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New Study Helps Predict Sudden Cardiac Arrest
New Study Helps Predict Sudden Cardiac Arrest
Sputnik Africa
Sudden cardiac arrest (SCA) is a major public health problem that affects millions of people worldwide every year. It occurs when the heart’s electrical system... 31.08.2023, Sputnik Africa
2023-08-31T15:23+0200
2023-08-31T15:23+0200
2023-08-31T16:54+0200
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A new study has revealed that half of the people who suffer sudden cardiac arrest, a life-threatening condition that causes the heart to stop beating, had warning signs in the 24 hours before their event.The study also found that these warning signs differed by gender, and that they could be used to identify high-risk individuals and prevent deaths through the use of digital technology.SCA can happen to anyone, even young and healthy people, and it often strikes without warning. The survival rate of SCA is very low, less than 10% in most cases unless immediate treatment with a defibrillator is provided.However, a new study published recently in the Lancet Digital Health journal suggests that SCA may not be as unpredictable as previously thought. The study, led by researchers from Stanford University and Oregon Health & Science University in the United States, analyzed data from two community-based studies of patients with SCA in California and Oregon.The researchers compared them with control populations who had similar symptoms but did not have SCA. The symptoms included chest pain, shortness of breath, palpitations, dizziness, fainting, sweating, nausea, vomiting, and abdominal pain.The study found that 50% of patients with SCA had at least one warning symptom 24 hours before their attact, compared with 19% of controls. The most common symptoms for women were shortness of breath (22%), whereas for men they were chest pain (27%), shortness of breath (15%), and sweating (10%). The study also found that the symptoms were more likely to occur in the morning or evening hours, and that they lasted longer than five minutes.The researchers used machine learning algorithms to develop a risk score that could predict the likelihood of SCA based on the symptoms and other factors such as age, sex, medical history, and medications. They validated their score using data from another study of SCA patients in Denmark. They found that their score had a high accuracy and could identify 77% of SCA cases within 24 hours.The researchers suggested that their findings could have important implications for preventing SCA and saving lives. They propose that digital technology, such as wearable devices, smartphone apps, or telemedicine platforms, could be used to monitor people's symptoms and alert them if they are at high risk of SCA. They also recommend that people who experience any of these warning signs should seek medical attention as soon as possible.
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New Study Helps Predict Sudden Cardiac Arrest
15:23 31.08.2023 (Updated: 16:54 31.08.2023) Muhammad Nooh Osman
Writer/Editor
Sudden cardiac arrest (SCA) is a major public health problem that affects millions of people worldwide every year. It occurs when the heart’s electrical system malfunctions and stops pumping blood to the rest of the body. It is not the same as a heart attack, which is caused by a blockage in a blood vessel.
A new study has revealed that half of the people who suffer sudden cardiac arrest, a life-threatening condition that causes the heart to stop beating, had warning signs in the 24 hours before their event.
The study also found that these warning signs differed by gender, and that they could be used to identify high-risk individuals and prevent deaths through the use of digital technology.
SCA can happen to anyone, even young and healthy people, and it often strikes without warning. The survival rate of SCA is very low, less than 10% in most cases unless immediate treatment with a defibrillator is provided.
However, a new study
published recently in the Lancet Digital Health journal suggests that SCA may not be as unpredictable as previously thought. The study, led by researchers from Stanford University and Oregon Health & Science University in the United States, analyzed data from two community-based studies of patients with SCA in California and Oregon.
The researchers compared them with control populations who had similar symptoms but did not have SCA. The symptoms included chest pain, shortness of breath, palpitations, dizziness, fainting, sweating, nausea, vomiting, and abdominal pain.
"Harnessing warning symptoms to perform effective triage for those who need to make a 911 call could lead to early intervention and prevention of imminent death," study co-author Sumeet Chugh said in a statement.
The study found that 50% of patients with SCA had at least one warning symptom 24 hours before their attact, compared with 19% of controls. The most common symptoms for women were shortness of breath (22%), whereas for men they were chest pain (27%), shortness of breath (15%), and sweating (10%). The study also found that the symptoms were more likely to occur in the morning or evening hours, and that they lasted longer than five minutes.
The
researchers used machine learning algorithms to develop a risk score that could predict the likelihood of SCA based on the symptoms and other factors such as age, sex, medical history, and medications. They validated their score using data from another study of SCA patients in Denmark. They found that their score had a high accuracy and could identify 77% of SCA cases within 24 hours.
The researchers suggested that their findings could have important implications for preventing SCA and saving lives. They propose that digital technology, such as wearable devices, smartphone apps, or telemedicine platforms, could be used to monitor people's symptoms and alert them if they are at high risk of SCA. They also recommend that people who experience any of these warning signs should seek
medical attention as soon as possible.
"This is the first community-based study to evaluate the association of warning symptoms – or sets of symptoms – with imminent sudden cardiac arrest using a comparison group with EMS-documented symptoms recorded as part of routine emergency care," Eduardo Marban, another author of the study, said.
