Observational studyCritical care medicine2018
The Association Between Ventilator Dyssynchrony, Delivered Tidal Volume, and Sedation Using a Novel Automated Ventilator Dyssynchrony Detection Algorithm.
Observational study in Critical care medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
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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
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application progress of machine learning in patient-ventilator asynchrony during mechanical ventilation: a systematic review.Critical care (London, England) · 2025Pooled it
- Early Neuromuscular Blockade in the Acute Respiratory Distress Syndrome.The New England journal of medicine · 2019Trial
- Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation.World journal of critical care medicine · 2026Review
- Post-resuscitation pre-hospital emergency anaesthesia for exchange of a supraglottic airway device with an endotracheal tube - a multicentre observational study.BMC emergency medicine · 2026Observational
- Deep learning for time-series segmentation of mechanical ventilator waveforms.Scientific reports · 2026Article
- Waveform data capture substantial variation in tidal volume and other respiratory parameters.Annals of the American Thoracic Society · 2026Article
- Ventilatory asynchronies induced by routine clinical practices in the intensive care unit: A systematic observation combined with a scoping review.Canadian journal of respiratory therapy : CJRT = Revue canadienne de la therapie respiratoire : RCTR · 2026Article
- RMS: a ML-based system for ICU respiratory monitoring and resource planning.NPJ digital medicine · 2025Article
- Deep Learning for Time-Series Segmentation of Mechanical Ventilator Waveforms.Research square · 2025Article
- Empirical phenotyping of joint patient-care data supports hypothesis-driven investigation of mechanical ventilation consequences.Scientific reports · 2025Article
- Developing A Data Pipeline to Quantify Ventilator Waveforms.medRxiv : the preprint server for health sciences · 2025Article
- Real-time detection of respiratory circuit events in mechanical ventilation using deep learning.NPJ digital medicine · 2025Article
- Can we predict the future of respiratory failure prediction?Critical care (London, England) · 2025Review
- Machine Learning and Artificial Intelligence in Intensive Care Medicine: Critical Recalibrations from Rule-Based Systems to Frontier Models.Journal of clinical medicine · 2025Review
- Artificial Intelligence for the Detection of Patient-Ventilator Asynchrony.Respiratory care · 2025Review
- Let's get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony.Intensive care medicine experimental · 2025Review
- Article
- Artificial intelligence in respiratory care.Frontiers in digital health · 2024Review
- Driving pressure, as opposed to tidal volume based on predicted body weight, is associated with mortality: results from a prospective cohort of COVID-19 acute respiratory distress syndrome patients.Critical care science · 2024Observational
- The oesophageal balloon for respiratory monitoring in ventilated patients: updated clinical review and practical aspects.European respiratory review : an official journal of the European Respiratory Society · 2023Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveVentilator dyssynchrony is potentially harmful to patients with or at risk for the acute respiratory distress syndrome. Automated detection of ventilator dyssynchrony from ventilator waveforms has been difficult. It is unclear if certain types of ventilator dyssynchrony deliver large tidal volumes and whether levels of sedation alter the frequency of ventilator dyssynchrony.
designA prospective observational study.
settingA university medical ICU. PATIENTS: Patients with or at risk for acute respiratory distress syndrome.
interventionsContinuous pressure-time, flow-time, and volume-time data were directly obtained from the ventilator. The level of sedation and the use of neuromuscular blockade was extracted from the medical record. Machine learning algorithms that incorporate clinical insight were developed and trained to detect four previously described and clinically relevant forms of ventilator dyssynchrony. The association between normalized tidal volume and ventilator dyssynchrony and the association between sedation and the frequency of ventilator dyssynchrony were determined. MEASUREMENTS AND MAIN
resultsA total of 4.26 million breaths were recorded from 62 ventilated patients. Our algorithm detected three types of ventilator dyssynchrony with an area under the receiver operator curve of greater than 0.89. Ventilator dyssynchrony occurred in 34.4% (95% CI, 34.41-34.49%) of breaths. When compared with synchronous breaths, double-triggered and flow-limited breaths were more likely to deliver tidal volumes greater than 10 mL/kg (40% and 11% compared with 0.2%; p < 0.001 for both comparisons). Deep sedation reduced but did not eliminate the frequency of all ventilator dyssynchrony breaths (p < 0.05). Ventilator dyssynchrony was eliminated with neuromuscular blockade (p < 0.001).
conclusionWe developed a computerized algorithm that accurately detects three types of ventilator dyssynchrony. Double-triggered and flow-limited breaths are associated with the frequent delivery of tidal volumes of greater than 10 mL/kg. Although ventilator dyssynchrony is reduced by deep sedation, potentially deleterious tidal volumes may still be delivered. However, neuromuscular blockade effectively eliminates ventilator dyssynchrony.
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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.