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    Analysis of hematological indicators via explainable artificial intelligence in the diagnosis of acute heart failure: a retrospective study
    (Frontiers Media Sa, 2024) Yilmaz, Rustem; Yagin, Fatma Hilal; Colak, Cemil; Toprak, Kenan; Samee, Nagwan Abdel; Mahmoud, Noha F.; Alshahrani, Amnah Ali
    Introduction Acute heart failure (AHF) is a serious medical problem that necessitates hospitalization and often results in death. Patients hospitalized in the emergency department (ED) should therefore receive an immediate diagnosis and treatment. Unfortunately, there is not yet a fast and accurate laboratory test for identifying AHF. The purpose of this research is to apply the principles of explainable artificial intelligence (XAI) to the analysis of hematological indicators for the diagnosis of AHF. Methods In this retrospective analysis, 425 patients with AHF and 430 healthy individuals served as assessments. Patients' demographic and hematological information was analyzed to diagnose AHF. Important risk variables for AHF diagnosis were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) feature selection. To test the efficacy of the suggested prediction model, Extreme Gradient Boosting (XGBoost), a 10-fold cross-validation procedure was implemented. The area under the receiver operating characteristic curve (AUC), F1 score, Brier score, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) were all computed to evaluate the model's efficacy. Permutation-based analysis and SHAP were used to assess the importance and influence of the model's incorporated risk factors. Results White blood cell (WBC), monocytes, neutrophils, neutrophil-lymphocyte ratio (NLR), red cell distribution width-standard deviation (RDW-SD), RDW-coefficient of variation (RDW-CV), and platelet distribution width (PDW) values were significantly higher than the healthy group (p < 0.05). On the other hand, erythrocyte, hemoglobin, basophil, lymphocyte, mean platelet volume (MPV), platelet, hematocrit, mean erythrocyte hemoglobin (MCH), and procalcitonin (PCT) values were found to be significantly lower in AHF patients compared to healthy controls (p < 0.05). When XGBoost was used in conjunction with LASSO to diagnose AHF, the resulting model had an AUC of 87.9%, an F1 score of 87.4%, a Brier score of 0.036, and an F1 score of 87.4%. PDW, age, RDW-SD, and PLT were identified as the most crucial risk factors in differentiating AHF. Conclusion The results of this study showed that XAI combined with ML could successfully diagnose AHF. SHAP descriptions show that advanced age, low platelet count, high RDW-SD, and PDW are the primary hematological parameters for the diagnosis of AHF.
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    Analysis of hematological indicators via explainable artificial intelligence in the diagnosis of acute heart failure: a retrospective study (vol 11, 1285067, 2024)
    (Frontiers Media Sa, 2024) Yilmaz, Rustem; Yagin, Fatma Hilal; Colak, Cemil; Toprak, Kenan; Samee, Nagwan Abdel; Mahmoud, Noha F.; Alshahrani, Amnah Ali
    [Abstract Not Available]
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    Fixed-Dose Antiplatelet Dual Combination in Patients with Coronary Artery Disease in Turkish Population: DAPT-TR
    (Arquivos Brasileiros Cardiologia, 2024) Oz, Ahmet; Toprak, Kenan; Aydin, Ertan; Sarac, Ibrahim; Dogdus, Mustafa; Opan, Selcuk; Yenercag, Mustafa
    Background: Dual antiplatelet therapy (DAPT) is the treatment of choice for patients with acute and chronic coronary syndromes as it reduces mortality and prevents recurrent thrombotic complications. The assessment of both ischaemic burden and bleeding risk is crucial in deciding which DAPT to choose and how long it should be continued. Objectives: The aim of our study was to perform prospective clinical follow-up of patients receiving fixed-dose combination therapy (ASA 75 mg + clopidogrel 75 mg). Our study is a multicentric, cross-sectional, observational, cohort study. Methods: A total of 1500 patients who were started on fixed-dose combination DAPT for acute or chronic coronary syndrome were included in the study. Primary endpoints were hospitalization for any reason, hospitalization for cardiovascular cause, acute myocardial infarction, stent thrombosis, target vessel revascularization and bleeding; the secondary endpoints were death for any reason or cardiovascular cause and stroke. The significance level adopted in the statistical analysis was 5%. Results: Median age was 63 years; 78.5% of the patients were receiving DAPT treatment for acute coronary syndrome. The rates of hospitalization for cardiovascular reasons, acute myocardial infartion, stent thrombosis and target-vessel revascularization were 7.9%, 2.3%, 1.3% and 4.2%, respectively. While the rate of BARC type 1 bleeding was 3.3%, the rate of BARC type 5, 3, or 2 bleeding was 0.6%. The secondary endpoints which were death from any cause, cardiovascular death and stroke were 0.5%, 0.3% and 0.3%, respectively. Conclusion: Our study shows that fixed-dose combination therapy is effective and safe in appropriately selected patients with acute or chronic coronary syndromes.