NAFLD and MAFLD independently increase the risk of major adverse cardiovascular events (MACE): a 20-year longitudinal follow-up study from regional Australia.

BACKGROUND AND AIMS: The association between fatty liver disease (FLD) and cardiovascular disease (CVD) in an Australian context has yet to be defined. The primary aim of this study was to investigate the association between FLD and 3-point major adverse cardiovascular events (MACE). METHODS: This was a longitudinal follow-up study of a randomly sampled adult cohort from regional Australia between 2001 and 2003. Baseline covariates included demographic details, anthropometry, health and lifestyle data, and laboratory tests. Non-alcoholic fatty liver disease (NAFLD) and metabolic-(dysfunction) associated fatty liver disease (MAFLD) were diagnosed in participants with fatty liver index (FLI) ≥ 60 and meeting other standard criteria. ICD-10 codes were used to define clinical outcomes linked to hospitalisations. Three-point MACE defined as non-fatal myocardial infarction (MI) and cerebrovascular accident (CVA) and CVD death. RESULTS: In total, 1324 and 1444 participants met inclusion criteria for NAFLD and MAFLD analysis, respectively. Over 23,577 and 25,469 person-years follow-up, NAFLD and MAFLD were independent predictors for 3-point MACE, adjusting for demographic covariates and known cardiometabolic risk factors, whilst considering non-CVD death as a competing event (NAFLD: sub-hazard ratio [sHR] 1.56, 95% confidence interval [CI 1.12-2.19]; MAFLD: sHR 1.51, 95% CI 1.11-2.06). The results held true on several sensitivity analyses. CONCLUSIONS: Both forms of FLD increase the risk for CVD independent of traditional cardiometabolic risk factors.

Lipidomic Risk Score to Enhance Cardiovascular Risk Stratification for Primary Prevention.

BACKGROUND: Accurate risk stratification is vital for primary prevention of cardiovascular disease (CVD). However, traditional tools such as the Framingham Risk Score (FRS) may underperform within the diverse intermediate-risk group, which includes individuals requiring distinct management strategies. OBJECTIVES: This study aimed to develop a lipidomic-enhanced risk score (LRS), specifically targeting risk prediction and reclassification within the intermediate group, benchmarked against the FRS. METHODS: The LRS was developed via a machine learning workflow using ridge regression on the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab; n = 10,339). It was externally validated with the Busselton Health Study (n = 4,492), and its predictive utility for coronary artery calcium scoring (CACS)-based outcomes was independently validated in the BioHEART cohort (n = 994). RESULTS: LRS significantly improved discrimination metrics for the intermediate-risk group in both AusDiab and Busselton Health Study cohorts (all P < 0.001), increasing the area under the curve for CVD events by 0.114 (95% CI: 0.1123-0.1157) and 0.077 (95% CI: 0.0755-0.0785), with a net reclassification improvement of 0.36 (95% CI: 0.21-0.51) and 0.33 (95% CI: 0.15-0.49), respectively. For CACS-based outcomes in BioHEART, LRS achieved a significant area under the curve improvement of 0.02 over the FRS (0.76 vs 0.74; P < 1.0 × 10-5). A simplified, clinically applicable version of LRS was also created that had comparable performance to the original LRS. CONCLUSIONS: LRS, augmenting the FRS, presents potential to improve intermediate-risk stratification and to predict atherosclerotic markers using a simple blood test, suitable for clinical application. This could facilitate the triage of individuals for noninvasive imaging such as CACS, fostering precision medicine in CVD prevention and management.

Excess Risk of Injury in Individuals With Type 1 or Type 2 Diabetes Compared With the General Population.

OBJECTIVE: To estimate the relative risk (RR) and excess hospitalization rate for injury in individuals with diabetes compared with the general population. RESEARCH DESIGN AND METHODS: Data were obtained from the Australian National Diabetes Services Scheme, hospitalization data sets, the Australian Pharmaceutical Benefits Scheme, the National Death Index, and the census spanning from 2011 to 2017. Hospitalizations for injury were coded as head and neck, lower-extremity, upper-extremity, or abdominal and thoracic injury; burns; or other injury. Poisson regression was used to estimate the age- and sex-adjusted RR of hospitalization for injury. RESULTS: The total number of hospitalizations for any injury was 117,705 in people with diabetes and 3,463,173 in the general population. Compared with that in the general population, an elevated adjusted risk of admission was observed for any injury (RR 1.22; 95% CI 1.21, 1.22), head and neck (1.28; 1.26, 1.30), lower extremity (1.24; 1.23, 1.26), abdominal and thoracic (1.29; 1.27, 1.30), upper extremity (1.03; 1.02, 1.05), burns (1.52; 1.44, 1.61), and other injury (1.37; 1.33, 1.40). The adjusted RR of any injury was 1.62 (1.58, 1.66) in individuals with type 1 diabetes, 1.65 (1.63, 1.66) in those with type 2 diabetes who were taking insulin, and 1.07 (1.06, 1.08) in individuals with type 2 diabetes not using insulin. Falls were the primary cause of injury in individuals with diabetes. CONCLUSIONS: Individuals with diabetes, especially those using insulin, had a higher risk of hospitalization for injury compared with the general population.

The worldwide trend in diabetes awareness, treatment, and control from 1985 to 2022: a systematic review and meta-analysis of 233 population-representative studies.

Background: With the rapid increase in the prevalence of DM, studies on the awareness, treatment, and control of this condition are essential. Therefore, this study aimed to review the literature and pool the awareness, treatment, and control of diabetes at the global, regional, and national levels. Methods: In this systematic review and meta-analysis, several databases, including MEDLINE/PubMed, Institute of Scientific Information (ISI), Scopus, and Google Scholar, were searched using appropriate keywords up to June 2022. Observational studies investigating the awareness, treatment, and control of glucose levels among diabetic individuals were included. Awareness, treatment, and control were defined as the proportion of participants who were aware of their diabetes condition, treated pharmacologically, and achieved adequate glucose control, respectively. Two investigators independently conducted the study selection, data extraction, and quality assessment. Heterogeneity among studies was calculated using Chi-square, and a random-effect meta-analysis was used to pool the rates. Results: A total of 233 studies published between 1985 and 2022 met the inclusion criteria. The included studies had a combined population of 12,537,968. The pooled awareness of DM was 60% (95%CI: 56-63) and ranged from 41% (25-57) in low-income countries to 68% (64-72) in high-income countries, with no significant trend observed over the assessed periods at the global level. The pooled treatment of DM globally was 45% (42-48) and varied from 37% (31-43) in lower-middle-income countries to 53% (47-59) in high-income countries, showing variation over the examined time period. Before 2000, the proportion of adequate DM control was 16% (12-20), which significantly improved and reached 22% (19-25) after 2010. The pooled awareness, treatment, and control of DM were higher in females, high-income countries, and urban areas compared to males, upper and lower-middle-income countries, and rural areas, respectively. The older adults population had higher awareness and treatment rates than the adult population, but their DM control did not differ significantly. Conclusion: Despite the high level of awareness and treatment among the diabetic population, treatment success (control) is considerably low, particularly in low-income countries and rural areas. It is crucial to improve awareness, treatment, and control by strengthening the primary care system in all countries.

Development and validation of a plasmalogen score as an independent modifiable marker of metabolic health: population based observational studies and a placebo-controlled cross-over study.

BACKGROUND: Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle. METHODS: We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years). FINDINGS: In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21-0.43), 0.39 (95% CI 0.25-0.61) and 0.42 (95% CI 0.30-0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56-0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score. INTERPRETATION: The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings. FUNDING: National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.

BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

Associations of vegetable and potato intakes with markers of type 2 diabetes risk in the AusDiab cohort.

CONTEXT: The associations of vegetable and potato intakes with type 2 diabetes (T2D) appear to be nuanced, depending on vegetable types and preparation method, respectively. OBJECTIVE: We investigated the associations of total vegetable, vegetable subgroup, and potato intakes with 1) markers of T2D at baseline and 2) incident T2D cumulative over a 12-year follow-up period in Australian adults. METHODS: Using data from the Australian Diabetes, Obesity and Lifestyle Study, intakes of vegetables and potatoes were assessed via a food frequency questionnaire at baseline. Associations between vegetable intake and 1) fasting plasma glucose (FPG), 2-hour post load plasma glucose (PLG), updated homeostasis model assessment of ß-cell function (HOMA2-%ß), HOMA2 of insulin sensitivity (HOMA2-%S), and fasting insulin levels at baseline and 2) cumulative incident T2D at the end of 12-year follow-up were examined using generalized linear and Cox proportional hazards models, respectively. RESULTS: In total, 8,009 participants were included having median age of 52 years, and vegetable intake of 132 g/day. Higher intake of total vegetable, green leafy, yellow/orange/red, and moderate intakes of cruciferous vegetables was associated with lower PLG. Additionally, higher green leafy vegetable intake was associated with lower HOMA2-%ß and serum insulin. Conversely, higher potato fries/chips intakes were associated with higher FPG, HOMA2-%ß, serum insulin, and lower HOMA2-%S. Participants with moderate cruciferous vegetables intake had a 25% lower risk of T2D at the end of 12 years follow-up. CONCLUSIONS: A higher intake of vegetables, particularly green leafy vegetables, may improve while consuming potato fries/chips, but not potatoes prepared in a healthy way, may worsen glucose tolerance and insulin sensitivity. Our findings suggest a nuanced relationship between vegetable subgroups and their impact on glucose tolerance.

Evaluating the incidence of complications among people with diabetes according to age of onset: Findings from the UK Biobank.

AIMS: To examine the impact of current age, age at diagnosis, and duration of diabetes on the incidence rate of complications among people with type 2 diabetes. METHODS: Baseline data from 19,327 individuals with type 2 diabetes in the UK Biobank were analysed. Poisson regression was used to model incidence rates by current age, age at diagnosis, and duration of diabetes for the following outcomes: myocardial infarction (MI), heart failure (HF), stroke, end-stage kidney diseases (ESKD), chronic kidney diseases (CKD), liver diseases, depression, and anxiety. RESULTS: The mean age at baseline was 60.2 years, and median follow-up was 13.9 years. Diabetes duration was significantly longer among those with younger-onset type 2 diabetes (diagnosed at <40 years) compared to later-onset type 2 diabetes (diagnosed at ≥40 years), 16.2 and 5.3 years, respectively. Incidence rates of MI, HF, stroke, and CKD had strong positive associations with age and duration of diabetes, whereas incidence rates of ESKD liver diseases, and anxiety mainly depended on duration of diabetes. The incidence rates of depression showed minor variation by age and duration of diabetes and were highest among those diagnosed at earlier ages. No clear evidence of an effect of age of onset of diabetes on risk of complications was apparent after accounting for current age and duration of diabetes. CONCLUSIONS: Our study indicates age at diagnosis of diabetes does not significantly impact the incidence of complications, independently of the duration of diabetes. Instead, complications are primarily influenced by current age and diabetes duration.

Cardiovascular disease hospitalizations among women who undergo fertility treatment.

RESEARCH QUESTION: Are women who receive fertility treatment at increased risk of cardiovascular disease (CVD) hospitalization compared with women who do not? DESIGN: A retrospective cohort study of all women registered for fertility treatment at Monash IVF between 1998 and 2014. This cohort was linked to the Victorian Admitted Episodes Dataset, which contains records of all hospital admissions in the Australian state of Victoria. Age- and Index of Relative Socioeconomic Disadvantage (IRSD)-adjusted relative risks of CVD hospitalization for women who did or did not undergo fertility treatment were determined using Poisson regression. Risks were calculated overall by CVD subtype and stratified by area-based social disadvantage using IRSD fifths, number of stimulated cycles and mean oocytes per cycle. RESULTS: Of 27,262 women registered for fertility treatment, 24,131 underwent treatment and 3131 did not. No significant difference was found in risk of CVD hospitalization between treated and untreated women overall (adjusted RR 0.93, 95% 0.82 to 1.05) or by CVD subtype. The admission risk for CVD was significantly lower in treated women who had a mean of fewer than five oocytes per cycle (adjusted RR 0.80, 95% CI 0.70 to 0.92) compared with untreated women. Treated women residing in areas within the second IRSD fifth were less likely to be hospitalized for CVD compared with untreated women (age-adjusted RR 0.66, 95% CI 0.49 to 0.89). CONCLUSIONS: Fertility treatment is not associated with increased risk of CVD hospitalization. Lower risk among some subgroups of treated women may be explained by social disadvantage.

Urine Albumin-Creatinine Ratio Variability in People With Type 2 Diabetes: Clinical and Research Implications.

RATIONALE & OBJECTIVE: Evidence has demonstrated that albuminuria is a key diagnostic and prognostic marker of diabetic chronic kidney disease, but the impact of its day-to-day variability has not been adequately considered. This study quantified within-individual variability of albuminuria in people with type 2 diabetes to inform clinical albuminuria monitoring. STUDY DESIGN: Descriptive cross-sectional analysis. SETTING & PARTICIPANTS: People with type 2 diabetes (n=826, 67.1 [IQR, 60.3-72.4] years, 64.9% male) participating in the Progression of Diabetic Complications (PREDICT) cohort study. EXPOSURE: Four spot urine collections for measurement of urinary albumin-creatinine ratio (UACR) within 4 weeks. OUTCOME: Variability of UACR. ANALYTICAL APPROACH: We characterized within-individual variability (coefficient of variation [CV], 95% limits of random variation, intraclass correlation coefficient), developed a calculator displaying probabilities that any observed difference between a pair of UACR values truly exceeded a 30% difference, and estimated the ranges of diagnostic uncertainty to inform a need for additional UACR collections to exclude or confirm albuminuria. Multiple linear regression examined factors influencing UACR variability. RESULTS: We observed high within-individual variability (CV 48.8%; 95% limits of random variation showed a repeated UACR to be as high/low as 3.78/0.26 times the first). If a single-collection UACR increased from 2 to 5mg/mmol, the probability that UACR actually increased by at least 30% was only 50%, rising to 97% when 2 collections were obtained at each time point. The ranges of diagnostic uncertainty were 2.0-4.0mg/mmol after an initial UACR test, narrowing to 2.4-3.2 and 2.7-2.9mg/mmol for the mean of 2 and 3 collections, respectively. Some factors correlated with higher (female sex; moderately increased albuminuria) or lower (reduced estimated glomerular filtration rate and sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor/angiotensin receptor blocker treatment) within-individual UACR variability. LIMITATIONS: Reliance on the mean of 4 UACR collections as the reference standard for albuminuria. CONCLUSIONS: UACR demonstrates a high degree of within-individual variability among individuals with type 2 diabetes. Multiple urine collections for UACR may improve capacity to monitor changes over time in clinical and research settings but may not be necessary for the diagnosis of albuminuria. PLAIN-LANGUAGE SUMMARY: Albuminuria (albumin in urine) is a diagnostic and prognostic marker of diabetic chronic kidney disease. However, albuminuria can vary within an individual from day to day. We compared 4 random spot urinary albumin-creatinine ratio (UACR) samples from 826 participants. We found that a second UACR collection may be as small as a fourth or as large as almost 4 times the first sample's UACR level. This high degree of variability presents a challenge to our ability to interpret changes in albuminuria. Multiple collections have been suggested as a solution. We have constructed tools that may aid clinicians in deciding how many urine collections are required to monitor and diagnose albuminuria. Multiple urine collections may be required for individual monitoring but not necessarily for diagnosis.

Special Issue: "New Trends in Diabetes, Hypertension, and Cardiovascular Diseases".

Cardiovascular disease (CVD) encompasses a range of disorders affecting the heart and blood vessels, including coronary heart disease and cerebrovascular disease [...].

SGLT-2 Inhibitor Use and Cause-Specific Hospitalization Rates: An Outcome-Wide Study to Identify Novel Associations of SGLT-2 Inhibitors.

Sodium-glucose co-transporter 2 inhibitors (SGLT2is) have demonstrated multifaceted pharmacological effects. In addition to type 2 diabetes, they are now indicated for heart failure and chronic kidney disease. This study aimed to identify novel associations between SGLT2i use and health outcomes using real-world data. Using linked data from a nationwide diabetes registry in Australia, we compared hospitalization rates in people living with type 2 diabetes commencing treatment with SGLT2i and dipeptidyl peptidase-4 inhibitor (DPP4i) between December 1, 2013, and June 30, 2019. Cause-specific hospitalizations were categorized across three hierarchies of diagnoses (first, first three, and first four digits of International Classification of Diseases, Tenth Version, Australian Modification codes). Incidence rate ratio (IRR) and 95% confidence interval (95% CI) for each cause-specific hospitalization were estimated using negative binomial regression. In the first hierarchy, hospitalization rates were lower across most diagnosis groups among SGLT2i initiators (n = 99,569) compared with DPP4i initiators (n = 186,353). In the second and third hierarchies, there were lower hospitalization rates relating to infections, anemias, and obstructive airway diseases among SGLT2i initiators compared with DPP4i initiators. These included sepsis (IRR: 0.60, 95% CI: 0.51-0.72) anemia (IRR: 0.55, 95% CI: 0.46-0.66), and chronic obstructive pulmonary diseases (IRR: 0.52, 95% CI: 0.40-0.68), as well as for previously known associations (e.g., heart failure (IRR: 0.63, 95% CI: 0.56-0.70)). SGLT2is have previously uncharacterized associations on a range of important clinical outcomes; validation of these associations requires further study, some of which may suggest novel benefits or new indications for SGLT2is.

Imputation of plasma lipid species to facilitate integration of lipidomic datasets.

Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

Causes of death among Australians with type 1 or type 2 diabetes, 2002-2019.

AIMS: This population-based study sought to explore in detail the conditions driving the diversification in causes of death among people with diabetes. METHODS: We linked Australians with type 1 or type 2 diabetes of all ages on the National Diabetes Services Scheme to the National Death Index for 2002-2019. We investigated the proportional contributions of different causes of death to total deaths over time across eight categories of causes of death, stratified by sex and diabetes type. The underlying causes of death were classified according to the International Classification of Diseases, Tenth Revision codes. RESULTS: Between 2002 and 2019, there was a shift in the causes of death among Australians with diabetes away from cardiovascular disease. The proportion of deaths attributed to cardiovascular disease declined in both sexes (ptrend <0.001), most substantially among women with type 2 diabetes from 48.2% in 2002 to 30.7% in 2019. Among men with type 2 diabetes, cancer replaced cardiovascular disease as the leading cause of death. The proportion of deaths due to dementia increased overall, from 2% in 2002 to over 7% in 2019, and across all age groups, notably from 1% to 4% in those aged 70-79. The proportion of deaths due to falls and Parkinson's disease also increased. CONCLUSIONS: There has been a shift of causes of death among those with diabetes away from cardiovascular disease. The proportion of deaths due to conditions such as dementia and falls is increasing among those with diabetes, which will require consideration when planning future resource allocation.

Liver disease mortality and hospitalisations among people with type 2 diabetes mellitus: A population-based study.

BACKGROUND AND AIMS: The burden of liver disease among people with diabetes at a population level is unknown. We explored the burden and trends of liver disease mortality and hospitalisations among Australians with diabetes. METHODS: We linked Australians with type 2 diabetes on the National Diabetes Services Scheme to the National Death Index for 2002-2019 to determine trends in the proportion of deaths due to liver disease, overall and by subcategory. We also determined the leading reasons and risk factors for liver disease hospitalisations in those with diabetes over this period. Finally, we compared the burden of liver disease hospitalisations among those with diabetes to the general population using excess hospitalisations per 100 000 person-years. RESULTS: Among Australians with type 2 diabetes (n = 1 122 431) liver diseases accounted for between 1.5% and 1.9% of deaths between 2002 and 2019, roughly one-third of the proportion of deaths caused by kidney disease. The proportion of deaths due to inflammatory liver diseases among those with diabetes increased from .08% in 2002 to .27% in 2019. Alcohol-related liver disease accounted for the greatest share (22.7%) of liver disease hospitalisation in those with diabetes, but the number of hospitalisations for this condition declined over time. Compared to the general population, men (RR 3.63, 95% CI 3.44-3.84) and women (RR 4.49, 4.21-4.78) with diabetes were at higher risk of hospitalisation for fibrosis and cirrhosis; however, this did not translate to a substantial excess risk per 100 000 population. CONCLUSIONS: Better screening methods for liver disease among people with diabetes should be developed and implemented into practice.

Reasons for Hospitalization Among Australians With Type 1 or Type 2 Diabetes and COVID-19.

OBJECTIVE: Our aim in this study was to determine the reasons for hospitalization in Australian people with diabetes who contract COVID-19. METHODS: All COVID-19 cases reported to the Victorian Department of Health and linked hospitalization data were assessed. We determined reasons for acute (0 to 30 days) and postacute (31 to 365 days) hospitalization among those with type 1 or type 2 diabetes and COVID-19, compared to those with COVID-19 and no diabetes, and to admissions before the COVID-19 pandemic. RESULTS: A total of 13,302 Australians with type 1 or type 2 diabetes were hospitalized in the state of Victoria in the 12 months after COVID-19 diagnosis. Respiratory diseases accounted for 40% of acute admissions among those with diabetes. Viral pneumonia was the leading cause of acute hospitalization among those with diabetes and constituted a larger proportion of admissions in those with compared to those without diabetes (adjusted prevalence ratio 1.87, 95% confidence interval 1.76 to 1.99). The distribution of postacute hospitalizations among those with diabetes aligned with that of people with diabetes before the COVID-19 pandemic. CONCLUSIONS: Respiratory diseases are the leading cause of acute hospitalization in those with type 1 or type 2 diabetes and COVID-19. The reasons for postacute hospitalization resemble those in people with diabetes and no COVID-19. We reinforce the importance of community management of people with diabetes in the ongoing pandemic.

Reasons for hospitalisation in youth with type 1 diabetes, 2010-2019.

AIMS: To determine the incidence of hospitalisation for all diagnoses among Australian youth with type 1 diabetes. METHODS: We linked Australians aged under 20 years with type 1 diabetes on the National Diabetes Services Scheme (n = 45,685) to hospital admission data from 2010 to 2019. We determined relative risks (RR) of hospitalisation among those with type 1 diabetes in the states of Victoria and Queensland (n = 21,898) compared to the general population for 2010-2017 using Poisson regression. RESULTS: Australian youth with type 1 diabetes had increased risk for almost all reasons for hospitalisation compared to the general population, especially infections such as anogenital herpesviral infections (RR 54.83, 95% CI 33.21-90.53), and mental health disorders including personality disorders (RR 9.70, 95% CI 8.02-11.72). Among those with type 1 diabetes, over 60% of hospitalisations were directly related to diabetes, almost half of which were for ketoacidosis. Approximately 15% of ketoacidosis admissions occurred within 3 months of diabetes diagnosis. One quarter of those with admissions for ketoacidosis were readmitted for ketoacidosis within 12 months. Residence in areas of high socio-economic disadvantage was an independent risk factor for admission and readmission for ketoacidosis. CONCLUSIONS: Youth with type 1 diabetes are susceptible to a wide range of complications. Clinicians should consider screening and prevention for conditions such as infections and mental health disorders. Targeted support and education around glycaemic management should be considered in those at high risk for ketoacidosis admission including those living in areas of high socio-economic disadvantage.

COX2 inhibitor use and type 2 diabetes treatment intensification: A registry-based cohort study.

AIM: This study examined the association between cyclooxygenase-2 inhibitor (COX2i) use and diabetes progression in people with type 2 diabetes. METHODS: We conducted a nation-wide cohort study using an Australian diabetes registry linked to medication dispensing data. We assessed time to diabetes treatment intensification among new users of COX2i compared to mild opioids. Inverse probability of treatment-weighted Cox regression models were used to adjust for age, sex, time since diabetes diagnosis, comorbidities, and socio-economic disadvantage. We conducted several sensitivity analyses, including per-protocol analyses and comparing use of any NSAID to mild opioids. RESULTS: There were 8,071 new users of COX2i and 7,623 of mild opioids with 4,168 diabetes treatment intensifications over a median follow-up of 1.6 years. Use of COX2i was associated with decreased risk of treatment intensification when compared to mild opioids (HR 0.91, 95 %CI 0.85-0.96). The results were not significant in the per-protocol analyses. Use of any NSAID was associated with a lower risk of treatment intensification compared to mild opioids (HR 0.90, 95 %CI 0.85-0.96). CONCLUSIONS: Treatment with COX2i may be associated with a modest decreased risk of diabetes treatment intensification compared to mild opioids. Future clinical studies are required to confirm whether COX2 inhibition has clinically significant benefits for glycaemic control.

Hospital admissions among people with diabetes: A systematic review.

OBJECTIVE: To describe the reasons for hospital admission among people with diabetes. METHODS: We searched Emcare, Embase, Medline and Google Scholar databases for population-based studies describing the causes of hospitalisation among people with diabetes. We included articles published in English from 1980 to 2022. For each study, we determined the most frequent reasons for admission. Studies were assessed for quality using the Newcastle Ottawa quality assessment tool. RESULTS: 6920 research articles were retrieved from the search of all sources. After screening the titles and abstracts of these, we reviewed the full text of 135 papers and finally included data from 42 studies. Admissions among the total diabetes were reported in 25 papers: 5 articles reported type 1 diabetes alone, 10 articles reported type 2 diabetes alone and the remaining 2 articles reported type 1 and type 2 diabetes separately. Among the 25 total and type 2 diabetes studies that reported the distribution of hospitalisations in broad categories, cardiovascular diseases (CVD) were the leading cause of admission in 19/25 (76%) of studies. Among the 19 studies that reported CVD admissions by subcategories, ischaemic or coronary heart disease was the leading subtype of CVD in 58% of studies. The other common causes of admissions were infections, renal disorders, endocrine, nutritional, metabolic and immunity disorders. In people with type 1 diabetes, acute diabetes complications were the leading cause of admission. CONCLUSION: CVD are the leading cause of hospital admission for people with diabetes, with ischaemic or coronary heart disease as the predominant subtype.