Optimisation des interactions patient-ventilateur en ventilation assistée : intérêt des nouveaux algorithmes de ventilation

During assisted mechanical ventilation, patient-ventilator interactions, which are associated with outcome, partly depend on ventilation algorithms.Objectives: : 1) during invasive mechanical ventilation, two modes offered real innovations and we wanted to assess whether the assistance could be customized depending on the patient's respiratory effort during proportional ventilatory modes: proportional assist ventilation with load-adjustable gain factors (PAV+) and neurally adjusted ventilator assist (NAVA); 2) during noninvasive ventilation (NIV): to assess whether NIV algorithms implemented on ICU and dedicated NIV ventilators decrease the incidence of patient-ventilator asynchrony.Methods: 1) In PAV+ we described a way to calculate the muscle pressure value from the values of both the gain adjusted by the clinician and the airway pressure. We then assessed the clinical feasibility of adjusting the gain with the goal of maintaining the muscle pressure within a normal range. 2) We compared titration of assistance between neurally adjusted ventilator assist (NAVA) and pressure support ventilation (PSV) based on respiratory effort indices. During NIV, we assessed the incidence of patient-ventilator asynchrony with and without the use of NIV algorithms: 1) using a bench model; 2) and in the clinical settings.Results: During PAV+, adjusting the gain with the goal of targeting a normal range of respiratory effort was feasible, simple, and most often sufficient to ventilate patients from the onset of partial ventilatory support until extubation. During NAVA, the analysis of respiratory effort indices allowed us to precise the boundaries within which the NAVA level should be adjusted and to compare patient-ventilator interactions with PSV within similar ranges of assistance. During NIV, our data stressed the heterogeneity of NIV algorithms implemented on ICU ventilators. We therefore reported that dedicated NIV ventilators allowed better patient-ventilator synchronization than ICU ventilators, even with their NIV algorithms engaged.Conclusions: During invasive mechanical ventilation, customizing the assistance during proportional ventilatory modes with the goal of targeting a normal range of respiratory effort optimizes patient-ventilator interactions and is feasible with PAV+. During NIV, dedicated NIV ventilators allow better patient-ventilator synchrony than ICU ventilators, even with their NIV algorithm engaged. ICU ventilators' NIV algorithms efficiency is however highly variable among ventilators.En ventilation assistée, les interactions patient-ventilateur, qui sont associés au pronostic, dépendent pour partie des algorithmes de ventilation. Objectifs : Caractériser l'intérêt potentiel des nouveaux algorithmes de ventilation dans l'optimisation des interactions patient-ventilateur : 1) en ventilation invasive, deux modes et leurs algorithmes nous ont semblé novateurs et nous avons cherché à personnaliser l'assistance du ventilateur en fonction de l'effort respiratoire du patient au cours de ces modes proportionnels : ventilation assistée proportionnelle (PAV+) et ventilation assistée neurale (NAVA) ; 2) en ventilation non-invasive (VNI) nous avons évalué si les algorithmes VNI des ventilateurs de réanimation et des ventilateurs dédiés à la VNI diminuaient l'incidence des asynchronies patient-ventilateur. Méthodes : 1) En PAV+ nous avons décrit un moyen de recalculer le pic de pression musculaire réalisée par le patient à chaque inspiration à partir du gain réglé et de la pression des voies aériennes monitorée par le respirateur. Nous avons alors évalué la faisabilité clinique d'ajuster l'assistance en ciblant un intervalle jugé normal de pression musculaire. 2) Nous avons comparé une titration de l'assistance en NAVA et en aide inspiratoire (AI) en se basant sur les indices d'effort respiratoire. 3 et 4) En VNI, nous avons évalué l'incidence des asynchronies patient-ventilateur avec et sans l'utilisation d'algorithmes VNI : sur banc d'essai au cours de conditions expérimentales reproduisant la présence de fuites autour de l'interface ; en clinique chez des patients de réanimation. Résultats : En PAV+, ajuster le gain dans le but de cibler un effort respiratoire normal était faisable, simple et souvent suffisant pour ventiler les patients depuis le sevrage de la ventilation mécanique jusqu'à l'extubation. En NAVA, l'analyse des indices d'effort respiratoire a permis de préciser les bornes d'utilisation et de comparer les interactions patient-ventilateur avec l'AI dans des intervalles d'assistance semblables. En VNI, nos données pointaient l'hétérogénéité des algorithmes VNI sur les ventilateurs de réanimation et retrouvaient une meilleure synchronisation patient-ventilateur avec l'utilisation de ventilateurs dédiés à la VNI pour des qualités de pressurisation par ailleurs identiques. Conclusions : En ventilation invasive, personnaliser l'assistance des modes proportionnels optimise les interactions patient-ventilateur et il est possible de cibler une zone d'effort respiratoire normale en PAV+. En VNI, les ventilateurs dédiés améliorent la synchronisation patient-ventilateur plus encore que les algorithmes VNI sur les ventilateurs de réanimation, dont l'efficacité varie grandement selon le ventilateur considéré

Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study

Objective: To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Design: Prospective multicenter randomized cross-over study. Setting: Intensive care units in three university hospitals. Methods: Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Results: Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p=0.004), late cycling in 11 (17%) and 5 (8%) (p=0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p<0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p=0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. Conclusion: In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cyclin

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe

Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome associated with COVID-19: An Emulated Target Trial Analysis.

RATIONALE: Whether COVID patients may benefit from extracorporeal membrane oxygenation (ECMO) compared with conventional invasive mechanical ventilation (IMV) remains unknown. OBJECTIVES: To estimate the effect of ECMO on 90-Day mortality vs IMV only Methods: Among 4,244 critically ill adult patients with COVID-19 included in a multicenter cohort study, we emulated a target trial comparing the treatment strategies of initiating ECMO vs. no ECMO within 7 days of IMV in patients with severe acute respiratory distress syndrome (PaO2/FiO2 <80 or PaCO2 ≥60 mmHg). We controlled for confounding using a multivariable Cox model based on predefined variables. MAIN RESULTS: 1,235 patients met the full eligibility criteria for the emulated trial, among whom 164 patients initiated ECMO. The ECMO strategy had a higher survival probability at Day-7 from the onset of eligibility criteria (87% vs 83%, risk difference: 4%, 95% CI 0;9%) which decreased during follow-up (survival at Day-90: 63% vs 65%, risk difference: -2%, 95% CI -10;5%). However, ECMO was associated with higher survival when performed in high-volume ECMO centers or in regions where a specific ECMO network organization was set up to handle high demand, and when initiated within the first 4 days of MV and in profoundly hypoxemic patients. CONCLUSIONS: In an emulated trial based on a nationwide COVID-19 cohort, we found differential survival over time of an ECMO compared with a no-ECMO strategy. However, ECMO was consistently associated with better outcomes when performed in high-volume centers and in regions with ECMO capacities specifically organized to handle high demand. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Patient-ventilator interactions optimization : new ventilation algorithms contribution

En ventilation assistée, les interactions patient-ventilateur, qui sont associés au pronostic, dépendent pour partie des algorithmes de ventilation. Objectifs : Caractériser l'intérêt potentiel des nouveaux algorithmes de ventilation dans l'optimisation des interactions patient-ventilateur : 1) en ventilation invasive, deux modes et leurs algorithmes nous ont semblé novateurs et nous avons cherché à personnaliser l'assistance du ventilateur en fonction de l'effort respiratoire du patient au cours de ces modes proportionnels : ventilation assistée proportionnelle (PAV+) et ventilation assistée neurale (NAVA) ; 2) en ventilation non-invasive (VNI) nous avons évalué si les algorithmes VNI des ventilateurs de réanimation et des ventilateurs dédiés à la VNI diminuaient l'incidence des asynchronies patient-ventilateur. Méthodes : 1) En PAV+ nous avons décrit un moyen de recalculer le pic de pression musculaire réalisée par le patient à chaque inspiration à partir du gain réglé et de la pression des voies aériennes monitorée par le respirateur. Nous avons alors évalué la faisabilité clinique d'ajuster l'assistance en ciblant un intervalle jugé normal de pression musculaire. 2) Nous avons comparé une titration de l'assistance en NAVA et en aide inspiratoire (AI) en se basant sur les indices d'effort respiratoire. 3 et 4) En VNI, nous avons évalué l'incidence des asynchronies patient-ventilateur avec et sans l'utilisation d'algorithmes VNI : sur banc d'essai au cours de conditions expérimentales reproduisant la présence de fuites autour de l'interface ; en clinique chez des patients de réanimation. Résultats : En PAV+, ajuster le gain dans le but de cibler un effort respiratoire normal était faisable, simple et souvent suffisant pour ventiler les patients depuis le sevrage de la ventilation mécanique jusqu'à l'extubation. En NAVA, l'analyse des indices d'effort respiratoire a permis de préciser les bornes d'utilisation et de comparer les interactions patient-ventilateur avec l'AI dans des intervalles d'assistance semblables. En VNI, nos données pointaient l'hétérogénéité des algorithmes VNI sur les ventilateurs de réanimation et retrouvaient une meilleure synchronisation patient-ventilateur avec l'utilisation de ventilateurs dédiés à la VNI pour des qualités de pressurisation par ailleurs identiques. Conclusions : En ventilation invasive, personnaliser l'assistance des modes proportionnels optimise les interactions patient-ventilateur et il est possible de cibler une zone d'effort respiratoire normale en PAV+. En VNI, les ventilateurs dédiés améliorent la synchronisation patient-ventilateur plus encore que les algorithmes VNI sur les ventilateurs de réanimation, dont l'efficacité varie grandement selon le ventilateur considéré.During assisted mechanical ventilation, patient-ventilator interactions, which are associated with outcome, partly depend on ventilation algorithms.Objectives: : 1) during invasive mechanical ventilation, two modes offered real innovations and we wanted to assess whether the assistance could be customized depending on the patient's respiratory effort during proportional ventilatory modes: proportional assist ventilation with load-adjustable gain factors (PAV+) and neurally adjusted ventilator assist (NAVA); 2) during noninvasive ventilation (NIV): to assess whether NIV algorithms implemented on ICU and dedicated NIV ventilators decrease the incidence of patient-ventilator asynchrony.Methods: 1) In PAV+ we described a way to calculate the muscle pressure value from the values of both the gain adjusted by the clinician and the airway pressure. We then assessed the clinical feasibility of adjusting the gain with the goal of maintaining the muscle pressure within a normal range. 2) We compared titration of assistance between neurally adjusted ventilator assist (NAVA) and pressure support ventilation (PSV) based on respiratory effort indices. During NIV, we assessed the incidence of patient-ventilator asynchrony with and without the use of NIV algorithms: 1) using a bench model; 2) and in the clinical settings.Results: During PAV+, adjusting the gain with the goal of targeting a normal range of respiratory effort was feasible, simple, and most often sufficient to ventilate patients from the onset of partial ventilatory support until extubation. During NAVA, the analysis of respiratory effort indices allowed us to precise the boundaries within which the NAVA level should be adjusted and to compare patient-ventilator interactions with PSV within similar ranges of assistance. During NIV, our data stressed the heterogeneity of NIV algorithms implemented on ICU ventilators. We therefore reported that dedicated NIV ventilators allowed better patient-ventilator synchronization than ICU ventilators, even with their NIV algorithms engaged.Conclusions: During invasive mechanical ventilation, customizing the assistance during proportional ventilatory modes with the goal of targeting a normal range of respiratory effort optimizes patient-ventilator interactions and is feasible with PAV+. During NIV, dedicated NIV ventilators allow better patient-ventilator synchrony than ICU ventilators, even with their NIV algorithm engaged. ICU ventilators' NIV algorithms efficiency is however highly variable among ventilators

Patient-Self Inflicted Lung Injury: A Practical Review

Patients with severe lung injury usually have a high respiratory drive, resulting in intense inspiratory effort that may even worsen lung damage by several mechanisms gathered under the name “patient-self inflicted lung injury” (P-SILI). Even though no clinical study has yet demonstrated that a ventilatory strategy to limit the risk of P-SILI can improve the outcome, the concept of P-SILI relies on sound physiological reasoning, an accumulation of clinical observations and some consistent experimental data. In this review, we detail the main pathophysiological mechanisms by which the patient’s respiratory effort could become deleterious: excessive transpulmonary pressure resulting in over-distension; inhomogeneous distribution of transpulmonary pressure variations across the lung leading to cyclic opening/closing of nondependent regions and pendelluft phenomenon; increase in the transvascular pressure favoring the aggravation of pulmonary edema. We also describe potentially harmful patient-ventilator interactions. Finally, we discuss in a practical way how to detect in the clinical setting situations at risk for P-SILI and to what extent this recognition can help personalize the treatment strategy