U-M/VA computer model suggests that common use of
acid-reducing medicine to prevent stomach bleeding increases mortality from
infections
Newswise, November 10, 2015 — Right now, in any American
hospital, about half of the patients have a prescription for an acid-reducing
drug to reduce heartburn or prevent bleeding in their stomach and gut.
But that well-intentioned drug may actually boost their risk
of dying during their hospital stay, a new study finds – by opening them up to
infections that pose more risk than bleeding would.
In fact, according to a computer simulation based on
real-world risk and benefit data, around 90 percent of hospital inpatients who
were first prescribed these drugs in the hospital have a higher risk of dying
when they’re taking them, compared with their risk if they hadn’t gotten the
prescription.
And for around 80 percent of patients who were already on
these common drugs, called proton-pump inhibitors or PPIs, when they arrived at
the hospital, staying on them also may lead to a small increase in the risk of
dying.
The extra risk of death comes from the fact that reducing acid
in the stomach can increase the risk of infections – especially pneumonia and
Clostridium difficile, both of which pose a serious risk to hospitalized
patients who develop them.
The study, which uses a computer model to achieve a result
that otherwise would require an impractically large clinical trial, is
published in the Journal of General Internal Medicine by a team from the
University of Michigan Medical School and VA Ann Arbor Healthcare System.
“Many patients who come into the hospital are on these
medications, and we sometimes start them in the hospital to try to prevent
gastrointestinal, or GI, bleeds,” says lead author Matthew Pappas, M.D., MPH.
“But other researchers have shown that these drugs seem to
increase the risk of pneumonia and C. diff, two serious and potentially
life-threatening infections that hospitalized patients are also at risk for,”
he continues.
“Our new model allows us to compare that increased risk with the
risk of upper GI bleeding. In general, it shows us that we’re exposing many
inpatients to higher risk of death than they would otherwise have – and though
it’s not a big effect, it is a consistent effect.”
As a result of the new findings, he says, very few hospital
patients should start taking or continue on PPIs as a preventive measure
against gastrointestinal bleeding.
Pappas, a hospitalist physician at U-M with an engineering
background and a VA Health Services Fellow, worked with Sandeep Vijan, M.D.,
MPH, who treats patients at the VAAHS and is a member of the VA Center for
Clinical Management Research and U-M’s Institute for Healthcare Policy and
Innovation.
Pappas is a clinical lecturer, and Vijan a professor, in the U-M
Medical School’s Division of General Medicine. The project’s only funding was
Pappas’s fellowship support.
Cutting PPI use to cut infection risk
Pappas notes that nationally, some efforts have already shown
ways to reduce the rate of new PPI prescriptions to hospitalized patients –
about 20 percent of whom receive such orders right now.
But truly reducing PPI use in hospitals to the most
appropriate patients – those with existing GI bleeding – will take more effort,
Pappas predicts.
That’s because PPIs are built into many heuristics, or rules
of thumb, that guide much hospital care. For instance, when a patient receives
high-dose steroids in the hospital, the physician may automatically also
prescribe a PPI to prevent the GI bleeding that steroids can cause.
“In fact, in running our simulation, we thought we would find
some populations such as those on steroids or other medications often
prescribed together with PPIs, who would not experience the increased mortality
risk,” Pappas says.
“But that turned out not to be the case.” GI bleeds are
risky, it’s true. But hospital-acquired pneumonia and C. diff are much more
common.
Although research is still needed on why PPI use increases a
patient’s vulnerability to hospital-acquired pneumonia and C. diff infection,
the effect of the acid-reducing drugs on gut bacteria likely has a direct
impact. In the case of pneumonia, suppressing acid production may increase the
amount of bacteria in the stomach and throat, which can then get into the lungs
and cause pneumonia.
Model can be used for other risk-benefit balancing
Pappas notes that the model he developed with Vijan and recent
U-M Ford School of Public Policy graduate Sanjay Jolly could be applied to many
other situations where a common preventive or treatment measure in medicine
also carries with it an increased risk of an unwanted effect.
Using such models, based on data from observational studies,
could answer important questions in medicine without needing to carry out
massive prospective clinical trials.
To answer the question of whether the
predicted increase in mortality risk caused by PPIs in inpatients is real, he
says, would take a clinical trial of more than 64,000 patients randomly
assigned to receive PPIs or not. Since PPIs are available as generic
medications, the likelihood of such a study being funded and performed is
nearly zero.
“Any time there are complex risk/benefit tradeoffs, without
the possibility of a high-quality trial, this kind of simulation can help us
come up with answers to inform clinical care,” he says.
For instance, he’s now studying the issue of “bridging”
medication in patients who have been prescribed blood-thinning medications to
prevent a stroke. Such patients often receive a prescription for an injected
drug that will reduce stroke risk during the week or two before their regular
oral drugs take effect.
But that injection carries its own risk.
“Humans aren’t very good at recognizing very rare events, and
reacting appropriately to things that are unlikely to happen,” says Pappas.
“Physicians have an instinct to want to prevent very bad, though rare events –
but everything we do carries risks. We need to be mindful of the things we are
doing to prevent rare outcomes, and keep the risks in perspective. Computers
can help.”
Reference: Journal of General Internal Medicine,
DOI:10.1007/s11606-015-3536-7
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