SynthesisBMC infectious diseases2025
The burden and predictors of hospital-acquired infection in intensive care units across Sub-Sahara Africa: systematic review and metanalysis.
Synthesis in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- Predictors of Length of Hospital Stay Among Under-Five Children with Clinical Pneumonia at a Rural Tertiary Hospital Setting in South Africa.Pediatric reports · 2026Article
- Minimizing hospital acquired intensive care unit infections: A focus on prevention.World journal of critical care medicine · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHospital-acquired infection (HAI) refers to an infection that occurs during hospitalization and typically manifests 48 h after admission. Evidence suggests that the prevalence of HAIs in Sub-Saharan Africa (SSA) is significantly higher compared to other regions. These infections remain a major concern in low-income countries, contributing to elevated morbidity and mortality rates. This study aimed to assess the burden and identify predictors of HAIs in intensive care units (ICUs) across SSA.
methodsThis review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed, Scopus, Embase, Web of Science, Africa Index Medicus, ScienceDirect, HINARI, and Google Scholar to identify relevant studies published in English. This systematic review encompasses 44 articles published between 2003 and 2024, with the majority (22 articles) published recently between 2020 and 2024. The actual database search was conducted between January 1, 2025, and February 1, 2025. Articles irrelevant to this study's objectives, those without abstracts or full texts, unpublished reports, editorials, studies that did not clearly define outcomes, and studies written in languages other than English were excluded. The analysis was conducted using Stata version 17. The protocol was registered with PROSPERO under the registration number CRD 63,194,923,892. Quality assessment was performed using the Newcastle-Ottawa Scale, and data extraction followed the Joanna Briggs Institute methodology.
resultsA total of 44 primary samples were included in this meta-analysis. Using the random effect DerSimonian model, we showed that the pooled prevalence of hospital-acquired infections (HAIs) in intensive care units was 28.22% (95% CI: 23.61-32.81). Determinants of HAIs in the intensive care units included neonatal or advanced age (> 50 years), intubation, trauma, surgery, presence of comorbidities, catheterization, prolonged hospital stay, and HIV-positive status. CONCLUSION AND RECOMMENDATIONS: Individuals in extreme age groups, those with chronic diseases or immunocompromised conditions, and patients with specific risk factors (e.g., catheterization, prolonged hospitalization) were more prone to HAIs. Strengthening the quality of care and implementing effective infection control measures are recommended to reduce the burden of healthcare-associated infections (HAIs) in sub-Saharan Africa.
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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 Socratic graph.