Articles tagged with Electrocardiography
Researchers analyzed data from over 3,000 participants and found no association between electrocardiogram measures and telomere length. The study suggests that ECG prolongation is age-dependent but not a marker of biological aging.
Researchers developed an AI algorithm using individual ECG heartbeats to accurately predict diabetes and pre-diabetes. The DiaBeats algorithm detected the diseases with an overall accuracy of 97%, irrespective of factors like age, gender, and coexisting metabolic disorders.
Researchers developed an AI-driven device that detects and predicts hemodynamic instability using a single ECG lead, outperforming traditional vital sign measurements with nearly 97% sensitivity. The technology has the potential to provide continuous dynamic monitoring capabilities in patients with intermittent static vital sign measur...
Researchers recommend expanding diagnostic workup to include cardiac arrhythmias for unexplained enuresis in adults and children. An electrocardiogram is a cost-effective and non-invasive test that can detect potentially fatal diseases.
Researchers developed a foldable sensor sheet using kirigami principles, enabling wearable devices to conform to the human body and detect electrocardiographic signals. The sensor measures 200 square millimeters and can accurately relay heart data across multiple people, making it suitable for early diagnosis of disease.
A study suggests that smartwatch heart rate measurement algorithms are less effective in people with darker skin tones due to increased melanin absorption. Researchers emphasize the need for diverse population inclusion and explore alternative light wavelengths for more accurate readings.
A study found that handheld electrocardiogram (ECG) devices increase the detection of atrial fibrillation in patients aged 85 and older, but not those 65 and older. The compact devices are feasible for screening most patients during primary care visits.
A small study found statistically significant improvements in various symptoms, including fatigue and chest discomfort, after EECP therapy in long COVID patients. Researchers believe this is the most plausible explanation for the benefits derived from EECP and its link to long COVID.
A study of continuous monthly mortality data found that excess deaths associated with COVID-19 reached greater peaks than most other periods of excess deaths since 1918. The relative excess of deaths in 2020 was 12.5% in Switzerland, 8.5% in Sweden, and 17.3% in Spain.
The USPSTF recommends against screening for atrial fibrillation in asymptomatic adults aged 50 or older. The current evidence is insufficient to assess the balance of benefits and harms of screening, which is associated with a substantial increase in stroke risk. Atrial fibrillation is a major risk factor for ischemic stroke.
A pilot study suggests that machine learning algorithms combining EKG and electronic health record data can more effectively screen for pulmonary embolisms than current tests. The fusion model was found to be 15-30% more effective at accurately identifying cases, especially severe ones.
A novel AI algorithm developed at Mayo Clinic can predict long-term patient survival after cardiac surgery using a single-lead EKG. The study found a clear correlation between long-term mortality and a positive AI ECG screen for reduced left ventricular ejection fraction among patients without apparent severe cardiomyopathy.
A new clinical syndrome of ICI-myocarditis has been identified, characterized by highly arrhythmogenic features. The study establishes specific electrocardiographic features to diagnose and prognosticate the syndrome, highlighting the need for further research on prediction and monitoring strategies.
A new AI-based computer algorithm created by Mount Sinai researchers can identify subtle changes in electrocardiograms to predict heart failure. The algorithm was 94% accurate at predicting healthy ejection fractions and 87% accurate at detecting weakened hearts, offering a promising alternative to traditional diagnosis methods.
Researchers found that shrinking waveforms on electrocardiograms can help identify high-risk patients with COVID-19 or influenza, allowing for more aggressive monitoring and treatment. The study also showed that this technique may be particularly useful in overwhelmed systems where timely intervention is crucial.
A Rice University lab developed a 'smart' shirt that gathers accurate EKGs and heart rates using conductive nanotube thread. The fibers, just as conductive as metal wires but washable and comfortable, provided better data than standard chest-strap monitors.
University of South Australia researchers create a computer vision system to detect premature babies' faces and vital signs from digital cameras, outperforming electrocardiogram machines. The technology has the potential to replace contact-based sensors, reducing skin tearing and infections.
Researchers propose using junctional pacemakers to replace the sinoatrial node in patients with bicuspid aortic valve and sinoatrial node dysfunction. This innovative approach offers a new treatment strategy for managing daily life while avoiding the need for sinoatrial node replacement surgery.
A case study presented ST-segment depression in leads I and aVL, which was resolved after 30 minutes due to high-frequency noise. The patient had no regional wall motion abnormalities or coronary stenosis, suggesting artifactual changes rather than pathophysiological findings.
An AI-enhanced EKG can detect subtle electrical changes in the heart associated with COVID-19 infection, offering a potential rapid and reliable screening test. The technology achieved positive predictive values of up to 37% and negative predictive values of 99.2% in real-world populations.
Researchers found that a significant gap between numerical age and biological age, as predicted by AI-enabled EKGs, is associated with increased risk of death from heart disease. The study validated the use of AI-aged EKGs in predicting mortality rates.
A new AI-powered ECG screening tool detected asymptomatic low ejection fraction in patients with improved diagnosis rates. The study found that the AI intervention increased the diagnosis of low ejection fraction by 32% relative to usual care.
A study evaluates the impact of COVID-19 infection on cardiac corrected QT interval changes, finding alterations in both patients with and without the infection. The research suggests that early phase treatment for COVID-19 may lead to significant cardiac changes.
Researchers at Kobe University developed an AI that uses a combination of electrocardiography (ECG) data and chest X-ray images to diagnose accessory pathways in the heart, which cause arrhythmic disorders. The AI's accuracy was significantly improved compared to previous methods.
A new algorithm uses artificial intelligence to automate electrocardiogram recordings, improving efficiency and accuracy in heart disease diagnosis. This innovation has the potential to streamline clinical workflows and enhance patient care.
Researchers at Mayo Clinic have developed an AI-powered mobile EKG device that can rapidly and accurately determine a patient's QTc, identifying those at risk of sudden cardiac death from congenital long QT syndrome or drug-induced QT prolongation. The device achieved high sensitivity and specificity in detecting clinically meaningful ...
A new study by Massachusetts General Hospital has established normal heart scan results for elite female and male soccer players. The research aims to differentiate between normal exercise-induced adaptations and abnormal responses detrimental to health.
Researchers at Kaunas University of Technology developed a non-invasive method to measure electrolyte levels, particularly potassium, through electrocardiogram. This can help prevent life-threatening conditions among people with chronic kidney disease.
A new sensor chip smaller than a ladybug records multiple lung and heart signals, body movements, and sounds to offer the big picture of a patient's heart and lung health. The chip's high resolution and quantified data could identify pathologies and enable clinical readings in the future.
Researchers at Mayo Clinic have created an artificial intelligence (AI) algorithm that can detect unseen characteristics of hypertrophic cardiomyopathy using standard EKGs. The AI's ability to diagnose the disease was found to be highly accurate, with an area under the curve of 0.96, outperforming traditional tests.
Researchers used deep neural networks to analyze ECG test results from over 2 million patients, identifying those at high risk of developing atrial fibrillation or dying within a year. The models were found to be superior in predicting mortality risk even in patients with normal ECGs.
Researchers have successfully recorded and processed data from 43 patients with heart failure using a machine learning-based ballistocardiogram (BCG) scale. The device measures circulation pulsing to detect worsening heart failure symptoms, potentially sparing patients hospital stays.
A handheld smartphone-enabled 1-lead ECG showed excellent diagnostic accuracy for detecting atrial fibrillation and flutter. The device's integrated algorithm correctly identified 87% of atrial fibrillation cases and 98% of non-atrial fibrillation cases.
Researchers used convolutional neural networks to analyze electrocardiogram data from over 500,000 patients, estimating their 'physiologic age' and determining sex with high accuracy. The study suggests AI-enhanced EKGs could help doctors identify asymptomatic conditions and improve healthcare outcomes.
Researchers trained AI to identify subtle differences in normal EKGs that indicate changes caused by atrial fibrillation. The AI-enabled EKG correctly identified the condition with 90% accuracy, improving treatment options and efficiency of heart disease screening.
A Mayo Clinic study found that applying artificial intelligence to a standard electrocardiogram (EKG) results in an affordable and accessible early indicator of asymptomatic left ventricular dysfunction, a precursor to heart failure. The AI/EKG test accuracy compares favorably with other common screening tests.
Researchers from the University of California, Santa Barbara developed new algorithms to localize atrial fibrillation using non-invasive electrocardiographic imaging. This technology has the potential to aid in diagnosis and prognosis of cardiac disorders without requiring invasive surgeries.
The USPSTF concludes that routine screening for atrial fibrillation with electrocardiography is not recommended due to the lack of evidence. Atrial fibrillation increases with age and is a major risk factor for ischemic stroke, but current screening methods have not been proven effective in preventing adverse outcomes.
The USPSTF recommends against adding ECG screening to standard risk assessment to prevent CVD events in asymptomatic adults at low risk. Cardiovascular disease is a leading cause of death among adults in the United States, but ECG screening has not been proven to reduce CVD events.
Researchers at the University of Tokyo have developed an ultrathin, highly elastic skin display that can show moving electrocardiogram waveforms recorded by a breathable on-skin electrode sensor. The device aims to enhance information accessibility for people with difficulty operating existing devices.
A recent study found that nearly 1 in 5 NBA players have abnormal electrocardiogram findings, some linked to athletic training. The research aimed to assess athlete-specific criteria for distinguishing normal from abnormal ECG patterns.
Researchers found that heart rate variability measured by an electrocardiogram indicated whether subjects had major depression or bipolar disorder. Patients with bipolar disorder had higher blood levels of inflammation biomarkers than those with major depression.
A new risk assessment tool has been developed by Cedars-Sinai researchers to predict and prevent sudden cardiac arrest. The score is calculated using widely available and inexpensive 12-lead electrocardiogram (EKG) technology, and patients with scores above 4 have a 20 times increased risk of sudden cardiac arrest.
Researchers found wrist-worn fitness trackers less accurate in measuring heart rate during exercise compared to traditional chest strap monitors. The most accurate readings came from the chest strap monitor, particularly for individuals with heart conditions.
Researchers found that CTA tests led to higher adoption of preventive measures and healthier lifestyle practices compared to exercise electrocardiography and stress tests. After 60 days, more people who underwent CTA tests started taking aspirin, statins, and beta-blockers, and eating healthier, with lower rates of obesity.
A study published in JAMA Cardiology found variable accuracy of wrist-worn heart rate monitors, particularly during moderate exercise. The results suggest that these devices should be used with caution for individuals relying on them to track fitness or stay within safe heart rate thresholds.
Researchers successfully combined a heart monitoring device with an existing CEW to detect and store cardiac rhythms, producing both incapacitating charges and interpretable EKG signals. The modified prototype demonstrates the potential for safety measures like cardiac biomonitoring to be incorporated into law enforcement devices.
Engineers at UC San Diego created a tricorder-like device that tracks lactate levels and heart signals in real-time, offering potential benefits for athletes and individuals with cardiovascular disease. The patch can be worn on the chest and communicates wirelessly with a smartphone or laptop.
The American College of Physicians recommends avoiding cardiac screening in low-risk adults, citing lack of benefits and potential harms. Instead, physicians should focus on treating modifiable risk factors such as smoking, diabetes, and hypertension.
Researchers at North Carolina State University have developed a new, wearable sensor that can accurately monitor electrophysiological signals like electrocardiography (EKG) or electromyography (EMG) for long periods. The sensor uses silver nanowires and is more accurate than existing sensors, especially when a patient is moving.
A study examining diagnostic tests in adolescents with hypertension found that echocardiograms and renal ultrasonography were underused, while electrocardiograms were overused. The findings highlight the need for better adherence to pediatric guidelines and further research on treatment effectiveness.
A new study suggests adding a modified echo to current screenings to identify student athletes with heart problems that could lead to sudden death. The study found that an abbreviated echo can increase the sensitivity of finding heart defects in competitive athletes.
Researchers found that EKG abnormalities in healthy elderly individuals increased the risk of heart attack. The study, which followed 2,192 adults aged 70 and older for eight years, suggests that EKGs could be used to detect heart disease earlier in patients without chest pain or symptoms.
A new study published in the BMJ Open found that exercise ECGs have benefits beyond diagnosis, including clarifying symptoms and engaging patients in the diagnostic process. The test can facilitate communication between clinicians and patients, providing reassurance on exercise capacity and tolerance.
Bioengineers from Rice University are testing a new law of biology to predict when critically ill patients will worsen, and which treatment is likely to prevent it. The study aims to provide clinicians with a patient-specific 'forecast' using data from electrocardiograms and other vital signs.
A new study has identified subtle markers of heart damage hidden in hours of EKG recordings, allowing doctors to identify high-risk heart attack patients. The researchers found that these anomalies can predict patient mortality within 12 months, enabling targeted treatments to save lives.
A Tel Aviv University study found that EKG screenings for young athletes do not prevent sudden death syndrome, contradicting mandatory screening laws. The study suggests that the screenings are costly and have limited effectiveness, with over 30,000 athletes needing to be screened to save one life.
Researchers identified DNA sequence variations associated with abnormal heart rhythms in multiple regions of the human genome. The study found links between these variations and increased risk for sudden cardiac death and heart damage.
The new clinics series provides comprehensive reviews of contemporary issues in cardiac electrophysiology, including epicardial interventions, advances in arrhythmia analyses, and antiarrhythmic drug therapy. These issues help electrophysiologists make informed clinical decisions for their patients.
A study of 500 patients found that EKG readings can yield false positive diagnoses for left ventricular hypertrophy with a rate of 77-82%, while false negatives occur at a rate of 6-7%. This can lead to unnecessary additional screenings.