(NaturalNews) In this high-tech world, sometimes it's better to rely on a low-tech solution or, in this case,
no tech.
A new study to be published in the Christmas issue of the
British Medical Journal found that dogs can be used to sniff out Clostridium difficile, or C-diff, the element that is responsible for a rising number of hospital infections that are extremely resistant to antibiotics.
The olfactory sense of dogs can be used to identify C-diff infections in stool samples as well as the air surrounding patients in the hospital environment, all with a high degree of accuracy, researchers said.
The journal said current findings support earlier conclusions that dogs are capable of detecting various types of cancer as well, and may have potential for screening hospital wards to help prevent C-diff outbreaks.
The infectious C-diff occurs most commonly in older patients who have recently finished a course of antibiotics in the hospital. But the infections can also begin in the community, especially in nursing homes and other skilled facilities. Symptoms of the infection can range from mild diarrhea to a life-threatening bowel inflammation.
Some questions remain, but early results are promisingEarly detection of the infection is important if doctors hope to contain its spread, but diagnostic tests confirming it are slow (and expensive), which can delay treatment for as much as a week.
Researchers said that diarrhea as a result of a C-diff infection has a certain smell, and that
dogs - with their superior olfactory capabilities - likely could detect it much better, in comparison with humans. That supposition prompted scientists in the Netherlands to see if dogs could be trained to sniff out C-diff.
Scientists used a two-year-old male Beagle (named
Cliff) that had been trained by a professional instructor to spot C-diff in stool samples and in patients who had contracted the
infection. Cliff was taught to either lay down or sit when he detected the specific scent.
Following two months of training, Cliff's detection capability was formally tested on 50 C-diff positive and 50 C-diff negative stool samples, said scientists. He managed to correctly identify all 50 positive samples and 47 of the 50 negative samples.
The results equate to 100 percent sensitivity and 94 percent specificity (sensitivity measures the proportion of positives correctly identified, while specificity measures the proportion of negatives correctly identified).
Cliff was then taken to two
hospital wards to conduct further detection tests in a live environment. The dog managed to correctly identify 25 of 30 cases (83 percent sensitivity) and 265 of 270 negative controls (98 percent specificity). Researchers added that the
dog was efficient and quick, managing to screen a complete hospital ward for the presence of patients infected with C-diff in fewer than 10 minutes.
Early detection certainly possibleScientists admitted there were some limitations to the study, such as the unpredictability of using an animal as a diagnostic tool, as well as the possibility that the dog itself could spread infections. Other scientists say other unanswered questions remain.
Still, they note that the study demonstrates that training a dog to detect C-diff infection with a high degree of accuracy, both in samples of stool and in patients who are hospitalized and could contract the infection.
"Early detection could overcome common diagnostic delays (lack of clinical suspicion, delays in sampling stool, and laboratory procedures) and lead to prompt hygienic measures and treatment," the researchers concluded. "This could have potential for C. difficile infection screening in healthcare facilities and thus contribute to C. difficile infection outbreak control and prevention."
Sources:http://www.eurekalert.org/pub_releases/2012-12/bmj-dca121212.phphttp://www.bmj.com/content/345/bmj.e7396http://www.naturalnews.com/037709_fecal_matter_c_diff_infection.html
Have comments on this article? Post them here:
people have commented on this article.
Email this article to a friend
Now Available from 
