ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2019
Multi-step optimization of the filtration method for the isolation of Campylobacter species from stool samples.
Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 7 citations in OpenAlex.
- Genetic Diversity ofMicroorganisms · 2025Article
- Assessing the Prevalence and Dynamics of Emerging Campylobacterales in Human Stool Samples in Brussels by Filtration Culture.Pathogens (Basel, Switzerland) · 2024Article
- Campylobacter occurrence and antimicrobial resistance profile in under five-year-old diarrheal children, backyard farm animals, and companion pets.PLoS neglected tropical diseases · 2024Article
- Development of a novel and specialized cultivation method for isolatingIranian journal of veterinary research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The filtration method (FM) is the most effective isolation technique for Epsilobacteriaceae from stool samples. FM's different adaptations make it difficult to compare data between studies. This study was performed in three phases to optimize FM from a routine laboratory perspective. In July-September 2014 (part I), FM was performed on Mueller-Hinton agar containing 5% sheep blood and Columbia agar containing 5% sheep blood. In July 2016 (part II), FM was performed using 0.60-μm pore size polycarbonate filters (0.6-PC filter) and 0.45-μm pore size cellulose acetate filters (0.45-AC filter); in January 2018 (part III), the addition of hydrogen to incubators was studied. On 1146 stools analyzed in part I, the positive samples that showed no growth on the Butzler medium (n = 22/72, 30.6%) had improved growth of Epsilobacteriaceae when using the Columbia instead of the Mueller-Hinton medium (21/22 strains vs. 11/22, p < 0.05). In part II, on 718 stools, 91 strains grew with FM (12.7%), more with 0.6-PC filter (90/91) than with 0.45-AC filter (44/91) (p < 0.05). In part III, 578 stools were cultured, 98 Epsilobacteriaceae strains grew with FM, and 7% hydrogen finding significantly more Epsilobacteriaceae than without hydrogen (90/98, 91.8%, vs. 72/98, 73.5%; p < 0.05). The use of a Columbia medium containing 5% sheep blood with 0.6-PC filters incubated at 37 °C in a 7% hydrogen-enriched atmosphere led to an almost fourfold increase in the isolation rate of Epsilobacteriaceae among the studied combinations. Reference centers for Campylobacter should use standardized protocols to enable the comparison of prevalence in space and time.
Indexed as
Identifiers
What 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.