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A 55-year-old man is hospitalized with severe community-acquired pneumonia, and the acute respiratory distress syndrome (ARDS) develops. The patient requires intubation and mechanical ventilation. An intensive care specialist recommends the use of a low-tidal-volume ventilation strategy, which may reduce the risk of ventilator-induced lung injury and is associated with better survival in patients with ARDS than conventional ventilation. A 55-year-old man is hospitalized with severe community-acquired pneumonia, and the acute respiratory distress syndrome develops. A low-tidal-volume ventilation strategy may reduce the risk of ventilator-induced lung injury and is associated with better survival than conventional ventilation. Foreword This Journal feature begins with a case vignette that includes a therapeutic recommendation. A discussion of the clinical problem and the mechanism of benefit of this form of therapy follows. Major clinical studies, the clinical use of this therapy, and potential adverse effects are reviewed. Relevant formal guidelines, if they exist, are presented. The article ends with the author's clinical recommendations. Stage A 55-year-old man who is 178 cm tall and weighs 95 kg is hospitalized with community-acquired pneumonia and progressively severe dyspnea. His arterial oxygen saturation while breathing 100% oxygen through a face mask is 76%; a chest radiograph shows diffuse alveolar infiltrates with air bronchograms. He is intubated and receives mechanical ventilation; ventilator settings include a tidal volume of 1000 ml, a positive end-expiratory pressure (PEEP) of 5 cm of water, and a fraction of inspired oxygen (FIO 2 ) of 0.8. With these settings, peak airway pressure is 50 to 60 cm of water, plateau airway pressure is . . .

Obstructive sleep apnea has well-established neurocognitive and cardiovascular sequelae. 1 Conservative estimates suggest that approximately 13% of men and 6% of women in North America have clinically important obstructive sleep apnea. 2 Despite the transformative benefits in some patients who receive therapy with continuous positive airway pressure (CPAP), 3 many patients remain inadequately treated owing to inconsistent levels of adherence to existing therapies. Thus, further research is required to allow new therapeutic options to evolve. Traditionally, obstructive sleep apnea has been defined by anatomical compromise in which soft tissues and craniofacial structures around the pharyngeal airway lead to increased airway collapsibility. 4 Because of . . .

Obstructive sleep apnoea is an increasingly common disorder of repeated upper airway collapse during sleep, leading to oxygen desaturation and disrupted sleep. Features include snoring, witnessed apnoeas, and sleepiness. Pathogenesis varies; predisposing factors include small upper airway lumen, unstable respiratory control, low arousal threshold, small lung volume, and dysfunctional upper airway dilator muscles. Risk factors include obesity, male sex, age, menopause, fluid retention, adenotonsillar hypertrophy, and smoking. Obstructive sleep apnoea causes sleepiness, road traffic accidents, and probably systemic hypertension. It has also been linked to myocardial infarction, congestive heart failure, stroke, and diabetes mellitus though not definitively. Continuous positive airway pressure is the treatment of choice, with adherence of 60–70%. Bi-level positive airway pressure or adaptive servo-ventilation can be used for patients who are intolerant to continuous positive airway pressure. Other treatments include dental devices, surgery, and weight loss.

Abstract Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.

The next three studies explored service utilisation, community interventions, and a social business model of early intervention and rehabilitation for people with disability in LMICs. [...]Al Imam et al. assessed the predictors of rehabilitation service utilisation in the LMIC setting [8]. Mushta, S.M.; King, C.; Goldsmith, S.; Smithers-Sheedy, H.; Badahdah, A.-M.; Rashid, H.; Badawi, N.; Khandaker, G.; McIntyre, S. Epidemiology of Cerebral Palsy among Children and Adolescents in Arabic-Speaking Countries: A Systematic Review and Meta-Analysis.

Sepsis is a leading cause of morbidity and mortality worldwide. Early identification of sepsis is important as it allows timely administration of potentially life-saving resuscitation and antimicrobial therapy. We present COMPOSER (COnformal Multidimensional Prediction Of SEpsis Risk), a deep learning model for the early prediction of sepsis, specifically designed to reduce false alarms by detecting unfamiliar patients/situations arising from erroneous data, missingness, distributional shift and data drifts. COMPOSER flags these unfamiliar cases as indeterminate rather than making spurious predictions. Six patient cohorts (515,720 patients) curated from two healthcare systems in the United States across intensive care units (ICU) and emergency departments (ED) were used to train and externally and temporally validate this model. In a sequential prediction setting, COMPOSER achieved a consistently high area under the curve (AUC) (ICU: 0.925–0.953; ED: 0.938–0.945). Out of over 6 million prediction windows roughly 20% and 8% were identified as indeterminate amongst non-septic and septic patients, respectively. COMPOSER provided early warning within a clinically actionable timeframe (ICU: 12.2 [3.2 22.8] and ED: 2.1 [0.8 4.5] hours prior to first antibiotics order) across all six cohorts, thus allowing for identification and prioritization of patients at high risk for sepsis.

The pathophysiologic causes of obstructive sleep apnea (OSA) likely vary among patients but have not been well characterized. To define carefully the proportion of key anatomic and nonanatomic contributions in a relatively large cohort of patients with OSA and control subjects to identify pathophysiologic targets for future novel therapies for OSA. Seventy-five men and women with and without OSA aged 20-65 years were studied on three separate nights. Initially, the apnea-hypopnea index was determined by polysomnography followed by determination of anatomic (passive critical closing pressure of the upper airway [Pcrit]) and nonanatomic (genioglossus muscle responsiveness, arousal threshold, and respiratory control stability; loop gain) contributions to OSA. Pathophysiologic traits varied substantially among participants. A total of 36% of patients with OSA had minimal genioglossus muscle responsiveness during sleep, 37% had a low arousal threshold, and 36% had high loop gain. A total of 28% had multiple nonanatomic features. Although overall the upper airway was more collapsible in patients with OSA (Pcrit, 0.3 [-1.5 to 1.9] vs. -6.2 [-12.4 to -3.6] cm H2O; P <0.01), 19% had a relatively noncollapsible upper airway similar to many of the control subjects (Pcrit, -2 to -5 cm H2O). In these patients, loop gain was almost twice as high as patients with a Pcrit greater than -2 cm H2O (-5.9 [-8.8 to -4.5] vs. -3.2 [-4.8 to -2.4] dimensionless; P = 0.01). A three-point scale for weighting the relative contribution of the traits is proposed. It suggests that nonanatomic features play an important role in 56% of patients with OSA. This study confirms that OSA is a heterogeneous disorder. Although Pcrit-anatomy is an important determinant, abnormalities in nonanatomic traits are also present in most patients with OSA.

This multicenter trial comparing nasal high-flow therapy with CPAP as primary support for preterm infants with respiratory distress showed a significantly higher treatment-failure rate with high-flow therapy. In 2014, there were more than 380,000 preterm births (i.e., births at a gestational age of <37 weeks) in the United States, accounting for approximately 10% of all births that year. 1 Preterm infants have a risk of the respiratory distress syndrome. The introduction of endotracheal ventilation has improved the survival rate among preterm infants but is associated with an increased risk of complications such as bronchopulmonary dysplasia. 2 Clinicians aim to use noninvasive respiratory support to minimize the risk of such complications. The most widely used noninvasive approach, nasal continuous positive airway pressure (CPAP), has been shown to be an effective . . .

In this randomized trial involving 438 hospitalized patients with severe Covid-19 pneumonia, the use of the monoclonal antibody tocilizumab did not result in significantly better clinical status or lower mortality than placebo at 28 days.

•The fixel-based analysis framework was proposed for fibre-specific statistical analysis of diffusion MRI data.•A “fixel” represents an individual fibre population in a voxel, allowing for increased specificity over voxel-wise measures.•A state-of-the-art fixel-based analysis pipeline consists of several bespoke steps, but is conceptually similar to a voxel-based analysis.•Fixel-based analysis has seen increased adoption recently, with 75 published studies to date.•The framework has unique benefits and future opportunities, but specific challenges and limitations exist as well. Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organization. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple “crossing” fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the “Fixel-Based Analysis” (FBA) framework, which implements bespoke solutions to this end. It has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to Fixel-Based Analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of all current FBA studies, categorized across a broad range of neuro-scientific domains, listing key design choices and summarizing their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the FBA framework, and outline some directions and future opportunities. [Display omitted]