The gut microbiota‐astrocyte axis: Implications for type 2 diabetic cognitive dysfunction DOI Creative Commons
Zi-han Li, Yayi Jiang,

Caiyi Long

et al.

CNS Neuroscience & Therapeutics, Journal Year: 2023, Volume and Issue: 29(S1), P. 59 - 73

Published: Jan. 4, 2023

Abstract Background Diabetic cognitive dysfunction (DCD) is one of the most insidious complications type 2 diabetes mellitus, which can seriously affect ability to self‐monitoring blood glucose and quality life in elderly. Previous pathological studies have focused on neuronal dysfunction, characterized by extracellular beta‐amyloid deposition intracellular tau hyperphosphorylation. In recent years, astrocytes been recognized as a potential therapeutic target for important participants central control metabolism. The disorder gut microbiota their metabolites linked series metabolic diseases such mellitus. imbalance intestinal flora has effect promoting occurrence deterioration several diabetes‐related complications. Gut microbes drive astrocyte activation. Aims We reviewed progress DCD related “gut microbiota‐astrocyte” axis terms peripheral inflammation, blood–brain barrier (BBB) systemic brain energy metabolism disorders deepen research explore targets. Conclusion “Gut axis, unique bidirectional crosstalk brain‐gut mediates intermediate process neurocognitive secondary

Language: Английский

2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease: A Report of the American Heart Association/American College of Cardiology Joint Committee on Clinical Practice Guidelines DOI Creative Commons
Salim S. Virani, L. Kristin Newby, Suzanne V. Arnold

et al.

Circulation, Journal Year: 2023, Volume and Issue: 148(9)

Published: July 20, 2023

AIM: The “2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease” provides an update to and consolidates new evidence since “2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Diagnosis Stable Ischemic Heart corresponding “2014 ACC/AHA/AATS/PCNA/SCAI/STS Focused Update Disease.” METHODS: A comprehensive literature search was conducted from September 2021 May 2022. Clinical studies, systematic reviews meta-analyses, other on human participants were identified that published in English MEDLINE (through PubMed), EMBASE, Cochrane Library, Agency Healthcare Research Quality, selected databases relevant this guideline. STRUCTURE: This guideline evidenced-based patient-centered approach management patients with chronic coronary disease, considering social determinants health incorporating principles shared decision-making team-based care. Relevant topics include general approaches treatment decisions, guideline-directed therapy reduce symptoms future cardiovascular events, pertaining revascularization recommendations special populations, patient follow-up monitoring, gaps, areas need research. Where applicable, based availability cost-effectiveness data, cost–value are also provided clinicians. Many previously guidelines have been updated evidence, created when supported by data.

Language: Английский

Citations

587
Type 2 diabetes mellitus in older adults: clinical considerations and management DOI
Srikanth Bellary, Ioannis Kyrou, James E. Brown

et al.

Nature Reviews Endocrinology, Journal Year: 2021, Volume and Issue: 17(9), P. 534 - 548

Published: June 25, 2021

Language: Английский

Citations

387
Type 2 diabetes and cognitive dysfunction—towards effective management of both comorbidities DOI
Velandai Srikanth, Alan J. Sinclair, Felicia Hill‐Briggs

et al.

The Lancet Diabetes & Endocrinology, Journal Year: 2020, Volume and Issue: 8(6), P. 535 - 545

Published: May 21, 2020

Language: Английский

Citations

313
2023 AHA/ACC/ACCP/ASPC/NLA/PCNA Guideline for the Management of Patients With Chronic Coronary Disease DOI Creative Commons
Salim S. Virani, L. Kristin Newby, Suzanne V. Arnold

et al.

Journal of the American College of Cardiology, Journal Year: 2023, Volume and Issue: 82(9), P. 833 - 955

Published: July 20, 2023

Language: Английский

Citations

217
Cognitive dysfunction in diabetes: how to implement emerging guidelines DOI Creative Commons
Geert Jan Biessels, Rachel A. Whitmer

Diabetologia, Journal Year: 2019, Volume and Issue: 63(1), P. 3 - 9

Published: Aug. 16, 2019

Cognitive dysfunction, including mild cognitive impairment and dementia, is increasingly recognised as an important comorbidity complication of diabetes that affects individual’s well-being management, associated with treatment-related complications. Recent guidelines therefore recommend screening for in older individuals diabetes. In addition, these suggest glucose-lowering treatment should be tailored those diagnosed impairment, to reduce the risk hypoglycaemia improve adherence. This review gives overview dysfunction people diabetes, briefly describing clinical features different stages their epidemiology. particular, it addresses essential additional steps need taken fully implement emerging on management into daily practice.

Language: Английский

Citations

207
Understanding multifactorial brain changes in type 2 diabetes: a biomarker perspective DOI
Geert Jan Biessels, Flavio Nobili, Charlotte E. Teunissen

et al.

The Lancet Neurology, Journal Year: 2020, Volume and Issue: 19(8), P. 699 - 710

Published: May 21, 2020

Language: Английский

Citations

142
Diabetes and Frailty: An Expert Consensus Statement on the Management of Older Adults with Type 2 Diabetes DOI Creative Commons
W. David Strain,

Su Down,

Pam Brown

et al.

Diabetes Therapy, Journal Year: 2021, Volume and Issue: 12(5), P. 1227 - 1247

Published: April 8, 2021

Prognosis and appropriate treatment goals for older adults with diabetes vary greatly according to frailty. It is now recognised that changes may be needed management in some people. Whilst there clear guidance on the evaluation of frailty subsequent target setting people living frailty, remains a lack formal healthcare professionals how achieve these targets. The type 2 complicated by comorbidities, shortened life expectancy exaggerated consequences adverse effects from treatment. In particular, are more prone hypoglycaemia vulnerable its consequences, including falls, fractures, hospitalisation, cardiovascular events all-cause mortality. Thus, assessment should routine component review all adults, glycaemic targets therapeutic choices modified accordingly. Evidence suggests over-treatment common, many having had their regimens intensified over preceding years when they were better health, or during recent acute hospital admissions blood glucose levels might have been atypically high, nutritional intake vary. addition, assistance taking medications, as often occurs later following implementation community care strategies admittance home, dramatically improve adherence, leading fall glycated haemoglobin (HbA1c) levels. As person gets older, simplification, switching de-escalation regimen necessary, depending level HbA1c Consideration given, therapies induce hypoglycaemia, such sulphonylureas shorter-acting insulins. We discuss use available glucose-lowering recommend simple algorithms

Language: Английский

Citations

129
Risk of Progression to Diabetes Among Older Adults With Prediabetes DOI Open Access
Mary R. Rooney, Andreea M. Rawlings, James S. Pankow

et al.

JAMA Internal Medicine, Journal Year: 2021, Volume and Issue: 181(4), P. 511 - 511

Published: Feb. 9, 2021

Importance

The termprediabetesis used to identify individuals at increased risk for diabetes. However, the natural history of prediabetes in older age is not well characterized.

Objectives

To compare different definitions and characterize risks diabetes among adults a community-based setting.

Design, Setting, Participants

In this prospective cohort analysis 3412 without from Atherosclerosis Risk Communities Study (baseline, 2011-2013), participants were contacted semiannually through December 31, 2017, attended follow-up visit between January 1, 2016, 2017 (median [range] follow-up, 5.0 [0.1-6.5] years).

Exposures

Prediabetes defined by glycated hemoglobin (HbA1c) level 5.7% 6.4%, impaired fasting glucose (IFG) (FG 100-125 mg/dL), either, or both.

Main Outcomes Measures

Incident total (physician diagnosis, glucose-lowering medication use, HbA1clevel ≥6.5%, FG ≥126 mg/dL).

Results

A (mean [SD] age, 75.6 [5.2] years; 2040 [60%] female; 572 [17%] Black) 5 (2011-2013, baseline). Of baseline, 2497 died. During 6.5-year period, there 156 incident cases (118 diagnosed) 434 deaths. 1490 (44%) had HbA1clevels 1996 (59%) IFG, 2482 (73%) met HbA1cor IFG criteria, 1004 (29%) both HbA1cand criteria. Among with 6.4% 97 (9%) progressed diabetes, 148 (13%) regressed normoglycemia (HbA1c, <5.7%), 207 (19%) those 112 (8%) 647 (FG, <100 236 (16%) baseline less than 5.7%, 239 (17%) 41 (3%) developed levels 100 mg/dL, 80 mg/dL) 26

Conclusions Relevance

study adults, prevalence was high; however, during regression death more frequent progression These findings suggest that may be robust diagnostic entity age.

Language: Английский

Citations

128
Efficient Automated Disease Diagnosis Using Machine Learning Models DOI Open Access
Naresh Kumar, Nripendra Narayan Das, Deepali Gupta

et al.

Journal of Healthcare Engineering, Journal Year: 2021, Volume and Issue: 2021, P. 1 - 13

Published: May 4, 2021

Recently, many researchers have designed various automated diagnosis models using supervised learning models. An early of disease may control the death rate due to these diseases. In this paper, an efficient model is machine we selected three critical diseases such as coronavirus, heart disease, and diabetes. proposed model, data are entered into android app, analysis then performed in a real-time database pretrained which was trained on same dataset deployed firebase, finally, detection result shown app. Logistic regression used carry out computation for prediction. Early can help identifying risk Comparative indicates that doctors give timely medications treatment.

Language: Английский

Citations

123
Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis DOI Creative Commons
Amin Mansoori, Toktam Sahranavard, Zeinab Hosseini

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Jan. 12, 2023

Abstract Type 2 Diabetes Mellitus (T2DM) is a significant public health problem globally. The diagnosis and management of diabetes are critical to reduce the complications including cardiovascular disease cancer. This study was designed assess potential association between T2DM routinely measured hematological parameters. subsample 9000 adults aged 35–65 years recruited as part Mashhad stroke heart atherosclerotic disorder (MASHAD) cohort study. Machine learning techniques logistic regression (LR), decision tree (DT) bootstrap forest (BF) algorithms were applied analyze data. All data analyses performed using SPSS version 22 SAS JMP Pro 13 at level 0.05. Based on performance indices, BF model gave high accuracy, precision, specificity, AUC. Previous studies suggested positive relationship triglyceride-glucose (TyG) index with T2DM, so we considered TyG factors. We found this aligned their results regarding except MCHC. most effective factors in age WBC (white blood cell). represented better predict T2DM. Our provides valuable information like WBC.

Language: Английский

Citations

55