Frequency of Screening and SBT Technique Trial - North American Weaning Collaboration (FAST-NAWC): a protocol for a multicenter, factorial randomized trial

Frequency of screening and SBT Technique Trial-North American Weaning Collaboration (FAST-NAWC): an update to the protocol and statistical analysis plan

BACKGROUND

This update summarizes key changes made to the protocol for the Frequency of Screening and Spontaneous Breathing Trial (SBT) Technique Trial-North American Weaning Collaborative (FAST-NAWC) trial since the publication of the original protocol. This multicenter, factorial design randomized controlled trial with concealed allocation, will compare the effect of both screening frequency (once vs. at least twice daily) to identify candidates to undergo a SBT and SBT technique [pressure support + positive end-expiratory pressure vs. T-piece] on the time to successful extubation (primary outcome) in 760 critically ill adults who are invasively ventilated for at least 24 h in 20 North American intensive care units.

METHODS/DESIGN

Protocols for the pilot, factorial design trial and the full trial were previously published in J Clin Trials ( https://doi.org/10.4172/2167-0870.1000284 ) and Trials (https://doi: 10.1186/s13063-019-3641-8). As planned, participants enrolled in the FAST pilot trial will be included in the report of the full FAST-NAWC trial. In response to the onset of the coronavirus disease of 2019 (COVID-19) pandemic when approximately two thirds of enrollment was complete, we revised the protocol and consent form to include critically ill invasively ventilated patients with COVID-19. We also refined the statistical analysis plan (SAP) to reflect inclusion and reporting of participants with and without COVID-19. This update summarizes the changes made and their rationale and provides a refined SAP for the FAST-NAWC trial. These changes have been finalized before completion of trial follow-up and the commencement of data analysis.

TRIAL REGISTRATION

Clinical Trials.gov NCT02399267.

Implementation of coordinated spontaneous awakening and breathing trials using telehealth-enabled, real-time audit and feedback for clinician adherence (TEACH): a type II hybrid effectiveness-implementation cluster-randomized trial

BACKGROUND

Intensive care unit (ICU) patients on mechanical ventilation often require sedation and analgesia to improve comfort and decrease pain. Prolonged sedation and analgesia, however, may increase time on mechanical ventilation, risk for ventilator associated pneumonia, and delirium. Coordinated interruptions in sedation [spontaneous awakening trials (SATs)] and spontaneous breathing trials (SBTs) increase ventilator-free days and improve mortality. Coordination of SATs and SBTs is difficult with substantial implementation barriers due to difficult-to-execute sequencing between nurses and respiratory therapists. Telehealth-enabled remote care has the potential to overcome these barriers and improve coordinated SAT and SBT adherence by enabling proactive high-risk patient monitoring, surveillance, and real-time assistance to frontline ICU teams.

METHODS

The telehealth-enabled, real-time audit and feedback for clinician adherence (TEACH) study will determine whether adding a telehealth augmented real-time audit and feedback to a usual supervisor-led audit and feedback intervention will yield higher coordinated SAT and SBT adherence and more ventilator-free days in mechanically ventilated patients than a usual supervisor-led audit and feedback intervention alone in a type II hybrid effectiveness-implementation cluster-randomized clinical trial in 12 Intermountain Health hospitals with 15 ICUs. In the active comparator control group (six hospitals), the only intervention is the usual supervisor-led audit and feedback implementation. The telehealth-enabled support (TEACH) intervention in six hospitals adds real-time identification of patients eligible for a coordinated SAT and SBT and consultative input from telehealth respiratory therapists, nurses, and physicians to the bedside clinicians to promote adherence including real-time assistance with execution. All intubated and mechanically ventilated patients ≥ 16 years of age are eligible for enrollment except for patients who die on the day of intubation or have preexisting brain death. Based on preliminary power analyses, we plan a 36-month intervention period that includes a 90-day run-in period. Estimated enrollment in the final analysis is up to 9900 mechanically ventilated patients over 33 months.

DISCUSSION

The TEACH study will enhance implementation science by providing insight into how a telehealth intervention augmenting a usual audit and feedback implementation may improve adherence to coordinated SAT and SBT and increase ventilator-free days.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT05141396 , registered 12/02/2021.

Biosignal-Based Digital Biomarkers for Prediction of Ventilator Weaning Success

We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care unit and collected continuous biosignal data: electrocardiogram (ECG), respiratory impedance, photoplethysmogram (PPG), arterial blood pressure, and ventilator parameters during a spontaneous breathing trial (SBT). We compared the collected biosignal data's variability between patients who successfully discontinued MV (n = 67) and patients who did not (n = 22). To evaluate the usefulness of the identified factors for predicting weaning success, we developed a machine learning model and evaluated its performance by bootstrapping. The following markers were different between the weaning success and failure groups: the ratio of standard deviations between the short-term and long-term heart rate variability in a Poincaré plot, sample entropy of ECG and PPG, α values of ECG, and respiratory impedance in the detrended fluctuation analysis. The area under the receiver operating characteristic curve of the model was 0.81 (95% confidence interval: 0.70-0.92). This combination of the biosignal data-based markers obtained during SBTs provides a promising tool to assist clinicians in determining the optimal extubation time.