The PROMIZING trial enrollment algorithm for early identification of patients ready for unassisted breathing

Background: Liberating patients from mechanical ventilation (MV) requires a systematic approach. In the context of a clinical trial, we developed a simple algorithm to identify patients who tolerate assisted ventilation but still require ongoing MV to be randomized. We report on the use of this algorithm to screen potential trial participants for enrollment and subsequent randomization in the Proportional Assist Ventilation for Minimizing the Duration of MV (PROMIZING) study. Methods: The algorithm included five steps: enrollment criteria, pressure support ventilation (PSV) tolerance trial, weaning criteria, continuous positive airway pressure (CPAP) tolerance trial (0 cmHO during 2 min) and spontaneous breathing trial (SBT): on fraction of inspired oxygen (FO) 40% for 30-120 min. Patients who failed the weaning criteria, CPAP Zero trial, or SBT were randomized. We describe the characteristics of patients who were initially enrolled, but passed all steps in the algorithm and consequently were not randomized. Results: Among the 374 enrolled patients, 93 (25%) patients passed all five steps. At time of enrollment, most patients were on PSV (87%) with a mean (± standard deviation) FO of 34 (± 6) %, PSV of 8.7 (± 2.9) cmHO, and positive end-expiratory pressure of 6.1 (± 1.6) cmHO. Minute ventilation was 9.0 (± 3.1) L/min with a respiratory rate of 17.4 (± 4.4) breaths/min. Patients were liberated from MV with a median [interquartile range] delay between initial screening and extubation of 5 [1-49] hours. Only 7 (8%) patients required reintubation. Conclusion: The trial algorithm permitted identification of 93 (25%) patients who were ready to extubate, while their clinicians predicted a duration of ventilation higher than 24 h

Neurological assessment with validated tools in general ICU : multicenter, randomized, before and after, pragmatic study to evaluate the effectiveness of an e-learning platform for continuous medical education

BACKGROUND: International guidelines recommend systematic assessment of pain, agitation/sedation and delirium with validated scales for all ICU patients. However, these evaluations are often not done. We have created an e-learning training platform for the continuous medical education, and assessed its efficacy in increasing the use of validated tools by all medical and nursing staff of the participating ICUs during their daily practice. METHODS: Multicenter, randomized, before and after study. The eight participating centers were randomized in two groups, and received training at different times. The use of validated tools (Verbal Numeric Rating or Behavioral Pain Scale for pain; Richmond Agitation-Sedation Scale for agitation; Confusion Assessment Method for the ICU for delirium) was evaluated from clinical data recorded in medical charts during a week, with follow-up up to six months after the training. All the operators were invited to complete a questionnaire, at baseline and after the training. RESULTS : Among the 374 nurses and physicians involved, 140 (37.4%) completed at least one of the three courses. The assessment of pain (38.1 vs. 92.9%, P<0.01) and delirium (0 vs. 78.6%, P<0.01) using validated tools significantly increased after training. Observation in the follow-up showed further improvement in delirium monitoring, with no signs of extinction for pain and sedation/agitation measurements. CONCLUSIONS: This e-learning program shows encouraging effectiveness, and the increase in the use of validated tools for neurological monitoring in critically ill patients lasts over time.BACKGROUND: International guidelines recommend systematic assessment of pain, agitation/sedation and delirium with validated scales for all ICU patients. However, these evaluations are often not done. We have created an e-learning training platform for the continuous medical education, and assessed its efficacy in increasing the use of validated tools by all medical and nursing staff of the participating ICUs during their daily practice. METHODS: Multicenter, randomized, before and after study. The eight participating centers were randomized in two groups, and received training at different times. The use of validated tools (Verbal Numeric Rating or Behavioral Pain Scale for pain; Richmond Agitation-Sedation Scale for agitation; Confusion Assessment Method for the ICU for delirium) was evaluated from clinical data recorded in medical charts during a week, with follow-up up to six months after the training. All the operators were invited to complete a questionnaire, at baseline and after the training. RESULTS : Among the 374 nurses and physicians involved, 140 (37.4%) completed at least one of the three courses. The assessment of pain (38.1 vs. 92.9%, P<0.01) and delirium (0 vs. 78.6%, P<0.01) using validated tools significantly increased after training. Observation in the follow-up showed further improvement in delirium monitoring, with no signs of extinction for pain and sedation/agitation measurements. CONCLUSIONS: This e-learning program shows encouraging effectiveness, and the increase in the use of validated tools for neurological monitoring in critically ill patients lasts over time

Plateau airway pressure understimates end-inspiratory alveolar pressure during mechanical ventilation

Introduction: Plateau airway pressure is thought to reflect end-inspiratory alveolar pressure. If this is true, Peak Expiratory Flow (PEF) following an inspiratory pause (when plateau airway pressure is the driving force) will be equal to PEF during on-going mechanical ventilation (when end-inspiratory alveolar pressure is the driving force). Methods: Five healthy anesthetized piglets were ventilated with 24 different combinations of Tidal Volume (300, 400, 500, 600, 700 and 800 ml) and Inspiratory Flow (300, 600, 900 and 1200 ml/sec). Following 5 minutes of ventilation with each combination, PEF was measured after a 5-sec inspiratory pause (PEFstat) and during on-going mechanical ventilation (PEFdyn, Fig. 1). Results: PEF recorded after an end-inspiratory pause was significantly lower than PEF recorded during on-going ventilation (49\ub112 L/sec vs. 55\ub115 L/sec, p<0.001; paired t-test). This discrepancy increased with Tidal Volume and Inspiratory Flow (p<0.005 for both; 2-way repeated measures analysis of variance). Conclusions: PEF driven by plateau airway pressure (PEFstat) is significantly lower than PEF driven by end-inspiratory alveolar pressure (PEFdyn). Based on this finding, one can conclude that plateau airway pressure is significantly lower than end-inspiratory alveolar pressure (especially if Tidal Volume)

Role of Strain Rate in the Pathogenesis of Ventilator-Induced Lung Edema

Objective: Lungs behave as viscoelastic polymers. Harms of mechanical ventilation could then depend on not only amplitude (strain) but also velocity (strain rate) of lung deformation. Herein, we tested this hypothesis. Design: Laboratory investigation. Setting: Animal unit. Subjects: Thirty healthy piglets. Interventions: Two groups of animals were ventilated for 54 hours with matched lung strains (ratio between tidal volume and functional residual capacity) but different lung strain rates (ratio between strain and inspiratory time). Individual strains ranged between 0.6 and 3.5 in both groups. Piglets ventilated with low strain rates had an inspiratory-to-expiratory time ratio of 1:2-1:3. Those ventilated with high strain rates had much lower inspiratory-to-expiratory time ratios (down to 1:9). Respiratory rate was always 15 breaths/min. Lung viscoelastic behavior, with ventilator setting required per protocol, was "quantified" as dynamic respiratory system hysteresis (pressure-volume loop [in Joules]) and stress relaxation (airway pressure drop during an end-inspiratory pause [in cm H2O]). Primary outcome was the occurrence of pulmonary edema within 54 hours. Measurements and Main Results: On average, the two study groups were ventilated with well-matched strains (2.1 ± 0.9 vs 2.1 ± 0.9; p = 0.864) but different strain rates (1.8 ± 0.8 vs 4.6 ± 1.5 s-1; p < 0.001), dynamic respiratory system hysteresis (0.6 ± 0.3 vs 1.4 ± 0.8 J; p = 0.001), and stress relaxation (3.1 ± 0.9 vs 5.0 ± 2.3 cm H2O; p = 0.008). The prevalence of pulmonary edema was 20% among piglets ventilated with low strain rates and 73% among those ventilated with high strain rates (p = 0.010). Conclusions: High strain rate is a risk factor for ventilator-induced pulmonary edema, possibly because it amplifies lung viscoelastic behavior