Platelet, Neutrophil and Lymphocyte Quantitative Abnormalities in Patients with Heart Failure: A Retrospective Study

Getawa, Solomon; Bayleyegn, Biruk

doi:10.2147/vhrm.s394765

Cited by 11 publications

(8 citation statements)

References 46 publications

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“…Similarly, in another study, it was found that neutrophilia and lymphocytosis were the most leukocyte abnormalities in patients with HF. It was also found to be significantly associated with neutrophilia, especially in female patients with HF [36]. In our current study, the AI LGMB models employed in our present investigation have demonstrated that NEU is the most hematological parameter for predicting AMI.…”

Section: Discussionsupporting

confidence: 61%

Assessment of Hematological Predictors via Explainable Artificial Intelligence in the Prediction of Acute Myocardial Infarction

Yilmaz,

Yagin,

Raza

et al. 2023

IEEE Access

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Acute myocardial infarction (AMI) is the main cause of death in developed and developing countries. AMI is a serious medical problem that necessitates hospitalization and sometimes results in death. Patients hospitalized in the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Many studies have been conducted on the prognosis of AMI with hemogram parameters. However, no study has investigated potential hemogram parameters for the diagnosis of AMI using an interpretable artificial intelligence-based clinical approach. The purpose of this research is to implement the principles of explainable artificial intelligence (XAI) in the analysis of hematological predictors for AMI. In this retrospective analysis, 477 (48.6%) patients with AMI and 504 (51.4%) healthy individuals were enrolled and assessed in predicting AMI. Of the patients with AMI, 182 (38%) had an ST-segment elevation MI (STEMI), and 295 (62%) had a non-ST-segment elevation MI (NSTEMI). Demographic and hematological information of the patients was analyzed to determine AMI. The XAI approach combined with machine learning approaches (Extreme Gradient Boosting, XGB; Adaptive Boosting, AB; Light Gradient Boosting Machine, LGBM) was applied for the estimation of AMI and distinguishing subgroups of AMI (STEMI and NSTEMI). The SHAP approach was used to explain the predictions intuitively. After selecting the 10 most important hematological parameters for AMI, the LGBM model achieved 83% and 74% accuracy for prediction of AMI, and distinguishing subgroups of AMI (STEMI and NSTEMI), respectively. SHAP results showed that neutrophil (NEU), white blood cell (WBC), platelet width of distribution (PDW), and basophil (BA) were the most important for AMI prediction. Mean corpuscular volume (MCV), BA, monocytes (MO), and lymphocytes (LY) were the most important hematological parameters that distinguish STEMI from NSTEMI. The proposed model serves as a valuable tool for physicians, facilitating the diagnosis, treatment, and follow-up of patients with AMI and distinguishing subgroups of AMI (STEMI and NSTEMI). Analyzing readily accessible hemogram parameters empowers medical professionals to make informed decisions and provide enhanced care to a wide range of individuals.

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Section: Discussionsupporting

confidence: 61%

Assessment of Hematological Predictors via Explainable Artificial Intelligence in the Prediction of Acute Myocardial Infarction

Yilmaz,

Yagin,

Raza

et al. 2023

IEEE Access

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“…In addition, comorbidities commonly present in patients with CHF, such as diabetes mellitus, CKD, hypertension, obesity, liver disease, and COPD, are themselves associated with increased inflammation [ 39 ]. Hematologic manifestations of inflammatory pathway activation include lymphopenia and elevations of neutrophils and platelets [ 25 , 26 , 49 , 50 , 51 , 52 , 53 ], the latter two cells being important mediators of inflammation through their release of pro-inflammatory cytokines [ 54 , 55 , 56 ]. Lindeman et al and others have demonstrated that platelets produce and release IL 1β under the right conditions [ 57 , 58 ].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, the activity and functional interrelationships among platelets, neutrophils, and lymphocytes have been associated with clinical outcomes in patients with cardiovascular disease [ 54 , 55 , 56 ]. The ratios between these three cell populations, such as the NLR and PLR, both easily obtained through routine blood work, may serve as surrogate biomarkers of an inflammatory state [ 25 , 26 , 49 , 50 , 52 , 53 , 55 , 59 , 60 ].…”

Section: Discussionmentioning

confidence: 99%

Short-Term Mortality in Hospitalized Patients with Congestive Heart Failure: Markers of Thrombo-Inflammation Are Independent Risk Factors and Only Weakly Associated with Renal Insufficiency and Co-Morbidity Burden

Iglesias,

Okoh,

Ang

et al. 2024

JCDD

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Congestive heart failure (CHF) is associated with significant morbidity and mortality. There has been renewed interest in using thrombo-inflammatory markers as prognostic tools in patients with CHF. To determine if thrombo-inflammatory markers are independent risk factors for 28-day mortality in hospitalized CHF patients, we retrospectively analyzed admission data extracted from 2008 consecutive patients admitted with a diagnosis of CHF to Zigong Fourth People’s Hospital. Multivariate Cox proportional hazards analysis demonstrated that the thrombo-inflammatory markers thrombin time, platelet/lymphocyte ratio (PLR), and D-dimer level were independent predictors of mortality. In addition, variables reflecting the severity of CHF (New York Heart Association class > 2), impaired renal function (elevated serum creatinine [SCr]), impaired organ perfusion (elevated BUN), and chronic liver disease were also independent predictors of mortality. Thrombo-inflammatory biomarkers were only weakly associated with SCr and the burden of co-morbidity, suggesting that thrombo-inflammation may in large part be attributable to CHF itself and that, moreover, its presence may confer an increased risk of mortality. Further large-scale prospective studies are needed to determine the existence and the consequences of a thrombo-inflammatory phenotype among patients with CHF.

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“…Heart failure involves a persistent systemic inflammatory reaction. The cascade of inflammatory cytokines reactions plays an important role in the occurrence and development of heart failure 158 . 20‐HETE gradually activates nicotinamide adenine dinucleotide phosphate (NADPH) oxidase to produce more ROS through the MAPK/ERK pathway, promote inflammatory reactions and aggravate myocardial cell damage 159 .…”

Section: Aa Metabolism In Human Health and Diseasesmentioning

confidence: 99%

Arachidonic acid metabolism in health and disease

Zhang,

Liu,

Sun

et al. 2023

MedComm

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Arachidonic acid (AA), an n‐6 essential fatty acid, is a major component of mammalian cells and can be released by phospholipase A2. Accumulating evidence indicates that AA plays essential biochemical roles, as it is the direct precursor of bioactive lipid metabolites of eicosanoids such as prostaglandins, leukotrienes, and epoxyeicosatrienoic acid obtained from three distinct enzymatic metabolic pathways: the cyclooxygenase pathway, lipoxygenase pathway, and cytochrome P450 pathway. AA metabolism is involved not only in cell differentiation, tissue development, and organ function but also in the progression of diseases, such as hepatic fibrosis, neurodegeneration, obesity, diabetes, and cancers. These eicosanoids are generally considered proinflammatory molecules, as they can trigger oxidative stress and stimulate the immune response. Therefore, interventions in AA metabolic pathways are effective ways to manage inflammatory‐related diseases in the clinic. Currently, inhibitors targeting enzymes related to AA metabolic pathways are an important area of drug discovery. Moreover, many advances have also been made in clinical studies of AA metabolic inhibitors in combination with chemotherapy and immunotherapy. Herein, we review the discovery of AA and focus on AA metabolism in relation to health and diseases. Furthermore, inhibitors targeting AA metabolism are summarized, and potential clinical applications are discussed.

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Platelet, Neutrophil and Lymphocyte Quantitative Abnormalities in Patients with Heart Failure: A Retrospective Study

Cited by 11 publications

References 46 publications

Assessment of Hematological Predictors via Explainable Artificial Intelligence in the Prediction of Acute Myocardial Infarction

Assessment of Hematological Predictors via Explainable Artificial Intelligence in the Prediction of Acute Myocardial Infarction

Short-Term Mortality in Hospitalized Patients with Congestive Heart Failure: Markers of Thrombo-Inflammation Are Independent Risk Factors and Only Weakly Associated with Renal Insufficiency and Co-Morbidity Burden

Arachidonic acid metabolism in health and disease

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