Uric Acid Variability as a Predictive Marker of Newly Developed Cardiovascular Events in Type 2 Diabetes

Predictive value of the serum uric acid to high-density lipoprotein cholesterol ratio for culprit plaques in patients with acute coronary syndrome

BACKGROUND

Hyperuricemia and low level of high-density lipoprotein cholesterol (HDL-C) are both risk factors for coronary artery disease (CAD). The uric acid to HDL-C ratio (UHR) has recently been identified as a new inflammatory and metabolic biomarker. However, the relationship between the UHR and coronary culprit plaques has not been fully investigated in patients with acute coronary syndrome (ACS).

METHODS

A total of 346 patients with ACS were enrolled in this study. Culprit lesion characteristics were assessed by optical coherence tomography (OCT). Logistic regression and linear correlation analyses were performed to assess the association between the UHR and culprit plaques. The predictive value of the UHR was investigated by receiver operating characteristic (ROC) curve analysis.

RESULTS

The percentages of typical culprit plaques, including ruptures, erosions and thrombi, were greater in the high-UHR subgroup than those in the low-UHR subgroup. A positive relationship was also found between the UHR and diameter stenosis (r = 0.160, P = 0.003) and between the UHR and area stenosis (r = 0.145, P = 0.007). The UHR was found to be independently associated with plaque rupture, erosion and thrombus. Furthermore, ROC analysis suggested that the UHR had a better predictive value than low-density lipoprotein cholesterol.

CONCLUSIONS

An elevated UHR level was independently related to the occurrence rate of culprit plaques. The UHR is a simple and easily acquired parameter for detecting culprit plaques in patients with ACS.

The role of high fat diet on serum uric acid level among healthy male first degree relatives of type 2 diabetes mellitus

First-degree relatives (FDR) of type 2 diabetes mellitus have increased risk of developing insulin resistance-related disorders including hyperuricemia. We investigated metabolic profile and serum uric acid (SUA) metabolism in response to high-fat diet among healthy male FDR in comparison to those without family history of diabetes. A total of 30 FDR and 30 non-FDR subjects completed a 5-days-hypercaloric diet with fat added to regular daily intake. Despite similar insulin response, FDR displayed different changes in SUA compared to non-FDR subjects (0.26 ± 0.83 mg/dL vs - 0.21 ± 0.78 mg/dL, p = 0.028). In subgroup analyses stratified by body mass index and waist circumference, significant different SUA changes between FDR and non-FDR subjects were only found in obese (0.48 ± 0.87 mg/dL vs - 0.70 ± 0.71 mg/dL, p = 0.001) and centrally obese (0.59 ± 0.83 mg/dL vs - 0.55 ± 0.82 mg/dL, p = 0.011) subgroups. In multivariate analysis, visceral adiposity seemed mediating the different response in SUA metabolism between FDR and non-FDR subjects induced by short-term obesogenic diet.

Multicomponent prediction of 2-year mortality and amputation in patients with diabetic foot using a random survival forest model: Uric acid, alanine transaminase, urine protein and platelet as important predictors

The current methods for the prediction of mortality and amputation for inpatients with diabetic foot (DF) use only conventional, simple variables, which limits their performance. Here, we used a random survival forest (RSF) model and multicomponent variables to improve the prediction of mortality and amputation for these patients. We performed a retrospective cohort study of 175 inpatients with DF who were recruited between 2014 and 2021. Thirty-one predictors in six categories were considered as potential covariates. Seventy percent (n = 122) of the participants were randomly selected to constitute a training set, and 30% (n = 53) were assigned to a testing set. The RSF model was used to screen appropriate variables for their value as predictors of 2-year all-cause mortality and amputation, and a multicomponent prediction model was established. Model performance was evaluated using the area under the curve (AUC) and the Hosmer-Lemeshow test. The AUCs were compared using the Delong test. Seventeen variables were selected to predict mortality and 23 were selected to predict amputation. Uric acid and alanine transaminase were the top two most useful variables for the prediction of mortality, whereas urine protein and platelet were the top variables for the prediction of amputation. The AUCs were 0.913 and 0.851 for the prediction of mortality for the training and testing sets, respectively; and the equivalent AUCs were 0.963 and 0.893 for the prediction of amputation. There were no significant differences between the AUCs for the training and testing sets for both the mortality and amputation models. These models showed a good degree of fit. Thus, the RSF model can predict mortality and amputation in inpatients with DF. This multicomponent prediction model could help clinicians consider predictors of different dimensions to effectively prevent DF from clinical outcomes .

A study of factors influencing long-term glycemic variability in patients with type 2 diabetes: a structural equation modeling approach

Aim

The present study aims to utilize structural equation modeling (SEM) to investigate the factors impacting long-term glycemic variability among patients afflicted with type 2 diabetes.

Method

The present investigation is a retrospective cohort study that involved the collection of data on patients with type 2 diabetes mellitus who received care at a hospital located in Chengdu, Sichuan Province, over a period spanning from January 1, 2013, to October 30, 2022. Inclusion criteria required patients to have had at least three laboratory test results available. Pertinent patient-related information encompassing general demographic characteristics and biochemical indicators was gathered. Variability in the dataset was defined by standard deviation (SD) and coefficient of variation (CV), with glycosylated hemoglobin variation also considering variability score (HVS). Linear regression analysis was employed to establish the structural equation models for statistically significant influences on long-term glycemic variability. Structural equation modeling was employed to analyze effects and pathways.

Results

Diabetes outpatient special disease management, uric acid variability, mean triglyceride levels, mean total cholesterol levels, total cholesterol variability, LDL variability, baseline glycated hemoglobin, and recent glycated hemoglobin were identified as significant factors influencing long-term glycemic variability. The overall fit of the structural equation model was found to be satisfactory and it was able to capture the relationship between outpatient special disease management, biochemical indicators, and glycated hemoglobin variability. According to the total effect statistics, baseline glycated hemoglobin and total cholesterol levels exhibited the strongest impact on glycated hemoglobin variability.

Conclusion

The factors that have a significant impact on the variation of glycosylated hemoglobin include glycosylated hemoglobin itself, lipids, uric acid, and outpatient special disease management for diabetes. The identification and management of these associated factors can potentially mitigate long-term glycemic variability, thereby delaying the onset of complications and enhancing patients' quality of life.

Clinical and Pharmacotherapeutic Profile of Patients with Type 2 Diabetes Mellitus Admitted to a Hospital Emergency Department

Type 2 diabetes mellitus (T2DM) is closely associated with other pathologies, which may require complex therapeutic approaches. We aim to characterize the clinical and pharmacological profile of T2DM patients admitted to an emergency department. Patients aged ≥65 years and who were already using at least one antidiabetic drug were included in this analysis. Blood glycemia, creatinine, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and hemoglobin were analyzed for each patient, as well as personal pathological history, diagnosis(s) at admission, and antidiabetic drugs used before. Outcome variables were analyzed using Pearson's Chi-Square, Fisher's exact test, and linear regression test. In total, 420 patients were randomly selected (48.6% male and 51.4% female). Patients with family support showed a lower incidence of high glycemia at admission (p = 0.016). Higher blood creatinine levels were associated with higher blood glycemia (p = 0.005), and hyperuricemia (HU) (p = 0.001), as well as HU, was associated with a higher incidence of acute cardiovascular diseases (ACD) (p = 0.007). Hemoglobin levels are lower with age (p = 0.0001), creatinine (p = 0.009), and female gender (p = 0.03). The lower the AST/ALT ratio, the higher the glycemia at admission (p < 0.0001). Obese patients with (p = 0.021) or without (p = 0.027) concomitant dyslipidemia had a higher incidence of ACD. Insulin (p = 0.003) and glucagon-like peptide-1 agonists (GLP1 RA) (p = 0.023) were associated with a higher incidence of decompensated heart failure, while sulfonylureas (p = 0.009), metformin-associated with dipeptidyl peptidase-4 inhibitors (DPP4i) (p = 0.029) or to a sulfonylurea (p = 0.003) with a lower incidence. Metformin, in monotherapy or associated with DPP4i, was associated with a lower incidence of acute kidney injury (p = 0.017) or acute chronic kidney injury (p = 0.014). SGLT2i monotherapy (p = 0.0003), associated with metformin (p = 0.026) or with DPP4i (p = 0.007), as well as insulin and sulfonylurea association (p = 0.026), were associated with hydroelectrolytic disorders, unlike GLP1 RA (p = 0.017), DPP4i associated with insulin (p = 0.034) or with a GLP1 RA (p = 0.003). Insulin was mainly used by autonomous and institutionalized patients (p = 0.0008), while metformin (p = 0.003) and GLP1 RA (p < 0.0001) were used by autonomous patients. Sulfonylureas were mostly used by male patients (p = 0.027), while SGLT2 (p = 0.0004) and GLP1 RA (p < 0.0001) were mostly used by patients within the age group 65-85 years. Sulfonylureas (p = 0.008), insulin associated with metformin (p = 0.040) or with a sulfonylurea (p = 0.048), as well as DPP4i and sulfonylurea association (p = 0.031), were associated with higher blood glycemia. T2DM patients are characterized by great heterogeneity from a clinical point of view presenting with several associated comorbidities, so the pharmacotherapeutic approach must consider all aspects that may affect disease progression.

Lower Serum Uric Acid Levels May Lower the Incidence of Diabetic Chronic Complications in U.S. Adults Aged 40 and Over

Previous studies have generally reported the association between serum uric acid (SUA) and diabetic complications, but large-scale research exploring the above association in U.S. adults with diabetes is limited. To explore the association between SUA and chronic complications of diabetes among U.S. patients aged ≥40, we used data from the National Health and Nutrition Examination Survey 1999−2008. SUA was divided into three levels: T1 (SUA ≥ 420 μmol/L), T2 (300 ≤ SUA < 420 μmol/L), and T3 (SUA < 300 μmol/L). Binary logistic regression and restricted cubic spline analysis were applied to evaluate the association between SUA and chronic complications of diabetes. A trend test was performed as the SUA increased substantially. After full-adjusted confounding factors, patients in the T3 group had a lower risk of diabetic kidney disease, cardiovascular disease, and peripheral neuropathy compared with the T1 group, with a OR (95% CIs) of 0.33 (0.21−0.52), 0.56 (0.36−0.87), and 0.49 (0.27−0.89), respectively. The restricted cubic spline showed a significant positive relationship between SUA and cardiovascular disease and diabetic kidney disease in diabetes patients, but not peripheral neuropathy. Maintaining a SUA of less than 300 μmol/L might be protective against the risk of cardiovascular disease, diabetic kidney disease, and peripheral neuropathy other than diabetic retinopathy compared with a SUA of more than 420 μmol/L in U.S. diabetes patients aged 40 and over.

Change of serum uric acid and progression of cardiometabolic multimorbidity among middle aged and older adults: A prospective cohort study

Background

Hyperuricemia is prevalent and associated with individual cardiometabolic diseases, highlighting the potential role of serum uric acid (SUA) in the development and progression of cardiometabolic multimorbidity (CMM, the coexistence of diabetes, heart disease, or stroke). This study aimed to examine the role of SUA change in the progression of CMM.

Methods

This prospective cohort study used data from the China Health and Retirement Longitudinal Study, included 4,820 participants aged 45 years or above with three complete surveys at 2011 (baseline), 2015, and 2018. SUA level at survey 2011 and 2015 was used to measure SUA change as keeping or rising to hyperuricemia, and keeping or declining to non-hyperuricemia. CMM progression was defined as the first report of CMM or additional report of cardiometabolic diseases during survey 2015 and 2018. We used logistic regression models to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of SUA change on CMM progression.

Results

During the follow-up of around 7 years, 519 (10.8%) of the participants kept or rose to hyperuricemia from survey 2011 to 2015, and 311 (6.5%) experienced CMM progression from survey 2015 to 2018. Participants who kept or rose to hyperuricemia had 1.86 (95% CI, 1.29, 2.68) increased odds of CMM progression compared with those who kept or declined to non-hyperuricemia. Specifically, keeping or rising to hyperuricemia (vs. keeping or declining to non-hyperuricemia) was associated with 2.01 times higher odds (95% CI, 1.18, 3.43) of incident diabetes and 1.67 times higher odds (OR:1.67; 95% CI, 1.15, 2.43) of incident cardiovascular diseases following diabetes.

Conclusion

Keeping or rising to hyperuricemia was associated with CMM progression, particularly with incident cardiovascular diseases following diabetes. These findings suggest that monitoring SUA change may provide innovative insights into the prevention of CMM, especially in the secondary prevention of CMM (i.e., preventing further progression to cardiovascular diseases among patients with diabetes).

Cross-sectional and longitudinal associations between lipid accumulation product and hyperuricemia

BACKGROUND AND AIMS

Lipid accumulation product (LAP) is a novel, sex-specific, index-describing lipid over accumulation. Previous studies used baseline LAP for predicting hyperuricaemia; however, the relationship between them is unclear. We aimed to investigate the relationship between LAP and the risk of hyperuricaemia in the Central Chinese population.

METHODS AND RESULTS

This large-scale observational study comprised a cross-sectional population sample and a prospective cohort of 44,294 healthy subjects. This study examined the association between LAP and the risk of hyperuricaemia in the total sample and subgroups using multiple logistic regression analysis and multivariate cox proportional hazards model analysis. As a result, there was a dose-response relationship between LAP and the risk of hyperuricaemia. The prevalence of hyperuricaemia was 13.4% in the cross-sectional study. During 9 years of follow-up, hyperuricaemia occurred in 928 (19.8%) participants. The corresponding hazard ratios after multiple adjustments of hyperuricaemia in the second, third and fourth quartile were 1.34 (95% confidence interval [CI], 1.04-1.72), 2.01 (95% CI, 1.54-2.63), and 2.44 (95% CI, 1.80-3.30)-fold higher vs. the first quartile, respectively. Subgroup analyses showed that the association between LAP and the risk of hyperuricaemia was more pronounced in females, individuals≤49 years old and subjects with eGFR ≥60 ml/min/1.73 m².

CONCLUSION

LAP was positively related to the risk of hyperuricaemia in the Central Chinese population, particularly in women, individuals≤49 years old and adults with relatively normal renal function. These findings suggested the potential of LAP as an independent risk indicator in preventing hyperuricaemia.