Patient-ventilator interaction with conventional and automated management of pressure support during difficult weaning from mechanical ventilation

Grieco, Domenico Luca; Bitondo, Maria Maddalena; Aguirre-Bermeo, Hernán; Italiano, Stefano; Idone, Francesco; Moccaldo, A; Santantonio, Maria Teresa; Eleuteri, Davide; Antonelli, Massimo; Mancebo, Jordi; Maggiore, Salvatore Maurizio

doi:10.1016/j.jcrc.2018.08.043

Cited by 12 publications

(17 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Δ P L , albeit primarily influenced by tidal volume, also includes a resistive component due to airflow; we assumed that resistive pressure did not change significantly between the four study steps, thus allowing to take Δ P L as a surrogate for transpulmonary driving pressure. Patient–ventilator synchrony: the following asynchronies were diagnosed by in-phase reading of esophageal and airway tracings [ 35 , 38 , 39 ], according to existing definitions and diagnostic criteria [ 39 – 41 ]: Ineffective efforts: negative flexion of esophageal pressure (i.e., active inspiratory effort) without a corresponding delivery of a mechanical breath by the ventilator. Autotriggering: delivery of a mechanical breath by the ventilator without a corresponding negative flexion of esophageal pressure.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Gas conditioning during helmet noninvasive ventilation: effect on comfort, gas exchange, inspiratory effort, transpulmonary pressure and patient–ventilator interaction

Bongiovanni

Grieco

Anzellotti

et al. 2021

Ann. Intensive Care

Self Cite

View full text Add to dashboard Cite

Background There is growing interest towards the use of helmet noninvasive ventilation (NIV) for the management of acute hypoxemic respiratory failure. Gas conditioning through heat and moisture exchangers (HME) or heated humidifiers (HHs) is needed during facemask NIV to provide a minimum level of humidity in the inspired gas (15 mg H2O/L). The optimal gas conditioning strategy during helmet NIV remains to be established. Methods Twenty patients with acute hypoxemic respiratory failure (PaO2/FiO2 < 300 mmHg) underwent consecutive 1-h periods of helmet NIV (PEEP 12 cmH2O, pressure support 12 cmH2O) with four humidification settings, applied in a random order: double-tube circuit with HHs and temperature set at 34 °C (HH34) and 37 °C (HH37); Y-piece circuit with HME; double-tube circuit with no humidification (NoH). Temperature and humidity of inhaled gas were measured through a capacitive hygrometer. Arterial blood gases, discomfort and dyspnea through visual analog scales (VAS), esophageal pressure swings (ΔPES) and simplified pressure–time product (PTPES), dynamic transpulmonary driving pressure (ΔPL) and asynchrony index were measured in each step. Results Median [IqR] absolute humidity, temperature and VAS discomfort were significantly lower during NoH vs. HME, HH34 and HH37: absolute humidity (mgH2O/L) 16 [12–19] vs. 28 [23–31] vs. 28 [24–31] vs. 33 [29–38], p < 0.001; temperature (°C) 29 [28–30] vs. 30 [29–31] vs. 31 [29–32] vs 32. [31–33], p < 0.001; VAS discomfort 4 [2–6] vs. 6 [2–7] vs. 7 [4–8] vs. 8 [4–10], p = 0.03. VAS discomfort increased with higher absolute humidity (p < 0.01) and temperature (p = 0.007). Higher VAS discomfort was associated with increased VAS dyspnea (p = 0.001). Arterial blood gases, respiratory rate, ΔPES, PTPES and ΔPL were similar in all conditions. Overall asynchrony index was similar in all steps, but autotriggering rate was lower during NoH and HME (p = 0.03). Conclusions During 1-h sessions of helmet NIV in patients with hypoxemic respiratory failure, a double-tube circuit with no humidification allowed adequate conditioning of inspired gas, optimized comfort and improved patient–ventilator interaction. Use of HHs or HME in this setting resulted in increased discomfort due to excessive heat and humidity in the interface, which was associated with more intense dyspnea. Trail Registration Registered on clinicaltrials.gov (NCT02875379) on August 23rd, 2016.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Patient–ventilator synchrony: the following asynchronies were diagnosed by in-phase reading of esophageal and airway tracings [ 35 , 38 , 39 ], according to existing definitions and diagnostic criteria [ 39 – 41 ]:…”

Section: Methodsmentioning

confidence: 99%

Gas conditioning during helmet noninvasive ventilation: effect on comfort, gas exchange, inspiratory effort, transpulmonary pressure and patient–ventilator interaction

Bongiovanni

Grieco

Anzellotti

et al. 2021

Ann. Intensive Care

Self Cite

View full text Add to dashboard Cite

show abstract

“…Paired comparisons between study steps were performed with the Wilcoxon rank sum test: mean differences (95% CI] are displayed for most significant results. Intraindividual variability was rated with the coefficient of variability (ratio of the SD to the mean 28 ). Correlations between continuous variables were assessed with Pearson's correlation test: r and, for significant results, the slope (95% CI] of the linear regression are displayed.…”

Section: Sample Size Calculation and Statistical Analysismentioning

confidence: 99%

Recruitment-to-inflation Ratio Assessed through Sequential End-expiratory Lung Volume Measurement in Acute Respiratory Distress Syndrome

Grieco,

Pintaudi,

Bongiovanni

et al. 2023

Anesthesiology

Self Cite

View full text Add to dashboard Cite

Background. Positive end-expiratory pressure (PEEP) benefits in acute respiratory distress syndrome (ARDS) are driven by lung dynamic strain reduction: this depends on the variable extent of alveolar recruitment. The recruitment-to-inflation (R/I) ratio estimates recruitability across a 10-cmH2O PEEP range through a simplified maneuver. Whether recruitability is uniform or not across this range is unknown. The hypotheses of this study are that R/I represents an accurate estimate of PEEP-induced changes in dynamic strain, but may show a non-uniform behaviour across the conventionally tested PEEP range (15-5 cmH2O). Methods. Twenty patients with moderate-to-severe COVID-19 ARDS underwent a decremental PEEP trial (PEEP 15-13-10-8-5 cmH2O). Respiratory mechanics and end-expiratory lung volume by nitrogen dilution were measured the end of each step. Gas exchange, recruited volume, R/I, changes in dynamic, static and total strain were computed between 15 and 5 cmH2O (global R/I) and within narrower PEEP ranges (granular R/I). Results. Between 15 and 5 cmH2O, median [Interquartile range] global R/I was 1.27 [0.40-1.69] and displayed a linear correlation with PEEP-induced dynamic strain reduction (r=-0.94, p<0.001). Intra-individual R/I variability within the narrower ranges was high (85% [70-109]). The relationship between granular R/I and PEEP was mathematically described by a non-linear, quadratic equation (r 2=0.96). Granular R/I across the narrower PEEP ranges had itself a linear correlation with PEEP-induced reduction in dynamic strain (r=-0.89, p<0.001). Conclusions. Both global and granular R/I well estimate PEEP-induced changes in lung dynamic strain. However, the effect of 10-cmH2O of PEEP on lung strain may be non-uniform. Granular R/I assessment within narrower PEEP ranges guided by end-expiratory lung volume measurement may aid more precise PEEP selection, especially when R/I obtained with the simplified maneuver between PEEP 15 and 5 cmH2O yields intermediate values, that are difficult to interpret for a proper choice between a high vs. low PEEP strategy.

show abstract

“…This is in part due to the increased complexity of new ventilation modes. Current emerging solutions focus on shortening the weaning process and increasing lung protective ventilation techniques [32], mainly supported by AI software solutions with advanced in vivo monitoring [33,34]. In some cases, this can lead to the ventilation device becoming a "black-box" for an attending physician.…”

Section: Occurrence Of Pvamentioning

confidence: 99%

Patient–Ventilator Interaction Testing Using the Electromechanical Lung Simulator xPULM™ during V/A-C and PSV Ventilation Mode

et al. 2021

View full text Add to dashboard Cite

During mechanical ventilation, a disparity between flow, pressure and volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. This paper introduces an alternative approach of simulating and evaluating patient–ventilator interactions with high fidelity using the electromechanical lung simulator xPULM™. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-control (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient–ventilator interactions. In V/A-C mode, a double-triggering was detected every third breathing cycle, leading to an asynchrony index of 16.67%, which is classified as severe. This asynchrony causes a significant increase of peak inspiratory pressure (7.96 ± 6.38 vs. 11.09 ± 0.49 cmH2O, p < 0.01)) and peak expiratory flow (−25.57 ± 8.93 vs. 32.90 ± 0.54 L/min, p < 0.01) when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases increased significantly (917.09 ± 45.74 vs. 468.40 ± 31.79 mL, p < 0.01) compared to apnea phases. Various dynamic clinical situations can be approximated using this approach and thereby could help to identify undesired patient–ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.

show abstract

Patient-ventilator interaction with conventional and automated management of pressure support during difficult weaning from mechanical ventilation

Cited by 12 publications

References 42 publications

Gas conditioning during helmet noninvasive ventilation: effect on comfort, gas exchange, inspiratory effort, transpulmonary pressure and patient–ventilator interaction

Gas conditioning during helmet noninvasive ventilation: effect on comfort, gas exchange, inspiratory effort, transpulmonary pressure and patient–ventilator interaction

Recruitment-to-inflation Ratio Assessed through Sequential End-expiratory Lung Volume Measurement in Acute Respiratory Distress Syndrome

Patient–Ventilator Interaction Testing Using the Electromechanical Lung Simulator xPULM™ during V/A-C and PSV Ventilation Mode

Contact Info

Product

Resources

About