Evidence map›Paper›PMID 36609225›Full record

ArticleBMC infectious diseases2023

Unintended impact of COVID-19 pandemic on the rate of catheter related nosocomial infections and incidence of multiple drug resistance pathogens in three intensive care units not allocated to COVID-19 patients in a large teaching hospital.

Farid Zand, Hedayatollah Vakili, Naeimehossadat Asmarian, Mansoor Masjedi, Golnar Sabetian, Reza Nikandish, Elham Shafiee, Azita Tabatabaei Esfehani, Fatemeh Azadi, Anahita Sanaei Dashti

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  3. Article
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  5. Article
  6. Treatment and Management ofInfection and drug resistance · 2024
    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

10 authors at 1 institution in 1 country.

Farid ZandAnesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Hedayatollah VakiliFaghihi Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
Naeimehossadat AsmarianAnesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Mansoor MasjediAnesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Golnar SabetianTrauma Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Reza NikandishAnesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Elham ShafieeAnesthesiology and Critical Care Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Azita Tabatabaei EsfehaniNemazee Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
Fatemeh AzadiNemazee Hospital, Shiraz University of Medical Sciences, Shiraz, Iran.
Anahita Sanaei DashtiProfessor Alborzi Clinical Microbiology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. anahitasanaei@gmail.com.
Shiraz University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe prevalence of resistant hospital infections in the intensive care unit (ICU) increases mortality and antibiotic resistance. COVID-19 pandemic may have unintended impact on nosocomial infections (NI) and the prevalence of resistant microorganism. METHODOLOGY: The present non-interventional study was performed by a pre and a post survey each lasting 8 months before (March-October 2019) and after (March-October 2020) the onset of COVID-19 pandemic in three ICU's, not allocated to COVID-19 patients, in Nemazee Hospital, Shiraz, Iran. The rates of the following nosocomial infections were compared at pre- and post-pandemic period: ventilator associated pneumonia (VAP), central line associated blood stream infection (CLABSI), catheter-associated urinary tract infections (CAUTI) and incidence of multiple drug resistance (MDR) pathogens.

resultsPre-pandemic and pandemic incidence of VAP was 23.5 and 17.2 cases per 1000 device-days, respectively; an absolute decrease of 27%. The main reason for the decrease in the rate of VAP during the pandemic was a significant decrease in the rate of VAP caused by Acinetobacter baumannii; from 39 to 17% in total VAP episodes. The rate of VAP associated with other microorganisms remained relatively unchanged from 14.2 cases in pre-pandemic period to 14.3 cases per 1000 MV-days during the pandemic (P = 0.801). Pre-pandemic incidence of CLABSI was 7.3 cases and, in pandemic period, was 6.5 cases per 1000 device-days (IRR = 0.88, 95% CI  0.43-1.73, P = 0.703). Pre-pandemic incidence of CAUTI was 2 and in pandemic period, was 1.4 cases per 1000 device-days (IRR = 0.70, 95% CI  0.22-1.98, P = 0.469).

conclusionThe results of the present study showed a decrease in the incidence of VAP in critically ill non-COVID-19 patients during the pandemic compared to before the pandemic, especially regarding Acinetobacter baumannii.

Indexed as

Acinetobacter baumanniiCatheter-Related InfectionsCOVID-19Cross InfectionPneumonia, Ventilator-AssociatedUrinary Tract InfectionsCathetersDrug Resistance, MultipleHospitals, TeachingHumansIncidenceIntensive Care UnitsPandemicsProspective StudiesCatheter-associated urinary tract infections (CAUTI)Central line associated blood stream infection (CLABSI)COVID-19Intensive care unit (ICU)Multiple drug resistance (MDR)Nosocomial infection (NI)Ventilator associated pneumonia (VAP)

Identifiers

PMID36609225
PMCPMC9821351
OpenAlexW4313650290

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.