110 research outputs found
Triglycerides and glycated hemoglobin for screening insulin resistance in obese patients
International audienceOBJECTIVE: Assessment of insulin resistance (IR) is essential in non-diabetic patients with obesity. Thus study aims to identify the best determinants of IR and to propose an original approach for routine assessment of IR in obesity. DESIGN AND PATIENTS: All adult with obesity defined by a body mass index >=30kg/m2, evaluated in the Nutrition Department between January 2010 and January 2015 were included in this cross-sectional study. Patients with diabetes were excluded. IR was diagnosed according to the HOMA-IR. Based on a logistic regression, we determined a composite score of IR. We then tested the variables with a principal component analysis and a hierarchical clustering analysis. RESULTS: A total of 498 patients with obesity were included. IR was associated with grade III obesity (OR=2.6[1.6-4.4], p\textless0.001), HbA1c>=5.7% (OR=2.6[1.7-4.0], p\textless0.001), hypertriglyceridemia \textgreater1.7mmol/l (OR=3.0[2.0-4.5], p\textless0.001) and age (OR=0.98[0.96-0.99], p=0.002). Exploratory visual analysis using factor map and clustering analysis revealed that lipid and carbohydrates metabolism abnormalities were correlated with insulin resistance but not with excessive fat accumulation and low-grade inflammation. CONCLUSIONS: Our results highlight the interest of simple blood tests such as HbA1c and triglyceride determination, which associated with BMI, may be widely available tools for screening IR in obese patients
Comparison of HbA1c detection in whole blood and dried blood spots using an automated ion-exchange HPLC system
International audienceAIM: Hemoglobin A1c (HbA1c) is a widely recognized analyte for diagnosing and monitoring diabetes. Dried blood spot (DBS) constitutes a useful alternative to blood collection by venipuncture. Analytical and clinical validation of DBS use is, however, necessary before implementation.Results/methodology: HbA1c levels from whole blood or DBS from a cohort patients with diabetes were compared. DBS specimens were stable at ambient temperature. HbA1c detection on DBS was accurate, robust, and the correlation and agreement with whole blood values was excellent.CONCLUSION: this study provides for the first time a complete method comparison and validation under the ISO15189 guideline using an automated HPLC system. This approach constitutes, therefore, a useful tool for diagnosing diabetes
Intact Fish Skin Graft vs. Standard of Care in Patients with Neuroischaemic Diabetic Foot Ulcers (KereFish Study) : An International, Multicentre, Double-Blind, Randomised, Controlled Trial Study Design and Rationale
Publisher Copyright: © 2022 by the authors.Background: Cell and/or tissue-based wound care products have slowly advanced in the treatment of non-healing ulcers, however, few studies have evaluated the effectiveness of these devices in the management of severe diabetic foot ulcers. Method: This study (KereFish) is part of a multi-national, multi-centre, randomised, controlled clinical investigation (Odin) with patients suffering from deep diabetic wounds, allowing peripheral artery disease as evaluated by an ankle brachial index equal or higher than 0.6. The study has parallel treatment groups: Group 1 treatment with KerecisŸ Omega3 Wound⹠versus Group 2 treatment with standard of care. The primary objective is to test the hypothesis that a larger number of severe diabetic ulcers and amputation wounds, including those with moderate arterial disease, will heal in 16 weeks when treated with KerecisŸ Omega3 Wound⹠than with standard of care. Conclusion: This study has received the ethics committee approval of each participating country. Inclusion of participants began in March 2020 and ended in July 2022. The first results will be presented in March 2023. The study is registered in ClinicalTrials.gov as Identifier: NCT04537520.Peer reviewe
Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study
Background: Approximately 450â000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63â093 individuals in the FHSC registry, 11â848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11â476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11â848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10â099 (89·9%) of 11â235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11â848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10â202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10â804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10â428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life
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Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990â2021: a systematic analysis for the Global Burden of Disease Study 2021
BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56â604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100â000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100â000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100â000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100â000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100â000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation
L'insulinorĂ©sistance chez l'hommeâ: des mĂ©canismes aux interventions nutritionnelles
International audienceObesity is presently regarded as the "the first non-infectious epidemic outbreak" in the history of Humanity. It is a multifactorial pathology, that contributes to the emergence of insulinoresistancy. Some obese individuals display an obesity qualified as metabolically sound, i.e., non-associated with metabolical anomalies. The present paper reviews the different possible mechanisms responsible for insulin-resistancy.LâobĂ©sitĂ© est aujourdâhui considĂ©rĂ©e comme «âla premiĂšre Ă©pidĂ©mie non infectieuse de lâhistoire de lâhommeâ». Câest une pathologie multifactorielle qui contribue Ă lâapparition de lâinsulinorĂ©sistance (IR). Certains sujets obĂšses prĂ©sentent une obĂ©sitĂ© dite mĂ©taboliquement saine, non associĂ©e Ă des anomalies mĂ©taboliques. Le prĂ©sent article passe en revue les diffĂ©rents mĂ©canismes possibles Ă lâorigine de lâIR
Facteurs prédictifs d'ischémie myocardique silencieuse et de sténoses coronaires dans une population de diabétiques asymptomatiques à haut risque vasculaire
MONTPELLIER-BU MĂ©decine UPM (341722108) / SudocPARIS-BIUM (751062103) / SudocMONTPELLIER-BU MĂ©decine (341722104) / SudocSudocFranceF
Social Deprivation, Healthcare Access and Diabetic Foot Ulcer: A Narrative Review
International audienceThe diabetic foot ulcer (DFU) is a common and serious complication of diabetes. There is also a strong relationship between the environment of the person living with a DFU and the prognosis of the wound. Financial insecurity seems to have a major impact, but this effect can be moderated by social protection systems. Socioeconomic and socio-educational deprivations seem to have a more complex relationship with DFU risk and prognosis. The area of residence is a common scale of analysis for DFU as it highlights the effect of access to care. Yet it is important to understand other levels of analysis because some may lead to over-interpretation of the dynamics between social deprivation and DFU. Social deprivation and DFU are both complex and multifactorial notions. Thus, the strength and characteristics of the correlation between the risk and prognosis of DFU and social deprivation greatly depend not only on the way social deprivation is calculated, but also on the way questions about the social deprivationâDFU relationship are framed. This review examines this complex relationship between DFU and social deprivation at the individual level by considering the social context in which the person lives and his or her access to healthcare
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