Objective To investigate the correlation between the uric acid to high-density lipoprotein cholesterol ratio (UHR) and the presence of atherosclerotic stenosis in both intracranial and extracranial arteries among patients who have experienced cerebral infarction. Methods Patients with cerebral infarction admitted to the Department of Neurology of Sichuan Provincial People’s Hospital between January 2021 and June 2024 were retrospective selected. According to the digital subtraction angiography (DSA) performance, patients were divided into cerebral atherosclerotic stenosis group and no cerebral atherosclerotic stenosis group. According to the location of atherosclerotic stenosis, patients were divided into extracranial atherosclerotic stenosis group, intracranial atherosclerotic stenosis group, intracranial and extracranial atherosclerotic stenosis group. According to the severity of atherosclerotic stenosis, patients were divided into mild group, moderate group and severe group. Clinical data and laboratory indicators were collected. Multifactorial regression was used to analyze the risk factors, Spearman correlation analysis was used to evaluate the relationship between UHR and the degree of stenosis, and the predictive value of UHR for intracranial and extracranial atherosclerotic stenosis was analyzed by the receiver operating characteristic curve. Results A total of 388 patients were included. Among them, 291 cases in cerebral atherosclerotic stenosis group and 97 cases in no cerebral atherosclerotic stenosis group; 85 cases in the intracranial atherosclerotic stenosis group, 123 cases in the extracranial atherosclerotic stenosis group, and 83 cases in the intracranial and extracranial atherosclerotic stenosis group; There were 104 cases in the mild group, 81 cases in the moderate group, and 106 cases in the severe group. The results of multiple logistic regression analysis showed that age, hypertension, UHR and uric acid were independent influencing factors associated with atherosclerotic stenosis of intracranial and extracranial arteries. Furthermore, the uric acid and UHR were also risk factors for the degree of stenosis (P<0.05). Spearman correlation analysis results showed that UHR was positively correlated with the degree of stenosis (r=0.516, P < 0.001). Receiver operating characteristic curve showed that the predictive value of UHR (area under the curve was 0.724) was superior to that of uric acid (area under the curve was 0.638) or HDL-C (area under the curve was 0.709). It also showed good predictive value for stenosis in different locations of intracranial and extracranial arteries. Conclusion UHR is an independent risk factor for intracranial and extracranial atherosclerotic stenosis with notabla predictive value
Objective To identify independent risk factors for in-hospital all-cause mortality in patients with sepsis and to integrate them into the quick Sequential Organ Failure Assessment (qSOFA) score to construct modified models, thereby improving the ability of the original qSOFA to predict mortality risk. Methods This retrospective study included adult patients who met the Sepsis-3 criteria for sepsis and were admitted to the Intensive Care Unit or Emergency Intensive Care Unit of Zigong Fourth People’ s Hospital between January 2018 and December 2023. Demographic characteristics, vital signs, comorbidities, and laboratory parameters were collected, and the Sequential Organ Failure Assessment (SOFA) and qSOFA scores were calculated. Multivariable logistic regression analysis was used to identify independent predictors of in-hospital mortality. Independent predictors were dichotomized according to cut-off values derived from receiver operating characteristic (ROC) curves and combined with qSOFA to construct new models. The ROC analysis with bootstrap validation was used to assess predictive performance, and comparative performance was further evaluated using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results A total of 218 patients were included. Multivariable logistic regression analysis identified blood urea nitrogen (BUN) [odds ratio (OR)=1.100, 95% confidence interval (CI) (1.040, 1.170)] and qSOFA [OR=2.610, 95%CI (1.450, 4.920)] as independent risk factors for in-hospital mortality, whereas high-density lipoprotein cholesterol (HDL-C) was an independent protective factor [OR=0.250, 95%CI (0.065, 0.841)]. After dichotomization by ROC-derived cut-off values, BUN and HDL-C were incorporated into qSOFA to generate B-qSOFA, H-qSOFA, and BH-qSOFA. Bootstrap ROC analysis showed that BH-qSOFA exhibited the highest discriminatory ability compared with all combined models as well as the conventional SOFA and qSOFA scores [area under the curve=0.803, 95%CI (0.735, 0.863)]. NRI and IDI analyses demonstrated that BH-qSOFA provided incremental prognostic improvement over qSOFA (NRI=0.969, IDI=0.165), B-qSOFA (NRI=0.644, IDI=0.054), and H-qSOFA (NRI=0.804, IDI=0.091) (all P<0.05). Conclusions Elevated BUN and qSOFA and decreased HDL-C are independent predictors of in-hospital mortality in sepsis. The BH-qSOFA model is simple and clinically practical, exhibits superior predictive performance over the original qSOFA. It may serve as a useful early instrument for prognostic risk stratification in patients with sepsis.
Objective To examine the associations of cumulative serum uric acid to high-density lipoprotein cholesterol ratio (cumUHR) and the trajectories of uric acid to high-density lipoprotein cholesterol ratio (UHR) with the risk of new-onset cardiometabolic multimorbidity (CMM) in middle-aged and older Chinese adults. Methods This study utilized data from the China Health and Retirement Longitudinal Study. A total of 2597 participants who were not diagnosed with CMM at baseline were included. First, K-means clustering analysis was applied to identify UHR trajectories over the 2012–2015 period. In addition, multivariable logistic regression models were used to assess the associations of cumUHR and UHR trajectories with CMM risk. Restricted cubic spline (RCS) model was performed to explore the dose-response relationship between cumUHR and CMM risk. Moreover, subgroup analyses and interaction tests were conducted to examine potential effect modifications by age and sex, etc. Finally, the predictive performance of cumUHR and UHR trajectories for CMM was assessed using receiver operating characteristic (ROC) curve analysis. Results The cumulative incidence of CMM was 3.31%, with 86 cases developing during the follow-up period until 2020. K-means clustering identified three groups of cumUHR trajectories. Multivariable logistic regression found a significant positive association between cumUHR and CMM risk [odds ratio (OR)=43.41, 95% confidence interval (CI) (4.32, 412.06), P=0.001]. Compared to the low-stable trajectory group, individuals in the sustained-high trajectory group had a significantly higher risk of developing CMM [OR=2.48, 95%CI (1.22, 4.99), P=0.011]. RCS analysis demonstrated a linear dose-response relationship between cumUHR and CMM risk (Poverall=0.004, Pnon-linear=0.727). The ROC analysis demonstrated area under the curve values of 0.755 and 0.759 for cumUHR and UHR trajectories, respectively. Conclusions Both cumUHR exposure and a sustained-high UHR trajectory are significantly associated with an increased risk of CMM in middle-aged and older Chinese adults. Long-term dynamic monitoring of UHR is of significant importance for the early prevention of CMM.
