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Screening for pulmonary tuberculosis in high-risk groups of diabetic patients.

糖尿病患者高危人群肺结核筛查。

  • 影响因子:2.89
  • DOI:10.1016/j.ijid.2020.01.019
  • 作者列表:"Ji Y","Cao H","Liu Q","Li Z","Song H","Xu D","Tian D","Qiu B","Wang J
  • 发表时间:2020-01-21
Abstract

BACKGROUND:The double burden of diabetes mellitus (DM) and tuberculosis (TB) has attracted increasing attention because DM not only increases the risk of active TB but also affects treatment outcomes. Screening for TB among diabetic patients has been recommended but requires real-world evidence by considering its cost-effectiveness, cost-utility and cost-benefit. METHODS:We carried out a screening program in Jiangyin City of Jiangsu Province, China. A total of 14869 diabetic patients received regular physical examination for three consecutive years and were followed for the diagnosis of TB. We evaluated the cost of screening and the effectiveness, utility and social benefits attributed to the program. We further conducted a matched case-control study and used the nomogram to identify the high-risk groups that can be the target population for screening. RESULTS:Among 14869 diabetic patients who participated in this screening program, 22 were diagnosed with TB, resulting in an incremental cost-effectiveness ratio (ICER) of 83,910 CNY per disability-adjusted life year (DALY) gained and a cost-benefit ratio of 0.50. If we limited the screening program to high-risk diabetic patients by considering body mass index (BMI), fasting blood glucose (FBG) and triglycerides, the ICER decreased to 34,303 CNY per DALY gained, and the cost-benefit ratio increased to 1.22. CONCLUSIONS:Screening TB using regular chest X-ray examination is feasible but not economical in areas with a low incidence of TB. It is recommended to select diabetic patients with low BMI, high FBG and low triglycerides as screening subjects for TB.

摘要

背景: 糖尿病 (DM) 和结核病 (TB) 的双重负担日益受到关注,因为 DM 不仅增加活动性 TB 的风险,而且影响治疗结果。已经推荐在糖尿病患者中进行结核病筛查,但需要考虑其成本效益、成本效用和成本效益的真实证据。 方法: 在中国江苏省江阴市开展筛查项目。共有 14869 名糖尿病患者连续三年接受定期体检,并被随访诊断为结核病。我们评估了筛查的成本以及归因于该项目的有效性、效用和社会效益。我们进一步进行了匹配的病例对照研究,并使用列线图确定可作为筛查目标人群的高危人群。 结果: 在参与该筛查项目的 14869 例糖尿病患者中,有 22 例被诊断为 TB,导致增量成本-效果比 (ICER) 每残疾调整生命年 (DALY) 获得 83,910 元人民币,成本效益比为 0.50。如果我们通过考虑体重指数 (BMI) 、空腹血糖 (FBG) 和甘油三酯将筛查项目限制在高危糖尿病患者,ICER 下降到每增加 DALY 34,303 CNY, 成本效益比增加到 1.22。 结论: 在结核病发病率低的地区,常规胸部 x线检查筛查结核病是可行的,但并不经济。推荐选择低 BMI 、高 FBG 、低甘油三酯的糖尿病患者作为结核病的筛查对象。

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影响因子:2.86
发表时间:2020-01-08
来源期刊:Acta Diabetologica
DOI:10.1007/s00592-019-01469-5
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
翻译标题与摘要 下载文献
影响因子:19.14
发表时间:2020-01-01
来源期刊:Nature Medicine
DOI:10.1038/s41591-019-0724-8
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
影响因子:4.34
发表时间:2020-01-27
DOI:10.1128/AAC.01777-19
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.

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