Protocol and Statistical Analysis Plan for the Mode of Ventilation During Critical Illness (MODE) Trial.

BACKGROUND: For every critically ill adult receiving invasive mechanical ventilation, clinicians must select a mode of ventilation. The mode of ventilation determines whether the ventilator directly controls the tidal volume or the inspiratory pressure. Newer hybrid modes allow clinicians to set a target tidal volume; the ventilator controls and adjusts the inspiratory pressure. A strategy of low tidal volumes and low plateau pressure improves outcomes, but the optimal mode to achieve these targets is not known. RESEARCH QUESTION: Can a cluster-randomized trial design be used to assess whether the mode of mandatory ventilation affects the number of days alive and free of invasive mechanical ventilation among critically ill adults? STUDY DESIGN AND METHODS: The Mode of Ventilation During Critical Illness (MODE) trial is a cluster-randomized, multiple-crossover pilot trial being conducted in the medical ICU at an academic center. The MODE trial compares the use of volume control, pressure control, and adaptive pressure control. The study ICU is assigned to a single-ventilator mode (volume control vs pressure control vs adaptive pressure control) for continuous mandatory ventilation during each 1-month study block. The assigned mode switches every month in a randomly generated sequence. The primary outcome is ventilator-free days to study day 28, defined as the number of days alive and free of invasive mechanical ventilation from the final receipt of mechanical ventilation to 28 days after enrollment. Enrollment began November 1, 2022, and will end on July 31, 2023. RESULTS: This manuscript describes the protocol and statistical analysis plan for the MODE trial of ventilator modes comparing volume control, pressure control, and adaptive pressure control. INTERPRETATION: Prespecifying the full statistical analysis plan prior to completion of enrollment increases rigor, reproducibility, and transparency of the trial results. CLINICAL TRIAL REGISTRATION: The trial was registered with clinicaltrials.gov on October 3, 2022, before initiation of patient enrollment on November 1, 2022 (ClinicalTrials.gov identifier: NCT05563779).

Protocol and statistical analysis plan for the Mode of Ventilation During Critical IllnEss (MODE) trial.

Introduction: For every critically ill adult receiving invasive mechanical ventilation, clinicians must select a mode of ventilation. The mode of ventilation determines whether the ventilator directly controls the tidal volume or the inspiratory pressure. Newer hybrid modes allow clinicians to set a target tidal volume, for which the ventilator controls and adjusts the inspiratory pressure. A strategy of low tidal volumes and low plateau pressure improves outcomes, but the optimal mode to achieve these targets is not known. Methods and analysis: The Mode of Ventilation During Critical Illness (MODE) trial is a cluster-randomized, multiple-crossover pilot trial being conducted in the medical intensive care unit (ICU) at an academic center. The MODE trial compares the use of volume control, pressure control, and adaptive pressure control. The study ICU is assigned to a single ventilator mode (volume control versus pressure control versus adaptive pressure control) for continuous mandatory ventilation during each 1-month study block. The assigned mode switches every month in a randomly generated sequence. The primary outcome is ventilator-free days (VFDs) to study day 28, defined as the number of days alive and free of invasive mechanical ventilation from the final receipt of mechanical ventilation to 28 days after enrollment. Enrollment began November 1, 2022 and will end on July 31, 2023. Ethics and dissemination: The trial was approved by the Vanderbilt University Medical Center institutional review board (IRB# 220446). Results of this study will be submitted to a peer-reviewed journal and presented at scientific conferences. Trial registration number: The trial was registered with clinicaltrials.gov on October 3, 2022, prior to initiation of patient enrollment on November 1, 2022 (ClinicalTrials.gov identifier: NCT05563779).

Warnings in early narrative assessment that might predict performance in residency: signal from an internal medicine residency program.

INTRODUCTION: Narrative assessment data are valuable in understanding struggles in resident performance. However, it remains unknown which themes in narrative data that occur early in training may indicate a higher likelihood of struggles later in training, allowing programs to intervene sooner. METHODS: Using learning analytics, we identified 26 internal medicine residents in three cohorts that were below expected entrustment during training. We compiled all narrative data in the first 6 months of training for these residents as well as 13 typically performing residents for comparison. Narrative data were blinded for all 39 residents during initial phases of an inductive thematic analysis for initial coding. RESULTS: Many similarities were identified between the two cohorts. Codes that differed between typical and lower entrusted residents were grouped into two types of themes: three explicit/manifest and three implicit/latent with six total themes. The explicit/manifest themes focused on specific aspects of resident performance with assessors describing 1) Gaps in attention to detail, 2) Communication deficits with patients, and 3) Difficulty recognizing the "big picture" in patient care. Three implicit/latent themes, focused on how narrative data were written, were also identified: 1) Feedback described as a deficiency rather than an opportunity to improve, 2) Normative comparisons to identify a resident as being behind their peers, and 3) Warning of possible risk to patient care. DISCUSSION: Clinical competency committees (CCCs) usually rely on accumulated data and trends. Using the themes in this paper while reviewing narrative comments may help CCCs with earlier recognition and better allocation of resources to support residents' development.