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Objective We aimed to compare the association of three novel inflammatory indicators with metabolic syndrome (MetS) among Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort participants. Methods According to the International Diabetes Federation (IDF) criteria, the cohort participants were divided into the MetS(+) and MetS(−) groups. The lymphocyte to high‐density lipoprotein cholesterol (HDL‐C) ratio (LHR), high‐sensitivity C‐reactive protein (hs‐CRP) to HDL‐C ratio (HCHR) and hs‐CRP to lymphocyte ratio (HCLR) were calculated and were compared between the groups. Binary logistic regression (LR) analysis was performed to find the association of the indices with the presence of MetS among men and women. Receiver‐operating characteristic (ROC) curve analysis was used to establish cut‐off values in predicting MetS for men and women. p‐Values <0.05 were considered as statistically significant. Results Among a total of 8890 participants (5500 MetS(−) and 3390 MetS(+)), LHR, HCHR and HCLR were significantly higher in the MetS(+) group than in MetS(−) group (p < 0.001). In LR analysis, after adjusting for multiple cofounders, LHR remained an independent factor for the presence of MetS among men (OR: 1.254; 95% CI: 1.202–1.308; p < 0.001) and women (OR: 1.393; 95% CI: 1.340–1.448; p < 0.001). HCHR also remained an independent factor for the presence of MetS only in women (OR: 1.058; 95% CI: 1.043–1.073; p < 0.001). ROC curve analysis showed that LHR had the higher AUC for predicting MetS in both men (AUC: 0.627; 95% CI: 0.611–0.643; p < 0.001) and women (AUC: 0.683; 95% CI: 0.670, 0.696; p < 0.001). Conclusion This suggests that among both genders, the LHR as an inexpensive and easy‐to‐access marker has a better diagnostic performance and could be a promising alternative to the traditional expensive inflammatory markers such as hs‐CRP for the evaluation of inflammation in patients with MetS. The article is about the association of novel inflammatory markers with metabolic syndrome (MetS). we found a novel and easy‐to‐access inflammatory marker, which may be an alternative to the traditional and expensive markers such as high‐sensitivity C‐reactive protein for the evaluation of inflammation in patients with MetS.

[2] There are many inflammatory markers in essential hypertension such as C-reactive protein (CRP) (already established marker of hypertension), vascular cell adhesion molecule, and inter-cellular adhesion molecule.™ There is little evidence that confirmed the association between the levels of high-sensitivity CRP (hs-CRP) and BP indices.™ High-sensitivity CRP (hs-CRP) was initially produced in hepatocytes stimulated by interleukin-6 (IL-6) and tumor necrosis factor (TNF), which were the biomarkers of systemic inflammation. DISCUSSION Figure 1 shows a significant difference in both systolic and diastolic blood pressure, and their mean values were mean systolic blood pressure was 105.50±9.71 mm Hg, 126.61±19.38 mm Hg, and 134.52±10.68 mm Hg, and the mean diastolic blood pressure was found to be 75.0±5.23 mm Hg, 81.76±10.75 mm Hg and 87.70±7.47 mm Hg in individuals classified as underweight, normal, and overweight, obesity was a strict-exclusion criteria in our study. [8] The major pathophysiology contributing to an increase in blood pressure with age is the stiffness of large arteries secondary to arteriosclerosis, which causes an increase in the reflection of pressure waves from arterioles to heart in the reverse direction during propagation. Inflammation decreases endothelium-dependent vasodilation mediated by vasodilators such as adenosine and nitric oxide which in turn increases blood pressure.

Objective High-sensitivity C-reactive protein to HDL-C ratio (HCHR) and high-sensitivity C-reactive protein to lymphocyte count ratio (HCLR) are two novel inflammatory indicators, and heart failure (HF) is linked to chronic inflammation. This study sought to evaluate the link between HCHR, HCLR, and HF. Methods We carried out a cross-sectional investigation using the National Health and Nutrition Examination Survey (NHANES, 2015–2018). We used multivariate logistic regression to determine the association between HCHR, HCLR, and HF, followed by smoothed curve fitting and threshold effect analysis, as well as subgroup analyses of the underlying demographic variables to investigate potential impacts. The receiver operating characteristic curves were employed to examine the correlation between each index and HF. Results This study included 8751 subjects, and multivariate logistic regression after Ln conversion for HCHR and HCLR showed that subjects in the highest tertile of Ln(HCHR) had a significantly higher risk of 45% than those in the lowest tertile in the fully adjusted model 3 (OR = 1.45, 95% CI 1.02–2.07; P for trend = 0.0269), whereas subjects in the highest tertile of Ln(HCLR) had a significantly higher risk of 52% (OR = 1.52, 95% CI 1.07–2.17; P for trend = 0.0184) than those in the lowest tertile. Ln(HCHR) and HF exhibited a nonlinear relationship, with an inflection point of -2.71 and a log-likelihood ratio of 0.024. Subgroup analyses revealed no significant interactions between Ln(HCHR), Ln(HCLR), and specific subgroups (all P for interactions > 0.05). The ROC curve indicated that Ln(HCLR) had the greatest diagnostic efficacy for HF (AUC: 0.638, 95% CI 0.607–0.669), succeeded by Ln(HCHR) (AUC: 0.620, 95% CI 0.589–0.652). Conclusion Our findings indicate that Ln(HCHR) and Ln(HCLR) are positively linked with the prevalence of HF among US adults. Specifically, Ln(HCHR) levels demonstrated a nonlinear correlation with HF, featuring an inflection point at -2.71.

Background This study aimed to investigate the associations of the high-sensitivity C-reactive protein to high-density lipoprotein cholesterol ratio (HCHR) and the high-sensitivity C-reactive protein to lymphocyte ratio (HCLR) with anemia in the general population. Methods A cross-sectional analysis was conducted using data from 8638 adults enrolled in the National Health and Nutrition Examination Survey (NHANES) 2015–2018. Anemia was defined according to the World Health Organization (WHO) criteria. HCHR and HCLR were calculated based on laboratory measurements. Multivariable logistic regression models were applied to estimate the associations between HCHR, HCLR, and anemia. Subgroup analyses and smooth curve fitting were performed to assess effect modification and potential nonlinear relationships. Sensitivity analyses were also performed to assess the robustness of the results. Results Among the 8638 participants, 930 individuals had anemia. Compared with non-anemic participants, those with anemia had significantly higher median levels of HCHR ( p  < 0.001) and HCLR ( p  < 0.001). In fully adjusted models, higher HCHR (OR = 1.007, 95% CI: 1.002–1.011, p  = 0.012) and HCLR (OR = 1.027, 95% CI: 1.013–1.042, p  = 0.004) were independently associated with an increased risk of anemia. Compared with the lowest quartile, participants in the highest quartile of both HCHR and HCLR had significantly greater odds of anemia (P for trend < 0.05). Subgroup analyses confirmed the consistency of the associations between HCHR, HCLR, and anemia. Smooth curve fitting revealed nonlinear relationships between HCHR, HCLR, and anemia risk. Conclusion Higher HCHR and HCLR were significantly associated with an increased risk of anemia among U.S. adults, underscoring the potential utility of inflammation-based composite biomarkers in anemia risk stratification. Nevertheless, further prospective studies are warranted to confirm causality and evaluate clinical applicability. Clinical trial number Not applicable.

ObjectiveTo investigate the association between the high-sensitivity C-reactive protein-to-hemoglobin ratio and stroke risk among middle-aged and older adults.MethodsA prospective follow-up study was conducted using cohort data from the China Health and Retirement Longitudinal Study (CHARLS) and the English Longitudinal Study of Ageing (ELSA). Participants without a history of stroke at baseline were included, comprising 5368 individuals from CHARLS and 1422 from ELSA. Cox proportional hazards regression models were used to analyze the association between C-reactive protein-to-hemoglobin ratio levels and stroke risk, along with dose-response analyses and subgroup interaction testing.ResultsAfter adjusting for sex, age, lifestyle factors, and multiple clinical biochemical indicators, the participants in Q2, Q3, and Q4 demonstrated a significantly higher risk of stroke than those in Q1 (reference group). The hazard ratios were 2.23 (1.35-3.69), 2.24 (1.36-3.71), and 3.14 (1.93-5.12), respectively (all  < 0.01). Dose-response analysis revealed an approximately linear positive association between C-reactive protein-to-hemoglobin ratio and stroke risk.ConclusionsC-reactive protein-to-hemoglobin ratio levels are significantly and positively associated with stroke risk in middle-aged and older adults.

High‐sensitivity C‐reactive protein (hs‐CRP) and lipoprotein‐associated phospholipase A2 (Lp‐PLA2) have been reported to be independent predictors of atherosclerosis. However, whether the combination of these two markers can improve the prediction of atherosclerosis is unknown. This study aimed to evaluate the association between combining hs‐CRP and Lp‐PLA2 and predicting carotid atherosclerosis. A total of 1982 participants aged ≥40 years were included in this study. Hs‐CRP and Lp‐PLA2 were measured by a high‐sensitivity nephelometry assay and quantitative sandwich enzyme‐linked immunosorbent assay, respectively. Ultrasonography was performed on the bilateral carotid arteries to evaluate stenosis and plaques. Multivariable logistic regression models were used to analyse the association between the combination of the hs‐CRP and Lp‐PLA2 levels and carotid plaques and stenosis. A total of 1579 (79.7%) and 181 (9.1%) subjects had carotid plaques and carotid stenosis, respectively. The group with high hs‐CRP and Lp‐PLA2 levels had the highest prevalence of carotid plaques (90.6%) and stenosis (20.8%). A significant association was found between high hs‐CRP and Lp‐PLA2 levels and carotid stenosis (adjusted odds ratio [OR]: 2.39; 95% confidence interval [CI]: 1.13‐5.09), but this combination was not associated with carotid plaques (OR: 2.62, 95% CI: 0.93‐7.38). The results suggested that the combination of hs‐CRP and Lp‐PLA2 were better predictors than either protein alone with regard to carotid atherosclerosis.

Background The triglyceride–glucose (TyG) index and high‐sensitivity C‐reactive protein (hsCRP) are the commonly used biomarkers for insulin resistance and systemic inflammation, respectively. We aimed to investigate the combined association of TyG and hsCRP with the major adverse cardiovascular events (MACE) in patients with chronic coronary syndrome (CCS). Methods A total of 9421 patients with CCS were included in this study. The primary endpoint was defined as a composite of MACE covering all‐cause death, nonfatal myocardial infarction, and revascularization. Results During the 2‐year follow‐up period, 660 (7.0%) cases of MACE were recorded. Participants were divided equally into three groups according to TyG levels. Compared with the TyG T1 group, the risk of MACE was significantly higher in the TyG T3 group. It is noteworthy that among patients in the highest tertile of TyG, hsCRP >3 mg/L was significantly associated with an increased risk of MACE, whereas the results were not significant in the medium to low TyG groups. When patients were divided into six groups according to hsCRP and TyG, the Cox regression analysis showed that patients in the TyG T3 and hsCRP >3 mg/L group had a significantly higher risk of MACE than those in the TyG T1 and hsCRP ≤3 mg/L group. However, no significant interaction was found between TyG and hsCRP on the risk of MACE. Conclusion Our study suggests that the concurrent assessment of TyG and hsCRP may be valuable in identifying high‐risk populations and guiding management strategies among CCS patients. Highlights A large‐scale study investigating the joint prognostic effect of TyG and hsCRP in patients with CCS. Patients with CCS who exhibit elevated levels of both TyG and hsCRP are at the highest risk of MACE. Simultaneous assessment of TyG and hsCRP may be valuable in identifying the high‐risk populations and guiding management strategies among patients with CCS.

Background Small dense low‐density lipoprotein cholesterol (sdLDL‐C) is a more significant atherosclerotic factor than LDL‐C. This investigation aimed to examine the correlation between sdLDL‐C levels and the risk of cardiometabolic multimorbidity (CMM) in middle‐aged and older adults. Methods Participants aged ≥ 45 years who did not have CMM at baseline from the China Health and Retirement Longitudinal Study (CHARLS) data set were included in this cohort study. The baseline data of the participants were collected in 2011 and followed up until 2020. sdLDL‐C is calculated using a validated formula. The relationship of sdLDL‐C with CMM risk was examined using Cox regression analyses. The combined effect of high‐sensitivity C‐reactive protein (hsCRP) and sdLDL‐C on CMM risk was explored. Results A total of 9616 participants were included, of whom 1814 (18.86%) had CMM and 7802 (81.14%) did not have CMM. Elevated sdLDL‐C levels were correlated with a higher risk of CMM (HR [95% CI] = 1.10 [1.04−1.15]). The interaction terms for sdLDL‐C and hsCRP presented that participants in the low sdLDL‐C and high hsCRP group (HR [95% CI] = 1.21 [1.03‐1.41]), the high sdLDL‐C and low hsCRP group (HR [95% CI] = 1.21 [1.08−1.36]), and the high sdLDL‐C and high hsCRP group (HR [95% CI] = 1.36 [1.15−1.62]) had a higher risk of CMM versus the low sdLDL‐C and low hsCRP group, and the trend for these interaction terms was significant (Ptrend = 0.031). Conclusion Elevated sdLDL‐C levels were related to an increased risk of CMM, and there was an interaction between sdLDL‐C and hsCRP on the increased risk of CMM. Elevated small dense low‐density lipoprotein cholesterol (sdLDL‐C) levels were associated with a higher risk of cardiometabolic multimorbidity (CMM). There was an interaction between sdLDL‐C and high‐sensitivity C‐reactive protein (hsCRP) on the increased risk of CMM.

Background Earlier studies showed a negative correlation between life's simple 7 (LS7) and high‐sensitivity C‐reactive protein (hs‐CRP), but no association has been found between life's essential 8 (LE8), an improved version of LS7, and hs‐CRP. Hypothesis This study investigated the association between LE8 and hs‐CRP utilizing data from the National Health and Nutritional Examination Survey. Methods A total of 7229 adults were incorporated in our study. LE8 was scored according to American Heart Association guidelines, and LE8 was divided into health behaviors and health factors. Serum samples of the participants were used to measure hs‐CRP. To investigate the association between LE8 and hs‐CRP, weighted linear regression, and restricted cubic spline were utilized. Results Among 7229 participants, the average age was 48.03 ± 16.88 years, 3689 (51.2%) were females and the median hs‐CRP was 1.92 (0.81−4.49) mg/L. In adjusted weighted linear regression, a negative correlation was observed between the LE8 score and hs‐CRP. Compared with the low LE8 score, the moderate LE8 score β was −0.533 (−0.646 to −0.420), and the high LE8 score β was −1.237 (−1.376 to −1.097). Health behaviors and health factors were also negatively associated with hs‐CRP. In stratified analyses, the negative correlation between LE8 and hs‐CRP remained consistent across subgroups. Conclusion There was a negative correlation between LE8 as well as its sub‐indicator scores and hs‐CRP. Maintaining a positive LE8 score may be conducive to lowering the level of hs‐CRP. The results of this study showed a negative correlation between life's essential 8 (LE8) and high‐sensitivity C‐reactive protein (hs‐CRP), and a stronger association between health factors and hs‐CRP than health behaviors.

Background This retrospective cohort study investigated the joint prognostic value of the triglyceride glucose-body mass index (TyG-BMI) and high-sensitivity C-reactive protein (hsCRP) for post-PCI adverse outcomes in patients with chronic coronary syndromes (CCS) undergoing percutaneous coronary intervention (PCI). Methods A total of 2274 patients were enrolled and categorized into TyG-BMI tertiles (T1-T3), and were further stratified by hsCRP levels (≤ 3 vs. > 3 mg/L). The primary endpoint was a composite of repeat revascularization or in-stent restenosis (ISR). Cox regression, restricted cubic spline, joint stratification, interaction, sensitivity, and time-specific analyses were performed, including an analysis censored at 12 months and a 1-year landmark analysis. Results Over a median follow-up of 60.5 months, 1054 patients (46.4%) experienced the primary endpoint. Each 100-unit increase in TyG-BMI was associated with a 30.8% higher risk of the composite endpoint (adjusted HR 1.308, 95% CI 1.106–1.546; P  = 0.002), with a linear association observed across the TyG-BMI range. Compared with T1, patients in T3 had a significantly higher risk of the composite endpoint (adjusted HR 1.263, 95% CI 1.086–1.468; P  = 0.002). In cross-stratified analyses, hsCRP > 3 mg/L was associated with a higher risk only in the T3 group (adjusted HR 1.325, 95% CI 1.082–1.623; P  = 0.006). Compared with patients in TyG-BMI T1 and hsCRP ≤ 3 mg/L, those in TyG-BMI T3 and hsCRP > 3 mg/L had a 52.3% higher risk of the composite endpoint (adjusted HR 1.523, 95% CI 1.239–1.872; P  < 0.001). No significant multiplicative or additive interaction between TyG-BMI and hsCRP was detected. In time-specific analyses, this combined high-risk subgroup showed a modest association with events within the first year after PCI, whereas in the 1-year landmark analysis it remained at the highest risk of the composite endpoint beyond 1 year (adjusted HR 1.569, 95% CI 1.218–2.021; P  < 0.001). Conclusion Concurrent elevation of TyG-BMI and hsCRP identifies a subgroup of CCS patients at particularly high risk of repeat revascularization or ISR after PCI. Combined assessment of these two markers may provide complementary prognostic information after PCI, particularly for identifying longer-term residual risk.