ArticleScientific reports2022
Study of risk factors for healthcare-associated infections in acute cardiac patients using categorical principal component analysis (CATPCA).
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 15 citations in OpenAlex.
- Cultural Adaptation and Selection of a Minimal Set of Variables from Two Adolescent Pregnancy Risk Instruments (IRENE and REND) in Colombian Schoolgirls.Nursing reports (Pavia, Italy) · 2026Article
- Cumulative Vulnerability in Cardiac Critical Care: A Framework for Understanding Healthcare-Associated Infections and Their Progression to Severe Infection and Sepsis.Medicina (Kaunas, Lithuania) · 2026Article
- Reduced Left Ventricular Ejection Fraction as a Marker of Vulnerability to Healthcare-Associated Infections in Coronary Care Unit Patients: A Single-Centre Cohort Study.Journal of clinical medicine · 2026Article
- Prevalence of Healthcare-Associated Infections in Patients with Cardiovascular Diseases: A Literature Review.Journal of clinical medicine · 2025Review
- Activating Thermoplastic Polyurethane Surfaces with Poly(ethylene glycol)-Based Recombinant Human α-Defensin 5 Monolayers for Antibiofilm Activity.ACS applied bio materials · 2025Article
- Article
- Forecasting medical state transition using machine learning methods.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using categorical principal component analysis, we aimed to determine the relationship between health care-associated infections (HAIs) and diagnostic categories (DCs) in patients with acute heart disease using data collected in the Spanish prospective ENVIN-HELICS intensive care registry over a 10-year period (2005-2015). A total of 69,876 admissions were included, of which 5597 developed HAIs. Two 2-component CATPCA models were developed. In the first model, all cases were included; the first component was determined by the duration of the invasive devices, the ICU stay, the APACHE II score and the HAIs; the second component was determined by the type of admission (medical or surgical) and by the DCs. No clear association between DCs and HAIs was found. Cronbach's alpha was 0.899, and the variance accounted for (VAF) was 52.5%. The second model included only admissions that developed HAIs; the first component was determined by the duration of the invasive devices and the ICU stay; the second component was determined by the inflammatory response, the mortality in the ICU and the HAIs. Cronbach's alpha value was 0.855, and VAF was 46.9%. These findings highlight the role of exposure to invasive devices in the development of HAIS in patients with acute heart disease.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.