Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Application of artificial intelligence in the diagnosis of sleep apnea

STUDY OBJECTIVES:Machine learning (ML) models have been employed in the setting of sleep disorders. This review aims to summarize the existing data about the role of ML techniques in the diagnosis, classification, and treatment of sleep related breathing disorders. METHODS:A systematic search in MedLine, EMBASE, and Cochrane databases through January 2022 was performed. RESULTS:Our search strategy revealed 132 studies that were included in the systematic review. Existing data show that ML models have been successfully used for diagnostic purposes. Specifically, ML models showed good performance in diagnosing sleep apnea using easily obtained features from the electrocardiogram, pulse oximetry and sound signals. Similarly, ML showed good performance for the classification of sleep apnea into obstructive and central categories, as well as predicting apnea severity. Existing data show promising results for the ML-based guided treatment of sleep apnea. Specifically, the prediction of outcomes following surgical treatment and optimization of continuous positive airway pressure therapy, can be guided by ML models. CONCLUSIONS:The adoption and implementation of ML in the field of sleep related breathing disorders is promising. Advancements in wearable sensor technology and ML models can help clinicians predict, diagnose and classify sleep apnea more accurately and efficiently

High-Dose Inhaled Nitric Oxide as Adjunct Therapy in Cystic Fibrosis Targeting Burkholderia multivorans

Background. Individuals with cystic fibrosis (CF) have persistent lung infections, necessitating the frequent use of antibiotics for pulmonary exacerbations. Some respiratory pathogens have intrinsic resistance to the currently available antibiotics, and any pathogen may acquire resistance over time, posing a challenge to CF care. Gaseous nitric oxide has been shown to have antimicrobial activity against a wide variety of microorganisms, including common CF pathogens, and offers a potential inhaled antimicrobial therapy. Case Presentation. Here, we present the case of a 16-year-old female with CF who experienced a precipitous decline in lung function over the prior year in conjunction with worsening antibiotic resistance of her primary pathogen, Burkholderia multivorans. She received 46 intermittent inhalations of 160 parts-per-million nitric oxide over a 28-day period. The gas was administered via a mechanical ventilator fitted with nitrogen dioxide scavenging chambers. Conclusions. High-dose inhaled nitric oxide was safe, well tolerated, and showed clinical benefit in an adolescent with cystic fibrosis and pulmonary colonization with Burkholderia multivorans

Application of artificial intelligence in the diagnosis of sleep apnea

STUDY OBJECTIVES:Machine learning (ML) models have been employed in the setting of sleep disorders. This review aims to summarize the existing data about the role of ML techniques in the diagnosis, classification, and treatment of sleep related breathing disorders. METHODS:A systematic search in MedLine, EMBASE, and Cochrane databases through January 2022 was performed. RESULTS:Our search strategy revealed 132 studies that were included in the systematic review. Existing data show that ML models have been successfully used for diagnostic purposes. Specifically, ML models showed good performance in diagnosing sleep apnea using easily obtained features from the electrocardiogram, pulse oximetry and sound signals. Similarly, ML showed good performance for the classification of sleep apnea into obstructive and central categories, as well as predicting apnea severity. Existing data show promising results for the ML-based guided treatment of sleep apnea. Specifically, the prediction of outcomes following surgical treatment and optimization of continuous positive airway pressure therapy, can be guided by ML models. CONCLUSIONS:The adoption and implementation of ML in the field of sleep related breathing disorders is promising. Advancements in wearable sensor technology and ML models can help clinicians predict, diagnose and classify sleep apnea more accurately and efficiently

Lung transplant referral practice patterns: a survey of cystic fibrosis physicians and general pulmonologists

BACKGROUND: Many individuals with cystic fibrosis (CF) die from respiratory failure without referral for lung transplant. Physician practices that may expedite, delay, or preclude referral, are poorly understood. METHODS: Two parallel, web-based surveys focusing on lung transplant referral triggers and barriers, as well as pre-referral evaluation, were emailed to pulmonologists practicing in the New England region. One questionnaire was sent to CF providers (n = 61), and the second to general pulmonary providers practicing at the same institutions (n = 61). RESULTS: There were 43 (70%) responses to the CF provider survey, and 25 (41%) responses to the general pulmonary (‘non-CF’) provider survey. Primary reasons for CF providers to refer their patients included: rapidly declining lung function (91%) and a forced expiratory volume in 1 s (FEV1) below 30% predicted (74%). The greatest barriers to referral for both CF and non-CF providers included active tobacco use (65 and 96%, respectively, would not refer), and active alcohol or other substance use or dependence (63 and 80%). Furthermore, up to 42% of CF providers would potentially delay their referral if triple-combination therapy or other promising new, disease-specific therapy were anticipated. In general, non-CF providers perform a more robust pre-referral medical work-up, while CF providers complete a psychosocial evaluation in higher numbers. Across both groups, communication with lung transplant programs was reported to be inadequate. CONCLUSIONS: Physician-level barriers to timely lung transplant referral exist and need to be addressed. Enhanced communication between lung transplant programs and pulmonary providers may reduce these barriers

International consensus statement on obstructive sleep apnea

Background: Evaluation and interpretation of the literature on obstructive sleep apnea is needed to consolidate and summarize key factors important for clinical management of the OSA adult patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA). Methods: Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus. Results: The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA and treatment on the multiple comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated. Conclusion: This review of the literature in OSA consolidates the available knowledge and identifies the limitations of the current evidence. This effort aims to highlight the basis of OSA evidence-based practice and identify future research needs. Knowledge gaps and opportunities for improvement include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy. This article is protected by copyright. All rights reserved

A core outcome set for future endometriosis research: an international consensus development study

OBJECTIVE: To develop a core outcome set for endometriosis. DESIGN: Consensus development study. SETTING: International. POPULATION: One hundred and sixteen healthcare professionals, 31 researchers and 206 patient representatives. METHODS: Modified Delphi method and modified nominal group technique. RESULTS: The final core outcome set includes three core outcomes for trials evaluating potential treatments for pain and other symptoms associated with endometriosis: overall pain; improvement in the most troublesome symptom; and quality of life. In addition, eight core outcomes for trials evaluating potential treatments for infertility associated with endometriosis were identified: viable intrauterine pregnancy confirmed by ultrasound; pregnancy loss, including ectopic pregnancy, miscarriage, stillbirth and termination of pregnancy; live birth; time to pregnancy leading to live birth; gestational age at delivery; birthweight; neonatal mortality; and major congenital abnormalities. Two core outcomes applicable to all trials were also identified: adverse events and patient satisfaction with treatment. CONCLUSIONS: Using robust consensus science methods, healthcare professionals, researchers and women with endometriosis have developed a core outcome set to standardise outcome selection, collection and reporting across future randomised controlled trials and systematic reviews evaluating potential treatments for endometriosis. TWEETABLE ABSTRACT: @coreoutcomes for future #endometriosis research have been developed @jamesmnduffy

A core outcome set for future endometriosis research : an international consensus development study

Objective: To develop a core outcome set for endometriosis. Design: Consensus development study. Setting: International. Population: One hundred and sixteen healthcare professionals, 31 researchers and 206 patient representatives. Methods: Modified Delphi method and modified nominal group technique. Results: The final core outcome set includes three core outcomes for trials evaluating potential treatments for pain and other symptoms associated with endometriosis: overall pain; improvement in the most troublesome symptom; and quality of life. In addition, eight core outcomes for trials evaluating potential treatments for infertility associated with endometriosis were identified: viable intrauterine pregnancy confirmed by ultrasound; pregnancy loss, including ectopic pregnancy, miscarriage, stillbirth and termination of pregnancy; live birth; time to pregnancy leading to live birth; gestational age at delivery; birthweight; neonatal mortality; and major congenital abnormalities. Two core outcomes applicable to all trials were also identified: adverse events and patient satisfaction with treatment. Conclusions: Using robust consensus science methods, healthcare professionals, researchers and women with endometriosis have developed a core outcome set to standardise outcome selection, collection and reporting across future randomised controlled trials and systematic reviews evaluating potential treatments for endometriosis. Tweetable abstract: @coreoutcomes for future #endometriosis research have been developed @jamesmnduffy