Characterization of postintensive care syndrome in a prospective cohort of survivors of COVID-19 critical illness: a 12-month follow-up study.

Purpose: Studies integrating an exhaustive longitudinal long-term follow-up of postintensive care syndrome (PICS) in critically ill COVID-19 survivors are scarce. We aimed to 1) describe PICS-related sequelae over a 12-month period after intensive care unit (ICU) discharge, 2) identify relevant demographic and clinical factors related to PICS, and 3) explore how PICS-related sequelae may influence health-related quality of life (HRQoL) in critically ill COVID-19 survivors.

Methods: We conducted a prospective cohort study in adult critically ill survivors of SARS-CoV-2 infection that did or did not need invasive mechanical ventilation (IMV) during the COVID-19 pandemic in Spain (March 2020 to January 2021).

Occurrence, co-occurrence and persistence of symptoms of depression and post-traumatic stress disorder in survivors of COVID-19 critical illness.

Intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) are associated with psychological distress and trauma. The COVID-19 pandemic brought with it a series of additional long-lasting stressful and traumatic experiences. However, little is known about comorbid depression and post-traumatic stress disorder (PTSD).

Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques.

Background: Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by visual inspection of airway pressure waveform. Clinical diagnosis is cumbersome and prone to underdiagnosis, being an opportunity for artificial intelligence. Our objective is to develop a supervised artificial intelligence algorithm for identifying airway pressure deformation during square-flow assisted ventilation and patient-triggered breaths.

Objective and subjective cognition in survivors of COVID-19 one year after ICU discharge: the role of demographic, clinical, and emotional factors.

Background: Intensive Care Unit (ICU) COVID-19 survivors may present long-term cognitive and emotional difficulties after hospital discharge. This study aims to characterize the neuropsychological dysfunction of COVID-19 survivors 12 months after ICU discharge, and to study whether the use of a measure of perceived cognitive deficit allows the detection of objective cognitive impairment. We also explore the relationship between demographic, clinical and emotional factors, and both objective and subjective cognitive deficits.

The Effect of Clusters of Double Triggering and Ineffective Efforts in Critically Ill Patients.

Objectives: To characterize clusters of double triggering and ineffective inspiratory efforts throughout mechanical ventilation and investigate their associations with mortality and duration of ICU stay and mechanical ventilation.

Design: Registry-based, real-world study.

Background: Asynchronies during invasive mechanical ventilation can occur as isolated events or in clusters and might be related to clinical outcomes.

Virtual Reality-Based Early Neurocognitive Stimulation in Critically Ill Patients: A Pilot Randomized Clinical Trial.

This study focuses on the application of a non-immersive virtual reality (VR)-based neurocognitive intervention in critically ill patients. Our aim was to assess the feasibility of direct outcome measures to detect the impact of this digital therapy on patients' cognitive and emotional outcomes. Seventy-two mechanically ventilated adult patients were randomly assigned to the "treatment as usual" (TAU, = 38) or the "early neurocognitive stimulation" (ENRIC, = 34) groups.

Cardiopulmonary coupling indices to assess weaning readiness from mechanical ventilation.

The ideal moment to withdraw respiratory supply of patients under Mechanical Ventilation at Intensive Care Units (ICU), is not easy to be determined for clinicians. Although the Spontaneous Breathing Trial (SBT) provides a measure of the patients' readiness, there is still around 15-20% of predictive failure rate. This work is a proof of concept focused on adding new value to the prediction of the weaning outcome.

Longitudinal Changes in Patient-Ventilator Asynchronies and Respiratory System Mechanics Before and After Tracheostomy.

Background: This was a pilot study to analyze the effects of tracheostomy on patient-ventilator asynchronies and respiratory system mechanics. Data were extracted from an ongoing prospective, real-world database that stores continuous output from ventilators and bedside monitors. Twenty adult subjects were on mechanical ventilation and were tracheostomized during an ICU stay: 55% were admitted to the ICU for respiratory failure and 35% for neurologic conditions; the median duration of mechanical ventilation before tracheostomy was 12 d; and the median duration of mechanical ventilation was 16 d.

Publisher Correction: Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cognitive phenotypes 1 month after ICU discharge in mechanically ventilated patients: a prospective observational cohort study.

Background: ICU patients undergoing invasive mechanical ventilation experience cognitive decline associated with their critical illness and its management. The early detection of different cognitive phenotypes might reveal the involvement of diverse pathophysiological mechanisms and help to clarify the role of the precipitating and predisposing factors. Our main objective is to identify cognitive phenotypes in critically ill survivors 1 month after ICU discharge using an unsupervised machine learning method, and to contrast them with the classical approach of cognitive impairment assessment.

Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation.

Patient-ventilator asynchronies can be detected by close monitoring of ventilator screens by clinicians or through automated algorithms. However, detecting complex patient-ventilator interactions (CP-VI), consisting of changes in the respiratory rate and/or clusters of asynchronies, is a challenge. Sample Entropy (SE) of airway flow (SE-Flow) and airway pressure (SE-Paw) waveforms obtained from 27 critically ill patients was used to develop and validate an automated algorithm for detecting CP-VI.

Evaluation of Respiratory Muscle Activity by Means of Concentric Ring Electrodes.

Surface electromyography (sEMG) can be used for the evaluation of respiratory muscle activity. Recording sEMG involves the use of surface electrodes in a bipolar configuration. However, electrocardiographic (ECG) interference and electrode orientation represent considerable drawbacks to bipolar acquisition.

Monitoring Asynchrony During Invasive Mechanical Ventilation.

Mechanical ventilation in critically ill patients must effectively unload inspiratory muscles and provide safe ventilation (ie, enhancing gas exchange, protect the lungs and the diaphragm). To do that, the ventilator should be in synchrony with patient's respiratory rhythm. The complexity of such interplay leads to several concerning issues that clinicians should be able to recognize.

Neural Offset Time Evaluation in Surface Respiratory Signals during Controlled Respiration.

The electrical activity of the diaphragm measured by surface electromyography (sEMGdi) provides indirect information on neural respiratory drive. Moreover, it allows evaluating the ventilatory pattern from the onset and offset (ntoff) estimation of the neural inspiratory time. sEMGdi amplitude variation was quantified using the fixed sample entropy (fSampEn), a less sensitive method to the interference from cardiac activity.

Engineered Macroscale Cardiac Constructs Elicit Human Myocardial Tissue-like Functionality.

In vitro surrogate models of human cardiac tissue hold great promise in disease modeling, cardiotoxicity testing, and future applications in regenerative medicine. However, the generation of engineered human cardiac constructs with tissue-like functionality is currently thwarted by difficulties in achieving efficient maturation at the cellular and/or tissular level. Here, we report on the design and implementation of a platform for the production of engineered cardiac macrotissues from human pluripotent stem cells (PSCs), which we term "CardioSlice.

Electromyography-Based Respiratory Onset Detection in COPD Patients on Non-Invasive Mechanical Ventilation.

To optimize long-term nocturnal non-invasive ventilation in patients with chronic obstructive pulmonary disease, surface diaphragm electromyography (EMGdi) might be helpful to detect patient-ventilator asynchrony. However, visual analysis is labor-intensive and EMGdi is heavily corrupted by electrocardiographic (ECG) activity. Therefore, we developed an automatic method to detect inspiratory onset from EMGdi envelope using fixed sample entropy (fSE) and a dynamic threshold based on kernel density estimation (KDE).

Evaluation of a Wearable Device to Determine Cardiorespiratory Parameters From Surface Diaphragm Electromyography.

The use of wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capacity of a Shimmer3 wearable device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdi).

Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects.

The current gold standard assessment of human inspiratory muscle function involves using invasive measures of transdiaphragmatic pressure (P) or crural diaphragm electromyography (oesEMG). Mechanomyography is a non-invasive measure of muscle vibration associated with muscle contraction. Surface electromyogram and mechanomyogram, recorded transcutaneously using sensors placed over the lower intercostal spaces (sEMG and sMMG respectively), have been proposed to provide non-invasive indices of inspiratory muscle activation, but have not been directly compared to gold standard P and oesEMG measures during voluntary respiratory manoeuvres.

Assessment of Respiratory Muscle Activity with Surface Electromyographic Signals Acquired by Concentric Ring Electrodes.

The assessment of respiratory muscle activity by surface electromyography (sEMG) is a promising noninvasive technique for the diagnosis and monitoring of chronic obstructive pulmonary disease. The diaphragm is the most important muscle in breathing, although in forced inspiration other muscles, such as sternocleidomastoid, are activated and contribute to the respiratory process. The measurement of the sEMG in these muscles (sEMGdi and sEMGscm, respectively) by means of two electrodes in conventional bipolar configuration (BEs) is a common practice to evaluate the respiratory muscle activity and allows to indirectly quantify the level of muscular activation.

Assessment of Inspiratory Muscle Activation using Surface Diaphragm Mechanomyography and Crural Diaphragm Electromyography.

The relationship between surface diaphragm mechanomyography (sMMGdi), as a noninvasive measure of inspiratory muscle mechanical activation, and crural diaphragm electromyography (oesEMGdi), as the invasive gold standard measure of diaphragm electrical activation, had not previously been examined. To investigate this relationship, oesEMGdi and sMMGdi were measured simultaneously in 6 healthy subjects during an incremental inspiratory threshold loading protocol, and analyzed using fixed sample entropy (fSampEn). A positive curvilinear relationship was observed between mean fSampEn sMMGdi and oesEMGdi (r = 0.

Evaluation of indirect measures of neural inspiratory time from invasive and noninvasive recordings of respiratory activity.

Measuring diaphragmatic electromyography (EMGdi) provides an indirect quantification of neural respiratory drive and allows the delimitation of diaphragm neural activation and deactivation during inspiration. EMGdi recordings have been incorporated in novel modes of assisted mechanical ventilation, such as neurally adjusted ventilatory assist (NAVA), to trigger and cycle-off the ventilator. The EMGdi signal improves the assistance delivered by more conventional ventilatory modes, in which the ventilator is synchronized with the patient employing a pneumatic triggering.

Inspiratory muscle activation increases with COPD severity as confirmed by non-invasive mechanomyographic analysis.

There is a lack of instruments for assessing respiratory muscle activation during the breathing cycle in clinical conditions. The aim of the present study was to evaluate the usefulness of the respiratory muscle mechanomyogram (MMG) for non-invasively assessing the mechanical activation of the inspiratory muscles of the lower chest wall in both patients with chronic obstructive pulmonary disease (COPD) and healthy subjects, and to investigate the relationship between inspiratory muscle activation and pulmonary function parameters. Both inspiratory mouth pressure and respiratory muscle MMG were simultaneously recorded under two different respiratory conditions, quiet breathing and incremental ventilatory effort, in 13 COPD patients and 7 healthy subjects.

Evaluating respiratory muscle activity using a wireless sensor platform.

Wireless sensors are an emerging technology that allows to assist physicians in the monitoring of patients health status. This approach can be used for the non-invasive recording of the electrical respiratory muscle activity of the diaphragm (EMGdi). In this work, we acquired the EMGdi signal of a healthy subject performing an inspiratory load test.