since a significant number of constraints and specifications of the real structure are not considered here, but as a proof of concept of this strategy.

The objective of the overall design problem is to minimize the weight of the structure while enforcing several mechanical constraints :

 obtaining a minimal global stiffness of the structure,  preserving the initial performance w.r.t. buckling,  ensuring that no failure occurs in the composite skins.

The optimization variables are the thickness of the skins and the core, as well as a set of stiffness parametersthe lamination parameters [ref] that fully characterize the behavior of the sandwich shell. A dedicated GUI is used to enter the parameters of the optimization problem, such as the materials for the elementary layer and the core, or the admissible range for the variables. The user is also allowed to subdivide the part as needed in order to design separate composite lay-ups. Here for instance we choose to separate the upper and lower cones from the center cylindrical body of the SYLDA, as shown in Figure 3.

Below we show the results of this test run on the Ariane 5 SYLDA, when only the global stiffness constraint is enforced.

Table 1 gives, for each zone of the structure, the optimal composite lay-up of the sandwich skins, as well as the optimal core thickness. This design results in a gain of 11.5% on the total weight of the structure, while the mechanical constraints remain valid. The gain in weight was achieved mainly thanks to fewer plies in the skin. Let us note again that the proposed design may not be technologically feasibleespecially considering the excessively thin cores of the sandwich shellsbut still shows that the global design strategy developed in this work is able to significantly improve a design based on a given bill of specifications, while being readily available for use in a design office. Indeed, as far as computation times are concerned, the whole process lasted less than fifteen minutes.

In the light of these promising results, further work is currently in progress in order to improve the tool and expand its capabilities. For instance, the analysis described above is being performed again but with a much broader set of mechanical constraints, in order to validate the strategy on a realistic test case. Additionally, this optimization tool will soon be applied to stiffened panels, and is expected to be able to find the number, shape, and lay-ups of composite stiffeners optimal for any given structure.

Conclusion

In this paper we introduced a novel global design strategy for composite structures. The goal of this strategy is to improve the design of a composite structure based on its specifications, while taking into account a large number of the specificities of these materials. A prototype version of this design tool shows very promising results. As a result, the development of an advanced version of this tool is underway. This advanced version will introduce new functionalities, such as taking into account damage initiation or failure prediction, or optimizing a structure with respect to cost/process constraints. Ultimately, the tool would also be able to guide the designer in finding the optimal shape and process for the part, in order to, finally, fully exploit the potential of the composite materials in aerospace structures.

Contact :

Cédric JULIEN cedric.julien@onera.fr Florian Lavelle florian.lavelle@cnes.fr Table 1

  Figure 1

Figure 4

 4 Figure 4