ArticleEnvironmental monitoring and assessment2008
Fecal source tracking by antibiotic resistance analysis on a watershed exhibiting low resistance.
Article in Environmental monitoring and assessment, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Identifying fecal pollution sources using 3M(™) Petrifilm (™) count plates and antibiotic resistance analysis in the Horse Creek Watershed in Aiken County, SC (USA).Environmental monitoring and assessment · 2014Article
- Identification of source of faecal pollution of Tirumanimuttar River, Tamilnadu, India using microbial source tracking.Environmental monitoring and assessment · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ongoing development of microbial source tracking has made it possible to identify contamination sources with varying accuracy, depending on the method used. The purpose of this study was to test the efficiency of the antibiotic resistance analysis (ARA) method under low resistance by tracking the fecal sources at Turkey Creek, Oklahoma exhibiting this condition. The resistance patterns of 772 water-isolates, tested with nine antibiotics, were analyzed by discriminant analysis (DA) utilizing a five-source library containing 2250 isolates. The library passed various representativeness tests; however, two of the pulled-sample tests suggested insufficient sampling. The resubstitution test of the library individual sources showed significant isolate misclassification with an average rate of correct classification (ARCC) of 58%. These misclassifications were explained by low antibiotic resistance (Wilcoxon test P < 0.0001). Seasonal DA of stream E. coli isolates for the pooled sources human/livestock/deer indicated that in fall, the human source dominated (P < 0.0001) at a rate of 56%, and that human and livestock respective contributions in winter (35 and 39%), spring (43 and 40%), and summer (37 and 35%) were similar. Deer scored lower (17-28%) than human and livestock at every season. The DA was revised using results from a misclassification analysis to provide a perspective of the effect caused by low antibiotic resistance and a more realistic determination of the fecal source rates at Turkey Creek. The revision increased livestock rates by 13-14% (0.04 <or= P <or= 0.06), and decreased human and deer by 6-7%. Negative misclassification into livestock was significant (0.04 <or= P <or= 0.06). Low antibiotic resistance showed the greatest effect in this category.
Indexed as
Identifiers
17562197What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.