Evidence map›Paper›PMID 38156205›Full record

ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2023

Impact of intensified prevention measures on the rate of hospital-acquired bloodstream infections among mechanically ventilated COVID-19 patients.

Shimrit Lampl, Yael Cohen, Yasmin Maor, Debby Ben-David

Open access · goldAbstract read
In one paragraph

Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 34% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

4 authors at 2 institutions in 1 country.

Shimrit LamplWolfson Medical Center, Holon, Israel.
Yael CohenWolfson Medical Center, Holon, Israel.
Yasmin MaorWolfson Medical Center, Holon, Israel.ORCID https://orcid.org/0000-0001-7258-3434
Debby Ben-DavidWolfson Medical Center, Holon, Israel.ORCID https://orcid.org/0000-0003-3267-5478
Tel Aviv University · ILWolfson Medical Center · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The COVID-19 pandemic was associated with increased rates of hospital-acquired infections. During the early months of the pandemic, we observed high rates of hospital-acquired bloodstream infections (HA-BSIs) among COVID-19 patients, prompting the implementation of intensified prevention measures. Objectives: To assess the prevalence of HA-BSI among mechanically ventilated COVID-19 patients, identify risk factors, and evaluate the effect of prevention measures. Methods: We conducted a retrospective matched case-control study in adult medical step-up units between March 1, 2020, and March 31, 2021. We matched mechanically ventilated COVID-19 patients with ventilated non-COVID-19 patients based on age group and length of stay before ventilation. In response to the high rates of HA-BSI among COVID-19 patients, a comprehensive infection control intervention was implemented. Results: A total of 136 COVID-19 patients were matched with 136 non-COVID-19 patients. No significant differences were observed in pre-hospitalization characteristics. The central venous catheter utilization ratio was higher in COVID-19 patients (83.6%) versus 35.6% in the control group ( Conclusions: Mechanically ventilated COVID-19 patients were at higher risk for developing HA-BSI compared to non-COVID-19 patients. Intensified prevention measures were associated with decreased rates of HA-BSI.

Identifiers

PMID38156205
PMCPMC10753508
OpenAlexW4389746100

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.