Heart News
Wrong cuff size can distort blood pressure readings
A customised approach can avoid over or under treatment
Aone-size-fits-all inflatable bag to measure blood pressure might lead to significant measurement inaccuracies , according to preliminary research presented at the American Heart Association ’ s Epidemiology , Prevention , Lifestyle & Cardiometabolic Health Conference 2022 .
“ Accurate blood pressure measurement depends on proper patient preparation , positioning , measurement technique , and individualized selection of cuff size , which should be based on the measured mid-arm circumference ,” Dr Tammy M . Brady , study author , vice chair for clinical research in pediatrics , associate professor of pediatrics in the division of pediatric nephrology and medical director of the Pediatric Hypertension Program at Johns Hopkins University , said in a press release .
After repeatedly measuring blood pressure with different cuffs in 165 adults , researchers found that those requiring a small cuff had “ notably lower blood pressure readings ” when using a regular inflatable bag , while people who needed a larger cuff saw “ significantly higher readings .”
This led to 39 percent of people being misdiagnosed with high blood pressure while the condition was missed in 22 percent of the participants . The risks involve potential overtreatment for the first group and a false sense of reassurance for the second .
In addition to increasing the risk for heart disease , high blood pressure can contribute to stroke , kidney disease , visual loss , and death . In 2019 , it was a primary or contributing factor in the death of more than half a million Americans .
AI programme spots hard-to-diagnose heart problems
The technology can help prevent problems and improve treatment outcomes
Researchers in the US have developed an artificial intelligence ( AI ) system to distinguish two types of life-threatening heart conditions that often go undiagnosed , cardiac amyloidosis and hypertrophic cardiomyopathy .
Cardiac amyloidosis is caused by the accumulation of the protein amyloid in the heart tissue and is often asymptomatic , while hypertrophic cardiomyopathy leads the heart muscle to stiffen and thicken . Both conditions prevent the heart from working normally and can appear similarly on an echocardiogram , the most used heart imaging method , or even look like normal tissue .
“ These two heart conditions are challenging for even expert cardiologists to accurately identify , and so patients often go on for years to decades before receiving a correct diagnosis ,” Dr David Ouyang , a cardiologist at the Smidt Heart Institute at Cedars-Sinai and senior author of the study , said in a press release . “ Our AI algorithm can pinpoint disease patterns that can ’ t be seen by the naked eye , and then use these patterns to predict the right diagnosis .”
The new technology was trained on 34,000 videos of patient cardiac ultrasounds , a standard examination in cardiology , and was able to pinpoint the patients with heart structures potentially related to the two conditions . “ The algorithm identified high-risk patients with more accuracy than the well-trained eye of a clinical expert ,” said Dr Ouyang , adding that this is due to its ability to make a distinction between benign conditions and heart disease , which may look similar on ultrasound images .
The AI-powered diagnostic approach could allow doctors to identify these diseases before they lead to health problems , thus enabling treatment to start early and improving outcomes .
22 MARCH 2022 GlobalHealthAsiaPacific . com