Duchenne muscular dystrophy is a devastating neuromuscular disorder characterized by the loss of dystrophin, inevitably leading to cardiomyopathy. Despite publications on prophylaxis and treatment with cardiac medications to mitigate cardiomyopathy progression, gaps remain in the specifics of medication initiation and optimization.

This document is an expert opinion statement, addressing a critical gap in cardiac care for Duchenne muscular dystrophy. It provides thorough recommendations for the initiation and titration of cardiac medications based on disease progression and patient response. Recommendations are derived from the expertise of the Advance Cardiac Therapies Improving Outcomes Network and are informed by established guidelines from the American Heart Association, American College of Cardiology, and Duchenne Muscular Dystrophy Care Considerations. These expert-derived recommendations aim to navigate the complexities of Duchenne muscular dystrophy-related cardiac care.

Comprehensive recommendations for initiation, titration, and optimization of critical cardiac medications are provided to address Duchenne muscular dystrophy-associated cardiomyopathy.

The management of Duchenne muscular dystrophy requires a multidisciplinary approach. However, the diversity of healthcare providers involved in Duchenne muscular dystrophy can result in variations in cardiac care, complicating treatment standardization and patient outcomes. The aim of this report is to provide a roadmap for managing Duchenne muscular dystrophy-associated cardiomyopathy, by elucidating timing and dosage nuances crucial for optimal therapeutic efficacy, ultimately improving cardiac outcomes, and improving the quality of life for individuals with Duchenne muscular dystrophy.

This document seeks to establish a standardized framework for cardiac care in Duchenne muscular dystrophy, aiming to improve cardiac prognosis.

Auditory verbal hallucinations (AVHs) in schizophrenia have been suggested to arise from failure of corollary discharge mechanisms to correctly predict and suppress self-initiated inner speech. However, it is unclear whether such dysfunction is related to motor preparation of inner speech during which sensorimotor predictions are formed. The contingent negative variation (CNV) is a slow-going negative event-related potential that occurs prior to executing an action. A recent meta-analysis has revealed a large effect for CNV blunting in schizophrenia. Given that inner speech, similar to overt speech, has been shown to be preceded by a CNV, the present study tested the notion that AVHs are associated with inner speech-specific motor preparation deficits.

The present study aimed to provide a useful framework for directly testing the long-held idea that AVHs may be related to inner speech-specific CNV blunting in patients with schizophrenia. This may hold promise for a reliable biomarker of AVHs.

Hallucinating (n=52) and non-hallucinating (n=45) patients with schizophrenia, along with matched healthy controls (n=42), participated in a novel electroencephalographic (EEG) paradigm. In the Active condition, they were asked to imagine a single phoneme at a cue moment while, precisely at the same time, being presented with an auditory probe. In the Passive condition, they were asked to passively listen to the auditory probes. The amplitude of the CNV preceding the production of inner speech was examined.

Healthy controls showed a larger CNV amplitude (p = .002, d = .50) in the Active compared to the Passive condition, replicating previous results of a CNV preceding inner speech. However, both patient groups did not show a difference between the two conditions (p > .05). Importantly, a repeated measure ANOVA revealed a significant interaction effect (p = .007, ηp2 = .05). Follow-up contrasts showed that healthy controls exhibited a larger CNV amplitude in the Active condition than both the hallucinating (p = .013, d = .52) and non-hallucinating patients (p < .001, d = .88). No difference was found between the two patient groups (p = .320, d = .20).

The results indicated that motor preparation of inner speech in schizophrenia was disrupted. While the production of inner speech resulted in a larger CNV than passive listening in healthy controls, which was indicative of the involvement of motor planning, patients exhibited markedly blunted motor preparatory activity to inner speech. This may reflect dysfunction in the formation of corollary discharges. Interestingly, the deficits did not differ between hallucinating and non-hallucinating patients. Future work is needed to elucidate the specificity of inner speech-specific motor preparation deficits with AVHs. Overall, this study provides evidence in support of atypical inner speech monitoring in schizophrenia.

None Declared

Childhood adversities (CAs) predict heightened risks of posttraumatic stress disorder (PTSD) and major depressive episode (MDE) among people exposed to adult traumatic events. Identifying which CAs put individuals at greatest risk for these adverse posttraumatic neuropsychiatric sequelae (APNS) is important for targeting prevention interventions.

Data came from n = 999 patients ages 18–75 presenting to 29 U.S. emergency departments after a motor vehicle collision (MVC) and followed for 3 months, the amount of time traditionally used to define chronic PTSD, in the Advancing Understanding of Recovery After Trauma (AURORA) study. Six CA types were self-reported at baseline: physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect and bullying. Both dichotomous measures of ever experiencing each CA type and numeric measures of exposure frequency were included in the analysis. Risk ratios (RRs) of these CA measures as well as complex interactions among these measures were examined as predictors of APNS 3 months post-MVC. APNS was defined as meeting self-reported criteria for either PTSD based on the PTSD Checklist for DSM-5 and/or MDE based on the PROMIS Depression Short-Form 8b. We controlled for pre-MVC lifetime histories of PTSD and MDE. We also examined mediating effects through peritraumatic symptoms assessed in the emergency department and PTSD and MDE assessed in 2-week and 8-week follow-up surveys. Analyses were carried out with robust Poisson regression models.

Most participants (90.9%) reported at least rarely having experienced some CA. Ever experiencing each CA other than emotional neglect was univariably associated with 3-month APNS (RRs = 1.31–1.60). Each CA frequency was also univariably associated with 3-month APNS (RRs = 1.65–2.45). In multivariable models, joint associations of CAs with 3-month APNS were additive, with frequency of emotional abuse (RR = 2.03; 95% CI = 1.43–2.87) and bullying (RR = 1.44; 95% CI = 0.99–2.10) being the strongest predictors. Control variable analyses found that these associations were largely explained by pre-MVC histories of PTSD and MDE.

Although individuals who experience frequent emotional abuse and bullying in childhood have a heightened risk of experiencing APNS after an adult MVC, these associations are largely mediated by prior histories of PTSD and MDE.

Many clinical trials leverage real-world data. Typically, these data are manually abstracted from electronic health records (EHRs) and entered into electronic case report forms (CRFs), a time and labor-intensive process that is also error-prone and may miss information. Automated transfer of data from EHRs to eCRFs has the potential to reduce data abstraction and entry burden as well as improve data quality and safety.

We conducted a test of automated EHR-to-CRF data transfer for 40 participants in a clinical trial of hospitalized COVID-19 patients. We determined which coordinator-entered data could be automated from the EHR (coverage), and the frequency with which the values from the automated EHR feed and values entered by study personnel for the actual study matched exactly (concordance).

The automated EHR feed populated 10,081/11,952 (84%) coordinator-completed values. For fields where both the automation and study personnel provided data, the values matched exactly 89% of the time. Highest concordance was for daily lab results (94%), which also required the most personnel resources (30 minutes per participant). In a detailed analysis of 196 instances where personnel and automation entered values differed, both a study coordinator and a data analyst agreed that 152 (78%) instances were a result of data entry error.

An automated EHR feed has the potential to significantly decrease study personnel effort while improving the accuracy of CRF data.

To assess preventability of hospital-onset bacteremia and fungemia (HOB), we developed and evaluated a structured rating guide accounting for intrinsic patient and extrinsic healthcare-related risks.

HOB preventability rating guide was compared against a reference standard expert panel.

A 10-member panel of clinical experts was assembled as the standard of preventability assessment, and 2 physician reviewers applied the rating guide for comparison.

The expert panel independently rated 82 hypothetical HOB scenarios using a 6-point Likert scale collapsed into 3 categories: preventable, uncertain, or not preventable. Consensus was defined as concurrence on the same category among ≥70% experts. Scenarios without consensus were deliberated and followed by a second round of rating.

Two reviewers independently applied the rating guide to adjudicate the same 82 scenarios in 2 rounds, with interim revisions. Interrater reliability was evaluated using the κ (kappa) statistic.

Expert panel consensus criteria were met for 52 scenarios (63%) after 2 rounds.

After 2 rounds, guide-based rating matched expert panel consensus in 40 of 52 (77%) and 39 of 52 (75%) cases for reviewers 1 and 2, respectively. Agreement rates between the 2 reviewers were 84% overall (κ, 0.76; 95% confidence interval [CI], 0.64–0.88]) and 87% (κ, 0.79; 95% CI, 0.65–0.94) for the 52 scenarios with expert consensus.

Preventability ratings of HOB scenarios by 2 reviewers using a rating guide matched expert consensus in most cases with moderately high interreviewer reliability. Although diversity of expert opinions and uncertainty of preventability merit further exploration, this is a step toward standardized assessment of HOB preventability.

Many institutions are attempting to implement patient-reported outcome (PRO) measures. Because PROs often change clinical workflows significantly for patients and providers, implementation choices can have major impact. While various implementation guides exist, a stepwise list of decision points covering the full implementation process and drawing explicitly on a sociotechnical conceptual framework does not exist.

To facilitate real-world implementation of PROs in electronic health records (EHRs) for use in clinical practice, members of the EHR Access to Seamless Integration of Patient-Reported Outcomes Measurement Information System (PROMIS) Consortium developed structured PRO implementation planning tools. Each institution pilot tested the tools. Joint meetings led to the identification of critical sociotechnical success factors.

Three tools were developed and tested: (1) a PRO Planning Guide summarizes the empirical knowledge and guidance about PRO implementation in routine clinical care; (2) a Decision Log allows decision tracking; and (3) an Implementation Plan Template simplifies creation of a sharable implementation plan. Seven lessons learned during implementation underscore the iterative nature of planning and the importance of the clinician champion, as well as the need to understand aims, manage implementation barriers, minimize disruption, provide ample discussion time, and continuously engage key stakeholders.

Highly structured planning tools, informed by a sociotechnical perspective, enabled the construction of clear, clinic-specific plans. By developing and testing three reusable tools (freely available for immediate use), our project addressed the need for consolidated guidance and created new materials for PRO implementation planning. We identified seven important lessons that, while common to technology implementation, are especially critical in PRO implementation.

To identify risk factors of patients placed in airborne infection isolation (AII) for possible pulmonary tuberculosis (TB) to better predict TB diagnosis and allow more judicious use of AII.

Case-control, retrospective study at a single tertiary-care academic medical center. The study included all adult patients admitted from October 1, 2014, through October 31, 2017, who were placed in AII for possible pulmonary TB. Cases were defined as those ultimately diagnosed with pulmonary TB. Controls were defined as those not diagnosed with pulmonary TB. Those with TB diagnosed prior to admission were excluded. In total, 662 admissions (558 patients) were included.

Overall, 15 cases of pulmonary TB were identified (2.7%); of these, 2 were people living with human immunodeficiency virus (HIV; PLWH). Statistical analysis was limited by low case number. Those diagnosed with pulmonary TB were more likely to have been born outside the United States (53% vs 13%; P < .001) and to have had prior positive TB testing, regardless of prior treatment (50% vs 19%; P = .015). A multivariate analysis using non–US birth and prior positive TB testing predicted an 18.2% probability of pulmonary TB diagnosis when present, compared with 1.0% if both factors were not present.

The low number of pulmonary TB cases indicated AII overuse, especially in PLWH, and more judicious use of AII is warranted. High-risk groups, including those born outside the United States and those with prior positive TB testing, should be considered for AII in the appropriate clinical setting.

Mental disorders cause high burden in adolescents, but adolescents often underutilise potentially beneficial treatments. Perceived need for and barriers to care may influence whether adolescents utilise services and which treatments they receive. Adolescents and parents are stakeholders in adolescent mental health care, but their perceptions regarding need for and barriers to care might differ. Understanding patterns of adolescent-parent agreement might help identify gaps in adolescent mental health care.

A nationally representative sample of Australian adolescents aged 13–17 and their parents (N=2310), recruited between 2013–2014, were asked about perceived need for four types of adolescent mental health care (counselling, medication, information and skill training) and barriers to care. Perceived need was categorised as fully met, partially met, unmet, or no need. Cohen's kappa was used to assess adolescent-parent agreement. Multinomial logistic regressions were used to model variables associated with patterns of agreement.

Almost half (46.5% (s.e.=1.21)) of either adolescents or parents reported a perceived need for any type of care. For both groups, perceived need was greatest for counselling and lowest for medication. Identified needs were fully met for a third of adolescents. Adolescent-parent agreement on perceived need was fair (kappa=0.25 (s.e.=0.01)), but poor regarding the extent to which needs were met (kappa = −0.10 (s.e.=0.02)). The lack of parental knowledge about adolescents' feelings was positively associated with adolescent-parent agreement that needs were partially met or unmet and disagreement about perceived need, compared to agreement that needs were fully met (relative risk ratio (RRR)=1.91 (95% CI=1.19–3.04) to RRR=4.69 (95% CI=2.38–9.28)). Having a probable disorder was positively associated with adolescent-parent agreement that needs were partially met or unmet (RRR=2.86 (95% CI=1.46–5.61)), and negatively with adolescent-parent disagreement on perceived need (RRR=0.50 (95% CI=0.30–0.82)). Adolescents reported most frequently attitudinal barriers to care (e.g. self-reliance: 55.1% (s.e.=2.39)); parents most frequently reported that their child refused help (38.7% (s.e.=2.69)). Adolescent-parent agreement was poor for attitudinal (kappa = −0.03 (s.e.=0.06)) and slight for structural barriers (kappa=0.02 (s.e.=0.09)).

There are gaps in the extent to which adolescent mental health care is meeting the needs of adolescents and their parents. It seems important to align adolescents' and parents' needs at the beginning and throughout treatment and to improve communication between adolescents and their parents. Both might provide opportunities to increase the likelihood that needs will be fully met. Campaigns directed towards adolescents and parents need to address different barriers to care. For adolescents, attitudinal barriers such as stigma and mental health literacy require attention.

To enhance enrollment into randomized clinical trials (RCTs), we proposed electronic health record-based clinical decision support for patient–clinician shared decision-making about care and RCT enrollment, based on “mathematical equipoise.”

As an example, we created the Knee Osteoarthritis Mathematical Equipoise Tool (KOMET) to determine the presence of patient-specific equipoise between treatments for the choice between total knee replacement (TKR) and nonsurgical treatment of advanced knee osteoarthritis.

With input from patients and clinicians about important pain and physical function treatment outcomes, we created a database from non-RCT sources of knee osteoarthritis outcomes. We then developed multivariable linear regression models that predict 1-year individual-patient knee pain and physical function outcomes for TKR and for nonsurgical treatment. These predictions allowed detecting mathematical equipoise between these two options for patients eligible for TKR. Decision support software was developed to graphically illustrate, for a given patient, the degree of overlap of pain and functional outcomes between the treatments and was pilot tested for usability, responsiveness, and as support for shared decision-making.

The KOMET predictive regression model for knee pain had four patient-specific variables, and an r2 value of 0.32, and the model for physical functioning included six patient-specific variables, and an r2 of 0.34. These models were incorporated into prototype KOMET decision support software and pilot tested in clinics, and were generally well received.

Use of predictive models and mathematical equipoise may help discern patient-specific equipoise to support shared decision-making for selecting between alternative treatments and considering enrollment into an RCT.

To ascertain opinions regarding etiology and preventability of hospital-onset bacteremia and fungemia (HOB) and perspectives on HOB as a potential outcome measure reflecting quality of infection prevention and hospital care.

Cross-sectional survey.

Hospital epidemiologists and infection preventionist members of the Society for Healthcare Epidemiology of America (SHEA) Research Network.

A web-based, multiple-choice survey was administered via the SHEA Research Network to 133 hospitals.

A total of 89 surveys were completed (67% response rate). Overall, 60% of respondents defined HOB as a positive blood culture on or after hospital day 3. Central line-associated bloodstream infections and intra-abdominal infections were perceived as the most frequent etiologies. Moreover, 61% thought that most HOB events are preventable, and 54% viewed HOB as a measure reflecting a hospital’s quality of care. Also, 29% of respondents’ hospitals already collect HOB data for internal purposes. Given a choice to publicly report central-line–associated bloodstream infections (CLABSIs) and/or HOB, 57% favored reporting either HOB alone (22%) or in addition to CLABSI (35%) and 34% favored CLABSI alone.

Among the majority of SHEA Research Network respondents, HOB is perceived as preventable, reflective of quality of care, and potentially acceptable as a publicly reported quality metric. Further studies on HOB are needed, including validation as a quality measure, assessment of risk adjustment, and formation of evidence-based bundles and toolkits to facilitate measurement and improvement of HOB rates.