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Background: The authors previously described an acoustic cardiographic model that predicted echocardiographic correlates of elevated left ventricular (LV) filling pressure. This study evaluated this bedside acoustic cardiographic model against invasive measurements of LV filling pressure. Methods and Results: Data were prospectively obtained from 68 adults referred for right heart catheterisation. Acoustic cardiographic measurements were obtained during right heart catheterisation. Elevated LV filling pressure was defined as a pulmonary capillary wedge pressure (PCWP) > or =15 mm Hg. Parameters generated from a previous dataset used for the current analysis were measures of LV systolic time, maximum negative area of the P wave, QTc interval and third heart sound (S3) score. Logistic regression was used to calculate area under the curve (AUC). Of the 66 patients included, 39 had elevated PCWP. Estimating the probability of an elevated PCWP from the derived model resulted in an AUC of 0.72 (95% CI 0.60 to 0.85). When the regression model's parameters were held constant but the parameter estimates were allowed to vary, the AUC in the validated model was 0.76 (95% CI 0.64 to 0.88). At a specificity of 90% the positive likelihood ratio (LR+) was 5.0 (1.7 to 15.3) and the negative likelihood ratio was 0.49 (0.34 to 0.71). Conclusion: These data demonstrate that the four-variable model predicts elevated filling pressure at the bedside with high specificity and an intermediate LR+. With improvements in sensitivity and further prospective validation of this model in a cohort of emergency department patients with undifferentiated dyspnoea this may be a useful bedside diagnostic modality. [ABSTRACT FROM AUTHOR]

Background: Anti-epileptic drugs are commonly used for seizure prophylaxis after neurological injury. We performed a study comparing intravenous (IV) levetiracetam (LEV) to IV phenytoin (PHT) for seizure prophylaxis after neurological injury.Methods: In this prospective, single-center, randomized, single-blinded comparative trial of LEV versus PHT (2:1 ratio) in patients with severe traumatic brain injury (sTBI) or subarachnoid hemorrhage (NCT00618436) patients received IV load with either LEV or fosphenytoin followed by standard IV doses of LEV or PHT. Doses were adjusted to maintain therapeutic serum PHT concentrations or if patients had seizures. Continuous EEG (cEEG) monitoring was performed for the initial 72 h; outcome data were collected.Results: A total of 52 patients were randomized (LEV = 34; PHT = 18); 89% with sTBI. When controlling for baseline severity, LEV patients experienced better long-term outcomes than those on PHT; the Disability Rating Scale score was lower at 3 months (P = 0.042) and the Glasgow Outcomes Scale score was higher at 6 months (P = 0.039). There were no differences between groups in seizure occurrence during cEEG (LEV 5/34 vs. PHT 3/18; P = 1.0) or at 6 months (LEV 1/20 vs. PHT 0/14; P = 1.0), mortality (LEV 14/34 vs. PHT 4/18; P = 0.227). There were no differences in side effects between groups (all P > 0.15) except for a lower frequency of worsened neurological status (P = 0.024), and gastrointestinal problems (P = 0.043) in LEV-treated patients.Conclusions: This study of LEV versus PHT for seizure prevention in the NSICU showed improved long-term outcomes of LEV-treated patients vis-à-vis PHT-treated patients. LEV appears to be an alternative to PHT for seizure prophylaxis in this setting. [ABSTRACT FROM AUTHOR]

STUDY OBJECTIVE: The Institute of Medicine, through its landmark report concerning errors in medicine, suggests that standardization of practice through systematic development and implementation of evidence-based clinical pathways is an effective way of reducing errors in emergency systems. The specialty of emergency medicine is well positioned to develop a complete system of innovative quality improvement, incorporating best practice guidelines with performance measures and practitioner feedback mechanisms to reduce errors and therefore improve quality of care. This article reviews the construction, ongoing development, and initial impact of such a system at a large, urban, university teaching hospital and at 2 affiliated community hospitals. METHODS: The Committee for Procedural Quality and Evidence-Based Practice was formed within the Department of Emergency Medicine to establish evidence-based guidelines for nursing and provider care. The committee measures the effect of such guidelines, along with other quality measures, through pre- and postguideline patient care medical record audits. These measures are fed back to the providers in a provider-specific, peer-matched 'scorecard.' RESULTS: The Committee for Procedural Quality and Evidence-Based Practice affects practice and performance within our department. Multiple physician and nursing guidelines have been developed and put into use. Using asthma as an example, time to first nebulizer treatment and time to disposition from the emergency department decreased. Initial therapeutic agent changed and documentation improved. CONCLUSION: A comprehensive, guideline-driven, evidence-based approach to clinical practice is feasible within the structure of a department of emergency medicine. High-level departmental support with dedicated personnel is necessary for the success of such a system. Internet site development (available at http://www.CPQE.com) for product storage has proven valuable. Patient care has been improved in several ways; however, consistent and complete change in provider behavior remains elusive. Physician scorecards may play a role in altering these phenomena. Emergency medicine can play a leadership role in the development of quality improvement, error reduction, and pay-for-performance systems. [ABSTRACT FROM AUTHOR]

Up to 55% of the homeless population report health problems. They often use the emergency department (ED) to obtain care when the health needs are not urgent. Nurse-managed clinics have the potential to reduce nonurgent ED use and improve the health of the homeless. The purpose of this study was to establish baseline health data on homeless persons prior to attending a nurse-managed clinic. This study was a cross-sectional, retrospective health survey of homeless clients at a nurse-managed clinic. A total of 110 participants completed a baseline health survey. Of these, 61% reported that prior to coming to the clinic, they used the ED as a source of health care. The most frequent medical diagnoses reported were substance use disorders, depression, back pain, hypertension, and asthma. Providing care for chronic conditions at a nurse-managed clinic has the potential to improve health and reduce use of the ED. [ABSTRACT FROM AUTHOR]

OBJECTIVE: HbA(1c) (A1C) is substantially determined by genetic factors not shared in common with glucose. Fractions of the variance in A1C, the glycation gap (GG; previously called the glycosylation gap) and the hemoglobin glycosylation index, correlate with diabetes complications. We therefore tested whether GG (measured A1C - A1C predicted from glycated serum proteins [GSPs]) was genetically determined and whether it accounted for the heritability of A1C. RESEARCH DESIGN AND METHODS: We conducted a classic twin study on A1C and GSP collected in 40 and 46 pairs of monozygotic and dizygotic healthy female twins, respectively. The predicted A1C was based on the regression line between A1C and GSP in a separate population spanning the pathophysiologic range. RESULTS: GG was more strongly correlated between monozygotic (r = 0.65) than dizygotic (r = 0.48) twins, adjusted for age and BMI. The best-fitting quantitative genetic model adjusted for age and BMI showed that 69% of population variance in GG is heritable, while the remaining 31% is due to unique environmental influences. In contrast, GSP was similarly correlated between monozygotic (r = 0.55) and dizygotic (r = 0.49) twins, hence not genetically determined. GG was strongly correlated to A1C (r = 0.48), attributable mostly to genetic factors. About one-third of the heritability of A1C is shared with GG; the remainder is specific to A1C. CONCLUSIONS: Heritability of the GG accounts for about one-third of the heritability of A1C. By implication, there are gene(s) that preferentially affect erythrocyte lifespan or glucose and/or nonenzymatic glycation or deglycation in the intracellular, rather than extracellular, compartment. [ABSTRACT FROM AUTHOR]

Objective. To evaluate both factors predicting nontransport and mortality rates in an emergency medical services system with a nontransport policy. Methods. We reviewed data from 1,581 transported and nontransported patients from October 2001 to July 2003. Patients who refused transport against medical advice were excluded. Extracted data included demographics, run characteristics, chief complaint, and clinical impression. Transported and nontransported patients were compared using Mann-Whitney U or chi-square tests. Logistic regression identified factors predictive of nontransport. A Social Security Death Index search determined 30-day mortality. Results. A total of 1,501 runs involving 1,059 patients were included. Median age was 60 years (range, 0-97 years). A total of 427 (40.4%) were male; 107 (10.2%) were nonwhite. Older patients were more likely to be transported (odds ratio, 1.03; confidence interval, 1.02-1.03). Race, frequency of calls, mutual aid, or time of day did not significantly influence probability of transport. Patients with cardiovascular, respiratory, and gastrointestinal complaints were more likely to be transported than those with other conditions (P < 0.005); patients with endocrine, trauma, and miscellaneous complaints were less likely to be transported (P < 0.003). Patients with renal, obstetrics/gynecology, and hema matology/oncology were complaints all transported. Mortality was 4.9% (confidence interval, 3.9%-6.2%) for transported patients and 1.0% for those not transported (confidence interval, 0.2%-3.7%). Conclusions. Age is a determinant when deciding on transporting patients. Patients with complaints with potentially higher acuity were transported most often. Only two nontransported patients died within 30 days, although it is unknown whether initial transport would have changed their mortality. Our data suggest that emergency medical services-initiated nontransport is influenced only by age and chief complaint and may not result in significant mortality. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Understanding perceived benefits and disadvantages of HIV testing in emergency departments (EDs) is imperative to overcoming barriers to implementation. We codify those domains of public health and clinical care most affected by implementing HIV testing in EDs, as determined by expert opinion. METHODS: Opinions were systematically collected from attendees of the 2007 National ED HIV Testing Consortium meeting. Structured evaluation of strengths, weaknesses, opportunities, and threats analysis was conducted to assess the impact of ED-based HIV testing on public health. A modified Delphi method was used to assess the impact of ED-based HIV testing on clinical care from both individual patient and individual provider perspectives. RESULTS: Opinions were provided by 98 experts representing 42 academic and nonacademic institutions. Factors most frequently perceived to affect public health were (strengths) high volume of ED visits and high prevalence of HIV, (weaknesses) undue burden on EDs, (opportunities) reduction of HIV stigma, and (threats) lack of resources in EDs. Diagnostic testing and screening for HIV were considered to have a favorable impact on ED clinical care from both individual patient and individual provider perspectives; however, negative test results were not perceived to have any benefit from the provider's perspective. The need for HIV counseling in the ED was considered to have a negative impact on clinical care from the provider's perspective. CONCLUSION: Experts in ED-based HIV testing perceived expanded ED HIV testing to have beneficial impacts for both the public health and individual clinical care; however, limited resources were frequently cited as a possible impediment. Many issues must be resolved through further study, education, and policy changes if the full potential of HIV testing in EDs is to be realized. [ABSTRACT FROM AUTHOR]

OBJECTIVES: In the absence of a gold standard, clinicians and researchers often categorize their opinions of the likelihood of inflicted injury using several ordinal scales. The objective of this protocol was to determine the reliability of expert ratings using several of these scales. METHODS: Participants were pediatricians with substantial academic and clinical activity in the evaluation of children with concerns for physical abuse. The facts from several cases that were referred to 1 hospital's child abuse team were abstracted and recorded as in a multidisciplinary team conference. Participants viewed the recording and rated each case using several scales of child abuse likelihood. RESULTS: Participants (n = 22) showed broad variability for most cases on all scales. Variability was lowest for cases with the highest aggregate concern for abuse. One scale that included examples of cases fitting each category and standard reporting language to summarize results showed a modest (18%-23%) decrease in variability among participants. The interpretation of the categories used by the scales was more consistent. Cases were rarely rated as 'definite abuse' when likelihood was estimated at < or = 95%. Only 7 of 156 cases rated < or = 15% likelihood were rated as 'no reasonable concern for abuse.' Only 9 of 858 cases rated > or = 35% likelihood were rated as 'reasonable concern for abuse.' CONCLUSIONS: Assessments of child abuse likelihood often show broad variability between experts. Although a rating scale with patient examples and standard reporting language may decrease variability, clinicians and researchers should be cautious when interpreting abuse likelihood assessments from a single expert. These data support the peer-review or multidisciplinary team approach to child abuse assessments. [ABSTRACT FROM AUTHOR]

Background: Little is known about the relationship between types of healthcare providers and outcomes in patients with epilepsy. This study compares the relative effects of provider type (epileptologist vs. other neurologist) and pharmacologic treatment (newer vs. older antiepileptic drugs) on seizure control in patients with epilepsy.Methods: We conducted a retrospective study of patients with medication-resistant epilepsy. Consecutive charts of 200 patients were abstracted using a standard case report form. For each patient, data included seizure frequency and medication use prior to, and while being treated by an epileptologist. Changes in seizure frequency were modeled using a generalized linear model.Results: After transferring care from a general neurologist to specialized epilepsy center, patients experienced fewer seizures (p < 0.001) and were more frequently seizure-free (p < 0.001). The improved seizure control was not related to treatment with newer vs. older antiepileptic drugs (p = 0.305).Conclusion: Our findings suggest an association between subspecialty epilepsy care and improved seizure control in patients with medication-resistant epilepsy. Further research should prospectively determine whether patients with medication-resistant epilepsy would benefit from being routinely referred to an epilepsy specialist. [ABSTRACT FROM AUTHOR]

Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technologies can potentially automate and streamline clinical trial operations. This review describes opportunities to integrate AI throughout a trial's life cycle, including designing the trial, identifying eligible patients, obtaining informed consent, ascertaining physiological and clinical event outcomes, interpreting imaging, and analyzing or disseminating the results. Nevertheless, AI poses risks, including generating inaccurate results, amplifying biases against underrepresented groups, and violating patient privacy. Medical journals and regulators are developing new frameworks to evaluate AI research tools and the data they generate. Given the high-stakes role of randomized trials in medical decision making, AI must be integrated carefully and transparently to protect the validity of trial results., Competing Interests: Funding Support and Author Disclosures Dr Cunningham has received support from the KL2/Harvard Catalyst Medical Research Investigator Training program and the American Heart Association (23CDA1052151); and has received consulting fees from Roche Diagnosis, Edgewise Therapeutics, KCK, and Occlutech. Dr Abraham has served as a consultant to Boehringer Ingelheim, CVRx, Impulse Dynamics, Sensible Medical, Vectorious, V-Wave, and Zoll Respicardia. Dr Bhatt has received research grant support to his institution from the National Institutes of Health (NIH) National Heart, Lung, and Blood Institute (NHLBI) and National Institute on Aging, the American College of Cardiology Foundation, and the Centers for Disease Control and Prevention (CDC); and has received consulting fees from the Kinetix Group, Merck, Sanofi Pasteur, and Novo Nordisk. Dr Dunn has served as a scientific advisor to Veri. Dr Felker has received research grants from NIH, Bayer, Bristol Myers Squibb, Novartis, Daxor, Merck, Cytokinetics, and CSL-Behring; has acted as a consultant to Novartis, Bristol Myers Squibb, Cytokinetics, Innolife, Boehringer Ingelheim, Abbott, Sanofi, Regeneron, Myovant, Sequana, Windtree Therapeutics, and Whiteswell; and has served on clinical endpoint committees or data safety monitoring boards for Merck, Medtronic, EBR Systems, Rocket Pharma, V-Wave, and LivaNova. Dr Jain has received consulting fees from Bristol Myers Squibb, ARTIS Ventures, and Broadview Ventures outside of the submitted work. Dr Lindsell has received grants and contracts from the NIH, the U.S. Department of Defense, CDC, Biomeme, Novartis, bioMérieux, AstraZeneca, AbbVie, Entegrion, and Endpoint Health, all outside of the submitted work; has obtained patents for risk stratification in sepsis and septic shock issued to Cincinnati Children’s Hospital Medical Center; has served on data safety monitoring boards unrelated to the current work; has held stock options in Bioscape Digital unrelated to the current work; and has served as Editor-in-Chief of the Journal of Clinical and Translational Science. Mr Mace is an employee of Acorai AB; and has held stock interest in Abbott Laboratories. Dr Martyn has served as an advisor to or has received consulting fees from Fire1, Cleveland Clinic/American Well Joint Venture, Boehringer Ingelheim/Eli Lilly, NIRSense, Novo Nordisk, AstraZeneca, and Apricity Robotics; and has received grant support from Ionis Therapeutics, AstraZeneca, and the Heart Failure Society of America. Dr Shah is an employee of Meta, which had no role in this work or providing financial support. Dr Tison has received research grants from MyoKardia, a wholly owned subsidiary of Bristol Myers Squibb, and Janssen Pharmaceuticals; and is an advisor to Viz.ai and Prolaio. Dr Fakhouri is an employee of the Office of Medical Policy, Center for Drug Evaluation and Research, U.S. Food and Drug Administration; the views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Food and Drug Administration. Dr Krumholz has received options from Element Science and Identifeye; has received payments from F-Prime for advisory roles; has co-founded and held equity in Hugo Health, Refactor Health, and ENSIGHT-AI; and has been associated with research contracts through Yale University from Janssen, Kenvue, and Pfizer. Dr O’Connor has received consulting fees from Merck, Abiomed, and Zealcare. Dr Solomon has received research grants from Alexion, Alnylam, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Boston Scientific, Cytokinetics, Edgewise, Eidos, Gossamer, GSK, Ionis, Lilly, MyoKardia, NIH NHLBI, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI; and has consulted for Abbott, Action, Akros, Alexion, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi-Sankyo, GSK, Lilly, Merck, MyoKardia, Novartis, Roche, Theracos, Quantum Genomics, Janssen, Cardiac Dimensions, Tenaya, Sanofi-Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, Sarepta, Lexicon, AnaCardio, Akros, and Valo. Drs Psotka and Fiuzat have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Because 20-30% of patients with sepsis deteriorate to critical illness, biomarkers that provide accurate early prognosis may identify which patients need more intensive treatment versus safe early discharge. The objective was to test the performance of sVEGFR2, suPAR and PCT, alone or combined with clinical signs and symptoms, for the prediction of clinical deterioration. This prospective observational study enrolled patients with suspected infection who met SIRS criteria without organ dysfunction (delta SOFA <2 from baseline) from 16 emergency departments. The primary endpoint was clinical deterioration (increased SOFA score ≥2 points, new or increased organ support, or death) within 72 hours of enrollment. Diagnosis and classification of infection status were adjudicated. 724 patients were enrolled, (54% men, median age 55 [38-70] y-o). Infection origin was abdominopelvic (21%), skin and soft tissues (17%), urinary (16%) and pulmonary (15%). 176 (24%) patients deteriorated, with a 28-day mortality of 1.4%. They had lower sVEGFR2 level (6.17 [5.00-7.40] vs 6.52 [5.40-7.84], p=0.024), higher circulating suPAR (5.25 [3.86-7.50] vs 4.18 [3.16-5.68], p<0.001) and higher PCT level (0.32 [0.08-1.80] vs 0.18 [0.05-0.98], p=0.004). suPAR demonstrated superior performance (AUC=0.65 [0.60-0.70]), compared to other biomarkers (PCT, AUC=0.57 [0.52-0.62] and sVEGFR2, AUC=0.58 [0.53-0.64]). Maximum accuracy was achieved from the combination of clinical information, sVEGFR2 and suPAR, yielding an AUC of 0.74 [0.69-0.78] and NPV 0.90 [0.88-0.94]. sVEGFR2 and suPAR were insufficiently accurate to rule out clinical deterioration. Panels of biomarkers will likely be needed to capture the heterogeneous mechanistic pathways involved in sepsis-related organ failure., (© 2024. The Author(s), under exclusive licence to Società Italiana di Medicina Interna (SIMI).)

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future., Competing Interests: Dr Lindsell reported receiving grants to the institution from the National Center for Advancing Translational Sciences (NCATS) for the submitted work; grants to the institution from NIH and Department of Defense and research funds to the institution from the CDC, bioMerieux, AstraZeneca, AbbVie, Entegrion Inc., and Endpoint Health outside the submitted work; patents for risk stratification in sepsis and septic shock issued to Cincinnati Children’s Hospital Medical Center; service on DSMBs unrelated to the current work; and stock options in Bioscape Digital unrelated to the current work. Dr Shotwell reported receiving grants to the institution from the National Heart, Lung, and Blood Institute (NHLBI) for the submitted work; grants to the institution from NIH and research funds from MedRegen LLC and Lupin Pharmaceuticals unrelated the submitted work; and service on DSMBs unrelated to the submitted work. Dr Anstrom reports grants to the institution from the NIH for the submitted work and outside the submitted work. Dr Berry is a part-owner of Berry Consultants, a scientific consulting company, which received funds for trial design work by NIH. Dr Harrell reports receiving funding from NCATS. Dr Grund reports grants to the institution from the NIH for the submitted work and outside the submitted work. Dr Moser reported receiving grants to the institution from the National Institute of Allergy and Infectious Disease of the National Institutes of Health, and unrelated to the current work, participates on a data safety monitoring board for the BONE STAR study. Dr Hughes reports research and training grants paid to institution from NIH related to COVID and infectious diseases. Dr Price is an employee of Eli Lilly and Company. Dr Stewart reported receiving grants to the institution from the National Center for Advancing Translational Sciences (NCATS) for the submitted work, grants to the institution from NIH, and service on DMC unrelated to the current work. Dr Thomas reported receiving grants to the institution from the National Heart Lung and Blood Institute for the submitted work. Dr Touloumi reported receiving grants to the institution from Gilead Sciences, UCL, Bristol University, EU and National Funds, and honoraria from Gilead Sciences. Dr LaVange reported receiving grants to the institution for the submitted work. Drs. Britain, Geller, Jagannathan, Leifer, and Proschan report no competing interests., (© The Author(s) 2024.)

This manuscript addresses a critical topic: navigating complexities of conducting clinical trials during a pandemic. Central to this discussion is engaging communities to ensure diverse participation. The manuscript elucidates deliberate strategies employed to recruit minority communities with poor social drivers of health for participation in COVID-19 trials. The paper adopts a descriptive approach, eschewing analysis of data-driven efficacy of these efforts, and instead provides a comprehensive account of strategies utilized. The Accelerate COVID-19 Treatment Interventions and Vaccines (ACTIV) public-private partnership launched early in the COVID-19 pandemic to develop clinical trials to advance SARS-CoV-2 treatments. In this paper, ACTIV investigators share challenges in conducting research during an evolving pandemic and approaches selected to engage communities when traditional strategies were infeasible. Lessons from this experience include importance of community representatives' involvement early in study design and implementation and integration of well-developed public outreach and communication strategies with trial launch. Centralization and coordination of outreach will allow for efficient use of resources and the sharing of best practices. Insights gleaned from the ACTIV program, as outlined in this paper, shed light on effective strategies for involving communities in treatment trials amidst rapidly evolving public health emergencies. This underscores critical importance of community engagement initiatives well in advance of the pandemic., Competing Interests: None., (© The Author(s) 2024.)

Accelerating COVID-19 Treatment Interventions and Vaccines (ACTIV) was initiated by the US government to rapidly develop and test vaccines and therapeutics against COVID-19 in 2020. The ACTIV Therapeutics-Clinical Working Group selected ACTIV trial teams and clinical networks to expeditiously develop and launch master protocols based on therapeutic targets and patient populations. The suite of clinical trials was designed to collectively inform therapeutic care for COVID-19 outpatient, inpatient, and intensive care populations globally. In this report, we highlight challenges, strategies, and solutions around clinical protocol development and regulatory approval to document our experience and propose plans for future similar healthcare emergencies., Competing Interests: The authors declare none., (© The Author(s) 2024.)

Rationale: Ansa cervicalis stimulation (ACS) of the infrahyoid muscles has been proposed as a neurostimulation therapy for obstructive sleep apnea (OSA). ACS stabilizes the pharynx by pulling it caudally, but its specific effects on flow limitation caused by palatal, oropharyngeal lateral wall, tongue base, or epiglottis collapse remains unclear., Objectives: To quantify the effect of ACS on collapsibility of different pharyngeal flow-limiting structures., Methods: Participants with OSA underwent bilateral ACS during drug-induced sleep endoscopy. Maximum inspiratory airflow was assessed over a range of positive airway pressures while ACS was applied. The flow-limiting structure for each breath was classified based on manometric and endoscopic findings and a linear mixed-effects model characterized their response to ACS. The influence of patient characteristics was explored with univariate models., Measurements and Main Results: Forty-one participants yielded 1761 breaths for analysis. On average, bilateral ACS decreased the observed pharyngeal critical closing (P CRIT ) and opening (P OPEN ) pressures by -3.0 [95% confidence interval: [-3.6, -2.3] and -3.7 [-4.4, -3.0] cmH2O, respectively (p<0.001). During tongue base obstruction, modeled ACS effects for P CRIT and P OPEN were -2.0 [-2.7, -1.4] and -3.1 [-3.8, -2.4] cmH 2 O, respectively (p<0.001). Greater reductions were generally observed for other flow-limiting structures. A lower apnea-hypopnea index was associated with a greater decrease in P OPEN (p<0.01). Other patient characteristics, including body mass index, did not influence P CRIT or P OPEN (p>0.05)., Conclusions: Bilateral ACS decreased collapsibility of all airway flow-limiting structures. ACS generally had greater effects on palatal, oropharyngeal lateral wall, and epiglottic collapse than the tongue base., (Copyright ©The authors 2024. For reproduction rights and permissions contact permissions@ersnet.org.)

Importance: The effect of montelukast in reducing symptom duration among outpatients with mild to moderate COVID-19 is uncertain., Objective: To assess the effectiveness of montelukast compared with placebo in treating outpatients with mild to moderate COVID-19., Design, Setting, and Participants: This randomized clinical trial (Accelerating COVID-19 Therapeutic Interventions and Vaccines [ACTIV]-6) was conducted from January 27 through June 23, 2023, during the circulation of Omicron subvariants. Participants aged 30 years or older with confirmed SARS-CoV-2 infection and 2 or more acute COVID-19 symptoms for less than 7 days were included across 104 US sites., Interventions: Participants were randomized 1:1 to receive montelukast, 10 mg once daily, or matched placebo for 14 days., Main Outcomes and Measures: The primary outcome was time to sustained recovery (defined as ≥3 consecutive days without symptoms). Secondary outcomes included time to death; time to hospitalization or death; a composite of health care utilization events (hospitalization, urgent care clinic visit, emergency department visit, or death); COVID-19 clinical progression scale score; and difference in mean time unwell. A modified intention-to-treat approach was used for the analysis., Results: Among 1250 participants who were randomized and received the study drug or placebo, the median age was 53 years (IQR, 42-62 years), 753 (60.2%) were female, and 704 (56.3%) reported receiving 2 or more doses of a SARS-CoV-2 vaccine. Among 628 participants who received montelukast and 622 who received placebo, differences in time to sustained recovery were not observed (adjusted hazard ratio [AHR], 1.02; 95% credible interval [CrI], 0.92-1.12; P = .63 for efficacy). Unadjusted median time to sustained recovery was 10 days (95% CI, 10-11 days) in both groups. No deaths occurred, and hospitalizations were reported for 2 participants (0.3%) in each group; the composite of health care utilization events was reported for 18 participants (2.9%) in the montelukast group and 18 (2.9%) in the placebo group (AHR, 1.01; 95% CrI, 0.45-1.84; P = .48 for efficacy). Five participants (0.4%) experienced serious adverse events (3 [0.5%] in the montelukast group and 2 [0.3%] in the placebo group)., Conclusions and Relevance: In this randomized clinical trial of outpatients with mild to moderate COVID-19, treatment with montelukast did not reduce duration of COVID-19 symptoms. These findings do not support the use of montelukast for the treatment of mild to moderate COVID-19., Trial Registration: ClinicalTrials.gov Identifier: NCT04885530.

Study Objective: To evaluate if out-of-hospital administration of fentanyl and intranasal ketamine, compared to fentanyl alone, improves early pain control after injury., Methods: We conducted an out-of-hospital randomized, placebo-controlled, blinded, parallel group clinical trial from October 2017 to December 2021. Participants were male, aged 18 to 65 years, receiving fentanyl to treat acute traumatic pain prior to hospital arrival, treated by an urban fire-based emergency medical services agency, and transported to the region's only adult Level I trauma center. Participants randomly received 50 mg intranasal ketamine or placebo. The primary outcome was the proportion with a minimum 2-point reduction in self-described pain on the verbal numerical rating scale 30 minutes after study drug administration assessed by 95% confidence interval overlap. Secondary outcomes were side effects, pain ratings, and additional pain medications through the first 3 hours of care., Results: Among the 192 participants enrolled, 89 (46%) were White, (median age, 36 years; interquartile range, 27 to 53 years), with 103 receiving ketamine and 89 receiving placebo. There was no difference in the proportion experiencing improved pain 30 minutes after treatment (46/103 [44.7%] ketamine versus 32/89 [36.0%] placebo; difference in proportions, 8.7%; 95% confidence interval, -5.1% to 22.5%; P=.22) or at any time point through 3 hours. There was no difference in secondary outcomes or side effects., Conclusion: In our sample, we did not detect an analgesic benefit of adding 50 mg intranasal ketamine to fentanyl in out-of-hospital trauma patients., (Copyright © 2024 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)

Objectives: Surgical outcomes determine national ranking, reputation, and funding, and are often assessed with objective surgical risk calculators (SRCs). Surgeons' assessments are not considered. This study aims to determine if surgeons or SRCs are more accurate in predicting outcomes. Methods: This prospective cohort study identified a surgeon's assessment on a patient's risk preoperatively. The patient's risk was also calculated using the SRC. Predictions were compared to patient outcomes and to each other to assess whether surgeons or the SRC were more accurate. Results: Of the 101 patients included, 37 (36.6%) experienced a complication of any kind and 18 (17.8%) experienced a serious complication. Smoking resulted in a 2.49 times higher overall complication rate ( P = .04). Laryngectomy patients experienced the highest rate of complications ( P = .02) compared to those undergoing free flap reconstruction [odds ratio (OR) 0.9] or any other surgery (OR 0.26). Both surgeons and the American College of Surgeons (ACS) tool performed poorly on the prediction of the outcome of any complication, with a receiver operating characteristic (ROC) area under the curve (AUC) of 0.51 [95% confidence interval (CI): 0.39-0.62] and 0.58 (95% CI: 0.47-0.70), respectively, which was not statistically significant ( P = .34). For the prediction of the outcome of serious complication, the AUC for surgeons and the ACS tool were 0.55 (95% CI: 0.41-0.69) and 0.60 (95% CI: 0.46-0.74), respectively, which was not statistically significant ( P = .58). Conclusions: Neither validated risk calculators nor surgeons are accurate in predicting perioperative risk. The only risk factor that contributes to improving predictions for complications is preoperative smoking, although age and type of surgery are also significant predictors. Risk calculators may therefore not be appropriate metrics for assessing hospital performance. These findings can help guide preoperative counseling and may help in the development of more accurate predictive tools as the healthcare field continues to incorporate artificial intelligence into surgical planning., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.