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Does intensive glycaemic control promote healing in diabetic foot ulcers? - a feasibility study.


  • 影响因子:2.65
  • DOI:10.1136/bmjopen-2019-029009
  • 作者列表:"Dissanayake A","Vandal AC","Boyle V","Park D","Milne B","Grech R","Ng A
  • 发表时间:2020-01-20

INTRODUCTION:One in four diabetes patients will develop a foot ulcer over their lifetime. The role of glycaemic control in the healing of foot ulcers in diabetes patients is not supported by randomised controlled trial (RCT) data. OBJECTIVES:To determine the feasibility of an RCT of glycaemic control with intensive insulin therapy in diabetic foot ulcer, by assessing: entry criteria, fasting capillary blood glucose (FCBG) medication satisfaction and sensitivity of different ulcer-healing endpoints to glycaemic control. DESIGN:Two substudies: one cross-sectional and one single-arm prospective. SETTING:Single-centre secondary care diabetic foot clinic in New Zealand. PARTICIPANTS:Substudy 1: 78 participants consisting of all people ≥18 years with a diabetic foot ulcer presenting to the clinic over 35 weeks in 2015.Substudy 2: 15 participants from Substudy 1 consenting to intensive insulin therapy. INTERVENTION:Substudy 1: None.Substudy 2: Intensive insulin therapy with standard podiatry care over 24 weeks. OUTCOME:Substudy 1: Proportion of participants satisfying potential RCT entry criteria; medication satisfaction (Diabetes Medication Satisfaction).Substudy 2: FCBG, index ulcer healing time, index ulcer size, health-related quality of life (HRQoL; EuroQol 5 Dimensions 5 Levels and Diabetic Foot Ulcer Scale-Short Form). RESULTS:Proportion in Substudy 1 satisfying all entry criteria was 31% (95% CI 21 to 42). FCBG values decreased between baseline and study end (difference -3.7 mmol/L, 95% CI -6.5 to -0.8); 83% (95% CI 44 to 95) of ulcers healed by 24 weeks. FCBG correlated negatively with medication satisfaction. Ulcer area logarithm was most sensitive to FCBG changes, displaying significant negative correlation with HRQoL outcomes. Detecting a 30% between-group difference in this outcome (80% power, α=5%) requires 220 participants per arm, achievable within 1 year with 15 centres similar to study setting. CONCLUSIONS:An adequately powered RCT requires cooperation between a large number of centres. Ulcer area logarithm should be primary endpoint. TRIAL REGISTRATION NUMBER:ANZCTR ACTRN12617001414303.


导读: 每四个糖尿病患者中就有一个会在一生中发展成 1英尺的溃疡。血糖控制在糖尿病患者足部溃疡愈合中的作用不受随机对照试验 (RCT) 数据的支持。 目的: 通过评估: 进入标准,空腹毛细血管血糖 (FCBG),确定胰岛素强化治疗控制糖尿病足溃疡血糖的 RCT 的可行性药物满意度和不同溃疡愈合终点对血糖控制的敏感性。 设计: 两个子研究: 一个横断面研究和一个单臂前瞻性研究。 单位: 新西兰单中心二级护理糖尿病足诊所。 参与者: 子研究 1: 78 名参与者,包括 2015年就诊超过 35 周的所有 ≥ 18 岁糖尿病足溃疡患者。子研究 2: 子研究 1 的 15 名参与者同意强化胰岛素治疗。 干预: 子研究 1: 无。子研究 2: 标准足部护理 24 周的强化胰岛素治疗。 结果: 子研究 1: 满足潜在 RCT 进入标准的参与者比例; 用药满意度 (糖尿病用药满意度)。子研究 2: FCBG 、指数溃疡愈合时间、指数溃疡大小、健康相关生活质量 (HRQoL; EuroQol 5 个维度 5 个水平和糖尿病足溃疡量表-简表)。 结果: 子研究 1 中满足所有入组标准的比例为 31% (95% CI 21 ~ 42)。FCBG 值在基线和研究结束之间下降 (差异-3.7 mmol/L,95% CI-6.5 至-0.8); 83% (95% CI 44 至 95) 的溃疡愈合 24 周。FCBG 与用药满意度呈负相关。溃疡面积对数对 FCBG 变化最敏感,与 HRQoL 结局呈显著负相关。检测该结局的 30% 组间差异 (80% 次方,α = 5%) 需要每组 220 名参与者,1 年内可实现,15 个中心与研究设置相似。 结论: 一个足够有力的 RCT 需要大量中心之间的合作。溃疡面积对数应为主要终点。 试用注册号: ANZCTR ACTRN12617001414303.



来源期刊:Acta Diabetologica
作者列表:["Benhalima, Katrien","Crombrugge, Paul","Moyson, Carolien","Verhaeghe, Johan","Vandeginste, Sofie","Verlaenen, Hilde","Vercammen, Chris","Maes, Toon","Dufraimont, Els","Block, Christophe","Jacquemyn, Yves","Mekahli, Farah","Clippel, Katrien","Den Bruel, Annick","Loccufier, Anne","Laenen, Annouschka","Minschart, Caro","Devlieger, Roland","Mathieu, Chantal"]

METHODS:Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA_1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.

关键词: 暂无
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来源期刊:Nature Medicine
作者列表:["Artzi, Nitzan Shalom","Shilo, Smadar","Hadar, Eran","Rossman, Hagai","Barbash-Hazan, Shiri","Ben-Haroush, Avi","Balicer, Ran D.","Feldman, Becca","Wiznitzer, Arnon","Segal, Eran"]

METHODS:Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy. Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring^ 1 – 4 . GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes^ 5 , 6 . Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model.

关键词: 暂无
翻译标题与摘要 下载文献
作者列表:["Lowes DJ","Hevener KE","Peters BM"]

METHODS::Repurposing of currently approved medications is an attractive option for the development of novel treatment strategies against physiological and infectious diseases. The antidiabetic sulfonylurea glyburide has demonstrated off-target capacity to inhibit activation of the NLRP3 inflammasome in a variety of disease models, including vaginal candidiasis, caused primarily by the fungal pathogen Candida albicans Therefore, we sought to determine which of the currently approved sulfonylurea drugs prevent the release of interleukin 1β (IL-1β), a major inflammasome effector, during C. albicans challenge of the human macrophage-like THP1 cell line. Findings revealed that the second-generation antidiabetics (glyburide, glisoxepide, gliquidone, and glimepiride), which exhibit greater antidiabetic efficacy than prior iterations, demonstrated anti-inflammatory effects with various degrees of potency as determined by calculation of 50% inhibitory concentrations (IC50s). These same compounds were also effective in reducing IL-1β release during noninfectious inflammasome activation (e.g., induced by lipopolysaccharide [LPS] plus ATP), suggesting that their anti-inflammatory activity is not specific to C. albicans challenge. Moreover, treatment with sulfonylurea drugs did not impact C. albicans growth and filamentation or THP1 viability. Finally, the use of ECE1 and Candidalysin deletion mutants, along with isogenic NLRP3-/- cells, demonstrated that both Candidalysin and NLRP3 are required for IL-1β secretion, further confirming that sulfonylureas suppress inflammasome signaling. Moreover, challenge of THP1 cells with synthetic Candidalysin peptide demonstrated that this toxin is sufficient to activate the inflammasome. Treatment with the experimental inflammasome inhibitor MCC950 led to similar blockade of IL-1β release, suggesting that Candidalysin-mediated inflammasome activation can be inhibited independently of potassium efflux. Together, these results demonstrate that the second-generation antidiabetic sulfonylureas retain anti-inflammatory activity and may be considered for repurposing against immunopathological diseases, including vaginal candidiasis.