In order to facilitate for the general physicians the making of a suitable selection of babies who are in the most urgent need of specialized treatment at cardiac centres, simple methods for diagnosing and qualifying congenital cardiovascular diseases were elaborated. The following "minor" criteria were taken for suspecting a CHD: 1) cardiorespiratory distress following birth, 2) sequentially repeated Apgar score below normal, 3) "pneumonia" symptoms with respiratory distress, dyspnoea and cyanosis, attacks of unconsciousness, 4) feeding difficulties, failure to thrive, inexplicable irritability, 5) presence of other congenital anomalies. The almost certain presence of serious heart disease should be recognized in children, showing the following "major" symptoms: 1) permanent cyanosis, pallor or greyish colour, 2) cardiorespiratory failure (resembling usually symptoms of pneumonia), 3) ECG patterns indicating ventricular hypertrophy signs, 4) other significantly abnormal ECG patterns (e.g. AV and intraventricular conduction disturbances), 5) cardiac enlargement and lung vascularity abnormalities in chest X-rays, 6) weak, or impalpable arterial, particularly femoral pulses, femoral arterial pressures significantly lower, than at upper extremities, bounding pulses and high-pressure amplitude in arms and legs, 7) abnormal heart sounds and pathologic heart and vascular murmurs. A diagnostic "key", based upon evaluation of the "major criteria" facilitates the diagnosis and differentiation of the most important CHD's at neonatal and infantile age. When using this "key" one should keep in mind the relative frequency of incidence of particular lesions. The initial diagnoses by the above "key" were verified in 354 patients by cardiovascular catherisation, angiocardiography, surgical exploration, and for by autopsy. The diagnoses were perfectly accurate in 83.6% cases, in further 11.3% cases being also accurate but were supplemented by some details, and had to be corrected in only 5.1% cases.
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Eur Heart J Digit Health
January 2025
Department of Cardiovascular Medicine, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA.
Aims: Gender-affirming hormone therapy (GAHT) is used by some transgender individuals (TG), who comprise 1.4% of US population. However, the effects of GAHT on electrocardiogram (ECG) remain unknown.
View Article and Find Full Text PDFCureus
December 2024
Department of Cardiology, Shariati Hospital, School of Medicine, Tehran University of Medical Sciences, Tehran, IRN.
Pulmonary thromboembolism (PTE) is the third most common cause of acute cardiovascular disease, which can lead to high morbidity and mortality if left untreated. Anatomical and electrophysiological variations and obesity may complicate timely diagnosis and delay required management. While computed tomography pulmonary angiography (CTPA) remains the most accurate diagnostic tool, initial assessments using electrocardiography (ECG) or echocardiography can be helpful in early suspicion.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Department of Anesthesiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Background: Lack of motivation and behavioral abnormalities are the hallmarks of postpartum depression (PPD). Severe uterine contractions during labor are pain triggers for psychiatric disorders, including PPD in women during the puerperium. Creating biomarkers to monitor PPD may help in its early detection and treatment.
View Article and Find Full Text PDFOxf Med Case Reports
January 2025
Emergency Medicine, Hamad General Hospital, Al Rayyan Road, P.O. Box 3050, Doha, Qatar.
Intermittent or transient right bundle branch block (RBBB) can occur in various clinical situations but is rarely described in acute pulmonary embolism. We present a unique case involving a 57-year-old male who experienced a syncopal episode during transit. He displayed signs of a transient right bundle branch block (RBBB) and S1Q3T3 on the initial EMS ECG, which reverted to normal ECG later.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Department of Cardiology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China.
Introduction: The risk of mortality associated with cardiac arrhythmias is considerable, and their diagnosis presents significant challenges, often resulting in misdiagnosis. This situation highlights the necessity for an automated, efficient, and real-time detection method aimed at enhancing diagnostic accuracy and improving patient outcomes.
Methods: The present study is centered on the development of a portable deep learning model for the detection of arrhythmias via electrocardiogram (ECG) signals, referred to as CardioAttentionNet (CANet).
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