Specific Training Improves the Detection and Management of Patient-Ventilator Asynchrony.

BACKGROUND: Patient-ventilator asynchrony is common in patients undergoing mechanical ventilation. The proportion of health-care professionals capable of identifying and effectively managing different types of patient-ventilator asynchronies is limited. A few studies have developed specific training programs, but they mainly focused on improving patient-ventilator asynchrony detection without assessing the ability of health-care professionals to determine the possible causes. METHODS: We conducted a 36-h training program focused on patient-ventilator asynchrony detection and management for health-care professionals from 20 hospitals in Latin America and Spain. The training program included 6 h of a live online lesson during which 120 patient-ventilator asynchrony cases were presented. After the 6-h training lesson, health-care professionals were required to complete a 1-h training session per day for the subsequent 30 d. A 30-question assessment tool was developed and used to assess health-care professionals before training, immediately after the 6-h training lecture, and after the 30 d of training (1-month follow-up). RESULTS: One hundred sixteen health-care professionals participated in the study. The median (interquartile range) of the total number of correct answers in the pre-training, post-training, and 1-month follow-up were significantly different (12 [8.75-15], 18 [13.75-22], and 18.5 [14-23], respectively). The percentages of correct answers also differed significantly between the time assessments. Study participants significantly improved their performance between pre-training and post-training (P < .001). This performance was maintained after a 1-month follow-up (P = .95) for the questions related to the detection, determination of cause, and management of patient-ventilator asynchrony. CONCLUSIONS: A specific 36-h training program significantly improved the ability of health-care professionals to detect patient-ventilator asynchrony, determine the possible causes of patient-ventilator asynchrony, and properly manage different types of patient-ventilator asynchrony.

Reverse triggering during mechanical ventilation: Diagnosis and clinical implications.

This review addresses the phenomenon of "reverse triggering", an asynchrony that occurs in deeply sedated patients or patients in transition from deep to light sedation. Reverse triggering has been reported to occur in 30-90% of all ventilated patients. The underlying pathophysiological mechanisms remain unclear, but "entrainment" is proposed as one of them. Detecting this asynchrony is crucial, and methods such as visual inspection, esophageal pressure, diaphragmatic ultrasound and automated methods have been used. Reverse triggering may have effects on lung and diaphragm function, probably mediated by the level of breathing effort and eccentric activation of the diaphragm. The optimal management of reverse triggering has not been established, but may include the adjustment of ventilatory parameters as well as of sedation level, and in extreme cases, neuromuscular block. It is important to understand the significance of this condition and its detection, but also to conduct dedicated research to improve its clinical management and potential effects in critically ill patients.

Diaphragm Ultrasound in Critically Ill Patients on Mechanical Ventilation-Evolving Concepts.

Mechanical ventilation (MV) is a life-saving respiratory support therapy, but MV can lead to diaphragm muscle injury (myotrauma) and induce diaphragmatic dysfunction (DD). DD is relevant because it is highly prevalent and associated with significant adverse outcomes, including prolonged ventilation, weaning failures, and mortality. The main mechanisms involved in the occurrence of myotrauma are associated with inadequate MV support in adapting to the patient's respiratory effort (over- and under-assistance) and as a result of patient-ventilator asynchrony (PVA). The recognition of these mechanisms associated with myotrauma forced the development of myotrauma prevention strategies (MV with diaphragm protection), mainly based on titration of appropriate levels of inspiratory effort (to avoid over- and under-assistance) and to avoid PVA. Protecting the diaphragm during MV therefore requires the use of tools to monitor diaphragmatic effort and detect PVA. Diaphragm ultrasound is a non-invasive technique that can be used to monitor diaphragm function, to assess PVA, and potentially help to define diaphragmatic effort with protective ventilation. This review aims to provide clinicians with an overview of the relevance of DD and the main mechanisms underlying myotrauma, as well as the most current strategies aimed at minimizing the occurrence of myotrauma with special emphasis on the role of ultrasound in monitoring diaphragm function.

EPISYNC study: predictors of patient-ventilator asynchrony in a prospective cohort of patients under invasive mechanical ventilation - study protocol.

INTRODUCTION: Patient-ventilator asynchrony is common during the entire period of invasive mechanical ventilation (MV) and is associated with worse clinical outcomes. However, risk factors associated with asynchrony are not completely understood. The main objectives of this study are to estimate the incidence of asynchrony during invasive MV and its association with respiratory mechanics and other baseline patient characteristics. METHODS AND ANALYSIS: We designed a prospective cohort study of patients admitted to the intensive care unit (ICU) of a university hospital. Inclusion criteria are adult patients under invasive MV initiated for less than 72 hours, and with expectation of remaining under MV for more than 24 hours. Exclusion criteria are high flow bronchopleural fistula, inability to measure respiratory mechanics and previous tracheostomy. Baseline assessment includes clinical characteristics of patients at ICU admission, including severity of illness, reason for initiation of MV, and measurement of static mechanics of the respiratory system. We will capture ventilator waveforms during the entire MV period that will be analysed with dedicated software (Better Care, Barcelona, Spain), which automatically identifies several types of asynchrony and calculates the asynchrony index (AI). We will use a linear regression model to identify risk factors associated with AI. To assess the relationship between survival and AI we will use Kaplan-Meier curves, log rank tests and Cox regression. The calculated sample size is 103 patients. The statistical analysis will be performed by the software R Programming (www.R-project.org) and will be considered statistically significant if the p value is less than 0.05. ETHICS AND DISSEMINATION: The study was approved by the Ethics Committee of Instituto do Coração, School of Medicine, University of São Paulo, Brazil, and informed consent was waived due to the observational nature of the study. We aim to disseminate the study findings through peer-reviewed publications and national and international conference presentations. TRIAL REGISTRATION NUMBER: NCT02687802; Pre-results.

Ability of ICU Health-Care Professionals to Identify Patient-Ventilator Asynchrony Using Waveform Analysis.

BACKGROUND: Waveform analysis by visual inspection can be a reliable, noninvasive, and useful tool for detecting patient-ventilator asynchrony. However, it is a skill that requires a properly trained professional. METHODS: This observational study was conducted in 17 urban ICUs. Health-care professionals (HCPs) working in these ICUs were asked to recognize different types of asynchrony shown in 3 evaluation videos. The health-care professionals were categorized according to years of experience, prior training in mechanical ventilation, profession, and number of asynchronies identified correctly. RESULTS: A total of 366 HCPs were evaluated. Statistically significant differences were found when HCPs with and without prior training in mechanical ventilation (trained vs non-trained HCPs) were compared according to the number of asynchronies detected correctly (of the HCPs who identified 3 asynchronies, 63 [81%] trained vs 15 [19%] non-trained, P < .001; 2 asynchronies, 72 [65%] trained vs 39 [35%] non-trained, P = .034; 1 asynchrony, 55 [47%] trained vs 61 [53%] non-trained, P = .02; 0 asynchronies, 17 [28%] trained vs 44 [72%] non-trained, P < .001). HCPs who had prior training in mechanical ventilation also increased, nearly 4-fold, their odds of identifying ≥2 asynchronies correctly (odds ratio 3.67, 95% CI 1.93-6.96, P < .001). However, neither years of experience nor profession were associated with the ability of HCPs to identify asynchrony. CONCLUSIONS: HCPs who have specific training in mechanical ventilation increase their ability to identify asynchrony using waveform analysis. Neither experience nor profession proved to be a relevant factor to identify asynchrony correctly using waveform analysis.

Interação paciente ventilador nas diferentes fases do ciclo ventilatório em ventilação por pressão de suporte / Patient-ventilator interaction on different phases of mechanical breath in pressure support ventilation

Introdução: O principal objetivo da ventilação mecânica é a diminuição do trabalho respiratório. Para que isto ocorra, o ciclo mecânico deveria coincidir com o tempo inspiratório neural do paciente. A assincronia paciente ventilador ocorre por fatores relacionados ao paciente e aos parâmetros ventilatórios e podem prolongar o tempo de suporte mecânico e permanência em unidades de terapia intensiva. Objetivos: Revisar a assincronia nas diferentes fases do ciclo respiratório, sua avaliação através dos gráficos e as intervenções capazes de melhorar a interação paciente ventilador em ventilação por pressão de suporte. Resultados/ Discussão: Através de busca em base de dados científicos, foram incluídos 26 artigos que abordavam o tema proposto. Os diferentes tipos de assincronia podem ser observados através de esforços ineficientes, atrasos no disparo, disparos automáticos, disparos duplos, presença de PEEP intrínseca, términos prematuro ou prolongado da inspiração e curvas diferentes do padrão usual. Conclusão: A correta identificação e ajustes conforme a demanda do paciente são pontos importantes na interação paciente ventilador e podem contribuir para a melhora do prognóstico destes pacientes.(AU)

Introduction: The main reason of mechanical ventilation is the decrease the work of breathing. To achieve it, the mechanical breath should coincide with the neural inspiratory time. Patient-ventilator asynchrony may be secondary for the facts related to the patient´s condition or ventilatory settings and may prolong support and UTI stay. Objectives: Review asynchrony in different phases of mechanical breath, the evaluation through ventilator waveforms and the proper settings to improve patient-ventilator interaction in pressure support ventilation. Results/ Discussion: Through research on scientific basis, 26 studies that match the theme were included. Asynchrony may be seen as inefficient efforts, trigger delay, auto-triggering, double triggering, presence of auto-PEEP, premature termination, delayed termination or unusual waveforms. Conclusion: Proper identification and adjustments that coincides with patient´s demand are critical points in patient ventilator interaction and may contribute to improve their prognosis.(AU)