Serum albumin concentrations, effect modifiers and first incident acute myocardial infarction: A cross-sectional study of 1552 cases and 6680 controls

Nonlinear relationship between blood urea nitrogen to albumin ratio and in-hospital mortality in non-diabetic patients with non-ST-segment elevation myocardial infarction

Background

The blood urea nitrogen (BUN) to albumin (ALB) ratio (BAR) is a novel biomarker that reflects both nutritional and inflammatory status and has been linked to the prognosis of various acute and chronic diseases. However, studies on its association with in-hospital prognosis in patients with non-ST-segment elevation myocardial infarction (NSTEMI) remain limited. Therefore, this study aimed to evaluate the relationship between BAR and in-hospital mortality in patients with NSTEMI.

Methods

This study included 772 non-diabetic NSTEMI patients. The predictive performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC). Multivariable logistic regression was performed to identify the independent risk factors of in-hospital mortality. Subgroup analyses were conducted to evaluate the association between BAR and in-hospital mortality across different patient subgroups. Restricted cubic spline (RCS) function was applied to examine the nonlinear relationship between BAR and in-hospital mortality, and the two-piecewise logistic regression model was used for threshold effects analysis.

Results

A total of 40 patients died during hospitalization. BAR exhibited strong predictive performance for in-hospital mortality (AUC = 0.83; 95% CI: 0.77-0.89). Multivariate analysis indicated that BAR was an independent risk factor for in-hospital mortality (OR = 1.06; 95% CI: 1.01-1.12), with a significant increase in mortality risk observed in most subgroups as BAR increased. A nonlinear relationship with a saturation effect was observed between BAR and in-hospital mortality (P for non-linearity = 0.002), with an inflection point of 8.51. Further two-piecewise logistic regression analysis revealed that when BAR was <8.51, the risk of in-hospital mortality increased significantly (OR = 1.69, 95% CI: 1.16-2.53), whereas when BAR was ≥8.51, the association was not statistically significant (OR = 0.99, 95% CI: 0.92-1.06).

Conclusion

Baseline BAR serves as a simple, clinically useful prognostic biomarker of in-hospital mortality in non-diabetic NSTEMI patients. Additionally, we identified a nonlinear relationship with saturation effect between BAR and in-hospital mortality.

Enhanced predictive performance of the GRACE risk score by incorporating lipoprotein(a) for major adverse cardiac events in acute myocardial infarction patients undergoing PCI

Background

As scientific research advances, the landscape of detection indicators and methodologies evolves continuously. Our current study aimed to identify some novel perioperative indicators that can enhance the predictive accuracy of the Global Registry of Acute Coronary Events (GRACE) score for the in-hospital major adverse cardiovascular events (MACEs) in patients with acute myocardial infarction.

Methods

A total of 647 adult patients with AMI admitted to the emergency department were consecutively enrolled in the retrospective research starting from June 2016 to September 2019. The endpoint was in-hospital MACE. Stepwise regression analysis and multivariate logistic regression were performed to select the indicators for the union model established by nomogram. Bootstrap with 1000 replicates was chosen as the internal validation of the union model. The area under the receiver operating curve (AUC) and calibration plot were used to evaluate the discrimination and calibration. Decision curve analysis (DCA) was performed to evaluate the clinical sufficiency of the nomogram. Akaike's information criterion (AIC) and Bayesian Information Criterion (BIC) were used to evaluate the goodness of fit.

Results

Lipoprotein(a) combined with serum uric acid, fasting blood glucose, and hemoglobin could improve the GRACE risk score. The AUC of the union model was 0.86, which indicated a better discriminative ability than the GRACE risk score alone (AUC, 0.81; P < 0.05). The calibration plots of the union model showed favorable consistency between the prediction of the model and actual observations, which was better than the GRACE risk score. DCA plots suggested that the union model had better clinical applicability than the GRACE risk score.

Conclusion

Lipoprotein(a) has shown promise in augmenting the predictive capability of the GRACE risk score, however, it may be beneficial to integrate it with other commonly used indicators.

Leveraging Machine Learning Techniques to Forecast Chronic Total Occlusion before Coronary Angiography

BACKGROUND

Chronic total occlusion (CTO) remains the most challenging procedure in coronary artery disease (CAD) for interventional cardiology. Although some clinical risk factors for CAD have been identified, there is no personalized prognosis test available to confidently identify patients at high or low risk for CTO CAD. This investigation aimed to use a machine learning algorithm for clinical features from clinical routine to develop a precision medicine tool to predict CTO before CAG.

METHODS

Data from 1473 CAD patients were obtained, including 1105 in the training cohort and 368 in the testing cohort. The baseline clinical characteristics were collected. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors that impact the diagnosis of CTO. A CTO predicting model was established and validated based on the independent predictors using a machine learning algorithm. The area under the curve (AUC) was used to evaluate the model.

RESULTS

The CTO prediction model was developed with the training cohort using the machine learning algorithm. Eight variables were confirmed as 'important': gender (male), neutrophil percentage (NE%), hematocrit (HCT), total cholesterol (TC), high-density lipoprotein cholesterol (HDL), ejection fraction (EF), troponin I (TnI), and N-terminal pro-B-type natriuretic peptide (NT-proBNP). The model achieved good concordance indices of 0.724 and 0.719 in the training and testing cohorts, respectively.

CONCLUSIONS

An easy-to-use tool to predict CTO in patients with CAD was developed and validated. More research with larger cohorts are warranted to improve the prediction model, which can support clinician decisions on the early discerning CTO in CAD patients.

The neutrophil percentage-to-albumin ratio is associated with all-cause mortality in critically ill patients with acute myocardial infarction

AIM

In this study, we evaluated the utility of neutrophil percentage-to-albumin ratio (NPAR) in predicting in critically ill patients with acute myocardial infarction (AMI).

METHODS

The information of patients were collected from Medical Information Mart for Intensive Care III database. Admission NPAR was calculated as neutrophil percentage divided by serum albumin. The endpoints of this study were 30-day, 90-day, 180-day, and 365-day all-cause mortality. Cox proportional hazards models and subgroup analyses were used to determine the relationship between admission NPAR and these endpoints.

RESULTS

798 critically ill patients with AMI were enrolled in. After adjustments for age, race and gender, higher admission NPAR was associated with increased risk of 30-day, 90-day, 180-day, and 365-day all-cause mortality in critically ill patients with AMI. And after adjusting for possible confounding variables, two different trends have emerged. Stratified by tertiles, high admission NPAR was independently associated with 180-day and 365-day all-cause mortality in critically ill patients with AMI (tertile 3 vs. tertile 1: adjusted HR, 95% CI 1.71, 1.10-2.66, p < 0.05; 1.66, 1.10-2.51, p < 0.05). In other hand, stratified by quartiles, highest admission NPAR levels were independently associated with 90-day, 180-day and 365-day all-cause mortality (quartile 4 vs. quartile 1: adjusted HR, 95% CI 2.36, 1.32-4.23, p < 0.05; 2.58, 1.49-4.47, p < 0.05; 2.61, 1.56-4.37, p < 0.05). ROC test showed that admission NPAR had a moderate ability to predict all-cause mortality of critically ill patients with AMI. No obvious interaction was found by subgroup analysis in most subgroups.

CONCLUSIONS

Admission NPAR was an independent predictor for 180-day and 365-day all-cause mortality in critically ill patients with AMI.

Prognostic impact of follow-up serum albumin after acute myocardial infarction

Aims

Previous studies have suggested that low serum albumin (LSA) at admission for acute myocardial infarction (AMI) is associated with adverse in‐hospital outcomes. The aim of this study was to investigate whether LSA in the remote phase after AMI is prognostic for long‐term outcomes.

Methods and results

This was a single‐centre, retrospective study of consecutive patients admitted for AMI from 2008 to 2016. Serum albumin concentrations were measured serially at admission and 1 year after discharge in Japanese patients. Occurrence of a composite of hospitalization for heart failure and cardiovascular death was the primary endpoint. The prognostic impact of remote LSA, defined as a serum albumin level < 3.8 g/dL at 1 year after discharge, was investigated with a multivariate‐adjusted Cox model. Among 1424 subjects analysed, 289 (20.3%) had LSA at admission, and 165 (11.6%) had LSA at 1 year after discharge. During follow‐up (median: 4.1 years), the primary endpoint occurred in 31/165 (18.8%) patients with remote LSA and 42/1259 (3.3%) patients without it [adjusted hazard ratio (aHR), 2.76; 95% confidence interval (CI), 1.32 to 5.72; P = 0.007]. The all‐cause death rate was 29.7% (49/165) in patients with remote LSA and 4.3% (54/1259) in patients without it (aHR, 4.02; 95% CI, 2.36 to 6.87; P < 0.001). The prognostic impact of remote LSA was consistent across albumin status in the acute phase of AMI.

Conclusions

Regardless of albumin status in the acute phase of AMI, LSA in the remote phase after AMI was significantly associated with long‐term adverse outcomes.

Correlations and Prognostic Roles of the Nutritional Status and Neutrophil-to-lymphocyte Ratio in Elderly Patients with Acute Myocardial Infarction Undergoing Primary Coronary Intervention

The prognostic capacities of nutritional status and inflammation in patients with acute myocardial infarction (AMI) have attracted increasing interest. However, the combined usefulness of the Controlling Nutritional Status (CONUT) score and neutrophil-to-lymphocyte ratio (NLR) in predicting adverse outcomes has not been investigated. The aim of our study was to investigate the relationship between the CONUT score and the NLR in patients with AMI and assessing the potential of these factors as prognostic markers.In this retrospective study, we reviewed the medical records of consecutive patients aged 65 years or older who were diagnosed with AMI and who underwent primary coronary intervention. We assessed the nutritional and inflammatory statuses using the CONUT score and the NLR, respectively. The NLR and CONUT score in the major adverse cardiovascular event (MACE) (+) patients were significantly higher than those in the MACE (-) patients. The areas under the receiver operating characteristic curves of the NLR and CONUT score were 0.71 and 0.77, respectively. The Kaplan-Meier analysis showed that patients with a high NLR (≥6.07) and CONUT score (≥3.5) had the worst prognoses. The multivariate Cox proportional hazards analyses suggested that the CONUT score was an independent predictor.The CONUT score was proven to be a significant prognostic factor of clinical outcomes in patients with AMI. However, further research in this area is needed to more fully understand the relationship among nutritional status, inflammation, and cardiovascular diseases, which might help reduce MACEs in patients with AMI.

Prognostic Impact of Serum Albumin for Developing Heart Failure Remotely after Acute Myocardial Infarction

Low serum albumin (LSA) on admission for acute myocardial infarction (AMI) is related to adverse in-hospital outcomes. However, the relationship between LSA and long-term post-AMI cardiovascular outcomes is unknown. A single-center, non-randomized, retrospective study was performed to investigate the prognostic impact of LSA at admission for AMI on cardiovascular death or newly developed HF in the remote phase after AMI. Admission serum albumin tertiles (<3.8, 3.8-4.2, ≥4.2 g/dL) were used to divide 2253 consecutive AMI from February 2008 to January 2016 patients into three groups. Primary outcome was a composite of hospitalization for HF and cardiovascular death remotely after AMI. Cox proportional hazard models were used to explore the relationship between admission LSA and primary outcome. During follow-up (median: 3.2 years), primary composite outcome occurred in 305 patients (13.5%). Primary composite outcome occurred individually for hospitalization for HF in 146 patients (6.5%) and cardiovascular death in 192 patients (8.5%). The cumulative incidence of primary composite outcome was higher in the LSA group than the other groups (log-rank test, p < 0.001). Even after adjustments for relevant clinical variables, LSA (<3.8 mg/dL) was an independent predictor of remote-phase primary composite outcome, irrespective of the clinical severity and subtype of AMI. Thus, LSA on admission for AMI was an independent predictor of newly developed HF or cardiovascular death and has a useful prognostic impact even remotely after AMI.

Predictive value of three Inflammation-based Glasgow Prognostic Scores for major cardiovascular adverse events in patients with acute myocardial infarction during hospitalization: a retrospective study

AIM

Inflammation-based Glasgow Prognostic Scores (GPS) have been reported to predict the prognosis of patients with acute ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). The goal of this study was to investigate whether three kinds of GPSs can effectively predict major cardiovascular adverse events (MACEs) in STEMI or non-ST-segment elevation myocardial infarction (NSTEMI) patients undergoing PPCI, elective PCI (EPCI) or conservative drug therapy during hospitalization.

METHODS

In this retrospective cohort study, patients with acute myocardial infarction (AMI) were divided into 0, 1 or 2 score according to the GPSs. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of GPSs for MACE and all-cause mortality during hospitalization. Three kinds of GPSs, Inflammation-based Glasgow Prognostic Score (GPS), modified GPS (MGPS) and high-sensitivity CRP-modified GPS (HS-MGPS) and Global Registry of Acute Coronary Events (GRACE) score were applied in this study.

RESULTS

A total of 188 patients were enrolled. The ROC curve with MACE showed that the AUC of GPS (0.820 (95% confidence interval (CI) [0.754-0.885]), P < 0.001) was larger than that of MGPS (0.789 (95% CI [0.715-0.863]), P < 0.001), HS-MGPS (0.787 (95% CI [0.717-0.856]), P < 0.001) and GRACE score (0.743 (95% CI [0.672-0.814]), P < 0.001). The ROC curve with all-cause mortality showed that the AUC of GPS (0.696 (95% CI [0.561-0.831]), P = 0.005) was similar to the HS-MGPS (0.698 (95% CI [0.569-0.826]), P = 0.005) and higher than the MGPS (0.668 (95% CI [0.525-0.812]), P = 0.016), but lower than the GRACE score (0.812 (95% CI [0.734-0.889]), P < 0.001). Multivariate logistic regression analysis showed that the GPS was an independent risk factor for the incidence of MACE during hospitalization. Compared with the odds ratio (OR) value for a GPS of 0, the OR for a GPS of 1 was 7.173 (95% CI [2.425-21.216]), P < 0.001), and that for a GPS of 2 was 18.636 (95% CI [5.813-59.746]), P < 0.001), but not an independent risk factor for all-cause mortality (P = 0.302). GRACE score was an independent risk factor for MACE (1.019 (95% CI [1.004-1.035]), P = 0.015) and all-cause mortality (1.040 (95% CI [1.017-1.064]), P = 0.001). In the subgroups classified according to the type of AMI, the presence of disease interference GPSs and the type of PCI, the ability of GPS to predict the occurrence of MACE seemed to be greater than that of MGPS and HS-MGPS.

CONCLUSION

The GPS has a good predictive value for the occurrence of MACE during hospitalization in patients with AMI, regardless of STEMI or NSTEMI, the choice of PCI mode and the presence or absence of diseases that interfere with GPS. However, GPS is less predictive of all-cause mortality during hospitalization than GRACE score, which may be due to the interference of patients with other diseases.

Impact of serum albumin levels on long-term all-cause, cardiovascular, and cardiac mortality in patients with first-onset acute myocardial infarction

BACKGROUND

To evaluate the association of serum albumin (SA) with long-term all-cause, cardiovascular, and cardiac mortality in patients with first-onset acute myocardial infarction (AMI).

METHODS

The cohort study enrolled 2305 patients with first-onset AMI. The median follow-up was of 1088days (3years). Impacts of SA on long-time mortality after AMI were determined using multivariate Cox proportional hazard regression analysis with backward selection.

RESULTS

The patients were divided into three categories by SA tertiles (≤3.62, 3.63-4.08, >4.08g/dl). High tertile group was used as reference, the adjusted HRs for all-cause death were 1.21 (P=0.338) and 1.74 (P=0.003) for intermediate and low tertile, respectively (p-for-trend=0.001); The equivalent values for cardiovascular death were 1.13 (P=0.588) and 1.64 (P=0.022), respectively (p-for-trend=0.009); The corresponding values for cardiac death were 1.07 (P=0.806) and 1.59 (P=0.048), respectively (p-for-trend=0.022). Moreover, adjusted HRs per 1-g/dl decrease in SA concentrations were 1.66 (P=0.001) for all-cause death, 1.47 (P=0.024) for cardiovascular death, and 1.61 (P=0.012) for cardiac death.

CONCLUSIONS

Low SA level (≤3.62g/dl) on admission was an independent predictor of long-term all-cause, cardiovascular, and cardiac mortality in patients with first-onset AMI. There was a dose-response relationship between decreased SA concentrations and increased long-term all-cause, cardiovascular, and cardiac mortality.

Risk burdens of modifiable risk factors incorporating lipoprotein (a) and low serum albumin concentrations for first incident acute myocardial infarction

Risk burdens of modifiable risk factors incorporating lipoprotein (a) (Lp(a)) and low serum albumin (LSA) concentrations for first incident acute myocardial infarction (AMI) haven’t been studied previously. Cross-sectional study of 1552 cases and 6125 controls was performed for identifying the association of risk factors with first incident AMI and their corresponding population attributable risks (PARs). Modifiable risk factors incorporating LSA and Lp(a) accounted for up to 92% of PAR for first incident AMI. Effects of these risk factors were different in different sexes across different age categories. Overall, smoking and LSA were the 2 strongest risk factors, together accounting for 64% of PAR for first incident AMI. After multivariable adjustment, Lp(a) and LSA accounted for 19% and 41%, respectively, and together for more than a half (54%) of PAR for first incident AMI. Modifiable risk factors incorporating LSA and Lp(a) have accounted for an overwhelmingly large proportion of the risk of first incident AMI, indicating most first incident AMI is preventable. The knowledge of risk burdens for first incident AMI incorporating Lp (a) and LSA may be beneficial for further reducing first incident AMI from a new angle.