Diabetes research and clinical practice最新文献

To analyze the ecological relationship between COVID-19 incidence in the total population and type 1 diabetes (T1D) incidence in children and adolescents, spatiotemporal models were applied considering time lags from 0 to 12 months. The results do not indicate a positive correlation between COVID-19 incidence and T1D incidence.

Aims: We assessed the extent to which using large geographic regions to group ethnicities (ancestries or countries-of-birth) masked intra-regional variation in diabetes risk.

Methods: We performed a cross-sectional analysis of the 2021 Australian National Census, which included self-reported health data. Ethnicity-specific diabetes prevalence was age/sex-standardised to a reference population of all census respondents 20 years and above.

Results: There were 17.5 million adults included in this study. Within four geographical regions, there wastwo-four-fold intra-regional variation in diabetes risk. Diabetes prevalence among people reporting a single East Asianancestry ranged from less than the Australian prevalence (Japanese 4.1%, Thai 6.1%) to twice the Australian prevalence (Filipino 12.2%). Among peoplereporting a single South/Central Asianancestry, diabetes prevalence ranged from 7.1% (Armenian) to 18.9% (Bangladeshi). Among people reporting a single Middle Eastern/North African ancestry, diabetes prevalence values rangedfrom 5.4% (Jewish) to 12.0% (Iraqi). In Oceania, the diabetes prevalence in people of Australian Aboriginal, Fijian, Maori, Samoan and Tongan ancestry was greater than the Australian prevalence(16.7%, 11.9%, 9.9%, 16.0% and 16.6%, respectively versus 6.1%).

Conclusions: There wastwo-four-fold variation in diabetes prevalence between populations within four geographical regions. Aggregating ethnicity into large geographic regional groups may incorrectly estimate diabetes risk.

Aims: To evaluate the effects of SGLT2 inhibitors on cardiovascular outcomes and mortality across KDIGO and urinary albumin-to-creatinine ratio [UACR] groups.

Methods: We searched MEDLINE, EMBASE, and CENTRAL up to August 8th, 2023. In pairs, researchers selected large randomized placebo-controlled trials of SGLT2 inhibitors, with minimum duration of one year. Researchers independently extracted study-level data and assessed within-study risk of bias with RoB 2.0 and certainty of evidence with GRADE. Meta-analyses employed a random-effects model.

Results: We included 14 trials, encompassing 97,412 participants and a median follow-up of 2.5 years. Risk of bias was overall low. Overall, SGLT2 inhibitors reduced major adverse cardiovascular events (MACE) (HR 0.89, 95 %-CI 0.85-0.93), cardiovascular death or hospitalization for heart failure (HHF) (HR 0.78, 95 %-CI 0.75-0.82), all-cause death (HR 0.89, 95 %-CI 0.83-0.94), and HHF (HR 0.71, 95 %-CI 0.67-0.75). The effect of SGLT2 inhibitors on MACE was different across KDIGO (P_interaction = 0.038) and UACR (P_interaction = 0.008) groups, with greater benefits in KDIGO Very High (HR 0.72, 95 %-CI 0.61-0.86) and UACR > 300 mg/g (HR 0.76, 95 %-CI 0.68-0.86) groups.

Conclusions: SGLT2 inhibitors are associated with reductions in cardiovascular outcomes and mortality. Greater reductions in MACE are expected in subjects in high-risk groups for kidney disease.

Aims: The study uses GBD 2021 data to measure the type 2 diabetes mellitus (T2DM) burden linked to particulate matter pollution (PM_2.5) exposure, highlighting environmental factors as rising contributors to the disease.

Methods: We used advanced methods like Joinpoint regression and decomposition analysis to track PM2.5 exposure's effects on T2DM, analyzing its burden by Socio-demographic indices (SDI) to find high-risk areas for targeted interventions.

Results: In 2021, the global burden of T2DM attributable to PM_2.5 exposure reached 12,904,493 DALYs, a substantial increase from 1990. The age-standardized mortality rates (ASMR) and age-standardized death rates (ASDR) showed an upward trend, with males exhibiting a higher disease burden than females. The burden was highest in lower SDI quintiles, with faster growth rates in ASDR and ASMR compared to higher SDI regions. The population attributable fractions (PAFs) for ASDR and ASMR due to PM_2.5 were 17.07 % and 17.47 %, respectively, with higher PAFs in lower SDI regions.

Conclusion: Our results show that air pollution significantly affects global T2DM rates, necessitating policies to lower PM2.5 and boost health system resilience. Ongoing monitoring and research are key to crafting strategies against pollution's health effects.

A recent presidential advisory from the American Heart Association (AHA) has introduced the term cardiovascular-kidney-metabolic (CKM) syndrome to describe the complex interplay among health conditions linking heart, kidney, and metabolism. The aim of our study was to compare the prevalence of concurrent CKM syndrome components before and during the COVID-19 pandemic and identify associated risk factors. We conducted a study utilizing data from a real-world population obtained from a primary care database. The study cohort comprised a closed group followed over a 6-year period (2017-2022). A total of 81,051 individuals were included: 32,650 in the pre-pandemic period and 48,401 in the 2020-2022 triennium. After propensity-score matching for sex, age, and BMI, the study included 30,511 participants for each period. 3554 individuals were diagnosed with type 2 diabetes in the pre-pandemic period, compared to 7430 during the pandemic. Hypertension, dyslipidemia, and obesity displayed significant increases in prevalence during the pandemic, and prediabetes had a particularly sharp rise of 170%. Age-stratified analyses revealed a higher burden of CKM conditions with advancing age. Our findings indicate a substantial increase in the prevalence of CKM syndrome during the COVID-19 pandemic, with nearly half of the patients exhibiting one or more CKM syndrome components.