Evidence map›Paper›PMID 39076419›Full record

Observational studyFrontiers in public health2024

16S rRNA amplicon sequencing and antimicrobial resistance profile of intensive care units environment in 41 Brazilian hospitals.

Daniela Carolina de Bastiani, Claudia Vallone Silva, Ana Paula Christoff, Giuliano Netto Flores Cruz, Leonardo Daniel Tavares, Luana Silva Rodrigues de Araújo, Bruno Martins Tomazini, Beatriz Arns, Filipe Teixeira Piastrelli, Alexandre Biasi Cavalcanti and 2 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  4. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Daniela Carolina de Bastiani *BiomeHub Biotechnologies, Florianópolis, SC, Brazil.
Claudia Vallone Silva *Big Data Department - Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Ana Paula Christoff *BiomeHub Biotechnologies, Florianópolis, SC, Brazil.
Giuliano Netto Flores CruzBiomeHub Biotechnologies, Florianópolis, SC, Brazil.
Leonardo Daniel TavaresBig Data Department - Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Luana Silva Rodrigues de AraújoBig Data Department - Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.
Bruno Martins TomaziniHospital Sírio Libanês, São Paulo, SP, Brazil.
Beatriz ArnsHospital Moinhos de Vento, Porto Alegre, RS, Brazil.
Filipe Teixeira PiastrelliHospital Alemão Oswaldo Cruz, São Paulo, SP, Brazil.
Alexandre Biasi CavalcantiHcor Research Institute, Paraíso, SP, Brazil.
Luiz Felipe Valter de OliveiraBiomeHub Biotechnologies, Florianópolis, SC, Brazil.
Adriano Jose PereiraBig Data Department - Hospital Israelita Albert Einstein, São Paulo, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Infections acquired during healthcare setting stay pose significant public health threats. These infections are known as Healthcare-Associated Infections (HAI), mostly caused by pathogenic bacteria, which exhibit a wide range of antimicrobial resistance. Currently, there is no knowledge about the global cleaning process of hospitals and the bacterial diversity found in ICUs of Brazilian hospitals contributing to HAI. Objective: Characterize the microbiome and common antimicrobial resistance genes present in high-touch Intensive Care Unit (ICU) surfaces, and to identify the potential contamination of the sanitizers/processes used to clean hospital surfaces. Methods: In this national, multicenter, observational, and prospective cohort, bacterial profiles and several antimicrobial resistance genes from 41 hospitals across 16 Brazilian states were evaluated. Using high-throughput 16S rRNA amplicon sequencing and real-time PCR, the bacterial abundance and resistance genes presence were analyzed in both ICU environments and cleaning products. Results: We identified a wide diversity of microbial populations with a recurring presence of HAI-related bacteria among most of the hospitals. The median bacterial positivity rate in surface samples was high (88.24%), varying from 21.62 to 100% in different hospitals. Hospitals with the highest bacterial load in samples were also the ones with highest HAI-related abundances. Conclusion: This study demonstrated a diverse and spread pattern of bacteria and antimicrobial resistance genes covering a large part of the national territory in ICU surface samples and in sanitizers solutions. This data should contribute to the adoption of surveillance programs to improve HAI control strategies and demonstrate that large-scale epidemiology studies must be performed to further understand the implications of bacterial contamination in hospital surfaces and sanitizer solutions.

Indexed as

Cross InfectionDrug Resistance, BacterialIntensive Care UnitsRNA, Ribosomal, 16SAnti-Bacterial AgentsBacteriaBrazilHospitalsHumansProspective StudiesReal-Time Polymerase Chain ReactionAnti-Bacterial AgentsRNA, Ribosomal, 16S16S rRNA ampliconantimicrobial resistance (AMR) genebacteriahospital surfacesmicrobiomeNGS—next generation sequencing

Identifiers

PMID39076419
PMCPMC11284946

What OpenQuestion holds

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Registered trials

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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.