Humans ; Myocardial Infarction ; diagnosis

101 male patient with diagnosis of acute myocardial infarction were involved in study. The participants have ages ranged from 42 to 85 (mean 62.13+/-8.17). Out of these patients, 4.9% had not a chest pain. 20% of patients had a severe angina and 40.6% of these had a mild angina. Time delay in admission of patients with severe chest pain was shortest (4.55 hours) and that of the patients with mild chest pain was longest (75.61 hours)
Myocardial Infarction ; Chest Pain ; diagnosis

101 men were diagnosed acute myocardial infarction. Of these patients 4.9% hadn't a chest pain, 20% had a severe angina, 40.6% a mild angina. The time delay of the patients with severe angina was the shortest (4.55h) while that of the patients with mild angina was the longest (75.61h)
Chest Pain ; Myocardial Infarction ; diagnosis

This paper introduces the troponin, a new gold standard for diagnosis of myocardial infarction and role of troponin in other diseases. The authors introduced also some new standards for diagnosis of the myocardial infarction such as cut-off value, isoenzyme CK-MB, GOT, myoglobin and LDH
Troponin ; Cardiomyopathies ; Infarction ; diagnosis ; Myocardial Infarction

Humans ; Myocardial Infarction ; diagnosis ; Takotsubo Cardiomyopathy ; diagnosis

Humans ; Myocardial Infarction ; diagnosis ; Pharyngitis ; complications

3 months after 2nd stage of myocard infarctus, 208 patients including 103 with heart failure and 105 with no heart failure (control), there is no difference in age and gender. Among risk factors, smoking and high uric acid level between two groups there is significant differences. ST heart rate is higher than control. There is no difference on systolic and diastolic blood pressure between 2 groups but on clinical symptoms, the difference is noted such as dyspnoea in effort, pneumatio rale, electro cardiogramme. Left ventricle function ultrasound has significant difference statistically
Myocardial Infarction ; Heart Failure, Congestive ; Patients ; diagnosis

Tissue array contains hundreds or thousands tissues from different cases, and has been known useful for rapid analysis of markers in a large numbered work. This has mainly been used in investigative purpose, and few has been reported for diagnostic trial. Diagnosis of early myocardial infarction is important in medicolegal field. Immunohistochemical staining using various antibodies has become a popular tool for this purpose, but standardization and reproducibility have been problems. Use of tissue array is promising in this points. We have made two cardiac tissue arrays using 87 different cases and have verified the feasibility of tissue array in forensic field. Experiences and several issues concerning tissue array are discussed.
Antibodies ; Diagnosis* ; Heart ; Immunohistochemistry ; Myocardial Infarction*

Myoglobin has been shown to be elevated in the serum after myocardial infarction. Myoglobin is one of the first to appear in the serum and its quantification may thus be used in the diagnosis of the early phase of acute myocardial infarction. The purpose of this study was to clarify the time course of myoglobin elevation in the early phase of acute myocardial infarction. We compared this with the time course of serum CPK and obtained following results: 1) Serum myoglobin becomes significantly elevated at 4 hours following onset of chest pain and apears earlier than CPK. 2) Serum myoglobin time curve peaks at 8 hours, whereas the CPK time surve peaks at 16 hours following onset of chest pain. 3) Mearsurement of serum myoglobin in the early phase of acute myocardial infarction can serve as valuable aid in diagnosis of myocardial infarction with other findings.
Chest Pain ; Diagnosis ; Myocardial Infarction* ; Myoglobin*

Myocardial infarction (MI) has the characteristics of high mortality rate, strong suddenness and invisibility. There are problems such as the delayed diagnosis, misdiagnosis and missed diagnosis in clinical practice. Electrocardiogram (ECG) examination is the simplest and fastest way to diagnose MI. The research on MI intelligent auxiliary diagnosis based on ECG is of great significance. On the basis of the pathophysiological mechanism of MI and characteristic changes in ECG, feature point extraction and morphology recognition of ECG, along with intelligent auxiliary diagnosis method of MI based on machine learning and deep learning are all summarized. The models, datasets, the number of ECG, the number of leads, input modes, evaluation methods and effects of different methods are compared. Finally, future research directions and development trends are pointed out, including data enhancement of MI, feature points and dynamic features extraction of ECG, the generalization and clinical interpretability of models, which are expected to provide references for researchers in related fields of MI intelligent auxiliary diagnosis.
Humans ; Electrocardiography ; Myocardial Infarction/diagnosis* ; Recognition, Psychology