Background: Accumulating evidence from clinical trials, large registries, and meta-analyses of population studies shows that increased Blood Pressure Variability (BPV) is predictive of Cardiovascular (CV) outcomes, independently of the average Blood Pressure (BP) values. One of the mechanisms explaining the relationship between BPV and target organ damage is the inflammatory response. The Systemic Immune Inflammation Index (SII), which relies on peripheral blood cell counts, including platelets, neutrophils, and lymphocytes, has emerged as a predictor of prognosis and outcomes in various diseases. The aim of this study was to investigate the association of the SII with Ambulatory Blood Pressure Variability (ABPV) in newly diagnosed hypertensive patients. Methods: This study was designed as a cross-sectional observational study. A total of 1606 consecutive newly diagnosed Hypertension (HT) patients were included in the study. The population was evaluated across 3 different categories according to HT grades (5 groups), eligibility for antihypertensive therapy (2 groups) and ABPV levels (2 groups). Results: Significant differences were observed between ABPV groups in terms of Neutrophil to Lymphocyte ratio, Platelet to Lymphocyte ratio, glucose, SII, high-sensitive CRP, HT grade, Inter-Ventricular Septum, Posterior Wall thickness, and Left Ventricular Mass (p < 0.005). There was a significant relationship between SII and ABPV (r: 0.619, p < 0.05). At the cutoff value of 580.49, SII had 77% sensitivity and 71% specificity for ABPV > 14 (AUC: 0.788). Conclusions: SII may assist in developing an early treatment approach to minimize complications in patients with high ABPV who are at a higher risk of CV events.

Background and Purpose: Arrhythmia, which presents with irregular and/or fast/slow heartbeats, is associated with morbidity and mortality risks. Photoplethysmography (PPG) provides information on volume changes of blood flow and can be used to diagnose arrhythmia. In this work, we have proposed a novel, accurate, self-organized feature engineering model for arrhythmia detection using simple, cost-effective PPG signals. Method: We have drawn inspiration from quantum circuits and employed a quantum-inspired feature extraction function /named the Tree Quantum Circuit Pattern (TQCPat). The proposed system consists of four main stages: (i) multilevel feature extraction using discrete wavelet transform (MDWT) and TQCPat, (ii) feature selection using Chi-squared (Chi2) and neighborhood component analysis (NCA), (iii) classification using k-nearest neighbors (kNN) and support vector machine (SVM) and (iv) information fusion. Results: Our proposed TQCPat-based feature engineering model has yielded a classification accuracy of 91.30% using 46,827 PPG signals in classifying six classes with ten-fold cross-validation. Conclusion: Our results show that the proposed TQCPat-based model is accurate for arrhythmia classification using PPG signals and can be tested with a large database and more arrhythmia classes.

Objectives: This study aimed to determine whether there is a difference in the electrocardiography (ECG) measurements of healthy controls and rheumatoid arthritis (RA) patients and to predict whether they can be used to determine the risk of arrhythmia in patients. Patients and methods: The prospective study included 50 cardiac asymptomatic RA patients (38 males, 12 females; mean age: 46.8±9.1 years; range, 18 to 60 years) who met the 2010 American College of Rheumatology/European Alliance of Associations for Rheumatology RA criteria and 50 healthy volunteers (34 males, 16 females; mean age: 43.4±10.4 years; range, 18 to 60 years) as a control group between June 1, 2022, and August 31, 2022. Disease activity of the patients was calculated with the Disase Activity Score (DAS28). Heart rate, minimum and maximum QT intervals, QT dispersion, minimum and maximum P waves, P wave dispersion (Pd), minimum and maximum Tp-e intervals, Tp-e dispersion, minimum and maximum corrected QT (QTc) intervals, QTc dispersion, and the Tp-e/QTc ratio in ECGs were calculated. Results: The mean disease duration of the RA group was 9.09±5.74 years. The mean C-reactive protein level was 9.83±8.29, the mean erythrocyte sedimentation rate was 26.12±16.28 mm/h, and the mean DAS28 was 3.03±0.37. There was a statistically significant increase in the maximum P wave, Pd, maximum QT, QT dispersion, maximum QTc, QTc dispersion, maximum Tp-e, Tp-e dispersion, and Tp-e/QTc dispersion parameters in the RA group compared to the control group, while there was a significant decrease in the minimum P wave, minimum QT, and minimum QTc parameters. Conclusion: In our study, the Pd, QTc dispersion, Tp-e dispersion, and Tp-e/QTc dispersion values of our patients, which indicate the risk of atrial and ventricular arrhythmia, were found to be significantly higher. This finding suggests that our patients had an increased risk of cardiac morbidity and mortality. Arrhythmias are the likely source of the increase in sudden cardiac death in RA, and these new indicators measured on ECG can be used as standardized cardiovascular morbidity and mortality indicators in the future.

Background and Objectives: The neutrophil-percentage-to-albumin ratio (NPAR) has been recognized as an independent risk factor for cardiovascular diseases. In our study, we investigated whether the NPAR is associated with the formation of coronary collateral circulation (CCC) in patients with chronic coronary syndrome (CCS). Materials and Methods: A total of 681 patients with CCS were included in this study. Of these patients, 571 had chronic total occlusion in at least one major vessel and developed collateral vessels. In total, 110 patients were in the control group, who had CCS but did not have complete occlusion in a major vessel and did not develop collateral vessels. Patients with collateral vessels on coronary angiography were divided into two groups according to the Rentrop score: poor CCC (Rentrop 0–1) and good CCC (Rentrop 2–3). Blood samples were taken for the NPAR and other biochemical parameters in all patients during hospitalization. The NPAR was calculated as the neutrophil-percentage-to-albumin ratio. Results: The group of patients with poor CCC had a higher white blood count (WBC), neutrophil, C-reactive protein (CRP), neutrophil–lymphocyte ratio (NLR), CRP/albumin ratio (CAR), and NPAR values than patients with good CCC (p < 0.001, for all). Multivariate logistic regression analysis showed that high NPAR levels were an independent predictor of poor CCC (OR: 2.79, 95% CI:1.7–4.6, p < 0.001), accompanied by neutrophil, CRP, CAR, and NLR levels. In the receiver operator characteristic curve (ROC analysis), the cut-off value for the NPAR to indicate poor CCC was 1.78 with a sensitivity of 76.6% and specificity of 81.4% (area under ROC curve = 0.804 95% CI (0.753–0.854), p < 0.001). Conclusions: We demonstrated that the NPAR may be an independent predictor of poor CCC development in clinical practice.

Aim: In this study, we aim to investigate the effect of dual anti-platelet agents on osseointegration by studying a sample of rats with titanium implants in their tibias. Material and Method: The titanium implants were placed surgically to the left tibias of a sample group of 50 rats. After implantation, the rats were randomly divided into five groups: acetylsalicylic acid (ASA) (n =10), treated with 20 mg/kg of ASA; ASA+ clopidogrel (CLPD) (n=10), treated with 20 mg/kg of ASA and 30 mg/kg of CLPD; ASA+ prasugrel (PRSG) (n=10), treated with 20 mg/kg of ASA and 15 mg/kg of PRSG; ASA+ ticagrelor (TCGR) (n=10), treated with 20 mg/kg of ASA and 300 mg/kg of TCGR; and a control group (CNT) (n =10) received no further treatment following implant surgery. The experimental period lasted four weeks, during which all medications were administered with oral gavage. Concluding the experimental period, the animals were euthanized, and researchers collected blood serums and the implants, along with some surrounding bones, from each rats. Results: Bone implant connection and bone filling ratios (%) were observed histologically and documented. The bone-implant connection and bone filling ratios of the rats do not show statistically significant differences between the groups examined (P>0.05). Conclusion: In this study, it was shown that there was no bone healing problem between the antiaggregant given groups and between these groups and the control group. Too many people have to take single or double antiaggregant due to many diseases. We think that it is an important study in terms of knowing that bone healing will not be negatively affected when dental implants or other bone prosthesis procedures are applied to these patients. The results of this study should be supported by further research.