Reverse triggering is a highly common ventilatory asynchrony in sedated critically ill patients. When accompanied by high respiratory effort, it may cause diaphragmatic and lung injury. However, assessing its incidence and the associated effort remains limited, as it relies on expert review of waveform segments representing <5% of the full recording. Automated methods to assess and better characterize this patient-ventilator interaction are needed. We conducted an observational study in subjects with acute hypoxemic respiratory failure. Using ventilator and esophageal tracings, we developed an automated tool in Python (PyCharm Community Edition 2025.1.3) to identify the prevalence of reverse triggering and characterize reverse triggering in terms of the magnitude of respiratory effort and temporal trends over ∼12-h recordings. The tool was validated against expert visual assessment. A total of 10 subjects were included (median age 56.5 years [interquartile range 45.0-69.0], 70% female). A total of 91 h of ventilatory recordings, corresponding to 97,687 respiratory cycles, were included. Reverse triggering was identified in 30.9% of all breaths, with marked inter-individual variability ranging from 4.6% to 77.4% across patients. Automated detection showed high diagnostic performance, with an overall accuracy of 89.1%, sensitivity of 85.9%, specificity of 92.4%, positive predictive value of 88.6%, and negative predictive value of 90.5%. The median reverse triggering associated respiratory effort (ΔPes) was -5.20 cm H2O. An automated tool using flow and airway pressure accurately detected reverse triggering during prolonged recordings. Reverse triggering was frequent and typically associated with low respiratory effort, with marked variability across patients.

Trans-spinal direct current stimulation (tsDCS) has been shown to impact diaphragm evoked potentials in young volunteers; however, it remains unclear if this translates into increased strength and ventilatory muscle function. This study aimed to evaluate whether an acute session of tsDCS can improve inspiratory muscle strength and ventilatory endurance in healthy young and older women. The study included healthy women aged 18-25 y and 60-80 y, who received either active or sham tsDCS applied over the C3-C5 cervical region. Inspiratory muscle strength was assessed by the S-index, whereas ventilatory endurance was evaluated using maximal voluntary ventilation (MVV). Data were compared using ANOVA two-way (between-within interaction), followed by post hoc pairwise tests, with Bonferroni correction for multiple comparisons, and statistical significancewas set at P < .05. Older women who received active tsDCS showed significant improvements in S-index (P = .01), with moderate effect sizes (Cohen's D = 0.74). No significant changes were observed in young women, possibly because of a physiological ceiling effect. MVV did not differ between groups. tsDCS improved inspiratory muscle strength in older women only, suggesting its effectiveness may be greater in populations with age-related decline. Future studies should explore tsDCS in other populations, clinical conditions, and over repeated sessions.

Pendelluft, the internal redistribution of gas within the lung, was first described as a phenomenon related to high breathing frequenciesand regional differences in time constants. The availability of electrical impedance tomography has transformed our understanding of this form of intrapulmonary discordance, revealing that effort-related pendelluft occurs commonly in mechanically ventilated patients and may contribute to patient self-inflicted lung injury. Emerging evidence suggests associations between pendelluft and adverse clinical outcomes, though meaningful gaps in our understanding remain. This review examines the pathophysiology of effort-related pendelluft, methods for its detection using EIT, factors influencing its occurrence, and associations with clinical outcomes.

Patient-ventilator interaction (PVI) has been extensively addressed in the literature, but there is no agreement on terms and definitions used. The result is that articles and books present concepts and terms that are inconsistent, confusing, and many times based on obsolete legacy ideas. To solve this problem, we propose a set of basic rules and standard nomenclature from which to establish a formal taxonomy and basis for its measurement. We also highlight some areas for research on PVI definitions, measurement, and clinical needs. Taxonomies have 2 components: a set of definitions relevant to the topic (called a standardized vocabulary) and a hierarchical organizational structure. This article offers a description of both components for the special purpose of understanding PVI.

Sleep in the ICU is subjectively and objectively poor. Patients in the ICU have short sleep duration and highly fragmented sleep. Poor sleep in the ICU is associated with worse outcomes, particularly the development of ICU delirium. Patients undergoing noninvasive or invasive mechanical ventilation struggle with sleep. For those patients on noninvasive ventilation, settings may need to be adjusted compared to wake to account for the physiological changes that occur with the sleep state. Specifically, upper airway collapsibility (ie, obstructive sleep apnea) must be considered as do changes in respiratory muscle function and ventilatory control. During invasive mechanical ventilation, ventilator dyssynchrony can contribute to sleep fragmentation and reduced sleep quantity and quality. Excessive ventilator support can lead to periodic breathing, whereas insufficient support can lead to fragmented sleep from excessive work of breathing. Although much work remains to be done, attention to ventilator mode and settings might improve sleep and outcomes in those with critical illness and respiratory failure.

Digital technology has made important inroads to advance the self-management and treatment of cystic fibrosis (CF) symptoms. To date, no integrative, comprehensive, systematic review of digital technology and CF has included the application of digital technology formental health. The purpose of the current study was to complete an up-to-date systematic review of digital technology interventions for CF across symptom monitoring, treatment adherence, airway clearance, nutrition, exercise, and mental health. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Articles reporting a quantitative study examining technology-based interventions for CF were included. Studies were excluded if they did not meet this criterion or if they were not written in English. PsycINFO, MEDLINE, EMBASE, and CINAHL databases were searched. Search terms included technology, CF, symptom monitoring, treatment adherence, quality of life, nutrition, exercise, and mental health. Thirty-four studies were included in the review. Results demonstrated variable types of digital technologies, most predominantly applied to exercise. Inconsistencies were observed in terms of the effectiveness or efficacy of digital technology to address study outcomes across many application areas. Most consistent findings were found for the efficacy of digital technology applications for symptom monitoring (ie, improving early detection or prediction of pulmonary exacerbation), treatment adherence (ie, improvements in medication adherence, and nebulizer use), and mental health (ie, reductions in depression and anxiety). Digital technology applications offer the potential for improved CF care; however, many of the existing studies show limited evidence for their effectiveness. Well-designed, methodologically robust studies are required to fully understand the utility of digital technology in CF care.