Predictive impact on medium-term mortality of hematological parameters in Acute Coronary Syndromes: added value on top of GRACE risk score

Red blood cell distribution width and mortality risk in critically ill cardiovascular patients

Background

The association between red blood cell distribution width (RDW) and mortality risk in critically ill cardiovascular patients has not been well studied.

Objective

To examine the association between RDW and 30-day all-cause and cause-specific mortality in critically ill cardiovascular patients.

Methods

This cohort study included 47,266 patients from the eICU database. RDW was categorized as <13.0 %, 13.0-13.4 %, 13.5-13.9 %, 14.0-14.4 %, 14.5-14.9 %, ≥15.0 %. Logistic regression model was used to estimate adjusted odds ratios (ORs), and log-linear regression model was used to examine absolute rate differences (RDs) in mortality risk. Cubic spline curve was used to explore the nonlinear association between changes in RDW and mortality.

Results

A graded association between higher RDW and incremental risk of death was observed. Compared with RDW of <13.0 %, the adjusted odds ratios for all-cause mortality were 1.29 (95 % CI, 1.10 to 1.53) for RDW of 13.5-13.9 %, 1.57 (95 % CI, 1.33 to 1.85) for RDW of 14.0-14.4 %, 1.94 (95 % CI, 1.64 to 2.29) for RDW of 14.5-15.0 %, and 3.15 (95 % CI, 2.74 to 3.63) for RDW of ≥15.0 %. The absolute rate differences for RDW of 13.5-13.9 %, 14.0-14.4 %, 14.5-14.9 %, and ≥15.0 % indicated an additional 6, 13, 14, and 40 deaths per 1000 patients, respectively. RDW was associated with most, but not all, cause-specific deaths.

Conclusion

RDW was strongly associated with all-cause mortality and most cause-specific mortality in critically ill cardiovascular patients. These findings underscore the importance of this readily available hematologic indicator in mortality risk stratification.

The predictive value of machine learning for mortality risk in patients with acute coronary syndromes: a systematic review and meta-analysis

BACKGROUND

Acute coronary syndromes (ACS) are the leading cause of global death. Optimizing mortality risk prediction and early identification of high-risk patients is essential for developing targeted prevention strategies. Many researchers have built machine learning (ML) models to predict the mortality risk in ACS patients. Our meta-analysis aimed to evaluate the predictive value of various ML models in predicting death in ACS patients at different times.

METHODS

PubMed, Embase, Web of Science, and Cochrane Library were searched systematically from database establishment to March 12, 2022 for studies developing or validating at least one ML predictive model for death in ACS patients. We used PROBAST to assess the risk of bias in the reported predictive models and a random-effects model to assess the pooled C-index and accuracy of these models.

RESULTS

Fifty papers were included, involving 216 ML prediction models, 119 of which were externally validated. The combined C-index of the ML models in the validation cohort predicting the in-hospital mortality, 30-day mortality, 3- or 6-month mortality, and 1 year or above mortality in ACS patients were 0.8633 (95% CI 0.8467-0.8802), 0.8296 (95% CI 0.8134-0.8462), 0.8205 (95% CI 0.7881-0.8541), and 0.8197 (95% CI 0.8042-0.8354), respectively, with the corresponding combined accuracy of 0.8569 (95% CI 0.8411-0.8715), 0.8282 (95% CI 0.7922-0.8591), 0.7303 (95% CI 0.7184-0.7418), and 0.7837 (95% CI 0.7455-0.8175), indicating that the ML models were relatively excellent in predicting ACS mortality at different times. Furthermore, common predictors of death in ML models included age, sex, systolic blood pressure, serum creatinine, Killip class, heart rate, diastolic blood pressure, blood glucose, and hemoglobin.

CONCLUSIONS

The ML models had excellent predictive power for mortality in ACS, and the methodologies may need to be addressed before they can be used in clinical practice.

Acute Myocardial Infarction (AMI) as the Effect Modifiers to Modify the Association Between Red Blood Cell Distribution Width (RDW) and Mortality in Critically Ill Patients With Stroke

Background and Objectives

Few studies have evaluated the impact of red blood cell distribution width (RDW) on prognosis for critically ill patients with acute stroke according to recent studies. The aim of this study was to investigate the association between RDW and mortality in these patients.

Methods

Clinical data were extracted from the eICU Collaborative Research Database (eICU-CRD) and analyzed. The exposure of interest was RDW measured at admission. The primary outcome was in-hospital mortality. Binary logistic regression models and interaction testing were performed to examine the RDW-mortality relationship and effect modification by acute myocardial infarction and hypertension (HP).

Results

Data from 10,022 patients were analyzed. In binary logistic regression analysis, after adjusting for potential confounders, RDW was found to be independently associated with in-hospital mortality {odds ratio (OR) 1.07, [95% confidence interval (CI) 1.03 to 1.11]; p = 0.001}. Higher RDW linked to an increase in mortality (OR, 1.07; 95% CI, 1.03 to 1.11; P for trend < 0.0001). Subgroup analysis showed that, in patients combined with AMI and without HP (both P-interaction <0.05), the correlation between RDW and in-hospital mortality is stronger (AMI group: OR, 1.30; 95% CI, 1.07 to 1.58, not the AMI group: OR, 1.06; 95% CI, 1.02, 1.10; the HP group: OR,.98; 95% CI,.91 to 1.07, not the HP group: OR, 1.09; 95% CI, 1.05 to 1.14).

Conclusions

A higher baseline RDW is independently correlated with prognosis in critically ill patients with acute stroke, and the correlation can be modified by AMI and HP duration.

Admission high‐sensitivity C‐reactive protein levels improve the Grace risk score prediction on in‐hospital outcomes in acute myocardial infarction patients

Background

Methods

Results

Conclusion

Should haematological inflammatory markers be included as an adjuvant in the differential diagnosis of acute scrotal pathologies?

The aim of this study was to determine discriminative role of haematological inflammatories between acute scrotal pathologies and malignancies. In addition, it was aimed to search for a predictive marker of testicular survival in the TT group. Medical data of 141 patients with acute scrotal pathology and 63 TTm patients who presented to our clinic between January 2015 and July 2019 were retrospectively reviewed and compared in terms of haematological values and demographic parameters following the inclusion of 92 healthy controls. In the TTm group, NLR was the discriminative parameter with a median of 2.42 (0.25-8.42), whereas discriminative median values of MCV for TT and CRP for EO were 83.65 (56.9-98.16) and 59.5 (2.9-337) respectively. NLR, PLR, MER and RDW values were statistically lower in the control group compared to the patients groups. In TT subgroup analysis, monocyte count, MER and CRP were found to be statistically higher in the orchiectomy group, while multivariate logistic regression analysis performed for testicular viability revealed monocyte count to be the only significant variable (Odds Ratio [95% Confidence Interval] = 0.046 (0.006-0.366), p<0.004). While our study demonstrated both diagnostic and discriminative values of haematological parameters, it also showed that monocyte count could predict testicular salvage in TT patients. However, further prospective studies are required.

Predictive Role of Platelet-Associated Indices on Admission and Discharge in the Long-Term Prognosis of Acute Coronary Syndrome Patients

Our study aimed to investigate the association between platelet indices and their in-hospital change and long-term prognosis in acute coronary syndrome (ACS). Data from a randomized controlled trial (NCT02927808) recruiting ACS patients were analyzed (survival analysis). The examined variables were platelet count (PC), mean platelet volume (MPV), platelet distribution width (PDW), and plateletcrit (PCT) on admission and discharge, as well as their alteration during hospitalization. The primary endpoint was major adverse cardiac events (MACE) (cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke or hospitalization for unstable angina) and all-cause mortality, while secondary endpoints were all-cause hospitalization and bleeding events. The study included 252 patients with a follow-up of 39 (28-45) months. In the univariate analysis, MACE was associated with discharge PC [hazard ratio (HR) 2.20, 95% confidence interval (CI) 1.10-4.40], discharge MPV (HR 0.48, 95% CI 0.25-0.94), and in-hospital PC difference (HR 0.25, 95% CI 0.13-0.51). In the multivariable analysis, only in-hospital PC decrease correlated with lower MACE incidence (adjusted HR .27, 95% CI 0.14-0.54) and lower all-cause hospitalization risk (adjusted HR 0.36, 95% CI 0.19-0.68). PC reduction during hospitalization for ACS is an independent predictor of better prognosis.

Value of Hematological and Coagulation Parameters as Prognostic Factors in Acute Coronary Syndromes

The values of hematological and coagulation biomarkers were evaluated as predictors of in hospital mortality and complications, in patients with acute coronary syndromes (ACS). This retrospective observational study enrolled 936 ACS subjects admitted to the Clinical Emergency Hospital of Oradea, Romania, between January-December 2019. Hematological and coagulation parameters were obtained at admission. During hospitalization, the following adverse events were recorded: death, ventricular rhythm disturbances, atrial fibrillation, heart failure, re-infarction, and stroke. Accuracy of hematological and coagulation parameters as predictors of adverse outcome were also evaluated. The diagnosis was unstable angina in 442 patients (47.22%), non-ST-elevation myocardial infarction (NSTEMI) in 113 patients (12.1%) and ST-elevation myocardial infarction (STEMI) in 381 patients (40.70%); 87 patients (9.29%) died during hospitalization and 193 (20.7%) developed complications. Predictors for in hospital mortality were as follows: red cell distribution width (RDW) (AUC 0.691, p < 0.0001), white blood cells (WBC) (AUC 0.684, p < 0.0001), neutrophils (NEU) (AUC 0.684, p < 0.0001), and prothrombin time (PT) (AUC 0.765, p < 0.0001). WBC (AUC 0.659, p < 0.0001), NEU (AUC 0.664, p < 0.0001), RDW (AUC 0.669, p < 0.0001), and PT (AUC 0.669, 95% CI 0.622-0.714, p < 0.0001) also had accuracy for complications prediction. RDW had a good ability to predict heart failure in NSTEMI patients (AUC 0.832, p < 0.0001). An acceptable ability to predict ventricular rhythm disturbances occurrence had WBC (AUC 0.758, p < 0.0001) and NEU (AUC 0.772, p < 0.0001). Hematological and coagulation parameters can help in risk stratification of ACS patients. RDW, WBC, NEU, and PT were able to predict mortality and in-hospital complications in ACS patients. RDW has a good accuracy in predicting complications and heart failure in NSTEMI patients. WBC and NEU are good predictors for ventricular rhythm disturbances.

Diagnostic and prognostic value of circulating miRNA-499 and miRNA-22 in acute myocardial infarction

BACKGROUND

Currently, acute myocardial infarction (AMI) represents a serious cardiovascular disease with high morbidity and mortality. Therefore, this study aimed to systematically evaluate the roles of miRNA-499 and miRNA-22 as potential biomarkers for AMI.

METHODS

According to the inclusion and exclusion criteria, we measured circulating levels of miRNAs in 50 AMI patients and 50 non-MI populations. The expression levels of plasma miRNA-499 and miRNA-22 were analyzed by real-time fluorescent quantitative polymerase chain reaction (qRT-PCR). A statistical analysis of clinical data of AMI patients was conducted by 90-day follow-up.

RESULTS

Real-time PCR analysis showed that the relative expression level of miRNA-499 increased gradually among the three groups (P < .05). However, the expression of miRNA-22 showed a downward trend (P < .05). According to logistic analysis, the relative levels of miRNA-499 and miRNA-22 were important predictors of AMI. When the miRNA-499 and miRNA-22 levels were 0.377 and 0.946 separately, the diagnostic value of miRNA-499 and miRNA-22 for AMI was 86.00% and 86.00% for sensitivity, and 98.00% and 94.00% for specificity, respectively. In addition, compared to the baseline GRACE scoring system, the combination of miRNA-499, miRNA-22, and GRACE scores had a stronger discriminating power for MACE occurrence, with a sensitivity of 100.00% and a specificity of 79.40%.

CONCLUSIONS

The results showed that plasma miRNA-499 and miRNA-22 were more sensitive and specific for the diagnosis of AMI, suggesting that they can be used as potential biomarkers for clinical diagnosis of AMI.

Evaluation of a novel score for predicting 2-year outcomes in patients with acute coronary syndrome after percutaneous coronary intervention

BACKGROUND

A novel risk model to predict long-term mortality in patients with acute coronary syndrome (ACS), derived from the EPICOR (long-term follow-up of antithrombotic management patterns in acute coronary syndrome patients) registry, has been released recently and its performance remains to be assessed. The objective is to evaluate the EPICOR score for 2-year mortality risk in ACS patients after percutaneous coronary intervention (PCI).

METHODS

From January to December in 2013, a total of 6087 consecutive patients presenting with ACS who were scheduled for PCI were enrolled. Use online simplified EPICOR calculator to assess the expected risk of death.

RESULTS

Sixty-eight patients (1.1%) died during 2-year follow-up. The areas under the receiver operating characteristics curve for mortality in the overall population, ST-segment elevation myocardial infarction (STEMI), and non-ST-segment elevation ACS were 0.712 (95% CI, 0.650-0.772; p < 0.001), 0.790 (95% CI, 0.676-0.903; p < 0.001), and 0.683 (95% CI, 0.615-0.751; p < 0.001), respectively. Moreover, it was noninferior to the updated Global Registry of Acute Coronary Events (GRACE) risk score. Patients were stratified into three categories: low-risk (n = 3382), medium-risk (n = 2547), and high-risk (n = 158). Kaplan-Meier curve demonstrated significant ongoing divergence in both mortality (0.6% vs 1.3% vs 9.5%; p < 0.001) and major adverse cardiovascular and cerebrovascular events (MACCEs) (11.8% vs 12.3% vs 19.6%; p = 0.014) among them. Multivariate Cox analysis revealed that medium- and high-risk groups predicted 2- and 12-fold hazards of death comparing to the lowest. Yet, it was not a significant predictor for MACCEs after adjusting confounding factors.

CONCLUSION

The simplified EPICOR score showed fair discriminatory power of 2-year mortality in patients with ACS and an improved performance in the STEMI subgroup. It could aid in risk stratification of ACS patients as an independent predictor.

The diagnostic and prognostic value of red cell distribution width in cardiovascular disease; current status and prospective

The red blood cell distribution width (RDW) is an index of the heterogeneity of circulating red blood cell size, which along with other standard complete blood count (CBC) parameters are used to identify hematological system diseases. Besides hematological disorders, several clinical studies have shown that an increased in the RDW may be associated with other diseases including acute pancreatitis, chronic kidney disease, gastrointestinal disorders, cancer, and of special interest in this review, cardiovascular disease (CVD). The diagnostic and prognostic value of RDW in different CVD (acute coronary syndrome, ischemic cerebrovascular disease, peripheral artery disease, atrial fibrillation, heart failure, and acute ischemic stroke) has been reviewed in this article, to provide an understanding how its measurement may be applied to improve the management of these conditions.

Predicting Long-Term Mortality after Acute Coronary Syndrome Using Machine Learning Techniques and Hematological Markers

Introduction

Hematological indices including red cell distribution width and neutrophil to lymphocyte ratio are proven to be associated with outcomes of acute coronary syndrome. The usefulness of machine learning techniques in predicting mortality after acute coronary syndrome based on such features has not been studied before.

Objective

We aim to create an alternative risk assessment tool, which is based on easily obtainable features, including hematological indices and inflammation markers.

Patients and Methods

We obtained the study data from the electronic medical records of 5053 patients hospitalized with acute coronary syndrome during a 5-year period. The time of follow-up ranged from 12 to 72 months. A machine learning classifier was trained to predict death during hospitalization and within 180 and 365 days from admission. Our method was compared with the Global Registry of Acute Coronary Events (GRACE) Score 2.0 on a test dataset.

Results

For in-hospital mortality, our model achieved a c-statistic of 0.89 while the GRACE score 2.0 achieved 0.90. For six-month mortality, the results of our model and the GRACE score on the test set were 0.77 and 0.73, respectively. Red cell distribution width (HR 1.23; 95% CL 1.16-1.30; P < 0.001) and neutrophil to lymphocyte ratio (HR 1.08; 95% CL 1.05-1.10; P < 0.001) showed independent association with all-cause mortality in multivariable Cox regression.

Conclusions

Hematological markers, such as neutrophil count and red cell distribution width have a strong association with all-cause mortality after acute coronary syndrome. A machine-learned model which uses the abovementioned parameters can provide long-term predictions of accuracy comparable or superior to well-validated risk scores.

Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes

BACKGROUND

Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in predicting short-term outcomes of acute coronary syndrome (ACS).

METHODS

We analyzed the predictive importance of laboratory and clinical features in 6769 hospitalizations of patients with ACS. Two binary classifications were considered: significant coronary lesion (SCL) or lack of SCL, and in-hospital death or survival. SCL was observed in 73% of patients. In-hospital mortality was observed in 1.4% of patients and it was higher in the case of patients with SCL. Ensembles of decision trees and decision rule models were trained to predict these classifications.

RESULTS

The best performing model for in-hospital mortality was based on the dominance-based rough set approach and the full set of laboratory as well as clinical features. This model achieved 81 ± 2.4% sensitivity and 81.1 ± 0.5% specificity in the detection of in-hospital mortality. The models trained for SCL performed considerably worse. The best performing model for detecting SCL achieved 56.9 ± 0.2% sensitivity and 66.9 ± 0.2% specificity. Dominance rough set approach classifier operating on the full set of clinical and laboratory features identifies presence or absence of diabetes, systolic and diastolic blood pressure and prothrombin time as having the highest confirmation measures (best predictive value) in the detection of in-hospital mortality. When we used the limited set of variables, neutrophil count, age, systolic and diastolic pressure and heart rate (taken at admission) achieved the high feature importance scores (provided by the gradient boosted trees classifier) as well as the positive confirmation measures (provided by the dominance-based rough set approach classifier).

CONCLUSIONS

Machine learned models can rely on the association between the elevated inflammatory markers and the short-term ACS outcomes to provide accurate predictions. Moreover, such models can help assess the usefulness of laboratory and clinical features in predicting the in-hospital mortality of ACS patients.

Blood homocysteine levels could predict major adverse cardiac events in patients with acute coronary syndrome: A STROBE-compliant observational study

The Global Registry of Acute Coronary Events (GRACE) risk score independently predicts major adverse cardiac events (MACEs) in patients with acute coronary syndrome (ACS). This study aims to evaluate whether the level of plasma homocysteine in addition to the GRACE score enhances the predictive value for MACEs in patients with acute coronary syndrome.A total of 361 patients with ACS evaluated at our hospital were included in the study and tested for blood homocysteine levels. We recorded 40 (11.1%) instances of MACE during a median follow-up of 43.3 months (quartile 40.6-44.4 months), including 29 cases (8.0%) of all-cause death and 11 cases (3.1%) of nonfatal myocardial infarction.The GRACE score was significantly associated with homocysteine levels, and multivariate Cox regression analysis showed that both the GRACE risk score and homocysteine content were independent predictors of MACEs (HR 2.63; 95% confidence interval (CI) 1.54 to 4.49; P < .001 and 2.27; 1.06 to 4.86; P = .035, respectively). Moreover, meta-analysis showed that as the homocysteine level increased, the incidence of MACEs also increased (log-rank 8.41; P = .015). GRACE scores adjusted by homocysteine level increased the area under the curve (AUC) from 0.78 to 0.83 (P = 0.006).Blood homocysteine levels are significantly associated with the GRACE risk score, and using both parameters can further improve risk stratification in patients with acute coronary syndrome.

The Role of Hematological Indices in Patients with Acute Coronary Syndrome

An increased systemic and local inflammation plays a key role in the pathophysiology of acute coronary syndrome (ACS). This review will discuss the role of hematological indices: white blood cells (WBC), neutrophil to lymphocyte ratio (NLR), red cell distribution width (RDW), and platelet indices, that is, platelet to lymphocyte ratio (PLR), mean platelet volume (MPV), and platelet distribution width (PDW) in the case of ACS. In recent years, a strong interest has been drawn to these indices, given that they may provide independent information on pathophysiology, risk stratification, and optimal management. Their low-cost and consequent wide and easy availability in daily clinical practice have made them very popular in the laboratory testing. Furthermore, many studies have pointed at their effective prognostic value in all-cause mortality, major cardiovascular events, stent thrombosis, arrhythmias, and myocardial perfusion disorders in terms of acute myocardial infarction and unstable angina. The most recent research also emphasizes their significant value in the combined analysis with other markers, such as troponin, or with GRACE, SYNTAX, and TIMI scores, which improve risk stratification and diagnosis in ACS patients.

Prevalence of Conventional Risk Factors and Evaluation of Baseline Indices Among Young and Elderly Patients with Coronary Artery Disease

INTRODUCTION

Coronary Artery Disease (CAD) is a leading cause of morbidity and mortality worldwide, manifesting in a variety of clinical spectrums such as an asymptomatic disease or acute coronary syndrome. It has become highly prevalent in Southeast Asia, including Pakistan. There has been little work done on the prevalence of traditional risk factors in different age groups and genders and there is a dire need to gauge the importance of baseline indices in CAD patients.

AIM

To determine the prevalence of conventional risk factors and evaluate the variations in lipid profiles, electrolyte levels and haematological indices among patients with CAD in different age groups and gender.

MATERIALS AND METHODS

This cross-sectional study was carried out in a Tertiary Care Hospital in Karachi, Sindh, Pakistan from January to June 2016, among patients with CAD. We recorded the presence of conventional risk factors and baseline indices within the first 24 hours of admission. Continuous variables were compared using Independent t-test or Mann-Whitney test and categorical variables were compared using chi-square or Fisher's exact test.

RESULTS

The most frequent risk factor was dyslipidemia (91.2%), followed by hypertension (70.4%), diabetes (51.2%), family history of CAD (40.0%) and smoking (29.2%). Total of 98.4% of patients had at least one risk factor. Diabetes and hypertension were found to be common in females; whereas, smoking was predominantly present in males. Diabetes and dyslipidemia were mostly encountered in elderly patients. The most frequent lipid alteration was low levels of High Density Lipoprotein (HDL). Cholesterol and HDL levels were found to be higher in females than males. Elderly patients had lower levels of HDL and higher levels of Cholesterol. The levels of haematological indices were found to be higher in males and younger patients. The median levels of serum sodium and potassium were found to be higher in elderly patients.

CONCLUSION

Our study findings corroborate with the findings from previous studies regarding the significance of risk factors in causing cardiovascular pathology. Medical interventions and dietary control to improve body's lipid status would be indispensable in the prevention of CAD. Deranged electrolyte levels necessitate correction of body electrolyte parameters as an adjunct in prevention strategies.

[Regression analysis of red cell distribution width and mean platelet volume in patients with acute myocardial infarction]

OBJECTIVE

To investigate clinical implications of changes in red cell distribution width (RDW) and mean platelet volume (MPV) in patients with acute myocardial infarction.

METHODS

A total of 127 patients (90 men and 37 women) were enrolled in this analysis, including 66 with acute myocardial infarction (AMI) and 61 with unstable angina (UA). The patients' baseline demographic and clinical data were compared between the two groups including age, hypertension, diabetes, smoking, BMI, blood biochemical profiles, cardiac functions and platelet and red blood cell parameters. The patients were further divided into subgroups according to the RDW 50% cumulative frequency, and the MPV, P-LCR, hsCRP, NT-proBNP, RBC, Dimer and MCV were compared. The correlations between platelet and erythrocyte test results were evaluated in both the AMI and UA patients. Regression analysis was performed to identify the factors affecting the RDW in the AMI group and a regression model was established.

RESULTS

The platelet and red blood cell test results, P-LCR, MPV, and RDW differed significantly between AMI and UA groups (P<0.01 or 0.05). Correlation analysis showed a significant positive correlation between RDW and MPV in AMI group (r=0.34, P<0.01). Between the subgroups with different RDW 50% cumulative frequencies, MPV, P-LCR, hsCRP, D-Dimer, and NT-proBNP all differed significantly (P<0.05 or 0.01). In AMI group, with RDW as the dependent variable, we established a multivariate regression model of RDW=0.19MPV+10.83.

CONCLUSION

RDW and MPV are closely correlated in patients with AMI. In multiple regression analysis, MPV can explain the changes in RDW in patients with AMI.

Red blood cell distribution width and cardiovascular diseases

BACKGROUND

The red blood cell distribution width (RDW) is a rather simple measure of red blood cell (RBC) size heterogeneity (i.e., anisocytosis), which is easily calculated by dividing the standard deviation (SD) of erythrocyte volumes for the mean corpuscular volume (MCV). Emerging evidence suggests that, besides RBC abnormalities, many human disorders may be frequently associated with a high degree of anisocytosis.

METHODS

In this narrative review, we analyzed the current scientific literature about the putative role and the potential epidemiologic association between RDW and cardiovascular diseases. The findings of the most representative epidemiological studies were summarized and discussed.

RESULTS

Overall, considerable and convincing evidence has been brought that an increased RDW value is associated with acute coronary syndrome (ACS) [including acute myocardial infarction (AMI)], ischemic cerebrovascular disease (including stroke), peripheral artery disease (PAD), as well as with atrial fibrillation (AF), heart failure (HF) and hypertension. Higher anisocytosis also significantly and independently predicts adverse outcomes in patients with these conditions.

CONCLUSIONS

Although the role of anisocytosis in the pathogenesis of cardiovascular diseases remains uncertain, the considerable evidence available so far suggests that the clinical use of RDW may be broadened beyond the conventional boundaries of erythrocyte disorders, in particular for assisting the diagnosis and prognostication of patients with ACS, ischemic cerebrovascular disease, PAD, HF and AF.

The Prognostic Role of Red Blood Cell Distribution Width in Coronary Artery Disease: A Review of the Pathophysiology

Red blood cell distribution width (RDW) is a measure of red blood cell volume variations (anisocytosis) and is reported as part of a standard complete blood count. In recent years, numerous studies have noted the importance of RDW as a predictor of poor clinical outcomes in the settings of various diseases, including coronary artery disease (CAD). In this paper, we discuss the prognostic value of RDW in CAD and describe the pathophysiological connection between RDW and acute coronary syndrome. In our opinion, the negative prognostic effects of elevated RDW levels may be attributed to the adverse effects of independent risk factors such as inflammation, oxidative stress, and vitamin D₃ and iron deficiency on bone marrow function (erythropoiesis). Elevated RDW values may reflect the intensity of these phenomena and their unfavorable impacts on bone marrow erythropoiesis. Furthermore, decreased red blood cell deformability among patients with higher RDW values impairs blood flow through the microcirculation, resulting in the diminution of oxygen supply at the tissue level, particularly among patients suffering from myocardial infarction treated with urgent revascularization.

Adjustment of the GRACE score by HemoglobinA1c enables a more accurate prediction of long-term major adverse cardiac events in acute coronary syndrome without diabetes undergoing percutaneous coronary intervention

Background

The Global Registry of Acute Coronary Events (GRACE) risk score is widely recommended for risk assessment in patients with acute coronary syndrome (ACS). Chronic hyperglycemia [hemoglobinA1c (HbA1c)] can independently predict major adverse cardiac events (MACEs) in patients with ACS. We investigated whether the prediction of MACEs with the GRACE score could be improved with the addition of HbA1c content in ACS patients without diabetes mellitus (DM) undergoing percutaneous coronary intervention (PCI).

Methods

We enrolled 549 ACS patients without DM who underwent PCI. The GRACE score and HbA1c content were determined on admission. Correlation was analyzed by Spearman’s rank correlation. Cumulative MACE curve was calculated using the Kaplan–Meier method. Multivariate Cox regression was used to identify predictors of MACEs. Additionally, the predictive value of HbA1c content alone and combined with GRACE score was estimated by the area under the receiver-operating characteristic curve (AUC), continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

Results

During a median of 42.3 months (interquartile range 39.3–44.2 months), 16 (2.9 %) were lost to follow-up, and patients experienced 69 (12.9 %) MACEs: 51 (9.6 %) all-cause deaths and 18 (3.4 %) nonfatal myocardial infarction cases. The GRACE score was positively associated with HbA1c content. Multivariate Cox analysis showed that both GRACE score and HbA1c content were independent predictors of MACEs (hazard ratio 1.030; 95 % CI 1.020–1.040; p < 0.001; 3.530; 95 % CI 1.927–6.466; p < 0.001, respectively). Furthermore, Kaplan–Meier analysis demonstrated increased risk of MACEs with increasing HbA1c content (log-rank 33.906, p < 0.001). Adjustment of the GRACE risk estimate by HbA1c improved the predictive value of the GRACE score [increase in AUC from 0.75 for the GRACE score to 0.80 for the GRACE score plus HbA1c, p = 0.012; IDI = 0.055, p < 0.001; NRI (>0) = 0.70, p < 0.001].

Conclusions

HbA1c content is positively associated with GRACE risk score and their combination further improved the risk stratification for ACS patients without DM undergoing PCI.

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-015-0274-4) contains supplementary material, which is available to authorized users.

Relation of platelet indices to severity of coronary artery disease in patients undergoing primary percutaneous coronary intervention

AIM

We investigated the association between platelet indices and the severity of coronary artery disease (CAD) in patients with ST-segment-elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PPCI).

METHODS

A total of 484 consecutive patients who were routinely referred to coronary angiography for STEMI and 81 age- and gender-matched patients with normal coronary arteries were included in the present study. We analyzed the relation between the platelet distribution width (PDW) and the angiographic severity of CAD. The SYNTAX score was used for assessing the severity of coronary atherosclerosis.

RESULTS

The mean platelet volume (MPV), the plateletcrit (PCT) and the neutrophil levels were significantly higher in the STEMI group than in the control group. Patients with an elevated SYNTAX score (>32) had higher PDW values. The levels of plateletcrit and the estimated glomerular filtration rate (eGFR) were lower in the high SYNTAX score group compared to the moderate-to-low SYNTAX score group. The PDW was positively correlated with age (r = 0.128, p=0.004) and SYNTAX score (r = 0.209, p<0.001). There was a mild, significant inverse association between the PDW level and the eGFR (r = -0.101, p=0.049), the mean platelet volume (MPV) (r = -290, p<0.001) and the PCT (r = -345, p<001). Using multivariate logistic regression analysis, we found that age (OR = 1.046, 95% CI 1.013-1.079, p=0.005), diabetes (OR = 4.779, 95% CI 2.339-9.767, p<0.001) and PDW (OR = 1.229, 95% CI 1.072-1409, p=0.003) were independent correlates of high SYNTAX score.

CONCLUSION

Platelet distribution width, an inexpensive and easily measurable laboratory variable, is independently associated with high SYNTAX score.