| Literature DB >> 22304733 |
Juan C Escobar1, Darlene Bhavnani, Gabriel Trueba, Karina Ponce, William Cevallos, Joseph Eisenberg.
Abstract
Diarrheal risk associated with Plesiomonas shigelloides infection was assessed in rural communities in northwestern Ecuador during 2004-2008. We found little evidence that single infection with P. shigelloides is associated with diarrhea but stronger evidence that co-infection with rotavirus causes diarrhea.Entities:
Mesh:
Year: 2012 PMID: 22304733 PMCID: PMC3310445 DOI: 10.3201/eid1802.110562
Source DB: PubMed Journal: Emerg Infect Dis ISSN: 1080-6040 Impact factor: 6.883
FigureCase prevalence (black) and weighted community prevalence (white) of enteric pathogens, Ecuador, 2004–2008. Identification of pathogenic Escherichia coli was based on the genes given in parentheses. EIEC, enteroinvasive E. coli; Ipah, invasion plasmid antigen gene; ETEC, enterotoxigenic E. coli; LT, heat-labile toxin; ST, heat-stable toxin; EPEC, enteropathogenic E. coli; bfp, bundle-forming pili.
RRs and bootstrapped 95% CIs for single infections and co-infections with Plesiomonas shigelloides, Ecuador, 2004–2008*
| Co-infection | RRSingle P.shig (95% CI) | RRCo-Infection (95% CI) | RRCrude (95% CI) | RRMH-Pooled (95% CI) | Wald test for heterogeneity | p value |
|---|---|---|---|---|---|---|
| Any pathogen | 1.5 (0.9–2.2) | 5.6 (3.5–9.3) | 2.6 (1.9–3.5) | 2.7 (1.9–3.6) | 32.1 | <0.001 |
| Rotavirus | 1.5 (0.9–2.2) | 16.2 (5.5–62.3) | 1.7 (1.1–2.5) | 1.9 (1.2–2.9) | 61.8 | <0.001 |
| 1.5 (0.9–2.2) | 2.1 (1.0–3.9) | 1.5 (1.0–2.2) | 1.6 (1.1–2.3) | 1.3 | 0.2 | |
| 1.5 (0.9–2.2) | 13.8 (3.3–69.3) | 1.6 (1.1–2.4) | 1.7 (1.1–2.6) | 32.8 | <0.001 |
*RR, risk ratio. RRcrude = the unadjusted RR and RRMH-pooled is the pooled Mantel-Haenszel RR ratio estimate. The Wald test assesses whether the strata RRSingle P.shig and RRco-infection differ. Because of the clustered study design and the unequal sampling probabilities of controls, we chose not to use logistic regression models. Instead, we applied a nonparametric approach by using sampling weights to estimate RRs, as one would for a cohort study. We bootstrapped 1,000 samples from the original dataset, and with each new sample, we estimated the RR associated with single infection and co-infection. The lower 0.025 and upper 0.975 percentiles of the bootstrap distribution are reported as 95% CIs. Statistical analyses were conducted by using R version 2.11.1 (www.r-project.org).