Reliability of transpulmonary pressure-time curve profile to identify tidal recruitment/hyperinflation in experimental unilateral pleural effusion

Setting positive end-expiratory pressure: using the pressure-volume curve

PURPOSE OF REVIEW

To discuss the role of pressure-volume curve (PV curve) in exploring elastic properties of the respiratory system and setting mechanical ventilator to reduce ventilator-induced lung injury.

RECENT FINDINGS

Nowadays, quasi-static PV curves and loops can be easily obtained and analyzed at the bedside without disconnection of the patient from the ventilator. It is shown that this tool can provide useful information to optimize ventilator setting. For example, PV curves can assess for patient's individual potential for lung recruitability and also evaluate the risk for lung injury of the ongoing mechanical ventilation setting.

SUMMARY

In conclusion, PV curve is an easily available bedside tool: its correct interpretation can be extremely valuable to enlighten potential for lung recruitability and select a high or low positive end-expiratory pressure (PEEP) strategy. Furthermore, recent studies have shown that PV curve can play a significant role in PEEP and driving pressure fine tuning: clinical studies are needed to prove whether this technique will improve outcome.

Performance and applications of bedside visual inspection of airway pressure-time curve profiles for estimating stress index in patients with acute respiratory distress syndrome

To determine the performance of bedside visual inspection of airway pressure-time (Paw-t) curve profiles (VI) for estimating stress index (SI) in patients with acute respiratory distress syndrome (ARDS). A prospective study in 30 subjects with ARDS receiving mechanical ventilation at two peak inspiratory flow (PIF) settings: 60 or 40 L/min. For each study session, two physicians inspected real-time Paw-t waveforms from mechanical ventilator's monitoring screens at bedside for 30 s and interpreted which of the three patterns (tidal recruitment, noninjurious ventilation or tidal overdistension) the Paw-t curve profile was compatible with. Subsequently, the study was repeated again at the second PIF setting. SI was derived from a standardized dedicated software program and categorized into three groups: SI < 0.9, or tidal recruitment; SI = 0.9-1.05, or noninjurious ventilation; and SI > 1.05, or tidal overdistension. The lower PIF setting increased the sensitivity of VI to correctly estimate SI (75% vs. 50%; p = 0.005). At PIF 40 L/min, the likelihood ratio of a positive test was 3.6, 5.4 or 7 if the Paw-t curve profile was interpreted as noninjurious ventilation, tidal recruitment or tidal overdistension, respectively. The likelihood ratio of a negative test ranged from 0.55 for tidal recruitment to 0.32 and 0.19 for noninjurious ventilation and tidal overdistension, respectively. Experience in mechanical ventilation did not influence the accuracy. Bedside VI is moderately accurate for estimating SI and may be used to monitor injurious ventilation in patients with ARDS, in addition to plateau airway pressure.

Journal of Clinical Monitoring and Computing 2017 end of year summary: respiration

This paper reviews 32 papers or commentaries published in Journal of Clinical Monitoring and Computing in 2016, within the field of respiration. Papers were published covering airway management, ventilation and respiratory rate monitoring, lung mechanics and gas exchange monitoring, in vitro monitoring of lung mechanics, CO₂ monitoring, and respiratory and metabolic monitoring techniques.