C-reactive protein-to-albumin ratio and 8-year incidence of type 2 diabetes: the Korean genome and epidemiology study

Associations Between Clinical Inflammatory Risk Markers, Body Composition, Heart Rate Variability, and Accelerometer-Assessed Physical Activity in University Students with Overweight and Obesity

This cross-sectional study aimed to identify associations between clinical inflammatory risk markers, body composition, heart rate variability (HRV), and self-reported and objectively assessed physical activity (PA) in university students with overweight and obesity. Seventeen participants (eight females) completed a screening visit following a randomized controlled four-arm crossover trial period with 8 h of uninterrupted prolonged sitting, alternate sitting and standing, continuous standing, and continuous slow walking, respectively. Clinical inflammatory risk markers were obtained from venous blood samples, and PA was assessed using the International Physical Activity Questionnaire (IPAQ-SF) and ActiGraph wGT3X-BT accelerometers. HRV was recorded over 24 h using the Faros 180 Holter electrocardiogram (ECG). White blood cell (WBC) counts were significantly correlated with fat mass (FM; p = 0.03) and visceral adipose tissue (VAT; p = 0.04) and inversely correlated with moderate PA (p = 0.02). Light-intensity PA (LIPA) and moderate-to-vigorous PA (MVPA) were correlated with HRV parameters (p = 0.02), and LIPA was inversely correlated with interleukin-6 (p = 0.003) and c-reactive protein (p = 0.04) during different trial conditions. In university students with overweight and obesity, higher values of FM were negatively correlated with WBC count, and integrating LIPA and MVPA in the students' daily life strengthened their sympathetic-parasympathetic regulation and positively mediated anti-inflammatory mechanisms.

C-reactive protein to albumin ratio and risk of incident metabolic syndrome in community-dwelling adults: longitudinal findings over a 12-year follow-up period

AIM

The C-reactive protein to albumin (CRP/Alb) ratio has emerged as a novel biomarker for various inflammatory diseases. This study aimed to evaluate the association between the CRP/Alb ratio and incident metabolic syndrome (MetS) with a large-sample, community-based Korean cohort over a 12-year follow-up period.

MATERIALS AND METHODS

Among 10,030 participants, a total of 6205 participants aged 40-69 years without MetS were selected from the Korean Genome and Epidemiology Study (KoGES). The baseline CRP/Alb ratio was divided into quartiles. The definition of newly developed MetS was the one proposed by the 2009 Joint Interim Statement of Circulation. Hazard ratios (HRs) with 95% confidence intervals (CIs) for incident MetS were calculated using multivariable Cox proportional hazards regression models after adjusting for potentially confounding variables.

RESULTS

During the 12-year follow-up period, MetS developed in 2535 subjects (40.9%, 2535/6205) with an incidence rate of 5.6-11.9 (over 2 years). Compared to the reference first quartiles, the HRs (95% CIs) of incident MetS in the second, third, and fourth quartiles increased in a dose-response manner. Compared to the reference quartile, the HRs (95% CIs) of the incidence of MetS for the second, third, and fourth quartiles of CRP/Alb ratio were 1.12 (0.99-1.27), 1.24 (1.11-1.40), and 1.51 (1.34-1.69) after adjusting for age, sex, smoking status, alcohol intake, physical activity, total cholesterol, mean arterial pressure, HOMA-IR, and total energy intake.

CONCLUSIONS

High CRP/Alb ratio at baseline may be a useful surrogate indicator of future incident MetS.

Association Between Different Inflammatory Markers and Generalized Abdominal Obesity: A Cross-Sectional Study

PURPOSE

Inflammation is strongly correlated with obesity. However, very few studies have reported associations between novel inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), C-reactive protein (CRP), and C-reactive protein-to-albumin ratio (CAR), and different obesity types. Therefore, this study aimed to explore the associations of these inflammatory markers with generalized and abdominal obesity.

MATERIALS AND METHODS

This cross-sectional study included data from 2015 to 2018 obtained from the National Health and Nutrition Examination Survey. Multivariate regression analysis was performed to determine the associations between different inflammatory biomarkers and obesity. The discriminative capacities of the markers for obesity types were depicted using receiver operating characteristic (ROC) curves, with corresponding area under the curve (AUC) metrics quantifying this discrimination.

RESULTS

After adjusting for confounding variables, generalized obesity was found to be positively associated with an increased risk of NLR by 35%, SII by 52%, CRP by 941%, and CAR by 925%, compared with the reference groups. In the model, the CRP concentration and CAR demonstrated high AUC values of 0.690 and 0.889, respectively, for the identification of generalized and abdominal obesity (P < 0.05).

CONCLUSION

This study revealed associations between obesity and inflammatory biomarkers, such as the NLR, SII, CRP, and CAR. CRP is the most sensitive marker for generalized obesity, while CAR shows the strongest association with abdominal obesity. These findings suggest that inflammatory biomarkers may be useful for assessing and managing obesity-related health concerns.

High C-Reactive Protein/ Albumin Ratio Predicts Mortality and Hemorrhage in Stroke Patients Undergoing Mechanical Thrombectomy: A Systematic Review and Meta-Analysis

BACKGROUND

Stroke outcomes are multifactorial, and the C-Reactive Protein to Albumin Ratio (CAR) has emerged as a potential prognostic marker. This study aims to evaluate CAR prognostic significance in stroke.

METHODS

Systematic searches across ScienceDirect, Medline, and Cochrane databases identified longitudinal studies. Unfavorable outcomes, including poor prognosis (modified rankin scale> 2), mortality, and severe complications like hemorrhage or restenosis, were considered. Analyses for unfavorable outcomes were conducted based on prior intervention, stroke type, and outcome type.

RESULTS

The meta-analysis included 12 cohort studies comprising 5042 participants. Elevated CAR (OR: 1.72; 95% confidence interval [CI]: 1.17-2.52; P = 0.01) and CRP (OR: 1.91; 95% CI: 1.31-2.77; P < 0.001) levels on admission were associated with unfavorable outcomes; no such association was observed for albumin (OR: 0.66; 95%CI: 0.24-1.80; P = 0.42). Elevated CAR levels were associated with unfavorable outcomes in patients undergoing mechanical thrombectomy (odds ratio [OR]: 2.70; 95% CI: 1.14-6.38; P < 0.02) and those with ischemic stroke (OR: 1.99; 95% CI: 1.24-3.18; P < 0.001), but no significant association was found in patients with hemorrhagic stroke. Furthermore, concerning specific outcomes, high CAR levels were associated with mortality (OR: 1.71; 95% CI: 1.00-2.95; P = 0.05) and hemorrhage (OR: 6.02; 95% CI: 1.61-23.87; P = 0.05). The area under the curve for CAR was 0.72 (0.68-0.76), with a sensitivity of 0.61 (0.49-0.71) and specificity of 0.73 (0.64-0.81).

CONCLUSIONS

Elevated CAR emerges as an effective marker in assessing unfavorable outcomes in stroke patients with moderately high sensitivity and specificity. High CAR levels exhibited statistically significant mortality and hemorrhage in stroke patients undergoing mechanical thrombectomy.

Investigating Neutrophil-to-Lymphocyte and C-Reactive Protein-to-Albumin Ratios in Type 2 Diabetic Patients with Dry Eye Disease

BACKGROUND

Patients with Diabetes mellitus (DM) are at risk of developing dry eye disease (DED). We investigated routine laboratory parameters in patients with type 2 DM (T2D) and T2D-DED to identify potential inflammatory markers.

METHODS

A retrospective study of 241 randomly selected patients (30 DED non-diabetic, 120 T2D, and 91 with T2D-DED). The neutrophil-to-lymphocyte ratios (NLR), CRP-to-albumin ratios (CAR), and the glycosylated haemoglobin A1c (HbA1c) results were correlated between groups.

RESULTS

The NLR and HbA1c were significantly higher in the T2D-DED group (p≤0.001 and 0.0001, respectively) when compared with T2D and DED non-diabetic groups. CAR was insignificantly high in the three groups (p=0.192). A positive correlation was identified between CAR and NLR in T2D-DED patients (p= 0.008).

CONCLUSION

In T2D-DED patients, NLR was significantly high and positively correlate with CAR. These results predicate diabetes with dry eye complications, and biomarker-mediated inflammation may have important roles in DED pathogenesis.

A scoping review of artificial intelligence-based methods for diabetes risk prediction

The increasing prevalence of type 2 diabetes mellitus (T2DM) and its associated health complications highlight the need to develop predictive models for early diagnosis and intervention. While many artificial intelligence (AI) models for T2DM risk prediction have emerged, a comprehensive review of their advancements and challenges is currently lacking. This scoping review maps out the existing literature on AI-based models for T2DM prediction, adhering to the PRISMA extension for Scoping Reviews guidelines. A systematic search of longitudinal studies was conducted across four databases, including PubMed, Scopus, IEEE-Xplore, and Google Scholar. Forty studies that met our inclusion criteria were reviewed. Classical machine learning (ML) models dominated these studies, with electronic health records (EHR) being the predominant data modality, followed by multi-omics, while medical imaging was the least utilized. Most studies employed unimodal AI models, with only ten adopting multimodal approaches. Both unimodal and multimodal models showed promising results, with the latter being superior. Almost all studies performed internal validation, but only five conducted external validation. Most studies utilized the area under the curve (AUC) for discrimination measures. Notably, only five studies provided insights into the calibration of their models. Half of the studies used interpretability methods to identify key risk predictors revealed by their models. Although a minority highlighted novel risk predictors, the majority reported commonly known ones. Our review provides valuable insights into the current state and limitations of AI-based models for T2DM prediction and highlights the challenges associated with their development and clinical integration.

Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10^-2). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10^-3). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10^-2). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.

Interleukin-6-to-Albumin Ratio as a Superior Predictor of Mortality in End-Stage Kidney Disease Patients

INTRODUCTION

In patients with chronic kidney disease (CKD), high interleukin-6 (IL-6) and low albumin circulating concentrations are associated with worse outcomes. We examined the IL-6-to-albumin ratio (IAR) as a predictor of risk of death in incident dialysis patients.

METHODS

In 428 incident dialysis patients (median age 56 years, 62% men, 31% diabetes mellitus, 38% cardiovascular disease [CVD]), plasma IL-6 and albumin were measured at baseline to calculate IAR. We compared the discrimination of IAR with other risk factors for predicting 60-month mortality using receiver operating characteristic curve (ROC) and analyzed the association of IAR with mortality using Cox regression analysis. We divided patients into IAR tertiles and analyzed: (1) cumulative incidence of mortality and the association of IAR with mortality risk in Fine-Gray analysis, taking kidney transplantation as competing risk and (2) the restricted mean survival time (RMST) to 60-month mortality and differences of RMST (∆RMST) between IAR tertiles to describe quantitative differences of survival time.

RESULTS

For all-cause mortality, the area under the ROC curve (AUC) for IAR was 0.700, which was greater than for IL-6 and albumin separately, while for CV mortality, the AUC for IAR (0.658) showed negligible improvement over IL-6 and albumin separately. In Cox regression analysis, IAR was significantly associated with all-cause mortality but not with CV mortality. Both high versus low and middle versus low tertiles of IAR associated with higher risk of all-cause mortality, subdistribution hazard ratio of 2.22 (95% CI 1.40-3.52) and 1.85 (95% CI 1.16-2.95), respectively, after adjusting for age, sex, diabetes mellitus, CVD, smoking, and estimated glomerular filtration rate. ∆RMST at 60 months showed significantly shorter survival time in middle and high IAR tertiles compared with low IAR tertile for all-cause mortality.

CONCLUSIONS

Higher IAR was independently associated with significantly higher all-cause mortality risk in incident dialysis patients. These results suggest that IAR may provide useful prognostic information in patients with CKD.

A novel inflammatory biomarker, high-sensitivity C-reactive protein-to-albumin ratio, is associated with 5-year outcomes in patients with type 2 diabetes who undergo percutaneous coronary intervention

BACKGROUND

Patients with coronary artery disease (CAD) combined with diabetes have a higher risk of cardiovascular events, and high-sensitivity C-reactive protein (hs-CRP)-to-albumin ratio (CAR) is a novel inflammatory biomarker. However, whether the CAR can identify high-risk patients with CAD and type 2 diabetes (T2DM) remains unclear.

METHODS

The present study was based on a prospective and observational cohort with 10,724 individuals who undergo percutaneous coronary intervention (PCI) in Fu Wai Hospital throughout the year 2013 consecutively enrolled. The primary endpoint was all-cause mortality. The secondary endpoint was cardiac mortality. CAR was calculated with the formula: hs-CRP (mg/L)/albumin (g/L). According to the optimal cut-off value of CAR for all-cause mortality, patients were divided into higher CAR (CAR-H) and lower CAR (CAR-L) groups.

RESULTS

A total of 2755 patients with T2DM who underwent PCI and received dual antiplatelet therapy were finally enrolled. During a follow-up of 5 years (interquartile range: 5.0-5.1 years), 126 (4.6%) all-cause mortalities and 74 (2.7%) cardiac mortalities were recorded. In the multivariable Cox model, CAR-H was associated with a higher risk of all-cause mortality (hazard ratio [HR]: 1.634, 95% confidence interval [CI] 1.121-2.380, p = 0.011) and cardiac mortality (HR: 1.733, 95% CI 1.059-2.835, p = 0.029) compared with CAR-L. When comparing the predictive value, CAR was superior to hs-CRP for all-cause mortality (area under the curve [AUC] 0.588 vs. 0.580, p = 0.002) and cardiac mortality (AUC 0.602 vs. 0.593, p = 0.004).

CONCLUSION

In this real-world cohort study, a higher level of CAR was associated with worse 5-year outcomes among diabetic patients with PCI.

The Novel Predictive Biomarkers for Type 2 Diabetes Mellitus in Active Pulmonary Tuberculosis Patients

Purpose

This study was to explore the predictive value of monocyte to high-density lipoprotein cholesterol ratio (MHR), neutrophils to high-density lipoprotein cholesterol ratio (NHR), C-reactive protein-to-lymphocyte ratio (CLR), and C-reactive protein-to-albumin ratio (CAR) for type 2 diabetes mellitus (T2DM) in patients with active pulmonary tuberculosis (APTB).

Patients and Methods

A total of 991 active pulmonary tuberculosis (APTB) patients (201 with T2DM) were hospitalized in the Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology were included. The routine blood examination indicators and biochemical parameters were collected to calculate MHR, NHR, CLR, and CAR. The Pearson correlation analysis, Univariate Logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of MHR, NHR, CLR, and CAR for APTB-T2DM patients.

Results

The levels of MHR, NHR, CLR, and CAR in the APTB-T2DM patients were significantly higher than in the APTB-no T2DM patients (P < 0.05). Additionally, the MHR, NHR, CLR, and CAR have a positive correlation with fasting blood glucose in the whole study population. However, in the APTB-T2DM patients, MHR, NHR, and CAR were not correlated with fasting blood glucose, and only CLR was positively correlated with fasting blood glucose. The area under curve (AUC) predicting APTB-T2DM patients of the MHR, NHR, CLR, and CAR was 0.632, 0.72, 0.715, and 0.713, respectively. Further, univariate logistic regression analyses showed that the higher MHR, NHR, CLR, and CAR were independent risk factors for APTB-T2DM (P < 0.01). The MHR, NHR, CLR, and CAR quartiles were used to divide the APTB patients into four groups for further analysis. The prevalence of T2DM was significantly higher in APTB individuals as MHR, NHR, CLR, and CAR values increased (P < 0.05).

Conclusion

MHR, NHR, CLR, and CAR are simple and practicable inflammatory parameters that could be used for assessing T2DM in APTB. APTB patients have a greater possibility to be diagnosed with T2DM with the higher MHR, NHR CLR, and CAR values. Therefore, more attention should be given to the indicator in the examination of APTB.