PubMed · 73987
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
E J Goldstein, H H Caffee, J E Price, D M Citronbaum, T A Miller, S M Finegold. 1977-12-17. Human bite infections.. https://doi.org/10.1016/s0140-6736(77)92701-5
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
In this paper we propose a sample size calculation method for testing on a binomial proportion when binary observations are dependent within clusters. In estimating the binomial proportion in clustered binary data, two weighting systems have been popular: equal weights to clusters and equal weights to units within clusters. When the number of units varies cluster by cluster, performance of these two weighting systems depends on the extent of correlation among units within each cluster. In addition to them, we will also use an optimal weighting method that minimizes the variance of the estimator. A sample size formula is derived for each of the estimators with different weighting schemes. We apply these methods to the sample size calculation for the sensitivity of a periodontal diagnostic test. Simulation studies are conducted to evaluate a finite sample performance of the three estimators. We also assess the influence of misspecified input parameter values on the calculated sample size. The optimal estimator requires equal or smaller sample sizes and is more robust to the misspecification of an input parameter than those assigning equal weights to units or clusters.
A premature baby developed a testicular abscess on day 28 of life. The pus aspirated from the abscess grew a mixture of beta hemolytic Streptococcus and a Bacteroides species. The source of this infection could not be identified. The baby improved on antibiotic therapy. This is the first reported case of a polymicrobial testicular infection involving an anaerobe in a neonate. The relevant literature is reviewed.
Batteroides fragilis is the anaerobe most frequently isolated from human infections. Strains of this species are not easily distinguished by phenotypic tests. It is important to make this distinction because virulence may vary between strains and because B. fragilis seems to be a heterogeneous species. The aim of this study was to assess the utility of randomly amplified polymorphic DNA (RAPD) analysis for differentiation of 46 strains of B. fragilis. Twenty-seven of the strains belonged to Johnson's DNA homology group I and 8 to group II, while 11 strains had not been assigned to any of these groups (NI group). The primers OPA16 and 18 were chosen among 30 primers tested for optimal RAPD analysis. OPA18 gave best discrimination, revealing a total of 15 genotypes while OPA16 gave 13. The gels obtained after RAPD analysis were evaluated with the Dendron computer-assisted program. Most strains showed similarity levels (S(AB)) within 70%. Strain clusters thus established were not always in agreement with DNA homology since strains from both homology groups fell in the same cluster. Similarly, strains of the NI group fell among the group I and II homology strains. RAPD was useful for differentiation of B. fragilis strains and thus probably suitable for epidemiological studies. On the other hand, DNA-DNA homology, comparing the entire genome of strains rather than a few random priming sites, would be more reliable for taxonomy. Computer-assisted gel analysis made it possible to objectively evaluate multiple banding patterns, thereby increasing the reliability of the RAPD analysis.