Waiting to exhale

MIT finds new diagnostic tool in capnograph analysis of CO2 in patients’ breath

Lori Lesko
CAMBRIDGE, Mass.—Scientists from the Massachusetts Institute of Technology (MIT) Research Laboratory of Electronics, working with physicians from Harvard Medical School and the Einstein Medical Center in Philadelphia, have discovered that repurposing a piece of medical equipment—standard in all ambulances in the U.S. and Europe—could help paramedics make accurate diagnoses on the spot and thus save lives.
 
That piece of medical equipment is called a capnograph, a device that measures the concentration of carbon dioxide in a patient’s exhalations, according to an article in the December issue of IEEE Transactions on Biomedical Engineering, written by the MIT/Harvard team. The waveform displayed by the capnograph is called a capnogram, which, according to the article, can determine with high accuracy whether a patient is suffering from emphysema or heart failure.
 
This information could prevent the wrong treatment regimen, which would increase the patient’s risk of severe complications and worse, according to George Verghese, professor of Electrical and Biomedical Engineering at MIT and one of the paper’s co-authors.
For instance, say an ambulance arrives on the scene to find an elderly man with shortness of breath, struggling to speak, Verghese posited. Is he suffering from acute emphysema or heart failure? The symptoms look the same, but initiating the wrong treatment regimen will increase the patient’s risk of severe complications.
 
“This machine (capnogram) is ubiquitous,” Verghese stated. “It’s actually in every emergency department and operating room, but the use that they’ve typically made of it is much more limited than what we were attempting here.”
 
Publication of the research paper is just the first step in the process of communicating this work, and encouraging further development, according to Verghese. “It may indeed be of interest to medical personnel, including paramedics, as an indication of what might be more routinely available in the future with further development by us and others,” he said, adding that they are still at “a relatively early stage” and will be “continuing our research into what the capnogram might be able to reveal about the cardiorespiratory state and for applications in monitoring and treatment.”
 
In the U.S., capnography was first introduced in the 1980s as a way to aid medical professionals inserting breathing tubes into the tracheas of sedated patients, according to MIT. But over time, physicians observed that the capnograms of patients with congestive heart failure and emphysema—or chronic obstructive pulmonary disease, as it’s known in the medical literature—were subtly but consistently different, both from each other and from those of healthy subjects.
 
The study began after Dr. Baruch Krauss, an emergency medicine specialist at Boston Children’s Hospital and an associate professor at Harvard Medical School, said he thought that the capnographic signal could be a source of diagnostically useful information, particularly for paramedics. MIT was interested, and the investigation began.
 
“The information had been known to be a source of limited diagnostic information, but [Krauss’] belief, a consequence of his own extensive experience, was that more information could be gleaned if the appropriate computational tools were applied,” Verghese said.
 
Thomas Heldt of MIT’s Institute of Medical Engineering and Science noted that, “We didn’t even know the word ‘capnography’ until Baruch set up a meeting with us and came and told us about it.”
 
In 2011, Verghese and Heldt recruited Rebecca Mieloszyk, a student in their group who had just begun her master’s degree, to investigate the relationship between patients’ capnograms and their ultimate diagnoses.
 
Mieloszyk’s first task was to identify features of the capnographic signal that appeared to vary between populations. Once she had identified maybe a dozen such features, she wrote a machine-learning algorithm that would look for patterns in the features that seemed to correlate with patients’ ultimate diagnoses. But that algorithm was somewhat unconventional.
 
In their tests, the MIT researchers and their colleagues found that their algorithm for distinguishing healthy subjects from those with emphysema yielded an area under the curve of 0.98, according to the journal article. The algorithm that distinguished emphysema patients from those with congestive heart failure checked in at 0.89.
 
To validate the findings of the published paper, other members of Verghese’s and Heldt’s team are evaluating whether capnography can measure the severity of asthma attacks and the degree of sedation in patients undergoing medical procedures. All of these findings could break new ground in the field of diagnostics.
 
Their work appeared in a paper titled “Automated Quantitative Analysis of Capnogram Shape for COPD–Normal and COPD–CHF Classification.”

Lori Lesko

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