ArticleAntibiotics (Basel, Switzerland)2023
Post-Stroke Infections: Insights from Big Data Using Clinical Data Warehouse (CDW).
Article in Antibiotics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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
5 citing papers in PubMed.
- Deep Vein Thrombosis Prevention in Acute Ischemic Stroke Patients with Lower Limb Paralysis: A Narrative Review.Journal of clinical medicine · 2026Review
- The impact of airway management guided by Protection Motivation Theory on the prevention and prognosis of post-stroke pneumonia.Frontiers in neurology · 2025Article
- Predictive modelling of hospital-acquired infection in acute ischemic stroke using machine learning.Scientific reports · 2024Article
- A Single-Center Retrospective Study of Bacterial Infections After Acute Ischemic Stroke: The Prevalence Before and During the COVID-19 Pandemic.Medicina (Kaunas, Lithuania) · 2024Article
- Similarities and Differences between Multisystem Inflammatory Syndrome in Children (MIS-C) and Kawasaki Disease Shock Syndrome.Children (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
This study analyzed a digitized database of electronic medical records (EMRs) to identify risk factors for post-stroke infections. The sample included 41,236 patients hospitalized with a first stroke diagnosis (ICD-10 codes I60, I61, I63, and I64) between January 2011 and December 2020. Logistic regression analysis was performed to examine the effect of clinical variables on post-stroke infection. Multivariable analysis revealed that post-stroke infection was associated with the male sex (odds ratio [OR]: 1.79; 95% confidence interval [CI]: 1.49-2.15), brain surgery (OR: 7.89; 95% CI: 6.27-9.92), mechanical ventilation (OR: 18.26; 95% CI: 8.49-44.32), enteral tube feeding (OR: 3.65; 95% CI: 2.98-4.47), and functional activity level (modified Barthel index: OR: 0.98; 95% CI: 0.98-0.98). In addition, exposure to steroids (OR: 2.22; 95% CI: 1.60-3.06) and acid-suppressant drugs (OR: 1.44; 95% CI: 1.15-1.81) increased the risk of infection. On the basis of the findings from this multicenter study, it is crucial to carefully evaluate the balance between the potential benefits of acid-suppressant drugs or corticosteroids and the increased risk of infection in patients at high risk for post-stroke infection.
Indexed as
Identifiers
What Socratic holds
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.