Fibrinogen–albumin ratio predicting major adverse cardiovascular outcomes post‐percutaneous coronary intervention: A systematic review and exploratory meta‐analysis
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SUBMITTER: Desai R
PROVIDER: S-EPMC10106656 | biostudies-literature | 2023 Feb
REPOSITORIES: biostudies-literature
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Project description:Inflammation and nutrition as main factors can affect the prognosis of patients with chronic total coronary occlusion (CTO) undergoing percutaneous coronary intervention (PCI). The C-reactive protein to albumin ratio (CAR) can clarify the inflammation and nutrition status, which are highly related to clinical outcomes. This study aims to investigate the association between CAR and adverse cardiovascular events in patients with CTO undergoing PCI. For this study, 664 patients were divided into three groups based on the tertiles of CAR. The primary endpoint was all-cause mortality and the secondary endpoint was major adverse cardiovascular events (MACE). Over a median follow-up of 33.7 months, the primary endpoint occurred in 64 patients (9.6%) and the secondary endpoint occurred in 170 patients (25.6%). The patients with higher CAR represented a worse prognosis with all-cause death and cardiovascular death after the adjustment for the baseline risk factors. Adding the CAR values raised the predictive value for the incidence of the all-cause death and cardiovascular death but not MACE. The capacity of prognosis prediction was improved after the addition of the CAR value to the traditional prediction model.
| S-EPMC8636141 | biostudies-literature
Project description:BackgroundThe number of models developed for predicting major adverse cardiovascular events (MACE) in patients undergoing percutaneous coronary intervention (PCI) is increasing, but the performance of these models is unknown. The purpose of this systematic review is to evaluate, describe, and compare existing models and analyze the factors that can predict outcomes.MethodsWe adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 during the execution of this review. Databases including Embase, PubMed, The Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP, and SINOMED were comprehensively searched for identifying studies published from 1977 to 19 May 2023. Model development studies specifically designed for assessing the occurrence of MACE after PCI with or without external validation were included. Bias and transparency were evaluated by the Prediction Model Risk Of Bias Assessment Tool (PROBAST) and Transparent Reporting of a multivariate Individual Prognosis Or Diagnosis (TRIPOD) statement. The key findings were narratively summarized and presented in tables.ResultsA total of 5,234 articles were retrieved, and after thorough screening, 23 studies that met the predefined inclusion criteria were ultimately included. The models were mainly constructed using data from individuals diagnosed with ST-segment elevation myocardial infarction (STEMI). The discrimination of the models, as measured by the area under the curve (AUC) or C-index, varied between 0.638 and 0.96. The commonly used predictor variables include LVEF, age, Killip classification, diabetes, and various others. All models were determined to have a high risk of bias, and their adherence to the TRIPOD items was reported to be over 60%.ConclusionThe existing models show some predictive ability, but all have a high risk of bias due to methodological shortcomings. This suggests that investigators should follow guidelines to develop high-quality models for better clinical service and dissemination.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=400835, Identifier CRD42023400835.
| S-EPMC10800829 | biostudies-literature
Project description:Monocyte count and serum albumin (Alb) have been proven to be involved in the process of systemic inflammation. Therefore, we investigated the prognostic value of monocyte-to-albumin ratio (MAR) in patients who underwent percutaneous coronary intervention (PCI). We enrolled a total of 3561 patients in the present study from January 2013 to December 2017. They were divided into two groups according to MAR cut-off value (MAR < 0.014, n=2220; MAR ≥ 0.014, n=1119) as evaluated by receiver operating characteristic (ROC) curve. The average follow-up time was 37.59 ± 22.24 months. The two groups differed significantly in the incidences of all-cause mortality (ACM; P<0.001), cardiac mortality (CM; P<0.001), major adverse cardiovascular events (MACEs; P=0.038), and major adverse cardiovascular and cerebrovascular events (MACCEs; P=0.037). Multivariate Cox regression analyses revealed MAR as an independent prognostic factor for ACM and CM. The incidence of ACM increased by 56.5% (hazard ratio [HR] = 1.565; 95% confidence interval [CI], 1.086-2.256; P=0.016) and that of CM increased by 76.3% (HR = 1.763; 95% CI, 1.106-2.810; P=0.017) in patients in the higher-MAR group. Kaplan-Meier survival analysis suggested that patients with higher MAR tended to have an increased accumulated risk of ACM (Log-rank P<0.001) and CM (Log-rank P<0.001). The findings of the present study suggested that MAR was a novel independent predictor of long-term mortality in patients who underwent PCI.
| S-EPMC8243340 | biostudies-literature
Project description:BackgroundPercutaneous coronary intervention (PCI) is considered the procedure of choice for patients with acute coronary syndrome (ACS), as it significantly improves cardiovascular outcomes. However, considerable uncertainty persists regarding the potential sex differences in PCI outcomes, due to conflicting results in previous studies.ObjectivesThis meta-analysis aims to evaluate potential sex-related differences in cardiovascular adverse outcomes after PCI among ACS patients.MethodsThe primary outcome was major adverse cardiovascular events (MACE) and its components. Outcomes were examined in various time frames including: short-term (within 1 month after PCI), mid-term (within 1 year), and long-term (within >1 year). A random effects model was used to estimate risk ratios (RR) and 95% CIs.ResultsAmong 32 trials, at short-term, PCI was associated with a higher risk of MACE (risk ratio [RR]: 1.43; 95% CI: 1.10-1.86), all-cause mortality (RR: 2.51; 95% CI: 1.70-3.71), and myocardial infarction (RR: 1.33; 95% CI: 1.00-1.77) in women compared with men. Over the long-term, women had a higher risk of MACE (RR: 1.11; 95% CI: 1.01-1.22), all-cause mortality (RR: 1.29; 95% CI: 1.17-1.42), and cardiovascular mortality (RR: 1.30; 95% CI: 1.11-1.52), when compared with men. However, the analysis for stroke and repeat revascularization showed no significant difference between the 2 groups in the long- and short-term.ConclusionsIn the meta-analysis of PCI-related trials in ACS, women have a higher risk of adverse cardiovascular outcomes compared with men.
| S-EPMC11780094 | biostudies-literature
Project description:PurposeInflammation is commonly considered a mechanism underlying contrast-associated acute kidney injury (CA-AKI). This study aimed to explore the predictive capability of the novel inflammatory marker lactate dehydrogenase-to-albumin ratio (LAR) for CA-AKI following percutaneous coronary intervention (PCI), and further compare it with other common inflammatory biomarkers.MethodsThis study enrolled 5,435 patients undergoing elective PCI. The primary outcome was CA-AKI, and the secondary outcome was all-cause mortality. All patients were grouped into three groups based on the LAR tertiles.ResultsThree hundred fifteen patients (5.8%) experienced CA-AKI during hospitalization. The fully adjusted logistic regression suggested a significant increase in the risk of CA-AKI in LAR Tertile 3 (odds ratio [OR]: 2.51, 95% confidence interval [CI]: 1.68-3.83, p < .001) and Tertile 2 (OR: 2.11, 95% CI: 1.42-3.20, p < .001) compared to Tertile 1. Additionally, receiver operating characteristic (ROC) analysis demonstrated that LAR exhibited significantly superior predictive capability for CA-AKI compared to other inflammatory biomarkers. Regarding the secondary outcome, multivariate COX regression analysis showed a positive correlation between elevated LAR levels and all-cause mortality.ConclusionIn patients undergoing elective PCI, LAR was significantly independently associated with CA-AKI, and it stood out as the optimal inflammatory biomarker for predicting CA-AKI.
| S-EPMC10823551 | biostudies-literature
Project description:ObjectiveTo estimate the incidence of major adverse cardiovascular events (MACE) with genotype test-guided antiplatelet therapy in patients undergoing percutaneous coronary intervention (PCI) for acute coronary syndrome.MethodsPatients who had undergone PCI for acute coronary syndrome as well as stable coronary artery disease were recruited. Salivary samples were obtained from these patients and genotyped for CYP2C19∗2, CYP2C19∗3 variations by sequencing method (GAAP x method). Patients were categorized as normal (GG, GG) (29%), intermediate (AG) (52%) or poor metabolizes (homozygous variant AA) (19%). Dual antiplatelets were given based on the genotyping data. Poor metabolizes received newer agent (ticagrelor), intermediate metabolizes received double-dose of clopidogrel and normal metabolizes received therapeutic doses of clopidogrel. All subjects were followed-up for six months.ResultsBased on the genotyping data of CYP2C19∗2 and CYP2C19∗3 variations, it was found that most patients were categorized as 'intermediate' (78, 51.65%), followed by 'normal' (43, 28.48%) and 'poor' metabolizes (30, 19.87%). Only 3 (1.5%) of 151 patients reported MACE at follow-up.ConclusionsGenotyping for CYP2C19 variations to assess clopidogrel resistance in patients undergoing PCI and subsequent drug selection helps reduce MACE after coronary intervention.
| S-EPMC7772580 | biostudies-literature
Project description:BackgroundRecurrent acute myocardial infarction requiring unplanned percutaneous coronary intervention (PCI) is one of the major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS) after PCI. There is a continuing controversy about the association between serum cystatin C, a biomarker for the evaluation of renal function, and the prognosis of ACS patients following PCI. The retrospective study evaluated the association between serum cystatin C level and MACE in ACS patients after PCI.MethodsData were retrieved for 330 patients with ACS for primary PCI in a single center. Serum cystatin C levels were measured before PCI. All patients underwent regular follow-ups after PCI, and the studied endpoint was MACE, defined as the need for a repeat revascularization in the heart. The predictive value of serum cystatin C for MACE was analyzed using univariate and multivariate analysis. Restricted cubic spline (RCS) analysis was applied to evaluate the dose-response relationship between serum cystatin C level and MACE in ACS patients following PCI.ResultsAfter a median follow-up of 63 months (range, 1-148 months), 121 of the 330 patients experienced MACE. Compared to patients who did not have MACE, patients who had MACE showed a significant decrease in serum cystatin C levels (0.99±0.32 vs. 1.15±0.78 mg/L, P=0.03). In multivariate regression analysis, serum cystatin C level was an independent risk factor for MACE. According to the serum cystatin C level, patients were divided into 4 categories, Cox regression analysis illustrated that the second quartile of serum cystatin C level indicated an increased risk of MACE in patients with PCI for primary ACS compared to the highest quartile [Q2: adjusted hazard ratio (HR) =2.109; 95% confidence interval (CI): 1.193-3.727; P=0.01]. RCS analysis showed a significant U-shaped dose-response relationship between cystatin C level and MACE in patients with PCI for ACS (P for non-linearity =0.004).ConclusionsThese results indicated an association between serum cystatin C level and post-PCI MACE in ACS patients.
| S-EPMC11384458 | biostudies-literature
Project description:BackgroundAlthough there have been several studies related to serum fibroblast growth factor 21 (FGF21) levels and acute myocardial infarction, the value of serum FGF21 levels in ST-segment elevation myocardial infarction (STEMI) patients after emergency percutaneous coronary intervention (PCI) has not been previously investigated.MethodsA total of 348 STEMI patients who underwent emergency PCI were enrolled from January 2016 to December 2018. The primary endpoint was the occurrence of major adverse cardiovascular events (MACEs), with a median follow-up of 24 months. Eighty patients with stable angina (SA) who underwent selective PCI served as the control group. Serum FGF21 levels were measured by ELISA.ResultsSerum FGF21 levels were significantly higher in the STEMI group than in the SA group (225.03 ± 37.98 vs. 135.51 ± 34.48, P < 0.001). Multiple linear regression analysis revealed that serum FGF21 levels were correlated with NT-proBNP (P < 0.001). According to receiver operating characteristic (ROC) analysis, the areas under the ROC curve (AUCs) of FGF21 and NT-proBNP were 0.812 and 0.865, respectively. The Kaplan-Meier curves showed that STEMI patients with lower FGF21 levels had an increased MACE-free survival rate. Cox analysis revealed that high FGF21 levels (HR: 2.011, 95% CI: [1.160-3.489]) proved to be a powerful tool in predicting the risk of MACEs among STEMI patients after emergency PCI.ConclusionElevated FGF21 levels on admission have been shown to be a powerful predictor of MACEs for STEMI patients after emergency PCI.
| S-EPMC8487623 | biostudies-literature
Project description:PurposeSerum fibrinogen and albumin play important roles in systemic inflammation and are implicated in tumor progression. The fibrinogen-to-albumin ratio (FAR) has shown a prognostic impact in several malignancies. This study aims to assess the prognostic value of the pretherapeutic FAR in patients with adenocarcinoma of the gastroesophageal junction (AEG) who underwent upfront resection.MethodsConsecutive patients who underwent surgical resection at the Department of Surgery at the Medical University of Vienna between 1992 and 2014 were included into this study. Optimal cut-off values were determined with the receiver-operating characteristic (ROC) curve, uni- and multivariate analyzes were calculated by the Cox proportional hazard regression model for overall survival (OS).ResultsAmong 135 included patients, the majority were male (79.26%), with a mean age of 66.53 years. Elevated FAR correlated significantly (p = 0.002) with shorter OS in univariate analysis, also confirmed as independent prognostic factor (p = 0.005) in multivariable analysis. The ROC curve of FAR (AUC = 0.744) outperformed fibrinogen (AUC = 0.738) and albumin (AUC = 0.378) in predicting OS for AEG patients.ConclusionThe FAR serves as an independent prognostic factor for OS in patients undergoing primarily resection for AEG. Given its routine availability and ease of calculation, FAR could help in diagnosis and treatment selection for AEG patients. Further validation studies are warranted to confirm these findings conclusively.
| S-EPMC11473574 | biostudies-literature
Project description:BackgroundAcute coronary syndrome is the topmost cause of death worldwide; therefore, it is necessary to predict major adverse cardiovascular events and cardiovascular deaths in patients with acute coronary syndrome to make correct and timely clinical decisions.ObjectiveThe current review aimed to highlight algorithms and important predictor variables through examining those studies which used machine learning algorithms for predicting major adverse cardiovascular events in patients with acute coronary syndrome.MethodsTo predict major adverse cardiovascular events in patients with acute coronary syndrome, the preferred reporting items for scoping reviews guidelines were used. In doing so, PubMed, Embase, Web of Science, Scopus, Springer, and IEEE Xplore databases were searched for articles published between 2005 and 2021. The checklist "Quality assessment of machine learning studies" was used to assess the quality of eligible studies. The findings of the studies are presented in the form of a narrative synthesis of evidence.ResultsIn total, among 2,558 retrieved articles, 22 studies were qualified for analysis. Major adverse cardiovascular events and mortality were predicted in 5 and 17 studies, respectively. According to the results, 14 (63.64%) studies did not perform external validation and only used registry data. The algorithms used in this study comprised, inter alia, Regression Logistic, Random Forest, Boosting Ensemble, Non-Boosting Ensemble, Decision Trees, and Naive Bayes. Multiple studies (N = 20) achieved a high area under the ROC curve between 0.8 and 0.99 in predicting mortality and major adverse cardiovascular events. The predictor variables used in these studies were divided into demographic, clinical, and therapeutic features. However, no study reported the integration of machine learning model into clinical practice.ConclusionMachine learning algorithms rendered acceptable results to predict major adverse cardiovascular events and mortality outcomes in patients with acute coronary syndrome. However, these approaches have never been integrated into clinical practice. Further research is required to develop feasible and effective machine learning prediction models to measure their potentially important implications for optimizing the quality of care in patients with acute coronary syndrome.
| S-EPMC9329142 | biostudies-literature