Transient increase in blood thrombogenicity may be a critical mechanism for the occurrence of acute myocardial infarction

Ueda, Yasunori; Kosugi, Shumpei; Abe, Haruhiko; Ozaki, Tatsuhisa; Mishima, Tsuyoshi; Date, Motoo; Uematsu, Masaaki; Koretsune, Yukihiro

doi:10.1016/j.jjcc.2020.08.007

Cited by 4 publications

(4 citation statements)

References 62 publications

(76 reference statements)

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“…gen, platelets and coagulation factors in the blood increases in the cold months. 17 We also found that the PT of participants with ischemic stroke onset in winter was higher than in other seasons. These factors can lead to aggravation of atherosclerosis and thrombosis, as well as insufficient blood supply to collateral branch vessels and secondary poor outcomes, which also partly explains why seasonal variations in long-term functional outcomes were more significant in the LAA subtype.…”

Section: Discussionsupporting

confidence: 54%

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―

Xue

Liu

Xia

et al. 2023

Circ J

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and spring. 7 Another study from Japan found no significant correlation between the 1-year clinical outcomes of ischemic stroke and seasonal changes. 8 In a recent study in Saudi Arabia, Alghamdi et al found that weather or seasonal variations had no effect on stroke incidence or outcomes. 9 However, previous studies have only covered short periods of 2-5 years, so in the present study we studied the relationship of season and patterns of neurological severity and outcomes of acute ischemic stroke in a hospital-based study with 9-year cohort data. The findings of this study can provide evidence for the formulation of effective strategies to deal with the adverse consequences of ischemic stroke. Methods Study PopulationThe study population was patients admitted to the Stroke Unit of the Second Hospital of Tianjin Medical University W orldwide, stroke is a leading cause of mortality and disability, 1 and China has a high prevalence and heavy burden of stroke, with ischemic stroke as the most common type, accounting for up to 70%. 2 In addition to the well-known common risk factors, including hypertension, diabetes mellitus, overweight, atrial fibrillation (AF) and smoking, 3 the relationship between meteorological factors and ischemic stroke has attracted the attention of researchers in recent years. 4 Several epidemiological and experimental studies investigated the strong influence of seasonality on stroke incidence, and most found higher stroke incidence during winter and spring and lower incidence during summer and autumn. 5,6In addition, weather changes may lead to severe stroke or worsen the outcome of stroke, which is a public health problem of concern. However, the results of clinical studies differ, and some are even contradictory. A recent study in the USA demonstrated that worse outcomes of ischemic stroke were more frequent in cold seasons including winter

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Section: Discussionsupporting

confidence: 54%

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―

Xue

Liu

Xia

et al. 2023

Circ J

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“…1). Acute MI patients with initial TIMI flow grade 0/1 had significantly higher AUC 30 than stable CAD patients, whereas there was no significant difference in AUC30 between acute MI patients with initial TIMI flow grade 2/3 and stable CAD patients (1,852 [1,661-1,910] vs. 1,677 [1,527-1,756], p < 0.001; 1,748 [1,450-1,826] vs. 1,677 [1,527-1,756], p ¼ 0.597, respectively; ►Fig. 2).…”

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confidence: 77%

“…However, further studies are still needed to clarify the mechanisms that contribute to the formation of occlusive thrombus at the thrombogenic vessel wall by which acute MI is caused. The hypothesis 30 that a temporary increase in blood thrombogenicity is involved in the development of acute MI should also be tested in those studies.…”

Section: Discussionmentioning

confidence: 99%

Temporary Rise in Blood Thrombogenicity in Patients with Acute Myocardial Infarction

Kosugi

Ueda

Abe

et al. 2021

TH Open

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Objective: Although blood thrombogenicity seems to be one of the determinant factors for the development of acute myocardial infarction (MI), it has not been dealt with in-depth. This study aimed to investigate blood thrombogenicity and its change in acute MI patients. Methods and Results: We designed a prospective, observational study that included 51 acute MI patients and 83 stable coronary artery disease (CAD) patients who underwent cardiac catheterization, comparing thrombogenicity of whole blood between: (1) acute MI patients and stable CAD patients; and (2) acute and chronic phase in MI patients. Blood thrombogenicity was evaluated by the Total Thrombus-Formation Analysis System (T-TAS) using the area under the flow pressure curve (AUC30) for the AR-chip. Acute MI patients had significantly higher AUC30 than stable CAD patients (median [interquartile range], 1771 [1585 - 1884] vs. 1677 [1527 - 1756], p = 0.010). Multivariate regression analysis identified acute MI with initial TIMI flow grade 0/1 as an independent determinant of high AUC30 (β = 0.211, p = 0.013). In acute MI patients, AUC30 decreased significantly from acute to chronic phase (1859 [1550 - 2008] to 1521 [1328 - 1745], p=0.001). Conclusion: Blood thrombogenicity was significantly higher in acute MI patients than in stable CAD patients. Acute MI with initial TIMI flow grade 0/1 was significantly associated with high blood thrombogenicity by multivariate analysis. In acute MI patients, blood thrombogenicity was temporarily higher in acute phase than in chronic phase.

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“…Myocardial infarction (MI) occurs when the sudden cessation of blood flow in a coronary artery due to occlusion, which results in the death of the part of the heart muscle supplied by the artery. The occlusion is almost always caused by acute thrombosis of the culprit infarct artery [ 1 ] induced by inflammation [ 2 ] and release of thrombogenic factors [ 3 ] at a location overlying a ruptured atherosclerotic plaque [ 4 ] that has formed from the progressive accumulation of cholesterol, fat, and fibrin in the coronary artery wall [ 5 ]. Depending on the coronary artery involved, different areas of the heart undergo cell death that disrupts locoregional myocardial contractility and electrical activation/conduction [ 6 ] in the affected muscle.…”

Section: Introductionmentioning

confidence: 99%

Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals

Barua

Aydemir

Doğan

et al. 2022

Int. J. Mach. Learn. & Cyber.

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Myocardial infarction (MI) is detected using electrocardiography (ECG) signals. Machine learning (ML) models have been used for automated MI detection on ECG signals. Deep learning models generally yield high classification performance but are computationally intensive. We have developed a novel multilevel hybrid feature extraction-based classification model with low time complexity for MI classification. The study dataset comprising 12-lead ECGs belonging to one healthy and 10 MI classes were downloaded from a public ECG signal databank. The model architecture comprised multilevel hybrid feature extraction, iterative feature selection, classification, and iterative majority voting (IMV). In the hybrid handcrafted feature (HHF) generation phase, both textural and statistical feature extraction functions were used to extract features from ECG beats but only at a low level. A new pooling-based multilevel decomposition model was presented to enable them to create features at a high level. This model used average and maximum pooling to create decomposed signals. Using these pooling functions, an unbalanced tree was obtained. Therefore, this model was named multilevel unbalanced pooling tree transformation (MUPTT). On the feature extraction side, two extractors (functions) were used to generate both statistical and textural features. To generate statistical features, 20 commonly used moments were used. A new, improved symmetric binary pattern function was proposed to generate textural features. Both feature extractors were applied to the original MI signal and the decomposed signals generated by the MUPTT. The most valuable features from among the extracted feature vectors were selected using iterative neighborhood component analysis (INCA). In the classification phase, a one-dimensional nearest neighbor classifier with ten-fold cross-validation was used to obtain lead-wise results. The computed lead-wise results derived from all 12 leads of the same beat were input to the IMV algorithm to generate ten voted results. The most representative was chosen using a greedy technique to calculate the overall classification performance of the model. The HHF-MUPTT-based ECG beat classification model attained excellent performance, with the best lead-wise accuracy of 99.85% observed in Lead III and 99.94% classification accuracy using the IMV algorithm. The results confirmed the high MI classification ability of the presented computationally lightweight HHF-MUPTT-based model.

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Transient increase in blood thrombogenicity may be a critical mechanism for the occurrence of acute myocardial infarction

Cited by 4 publications

References 62 publications

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―

Temporary Rise in Blood Thrombogenicity in Patients with Acute Myocardial Infarction

Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals

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Transient increase in blood thrombogenicity may be a critical mechanism for the occurrence of acute myocardial infarction

Cited by 4 publications

References 62 publications

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients ― A 9-Year Study of 5,238 Patients ―

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients ― A 9-Year Study of 5,238 Patients ―

Temporary Rise in Blood Thrombogenicity in Patients with Acute Myocardial Infarction

Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals

Contact Info

Product

Resources

About

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―

Seasonal Variation in Neurological Severity and Clinical Outcomes in Ischemic Stroke Patients　― A 9-Year Study of 5,238 Patients ―