ArticleCritical care (London, England)2013
An automated and standardized neural index to quantify patient-ventilator interaction.
Article in Critical care (London, England), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05144607 (Impact of the Display of Inspiratory Muscle Pressure Curves Estimated by Artificial Intelligence on the Ability of Health Care Professionals to Correctly Identify Patient-ventilator Asynchronies - Pmus Study), which is not on this map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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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.
Impact of the Display of Inspiratory Muscle Pressure Curves Estimated by Artificial Intelligence on the Ability of Health Care Professionals to Correctly Identify Patient-ventilator Asynchronies - Pmus Study
Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Monitoring the patient-ventilator asynchrony during non-invasive ventilation.Frontiers in medicine · 2022Pooled it
- Noninvasive Neurally Adjusted Ventilator Assist Ventilation in the Postoperative Period Produces Better Patient-Ventilator Synchrony but Not Comfort.Pulmonary medicine · 2020Trial
- Neural versus pneumatic control of pressure support in patients with chronic obstructive pulmonary diseases at different levels of positive end expiratory pressure: a physiological study.Critical care (London, England) · 2015Trial
- Application of neurally adjusted ventilatory assist (NAVA): a narrative review.Journal of thoracic disease · 2025Review
- Estimation of Respiratory Effort Through Diaphragmatic Electromyography Features.Sensors (Basel, Switzerland) · 2025Article
- Let's get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony.Intensive care medicine experimental · 2025Review
- Timing of activation of different inspiratory muscles during incremental inspiratory loading in healthy adults: A cross-sectional study.Canadian journal of respiratory therapy : CJRT = Revue canadienne de la therapie respiratoire : RCTR · 2025Article
- Post-insufflation diaphragm contractions in patients receiving various modes of mechanical ventilation.Critical care (London, England) · 2024Article
- Reimagining critical care: Trends and shifts in 21World journal of critical care medicine · 2024Article
- Article
- Advanced Respiratory Monitoring during Extracorporeal Membrane Oxygenation.Journal of clinical medicine · 2024Review
- Dyssynchronous diaphragm contractions impair diaphragm function in mechanically ventilated patients.Critical care (London, England) · 2024Observational
- Automated characterization of patient-ventilator interaction using surface electromyography.Annals of intensive care · 2024Article
- Closing the Gap in Patient-Ventilator Discordance Recognition.Respiratory care · 2024Article
- The Ability of Critical Care Physicians to Identify Patient-Ventilator Asynchrony Using Waveform Analysis: A National Survey.Respiratory care · 2024Article
- Analysis and applications of respiratory surface EMG: report of a round table meeting.Critical care (London, England) · 2024Review
- Recording of a left ventricle assist device electrical current with a neurally adjusted ventilation assist (NAVA) catheter: a small case series.Journal of clinical monitoring and computing · 2023Article
- Magnitude of Synchronous and Dyssynchronous Inspiratory Efforts during Mechanical Ventilation: A Novel Method.American journal of respiratory and critical care medicine · 2023Article
- Respiratory Variations of Central Venous Pressure as Indices of Pleural Pressure Swings: A Narrative Review.Diagnostics (Basel, Switzerland) · 2023Review
- Pressure-flow breath representation eases asynchrony identification in mechanically ventilated patients.Journal of clinical monitoring and computing · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe aim of this study was to validate an automated, objective and standardized algorithm for quantifying and displaying patient-ventilator interaction.
methodsUsing a new method to detect patient-ventilator synchrony, the present study re-analyzed previously acquired and published data from 24 mechanically ventilated adult patients (Colombo et al., Crit Care Med. 2011 Nov;39(11):2452-7). Patient-ventilator interactions were evaluated by comparing ventilator pressure and diaphragm electrical activity (EAdi) waveforms, recorded during pressure support ventilation. The EAdi and ventilator pressure waveforms were analyzed for their timings (manually and automatically determined), and the error between the two waveforms was quantified. A new index of patient-ventilator interaction (NeuroSync index), which is standardized and automated, was validated and compared to manual analysis and previously published indices of asynchrony.
resultsThe comparison of manual and automated detection methods produced high test-retest and inter-rater reliability (Intraclass correlation coefficient = 0.95). The NeuroSync index increased the sensitivity of detecting dyssynchronies, compared to previously published indices, which were found to only detect asynchronies.
conclusionThe present study introduces an automated method and the NeuroSync index to determine patient-ventilator interaction with a more sensitive analysis method than those previously described. A dashboard-style of graphical display allows a rapid overview of patient-ventilator interaction and breathing pattern at the bedside.
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