ArticleScientific reports2023
Defining predictors for successful mechanical ventilation weaning, using a data-mining process and artificial intelligence.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07098611 (A New Tool for Extubation Readiness in Mechanically Ventilated Patients), which is not on this map. Cited by 10 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.
A New Tool for Extubation Readiness in Mechanically Ventilated Patients: Readiness for EXtubation Score (REXs STUDY)
Who cites it
10 citing papers in PubMed.
- Dynamic Parameters within the First 72 H of ICU Admission Predict Extubation Failure and 28-Day Mortality in Severe Pneumonia-Induced ARDS: A Retrospective Cohort Study.The clinical respiratory journal · 2026Article
- Novel Respiratory Breath Hold Index: A Predictor for Successful Extubation in Mechanically Ventilated Patients, a Prospective Cohort Study.Life (Basel, Switzerland) · 2025Article
- Role of artificial intelligence in enhancing mechanical ventilation - A peek into the future.Indian journal of anaesthesia · 2025Article
- Article
- The association of ventilator mechanical power with weaning outcomes in intensive care unit patients: a narrative review.Journal of thoracic disease · 2025Review
- Advances in Machine Learning for Mechanically Ventilated Patients.International journal of general medicine · 2025Review
- Challenges in Transitioning from Controlled to Assisted Ventilation in Acute Respiratory Distress Syndrome (ARDS) Management.Journal of clinical medicine · 2024Article
- Geriatric rehabilitation center outcomes after successful weaning from extremely prolonged mechanical ventilation in older adults.Croatian medical journal · 2024Article
- Using Artificial Intelligence to Predict Mechanical Ventilation Weaning Success in Patients with Respiratory Failure, Including Those with Acute Respiratory Distress Syndrome.Journal of clinical medicine · 2024Review
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mechanical ventilation weaning within intensive care units (ICU) is a difficult process, while crucial when considering its impact on morbidity and mortality. Failed extubation and prolonged mechanical ventilation both carry a significant risk of adverse events. We aimed to determine predictive factors of extubation success using data-mining and artificial intelligence. A prospective physiological and biomedical signal data warehousing project. A 21-beds medical Intensive Care Unit of a University Hospital. Adult patients undergoing weaning from mechanical ventilation. Hemodynamic and respiratory parameters of mechanically ventilated patients were prospectively collected and combined with clinical outcome data. One hundred and eight patients were included, for 135 spontaneous breathing trials (SBT) allowing to identify physiological parameters either measured before or during the trial and considered as predictive for extubation success. The Early-Warning Score Oxygen (EWSO
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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.