Type 2 Diabetes Mellitus Cohort Research Articles

Abstract 4118451: A Real-world Evaluation of Longitudinal Healthcare Expenses in a Health System Registry of Type-2 Diabetes Mellitus and Cardiovascular Disease Enabled by the 21 st Century Cures Act

Background: An evaluation of the longitudinal burden of healthcare expenses in type-2 diabetes mellitus (T2DM) is limited to self-selected cohorts and claims-based or self-reported spending. Leveraging the 21 st Century Cures Act rule that made reporting hospital-level service prices mandatory, we demonstrate healthcare spending in T2DM with and without cardiovascular disease in a diverse multisite EHR-based T2DM cohort. Methods: Patients with T2DM seeking regular care (≥ 1 visit/2 years) across 5 hospitals and a large outpatient network (2013-2023) in the Yale New Haven Health System (YNHHS). Cohorts were defined by the presence of atherosclerotic cardiovascular disease (ASCVD) and/or heart failure (HF) before or up to 1 year after the T2DM diagnosis. We used the YNHHS chargemaster file to extract Medicare and insurance-negotiated cash prices. We linked census data using residential zip codes to estimate household income, used multivariable logistic regression to identify factors associated with financial hardship (health expenses >20% of income), and evaluated expenses during the last year of life. All values were inflation-adjusted to 2023 US$. Results: Overall, 106881 patients with T2DM followed for 5.4 years (3.1-7.5) had 147919 hospitalizations, representing $3.41B in expected healthcare expenses. 8% of patients with T2DM without ASCVD/HF, 14% with ASCVD, 23% with HF, and 28% with ASCVD and HF had a financial obligation for healthcare above the threshold for financial hardship. Compared with White patients, Black and Hispanic patients were more likely, and Asians were less likely to have financial hardship (OR: Black, 1.81 [1.73-1.91]; Hispanic, 1.39 [1.31-1.48]; Asian, 0.46 [0.37-0.57]), after accounting for age, sex, and comorbidities. Comorbid HF at baseline portended 2x higher odds of financial hardship (OR: HF, 2.20 [2.00-2.42]; ASCVD and HF, 1.98 [1.84-2.14]) compared with T2DM alone. Care in the last year of life represented 72-80% of overall health expenses, with 55-61% of patients at risk for financial hardship across cohorts. Conclusion: A digital individualized expense-linked registry of patients enabled by recent US price transparency rules defined that annually, one-fifth of patients with T2DM and cardiovascular disease had healthcare events exceeding 20% of their annual income, and vulnerable racial/ethnic minorities were at high risk for financial toxicity.

Clinical, genomic, and proteomic perspectives in the analysis of comorbid conditions in type 2 diabetes mellitus: a retrospective study.

Type-2 Diabetes Mellitus (T2DM) affects millions globally, with escalating rates. It often leads to undiagnosed complications and commonly coexists with other health conditions. This study investigates two types of prevalent comorbidities related to T2DM-the circulatory system (DCM1) and digestive system diseases (DCM2)-using clinical, genomic and proteomic datasets. The aim is to identify new biomarkers by applying existing machine learning (ML) based techniques for early detection, prognosis and diagnosis of these comorbidities. Here, we report a cross-sectional retrospective analysis from a T2DM dataset of T2DM associated concordant comorbidities (diseases with shared pathophysiology and management) from the Diastrat cohort (a T2DM cohort) recruited at the Northern Ireland Centre for Stratified Medicine (NICSM), in Northern Ireland. In the clinical data analysis, we identified that lipidemia was shown to negatively correlate with depression in the DCM1 group while positively correlate with depression in the DCM2 group. In genomic analysis, we identified statistically significant variants rs9844730 in procollagen-lysine (PLOD2), rs73590361 in beta-1,4-N-acetyl- galactosaminyl-transferase (B4GALNT3) and rs964680 in A kinase (PRKA) anchor protein 14 (AKAP14) which appear to differentiate DCM1 and DCM2 groups. In proteomic analysis, we identified 4 statistically significant proteins: natriuretic peptides B (BNP), pro-adrenomedullin (ADM), natriuretic peptides B (NT-proBNP) and discoidin (DCBLD2) that can differentiate DCM1 and DCM2 groups and have built robust ML model using clinical, genomic, and proteomic markers (0.83 receiver operative characteristics curve area, 84% positive predictive value and 83% negative predictive value and a classification accuracy of 83%) for prediction of DCM1 and DCM2 groups. Our study successfully identifies novel clinical, genomic, and proteomic biomarkers that differentiate between circulatory and digestive system comorbidities in Type-2 Diabetes Mellitus patients. The machine learning model we developed demonstrates strong predictive capabilities, providing a promising tool for the early detection, prognosis, and diagnosis of these T2DM-associated comorbidities. These findings have the potential to enhance personalized management strategies for patients with T2DM, ultimately improving clinical outcomes. Further research is needed to validate these biomarkers and integrate them into clinical practice.

7515 Plasma proteomic signatures for type 2 diabetes mellitus and related traits in the UK Biobank

Abstract Disclosure: T. Gupte: None. Z. Azizi: None. K. Nzenkue: None. P. Kho: None. M. Chen: None. J. Zhou: None. R. Guarischi-Sousa: None. D.J. Panyard: None. F. Abbasi: None. K. Watson: None. S. Clarke: None. P.S. Tsao: None. T.L. Assimes: None. Background: The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to associate with two primary risk factors of type 2 diabetes mellitus (T2DM) and to predict incident T2DM. Methods: Clinical, genetic, and high-throughput proteomic data from three subcohorts of 5586, 5584, and 36339 individuals in the UK Biobank were analyzed for association with DXA-measured truncal fat, maximum VO2, and incident T2DM, respectively. Exclusion criteria included prevalent T2DM, history of T1DM, or elevated A1c (>48 mmol/mol) values. We used LASSO to assess relative ability of 13 clinical variables including the Q-Diabetes (Q-D) score, 36 polygenic risk scores (PRSs), and 2923 proteins to associate with each trait by comparing variances explained (R2) and AUC statistics between data types. Stability selection with randomized LASSO identified the most robustly associated proteins for each trait. The benefit of proteomic signatures (PSs) over the Q-D score was evaluated through the derivation of Δ AUC values. Separate case-control groups were developed to evaluate T2DM prediction in the adiposity and fitness cohorts. Results: Across all three subcohorts, the mean age was 56.6 years, 54.9% were female, and 5.4% developed T2DM over a median follow-up of 7.7 years. In the adiposity cohort, a protein-only LASSO model explained 73.2% of the variance in truncal fat and GLIPR1, CLMP, LEP, FABP4, and FAM3C were among the top proteins selected. In the fitness cohort, a protein-only LASSO model explained 61.9% of the variance in maximum VO2 and LEP, CD99, AGRN, ELN, and CA14 were among the top proteins selected. LASSO-derived PSs increased the R2 of truncal fat and maximum VO2 over clinical and genetic factors by 13% and 1%, respectively, with the former also improving risk prediction of T2DM over Q-D [Δ AUC: 0.026 (95% CI -0.007, 0.060)]. In the T2DM cohort, a protein-only LASSO model returned an AUC of 0.856 (95% CI 0.840, 0.871) and PLXNB2, PODXL, PLA2G7, FGFR2, and NFASC were among the top proteins selected. We observed a similar improvement in T2DM prediction over Q-D [Δ AUC: 0.015 (95% CI 0.009, 0.023)] when using a PS derived strictly from the T2DM outcome and augmented with non-overlapping proteins associated with fat and fitness. A few proteins (ranging between 15-33 for each trait) identified by stability selection algorithms offered most of the improvement in risk prediction. Conclusion: Plasma PS modestly improves the prediction of T2DM over that possible with clinical and genetic factors. Further studies are warranted to better elucidate the clinical utility of these signatures in predicting T2DM risk over the standard practice of using the Q-D score. Presentation: 6/2/2024

Real-world study of the multimorbidity and health service utilisation among individuals with non-diabetic hyperglycemia and type 2 diabetes mellitus in North West London

IntroductionThe prevalence of non-diabetic hyperglycemia (NDH) and type 2 diabetes mellitus (T2DM) is increasing. While T2DM is recognised to be associated with multimorbidity and early mortality, people with NDH are...

Inter-relation between diabetes mellitus and hypertension in terms of incidence and prediction in Saudi Arabia: a retrospective cohort study

BackgroundHypertension (HTN) and type 2 diabetes mellitus (T2DM) are interconnected metabolic disorders with escalating global incidence and prevalence. However, no longitudinal studies have specifically examined the incidence of HTN and T2DM in the same study population. This study aimed to elucidate the association between HTN and T2DM and ascertain their respective roles in the development of each other.MethodsThis retrospective cohort study encompassed 809 Saudi patients from primary healthcare centers in Al Madinah Al Munawarah, Saudi Arabia. The sample was stratified into three cohorts: 226 patients with HTN but without T2DM, 274 patients with T2DM but without HTN, and 309 patients devoid of both T2DM and HTN. Over a retrospective follow-up period of approximately 5 years, incidence density rates (IDR) were computed for HTN in the T2DM cohort, T2DM in the HTN cohort, and both HTN and T2DM in the control cohort. Multiple logistic regression analysis was employed to identify predictors of HTN and T2DM.ResultsThe IDR of T2DM among patients with HTN stood at 73.9 (95% confidence interval [CI] 56, 92) per 1000 person-years, in contrast to 33.9 (95% CI 24, 44) per 1000 person-years in the control cohort (adjusted odds ratio [OR] = 7.1, 95%CI 3.55, 14.13). Conversely, the IDR of HTN among patients with type-2 T2DM was 55.9 (95% CI 42, 70) per 1000 person-years, while in the control cohort, it was 20.8 (95% CI 13, 28) per 1000 person-years (adjusted OR = 5.8, 95% CI 3.11, 11.09). Significant predictors of HTN in the logistic regression model encompassed age, smoking status, family history of HTN, T2DM status, and body mass index (BMI). Similarly, significant predictors of T2DM in the logistic regression model included age, sex, family history of T2DM, HTN, and BMI.ConclusionThis study unveils HTN and T2DM as mutually significant risk factors. The IDR of each condition in the presence of the other significantly exceeded that among individuals devoid of HTN or T2DM.

Lipid Levels and Risk of Diabetic Polyneuropathy in 2 Danish Type 2 Diabetes Cohorts.

Reduction of blood lipids may aid in preventing diabetic polyneuropathy (DPN), but evidence remains conflicting. We investigated the association between lipid parameters and DPN risk in individuals with type 2 diabetes mellitus (T2DM). We conducted a population-based cohort study of individuals with newly diagnosed T2DM and a cross-sectional study using a clinically recruited T2DM cohort. Triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and non-HDL cholesterol were measured in routine diabetes care. Each lipid parameter was categorized according to the latest cutoffs in clinical guidelines on dyslipidemia. DPN was assessed with validated hospital diagnosis codes in the population-based cohort and with the Michigan Neuropathy Screening Instrument questionnaire in the clinical cohort. We calculated hazard ratios (HRs) using Cox regression and prevalence ratios (PRs) using Poisson regression. We included 61,853 individuals in the population-based cohort (median age 63 [quartiles 54-72] years) and 4,823 in the clinical cohort (median age 65 [quartiles 57-72] years). The incidence rate of hospital-diagnosed DPN in the population-based cohort was 3.6 per 1000 person-years during a median follow-up of 7.3 years. Achieving guideline targets for HDL, LDL, and non-HDL cholesterol showed no association with DPN risk. By contrast, adjusted HRs (95% CI) for DPN were 1.02 (0.89-1.18) for triglyceride levels between 150 and 204 mg/dL (1.7-2.3 mmol/L) and 1.28 (1.13-1.45) for levels >204 mg/dL (2.3 mmol/L). In the clinical cohort with a DPN prevalence of 18%, DPN associated strongly with triglycerides >204 mg/dL (2.3 mmol/L) with an adjusted PR (95% CI) of 1.40 (1.21-1.62). The prevalence of DPN was modestly elevated for individuals with HDL cholesterol <39 mg/dL (1.0/1.3 mmol/L) in men and <50 mg/dL (1.3 mmol/L) in women (PR 1.13 [0.99-1.28]) and for individuals with non-HDL cholesterol >131 mg/dL (3.4 mmol/L) (PR 1.27 [1.05-1.52]). In both cohorts, spline models showed an increasing risk of DPN starting from triglyceride levels >124 mg/dL (1.4 mmol/L). All results were similar among statin users. High triglyceride levels are a strong DPN risk factor. Future intervention studies shall determine whether triglyceride reduction is more important for DPN prevention than reduction of other lipids.

Recent Glycemia Is a Major Determinant of β-Cell Function in Type 2 Diabetes Mellitus.

Progressive deterioration of β-cell function is a characteristic of type 2 diabetes mellitus (T2DM). We aimed to investigate the relative contributions of clinical factors to β-cell function in T2DM. In a T2DM cohort of 470 adults (disease duration 0 to 41 years), β-cell function was estimated using insulinogenic index (IGI), disposition index (DI), oral disposition index (DIO), and homeostasis model assessment of β-cell function (HOMA-B) derived from a 75 g oral glucose tolerance test (OGTT). The relative contributions of age, sex, disease duration, body mass index, glycosylated hemoglobin (HbA1c) levels (at the time of the OGTT), area under the curve of HbA1c over time (HbA1c AUC), coefficient of variation in HbA1c (HbA1c CV), and antidiabetic agents use were compared by standardized regression coefficients. Longitudinal analyses of these indices were also performed. IGI, DI, DIO, and HOMA-B declined over time (P<0.001 for all). Notably, HbA1c was the most significant factor affecting IGI, DI, DIO, and HOMA-B in the multivariable regression analysis. Compared with HbA1c ≥9%, DI was 1.9-, 2.5-, 3.7-, and 5.5-fold higher in HbA1c of 8%-<9%, 7%-<8%, 6%-<7%, and <6%, respectively, after adjusting for confounding factors (P<0.001). Conversely, β-cell function was not affected by the type or duration of antidiabetic agents, HbA1c AUC, or HbA1c CV. The trajectories of the IGI, DI, DIO, and HOMA-B mirrored those of HbA1c. β-Cell function declines over time; however, it is flexible, being largely affected by recent glycemia in T2DM.

Risk of diabetes mellitus based on the interactive association between G6PD rs72554664 polymorphism and sex in Taiwan Biobank individuals

The presence of glucose-6-phosphate dehydrogenase (G6PD) deficiency may increase the risk of type 2 diabetes mellitus (T2DM), with differing prevalence between males and females. Although G6PD deficiency is an X-linked genetic condition, its interaction with sex regarding T2DM risk among the Taiwanese population has not been fully explored. This study aimed to investigate the association between G6PD deficiency and T2DM risk in the Taiwanese population, focusing on the potential influence of sex. Data were obtained from the Taiwan Biobank (TWB) database, involving 85,334 participants aged 30 to 70 years. We used multiple logistic regression analysis to assess the interaction between G6PD rs72554664 and sex in relation to T2DM risk. The T2DM cohort comprised 55.35% females and 44.65% males (p < 0.001). The TC + TT genotype of rs72554664 was associated with an increased risk of T2DM, with an odds ratio (OR) of 1.95 (95% CI: 1.39–2.75), and males showed an OR of 1.31 (95% CI: 1.19–1.44). Notably, the G6PD rs72554664-T allelic variant in hemizygous males significantly elevated the T2DM risk (OR), 4.57; p < 0.001) compared to females with the CC genotype. Our findings suggest that the G6PD rs72554664 variant, in conjunction with sex, significantly affects T2DM risk, particularly increasing susceptibility in males. The association of the G6PD rs72554664-T allelic variant with a higher risk of T2DM highlights the importance of sex-specific mechanisms in the interplay between G6PD deficiency and T2DM.

Role of serum endotoxin, FGF19, TLR2, TNF-α, IL-12 and IL-10 in NAFLD-associated T2DM pathogenesis: Insights into Th1 bias and protective mechanisms.

Non-alcoholic fatty liver disease (NAFLD) in non-obese patients is pathophysiologically distinct, exhibiting common immunological link with type-2 diabetes mellitus (T2DM). This study aims to delineate the role of Toll-like receptor 2 (TLR2)-mediated immuno-modulation along with its association with fibroblast growth factor receptor 4 (FGFR4) and its ligand fibroblast growth factor 19 (FGF19) in the pathogenesis of NAFLD without or with T2DM. Blood samples were collected from patients with NAFLD (n = 90), NAFLD with T2DM (n = 90) and healthy cohorts (n = 90) with consent and clinical records. Real-time polymerase chain reaction (PCR), enzyme-linked immunoassay (ELIZA) and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) were used to analyze messenger ribonucleic acid (mRNA), protein expression and gene polymorphism. The molecular genetic analysis revealed the prevalence of variant allele(A) in FGFR4 gene in both cases compared to controls. The mRNA expression of FGF19 and TLR2 exhibited significant upregulation in NAFLD without T2DM compared to NAFLD with T2DM. Tumor necrosis factor-α (TNF-α) and interleukin-12 (IL-12) showed upregulation in both disease cohorts compared to control while IL-10 showed significant downregulation in NAFLD with T2DM compared to the other two cohorts. Correlation analysis between FGF19 and TLR2 revealed significant positive association in both NAFLD with and without T2DM. The Th1:Th2 ratio showed significant upregulation in NAFLD with T2DM compared to NAFLD without T2DM. In conclusion, elevated serum endotoxin levels appear to contribute to NAFLD and T2DM development. Upregulated FGF19 seems to be protective against developing T2DM in NAFLD patients. Higher TLR2, TNF-α and IL-12 expression in NAFLD without T2DM suggests a Th1 bias in its pathogenesis, while reduced IL-10 in NAFLD with T2DM implies a more skewed Th1 state in this condition.

Combined serum CTRP7 and CTRP15 levels as a novel biomarker for insulin resistance and type 2 diabetes mellitus

AimsThis study aimed to examine the alterations in the serum CTRP7 and CTRP15 concentrations in patients newly diagnosed with type 2 diabetes mellitus (T2DM) and to assess the diagnostic potential of the log10 (CTRP7+CTRP15) for insulin resistance (IR) and T2DM. MethodsSerum CTRP7, CTRP15, and adiponectin levels were measured using an enzyme-linked immunosorbent assay (ELISA). Bioinformatics analysis was conducted to investigate CTRP7 and CTRP15-related genes and metabolic signaling pathways. ResultsLog10 (CTRP7+CTRP15) levels were notably elevated in the impaired glucose tolerance (IGT) and T2DM cohorts compared with those in the normal control (NGT) cohort. Log10(CTRP7+CTRP15) exhibited positive correlations with HOMA-IR, area under the glucose curve (AUCg), HbA1c%, triglyceride (TG), visceral adiposity index (VAI), body mass index (BMI), and free fatty acid (FFA), levels but negative correlations with adiponectin. Multivariate stepwise regression analysis revealed that HOMA-IR, BMI, HbA1c and FFA levels were independent factors affecting the log10 (CTRP7+CTRP15). Logistic regression analysis revealed that log10 (CTRP7+CTRP15) was independently associated with T2DM and significantly associated with increased risk. Receiver operating characteristic (ROC) curve analysis indicated that the predictive value of log10 (CTRP7+CTRP15) for T2DM and IR was superior to that of CTRP7 or CTRP15 alone. Intervention studies demonstrated that insulin, FFAs and acute exercise contribute to the elevation of serum CTRP7 levels, while hyperglycemia inhibited CTRP7 secretion. Short-term changes in blood glucose, insulin, FFA and acute exercise had minimal effects on serum CTRP15 levels. Bioinformatics analysis revealed that CTRP7 and CTRP15 interact with multiple metabolism-related genes and are enriched in glucose and lipid metabolism-related pathways. ConclusionLog10 (CTRP7+CTRP15) may serve as a valuable diagnostic marker for the management of metabolic-related diseases, particularly T2DM and IR.

Glucometabolic-Related Genes as Diagnostic Biomarkers and Therapeutic Targets for Alzheimer's Disease and Type 2 Diabetes Mellitus: A Bioinformatics Analysis.

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two widespread chronic disorders characterized by shared risk factors and molecular pathways. Glucose metabolism, pivotal for cellular homeostasis and energy supply, plays a critical role in these diseases. Its disturbance has been linked to the pathogenesis of both AD and T2DM. However, a comprehensive investigation into the specific roles of glucometabolic genes in the onset and progression of AD and T2DM has yet to be conducted. By analyzing microarray datasets from the Gene Expression Omnibus (GEO) repository, we identified differentially expressed glucometabolic genes (DEGs) in AD and T2DM cohorts. A range of bioinformatics tools were employed for functional annotation, pathway enrichment, protein interaction network construction, module analysis, ROC curve assessment, correlation matrix construction, gene set enrichment analysis, and gene-drug interaction mapping of these DEGs. Key genes were further validated using quantitative real-time polymerase chain reaction (qRT-PCR) in AD and T2DM murine models. Our investigation identified 41 glucometabolic-related DEGs, with six prominent genes (G6PD, PKM, ENO3, PFKL, PGD, and TALDO1) being common in both AD and T2DM cohorts. These genes play crucial roles in metabolic pathways including glycolysis, pentose phosphate pathway, and amino sugar metabolism. Their diagnostic potential was highlighted by area under curve (AUC) values exceeding 0.6 for AD and 0.8 for T2DM. Further analysis explored the interactions, pathway enrichments, regulatory mechanisms, and potential drug interactions of these key genes. In the AD murine model, quantitative real-time polymerase chain reaction (qRT-PCR) analysis revealed significant upregulation of G6pd, Eno3, and Taldo1. Similarly, in the T2DM murine model, elevated expression levels of G6pd, Pfkl, Eno3, and Pgd were observed. Our rigorous research sheds light on the molecular interconnections between AD and T2DM from a glucometabolic perspective, revealing new opportunities for pharmacological innovation and therapeutic approaches. This study appears to be the first to extensively investigate glucometabolic-associated DEGs and key genes in both AD and T2DM, utilizing multiple datasets. These insights are set to enhance our understanding of the complex pathophysiology underlying these widespread chronic diseases.

The association between TyG and all-cause/non-cardiovascular mortality in general patients with type 2 diabetes mellitus is modified by age: results from the cohort study of NHANES 1999–2018

BackgroundThe prognostic value of triglyceride-glucose (TyG) index in general type 2 diabetes mellitus (T2DM) patients is still unclear. Therefore, we aimed to determine the associations between TyG and all-cause/cause-specific death in a T2DM cohort and explore whether such associations would be modified by age.MethodsA total of 3,376 patients with T2DM from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 were selected and divided into the younger group (< 65 yrs) and the older group (≥ 65 yrs). Baseline TyG was calculated and cause-specific mortality status [cardiovascular (CV), cancer, and non-CV] was determined by the NHANES Public-Use Linked Mortality Files through 31 December 2019. Multivariate Cox and restricted cubic spline (RCS) regression models were used to evaluate the association between TyG and all-cause/cause-specific mortality. Interaction between TyG and age to mortality was also evaluated. Sensitivity analyses were performed in patients without cardiovascular disease, chronic kidney disease, or insulin treatment.ResultsDuring a median follow-up of 107 months, 805 all-cause deaths occurred, of which 250 and 144 were attributed to CV and cancer deaths. There was a significant age interaction to the association between TyG and all-cause/non-CV mortality. After fully adjusting for potential confounding factors, higher TyG was associated with an increased risk of all-cause [TyG per unit increase Hazard Ratio (HR) 1.33, 95% Confidence Interval (CI) 1.06–1.66, p = 0.014] and non-CV mortality (TyG per unit increase HR 1.54, 95% CI 1.18–2.01, p = 0.002) only in the younger group, but not in the older group. There was no significant association between TyG and CV/cancer death in the total cohort and two age subgroups. Similar results were found in RCS and sensitivity analyses.ConclusionIn a national sample of patients with T2DM in the United States, we found that the association between TyG and all-cause/non-CV death was modified by age. Higher TyG was only associated with an increased risk of all-cause/non-CV only in T2DM patients younger than 65 years old, but not in older patients.

Association Between Age at Diabetes Diagnosis and Subsequent Incidence of Cancer: A Longitudinal Population-Based Cohort.

Diabetes presenting at a younger age has a more aggressive nature. We aimed to explore the association of age at type 2 diabetes mellitus (T2DM) diagnosis with subsequent cancer incidence in a large Chinese population. The prospective population-based longitudinal cohort included 428,568 newly diagnosed T2DM patients from 2011 to 2018. Participants were divided into six groups according to their age at diagnosis: 20-54, 55-59, 60-64, 65-69, 70-74, and ≥75 years. The incidence of overall and 14 site-specific cancers was compared with the Shanghai general population including 100,649,346 person-years. A total of 18,853 and 582,643 overall cancer cases were recorded in the T2DM cohort and the general population. The age-standardized rate of overall cancer in T2DM patients was 501 (95% CI: 491, 511) per 100,000 person-years, and the standardized incidence ratio (SIR) was 1.10 (1.09, 1.12). Younger age at T2DM diagnosis was associated with higher incidence of overall and site-specific cancers. SIRs for overall cancer with T2DM diagnosis at ages 20-54, 55-59, 60-64, 65-69, 70-74, and ≥75 years were 1.48 (1.41, 1.54), 1.30 (1.25, 1.35), 1.19 (1.15, 1.23), 1.16 (1.12, 1.20), 1.06 (1.02, 1.10), and 0.86 (0.84, 0.89), respectively. Similar trends were observed for site-specific cancers, including respiratory, colorectum, stomach, liver, pancreatic, bladder, central nervous system, kidney, and gallbladder cancer and lymphoma among both males and females. Our findings highlight the necessity of stratifying management for T2DM according to age of diagnosis. As with a range of vascular outcomes, age-standardized cancer risks are greater in earlier compared with later onset T2DM.

The Combined Effect of Systemic Immune-Inflammation Index and Type 2 Diabetes Mellitus on the Prognosis of Patients Undergoing Percutaneous Coronary Intervention: A Large-Scale Cohort Study.

Chronic low-grade inflammation is the common mechanism of both atherosclerosis and type 2 diabetes mellitus (T2DM), and systemic immune-inflammation index (SII) has been emerged as a novel and simple inflammatory biomarker. However, the association between SII and glycemic metabolism and their synergetic effect on the prognosis of coronary artery disease (CAD) patients remains unclear. A total of 8602 patients hospitalized for percutaneous coronary intervention (PCI) were included. The primary endpoint was major adverse cardiovascular events (MACE), including all-cause death, myocardial infarction (MI), and target vessel revascularization. According to the optimal cut-off value of SII for MACEs, patients were grouped into higher levels of SII (SII-H) and lower levels of SII (SII-L) and further divided by the concomitance of T2DM into four groups: SII-H/T2DM, SII-H/Non-T2DM, SII-L/T2DM, SII-L/Non-T2DM. During a median 2.4-year follow-up, 522 MACEs occurred. The optimal cut-off value of SII for MACEs was 502.5. A 1-unit increase of SII (transformed by natural logarithm) was associated with a 29% increase of MACE risks in the T2DM cohort [adjusted hazard ratio (HR): 1.29, 95% confidence interval (CI): 1.03 to 1.61, P = 0.024], while had no effect in the non-T2DM cohort (HR: 1.03, 95% CI: 0.80 to 1.34, P = 0.800). Compared to those in SII-H/T2DM group, patients in SII-H/Non-T2DM, SII-L/T2DM, SII-L/Non-T2DM had significantly decreased risk of MACEs [adjusted HR: 0.77, 95% CI: 0.61 to 0.98, P = 0.036; adjusted HR: 0.66, 95% CI: 0.50 to 0.87, P = 0.003; adjusted HR: 0.58, 95% CI: 0.45 to 0.74, P < 0.001; respectively]. Multivariable Cox regression analysis also indicated the highest risk in T2DM patients with higher levels of SII than others (P for trend < 0.001). In this large-scale real-world study, diabetic patients with elevated SII levels were associated with worse clinical outcomes after PCI.

Impact of the first COVID-19 lockdown in Austria on laboratory and mental parameters in diabetic patients: a retrospective analysis highlighting the importance of regular medical consultations in a patient cohort.

Due to the COVID-19 pandemic, the first lockdown was implemented in Austria for almost 7 weeks. In contrast to many other countries, medical consultations were permitted, either by telemedicine or at doctors' offices. Nevertheless, restrictions related to this lockdown could possibly cause an increased risk of deterioration in health, especially in diabetes. This study aimed to assess the impact of Austria's first lockdown on laboratory and mental parameters in a type-2 diabetes mellitus cohort. Overall 347 mainly elderly patients with type-2 diabetes (56% male; aged 63.7±10.1 years) were included in this retrospective practitioner-based analysis. Laboratory as well as mental parameters were compared from before and after the lockdown. The lockdown showed no significant effect on HbA1c levels. On the other hand, total cholesterol (P<0.001) and LDL cholesterol (P<0.001) levels improved significantly, whereas body weight (P<0.01) and mental well-being based on the EQ-5D-3L questionnaire (P<0.01) increased significantly in terms of worsening. Lack of movement and staying at home resulted in a significant weight gain and worsening of mental well-being in type-2 diabetes during the first lockdown in Austria. Thanks to regular medical consultations, laboratory parameters remained stable or even improved. Thus, routine health check-ups in mainly elderly type 2 diabetic patients are essential to minimize the deterioration of health conditions during lockdowns.

HSD73 Characteristics of Type 2 Diabetes Patients That Used Virtual Care Since COVID-19 Pandemic: Evidence from a Large Commercial Healthcare Claims Database in the US

The use of virtual care has accelerated since the emergence of COVID-19 pandemic. This study aims to analyze the differences in patient characteristics between new and existing type 2 diabetes mellitus (T2DM) patients that utilized virtual care. Adult patients (age³18 years) with T2DM who had a virtual care (phone or video) visit between April 1, 2020 and March 31, 2022 from the OptumLabs Data Warehouse® were identified. The date of the first virtual visit was defined as the index date. Patients were required to be continuously insured at least 1 year prior to their index date (baseline) and at least 90 days of follow-up coverage. T2DM patients were categorized as newly diagnosed and as existing T2DM patients based on whether a diabetes diagnosis was observed in the baseline or not. A total of 1,864,203 unique T2DM patients were eligible, with18.5% identified as newly diagnosed and 81.5% as existing T2DM patients. On average, newly diagnosed T2DM patients were younger than existing T2DM patients. Majority (54.5%) of newly diagnosed T2DM patients were commercially insured compared to only 38.6% existing T2DM patients. Among the existing T2DM patients, 61.2% were White, 17.9% Non-Hispanic Black, 12.7% Hispanic and 8.2% others. Of this population, 12.7 % had a household income ≥ $125,000, 13.3% had at least a Bachelor’s degree, and 80.3% reside in a metropolitan area. For the newly diagnosed T2DM cohort, 59.7% were White, 15.3% Non-Hispanic Black, 13.4% Hispanic, and 11.6% others. More of the newly diagnosed T2DM cohort had higher household income, higher education, and resided in a metropolitan area compared to patients with existing T2DM. T2DM patients that used virtual care were heterogenous in terms of their baseline characteristics. This underscores the emerging trend that virtual care can potentially play a complementary role in managing patients with diabetes.

The burden of nonalcoholic steatohepatitis (NASH) in the United States

BackgroundThere is limited data on the comparative economic and humanistic burden of non-alcoholic steatohepatitis (NASH) in the United States. The objective was to examine the burden of disease comparing NASH to a representative sample of the general population and separately to a type 2 diabetes mellitus (T2DM) cohort by assessing health-related quality of life (HRQoL) measures, healthcare resource use (HRU) and work productivity and activity impairment (WPAI).MethodsData came from the 2016 National Health and Wellness Survey, a nationally representative patient-reported outcomes survey conducted in the United States. Respondents with physician-diagnosed NASH, physician-diagnosed T2DM, and respondents from the general population were compared. Humanistic burden was examined with mental (MCS) and physical (PCS) component summary scores from the Short-Form (SF)-36v2, concomitant diagnosis of anxiety, depression, and sleep difficulties. Economic burden was analysed based on healthcare professional (HCP) and emergency room (ER) visits, hospitalizations in the past six months; absenteeism, presenteeism, overall work impairment, and activity impairment scores on WPAI questionnaire. Bivariate and multivariable analysis were conducted for each outcome and matched comparative group.ResultsAfter adjusting for baseline demographics and characteristics, NASH (N = 136) compared to the matched general population cohort (N = 544), reported significantly lower (worse) mental (MCS 43.19 vs. 46.22, p = 0.010) and physical (PCS 42.04 vs. 47.10, p < 0.001) status, higher % with anxiety (37.5% vs 25.5%, p = 0.006) and depression (43.4% vs 30.1%, p = 0.004), more HCP visits (8.43 vs. 5.17), ER visits (0.73 vs. 0.38), and hospitalizations (0.43 vs. 0.2) all p’s < 0.05, and higher WPAI scores (e.g. overall work impairment 39.64% vs. 26.19%, p = 0.011). NASH cohort did not differ from matched T2DM cohort (N = 272) on mental or work-related WPAI scores, but had significantly worse physical status (PCS 40.52 vs. 44.58, p = 0.001), higher % with anxiety (39.9% vs 27.8%, p = 0.043), more HCP visits (8.63 vs. 5.68, p = 0.003) and greater activity impairment (47.14% vs. 36.07%, p = 0.010).ConclusionThis real-world study suggests that burden of disease is higher for all outcomes assessed among NASH compared to matched general controls. When comparing to T2DM, NASH cohort has comparable mental and work-related impairment but worse physical status, daily activities impairment and more HRU.

MP10-05 LITHOPROTECTIVE EFFECT OF GLP-1 AGONISTS IN DIABETIC STONE FORMERS

You have accessJournal of UrologyCME1 Apr 2023MP10-05 LITHOPROTECTIVE EFFECT OF GLP-1 AGONISTS IN DIABETIC STONE FORMERS Kelley Zhao, Brian Shkolnik, Jennifer Lu, Joshua Miller, and David Schulsinger Kelley ZhaoKelley Zhao More articles by this author , Brian ShkolnikBrian Shkolnik More articles by this author , Jennifer LuJennifer Lu More articles by this author , Joshua MillerJoshua Miller More articles by this author , and David SchulsingerDavid Schulsinger More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003225.05AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Type 2 Diabetes mellitus (T2DM) is associated with increased risk of calcium oxalate and uric acid (UA) stones. The most commonly prescribed medication for T2DM, Metformin, worsens this risk by increasing urinary oxalate, increasing urinary calcium and decreasing urine pH. With the increasing popularity of next-generation hypoglycemic agents, it is important to study the risk of stone formation with these newer medications. This study aims to assess the effects of various hypoglycemic agents on 24-hour urine studies in diabetic stone formers. METHODS: A retrospective review was conducted for all patients with a history of nephrolithiasis and a 24-hour urine study seen between July 2017-December 2019 for an outpatient visit. Patients with T2DM were assessed for use of hypoglycemic agents (metformin, sulfonylurea, GLP-1 agonist, DPP-4 inhibitors, SGLT-2 inhibitors, insulin), stone analysis, BMI, HbA1c, and 24-hour urine study. Two-tailed t-tests were used for mean comparison and chi square tests for stone rate comparison. RESULTS: Among the included 510 patients, 86 had T2DM (45 males, 41 females, mean age 63.6 years). Compared to the non-T2DM cohort, T2DM patients had lower urine pH (5.62 vs 6.14, p<0.00001), higher urine oxalate (41.7 vs 36.14, p=0.013) and higher UA supersaturation (1.45 vs 0.94, p<0.00001). Patients on GLP-1 agonists had greater urinary citrate than both the T2DM cohort (927.94 vs 544.59, p=0.007) and the non-T2DM cohort (566.55, p<0.0001). Between diabetic GLP-1 agonist users and non-users, there was no significant difference in BMI (non-GLP 33.1 vs GLP 35.4, p=0.34) or HbA1c (non-GLP 7.0 vs GLP 7.2, p=0.74). Though T2DM patients had higher rates of UA stones (31.7% vs 12.1%, p<0.0001), GLP-1 agonists users did not have a higher rate of UA stones compared to non-T2DM patients (18.2% vs 12.1%, p=0.54). There were no significant differences found with Metformin, sulfonylurea, DPP-4 inhibitors, SGLT-2 inhibitors, or insulin. CONCLUSIONS: T2DM is a known risk factor for nephrolithiasis, however, treatment with GLP-1 agonists may be litho-protective. The significant increase in urine citrate and reduction in UA stone formation suggests a lithoprotective effect of GLP-1 agonists independent of weight or diabetes control. Consideration should be made to recommend GLP-1 agonists to T2DM patients with nephrolithiasis. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e115 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kelley Zhao More articles by this author Brian Shkolnik More articles by this author Jennifer Lu More articles by this author Joshua Miller More articles by this author David Schulsinger More articles by this author Expand All Advertisement PDF downloadLoading ...

The Prevalence of Chronic Kidney Disease and Albuminuria in Patients With Type 1 and Type 2 Diabetes Attending a Single Centre.

Background Diabetes is the leading cause of chronic kidney disease worldwide. Diabetic kidney disease is one of the microvascular complications of diabetes and it involves changes in glomerular hemodynamics, interstitial fibrosis, and tubular atrophy. Early detection and management of Diabetic kidney disease (DKD) help to reduce morbidity and mortality. This study aims to assess the prevalence of nephropathy and albuminuria in the diabetic population attending an Irish tertiary care center. Methods Retrospective data collection and analysis of patients diagnosed with Type 1 diabetes mellitus(T1DM) and Type 2 diabetes mellitus (T2DM) through the Development and Integration of Accurate Mathematical Operations in Numerical Data-Processing (DIAMOND) database in a single Irish tertiary care center. An audit tool was used to collect patients' information including gender, age, type of diabetes, serum creatinine, urinary albumin excretion, albumin creatinine ratio (ACR), body mass index, and last available glycated hemoglobin (HbA1c). Results Out of 7394 subjects with T2DM, 3139 (42%) were identified with chronic kidney disease (CKD).There were 1866 subjects with positive ACR out of 3139 subjects with CKD in the T2DM cohort.This shows that 25% of subjects have diabetic kidney disease and 17% have CKD of undetermined etiology.In the T1DM cohort with 1166 subjects, 209 (18%) were identified with CKD.Out of these 209 subjects with CKD, 164 (14%) were ACR-positive.The prevalence of CKD and albuminuria were related to age in both T1DM and T2DM populations. Albuminuria showed a linear relationship with age in subjects with no known CKD, which shows that age causally relates to albuminuria independent of type and duration of diabetes. Conclusion CKD is more prevalent in patients with T2DM as compared to T1DM, whereas the prevalence of albuminuria is higher in the T1DM population.

Assessment of QRISK3 as a predictor of cardiovascular disease events in type 2 diabetes mellitus.

The risk of cardiovascular disease (CVD) in diabetes mellitus (DM) patients is two- to three-fold higher than in the general population. We designed a 10-year cohort trial in T2DM patients to explore the performance of QRESEARCH risk estimator version 3 (QRISK3) as a CVD risk assessment tool and compared to Framingham Risk Score (FRS). This is a single-center analysis of prospective data collected from 566 newly-diagnosed patients with type 2 DM (T2DM). The risk scores were compared to CVD development in patients with and without CVD. The risk variables of CVD were identified using univariate analysis and multivariate cox regression analysis. The number of patients classified as low risk (<10%), intermediate risk (10%-20%), and high risk (>20%) for two tools were identified and compared, as well as their sensitivity, specificity, positive and negative predictive values, and consistency (C) statistics analysis. Among the 566 individuals identified in our cohort, there were 138 (24.4%) CVD episodes. QRISK3 classified most CVD patients as high risk, with 91 (65.9%) patients. QRISK3 had a high sensitivity of 91.3% on a 10% cut-off dichotomy, but a higher specificity of 90.7% on a 20% cut-off dichotomy. With a 10% cut-off dichotomy, FRS had a higher specificity of 89.1%, but a higher sensitivity of 80.1% on a 20% cut-off dichotomy. Regardless of the cut-off dichotomy approach, the C-statistics of QRISK3 were higher than those of FRS. QRISK3 comprehensively and accurately predicted the risk of CVD events in T2DM patients, superior to FRS. In the future, we need to conduct a large-scale T2DM cohort study to verify further the ability of QRISK3 to predict CVD events.