ArticleAnnals of translational medicine2019
Active surveillance of ventilator-associated pneumonia in the intensive care unit and establishment of the risk grading system and effect evaluation.
Article in Annals of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 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
3 citing papers in PubMed, 6 citations in OpenAlex.
- Retraction to active surveillance of ventilator-associated pneumonia in the intensive care unit and establishment of the risk grading system and effect evaluation.Annals of translational medicine · 2021Article
- Neutrophil-to-Lymphocyte Ratio Predicts Mortality in Adult Renal Transplant Recipients with Severe Community-Acquired Pneumonia.Pathogens (Basel, Switzerland) · 2020Article
- Predicting ventilator-associated pneumonia.Annals of translational medicine · 2020Article
Corrections and comments
- Retraction · 2021-02-01Plagiarism of/in Article ·
- Commented on by
- Retracted
Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo discuss ventilator-associated pneumonia (VAP) patient's clinical characteristic and related factors in the intensive care unit (ICU), and to establish a risk grading system for VAP patients in the ICU in order to provide a reference for VAP prevention.
methodsA total of 1,513 patients in eight ICUs who received mechanical ventilation between June 2015 and June 2018 were randomized and into two groups, with 908 patients in the model group and 605 patients in the verification group. The model group was used to analyze the influencing factors of VAP and establish a risk grading system, while the verification group was used to verify the risk grading system. A receiver operating characteristic (ROC) curve was used to evaluate the predictive effect of the grading system.
resultsDuring the 3-year study period, of the 1,513 total patients, 188 patients were infected with VAP, leading to an incidence rate of 12.43% (188/1,513) and an infection rate of 15.23‰ (188/12,347). ICU length of stay, mechanical ventilation days, frequency of oral care, unused subglottic secretion drainage, tracheotomy, APACHE II score, and combined antibiotics use were risk factors of VAP infection for patients who received mechanical ventilation in the modeling group (P<0.05). In a VAP risk-grading system established based on risk factors, the high, medium and low-grade patients had a statistically significantly different VAP infection rate in the model group, and patients with a high grade had a higher risk of VAP infection. Patients' data in the model and verification groups were used to draw a ROC curve which showed a good predictive effect.
conclusionsThis study establishes and verifies the VAP risk grading system for patients who receive mechanical ventilation. It is helpful in high-risk patient surveillance and in reducing and preventing VAP infection.
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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 OpenQuestion graph.