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Cardiovascular Diabetology Mar 2022We conducted a systematic review and meta-analysis of the cardiovascular, kidney, and safety outcomes of sodium-glucose cotransporter 2 inhibitors (SGLT2i) among... (Meta-Analysis)
Meta-Analysis
BACKGROUND
We conducted a systematic review and meta-analysis of the cardiovascular, kidney, and safety outcomes of sodium-glucose cotransporter 2 inhibitors (SGLT2i) among patients with diabetic kidney disease (DKD).
METHODS
We searched electronic databases for major randomized placebo-controlled clinical trials published up to September 30, 2021 and reporting on cardiovascular and kidney outcomes of SGLT2i in patients with DKD. DKD was defined as chronic kidney disease in individuals with type 2 diabetes. Random-effects meta-analysis models were used to estimate pooled hazard ratios (HR) and 95% confidence intervals (CI) for clinical outcomes including major adverse cardiovascular events (MACE: myocardial infarction [MI], stroke, and cardiovascular death), kidney composite outcomes (a combination of worsening kidney function, end-stage kidney disease, or death from renal or cardiovascular causes), hospitalizations for heart failure (HHF), deaths and safety events (mycotic infections, diabetic ketoacidosis [DKA], volume depletion, amputations, fractures, urinary tract infections [UTI], acute kidney injury [AKI], and hyperkalemia).
RESULTS
A total of 26,106 participants with DKD from 8 large-scale trials were included (median age: 65.2 years, 29.7-41.8% women, 53.2-93.2% White, median follow-up: 2.5 years). SGLT2i were associated with reduced risks of MACE (HR 0.83, 95% CI 0.75-0.93), kidney composite outcomes (HR 0.66, 95% CI 0.58-0.75), HHF (HR 0.62, 95% CI 0.55-0.71), cardiovascular death (HR 0.84, 95% CI 0.74-0.96), MI (HR 0.78, 95% CI 0.67-0.92), stroke (HR 0.76, 95% CI 0.59-0.97), and all-cause death (HR 0.86, 95% CI 0.77-0.96), with no significant heterogeneity detected. Similar results were observed among participants with reduced estimated glomerular filtration rate (eGFR: < 60 mL/min/1.73m). The relative risks (95% CI) for adverse events were 3.89 (1.42-10.62) and 2.50 (1.32-4.72) for mycotic infections in men and women respectively, 3.54 (0.82-15.39) for DKA, and 1.29 (1.13-1.48) for volume depletion.
CONCLUSIONS
Among adults with DKD, SGLT2i were associated with reduced risks of MACE, kidney outcomes, HHF, and death. With a few exceptions of more clear safety signals, we found overall limited data on the associations between SGLT2i and safety outcomes. More research is needed on the safety profile of SGLT2i in this population.
Topics: Adult; Aged; Cardiovascular Diseases; Diabetes Mellitus, Type 2; Diabetic Ketoacidosis; Diabetic Nephropathies; Female; Heart Failure; Humans; Kidney; Male; Myocardial Infarction; Sodium-Glucose Transporter 2 Inhibitors; Stroke
PubMed: 35321742
DOI: 10.1186/s12933-022-01476-x -
JACC. Cardiovascular Imaging May 2022This systematic review and meta-analysis investigated the association of diabetes and glycemic control with myocardial fibrosis (MF). (Meta-Analysis)
Meta-Analysis
OBJECTIVES
This systematic review and meta-analysis investigated the association of diabetes and glycemic control with myocardial fibrosis (MF).
BACKGROUND
MF is associated with an increased risk of heart failure, coronary artery disease, arrhythmias, and death. Diabetes may influence the development of MF, but evidence is inconsistent.
METHODS
The authors searched EMBASE, Medline Ovid, Cochrane CENTRAL, Web of Science, and Google Scholar for observational and interventional studies investigating the association of diabetes, glycemic control, and antidiabetic medication with MF assessed by histology and cardiac magnetic resonance (ie, extracellular volume fraction [ECV%] and T time).
RESULTS
A total of 32 studies (88% exclusively on type 2 diabetes) involving 5,053 participants were included in the systematic review. Meta-analyses showed that diabetes was associated with a higher degree of MF assessed by histological collagen volume fraction (n = 6 studies; mean difference: 5.80; 95% CI: 2.00-9.59) and ECV% (13 studies; mean difference: 2.09; 95% CI: 0.92-3.27), but not by native or postcontrast T time. Higher glycosylated hemoglobin levels were associated with higher degrees of MF.
CONCLUSIONS
Diabetes is associated with higher degree of MF assessed by histology and ECV% but not by T time. In patients with diabetes, worse glycemic control was associated with higher MF degrees. These findings mostly apply to type 2 diabetes and warrant further investigation into whether these associations are causal and which medications could attenuate MF in patients with diabetes.
Topics: Cardiomyopathies; Diabetes Mellitus, Type 2; Fibrosis; Humans; Magnetic Resonance Imaging, Cine; Myocardium; Predictive Value of Tests
PubMed: 35512952
DOI: 10.1016/j.jcmg.2021.12.008 -
Diabetes Research and Clinical Practice Jan 2016Diabetes mellitus (DM) may be a risk factor for venous thromboembolism (VTE) but results are inconsistent. (Meta-Analysis)
Meta-Analysis Review
UNLABELLED
Diabetes mellitus (DM) may be a risk factor for venous thromboembolism (VTE) but results are inconsistent.
AIM
We conducted a systematic review and meta-analysis of epidemiologic studies to quantify the association between DM and VTE.
METHODS AND RESULTS
We included studies identified in PubMed, Web of Science, and CINAHL through 07/31/2014. We identified 19 studies that met our selection criteria. We pooled RRs using a random-effects model: the pooled RR for the association of DM with VTE was 1.10 (95% CI: 0.94-1.29). Between-study heterogeneity was explored with a forest plot, funnel plot, meta-regression, and a stratified analysis. Between-study heterogeneity was observed and not explained by study design, method of DM assessment, or degree of adjustment for confounding. Sensitivity analyses omitted one study at a time to assess the influence of any single study on the pooled estimate. These analyses indicated that one large study was highly influential; when this study was excluded, the pooled estimate increased and just reached statistical significance: 1.16 (95% CI: 1.01-1.34).
CONCLUSIONS
This meta-analysis suggests either no association or a modest positive one between DM and VTE in the general population. DM is unlikely to play a major role in VTE development.
Topics: Diabetes Mellitus; Diabetic Angiopathies; Humans; Risk Factors; Venous Thromboembolism
PubMed: 26612139
DOI: 10.1016/j.diabres.2015.10.019 -
International Journal of Molecular... Mar 2023Gestational diabetes mellitus (GDM) is a severe pregnancy complication for both the woman and the child. Women who suffer from GDM have a greater risk of developing Type... (Meta-Analysis)
Meta-Analysis Review
Gestational diabetes mellitus (GDM) is a severe pregnancy complication for both the woman and the child. Women who suffer from GDM have a greater risk of developing Type 2 diabetes mellitus (T2DM) later in life. Identification of any potential biomarkers for the early prediction of gestational diabetes can help prevent the disease in women with a high risk. Studies show microRNA (miRNA) as a potential biomarker for the early discovery of GDM, but there is a lack of clarity as to which miRNAs are consistently altered in GDM. This study aimed to perform a systematic review and meta-analysis to investigate miRNAs associated with GDM by comparing GDM cases with normoglycemic controls. The systematic review was performed according to PRISMA guidelines with searches in PubMed, Web of Science, and ScienceDirect. The primary search resulted in a total of 849 articles, which were screened according to the prior established inclusion and exclusion criteria. Following the screening of articles, the review was based on the inclusion of 35 full-text articles, which were evaluated for risk of bias and estimates of quality, after which data were extracted and relative values for miRNAs were calculated. A meta-analysis was performed for the miRNA species investigated in three or more studies: MiR-29a, miR-330, miR-134, miR-132, miR-16, miR-223, miR-155, miR-122, miR-17, miR-103, miR-125, miR-210, and miR-222. While some miRNAs showed considerable between-study variability, miR-29a, miR-330, miR-134, miR-16, miR-223, and miR-17 showed significant overall upregulation in GDM, while circulating levels of miR-132 and miR-155 were decreased among GDM patients, suggesting further studies of these as biomarkers for early GDM discovery.
Topics: Pregnancy; Child; Humans; Female; Diabetes, Gestational; Circulating MicroRNA; Diabetes Mellitus, Type 2; MicroRNAs; Biomarkers
PubMed: 37047159
DOI: 10.3390/ijms24076186 -
Nutrition, Metabolism, and... Jul 2023Previously, no relationship between milk consumption and the risk of type 2 diabetes has been found in prospective cohorts. However, Mendelian randomization allows...
AIMS
Previously, no relationship between milk consumption and the risk of type 2 diabetes has been found in prospective cohorts. However, Mendelian randomization allows researchers to almost bypass much residual confounding, providing a more precise effect estimate. This systematic review aims to investigate the risk of type 2 diabetes and levels of HbA1c by assessing all Mendelian Randomization studies investigating this subject matter.
DATA SYNTHESIS
PubMed and EMBASE were searched from October 2021 through February 2023. Inclusion and exclusion criteria were formulated to filter out irrelevant studies. Studies were qualitatively assessed with STROBE-MR together with a list of five MR criteria. Six studies were identified, containing several thousand participants. All studies used the SNP rs4988235 as the main exposure and type 2 diabetes and/or HbA1c as the main outcome. Five studies were graded as "good" with STROBE-MR, with one graded as "fair". For the six MR criteria, five studies were graded "good" in four criteria, while two studies were graded "good" in two criteria. Overall, genetically predicted milk consumption did not seem to be associated with an increased risk of type 2 diabetes.
CONCLUSIONS
This systematic review found that genetically predicted milk consumption did not seem to increase the risk of type 2 diabetes. Future Mendelian randomization studies concerning this topic should consider conducting two-sample Mendelian Randomization studies, in order to derive a more valid effect estimate.
Topics: Humans; Animals; Milk; Diabetes Mellitus, Type 2; Glycated Hemoglobin; Mendelian Randomization Analysis; Prospective Studies; Polymorphism, Single Nucleotide; Genome-Wide Association Study
PubMed: 37246077
DOI: 10.1016/j.numecd.2023.04.013 -
Biomedical Papers of the Medical... Sep 2017Cardiovascular (CV) disease is the primary cause of death in diabetic patients and one of the explanations may be increased arterial stiffness. Arterial stiffness... (Review)
Review
Cardiovascular (CV) disease is the primary cause of death in diabetic patients and one of the explanations may be increased arterial stiffness. Arterial stiffness assessment using pulse wave analysis, is a predictive factor of CV events. The aim of this paper is to review the current knowledge of relations between diabetes mellitus and pulse wave analysis. A MEDLINE search was performed to retrieve both original and review articles addressing the relations and influences on arterial stiffness in diabetics. Pulse wave analysis is considered as a gold standard in CV risk evaluation for patients at risk, especially diabetics. Arterial stiffness assessment may be helpful for choosing more aggressive diagnostic and therapeutic strategies, particularly in younger patients to reduce the incidence of CV disease in these patients.
Topics: Diabetes Mellitus, Type 2; Diabetic Angiopathies; Humans; Predictive Value of Tests; Pulsatile Flow; Pulse Wave Analysis; Risk Factors; Vascular Stiffness
PubMed: 28627523
DOI: 10.5507/bp.2017.028 -
Frontiers in Endocrinology 2022Diabetes mellitus (DM) and its related complications are among the leading causes of disability and mortality worldwide. Substantial studies have explored epigenetic...
Diabetes mellitus (DM) and its related complications are among the leading causes of disability and mortality worldwide. Substantial studies have explored epigenetic regulation that is involved in the modifications of DNA and proteins, but RNA modifications in diabetes are still poorly investigated. In recent years, posttranscriptional epigenetic modification of RNA (the so-called 'epitranscriptome') has emerged as an interesting field of research. Numerous modifications, mainly -methyladenosine (mA), have been identified in nearly all types of RNAs and have been demonstrated to have an indispensable effect in a variety of human diseases, such as cancer, obesity, and diabetes. Therefore, it is particularly important to understand the molecular basis of RNA modifications, which might provide a new perspective for the pathogenesis of diabetes mellitus and the discovery of new therapeutic targets. In this review, we aim to summarize the recent progress in the epitranscriptomics involved in diabetes and diabetes-related complications. We hope to provide some insights for enriching the understanding of the epitranscriptomic regulatory mechanisms of this disease as well as the development of novel therapeutic targets for future clinical benefit.
Topics: Diabetes Mellitus; Epigenesis, Genetic; Humans; RNA
PubMed: 35692393
DOI: 10.3389/fendo.2022.907060 -
Sensors (Basel, Switzerland) Jun 2022(1) Background: Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated levels of blood glucose. Recently, some studies approached the diabetes... (Review)
Review
(1) Background: Diabetes mellitus (DM) is a chronic, metabolic disease characterized by elevated levels of blood glucose. Recently, some studies approached the diabetes care domain through the analysis of the modifications of cardiovascular system parameters. In fact, cardiovascular diseases are the first leading cause of death in diabetic subjects. Thanks to their cost effectiveness and their ease of use, electrocardiographic (ECG) and photoplethysmographic (PPG) signals have recently been used in diabetes detection, blood glucose estimation and diabetes-related complication detection. This review's aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (2) Method: We performed a systematic review based on articles that focus on the use of ECG and PPG signals in diabetes care. The search was focused on keywords related to the topic, such as "Diabetes", "ECG", "PPG", "Machine Learning", etc. This was performed using databases, such as PubMed, Google Scholar, Semantic Scholar and IEEE Xplore. This review's aim is to provide a detailed overview of all the published methods, from the traditional (non machine learning) to the deep learning approaches, to detect and manage diabetes using PPG and ECG signals. This review will allow researchers to compare and understand the differences, in terms of results, amount of data and complexity that each type of approach provides and requires. (3) Results: A total of 78 studies were included. The majority of the selected studies focused on blood glucose estimation (41) and diabetes detection (31). Only 7 studies focused on diabetes complications detection. We present these studies by approach: traditional, machine learning and deep learning approaches. (4) Conclusions: ECG and PPG analysis in diabetes care showed to be very promising. Clinical validation and data processing standardization need to be improved in order to employ these techniques in a clinical environment.
Topics: Algorithms; Blood Glucose; Diabetes Mellitus; Electrocardiography; Humans; Photoplethysmography
PubMed: 35808386
DOI: 10.3390/s22134890 -
Frontiers in Endocrinology 2023After the acute phase of SARS-CoV-2 infection, the onset of glycemic impairment and diabetes have been reported. Nevertheless, the exact burden of glycemic impairment... (Meta-Analysis)
Meta-Analysis
AIMS
After the acute phase of SARS-CoV-2 infection, the onset of glycemic impairment and diabetes have been reported. Nevertheless, the exact burden of glycemic impairment and diabetes after COVID-19 has not been clearly described.
MATERIALS AND METHODS
Electronic search was run in Pubmed (MEDLINE), Web of Science, Scopus, and ClinicalTrial.org for reports published from database inception to September 2022. We included observational studies reporting quantitative data on diabetes prevalence or its onset in subjects with a history of SARS-CoV-2 infection from at least 60 days. Risk of bias was assessed by the JBI's critical appraisal checklist. Random effect model was used to calculate pooled data. The review protocol was registered on PROSPERO (CRD42022310722).
RESULTS
Among 1,630 records screened, 20 studies were included in the analysis. The mean or median age of participants ranged from ~ 35 to 64 years, with a percentage of males ranging from 28% to 80%. Only two studies were considered at low risk of bias. The estimate of diabetes prevalence, calculated on a total of 320,948 participants pooled with 38,731 cases, was 16% (95%CI: 11-22%). The estimate of proportion of incident cases of diabetes was 1.6% (95%CI: 0.8-2.7%). Subgroup analysis showed that previous hospitalization increased the prevalence of diabetes and the proportion of incident cases.
CONCLUSION
Diabetes is common in individuals who have experienced SARS-CoV-2 infection, especially if they required hospitalization. This data may be helpful to screen for diabetes and manage its complications in individuals who experienced COVID-19.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022310722, identifier CRD42022310722.
Topics: Male; Humans; Adult; Middle Aged; COVID-19; Prevalence; SARS-CoV-2; Diabetes Mellitus; Databases, Factual
PubMed: 37732118
DOI: 10.3389/fendo.2023.1215879 -
Biomolecules Jun 2021Amyotrophic Lateral Sclerosis (ALS) is a degenerative disorder which affects the motor neurons. Growing evidence suggests that ALS may impact the metabolic system,...
BACKGROUND
Amyotrophic Lateral Sclerosis (ALS) is a degenerative disorder which affects the motor neurons. Growing evidence suggests that ALS may impact the metabolic system, including the glucose metabolism. Several studies investigated the role of Diabetes Mellitus (DM) as risk and/or prognostic factor. However, a clear correlation between DM and ALS has not been defined. In this review, we focus on the role of DM in ALS, examining the different hypotheses on how perturbations of glucose metabolism may interact with the pathophysiology and the course of ALS.
METHODS
We undertook an independent PubMed literature search, using the following search terms: ((ALS) OR (Amyotrophic Lateral Sclerosis) OR (Motor Neuron Disease)) AND ((Diabetes) OR (Glucose Intolerance) OR (Hyperglycemia)). Review and original articles were considered.
RESULTS
DM appears not to affect ALS severity, progression, and survival. Contrasting data suggested a protective role of DM on the occurrence of ALS in elderly and an opposite effect in younger subjects.
CONCLUSIONS
The actual clinical and pathophysiological correlation between DM and ALS is unclear. Large longitudinal prospective studies are needed. Achieving large sample sizes comparable to those of common complex diseases like DM is a challenge for a rare disease like ALS. Collaborative efforts could overcome this specific issue.
Topics: Age Factors; Amyotrophic Lateral Sclerosis; Diabetes Mellitus; Glucose; Humans
PubMed: 34200812
DOI: 10.3390/biom11060867