63 research outputs found

    Comparative effectiveness of dapagliflozin vs DPP-4 inhibitors on a composite endpoint of HbA1c, body weight and blood pressure reduction in the real world

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    Background: Treatment of type 2 diabetes (T2D) should aim at preventing or delaying complications through the control of glycaemia and cardiovascular risk factors. We herein compared the SGLT-2 inhibitor dapagliflozin vs DPP-4 inhibitors (DPP-4i) on a composite endpoint of glycaemic and extraglycaemic effectiveness. Methods: This was a multicentre, retrospective real-world study conducted at 56 outpatient clinics in Italy. We collected data on patients newly started on dapagliflozin or DPP-4i in 2015-2017. The primary endpoint was the proportion of patients attaining a simultaneous reduction of HbA1c ≄0.5%, body weight ≄2 kg, systolic blood pressure (SBP) ≄2 mmHg. Confounding by indication was addressed by propensity score matching (PSM) or multivariable adjustment (MVA). Results: Patients initiating dapagliflozin (n = 2091) or DPP-4i (n = 2144) differed for most clinical characteristics. After PSM, two well-balanced groups of 1149 patients each were compared. The primary endpoint was reached in a greater proportion of patients who received dapagliflozin (17.6%) compared to DPP-4i (11.7%), with a relative risk of 1.50 (1.21-1.86; P <.001). Similar results were obtained in the as-treated and intention-to-treat datasets or using MVA in place of PSM. The beneficial effect of dapagliflozin was mainly due to its greater effectiveness on body weight and, to a lesser extent, on SBP. The change in HbA1c did not differ between groups. Conclusions: T2D patients initiating the SGLT2i dapagliflozin had a greater probability of attaining a composite endpoint of clinically relevant reductions in HbA1c, body weight and SBP, compared to similar patients initiating a DPP-4i in the same period and healthcare setting

    Genetic Variants in \u3cem\u3eHSD17B3\u3c/em\u3e, \u3cem\u3eSMAD3\u3c/em\u3e, and \u3cem\u3eIPO11\u3c/em\u3e Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

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    Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin‐treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed‐up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P \u3c 5 × 10‐6). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q \u3c 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q \u3c 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor‐beta (TGF‐ÎČ) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D

    Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

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    Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 x 10(-6)). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D

    Computerized cognitive training and brain derived neurotrophic factor during bed rest: Mechanisms to protect individual during acute stress

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    Acute stress, as bed rest, was shown to increase plasma level of the neurotrophin brain-derived neurotrophic factor (BDNF) in older, but not in young adults. This increase might represent a protective mechanism towards acute insults in aging subjects. Since computerized cognitive training (CCT) is known to protect brain, herein we evaluated the effect of CCT during bed rest on BDNF, muscle mass, neuromuscular function and metabolic parameters. The subjects that underwent CCT did not show an increase of BDNF after bed rest, and showed an anti-insular modification pattern in metabolism. Neuromuscular function parameters, already shown to beneficiate from CCT, negatively correlated with BDNF in research participants undergoing CCT, while positively correlated in the control group. In conclusion, BDNF increase can be interpreted as a standardized protective mechanism taking place whenever an insult occurs; it gives low, but consistent preservation of neuromuscular function. CCT, acting as an external protective mechanism, seems to modify this standardized response, avoiding BDNF increase or possibly modifying its time course. Our results suggest the possibility of differential neuroprotective mechanisms among ill and healthy individuals, and the importance of timing in determining the effects of protective mechanism

    Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

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    Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 × 10 -6 ). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-ÎČ) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D

    Prevalence of hepatic steatosis in patients with type 2 diabetes and response to glucose-lowering treatments. A multicenter retrospective study in Italian specialist care

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    Type 2 diabetes (T2D) is a risk factor for metabolic dysfunction-associated fatty liver disease (MAFLD), which is becoming the commonest cause of chronic liver disease worldwide. We estimated MAFLD prevalence among patients with T2D using the hepatic steatosis index (HSI) and validated it against liver ultrasound. We also examined whether glucose-lowering medications (GLM) beneficially affected HSI

    Precision gestational diabetes treatment: a systematic review and meta-analyses

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    Genotype-stratified treatment for monogenic insulin resistance: a systematic review

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    Lung cancer presenting with gastrointestinal symptoms: a tricky diagnosis

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    Lung cancer presenting with gastrointestinal symptoms: a tricky diagnosi
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