Artificial intelligence in diabetes management: Advancements, opportunities, and challenges

Cell Reports Medicine, Journal Year: 2023, Volume and Issue: 4(10), P. 101213 - 101213

Published: Oct. 1, 2023

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes diabetic complications, related substantial economic burden make a significant health challenge worldwide. A shortage specialists, uneven distribution medical resources, low adherence medications, improper self-management contribute poor glycemic control in patients with diabetes. Recent advancements digital technologies, especially artificial intelligence (AI), provide opportunity achieve better efficiency care, which may diminish the increase diabetes-related health-care expenditures. Here, we review recent progress application AI management then discuss opportunities challenges clinical practice. Furthermore, explore possibility combining expanding upon existing technologies develop an AI-assisted ecosystem that includes prevention

Language: Английский

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Optimal Dose and Type of Physical Activity to Improve Glycemic Control in People Diagnosed With Type 2 Diabetes: A Systematic Review and Meta-analysis

Diabetes Care, Journal Year: 2024, Volume and Issue: 47(2), P. 295 - 303

Published: Jan. 19, 2024

BACKGROUND The optimal dose or type of physical activity to control glycosylated hemoglobin (HbA1c) in people with diabetes remains unknown. Current guidelines do not include consideration baseline HbA1c for prescription. PURPOSE To examine the dose-response relationship between and (%) individuals 2 diabetes. DATA SOURCES A systematic search was performed Embase, MEDLINE, Scopus, CINAHL, SPORTDiscus, Web Science. STUDY SELECTION We included trials that involved participants diagnosed any as intervention. EXTRACTION Pre- postintervention data, population interventions characteristics, descriptive statistics were collected calculate change scores each study arm. SYNTHESIS used Bayesian random-effects meta-analyses summarize high-quality evidence from 126 studies (6,718 participants). 1,100 MET min/week, resulting reductions, ranging −1.02% −0.66% severe uncontrolled diabetes, −0.64% −0.49% −0.47% −0.40% controlled −0.38% −0.24% prediabetes. LIMITATIONS time required achieve these reductions could be estimated due heterogeneity interventions’ duration protocols interpersonal variability this outcome. CONCLUSIONS result meta-analysis provide key information about weekly level, effectiveness different types active interventions. These results enable clinicians prescribe tailored programs population.

Language: Английский

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Consensus Guidance for Monitoring Individuals With Islet Autoantibody–Positive Pre-Stage 3 Type 1 Diabetes

Diabetes Care, Journal Year: 2024, Volume and Issue: unknown

Published: June 24, 2024

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at time stage 3 type 1 diabetes diagnosis, and emerging availability therapy delay disease progression, programs are being increasingly emphasized. Once broadly implemented, initiatives will identify significant numbers islet autoantibody-positive (IAb+) children adults who risk for (confirmed single IAb+) or living with (multiple early-stage (stage 2) diabetes. These individuals need monitoring progression; much this care happen in nonspecialized settings. To inform monitoring, JDRF, conjunction international experts societies, developed consensus guidance. Broad advice from guidance includes following: 1) partnerships should be fostered between endocrinologists primary providers people IAb+; when IAb+ initially identified, there is a confirmation using second sample; 3) lower progression than multiple individuals; 4) have periodic medical including regular assessments glucose levels, education about symptoms DKA, psychosocial support; 5) interested 2 offered trial participation approved therapies; 6) all health professionals involved responsibility provide education. The also emphasizes unmet needs further research on increase rigor future recommendations clinical care.

Language: Английский

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Sedentary lifestyle, physical activity, and gastrointestinal diseases: evidence from mendelian randomization analysis

EBioMedicine, Journal Year: 2024, Volume and Issue: 103, P. 105110 - 105110

Published: April 6, 2024

BackgroundThe causal associations of physical activity and sedentary behavior with the risk gastrointestinal disease are unclear. We performed a Mendelian randomization analysis to examine these associations.MethodsGenetic instruments associated leisure screen time (LST, an indicator lifestyle) moderate-to-vigorous intensity (MVPA) at genome-wide significance (P < 5 × 10−8) level were selected from association study. Summary statistics for diseases obtained UK Biobank study, FinnGen large consortia. Multivariable MR analyses conducted genetically determined LST adjustment MVPA vice versa. also multivariable proxied smoking, body mass index (BMI), waist-to-hip ratio, type 2 diabetes, fasting insulin both exposures.FindingsGenetically longer was increased reflux, gastric ulcer, duodenal chronic gastritis, irritable bowel syndrome, diverticular disease, Crohn's ulcerative colitis, non-alcoholic fatty liver alcoholic cholangitis, cholecystitis, cholelithiasis, acute pancreatitis, appendicitis. Most remained after genetic liability MVPA. Genetic decreased gastroesophageal pancreatitis. The attenuated albeit directionally adjusting predicted LST. found that BMI diabetes mediated several diseases.InterpretationThe study suggests lifestyle may play role in development many diseases.FundingNatural Science Fund Distinguished Young Scholars Zhejiang Province (LR22H260001), Natural Foundation Hunan (2021JJ30999), Swedish Heart-Lung (Hjärt-Lungfonden, 20210351), Research Council (Vetenskapsrådet, 2019-00977), Cancer Society (Cancerfonden), Wellcome Trust (225790/7/22/Z), United Kingdom Innovation Medical (MC_UU_00002/7) National Institute Health Cambridge Biomedical Centre (NHIR203312).

Language: Английский

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Is ChatGPT an Effective Tool for Providing Dietary Advice?

Nutrients, Journal Year: 2024, Volume and Issue: 16(4), P. 469 - 469

Published: Feb. 6, 2024

The chatbot Chat Generative Pretrained Transformer (ChatGPT) is becoming increasingly popular among patients for searching health-related information. Prior studies have raised concerns regarding accuracy in offering nutritional advice. We investigated November 2023 ChatGPT's potential as a tool providing guidance relation to different non-communicable diseases (NCDs). First, the dietary advice given by ChatGPT (version 3.5) various NCDs was compared with guidelines; then, chatbot's capacity manage complex case several investigated. A panel of nutrition experts assessed responses. Overall, offered clear advice, appropriateness responses ranging from 55.5% (sarcopenia) 73.3% (NAFLD). Only two recommendations (one obesity, one non-alcoholic-fatty-liver disease) contradicted guidelines. single suggestion T2DM found be "unsupported", while many were deemed "not fully matched" guidelines despite not directly contradicting them. However, when handled overlapping conditions, limitations emerged, resulting some contradictory or inappropriate In conclusion, although exhibited reasonable general NCDs, its efficacy decreased situations necessitating customized strategies; therefore, currently unable replace healthcare professional's consultation.

Language: Английский

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Association of Visceral Obesity Indices With Incident Diabetic Retinopathy in Patients With Diabetes: Prospective Cohort Study

JMIR Public Health and Surveillance, Journal Year: 2024, Volume and Issue: 10, P. e48120 - e48120

Published: Feb. 6, 2024

Background Visceral adipose tissue plays an active role in the pathogenesis of type 2 diabetes and vascular dysfunction. The lipid accumulation product (LAP), visceral adiposity index (VAI), Chinese VAI (CVAI) have been proposed as simple validated surrogate indices for measuring tissue. However, evidence from prospective studies on associations between these novel obesity diabetic retinopathy (DR) remains scant. Objective This study aimed to investigate longitudinal LAP, VAI, CVAI with incident DR patients diabetes. Methods was a cohort conducted Guangzhou southern China. We collected baseline data November 2017 July 2020, while on-site follow-up visits were annually until January 2022. participants consisted 1403 clinical diagnosis diabetes, referred primary care, who free at baseline. levels calculated by sex-specific equations based anthropometric biochemical parameters. assessed using 7-field color stereoscopic fundus photographs graded according modified Airlie House Classification scheme. Time-dependent Cox proportional hazard models constructed estimate ratios 95% CIs. Restricted cubic spline curves fitted examine dose-response relationship 3 new-onset DR. Subgroup analyses performed potential effect modifiers. Results mean age 64.5 (SD 7.6) years, over half (816/1403, 58.2%) female. During median 2.13 406 events observed. A 1-SD increment or consistently associated increased risk DR, multivariable‑adjusted ratio 1.24 (95% CI 1.09-1.41; P=.001), 1.22 1.09-1.36; P<.001), 1.48 1.19-1.85; respectively. Similar patterns observed across tertiles LAP (P trend=.001), trend<.001), trend=.009). Patients highest tertile had 84%, 86%, 82% higher respectively, compared those lowest tertile. nonlinear noted (both P nonlinearity<.05), but not nonlinearity=.51). did detect presence modification age, sex, duration BMI, comorbidity (all interaction>.10). Conclusions obesity, measured CVAI, is independently Our findings may suggest necessity incorporating regular monitoring into routine practice enhance population-based prevention

Language: Английский

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Social Psychology and Health

Published: Jan. 1, 2025

Language: Английский

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Food Insecurity and Diabetes: Overview of Intersections and Potential Dual Solutions

Diabetes Care, Journal Year: 2023, Volume and Issue: 46(9), P. 1599 - 1608

Published: June 24, 2023

Food insecurity increases the risk of developing diabetes and its complications. In this article, we describe complex relationship that exists between food potential mechanisms may underlie association. We then how two different types interventions, food-is-medicine federal nutrition assistance programs, help address both health. Finally, outline research, policy, practice opportunities exist to reduce diabetes-related health disparities.

Language: Английский

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Advances in the management of type 2 diabetes in adults

BMJ Medicine, Journal Year: 2023, Volume and Issue: 2(1), P. e000372 - e000372

Published: Sept. 1, 2023

Type 2 diabetes is a chronic and progressive cardiometabolic disorder that affects more than 10% of adults worldwide major cause morbidity, mortality, disability, high costs. Over the past decade, pattern management has shifted from predominantly glucose centric approach, focused on lowering levels haemoglobin A

Language: Английский

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Achievement of Guideline-Recommended Targets in Diabetes Care in China

Annals of Internal Medicine, Journal Year: 2023, Volume and Issue: 176(8), P. 1037 - 1046

Published: July 31, 2023

Background: Nationwide achievement of guideline-recommended diabetes care targets has not been comprehensively assessed in China. Objective: To estimate the proportions adults with achieving major clinical risk factor control, body mass index (BMI), lifestyle, and dietary specified Chinese guidelines. Design: cross-sectional survey. Setting: China, 2015 to 2017. Participants: A national sample 8401 self-reported a subset 3531 data. Measurements: The included 1) ABC (individualized hemoglobin A1c [HbA1c] target; blood pressure [BP] <130/80 mm Hg; low-density lipoprotein cholesterol [LDL-C] level <2.6 or <1.8 mmol/L [<100 <70 mg/dL], depending on presence atherosclerotic cardiovascular disease), 2) BMI below 24 kg/m2, 3) lifestyle (not currently smoking drinking, leisure time activity level, sleep duration 7 8 hours), 4) (50% 65% energy from carbohydrate, 15% 20% protein, 30% fat, ≥14 g fiber per 1000 kcal, <2000 mg sodium day). Results: proportion each target was 64.1% (95% CI, 61.4% 66.8%) for HbA1c, 22.2% (CI, 20.2% 24.1%) BP, 23.9% 21.9% 25.9%) LDL-C. kg/m2 32.2% 30.3% 34.2%). 75.8% 73.9% 77.7%) smoking, 66.7% 64.4% 69.1%) 17.9% 15.8% 20.1%) activity, 52.0% 49.6% 54.3%) duration. 39.1% 36.0% 42.2%) 20.1% 16.9% 23.3%) 20.5% 17.6% 23.4%) 9.0% 7.0% 10.9%) sodium, 2.5% 1.3% 3.6%) fiber. Only 4.4% 3.5% 5.2%) participants achieved all 3 targets, 5.1% 4.3% 6.0%) 4 5 targets. Limitations: Self-reported data age Conclusion: Achievement exceedingly low. findings highlight need immediate health actions improve care. Primary Funding Source: Shanghai Municipal Education Commission, National Key R&D Program People's Republic Health Commission

Language: Английский

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