Threshold-modifying effect of the systemic inflammatory response index on kidney function decline in hypertensive patients.

BACKGROUND: Chronic kidney disease (decreased kidney function) is common in hypertensive patients. The SIRI is a novel immune biomarker. We investigated the correlation between the SIRI and kidney function in hypertensive patients. METHODS: The present study analyzed data from participants who suffered from hypertension in the NHANES from 2009 to 2018. Multivariate regression analysis and subgroup analysis were used to clarify whether the SIRI was an independent risk factor for decreased kidney function. RCSs were utilized to evaluate the correlation between the SIRI and the eGFR and between the SIRI and the ACR. In addition, we modeled the mediating effect of the SIRI on the eGFR and the ACR using blood pressure as a mediating variable. RESULTS: The highest SIRI was an independent risk factor for a decreased eGFR [odds ratio (OR) = 1.46, 95% CI (1.15, 1.86)] and an increased ACR [OR = 2.26, 95% CI (1.82, 2.82)] when the lowest quartile was used as the reference. The RCS results indicated an inverted U-shaped relationship between the SIRI and the eGFR and between the SIRI and the ACR (the inflection points were 1.86 and 3.09, respectively). The mediation effect analysis revealed that the SIRI was the main factor influencing kidney function, and diastolic blood pressure was a mediating variable. In particular, there was a fully mediating effect between the SIRI and UCr, with a mediating effect value of -0.61 (-0.90, -0.36). CONCLUSIONS: The association between the SIRI and renal function in hypertensive patients was significant and was particularly dominated by the association between the SIRI and the ACR. This difference may be due to the mediating effect of diastolic blood pressure.

Risk analysis of the association between different hemoglobin glycation index and poor prognosis in critical patients with coronary heart disease-A study based on the MIMIC-IV database.

BACKGROUND: The hemoglobin glycation index (HGI) is the difference between the observed and predicted values of glycosylated hemoglobin (HbA1c), which is closely associated with a variety of poor prognoses. However, there are still no studies on the correlation between HGI and poor prognosis in patients with critical coronary artery disease. The purpose of this study was to analyze the correlation between HGI and all-cause mortality in patients with critical coronary artery disease using the MIMIC-IV database. METHODS: The HGI was calculated by constructing a linear regression equation between HbA1c and fasting plasma glucose (FPG). A Kaplan‒Meier survival analysis model was constructed based on the HGI quartiles to clarify the differences in all-cause mortality rates between groups, and the log-rank test was used to assess the differences between groups. The hazard ratio (HR) of HGI as a risk factor for outcome events was assessed using the Cox proportional risk model and restricted cubic spline (RCS), with the Q2 group serving as the reference group. RESULTS: A total of 5260 patients were included in this study. The 30-day mortality rate of the patients was 4.94% and the mortality rate within 365 days was 13.12%. A low HGI was significantly associated with 30-day mortality (HR, 1.96; 95% CI, (1.38, 2.78); P < 0.001) and 365-day mortality (HR, 1.48; 95% CI, (1.19, 1.85); P < 0.001) in patients with critical coronary artery disease in the completely adjusted Cox proportional risk model. In addition, high levels of HGI were associated with 365-day mortality (HR, 1.31; 95% CI, (1.02, 1.69); P < 0.05). RCS analysis revealed a U-shaped relationship between HGI and outcome events. According to the stratified analysis, the interaction test revealed that the correlation between HGI and outcome events remained stable. CONCLUSION: There was a significant correlation between HGI and all-cause mortality in patients with critical coronary artery disease, particularly in those with low HGI. HGI can be used as a potential indicator for assessing the short- and long-term risk of mortality in such patients.

The optimal QTc selection in patients of acute myocardial infarction with poor perioperative prognosis.

BACKGROUND: The predictive utility of QTc values, calculated through various correction formulas for the incidence of postoperative major adverse cardiovascular and cerebrovascular events (MACCE) in patients experiencing acute myocardial infarction (AMI), warrants further exploration. This study endeavors to ascertain the predictive accuracy of disparate QTc values for MACCE occurrences in patients with perioperative AMI. METHODS: A retrospective cohort of three hundred fourteen AMI patients, comprising 81 instances of in-hospital MACCE and 233 controls, was assembled, with comprehensive collection of baseline demographic and clinical data. QTc values were derived employing the correction formulas of Bazett, Fridericia, Hodges, Ashman, Framingham, Schlamowitz, Dmitrienko, Rautaharju, and Sarma. Analytical methods encompassed comparative statistics, Spearman correlation analysis, binary logistic regression models, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). RESULTS: QTc values were significantly elevated in the MACCE cohort compared to controls (P < 0.05). Spearman's correlation analysis between heart rate and QTc revealed a modest positive correlation for the Sarma formula (QTcBaz) (ρ = 0.46, P < 0.001). Within the multifactorial binary logistic regression, each QTc variant emerged as an independent risk factor for MACCE, with the Sarma formula-derived QTc (QTcSar) presenting the highest hazard ratio (OR = 1.025). ROC curve analysis identified QTcSar with a threshold of 446 ms as yielding the superior predictive capacity (AUC = 0.734), demonstrating a sensitivity of 60.5% and a specificity of 82.8%. DCA indicated positive net benefits for QTcSar at high-risk thresholds ranging from 0 to 0.66 and 0.71-0.96, with QTcBaz, prevalent in clinical settings, showing positive net benefits at thresholds extending to 0-0.99. CONCLUSION: For perioperative AMI patients, QTcSar proves more advantageous in monitoring QTc intervals compared to alternative QT correction formulas, offering enhanced predictive prowess for subsequent MACCE incidents.