The Value of Pre-Infarction Angina and Plasma D-Dimer in Predicting No-Reflow After Primary Percutaneous Coronary Intervention in ST-Segment Elevation Acute Myocardial Infarction Patients

The predictive value of systemic immune-inflammation index for long-term cardiovascular mortality in non-ST segment elevation myocardial infarction

BACKGROUND

Increased levels of inflammatory markers have been found in association with the severity of coronary atherosclerosis. Systemic immuneinflammation index (SII), which is calculated by multiplying neutrophil and platelet counts and then dividing the result by the lymphocyte count, can also be used as a prognostic indicator in different cardiovascular diseases. In this study, we investigated SII levels and long-term mortality of patients with non-ST segment elevation myocardial infarction (NSTEMI).

METHODS

This is an observational, single-center study. Two hundred-eight patients who underwent coronary angiography for NSTEMI were included in the study. Patients were divided into 3 tertiles based on SII levels. We researched the relationship between level level and 1, 3 and 5 years mortality (NSTEMI).

RESULTS

One-year mortality of the patients was significantly higher among patients in the upper SII tertile when compared with the lower and middle SII tertile groups [11 (15.9%) vs. 2 (2.9%) and 6 (8.7%); P  = 0.008, P  = 0.195, respectively). Three-year mortality of the patients was significantly higher among patients in the upper SII tertile when compared with the lower and middle SII tertile groups [21 (30.4%) vs. 5 (7.1%) and 12 (17.4%); P  < 0.001, P  = 0.072, respectively). Five-year mortality of the patients was significantly higher among patients in the upper SII tertile when compared with the lower and middle SII tertile groups [26 (37.7%) vs. 8 (11.4%) and 15 (21.7%); P  < 0.001, P  = 0.040, respectively).

CONCLUSION

Our study showed that NSTEMI patients with higher SII had worse long-term mortality.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Development and Validation of Nomogram for the Prediction of Malignant Ventricular Arrhythmia Including Circulating Inflammatory Cells in Patients with Acute ST-Segment Elevation Myocardial Infarction

Background

Malignant ventricular arrhythmia (MVA) can seriously affect the hemodynamic changes of the body. In this study, we developed and validated a nomogram to predict the in-hospital MVA risk in patients with STEMI after emergency PCI.

Methods

The multivariable logistic regression analysis included variables with a P<0.05 in the univariate logistic regression analysis and investigated the independent predictors affecting in-hospital MVA after PCI in patients with STEMI in the training cohort. The construction of a nomogram model used independent predictors to predict the risk of in-hospital MVA, and C-index, Hosmer-Lemeshow (HL) test, calibration curves, decision curve analysis (DCA), and receiver operating characteristic (ROC) were used to validate the nomogram.

Results

Killip class [OR=5.034 (95% CI: 1.596-15.809), P=0.005], CK-MB [OR=1.002 (95% CI: 1.001-1.004), P=0.022], serum potassium [OR=0.618 (95% CI: 0.406-0.918), P=0.020], NLR [OR=1.073 (95% CI: 1.034-1.115), P<0.001], and monocyte [OR=1.974 (95% CI: 1.376-2.925), P<0.001] were the independent predictors of in-hospital MVA after PCI in patients with STEMI. A nomogram including the 5 independent predictors was developed to predict the risk of in-hospital MVA. The C-index, equivalent to the area under the ROC curve (AUC), was 0.803 (95% confidence interval [CI]: 0.738-0.868) in the training cohort, and 0.801 (95% CI:0.692-0.911) in the validation cohort, showing that the nomogram had a good discrimination. The HL test (χ²=8.439, P=0.392 in the training cohort; χ²=9.730, P=0.285 in the validation cohort) revealed a good calibration. The DCA suggested an obvious clinical net benefit.

Conclusion

Killip class, CK-MB, serum potassium, NLR, and monocyte were independent factors for in-hospital MVA after PCI in patients with STEMI. The nomogram model constructed based on the above factors to predict the risk of in-hospital MVA had satisfactory discrimination, calibration, and clinical effectiveness, and was an excellent tool for early prediction of the risk of in-hospital MVA after PCI in patients with STEMI.

Construction and evaluation of nomogram model for individualized prediction of risk of major adverse cardiovascular events during hospitalization after percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction

Background

Emergency percutaneous coronary intervention (PCI) in patients with acute ST-segment elevation myocardial infarction (STEMI) helps to reduce the occurrence of major adverse cardiovascular events (MACEs) such as death, cardiogenic shock, and malignant arrhythmia, but in-hospital MACEs may still occur after emergency PCI, and their mortality is significantly increased once they occur. The aim of this study was to investigate the risk factors associated with MACE during hospitalization after PCI in STEMI patients, construct a nomogram prediction model and evaluate its effectiveness.

Methods

A retrospective analysis of 466 STEMI patients admitted to our hospital from January 2018 to June 2022. According to the occurrence of MACE during hospitalization, they were divided into MACE group (n = 127) and non-MACE group (n = 339), and the clinical data of the two groups were compared; least absolute shrinkage and selection operator (LASSO) regression was used to screen out the predictors with non-zero coefficients, and multivariate Logistic regression was used to analyze STEMI Independent risk factors for in-hospital MACE in patients after emergency PCI; a nomogram model for predicting the risk of in-hospital MACE in STEMI patients after PCI was constructed based on predictive factors, and the C-index was used to evaluate the predictive performance of the prediction model; the Bootstrap method was used to repeat sampling 1,000 Internal validation was carried out for the second time, the Hosmer-Lemeshow test was used to evaluate the model fit, and the calibration curve was drawn to evaluate the calibration degree of the model. Receiver operating characteristic (ROC) curves were drawn to evaluate the efficacy of the nomogram model and thrombolysis in myocardial infarction (TIMI) score in predicting in-hospital MACE in STEMI patients after acute PCI.

Results

The results of LASSO regression showed that systolic blood pressure, diastolic blood pressure, Killip grade II-IV, urea nitrogen and left ventricular ejection fraction (LVEF), IABP, NT-ProBNP were important predictors with non-zero coefficients, and multivariate logistic regression analysis was performed to analyze that Killip grade II-IV, urea nitrogen, LVEF, and NT-ProBNP were independent factors for in-hospital MACE after PCI in STEMI patients; a nomogram model for predicting the risk of in-hospital MACE after PCI in STEMI patients was constructed with the above independent predictors, with a C-index of 0.826 (95% CI: 0.785-0.868) having a good predictive power; the results of H-L goodness of fit test showed χ² = 1.3328, P = 0.25, the model calibration curve was close to the ideal model, and the internal validation C-index was 0.818; clinical decision analysis also showed that the nomogram model had a good clinical efficacy, especially when the threshold probability was 0.1-0.99, the nomogram model could bring clinical net benefits to patients. The nomogram model predicted a greater AUC (0.826) than the TIMI score (0.696) for in-hospital MACE after PCI in STEMI patients.

Conclusion

Urea nitrogen, Killip class II-IV, LVEF, and NT-ProBNP are independent factors for in-hospital MACE after PCI in STEMI patients, and nomogram models constructed based on the above factors have high predictive efficacy and feasibility.

D-Dimer-to-Albumin Ratio: A Novel Indicator to Predict Poor Outcomes in Patients with HBV-Associated Decompensated Cirrhosis

BACKGROUND

The purpose of the present study was to investigate the impact of D-dimer-to-albumin ratio (DAR) on outcomes in patients with hepatitis B virus-associated decompensated cirrhosis (HBV-DeCi).

METHODS

A total of 172 HBV-DeCi patients were enrolled. Logistic regression was used to explore the association between DAR and 30-day mortality. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of DAR for predicting mortality.

RESULTS

The 30-day mortality was 19.8%. DAR was clearly higher in the nonsurvivors compared with the survivors, and increasing DAR was associated with an increasing risk of death. DAR was independently associated with mortality and its AUC for mortality was equivalent to that for Model for End-Stage Liver Disease score.

CONCLUSIONS

DAR may be a potential prognostic marker for mortality in HBV-DeCi patients.

A nomogram risk prediction model for no-reflow after primary percutaneous coronary intervention based on rapidly accessible patient data among patients with ST-segment elevation myocardial infarction and its relationship with prognosis

Background

No-reflow occurring after primary percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) can increase the incidence of major adverse cardiovascular events (MACE). The present study aimed to construct a nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients, and to further explore its prognostic utility in this patient population.

Methods

Research subjects included 443 STEMI patients who underwent primary PCI between February 2018 and February 2021. Rapidly available clinical data obtained from emergency admissions were collected. Independent risk factors for no-reflow were analyzed using a multivariate logistic regression model. Subsequently, a nomogram for no-reflow was constructed and verified using bootstrap resampling. A receiver operating characteristic (ROC) curve was plotted to evaluate the discrimination ability of the nomogram model and a calibration curve was used to assess the concentricity between the model probability curve and ideal curve. Finally, the clinical utility of the model was evaluated using decision curve analysis.

Results

The incidence of no-reflow was 18% among patients with STEMI. Killip class ≥2 on admission, pre-operative D-dimer and fibrinogen levels, and systemic immune–inflammation index (SII) were independent risk factors for no-reflow. A simple and quickly accessible prediction nomogram for no-reflow after PCI was developed. This nomogram demonstrated good discrimination, with an area under the ROC curve of 0.716. This nomogram was further validated using bootstrapping with 1,000 repetitions; the C-index of the bootstrap model was 0.706. Decision curve analysis revealed that this model demonstrated good fit and calibration and positive net benefits. Kaplan–Meier survival curve analysis revealed that patients with higher model scores were at a higher risk of MACE. Multivariate Cox regression analysis revealed that higher model score(s) was an independent predictor of MACE (hazard ratio 2.062; P = 0.004).

Conclusions

A nomogram prediction model that can be quickly referred to before surgery to predict the risk for no-reflow after PCI in STEMI patients was constructed. This novel nomogram may be useful in identifying STEMI patients at higher risk for no-reflow and may predict prognosis in this patient population.

Machine learning to predict no reflow and in-hospital mortality in patients with ST-segment elevation myocardial infarction that underwent primary percutaneous coronary intervention

Background

The machine learning algorithm (MLA) was implemented to establish an optimal model to predict the no reflow (NR) process and in-hospital death that occurred in ST-elevation myocardial infarction (STEMI) patients who underwent primary percutaneous coronary intervention (pPCI).

Methods

The data were obtained retrospectively from 854 STEMI patients who underwent pPCI. MLA was applied to predict the potential NR phenomenon and confirm the in-hospital mortality. A random sampling method was used to split the data into the training (66.7%) and testing (33.3%) sets. The final results were an average of 10 repeated procedures. The area under the curve (AUC) and the associated 95% confidence intervals (CIs) of the receiver operator characteristic were measured.

Results

A random forest algorithm (RAN) had optimal discrimination for the NR phenomenon with an AUC of 0.7891 (95% CI: 0.7093–0.8688) compared with 0.6437 (95% CI: 0.5506–0.7368) for the decision tree (CTREE), 0.7488 (95% CI: 0.6613–0.8363) for the support vector machine (SVM), and 0.681 (95% CI: 0.5767–0.7854) for the neural network algorithm (NNET). The optimal RAN AUC for in-hospital mortality was 0.9273 (95% CI: 0.8819–0.9728), for SVM, 0.8935 (95% CI: 0.826–0.9611); NNET, 0.7756 (95% CI: 0.6559–0.8952); and CTREE, 0.7885 (95% CI: 0.6738–0.9033).

Conclusions

The MLA had a relatively higher performance when evaluating the NR risk and in-hospital mortality in patients with STEMI who underwent pPCI and could be utilized in clinical decision making.

D-dimer for risk stratification and antithrombotic treatment management in acute coronary syndrome patients: asystematic review and metanalysis

BACKGROUND

Data on the prognostic role of D-dimer in patients with acute coronary syndrome (ACS) are controversial. Our aim was to summarize current evidence on the association between D-dimer levels and short/long-term poor prognosis of ACS patients. We also investigated the association between D-dimer and no-reflow phenomenon.

METHODS

Systematic review and metanalysis of observational studies including ACS patients and reporting data on D-dimer levels. PubMed and SCOPUS databases were searched. Data were combined with hazard ratio (HR) and metanalysed. The principal endpoint was a composite of cardiovascular events (CVEs) including myocardial infarction, all-cause and cardiovascular mortality.

RESULTS

Overall, 32 studies included in the systematic review with 28,869 patients. Of them, 6 studies investigated in-hospital and 26 studies long-term outcomes. Overall, 23 studies showed positive association of high D-dimer levels with CVEs. D-dimer levels predicted poor prognosis in all studies reporting in-hospital outcomes. Five studies satisfied inclusion criteria and were included in the metanalysis, with a total of 8616 patients. Median follow-up was 13.2 months with 626 CVEs. The pooled HR for D-dimer levels and CVEs was 1.264 (95% CI 1.134-1.409). Five out of 7 studies (4195 STEMI patients) investigating the association between D-dimer levels and no-reflow showed a positive correlation of D-dimer levels with no-reflow.

CONCLUSIONS

In patients with ACS, D-dimer was associated with higher in-hospital and short/long-term complications. D-dimer was also higher in patients with no-reflow phenomenon. The use of D-dimer may help to identify patients with residual thrombotic risk after ACS.

TRIAL REGISTRATION

The review protocol was registered in PROSPERO International Prospective Register of Systematic Reviews: CRD42021267233 .

Low serum albumin levels and in-hospital outcomes in patients with ST segment elevation myocardial infarction

BACKGROUND AND AIMS

Low serum albumin (SA) is associated with an increased risk of long-term adverse events (AEs) among patients with chronic coronary syndromes. Its prognostic role in patients with ST-elevation myocardial infarction (STEMI) is less clear. To investigate the association between low SA and in-hospital AEs in STEMI patients.

METHODS AND RESULTS

Multicenter retrospective cohort study of 220 STEMI patients undergoing primary percutaneous coronary intervention within 12 h from the onset of symptoms. Hypoalbuminemia was defined by serum SA <35 g/L. SA. In-hospital AEs were defined as cardiogenic shock, resuscitated cardiac arrest and death. Median SA was 38 (IQR 35.4-41.0) g/L and 37 (16.8%) patients showed hypoalbuminemia (<35 g/L) on admission. Patients with hypoalbuminemia were older, more frequently women and diabetics, prior CAD and HF. Furthermore, they showed lower hemoglobin levels and impaired renal function. At multivariable logistic regression analysis, diabetes (odds ratio [OR]:4.59, 95% confidence interval [CI] 1.71-12.28, p = 0.002) and haemoglobin (OR:0.52, 95%CI 0.37-0.72, p < 0.001) were associated with low SA. In a subgroup of 132 patients, SA inversely correlated with D-Dimer (rS -0.308, p < 0.001). Globally, twenty-eight (14.6%) AEs were recorded. Hypoalbuminemia (OR:3.43, 95%CI 1.30-9.07, p = 0.013), high-sensitive (HS)-Troponin peak above median (OR:5.41, 95%CI 1.99-14.7, p = 0.001), C-reactive protein (CRP) peak above median (OR:6.03, 95%CI 2.02-18.00, p = 0.001), and in-hospital infection (OR:3.61, 95%CI 1.21-10.80, p = 0.022) were associated with AEs.

CONCLUSION

Low SA levels are associated with worse in-hospital AEs in STEMI patients, irrespective of HS-troponin and CRP plasma levels. Our findings suggest that low SA may contribute to the pro-thrombotic phenotype of these patients.

Prognostic value of the combination of GRACE risk score and mean platelet volume to lymphocyte count ratio in patients with ST-segment elevation myocardial infarction after percutaneous coronary intervention

The Global Registry of Acute Coronary Events (GRACE) risk score and the mean platelet volume to lymphocyte count ratio (MPVLR) can be used independently to predict adverse outcomes in patients with acute coronary syndromes. However, the level of MPVLR in relation to the GRACE score, and whether a combination of these methods can better predict the clinical adverse outcome of patients with ST-segment elevation myocardial infarction (STEMI), have not been previously examined. Therefore, the aim of the present study was to investigate whether the combination of GRACE risk score and MPVLR is a good predictor of a 30-day major adverse cardiovascular events (MACE) in patients with STEMI. A total of 464 patients with STEMI undergoing percutaneous coronary intervention (PCI) were enrolled, and divided into four groups based on the optimal cut-off values for GRACE score and MPVLR. GRACE score and MPVLR levels were separately recorded during admission. Spearman's rank correlation analysis showed a positive correlation between GRACE score and MPVLR (ρ=0.304; P<0.001). Both GRACE score [hazard ratio (HR), 1.706; 95% CI, 1.435-3.058; P<0.001] and MPVLR level (HR, 1.668; 95% CI, 1.202-2.170; P<0.001) were found to be independent predictors of a 30-day MACE. Additionally, the high MPVLR + high GRACE score group of patients had an HR of 2.455 (95% CI, 1.736-3.188) for a 30-day MACE, when using the low MPVLR + low GRACE score group as a reference. Based on the area under the curve, MPVLR combined with GRACE scores achieved an improved performance in differentiating angiographic no-reflow during a 30-day MACE, compared with individual MPVLR and GRACE scores. Therefore, the present results suggested that the GRACE score may be positively correlated with MPVLR and that their combination accurately predicted the occurrence of short-term MACE in patients with STEMI after PCI.

D-Dimer Level Predicts Angiographic No-Reflow Phenomenon After Percutaneous Coronary Intervention Within 2-7 Days of Symptom Onset in Patients with ST-Segment Elevation Myocardial Infarction

It remains uncertain whether plasma D-dimer level can predict no-reflow in patients with STEMI who had pPCI after 48 h of symptom onset. This study retrospectively enrolled 229 consecutive patients who had pPCI for acute STEMI within 2-7 days of symptom onset between January 2008 and December 2018. Patients were divided into no-reflow group (TIMI flow grade 0-2) and reflow group (TIMI flow grade 3). Predictors of no-reflow were assessed by univariate and multivariate binary logistic regression analyses. Plasma D-dimer level can independently predict no-reflow in patients with STEMI who had pPCI within 2-7 days of symptom onset (OR 2.52 per 1 mg/L increase, 95% CI 1.16-5.47, p = 0.019). This finding indicated that pPCI may be safe and feasible for STEMI patients within 2-7 days of symptom onset with low D-dimer level. Graphical Abstract Plasma D-dimer level can independently predict no-reflow in patients with STEMI who had pPCI within 2-7 days of symptom onset. pPCI may be safe and feasible for STEMI patients within 2-7 days of symptom onset with low D-dimer level.

D-dimer level predicts in-hospital adverse outcomes after primary PCI for ST-segment elevation myocardial infarction

BACKGROUND

Use of D-dimer for prognostication of patients with ST-segment elevation myocardial infarction (STEMI) remains controversial and undefined among those with angiographically evident thrombus or no-reflow phenomenon.

METHODS

We retrospectively analyzed consecutive STEMI patients who received primary percutaneous coronary intervention (PCI) at Zhongshan Hospital Fudan University from January 2008 to December 2018. Outcomes were in-hospital major adverse cardiovascular events (MACE: cardiac death, non-fatal acute myocardial infarction, re-vascularization and stroke), peak troponin T and NT-proBNP levels, left ventricular ejection fraction (LVEF) and hospitalization duration.

RESULTS

Among 1165 patients, those with increased (≥0.8 mg/L, n = 224, 19.2%) vs. normal (n = 941, 80.8%) D-dimer level were older; more often women and non-smokers. Increased D-dimer group had similar frequency of AET (58.7% vs. 62.1%, P = .353), more frequently no-reflow phenomenon (13.1% vs. 18.8%, P = .028), higher peak values of troponin T (3.5 [0.9-7.0] vs. 4.5 [1.8-8.7], P = .001) and NT-proBNP (903.3 [532.3-2098.5] vs. 2070.0 [859.1-4378.0], p < .001). In increased D-dimer group, LVEF (53.3 ± 8.3 vs. 48.8 ± 9.8, P < .001) was lower, hospitalization was longer (8.0 ± 4.9 vs. 10.5 ± 6.9 days, P < .001) and risk of developing in-hospital MACE (1.5% vs. 12.1%, P < .001) was greater. D-dimer level was an independent risk factor for MACE (OR 8.408, 95%CI 4.065-17.392, P < .001), including the angiographically evident thrombus (OR 6.939, 95% CI 2.944-16.355, P < .001) and the no-reflow (OR 8.114, 95% CI 1.598-41.196, P = .012) subgroups.

CONCLUSIONS

Increased D-dimer level was an independent risk factor for in-hospital MACE in STEMI patients undergoing primary PCI, including those with angiographically evident thrombus and no-reflow phenomenon. D-dimer was not associated to no-reflow phenomenon in STEMI patients.

Prognostic Value of Pre-Infarction Angina Combined with Mean Platelet Volume to Lymphocyte Count Ratio for No-Reflow and Short-Term Mortality in Patients with ST-Segment Elevation Myocardial Infarction Undergoing Percutaneous Coronary Intervention

Background

The aim of the present study was to investigate the clinical predictive value of pre-infarction angina (PIA) combined with mean platelet volume to lymphocyte count ratio (MPVLR) for no-reflow phenomenon and short-term mortality in patients with ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI).

Material/Methods

A total of 1009 STEMI patients who had undergone PCI were enrolled and subdivided into 4 groups based on the occurrence of PIA and the presence of MPVLR above or below the cutoff value. Analysis of the predictors of the no-reflow phenomenon and 90-day mortality was conducted. Further, evaluation and comparison of the clinical predictive value of PIA, MPVLR, and their combination were done.

Results

Both MPVLR (odds ratio [OR]=1.476, 95% confidence interval [CI]: 1.401 to 1.756, P<0.001; hazard ratio [HR]=1.430, 95% CI: 1.287 to 1.643, P<0.001) and PIA (OR=0.905, 95% CI: 0.783 to 0.986, P<0.001; HR=0.878, 95% CI: 0.796 to 0.948, P<0.001) were independent predictors of no-reflow phenomenon and 90-day mortality. Spearman’s rank correlation test revealed that MPVLR (r=−0.297, P<0.001), monocyte to lymphocyte count ratio (MLR) (r=−0.211, P<0.001) and neutrophil to lymphocyte count ratio (NLR) (r=−0.389, P<0.001) in peripheral blood were significantly negatively correlated with postoperative left ventricular ejection fraction (LVEF). Upon comparing the area under curve (AUC), the MPVLR combined with PIA achieved better performance in differentiating no-reflow phenomenon (AUC=0.847, 95% CI: 0.821 to 0.874) and 90-day mortality (AUC=0.790, 95% CI: 0.725 to 0.855), than the GRACE score, MPVLR and PIA alone, and had similar performance to all other pairwise combinations of the GRACE score, MPVLR and PIA.

Conclusions

High MPVLR and PIA were independent predictors of the no-reflow phenomenon and 90-day mortality in patients with STEMI after PCI. Moreover, Combined application of MPVLR and PIA can effectively predict the occurrence of the no-reflow phenomenon and 90-day mortality.

Systemic Immune-Inflammatory Index Predicts Clinical Outcomes for Elderly Patients with Acute Myocardial Infarction Receiving Percutaneous Coronary Intervention

BACKGROUND We assessed the utility of the systemic immune-inflammatory index (SII) in estimating the in-hospital and long-term prognosis of elderly patients with acute myocardial infarction (AMI) who received percutaneous coronary intervention (PCI). MATERIAL AND METHODS Our study evaluated 711 consecutive elderly patients (age 65-85 years) from January 2015 to December 2017. The correlation between clinical outcomes and SII was analyzed through the stepwise Cox regression analysis and the Kaplan-Meier approach. The clinical endpoints were all-cause mortality and major adverse cardiovascular and cerebrovascular events (MACCE) in-hospital and during 3-year follow-up. RESULTS The study enrolled 711 elderly patients with AMI (66.95% male, 71.99±0.19 years). Kaplan-Meier analysis showed a lower survival rate in patients with higher SII scores, which also predicted in-hospital and long-term (≤3 years) outcomes. In multivariate analyses, SII showed an independent predictive value for in-hospital mortality (hazard ratio (HR), 3.32; 95% confidence interval (CI), 1.55-7.10; p<0.01), in-hospital MACCE (HR, 1.43; 95%CI, 1.02-2.00; p=0.04), long-term mortality (HR, 1.95; 95%CI, 1.23-3.09; p<0.01), along with long-term MACCE (HR, 1.72; 95%CI, 1.23-2.40; p<0.01). Moreover, SII showed a weak but significant positive relationship with the Gensini score among patients developing non-ST-segment elevation myocardial infarction (r=0.18; p<0.01). CONCLUSIONS SII, a readily available laboratory marker, is a potential indicator to predict the clinical endpoints for elderly patients with AMI undergoing PCI.

D-dimer as a potential clinical marker for predicting metastasis and progression in cancer

D-dimer is a widely used biomarker for indicating the activation of coagulation and fibrinolysis, and is reported to serve important roles in cancer progression. The aim of the current retrospective study was to investigate the association of D-dimer plasma level with the development of various cancers. Patients with breast (n=86), gastric (n=317), pancreatic (n=37), colon (n=153) and rectal (n=137) cancers and 92 healthy volunteers were assessed in the present study. Plasma levels of D-dimer in the patients and healthy controls were measured by immunoturbidimetric assays. The association of D-dimer levels with the clinicopathological features of patients were also determined. The plasma levels of D-dimer were significantly higher in patients with breast cancer (P=0.0022), gastric cancer (P<0.0001), pancreatic cancer (P=0.0003), colon cancer (P=0.0001) and rectal cancer (P=0.0028), compared with the healthy controls. It was also determined that the plasma D-dimer levels were positively associated with clinical cancer stage (P<0.05) and metastasis (P<0.05). These findings suggested that the plasma D-dimer level may be used as marker for predicting cancer metastasis and progression.