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Pilates Method Training: Functional and Blood Glucose Responses of Older Women With Type 2 Diabetes.

普拉提方法训练: 老年女性 2 型糖尿病患者的功能和血糖反应。

  • 影响因子:2.59
  • DOI:10.1519/JSC.0000000000002704
  • 作者列表:"Melo KCB","Araújo FS","Cordeiro Júnior CCM","de Andrade KTP","Moreira SR
  • 发表时间:2020-02-20
Abstract

:Melo, KCB, Araújo, FdS, Cordeiro Júnior, CCM, de Andrade, KTP, and Moreira, SR. Pilates method training: Functional and blood glucose responses of older women with type 2 diabetes. J Strength Cond Res XX(X): 000-000, 2020-The objective of this study was to investigate the effect of 12 weeks of the Pilates method on the functional capacity (FC) and glycemic control of older women with type 2 diabetes (T2D). Twenty-two women with T2D were randomized into control (CONTROL: 67.5 ± 6.3 years; 154.7 ± 6.1 cm; 73.5 ± 6.1 kg) and Pilates (PILATES: 65.5 ± 5.5 years; 155.0 ± 4.5 cm; 66.2 ± 5.4 kg) groups, which held sessions of 60 minutes at a frequency of 3 times per week during 12 weeks. Blood glucose was measured before and after sessions in PILATES, as well as in moments of pre, rest, 4, 8, and 12 weeks of the PILATES and CONTROL interventions. The glycated hemoglobin (HbA1c) level before and after 12 weeks of the intervention was evaluated. The general index of the FC (GIFC) was obtained through a battery of tests for older patients with T2D. Analysis of variance detected differences in the GIFC for PILATES vs. CONTROL, respectively, in 4 weeks (30.3 ± 4.6 vs. 34.8 ± 4.9 seconds; p < 0.05), 8 weeks (29.2 ± 4.5 vs. 34.6 ± 4.9 seconds; p < 0.05), and 12 weeks (27.2 ± 4.0 vs. 35.3 ± 4.6 seconds; p < 0.05). PILATES presented a difference in postprandial glycemia pre- vs. 4 and 12 weeks (246.1 ± 58.5 vs. 219.9 ± 59.9 and 207.6 ± 49.1 mg·dl, respectively; p < 0.05), as well as in HbA1c pre- vs. 12 weeks (7.8 ± 1.0 vs. 6.7 ± 0.6%, respectively; p < 0.05). Differences in postprandial glycemia (p < 0.05) were found in PILATES before vs. after sessions, respectively, of 1st-12th (217.1 ± 49.1 vs. 157.9 ± 55.7 mg·dl), 13th-24th (204.5 ± 44.7 vs. 146.3 ± 44.5 mg·dl), and 25th-36th (214.3 ± 40.4 vs. 152.7 ± 52.0 mg·dl). A correlation between postprandial glycemia and GIFC after 12 weeks was detected (r = 0.37; p = 0.04). It is concluded that 12 weeks of the Pilates method induces improvement and relationship in the FC and glycemic control in older women with T2D.

摘要

: Melo 、 KCB 、 ara ú jo 、 FdS 、 Cordeiro j ú nior 、 CCM 、 de Andrade 、 KTP 和 Moreira,SR。普拉提方法训练: 老年女性 2 型糖尿病患者的功能和血糖反应。J Strength Cond Res XX (X): 000-000,2020-本研究的目的是调查 12 周普拉提法对功能能力 (FC) 的影响老年女性 2 型糖尿病 (T2D) 患者的血糖控制。22 例 T2D 妇女随机分为对照组 (对照组: 67.5 ± 6.3 岁; 154.7 ± 6.1厘米; 73.5 ± 6.1千克) 和普拉提 (普拉提: 65.5 ± 5.5 岁; 155.0 ± 4.5厘米; 66.2 ± 5.4千克) 组,在 12 周内以每周 3 次的频率举行 60 分钟的会议。在普拉提治疗前后以及普拉提和控制干预的前、休息、 4 、 8 和 12 周时测量血糖。评估干预前和干预 12 周后的糖化血红蛋白 (HbA1c) 水平。通过一系列老年 T2D 患者的试验获得 FC (GIFC) 的一般指数。方差分析分别在 4 周内检测到普拉提与对照的 GIFC 差异 (30.3 ± 4.6 vs. 34.8 ± 4.9 秒; p

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发表时间:2020-01-08
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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.

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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.

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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"]

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