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Background: Misophonia is a recently identified disorder in which individuals experience intense, uncontrollable and disproportional irritation, anger or disgust when confronted with specific sounds or stimuli associated with these sounds. Prevalence rates in children and adolescents are currently still to be investigated. The reported average age of onset is around 13 years, in clinical practice children from 8 years old are referred.Misophonia is associated with avoidance and anticipation anxiety, possibly leading to serious educational and social consequences for children and families. Worldwide, no evidence-based treatment exists specifically for children and adolescents with misophonia.This article presents the design of a randomized controlled trial testing the effectiveness of cognitive behavioral therapy (CBT) combined with psychomotor therapy (PMT) for misophonia in children and adolescents (aged 8–18). Methods: In total, 82 patients will be randomly assigned to a treatment condition or waiting list condition of 3 months (WCG). Treatment consists of 7 weekly group therapy sessions (1.5 h CBT plus 1.5 h PMT) and a follow-up after 3 weeks. Pre and post treatment assessments will be conducted during a baseline assessment, after 3 and 6 months. The primary outcome will be assessed by the Amsterdam Misophonia Scale – Youth (AMISOS-Y) and secondary outcomes (e.g. quality of life) and putative predictors (e.g. parenting burden) will be studied. Conclusion: This trial is the first study worldwide testing the effectiveness of a combined CBT plus PMT protocol for misophonia in children and adolescents. If proven effective, this protocol provides an innovation to improve care for youth with misophonia.

Misophonia is a disorder in which patients suffer from anger or disgust when confronted with specific sounds such as those associated with eating or breathing, causing avoidance of cue related situations resulting in significant functional impairment. Functional magnetic resonance imaging studies suggest misophonia is associated with increased activity in the auditory cortex and salience network, which might reflect increased vigilance toward specific misophonia triggers. New treatments have been developed and investigated in the last years in which this vigilance plays an important role. This is a synopsis of the first group protocol for systemic Cognitive Behavioral Therapy (G-CBT) for misophonia. We discuss the model of CBT for misophonia, provide a detailed guide to the treatment illustrated with a case study, discuss advantages, limitations, and possible pitfalls by a qualitative evaluation of the protocol, and review evidence for the protocol.

Abstract Background COPD is a heterogeneous chronic inflammatory disease of the airways and it is well accepted that the GOLD classification does not fully represent the complex clinical manifestations of COPD and this classification therefore is not well suited for phenotyping of individual patients with COPD. Besides the chronic inflammation in the lung compartment, there is also a systemic inflammation present in COPD patients. This systemic inflammation is associated with elevated levels of cytokines in the peripheral blood, but the precise composition is unknown. Therefore, differences in phenotype of peripheral blood neutrophils in vivo could be used as a read out for the overall systemic inflammation in COPD. Method Our aim was to utilize an unsupervised method to assess the proteomic profile of peripheral neutrophils of stable COPD patients and healthy age matched controls to find potential differences in these profiles as read-out of inflammatory phenotypes. We performed fluorescence two-dimensional difference gel electrophoresis with the lysates of peripheral neutrophils of controls and stable COPD patients. Results We identified two groups of COPD patients based on the differentially regulated proteins and hierarchical clustering whereas there was no difference in lung function between these two COPD groups. The neutrophils from one of the COPD groups were less responsive to bacterial peptide N-formyl-methionyl-leucyl-phenylalanine (fMLF). Conclusion This illustrates that systemic inflammatory signals do not necessarily correlate with the GOLD classification and that inflammatory phenotyping can significantly add in an improved diagnosis of single COPD patients. Trial registration Clinicaltrials.gov: NCT00807469 registered December 11th 2008

Objectives: This study aimed to identify the prevalence of and factors associated with diagnostic uncertainty when critically ill children are admitted to the PICU. Understanding diagnostic uncertainty is necessary to develop effective strategies to reduce diagnostic errors in the PICU., Design: Multicenter retrospective cohort study with structured medical record review by trained clinicians using a standardized instrument to identify diagnostic uncertainty in narrative clinical notes. Diagnoses and diagnostic uncertainty were compared across time from PICU admission to hospital discharge. Generalized linear mixed models were used to determine patient, clinician, and encounter characteristics associated with diagnostic uncertainty at PICU admission., Setting: Four academic tertiary-referral PICUs., Patients: Eight hundred eighty-two randomly selected patients 0-18 years old who were nonelectively admitted to participating PICUs., Interventions: None., Measurements and Main Results: PICU admission notes for 228 of 882 patients (25.9%) indicated diagnostic uncertainty. Patients with uncertainty decreased over time but 58 (6.6%) had remaining diagnostic uncertainty at hospital discharge. Multivariable analysis showed that diagnostic uncertainty was significantly associated with off hours admission (odds ratio [OR], 1.52; p = 0.037), greater severity of illness (OR, 1.04; p = 0.025), an atypical presentation (OR, 2.14; p = 0.046), diagnostic discordance at admission between attending intensivists and resident physicians/advanced practice providers (OR, 3.62; p < 0.001), and having a neurologic primary diagnosis (OR, 1.87; p = 0.03). Older patients (OR, 0.96; p = 0.014) and those with a respiratory (OR, 0.58; p = 0.009) or trauma primary diagnosis (OR, 0.08; p < 0.001) were less likely to have diagnostic uncertainty. There were no significant associations between diagnostic uncertainty and attending intensivists' characteristics., Conclusions: Diagnostic uncertainty at PICU admission was common and was associated with off hours admission, severe illness, atypical presentation, diagnostic discordance between clinicians, and a neurologic primary diagnosis. Further study on the recognition and management of diagnostic uncertainty is needed to inform interventions to improve diagnosis among critically ill children., Competing Interests: Dr. Landrigan has consulted with and holds equity in the I-PASS (Handoff elements mnemonic: I-illness severity, P-patient summary, A-action items, S-situation awareness, S-synthesis) Institute, which seeks to train institutions in best handoff practices and aid in their implementation. In addition, Dr. Landrigan has received monetary awards, honoraria, and travel reimbursement from multiple academic and professional organizations for teaching and consulting on sleep deprivation, physician performance, handoffs, and safety; he has served as an expert witness in cases regarding patient safety and sleep deprivation; and he received funding from the Agency for Healthcare Research and Quality (AHRQ). Drs. Cifra’s, K. A. Smith’s, Bloxham’s, Hoppe’s, Miller’s, Riffe’s, Robb’s, Simone’s, Tumulty’s, Dawson’s, and Herwaldt’s institutions received funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the AHRQ, and the National Center for Advancing Translational Sciences. Drs. Cifra, Bloxham, Miller, and Tumulty received funding from the AHRQ, MedStar Research Institute, and De Gruyter. Drs. Cifra, C. M. Smith, K. A. Smith, Bagdure, Bloxham, Goldhar, Hoppe, Miller, Pizzo, Riffe, Robb, Tumulty, Wolfe, Wendt, Eyck, Dawson, Reisingerr, Singh, and Herwaldt received support for article research from the National Institutes of Health. Dr. Gorga disclosed institutional grant funding. Dr. Ten Eyck disclosed work for hire. Dr. Dawson received funding from Neurosurgery, the University of Nebraska Medical Center, and IotaSoft. Dr. Singh is supported in part by the AHRQ (R01HS028595 and R18HS029347), the Houston Veterans Administration (VA) Health Services Research and Development Center for Innovations in Quality, Effectiveness and Safety (CIN 13–413), and the VA National Center for Patient Safety; he disclosed government work. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of the VA or the U.S. government. Dr. Herwaldt’s institution received funding from the Centers for Disease Control and Prevention. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2024 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objectives: Effective interventions to prevent diagnostic error among critically ill children should be informed by diagnostic error prevalence and etiologies. We aimed to determine the prevalence and characteristics of diagnostic errors and identify factors associated with error in patients admitted to the PICU., Design: Multicenter retrospective cohort study using structured medical record review by trained clinicians using the Revised Safer Dx instrument to identify diagnostic error (defined as missed opportunities in diagnosis). Cases with potential errors were further reviewed by four pediatric intensivists who made final consensus determinations of diagnostic error occurrence. Demographic, clinical, clinician, and encounter data were also collected., Setting: Four academic tertiary-referral PICUs., Patients: Eight hundred eighty-two randomly selected patients 0-18 years old who were nonelectively admitted to participating PICUs., Interventions: None., Measurements and Main Results: Of 882 patient admissions, 13 (1.5%) had a diagnostic error up to 7 days after PICU admission. Infections (46%) and respiratory conditions (23%) were the most common missed diagnoses. One diagnostic error caused harm with a prolonged hospital stay. Common missed diagnostic opportunities included failure to consider the diagnosis despite a suggestive history (69%) and failure to broaden diagnostic testing (69%). Unadjusted analysis identified more diagnostic errors in patients with atypical presentations (23.1% vs 3.6%, p = 0.011), neurologic chief complaints (46.2% vs 18.8%, p = 0.024), admitting intensivists greater than or equal to 45 years old (92.3% vs 65.1%, p = 0.042), admitting intensivists with more service weeks/year (mean 12.8 vs 10.9 wk, p = 0.031), and diagnostic uncertainty on admission (77% vs 25.1%, p < 0.001). Generalized linear mixed models determined that atypical presentation (odds ratio [OR] 4.58; 95% CI, 0.94-17.1) and diagnostic uncertainty on admission (OR 9.67; 95% CI, 2.86-44.0) were significantly associated with diagnostic error., Conclusions: Among critically ill children, 1.5% had a diagnostic error up to 7 days after PICU admission. Diagnostic errors were associated with atypical presentations and diagnostic uncertainty on admission, suggesting possible targets for intervention., Competing Interests: Drs. Cifra, Smith, Riffe, Landrigan, and Dawson’s institutions received funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development through a K12 grant to the University of Iowa Stead Family Department of Pediatrics (no. HD027748-28) and the National Center for Advancing Translational Sciences. Drs. Cifra, KA Smith, Riffe, Landrigan, Dawson, and Herwaldt’s institutions received funding from the Agency for Healthcare Research and Quality (AHRQ) through a K08 grant (no. HS026965). This work was further supported by the National Center for Advancing Translational Sciences of the National Institutes of Health (no. UL1TR002537) through the University of Iowa’s Institute for Clinical and Translational Science. Dr. Cifra received funding from the AHRQ, MedStar Research Institute, and De Gruyter. Drs. Cifra, CM Smith, KA Smith, Riffe, Ten Eyck, Landrigan, and Dawson received support for article research from the National Institutes of Health. Drs. Custer and Tumulty’s institution received funding from University of Iowa. Dr. Miller’s institution received funding from the University of Iowa Department of Pediatrics. Dr. Landrigan received funding from I-PASS Institute and Missouri Hospital Association Executive Speakers Bureau. Dr. Singh is funded in part by the Houston Veterans Administration (VA) Health Services Research and Development (HSR&D) Center for Innovations in Quality, Effectiveness, and Safety (CIN13–413), the VA HSR&D Service (IIR17–127 and the Presidential Early Career Award for Scientists and Engineers USA 14–274), the VA National Center for Patient Safety, the Agency for Healthcare Research and Quality (R01HS27363), and the Gordon and Betty Moore Foundation. He disclosed government work. Dr. Herwaldt’s institution received funding from the Centers for Disease Control and Prevention; she disclosed that Professional Disposables International, Inc. (PDI) is providing a product for a clinical trial. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2023 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.)

Objective: Care of critically ill children includes sedation but current therapies are suboptimal. To describe dexmedetomidine use in children supported on mechanical ventilation for acute respiratory failure., Design: Secondary analysis of data from the Randomized Evaluation of Sedation Titration for Respiratory Failure clinical trial., Setting: Thirty-one PICUs., Patients: Data from 2,449 children; 2 weeks to 17 years old., Interventions: Sedation practices were unrestrained in the usual care arm. Patients were categorized as receiving dexmedetomidine as a primary sedative, secondary sedative, periextubation agent, or never prescribed. Dexmedetomidine exposure and sedation and clinical profiles are described., Measurements and Main Results: Of 1,224 usual care patients, 596 (49%) received dexmedetomidine. Dexmedetomidine as a primary sedative patients (n = 138; 11%) were less critically ill (Pediatric Risk of Mortality III-12 score median, 6 [interquartile range, 3-11]) and when compared with all other cohorts, experienced more episodic agitation. In the intervention group, time in sedation target improved from 28% to 50% within 1 day of initiating dexmedetomidine as a primary sedative. Dexmedetomidine as a secondary sedative usual care patients (n = 280; 23%) included more children with severe pediatric acute respiratory distress syndrome or organ failure. Dexmedetomidine as a secondary sedative patients experienced more inadequate pain (22% vs 11%) and sedation (31% vs 16%) events. Dexmedetomidine as a periextubation agent patients (n = 178; 15%) were those known to not tolerate an awake, intubated state and experienced a shorter ventilator weaning process (2.1 vs 2.3 d)., Conclusions: Our data support the use of dexmedetomidine as a primary agent in low criticality patients offering the benefit of rapid achievement of targeted sedation levels. Dexmedetomidine as a secondary agent does not appear to add benefit. The use of dexmedetomidine to facilitate extubation in children intolerant of an awake, intubated state may abbreviate ventilator weaning. These data support a broader armamentarium of pediatric critical care sedation., Competing Interests: No conflicts of interest.