Abstract
BackgroundThe Center for Disease Control and Prevention (CDC) indicates that one of the largest problems threatening healthcare includes antibiotic resistance. Tetracycline, an effective antibiotic that has been in use for many years, is becoming less successful in treating certain pathogens. To better understand the temporal patterns in the growth of antibiotic resistance, patient diagnostic test records can be analyzed.MethodsData mining methods including frequent item set mining and association rules via the Apriori algorithm were used to analyze results from 80,241 Target Enriched Multiplex-PCR (TEM-PCR) reference laboratory tests. From the data mining results, five common respiratory pathogens and their co-detection rates with tetracycline resistance genes (TRG) were further analyzed and organized according to year, patient age, and geography.ResultsFrom 2010, all five pathogens were associated with at least a 24% rise in co-detection rate for TRGs. Patients from 0–2 years old exhibited the lowest rate of TRG co-detection, while patients between 13–50 years old displayed the highest frequency of TRG co-detection. The Northeastern region of the United States recorded the highest rate of patients co-detected with a TRG and a respiratory pathogen. Along the East–west gradient, the relative frequency of co-detection between TRGs and respiratory pathogens decreased dramatically.ConclusionsSignificant trends were uncovered regarding the co-detection frequencies of TRGs and respiratory pathogens over time. It is valuable for the field of public health to monitor trends regarding the spread of resistant infectious disease, especially since tetracycline continues to be utilized a treatment for various microbial infections. Analyzing large datasets containing TEM-PCR results for co-detections provides valuable insights into trends of antibiotic resistance gene expression so that the effectiveness of first-line treatments can be continuously monitored.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2334-14-460) contains supplementary material, which is available to authorized users.
Highlights
The Center for Disease Control and Prevention (CDC) indicates that one of the largest problems threatening healthcare includes antibiotic resistance
Frequent item sets are groups of DNA markers that occur more frequently than a minimum support level in the database. In this dataset, Tetracycline resistance genes (TRGs) and S. pneumoniae were codetected in 19.8% of the tests that identified at least one marker, which is above the minimum support count of 50 positive tests
S. pneumoniae and H. influenzae were co-detected with TRGs 19.8% and 15.1% of all positive tests results
Summary
The Center for Disease Control and Prevention (CDC) indicates that one of the largest problems threatening healthcare includes antibiotic resistance. Antibiotic resistance directly costs healthcare over $20 billion annually; after including lost productivity, the total costs exceed $35 billion [8] These enormous costs of tetracycline resistance may be largely unnecessary, as over 50% of the antibiotics prescribed are unnecessary [8]. Agriculturalists are reluctant to follow these policy changes because of a lack of factual evidence linking excess usage to rising levels of resistance Even if this aspect of tetracycline resistance is widely disputed, the CDC strongly argues that tracking trends in existing antibiotic infections is a key weapon in preventing new antibiotic resistant infections
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