Evidence map›Paper›PMID 40636544›Full record

ReviewHealth science reports2025

Prevalence of Healthcare-Acquired Infections Among Adults in Intensive Care Units: A Systematic Review and Meta-Analysis.

Alex Odoom, Eric S Donkor

Abstract readReview
In one paragraph

Review in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. 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

2 authors.

Alex OdoomDepartment of Medical Microbiology University of Ghana Medical School Accra Ghana.ORCID https://orcid.org/0000-0001-5761-1564
Eric S DonkorDepartment of Medical Microbiology University of Ghana Medical School Accra Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aim: Healthcare-acquired infections (HAIs) are a major cause of morbidity and mortality among critically ill adult patients admitted to intensive care units (ICUs) with underlying health conditions. Precisely estimating the burden of HAIs in adult ICUs is important for guiding prevention efforts and assessing the impact of intervention programs. This review aims to synthesize the available epidemiological data on the prevalence of different HAI types in adult ICUs. Methods: A systematic search was conducted via the PubMed, Scopus, and Web of Science databases to identify prevalence studies of HAIs published up to August 14, 2024, involving adult ICU patients. Pooled prevalence estimates and 95% confidence intervals were calculated using random effects models. Heterogeneity was assessed using the Results: A total of 21 studies involving 15,966 patients with 4288 adult ICU HAI cases were included in the meta-analysis. Pneumonia, whether ventilator-associated (VAP) or non-VAP, demonstrated the highest prevalence. The pooled all-cause pneumonia and VAP prevalence were 51.0% (95% CI 40.0-63.0%, Conclusion: This review revealed that BSIs, UTIs, pneumonia, and VAP constitute the most common HAIs in adults. Invasive devices, surgery, antimicrobial exposure, and underlying patient health conditions increase the risk. Targeting reductions in device usage durations and optimizing antibiotic stewardship may help lower infection rates in intensive care units.

Indexed as

healthcare‐acquired infectionsintensive care unitinvasive devicesprevalencereviewrisk factors

Identifiers

PMID40636544
PMCPMC12239516

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.