scholarly journals The Role of Hematological Indices in Patients with Acute Coronary Syndrome

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jan Budzianowski ◽  
Konrad Pieszko ◽  
Paweł Burchardt ◽  
Janusz Rzeźniczak ◽  
Jarosław Hiczkiewicz
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Stratification ◽  
Low Cost ◽  
White Blood Cells ◽  
Distribution Width ◽  
Hematological Indices ◽  
Lymphocyte Ratio ◽  
Coronary Syndrome ◽  
Improve Risk Stratification

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.

2204Predicting the trajectory of depression following an acute coronary syndrome: the role of resilience

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
J H C Smith ◽  
S Toukhsati ◽  
A J P Francis ◽  
V Stavropoulos ◽  
D L Hare
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Stratification ◽  
Depression Scale ◽  
Post Discharge ◽  
Chi Square ◽  
Coronary Syndrome ◽  
Improve Risk Stratification ◽  
Treatment Implementation ◽  
Cardiac Depression ◽  
Class B

Abstract Background Depression is common in patients following an Acute Coronary Syndrome (ACS) substantially increases the risk of future events and mortality. Post-ACS depression typically resembles one of four longitudinal trajectories: chronic; absent; recovered, or delayed depression. Early identification of a patient's post-ACS depression trajectory will improve risk stratification, treatment implementation and risk management. Purpose To explore whether stable psychosocial traits, such as resilience, predict the trajectory of depression one month and 6 months following an ACS admission. Method Consecutive adult ACS patients (STEMI/NSTEMI) admitted to a large general hospital completed the Cardiac Depression Scale (CDS) and the Sense of Coherence scale during their admission, then one and six months following discharge. Results 132 ACS in-patients (males = 111; mean age = 63.13±13.47) satisfied enrolment criteria. Unconditional linear latent growth modelling identified a 3-class model for the trajectory of depression post-ACS (increasing depression; consistent non-depressed; decreasing non-depressed). For the increasing depression class, resilience at baseline was significant and negative compared to the consistent class, b=−0.06, Wald chi square (1) = 4.42, p=0.036 and the decreasing class, b=−0.09, Wald chi square (1) = 7.20, p=0.007. Conclusions Patients who reported lower levels of resilience during an ACS admission were significantly more likely to experience initially high levels of depressive symptoms (CDS ≥85) that exceeded the clinically relevant cut-off (CDS ≥95) at 6 months post-discharge. This study suggests that screening for resilience and depression will improve risk stratification for persistent and delayed depression post-ACS.

scholarly journals Novel predictor of the occurrence of DKA in T1DM patients without infection: A combination of neutrophil/lymphocyte ratio and white blood cells

2021 ◽  
Vol 16 (1) ◽  
pp. 1365-1376
Author(s):  
Yiping Cheng ◽  
Wenhao Yu ◽  
Yuping Zhou ◽  
Tao Zhang ◽  
Haiyan Chi ◽  
...  
Keyword(s):  
Blood Cells ◽  
Low Cost ◽  
Characteristic Curve ◽  
White Blood Cells ◽  
Area Under The Curve ◽  
Control Group ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio

Abstract The role of inflammation has been identified in the pathogenesis of diabetic ketoacidosis (DKA). The neutrophil/lymphocyte ratio (NLR) and white blood cells (WBC) can be used to predict a systemic inflammatory response. Changes in NLR and WBC levels have never been explored in type 1 diabetes mellitus (T1DM) patients with DKA and an uninfected state. This retrospective study included a total of 644 participants. NLR and WBC were measured in the control group (n = 316) and in T1DM patients with mild-DKA (n = 92), severe-DKA (n = 52), and non-DKA (n = 184) in an uninfected state. Then, we assessed the independent predictors of DKA occurrence in T1DM patients in an uninfected state. The diagnostic performance of variables was determined by receiver operating characteristic curve analysis. Serum NLR of T1DM patients is significantly higher than that of normal controls, and if DKA occurs, NLR increases further and increases with the severity of DKA. In addition to diastolic blood pressure, blood urea nitrogen, glycated hemoglobin (HbA1c), and WBC, NLR was also independently associated with DKA in T1DM patients with an uninfected state (OR = 1.386, 95% CI: 1.127–1.705, p = 0.002). Furthermore, the diagnosis analysis showed that except for NLR and WBC, the area under the curve (AUC) of indicators with a statistical difference in patients with and without DKA were 0.747 for DKA diagnosis, and after the addition of NLR and WBC, the AUC was 0.806. The increased NLR level represents a low-cost and highly accessible predictor for DKA in T1DM patients with an uninfected state. The addition of inflammation indicators can play a statistically significant role in the prediction model of the DKA occurrence.

scholarly journals The role of biomarkers in the diagnosis and risk stratification of acute coronary syndrome

2018 ◽  
Vol 4 (1) ◽  
pp. FSO251 ◽  
Author(s):  
Sanoj Chacko ◽  
Sohaib Haseeb ◽  
Benedict M Glover ◽  
David Wallbridge ◽  
Alan Harper
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Stratification ◽  
Coronary Syndrome

scholarly journals Association of Neutrophil Lymphocyte Ratio (NLR) with Global Registry of Acute Coronary Events (GRACE) Scores in Acute Coronary Syndrome

2020 ◽  
Vol 2 (3) ◽  
pp. 162-170
Author(s):  
Baginda Yusuf Siregar ◽  
Refli Hasan ◽  
Rahmad Isnanta
Keyword(s):  
Acute Coronary Syndrome ◽  
Risk Stratification ◽  
Design Data ◽  
Cross Sectional ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Coronary Syndrome ◽  
Coronary Events ◽  
Global Registry ◽  
Grace Score

Background. Inflammation plays an important role in the initiation of atherosclerosis from the beginning of plaque to rupture cause Acute Coronary Syndrome (ACS). Neutrophil Lymphocyte Ratio (NLR) indicator of systemic inflammation in ACS. Risk stratification was needed for assessment and selection of initial invasive strategies and find the best strategy in ACS. The Global Registry of Acute Coronary Events (GRACE) scores recommended risk stratification of ACS. Aims of the study to determine the association and cut-off value NLR with risk stratification GRACE score. Method. This study is analytical with a cross-sectional retrospective design. Data were analyzed after distribution test, then mean difference and correlation test was using the SPPS program where p <0.05 was considered statistically significant. Results. This study showed significantly higher NLR value in the high risk stratification and intermediate-risk compared to low risk stratification (7.9 ± 2.7 vs 3.6 ± 1.7; p=0.001) (5.2 ± 2.3 vs 3.6 ± 1.7; p=0.018). Significant correlation between NLR ​​with GRACE scores (r=0.570; p<0.001). Significant AUC values ​​were obtained (0.782, p <0.001, IK95% 0.674-0.89), and cut-off values NLR 4 ​​with sensitivity (78.8%) and specificity (70.3%) on the GRACE score. Conclusion. The significant association between NLR ​​with GRACE risk score in ACS.

scholarly journals Association of Platelet Lymphocyte Ratio (PLR) and Neutrophil Lymphocyte Ratio (NLR) with Global Registry of Acute Coronary Events (GRACE) Score in Acute Coronary Syndrome

2021 ◽  
Vol 8 (5) ◽  
pp. 1-6
Author(s):  
Baginda Yusuf Siregar ◽  
Refli Hasan ◽  
Rahmad Isnanta
Keyword(s):  
Acute Coronary Syndrome ◽  
High Risk ◽  
Risk Stratification ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Coronary Syndrome ◽  
Platelet Lymphocyte Ratio ◽  
Coronary Events ◽  
Global Registry ◽  
Grace Score

Introduction: Acute Coronary Syndrome (ACS) has morbidity and mortality significantly increase, it requires risk stratification for the assessment and selection of initial invasive strategies. The Global Registry of Acute Coronary Events (GRACE) scores recommended as risk stratification of ACS. Some of studies found that the combination of GRACE scores with other clinical and laboratory parameters can increase predictive value of ACS. Platelet Lymphocyte Ratio (PLR) and Neutrophil Lymphocyte Ratio (NLR) act as parameter of systemic inflammation in ACS. Aims of the study to determine the association between PLR and NLR with risk stratification GRACE score. Method: This study is analytical with a cross-sectional retrospective design. This study included 70 patients with a diagnosis of ACS based on medical record data. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS) 22.0. P-value <0.05 was considered statistically significant. Results: This study was found a positive correlation between PLR and NLR with the GRACE score of patients ACS (r=0.485, p<0.001; r=0.570, p<0.001). The PLR and NLR were both found the significantly higher in the high risk GRACE score respectively (188 ± 47, p < 0.001; 7.9± 2.7, p<0.001). The ROC curve analysis, cutt-off PLR of 123 and above (sensitivity of 72.7 %; specificity of 70.3), while cutt-off NLR of 4 and above (sensitivity of 78.8%; specificity of 70.3%) to detect high risk GRACE score. Conclusion: There is a significant association between PLR and NLR with GRACE score Keywords: Platelet Lymphocyte Ratio, Neutrophil Lymphocyte Ratio, GRACE score, Acute Coronary Syndrome.

The role of plateletcrit and red blood cell distribution width as a predictor of in-hospital mortality in patients with acute coronary syndrome

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Sudharsono ◽  
D Khairina ◽  
A Fajar Muzakkir ◽  
A Hakim Alkatiri ◽  
M.Z Muzakkir Amir
Keyword(s):  
Acute Coronary Syndrome ◽  
Blood Cell ◽  
Hospital Mortality ◽  
Red Blood Cell ◽  
Cell Distribution ◽  
Distribution Width ◽  
Coronary Syndrome ◽  
Grace Score ◽  
Red Blood Cell Distribution

Abstract Introduction Red Blood Cell Distribution Width (RDW CV) and Plateletcrit (PCT) are part of complete blood count (CBC) examination. There are few studies have been reported the use of these parameters to predict clinical outcome including mortality, but none of them conducted in Asian population. We seek to investigate the role of PCT and RDW CV as a potential objective biomarker to predict in hospital mortality coincide with Global Registry of Acute Cardiac Events (GRACE) score in Acute Coronary Syndrome (ACS). Methods We respectively analysed patients with ACS who were admitted to the coronary care unit between June 2018 and December 2019. The GRACE and CBC were taken consecutively. Results A total of 1053 patients with ACS (46% non-ST elevated ACS (NSTE-ACS) and 54% ST elevated myocardial infarction (STEMI)] were enrolled in this study. PCT and RDW-CV was found to be significantly correlated with mortality (p&lt;0.001). Further analysis showed significant higher level of PCT in patients with event compared to the other group (0.32 vs 0.24, p&lt;0.001). Similar result was found for RDW (14.1 vs 13.2, p&lt;0.001). ROC curve analysis for PCT and RDW-CV levels showed an AUC of 0.65, (cut off value: 0.25. p&lt;0.001) and 0.69 (cut off value 13.05, p&lt;0.001), respectively. High PCT and RDW-CV level were found to be a good predictor of mortality in ACS patients. (OR 2.6 and OR 3.4 respectively, p&lt;0.001) In patients with high risk GRACE risk categories, we found a significantly higher levels of PCT (0.27 vs 0.24, p&lt;0.001) and RDW-CV (13.8 vs 13.2, p&lt;0.001) compared to low-intermediate risk group. Conclusion(s) We found that both PCT and RDW-CV may act as novel and promising tool to predict in hospital mortality directly proportional with GRACE Score among ACS patient. Figure 1. ROC curve for PCT and RDW-CV. Funding Acknowledgement Type of funding source: None

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

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Konrad Pieszko ◽  
Jarosław Hiczkiewicz ◽  
Paweł Budzianowski ◽  
Jan Budzianowski ◽  
Janusz Rzeźniczak ◽  
...  
Keyword(s):  
Machine Learning ◽  
Acute Coronary Syndrome ◽  
Red Cell Distribution Width ◽  
Machine Learning Techniques ◽  
Red Cell ◽  
Cell Distribution ◽  
Distribution Width ◽  
Hematological Indices ◽  
Coronary Syndrome ◽  
Grace Score

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.

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