A new analysis explains why common cuff-based blood pressure checks can be wrong. It shows that the artery beneath the cuff stays closed longer than expected, which makes systolic pressure appear lower than it is.
The study also points to simple tweaks that could sharpen readings and detect more cases of hypertension.
Researchers at the University of Cambridge built a physical model to test the mechanics behind the error. Their findings suggest protocol changes could improve accuracy without replacing standard cuffs.
Most blood pressure measurements use the auscultatory method. A cuff inflates around the upper arm until it blocks blood flow.
As the cuff deflates, a clinician listens for tapping sounds while watching the gauge. The first taps mark systolic pressure, and the last taps indicate diastolic pressure.
“The auscultatory method is the gold standard, but it overestimates diastolic pressure, while systolic pressure is underestimated,” said co-author Kate Bassil from Cambridge’s Department of Engineering.
“We have a good understanding of why diastolic pressure is overestimated, but why systolic pressure is underestimated has been a bit of a mystery.”
“Pretty much every clinician knows blood pressure readings are sometimes wrong, but no one could explain why they are being underestimated – there’s a real gap in understanding,” said co-author Anurag Agarwal, a professor at Cambridge’s Department of Engineering.
Earlier bench setups used rubber tubes to mimic arteries. Those tubes did not fully collapse under cuff pressure, which masked the source of the systolic error.
The team designed a simplified rig to recreate what happens in the arm below the cuff. Inflate the cuff, and the downstream segment becomes very low pressure.
That drop keeps the blood vessel walls pressed together for longer as the cuff pressure falls. Reopening is delayed, and the tapping begins later than it should. At that moment, the gauge reads too low for systolic pressure.
Instead of round rubber tubes, the researchers used flat-laying tubes that close completely under load. That substitution was key. It reproduced the low downstream pressures seen in the body.
The experimental method also revealed how cuff deflation timing interacts with vessel collapse and reopening.
In this setup, the delayed reopening showed up clearly. The physical mechanism matched what clinicians observe. Systolic pressure is biased down, while diastolic skews up. Together, those shifts can hide disease, especially when true systolic pressure is high.
“We are currently not adjusting for this error when diagnosing or prescribing treatments, which has been estimated to lead to as many as 30 percent of cases of systolic hypertension being missed,” Bassil said.
The study points to low-cost changes. One idea is to raise the arm before measuring. That could set a more predictable downstream pressure. If the underestimation then becomes predictable, clinicians can account for it.
“You might not even need new devices, just changing how the measurement is done could make it more accurate,” Agarwal said.
If new monitors are developed, they could ask for added inputs. Age, BMI, or tissue characteristics may correlate with downstream pressure.
Devices could use those signals to tailor the correction for each person. The goal is the same: reduce bias at the moment when the taps first appear.
Hypertension is the leading modifiable risk for early death worldwide. Missed systolic disease delays treatment, raising the odds of heart attack, stroke, and heart failure. Even small gains in accuracy can shift outcomes at the population scale.
More reliable readings also protect patients from the opposite error: overestimation, which can lead to unnecessary medications and side effects.
Getting both numbers right helps clinicians set appropriate treatment targets and helps patients trust the plan.
The Cambridge team is preparing for clinical trials to test the correction in real-world settings and across diverse populations.
Partnerships with clinicians and industry will be essential. Better calibration models will require broad validation, and training and workflow updates will also be important.
The promise is practical: keep the cuff, change the protocol, and understand the physics in the artery beneath the fabric. With these changes, routine checks could flag true risk more often, and the path from diagnosis to prevention could become much clearer.
The study is published in the journal PNAS Nexus.
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