Rethinking Blood Pressure: Cambridge Study Reveals Measurement Flaws
High blood pressure, commonly known as hypertension, is a major health concern linked to severe conditions like heart disease and strokes. However, typical methods of measuring blood pressure might be missing nearly 30% of high blood pressure cases due to inaccuracies.
Researchers from the University of Cambridge have developed a novel model to explore the physics behind these measurement errors. Their findings, published in PNAS Nexus, suggest simple modifications could dramatically improve the accuracy of blood pressure readings.
Blood pressure is often measured using a cuff-based method. This traditional technique, also called the auscultatory method, involves inflating a cuff around the arm, cutting off blood flow, and listening for tapping sounds as the cuff deflates. The readings are given as two numbers: systolic (maximum) and diastolic (minimum) pressure. The ideal reading is 120/80.
According to co-author Kate Bassil from Cambridge’s Department of Engineering, “The auscultatory method has long been the gold standard, but it tends to overestimate diastolic pressure and underestimate systolic pressure.”
Co-author Professor Anurag Agarwal explains, “Clinicians have been aware of the inaccuracies, but the reasons behind the underestimation of systolic pressure were unclear.”
Past studies used rubber tubes that didn’t mimic how arteries behave under cuff pressure. The Cambridge team built a physical model that better represents the physiological conditions, revealing that low pressure in the arm below the cuff could delay the reopening of the artery, causing an underestimation of systolic pressure.
This discovery suggests that adjusting the measurement process, such as raising the arm before taking a reading, could correct this inaccuracy without needing new devices. If new devices are created, they might integrate additional inputs like age or body mass index to provide more accurate readings.
The research team seeks funding for clinical trials to further test these findings in real-world settings. Collaboration with industry and clinical professionals will be crucial to implementing these changes in practice.
This study was supported by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI). Anurag Agarwal is a Fellow of Emmanuel College, Cambridge.