Abstract Background Infants younger than 6 months of age are at high risk for complications of coronavirus disease 2019 (Covid-19) and are not eligible for vaccination. Transplacental transfer of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after maternal Covid-19 vaccination may confer protection against Covid-19 in infants. Methods We used a case–control test-negative design to assess the effectiveness of maternal vaccination during pregnancy against hospitalization for Covid-19 among infants younger than 6 months of age. Between July 1, 2021, and March 8, 2022, we enrolled infants hospitalized for Covid-19 (case infants) and infants hospitalized without Covid-19 (control infants) at 30 hospitals in 22 states. We estimated vaccine effectiveness by comparing the odds of full maternal vaccination (two doses of mRNA vaccine) among case infants and control infants during circulation of the B.1.617.2 (delta) variant (July 1, 2021, to December 18, 2021) and the B.1.1.259 (omicron) variant (December 19, 2021, to March 8, 2022). Results A total of 537 case infants (181 of whom had been admitted to a hospital during the delta period and 356 during the omicron period; median age, 2 months) and 512 control infants were enrolled and included in the analyses; 16% of the case infants and 29% of the control infants had been born to mothers who had been fully vaccinated against Covid-19 during pregnancy. Among the case infants, 113 (21%) received intensive care (64 [12%] received mechanical ventilation or vasoactive infusions). Two case infants died from Covid-19; neither infant’s mother had been vaccinated during pregnancy. The effectiveness of maternal vaccination against hospitalization for Covid-19 among infants was 52% (95% confidence interval [CI], 33 to 65) overall, 80% (95% CI, 60 to 90) during the delta period, and 38% (95% CI, 8 to 58) during the omicron period. Effectiveness was 69% (95% CI, 50 to 80) when maternal vaccination occurred after 20 weeks of pregnancy and 38% (95% CI, 3 to 60) during the first 20 weeks of pregnancy. Conclusions Maternal vaccination with two doses of mRNA vaccine was associated with a reduced risk of hospitalization for Covid-19, including for critical illness, among infants younger than 6 months of age. (Funded by the Centers for Disease Control and Prevention.)
A. Sisó-Almirall, P. Brito-Zerón, Laura Conangla Ferrín
et al.
Long COVID-19 may be defined as patients who, four weeks after the diagnosis of SARS-Cov-2 infection, continue to have signs and symptoms not explainable by other causes. The estimated frequency is around 10% and signs and symptoms may last for months. The main long-term manifestations observed in other coronaviruses (Severe Acute Respiratory Syndrome (SARS), Middle East respiratory syndrome (MERS)) are very similar to and have clear clinical parallels with SARS-CoV-2: mainly respiratory, musculoskeletal, and neuropsychiatric. The growing number of patients worldwide will have an impact on health systems. Therefore, the main objective of these clinical practice guidelines is to identify patients with signs and symptoms of long COVID-19 in primary care through a protocolized diagnostic process that studies possible etiologies and establishes an accurate differential diagnosis. The guidelines have been developed pragmatically by compiling the few studies published so far on long COVID-19, editorials and expert opinions, press releases, and the authors’ clinical experience. Patients with long COVID-19 should be managed using structured primary care visits based on the time from diagnosis of SARS-CoV-2 infection. Based on the current limited evidence, disease management of long COVID-19 signs and symptoms will require a holistic, longitudinal follow up in primary care, multidisciplinary rehabilitation services, and the empowerment of affected patient groups.
The inherently slow acquisition speed of MRI makes abdominal imaging highly sensitive to respiratory motion artifacts. Since the early days of MRI, the development of respiratory motion compensation has been an active research topic, and this field has achieved substantial technical progress. Despite these advances, majority of these techniques are not clinically available, and motion management methods used in clinical abdominal MRI today have changed little over the past decades. This observation is striking and points to a significant gap between technical innovation and clinical translation in this area. This review is motivated by this question: why have so many motion management techniques not been adopted into routine clinical workflows? Unlike conventional survey-style reviews that focus on summarizing emerging methods, this article takes a different, and perhaps opposite, perspective to investigate why those technologically sophisticated innovations are misaligned with practical clinical needs. Specifically, we discuss the barriers behind the gap between research advances and clinical practice, clarify the clinical requirements for effective respiratory motion management in abdominal MRI, and highlight research directions with stronger relevance to routine workflows. The review begins with an overview of the clinical impact of respiratory motion in abdominal MRI, followed by a discussion of standard abdominal MRI sequences and their motion sensitivity. We then summarize current clinical strategies and advanced approaches, along with the barriers that hinder their clinical adoption. The article concludes with future directions and broader lessons learned from this translational gap, with the goal of guiding future developments towards improved clinical integration.
Allergic bronchopulmonary aspergillosis (ABPA) is a complex hypersensitivity reaction to the fungus <i>Aspergillus fumigatus</i>, primarily affecting individuals with asthma or cystic fibrosis (CF). It is characterized by chronic inflammation, mucus plugging, and bronchiectasis. ABPA often presents with recurrent asthma exacerbations, fever, malaise, and productive cough. However, in rare instances, ABPA can manifest with atypical and severe clinical presentations, posing diagnostic challenges and requiring specialized management strategies. This case series explores three such rare presentations: ABPA with whole lung collapse, ABPA with type 2 respiratory failure, and ABPA mimicking malignancy. Recognizing these varied presentations and their underlying pathophysiological mechanisms is crucial for timely and accurate diagnosis. Early intervention with corticosteroids and antifungal therapy can significantly improve patient outcomes and prevent complications such as permanent lung damage.
How to cite this article: Anand R, Pandiyan AS, Jayavignesh J, <i>et al.</i> Allergic Bronchopulmonary Aspergillosis Unmasked: Case Series of Varied Pulmonary Presentations. Indian J Respir Care 2025;14(2):133–136.
Ina-Maria Rückert-Eheberg, Alexander Steger, Alexander Müller
et al.
<h4>Objective</h4>The aim of the study was to derive median age- and sex-specific respiratory rates in a population-based sample of adults and to identify disease and lifestyle factors associated with elevated respiratory rates.<h4>Methods</h4>In the population-based KORA FF4 study conducted in Augsburg, Germany, 5-minute 12-lead resting electrocardiograms (ECGpro-system, AMEDTEC) were recorded in 2,224 participants from 39 to 88 years. Respiratory rate was derived from these electrocardiograms. Sex- and age-specific medians, IQRs, and percentiles were calculated. Associations of sociodemographic, disease, and lifestyle variables with elevated resting respiratory rate were assessed by univariable and multivariable logistic regression analyses.<h4>Results</h4>Respiratory rate decreased slightly from youngest to middle-aged women and men and increased in old age. Overall, median (IQR) was 15.80 (3.16) breaths per minute (brpm). Five percent of the participants had values lower than 12.06 brpm, and five percent had values above 20.06 brpm (95th percentile). Elevated respiratory rates of ≥ 18.6 brpm were found in 13.8% (n = 308). In an adjusted logistic regression model, age, abdominal obesity, diabetes, COPD, smoking, and low education were significantly associated with elevated respiratory rate. Stratified analyses showed that education appeared to be more relevant in women, while the effect of diabetes was more pronounced in men.<h4>Conclusions</h4>High respiratory rate may be an indicator of impaired health in the general population, especially regarding pulmonary and metabolic characteristics, and unfavorable lifestyle and living conditions. Individuals with an increased respiratory rate should therefore be examined and followed up more closely to recognize diseases and adverse progressions at an early stage and to possibly prevent them.
Tharaka Fonseka, Buddhi Wijenayake, Athulya Ratnayake
et al.
Understanding the relationship between population dynamics and disease-specific mortality is central to evidence-based health policy. This study introduces two novel metrics, PoPDivergence and PoPStat, one to quantify the difference between population pyramids and the other to assess the strength and nature of their association with the mortality of a given disease. PoPDivergence, based on Kullback-Leibler divergence, measures deviations between a countrys population pyramid and a reference pyramid. PoPStat is the correlation between these deviations and the log form of disease-specific mortality rates. The reference population is selected by a brute-force optimization that maximizes this correlation. Utilizing mortality data from the Global Burden of Disease 2021 and population statistics from the United Nations, we applied these metrics to 371 diseases across 204 countries. Results reveal that PoPStat outperforms traditional indicators such as median age, GDP per capita, and Human Development Index in explaining the mortality of most diseases. Noncommunicable diseases (NCDs) like neurological disorders and cancers, communicable diseases (CDs) like neglected tropical diseases, and maternal and neonatal diseases were tightly bound to the underlying demographic attributes whereas NCDs like diabetes, CDs like respiratory infections and injuries including self-harm and interpersonal violence were weakly associated with population pyramid shapes. Notably, except for diabetes, the NCD mortality burden was shared by constrictive population pyramids, while mortality of communicable diseases, maternal and neonatal causes and injuries were largely borne by expansive pyramids. Therefore, PoPStat provides insights into demographic determinants of health and empirical support for models on epidemiological transition. Code and scripts: https://github.com/Buddhi19/DevisingPoPStat.git
Nhi Nguyen, Constantino Álvarez Casado, Le Nguyen
et al.
Video-based respiratory rate (RR) estimation is often unreliable due to inconsistent signal quality across extraction methods. We present a predictive, quality-aware framework that integrates heterogeneous signal sources with dynamic assessment of reliability. Ten signals are extracted from facial remote photoplethysmography (rPPG), upper-body motion, and deep learning pipelines, and analyzed using four spectral estimators: Welch's method, Multiple Signal Classification (MUSIC), Fast Fourier Transform (FFT), and peak detection. Segment-level quality indices are then used to train machine learning models that predict accuracy or select the most reliable signal. This enables adaptive signal fusion and quality-based segment filtering. Experiments on three public datasets (OMuSense-23, COHFACE, MAHNOB-HCI) show that the proposed framework achieves lower RR estimation errors than individual methods in most cases, with performance gains depending on dataset characteristics. These findings highlight the potential of quality-driven predictive modeling to deliver scalable and generalizable video-based respiratory monitoring solutions.
The complexity of mathematical models describing respiratory mechanics has grown in recent years, however, parameter identifiability of such models has only been studied in the last decade in the context of observable data. This study investigates parameter identifiability of a nonlinear respiratory mechanics model tuned to the physiology of an extremely preterm infant, using global Morris screening, local deterministic sensitivity analysis, and singular value decomposition-based subset selection. The model predicts airflow and dynamic pulmonary volumes and pressures under varying levels of continuous positive airway pressure, and a range of parameters characterizing both surfactant-treated and surfactant-deficient lung. Sensitivity analyses indicated eleven parameters influence model outputs over the range of continuous positive airway pressure and lung health scenarios. The model was adapted to data from a spontaneously breathing 1 kg infant using gradient-based optimization to estimate the parameter subset characterizing the patient's state of health.
Serverless computing has redefined cloud application deployment by abstracting infrastructure and enabling on-demand, event-driven execution, thereby enhancing developer agility and scalability. However, maintaining consistent application performance in serverless environments remains a significant challenge. The dynamic and transient nature of serverless functions makes it difficult to distinguish between benign and anomalous behavior, which in turn undermines the effectiveness of traditional anomaly detection methods. These conventional approaches, designed for stateful and long-running services, struggle in serverless settings where executions are short-lived, functions are isolated, and observability is limited. In this first comprehensive vision paper on anomaly detection for serverless systems, we systematically explore the unique challenges posed by this paradigm, including the absence of persistent state, inconsistent monitoring granularity, and the difficulty of correlating behaviors across distributed functions. We further examine a range of threats that manifest as anomalies, from classical Denial-of-Service (DoS) attacks to serverless-specific threats such as Denial-of-Wallet (DoW) and cold start amplification. Building on these observations, we articulate a research agenda for next-generation detection frameworks that address the need for context-aware, multi-source data fusion, real-time, lightweight, privacy-preserving, and edge-cloud adaptive capabilities. Through the identification of key research directions and design principles, we aim to lay the foundation for the next generation of anomaly detection in cloud-native, serverless ecosystems.
(1) Background/Objectives: Dexmedetomidine is a sedative for patients receiving invasive mechanical ventilation (IMV) that previous single-site studies have found to be associated with improved survival in patients with COVID-19. The reported clinical benefits include dampened inflammatory response, reduced respiratory depression, reduced agitation and delirium, improved preservation of responsiveness and arousability, and improved hypoxic pulmonary vasoconstriction and ventilation-perfusion ratio. Whether improved mortality is evident in large, multi-site COVID-19 data is understudied. (2) Methods: The association between dexmedetomidine use and mortality in patients with COVID-19 receiving IMV was assessed. This retrospective multi-center cohort study utilized patient data in the United States from health systems participating in the National COVID Cohort Collaborative (N3C) from 1 January 2020 to 3 November 2022. The primary outcome was 28-day mortality rate from the initiation of IMV. Propensity score matching adjusted for differences between the group with and without dexmedetomidine use. Adjusted hazard ratios (aHRs) for 28-day mortality were calculated using multivariable Cox proportional hazards models with dexmedetomidine use as a time-varying covariate. (3) Results: Among the 16,357,749 patients screened, 3806 patients across 17 health systems met the study criteria. Mortality was lower with dexmedetomidine use (aHR, 0.81; 95% CI, 0.73–0.90; p < 0.001). On subgroup analysis, mortality was lower with earlier dexmedetomidine use—initiated within the median of 3.5 days from the start of IMV—(aHR, 0.67; 95% CI, 0.60–0.76; p < 0.001) as well as use prior to standard, widespread use of dexamethasone for patients on respiratory support (prior to 30 July 2020) (aHR, 0.54; 95% CI, 0.42–0.69; p < 0.001). In a secondary model that was restricted to 576 patients across six health system sites with available PaO2/FiO2 data, mortality was not lower with dexmedetomidine use (aHR 0.95, 95% CI, 0.72–1.25; p = 0.73); however, on subgroup analysis, mortality was lower with dexmedetomidine use initiated earlier than the median dexmedetomidine start time after IMV (aHR, 0.72; 95% CI, 0.53–0.98; p = 0.04) and use prior to 30 July 2020 (aHR, 0.22; 95% CI, 0.06–0.78; p = 0.02). (4) Conclusions: Dexmedetomidine use was associated with reduced mortality in patients with COVID-19 receiving IMV, particularly when initiated earlier, rather than later, during the course of IMV as well as use prior to the standard, widespread usage of dexamethasone during respiratory support. These particular findings might suggest that the associated mortality benefit with dexmedetomidine use is tied to immunomodulation. However, further research including a large randomized controlled trial is warranted to evaluate the potential mortality benefit of DEX use in COVID-19 and evaluate the physiologic changes influenced by DEX that may enhance survival.
The question of enhancing treatment effectiveness in managing respiratory diseases based on physiotherapeutic methods remains highly relevant. We consider the possibility of using pulsed low-frequency electrostatic massage therapy in the rehabilitation treatment of patients with chronic obstructive heart disease, bronchial asthma, pneumonia, and cystic fibrosis. The biological action and therapeutic effects of low-frequency electrostatic therapy are presented. Effects of low-frequency electrostatic therapy on muscle tone, as well as its decongestion, trophic, and regenerative action, are demonstrated. The mechanisms of pathogenetic action in respiratory pathologies require further research and elucidation.
Sridesh Nath, Hafiz Qurashi, Georgios D. Kitsios
et al.
Abstract Introduction Acute respiratory distress syndrome (ARDS) is characterized by diffuse lung injury. The impact of pre-existing chronic obstructive pulmonary disease (COPD) or emphysema on ARDS pathogenesis is not well characterized. Methods Secondary analysis of ARDS patients enrolled in the Acute Lung Injury Registry and Biospecimen Repository at the University of Pittsburgh between June 2012 and September 2021. Patients were categorized into two mutually exclusive groups by the prevalence of COPD or emphysema at the time of ARDS diagnosis. The COPD/emphysema group comprised ARDS patients with radiological evidence of emphysema, chart diagnosis of COPD, or both. Demographics, lung mechanics, and clinical outcomes were obtained from the electronic medical record. Host-response biomarkers known to have validated associations with ARDS were previously measured in plasma and lower respiratory tract samples using a customized Luminex assay. Continuous and categorical variables were compared between groups with and without COPD/emphysema. Results 217 patients with ARDS were included in the study, 57 (27%) had COPD/emphysema. Patients with COPD/emphysema were older (median 62 [interquartile range 55–69] versus 53 [41–64] years, p < 0.01), more likely to be male (62% vs. 44%, p = 0.02) and had a higher prevalence of congestive heart failure (25% vs. 4%, p < 0.01) compared to patients without COPD/emphysema. Baseline demographics, laboratory parameters, and mechanical ventilatory characteristics were otherwise similar between the two groups. No difference in 90-day mortality was observed between groups; however, patients with COPD/emphysema had shorter duration of intensive care unit (ICU) stay (median 10 [7–18] versus 16 [9–28] days, p = 0.04) and shorter duration of mechanical ventilation (median 7 [4–16] vs. 12 [6–20] days, p = 0.01). Host response biomarkers in serum and lower respiratory tract samples did not significantly differ between groups. Conclusion ARDS patients with COPD or emphysema had similar respiratory mechanics, host response biomarker profiles, and mortality compared to those without COPD or emphysema but with a shorter median duration of mechanical ventilation and ICU length of stay. Future studies should address differences in clinical and biological responses by disease severity, and should investigate the impact of severity of COPD and emphysema on mechanical ventilation and targeted therapeutic strategies in ARDS. Clinical trial number Not applicable
Lujian Zhu,1,* Jing Zhou,1,* Chen Yu,2 Lei Gu,3 Qin Wang,1 Hanglu Xu,1 Yin Zhu,4 Maodong Guo,5 Minli Hu,5 Wei Peng,6 Hao Fang,7 Haizhen Wang8 1Department of Infectious Diseases, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China; 3Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China; 4Department of Infectious Diseases, Taizhou Enze Medical Center (Group), Enze Hospital, Taizhou, People’s Republic of China; 5Department of Gastroenterology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China; 6Department of Intensive Care Unit, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China; 7Department of Trauma Surgery, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China; 8Department of Health Management Center, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China*These authors contributed equally to this workCorrespondence: Haizhen Wang, Department of Health Management Center, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, People’s Republic of China, Email whz002012@sina.comAbstract: Ferroptosis, a type of programmed cell death that relies on iron, is distinct in terms of its morphological, biochemical and genetic features. Unlike other forms of cell death, such as autophagy, apoptosis, necrosis, and pyroptosis, ferroptosis is primarily caused by lipid peroxidation. Cells that die due to iron can potentially trigger an immune response which intensifies inflammation and causes severe inflammatory reactions that eventually lead to multiple organ failure. In recent years, ferroptosis has been identified in an increasing number of medical fields, including neurological pathologies, chronic liver diseases and sepsis. Ferroptosis has the potential to cause an inflammatory tempest, with many of the catalysts and pathological indications of respiratory ailments being linked to inflammatory reactions. The growing investigation into ferroptosis in respiratory disorders has also garnered significant interest to better understand the mechanism of ferroptosis in these diseases. In this review, the recent progress in understanding the molecular control of ferroptosis and its mechanism in different respiratory disorders is examined. In addition, this review discusses current challenges and prospects for understanding the link between respiratory diseases and ferroptosis.Keywords: respiratory system, ferroptosis, iron metabolism, oxidative stress, treatment
Muhammad Yahya Ayyashy Mujahidan, Martin Clinton Tosima Manullang
Respiratory rate is a vital sign indicating various health conditions. Traditional contact-based measurement methods are often uncomfortable, and alternatives like respiratory belts and smartwatches have limitations in cost and operability. Therefore, a non-contact method based on Pixel Intensity Changes (PIC) with RGB camera images is proposed. Experiments involved 3 sizes of bounding boxes, 3 filter options (Laplacian, Sobel, and no filter), and 2 corner detection algorithms (ShiTomasi and Harris), with tracking using the Lukas-Kanade algorithm. Eighteen configurations were tested on 67 subjects in static and dynamic conditions. The best results in static conditions were achieved with the Medium Bounding box, Sobel Filter, and Harris Method (MAE: 0.85, RMSE: 1.49). In dynamic conditions, the Large Bounding box with no filter and ShiTomasi, and Medium Bounding box with no filter and Harris, produced the lowest MAE (0.81) and RMSE (1.35)
Deep learning techniques have shown promising results in the automatic classification of respiratory sounds. However, accurately distinguishing these sounds in real-world noisy conditions remains challenging for clinical deployment. In addition, predicting signals with only background noise may reduce user trust in the system. This study explores the feasibility and effectiveness of incorporating a deep learning-based audio enhancement step into automatic respiratory sound classification systems to improve robustness and clinical applicability. We conducted extensive experiments using various audio enhancement model architectures, including time-domain and time-frequency-domain approaches, combined with multiple classification models to evaluate the module's effectiveness. The classification performance was compared against the noise injection data augmentation method. These experiments were carried out on two datasets: the ICBHI respiratory sound dataset and the FABS dataset. Furthermore, a physician validation study assessed the system's clinical utility. Integrating the audio enhancement module resulted in a 21.9% increase in the ICBHI classification score and a 4.1% improvement on the FABS dataset in multi-class noisy scenarios. Quantitative analysis revealed efficiency gains, higher diagnostic confidence, and increased trust, with workflows using enhanced audio improving diagnostic sensitivity by 11.6% and enabling high-confidence diagnoses. Incorporating an audio enhancement algorithm boosts the robustness and clinical utility of automatic respiratory sound classification systems, enhancing performance in noisy environments and fostering greater trust among medical professionals.
Since December 2019, a respiratory pandemic named as coronavirus disease 2019 (Covid-19) caused by a new coronavirus named as SARS-CoV-2, has taken the world by storm. The symptoms are fever, malaise, and cough which resolve in a few days in most cases; but may progress to respiratory distress and organ failure. Transmission is through droplet infection or fomites, but other modes such as airborne transmission and oro-fecal transmission are also speculated. Research is underway to develop effective vaccines and medicines for the disease. In such a scenario, we present the measures described in Unani system of medicine for health protection during epidemics. Unani is a traditional system of medicine developed during the middle ages, which employs natural drugs of herbal, animal and mineral origin for treatment. In Unani medicine, during an epidemic, apart from isolation and quarantine, three measures are of utmost importance, (i) purification of surroundings using certain herbal drugs as fumigants or sprays, (ii) health promotion and immune-modulation, and (iii) use of health-protecting drugs and symptom-specific drugs. Drugs such as loban (Styrax benzoides W. G. Craib), sandroos (Hymenaea verrucosa Gaertn.) za'fran (Crocus sativus L.), vinegar etc. are prescribed in various forms. Scientific researches on these drugs reveal the presence of a number of pharmacologically active substances, which may provide a new insight into the management of infections and epidemics.
Background: Ventilation with lower positive end–expiratory pressure (PEEP) may cause loss of lung aeration in critically ill invasively ventilated patients. This study investigated whether a systematic lung ultrasound (LUS) scoring system can detect such changes in lung aeration in a study comparing lower versus higher PEEP in invasively ventilated patients without acute respiratory distress syndrome (ARDS). Methods: Single center substudy of a national, multicenter, randomized clinical trial comparing lower versus higher PEEP ventilation strategy. Fifty–seven patients underwent a systematic 12–region LUS examination within 12 h and between 24 to 48 h after start of invasive ventilation, according to randomization. The primary endpoint was a change in the global LUS aeration score, where a higher value indicates a greater impairment in lung aeration. Results: Thirty–three and twenty–four patients received ventilation with lower PEEP (median PEEP 1 (0–5) cm H2O) or higher PEEP (median PEEP 8 (8–8) cm H2O), respectively. Median global LUS aeration scores within 12 h and between 24 and 48 h were 8 (4 to 14) and 9 (4 to 12) (difference 1 (–2 to 3)) in the lower PEEP group, and 7 (2–11) and 6 (1–12) (difference 0 (–2 to 3)) in the higher PEEP group. Neither differences in changes over time nor differences in absolute scores reached statistical significance. Conclusions: In this substudy of a randomized clinical trial comparing lower PEEP versus higher PEEP in patients without ARDS, LUS was unable to detect changes in lung aeration.