Linked Life Data

9698267

Source:http://linkedlifedata.com/resource/pubmed/id/9698267

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1998-10-9
pubmed:abstractText
In this study we examine the variation in Schistosoma japonicum egg counts caused by differences in worm loads between individuals and the variability of egg counts within individuals with a given worm load. Six villages were selected from an area moderately endemic for Asian schistosomiasis in the Dongting Lake region (Hunan province), China. From a total population of 3451 individuals (53.8% male; x = 31 years), 163 subjects were identified as consistently stool egg-positive based on three successive positive Kato-Katz (KK) smears (41.67 mg/smear) obtained from one stool specimen. The distribution of eggs among individuals was found to be strongly aggregated (k = 0.27), but the distribution within the three smears was found to be only slightly aggregated (k = 2.59), indicating only minor clustering of eggs in stools. The relatively slight clustering of eggs within stool specimens suggests that a single KK smear may be quite adequate for detecting individuals moderately to heavily infected (> 100 eggs/g stool (epg)), as needed for a strategy of morbidity control. However, for estimating the true prevalence of infection in a community, or for obtaining an accurate estimate of egg excretion for research studies, multiple KK smears are warranted.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
0001-706X
pubmed:author
pubmed:issnType
Print
pubmed:day
30
pubmed:volume
70
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
205-10
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Faecal egg aggregation in humans infected with Schistosoma japonicum in China.
pubmed:affiliation
Tropical Health Program, Australian Centre for International and Tropical Health and Nutrition, The Queensland Institute of Medical Research, Brisbane. allenR@qimr.edu.au
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't