<i>Journal of Diabetes</i> NEWS
Notice bibliographique
Résumé
The European Association for the Study of Obesity (EASO) held its 19th European Congress on Obesity (ECO) on 9–12 May 2012 in Lyon, France, to discuss what is arguably one of the fastest growing public health problems worldwide. Obesity has risen to the forefront of government and public health initiatives due to its association with several comorbid conditions, such as type 2 diabetes, cardiovascular disease, and hypertension among others. Attendees gathered at ECO to learn about all the latest developments in the management, treatment, and scientific understanding of obesity. Below, we present some of the highlights from the meeting (http://www.eco2012.org/documents/Final ECO2012Programme-AtAGlance.pdf, accessed 4 June 2012). At the opening plenary lecture, Dr Arnaud Basdevant, MD (Institut Cardiometabolisme et Nutrition, Paris, France), emphasized the heterogeneity of obesity, advocating a systems-based approach for the diagnosis, stratification, and treatment of patients with obesity. As a greater understanding is emerging about the pathogenesis of this disease, it has become more apparent that there are multiple phenotypes associated with obesity, and patients may be differentially treated based on their specific subtype. Dr Basdevant suggested that the current categorization of obesity phenotypes is rudimentary at best because body mass index (BMI) remains the cornerstone of classification and is not particularly useful. Dr Basdevant proposed that other factors be assessed, such as fat mass, adipose tissue structure, inflammation, fibrosis, and ectopic fat. Dr Basdevant stated that in his ideal future diagnoses would be based on individual health signatures that include hundreds of data points; the challenge is to identify robust and easy-to-use composite markers. The talks for the remainder of the conference tended to focus on treatment options for obesity, with a particular emphasis on pharmaceutical drugs in development. Arya Sharma, MD, PhD (University of Alberta, Alberta, Canada), stated that at least a 10% reduction in body weight must be seen to have a significant long-term impact on health. He commented that surgery is currently the most efficacious option in treating severe obesity, but it does not provide a population-level solution. Conversely, lifestyle modification is difficult to sustain and there are currently no drugs available on the market that bring about ≥10% weight loss. Fortunately, two drugs in development appear to have achieved that benchmark: phentermine/topiramate (Qnexa; Vivus, Mountain View, CA, USA) surpassed this threshold in the EQUIP trial,1 and liraglutide (Victoza; Novo Nordisk, Basgsværd, Denmark) could potentially meet this efficacy threshold in its ongoing development program. The EQUIP trial enrolled morbidly obese patients and found that a high dose of phentermine/topiramate brought about a 12–14% weight loss.1 In addition, Stephan Rössner, MD, PhD (Karolinska Institute, Stockholm, Sweden), demonstrated in the CONQUER trial (which also enrolled obese patients with serious comorbidities) that patients receiving phentermine/topiramate experienced significantly more weight loss versus placebo, irrespective of their baseline Edmonton Obesity Staging System (EOSS).2 The EOSS stratifies individuals based on their comorbidities and functional status as they relate to obesity.3 Those receiving the higher dose of phentermine/topiramate (15 mg/92 mg) lost, on average, between 9.5% and 10% of their baseline weight (depending on their EOSS stage), with between 45% and 48% of participants losing >10% of their baseline weight.4 Nick Finer, MBBS (University College London, London, UK), discussed a Phase II obesity dose-ranging trial for Novo Nordisk’s liraglutide (Victoza), a glucagon-like peptide (GLP)-1 currently approved for the treatment of type 2 diabetes. Dr Finer presented several post hoc analyses on a Phase II trial evaluating the efficacy of liraglutide for weight loss in obese patients without type 2 diabetes. Liraglutide 3.0 mg responders (those who lost ≥5% of weight 12 weeks after the initiation of therapy) who completed 1 year of therapy experienced 10.3% weight loss from baseline, and an average of 35.6% excess body weight loss. In addition, the numbers needed to treat (NNT) to achieve 5% or 10% weight loss with liraglutide 3.0 mg were highly favorable: two patients would need to be treated for one to achieve 5% weight loss, and only three patients would need to be treated for one to achieve 10% weight loss. Dr Finer noted that defining responder/non-responder status would allow for the development of stopping rules to asses the real-world health economic benefits for liraglutide and other obesity medications, whereas using excess body weight loss and NNT as measures could provide a more optimistic interpretation of data to patients and healthcare providers, also allowing for easier comparison with surgery (although baseline BMI would still need to be taken into account). Ian Caterson, MD, PhD (University of Sydney, Sydney, NSW, Australia), presented the results of a recent analysis of the Sibutramine Cardiovascular OUTcome Trial (SCOUT) that contradicted previous results linking the withdrawn anti-obesity drug Meridia (Abbott, North Chicago, IL, USA) with increased cardiovascular risk. The original analysis of SCOUT found that treatment with sibutramine increased the risk of cardiovascular events by 16% above placebo.5 This conclusion led to Meridia’s withdrawal from all major markets in 2010. However, Dr Caterson’s analysis concluded that intentional weight loss, with or without the use of Meridia, was associated with a reduction of cardiovascular risk.6 Dr Caterson commented that these new results suggest that including patients who did not lose weight in the initial analyses masked the potential benefits of weight loss, with and without pharmacotherapy. Based on this new information, Dr Caterson suggested there may be potential to reconsider the use of the drug given the few obesity drugs currently available. In addition to drugs, there was an interesting talk by Michael Rosenbaum, MD (Columbia University, New York, NY, USA), about the importance of not only losing weight, but also preventing weight regain. He pointed out that the available data suggest long-term weight loss maintenance is only successful 5.9–20% of the time. Notably, Dr Rosenbaum pointed out that the amount of weight loss did not predict the likelihood of successful weight loss maintenance. Part of the difficulty with sustaining weight loss is that following weight loss individuals enter a hypometabolic state: they expend less energy than expected at their new weight due, in part, to increased muscle efficiency. Dr Rosenbaum noted that energy expenditure will drop by approximately 22% (∼300–500 kcal/day) with every 10% decrease in caloric intake.7,8 Thus, in order to maintain a lower weight, individuals must eat even less or exercise more to make up for the observed decline in non-resting energy expenditure. Given the difficulty of maintaining weight loss and the low success rate of weight loss maintenance, Dr Rosenbaum noted that there remains much room for innovation of therapeutics in this area. One last presentation of note that we attended was delivered by Tiphaine Le Roy, PhD (MICALIS, Jouy en Josas, France), on the role of gut microbiota in the development of obesity, type 2 diabetes, and non-alcoholic fatty liver disease. She highlighted the results from a study that transplanted the gut microbiota from either mice that responded to a high-fat diet (exhibited increased insulin resistance and hepatic fat content) or mice that did not respond to a high-fat diet (gained weight but maintained normal glucose tolerance, insulin sensitivity, and hepatic fat content) into a group of germ-free mice. The results demonstrated a clear difference between mice (RR) transplanted with gut microbiota from responders (i.e. those gaining weight) and mice (NRR) that received microbiota from non-responders to a high-fat diet. More specifically, fasting glucose levels in NRR and RR mice were 100 and 140 mg/dL, respectively. Similarly, fasting insulin levels were 50% higher in the RR mice, homeostatic model assessment of insulin resistance (HOMA-IR) was double in RR mice, and hepatic steatosis only occurred in RR mice. Dr Le Roy concluded that the results suggest that gut microbiota play a causal role in the development of type 2 diabetes and hepatic steatosis in mice. However, whether these findings are translatable to humans remains unclear.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».