Cholesterol affects the relationship between albumin and major adverse cardiac events in patients with coronary artery disease: a secondary analysis.
Scientific reports
We aimed to examine whether the efficacy of the risk of poor prognosis in patients with coronary artery disease is jointly affected by total cholesterol and baseline serum albumin in a secondary analysis of previous study. We analyzed the data of 204 patients from October 2014 to October 2017 for newly diagnosed stable CAD. The outcome was major adverse cardiac events (MACE; defined as all cause mortality, non fatal myocardial infarction, and non fatal stroke). The median duration of follow-up was 783 days. Multivariable COX model was performed to revalidate the relationship between the sALB and MACE and interaction tests were conducted to find the effects of total cholesterol on their association. A total of 28 MACE occurred among the 204 participants. The risk of MACE varied by baseline serum albumin and total cholesterol. Specifically, lower serum albumin indicated higher risk of MACE (HR 3.52, 95% CI 1.30-9.54), and a test for interaction between baseline serum albumin and total cholesterol on MACE was significant (P = 0.0005). We suggested that baseline serum albumin and total cholesterol could interactively affect the risk of poor prognosis of patients with coronary artery diseases. Our findings need to be confirmed by further randomized trials.
10.1038/s41598-022-16963-0
Body Mass Index and Major Adverse Cardiovascular Events: A Secondary Analysis Based on a Retrospective Cohort Study.
Liu Xiaobo,Liu Peng
Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND The association between body mass index (BMI) and major adverse cardiovascular events (MACE) has not been clarified and is controversial. Therefore, the purpose of present study is to explore the association between BMI and MACE. MATERIAL AND METHODS This was a secondary analysis of a retrospective cohort study in which 204 participants who were diagnosed with stable coronary artery disease (CAD) and received elective percutaneous coronary intervention (PCI) were recruited. According to the BMI, patients were divided into 3 categories - underweight (BMI <18.5 kg/m²), normal BMI (18.5 ≤BMI <25 kg/m²), and overweight (BMI ≥25 kg/m²)], and the patients were followed up. The primary endpoint was MACE. RESULTS After a median follow-up of 783 days, MACE events had occurred in 18 participants. After controlling for potential confounding factors, no difference was observed in MACE between the underweight group and the normal BMI group (OR=1.73, 95% CI 0.42 to 7.17); but there were significantly fewer MACE in the overweight group than in the normal BMI group (OR=0.17; 95% CI: 0.03 to 0.84). Pearson correlation analysis showed that BMI was positively correlated with hemoglobin (r=0.2102) and albumin (r=0.2780), but negatively correlated with high-density lipoprotein cholesterol (r=-0.2052). The receiver operating characteristic curve (ROC) showed that the best threshold for BMI to predict MACE was 24.23, the area under the curve was 0.729, sensitivity was 0.893, and the specificity was 0.460. CONCLUSIONS Our study shows that overweight patient with stable CAD have lower risk of MACE after PCI, and the optimal threshold for predicting MACE is 24.23.
10.12659/MSM.919700
C-Reactive protein predicts all-cause and cardiovascular mortality in hemodialysis patients.
Yeun J Y,Levine R A,Mantadilok V,Kaysen G A
American journal of kidney diseases : the official journal of the National Kidney Foundation
Hypoalbuminemia predicts death in dialysis patients. Although hypoalbuminemia has been attributed to malnutrition, evidence of inflammation (C-reactive protein [CRP] and cytokine levels) has recently been recognized to predict albumin concentration in dialysis patients. We measured CRP and albumin levels in October 1995 in 91 hemodialysis (HD) patients. During a 34-month follow-up period, we determined the incidence and cause of death. Patients were divided into four groups based on serum albumin levels (<3.5 [lowest quartile], 3.5 to 3.8, 3.9 to 4.0, and >4.0 g/dL [highest quartile]). Survival differed among the four groups (P = 0.0063). Patients with albumin levels greater than 4.0 g/dL had the greatest survival. Kaplan-Meier survival estimates of patients from varying CRP quartiles (<2.6, 2.6 to 5.2, 5.3 to 11.5, and >11.5 microg/mL) differed among the four groups (P < 0.0001). The group with the greatest CRP level (>11.5 microg/mL) had the lowest survival. Multivariate analysis using the Cox proportional hazards model showed that only CRP level (chi-square = 21.11; P < 0.0001) and age (chi-square = 5.44; P = 0.020) predicted death. Albumin level (chi-square = 0.16; P = 0.69) was not predictive. Only when CRP was excluded from the model did low serum albumin level (chi-square = 12. 04; P = 0.0004) predict death. CRP level (chi-square = 16.79; P < 0. 0001) and age (chi-square = 6.38; P = 0.012) also superceded albumin level (chi-square = 0.45; P = 0.51) in predicting cardiovascular mortality. Although values for blood urea nitrogen, creatinine, and normalized protein catabolic rate were significantly less among patients who died, these parameters, as well as cholesterol level and diabetes, were not important predictors of death in multivariate analysis. The acute-phase response or the cause of the acute-phase response is largely responsible for the effect of hypoalbuminemia on mortality in HD patients.
Elevated AST/ALT ratio is associated with all-cause mortality and cancer incident.
Journal of clinical laboratory analysis
BACKGROUND:The aspartate transaminase (AST)-to-alanine aminotransferase (ALT) ratio, which is used to measure liver injury, has been found to be associated with some chronic diseases and mortality. However, its relevance to cancer incidence resulting from population-based prospective studies has rarely been reported. In this study, we investigated the correlation of the AST/ALT ratio as a possible predictor of mortality and cancer incidence. METHODS:A total of 9,946 participants fulfilled the inclusion criteria for a basic public health service project of the Health Checkup Program conducted by the BaiYun Community Health Service Center, Taizhou. Deceased participants and cancer incident cases were from The Taizhou Chronic Disease Information Management System. Odds ratios (ORs) and interval of quartile range (IQR) computed by logistic regression analysis and cumulative incidence rate were calculated by the Kaplan-Meier survival method and compared with log-rank test statistics. RESULTS:Serum ALT and AST levels were both increased in patients with chronic diseases, but the ratio of AST/ALT was generally decreased. The cancer incident cases (488 new cases) had a greater baseline ratio (median =1.23, IQR: 0.96-1.54) than noncancer cases (median =1.15, IQR: 0.91-1.44). Compared to the first quartile of the AST/ALT ratio, the population in the top quartile had a higher cumulative cancer incidence rate (7.54% vs. 4.44%) during follow-up period. Furthermore, an elevated AST/ALT ratio increased the risk of all-cause mortality. CONCLUSIONS:The ratio of AST/ALT is a potential biomarker to assess healthy conditions and long-term mortality. Especially for cancer, the AST/ALT ratio not only increases at baseline but also predicts the future development of cancer. The clinical value and potential mechanism deserve further research.
10.1002/jcla.24356
Impact of the De Ritis Ratio on the Prognosis of Patients with Stable Coronary Artery Disease Undergoing Percutaneous Coronary Intervention.
Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND The aim of this study was to emphasize the impact of the aspartate aminotransferase-to-alanine aminotransferase ratio (De Ritis ratio) on the prognosis of patients with stable coronary artery disease (SCAD) undergoing percutaneous coronary intervention (PCI). MATERIAL AND METHODS Patients with SCAD who underwent elective PCI at Shinonoi General Hospital were included. SCAD was defined as epicardial coronary artery diameter stenosis ≥90% or epicardial coronary artery diameter stenosis ≥75% accompanied by symptoms or stress-induced myocardial ischemia. Clinical data were collected, and cardiovascular events were followed after discharge. One-way Cox proportional risk analysis was performed to assess the risk stratification value of the De Ritis ratio, using major adverse cardiac and cerebrovascular events (MACCE) and all-cause mortality as the primary and secondary endpoints, respectively. The independent risk stratification value was evaluated by multivariate Cox proportional risk analysis. RESULTS Among 204 patients with SCAD undergoing PCI, during a median follow-up period of 706 days (24 months), 13.7% (28/204) patients experienced MACCE, and 8.8% (18/204) experienced all-cause mortality. Multifactorial Cox regression analysis revealed that a high De Ritis ratio was an independent risk factor for MACCE (HR=2.96, 95% CI: 1.29-6.78, P=0.01) and all-cause mortality (HR=3.61, 95% Cl: 1.31-9.86, P=0.012). The sensitivity analysis further confirmed the incremental value of the De Ritis ratio for adverse cardiovascular events. CONCLUSIONS A high De Ritis ratio was an independent and valuable risk stratification factor for MACCE and all-cause mortality in patients with SCAD after PCI.
10.12659/MSM.937737
Association between serum albumin-to-creatinine ratio and clinical outcomes among patients with ST-elevation myocardial infarction after percutaneous coronary intervention: a secondary analysis based on Dryad databases.
Frontiers in cardiovascular medicine
Background:The prognostic value of the serum albumin-to-creatinine ratio (sACR) in patients with ST-elevation myocardial infarction (STEMI) remains unclear. This study aims to investigate the impact of the sACR on incident major adverse cardiovascular events (MACEs) among revascularized patients with STEMI at long-term follow-up. Methods:A total of 461 patients with STEMI who underwent successful primary percutaneous coronary intervention (PCI) were enrolled to explore the association between the sACR and MACE during a 30-month follow-up. The Cox regression proportional hazard model was used to evaluate the prognostic value of the sACR. Heterogeneity among specific groups was investigated by subgroup analysis. Results:A total of 118 patients developed MACE during the follow-up. A negative association between the sACR and MACE was found after adjusting for other MACE-related risk factors. In subgroup analyses, the sACR was inversely associated with MACE in patients aged ≥ 60 years [hazard ratio (HR), 0.478; 95% confidence interval (CI), 0.292-0.784], male (HR, 0.528; 95% CI, 0.327-0.851), with hypertension history (HR, 0.470; 95% CI, 0.271-0.816), and with anterior wall myocardial infarction (HR, 0.418; 95% CI, 0.239-0.730). Meanwhile, the negative association between the sACR and MACE remained significant in a sensitivity analysis that excluded patients with low serum albumin levels (HR, 0.553; 95% CI, 0.356-0.860). Conclusions:Patients with STEMI who underwent successful PCI with a low sACR had a higher risk of developing MACE, indicating that the sACR could be used to identify patients with STEMI who are at high risk of developing MACE.
10.3389/fcvm.2023.1191167
A clinical model to predict the progression of knee osteoarthritis: data from Dryad.
Journal of orthopaedic surgery and research
BACKGROUND:Knee osteoarthritis (KOA) is a multifactorial, slow-progressing, non-inflammatory degenerative disease primarily affecting synovial joints. It is usually induced by advanced age and/or trauma and eventually leads to irreversible destruction of articular cartilage and other tissues of the joint. Current research on KOA progression has limited clinical application significance. In this study, we constructed a prediction model for KOA progression based on multiple clinically relevant factors to provide clinicians with an effective tool to intervene in KOA progression. METHOD:This study utilized the data set from the Dryad database which included patients with Kellgren-Lawrence (KL) grades 2 and 3. The KL grades was determined as the dependent variable, while 15 potential predictors were identified as independent variables. Patients were randomized into training set and validation set. The training set underwent LASSO analysis, model creation, visualization, decision curve analysis and internal validation using R language. The validation set is externally validated and F1-score, precision, and recall are computed. RESULT:A total of 101 patients with KL2 and 94 patients with KL3 were selected. We randomly split the data set into a training set and a validation set by 8:2. We filtered "BMI", "TC", "Hypertension treatment", and "JBS3 (%)" to build the prediction model for progression of KOA. Nomogram used to visualize the model in R language. Area under ROC curve was 0.896 (95% CI 0.847-0.945), indicating high discrimination. Mean absolute error (MAE) of calibration curve = 0.041, showing high calibration. MAE of internal validation error was 0.043, indicating high model calibration. Decision curve analysis showed high net benefit. External validation of the metabolic syndrome column-line graph prediction model was performed by the validation set. The area under the ROC curve was 0.876 (95% CI 0.767-0.984), indicating that the model had a high degree of discrimination. Meanwhile, the calibration curve Mean absolute error was 0.113, indicating that the model had a high degree of calibration. The F1 score is 0.690, the precision is 0.667, and the recall is 0.714. The above metrics represent a good performance of the model. CONCLUSION:We found that KOA progression was associated with four variable predictors and constructed a predictive model for KOA progression based on the predictors. The clinician can intervene based on the nomogram of our prediction model. KEY INFORMATION:This study is a clinical predictive model of KOA progression. KOA progression prediction model has good credibility and clinical value in the prevention of KOA progression.
10.1186/s13018-023-04118-4