Inequities in Atrial Fibrillation Trials: An Analysis of Participant Race, Ethnicity, and Sex Over Time.

BACKGROUND: Despite the importance of racial and ethnic representation in clinical trials, limited data exist regarding the enrollment trends of these groups in atrial fibrillation (AF) trials over time. OBJECTIVES: The purpose of this study is to examine the characteristics of contemporary AF clinical trials and evaluate their association with race and ethnicity over time. METHODS: We performed a systematic search of all completed AF trials registered in ClinicalTrials.gov between conception to December 31, 2023 and manually extracted composition of race/ethnicity. We stratified trials by study characteristics, including impact factor, publication status, funding source, and location. We calculated the participation prevalence ratio (PPR) by dividing the percentage of non-White participants by the percentage of non-White participants among the disease population (PPR 0.8-1.2 suggests proportional representation) over time. RESULTS: We identified 277 completed AF trials encompassing a total of 1,933,441 adults, with a median proportion of non-White at 12% (IQR: 6-27), 121 (43.7%) device-focused, and 184 (66.4%) funded by industry. Only 36.1% of trials reported comprehensive race information. Overall, non-White participants were underrepresented (PPR = 0.511; P < 0.001), including Black (PPR = 0.263) and Hispanic (PPR = 0.337) participants. The proportion of non-White participants did not change significantly between 2000 and 2023 (11% vs 9%; P = 0.343). CONCLUSION: Despite greater awareness, race/ethnicity reporting and representation of non-White groups in AF clinical trials are poor and have not improved significantly over time. These findings demand additional recruitment efforts and novel recruitment policies to ensure adequate representation of these demographic subgroups in future AF clinical trials.

Who are we missing? Language exclusivity of patient-reported outcomes in atrial fibrillation clinical trials.

INTRODUCTION: Patient-reported outcomes (PROs) are increasingly used to evaluate quality of life (QoL) in Atrial Fibrillation (AF) patients, providing crucial insights in clinical trials. This study examines the frequency of PRO use in AF trials and the linguistic accessibility of AF-specific PROs. BACKGROUND: As the United States becomes more multilingual, ensuring PROs are available in various languages is vital. The number of people speaking a language other than English at home has tripled from 23.1 million in 1980 to 67.8 million in 2019. This diversity necessitates the availability of PROs in multiple languages for inclusive clinical assessments. METHODS: We queried ClinicalTrials.gov for all US interventional AF trials up to November 28, 2023, reviewing each for PRO usage as primary or secondary outcomes. We identified the five most common AF-specific and generic PROs, extracting their available translations and original languages from published sources. RESULTS: Of 233 identified trials, 191 had associated publications, with 180 (94.2%) conducted solely in English. Only one trial (0.4%) used an AF-specific PRO as a primary outcome, compared to four (1.7%) with a generic PRO. Ten trials (4.3%) used AF-specific PROs as secondary endpoints, versus 22 (9.4%) using generic PROs. AF-specific PROs had significantly fewer translations than generic PROs (11.2 vs. 148.8; p < .001). The AF Effect on Quality-of-Life (AFEQT) was available in 24 languages, with limited translations in commonly spoken US languages like Arabic and Asian languages. CONCLUSION: The limited availability of AF-specific PRO translations highlights a barrier to inclusive AF clinical trials. Expanding translations for AF-specific PROs is crucial for equitable QoL assessments.

Heterogeneity in Antidepressant Treatment and Major Depressive Disorder Outcomes Among Clinicians.

Importance: While abundant work has examined patient-level differences in antidepressant treatment outcomes, little is known about the extent of clinician-level differences. Understanding these differences may be important in the development of risk models, precision treatment strategies, and more efficient systems of care. Objective: To characterize differences between outpatient clinicians in treatment selection and outcomes for their patients diagnosed with major depressive disorder across academic medical centers, community hospitals, and affiliated clinics. Design, Setting, and Participants: This was a longitudinal cohort study using data derived from electronic health records at 2 large academic medical centers and 6 community hospitals, and their affiliated outpatient networks, in eastern Massachusetts. Participants were deidentified clinicians who billed at least 10 International Classification of Diseases, Ninth Revision (ICD-9) or Tenth Revision (ICD-10) diagnoses of major depressive disorder per year between 2008 and 2022. Data analysis occurred between September 2023 and January 2024. Main Outcomes and Measures: Heterogeneity of prescribing, defined as the number of distinct antidepressants accounting for 75% of prescriptions by a given clinician; proportion of patients who did not return for follow-up after an index prescription; and proportion of patients receiving stable, ongoing antidepressant treatment. Results: Among 11 934 clinicians treating major depressive disorder, unsupervised learning identified 10 distinct clusters on the basis of ICD codes, corresponding to outpatient psychiatry as well as oncology, obstetrics, and primary care. Between these clusters, substantial variability was identified in the proportion of selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and tricyclic antidepressants prescribed, as well as in the number of distinct antidepressants prescribed. Variability was also detected between clinician clusters in loss to follow-up and achievement of stable treatment, with the former ranging from 27% to 69% and the latter from 22% to 42%. Clinician clusters were significantly associated with treatment outcomes. Conclusions and Relevance: Groups of clinicians treating individuals diagnosed with major depressive disorder exhibit marked differences in prescribing patterns as well as longitudinal patient outcomes defined by electronic health records. Incorporating these group identifiers yielded similar prediction to more complex models incorporating individual codes, suggesting the importance of considering treatment context in efforts at risk stratification.

Dimensional measures of psychopathology in children and adolescents using large language models.

BACKGROUND: To enable greater use of NIMH Research Domain Criteria (RDoC) in real-world settings, we applied large language models to estimate dimensional psychopathology from narrative clinical notes. METHODS: We conducted a cohort study using health records from individuals age 18 years or younger evaluated in the psychiatric emergency department of a large academic medical center between November 2008 and March 2015. Outcomes were hospital admission and length of emergency department stay. RDoC domains were estimated using a HIPAA-compliant large language model (gpt-4-1106-preview), and compared to a previously-validated token-based approach. RESULTS: The cohort included 3,059 individuals (median age 16 (25%-75% 13-18); 1580 (52%) female, 1479 (48%) male; 105 (3.4%) identified as Asian, 329 (11%) as Black, 288 (9.4%) Hispanic, 474 (15%) as another race, and 1863 (61%) as white), of whom 1695 (55%) were admitted. Correlation between LLM-extracted RDoC scores and the token-based scores ranged from small to medium by Kendall's Tau (0.14-0.22). In logistic regression models adjusted for sociodemographic and clinical features, admission likelihood was associated with greater scores on all domains, with the exception of sensorimotor, which was inversely associated (p<.001 for all adjusted associations). Tests for bias suggested modest but statistically significant differences in positive valence scores by race (p<.05 for Asian, Hispanic, and Black individuals). CONCLUSION: A large language model extracted estimates of 6 RDoC domains in an explainable manner, which were associated with clinical outcomes. This approach can contribute to a new generation of prediction models or biological investigations based on dimensional psychopathology.

Transcranial Direct Current Stimulation to Ameliorate Post-Stroke Cognitive Impairment.

Post-stroke cognitive impairment is a common and disabling condition with few effective therapeutic options. After stroke, neural reorganization and other neuroplastic processes occur in response to ischemic injury, which can result in clinical improvement through spontaneous recovery. Neuromodulation through transcranial direct current stimulation (tDCS) is a promising intervention to augment underlying neuroplasticity in order to improve cognitive function. This form of neuromodulation leverages mechanisms of neuroplasticity post-stroke to optimize neural reorganization and improve function. In this review, we summarize the current state of cognitive neurorehabilitation post-stroke, the practical features of tDCS, its uses in stroke-related cognitive impairment across cognitive domains, and special considerations for the use of tDCS in the post-stroke patient population.

Multistate, Ultrathin, Back-End-of-Line-Compatible AlScN Ferroelectric Diodes.

The growth in data generation necessitates efficient data processing technologies to address the von Neumann bottleneck in conventional computer architecture. Memory-driven computing, which integrates nonvolatile memory (NVM) devices in a 3D stack, is gaining attention, with CMOS back-end-of-line (BEOL)-compatible ferroelectric (FE) diodes being ideal due to their two-terminal design and inherently selector-free nature, facilitating high-density crossbar arrays. Here, we demonstrate BEOL-compatible, high-performance FE diodes scaled to 5, 10, and 20 nm FE Al0.72Sc0.28N/Al0.64Sc0.36N films. Through interlayer (IL) engineering, we show substantial improvements in the on/off ratios (>166 times) and rectification ratios (>176 times) in these scaled devices. These characteristics also enable 5-bit multistate operation with a stable retention. We also experimentally and theoretically demonstrate the counterintuitive result that the inclusion of an IL can lead to a decrease in the ferroelectric switching voltage of the device. An in-depth analysis into the device transport mechanisms is performed, and our compact model aligns seamlessly with the experimental results. Our results suggest the possibility of using scaled AlxSc1-xN FE diodes for high-performance, low-power, embedded NVM.

Hofbauer cells and fetal brain microglia share transcriptional profiles and responses to maternal diet-induced obesity.

Maternal immune activation is associated with adverse offspring neurodevelopmental outcomes, many mediated by in utero microglial programming. As microglia remain inaccessible throughout development, identification of noninvasive biomarkers reflecting fetal brain microglial programming could permit screening and intervention. We used lineage tracing to demonstrate the shared ontogeny between fetal brain macrophages (microglia) and fetal placental macrophages (Hofbauer cells) in a mouse model of maternal diet-induced obesity, and single-cell RNA-seq to demonstrate shared transcriptional programs. Comparison with human datasets demonstrated conservation of placental resident macrophage signatures between mice and humans. Single-cell RNA-seq identified common alterations in fetal microglial and Hofbauer cell gene expression induced by maternal obesity, as well as sex differences in these alterations. We propose that Hofbauer cells, which are easily accessible at birth, provide insights into fetal brain microglial programs and may facilitate the early identification of offspring vulnerable to neurodevelopmental disorders.

Chemically Driven Sintering of Colloidal Cu Nanocrystals for Multiscale Electronic and Optical Devices.

Emerging applications of Internet of Things (IoT) technologies in smart health, home, and city, in agriculture and environmental monitoring, and in transportation and manufacturing require materials and devices with engineered physical properties that can be manufactured by low-cost and scalable methods, support flexible forms, and are biocompatible and biodegradable. Here, we report the fabrication and device integration of low-cost and biocompatible/biodegradable colloidal Cu nanocrystal (NC) films through room temperature, solution-based deposition, and sintering, achieved via chemical exchange of NC surface ligands. Treatment of organic-ligand capped Cu NC films with solutions of shorter, environmentally benign, and noncorrosive inorganic reagents, namely, SCN- and Cl-, effectively removes the organic ligands, drives NC grain growth, and limits film oxidation. We investigate the mechanism of this chemically driven sintering by systemically varying the Cu NC size, ligand reagent, and ligand treatment time and follow the evolution of their structure and electrical and optical properties. Cl--treated, 4.5 nm diameter Cu NC films yield the lowest DC resistivity, only 3.2 times that of bulk Cu, and metal-like dielectric functions at optical frequencies. We exploit the high conductivity of these chemically sintered Cu NC films and, in combination with photo- and nanoimprint-lithography, pattern multiscale structures to achieve high-Q radio frequency (RF) capacitive sensors and near-infrared (NIR) resonant optical metasurfaces.

Nonvolatile Control of Valley Polarized Emission in 2D WSe2-AlScN Heterostructures.

Achieving robust and electrically controlled valley polarization in monolayer transition metal dichalcogenides (ML-TMDs) is a frontier challenge for realistic valleytronic applications. Theoretical investigations show that the integration of 2D materials with ferroelectrics is a promising strategy; however, an experimental demonstration has remained elusive. Here, we fabricate ferroelectric field-effect transistors using a ML-WSe2 channel and an Al0.68Sc0.32N (AlScN) ferroelectric dielectric and experimentally demonstrate efficient tuning as well as non-volatile control of valley polarization. We measure a large array of transistors and obtain a maximum valley polarization of ∼27% at 80 K with stable retention up to 5400 s. The enhancement in the valley polarization is ascribed to the efficient exciton-to-trion (X-T) conversion and its coupling with an out-of-plane electric field, viz., the quantum-confined Stark effect. This changes the valley depolarization pathway from strong exchange interactions to slow spin-flip intervalley scattering. Our research demonstrates a promising approach for achieving non-volatile control over valley polarization for practical valleytronic device applications.

Maternal SARS-CoV-2 impacts fetal placental macrophage programs and placenta-derived microglial models of neurodevelopment.

BACKGROUND: The SARS-CoV-2 virus activates maternal and placental immune responses. Such activation in the setting of other infections during pregnancy is known to impact fetal brain development. The effects of maternal immune activation on neurodevelopment are mediated at least in part by fetal brain microglia. However, microglia are inaccessible for direct analysis, and there are no validated non-invasive surrogate models to evaluate in utero microglial priming and function. We have previously demonstrated shared transcriptional programs between microglia and Hofbauer cells (HBCs, or fetal placental macrophages) in mouse models. METHODS AND RESULTS: We assessed the impact of maternal SARS-CoV-2 on HBCs isolated from 24 term placentas (N = 10 SARS-CoV-2 positive cases, 14 negative controls). Using single-cell RNA-sequencing, we demonstrated that HBC subpopulations exhibit distinct cellular programs, with specific subpopulations differentially impacted by SARS-CoV-2. Assessment of differentially expressed genes implied impaired phagocytosis, a key function of both HBCs and microglia, in some subclusters. Leveraging previously validated models of microglial synaptic pruning, we showed that HBCs isolated from placentas of SARS-CoV-2 positive pregnancies can be transdifferentiated into microglia-like cells (HBC-iMGs), with impaired synaptic pruning behavior compared to HBC models from negative controls. CONCLUSION: These findings suggest that HBCs isolated at birth can be used to create personalized cellular models of offspring microglial programming.

Stratifying Risk for Postpartum Depression at Time of Hospital Discharge.

Objective: Postpartum depression (PPD) represents a major contributor to postpartum morbidity and mortality. Beyond efforts at routine screening, risk stratification models could enable more targeted interventions in settings with limited resources. Thus, we aimed to develop and estimate the performance of a generalizable risk stratification model for PPD in patients without a history of depression using information collected as part of routine clinical care. Methods: We performed a retrospective cohort study of all individuals who delivered between 2017 and 2022 in one of two large academic medical centers and six community hospitals. An elastic net model was constructed and externally validated to predict PPD using sociodemographic factors, medical history, and prenatal depression screening information, all of which was known before discharge from the delivery hospitalization. Results: The cohort included 29,168 individuals; 2,703 (9.3%) met at least one criterion for postpartum depression in the 6 months following delivery. In the external validation data, the model had good discrimination and remained well-calibrated: area under the receiver operating characteristic curve 0.721 (95% CI: 0.707-0.734), Brier calibration score 0.088 (95% CI: 0.084 - 0.092). At a specificity of 90%, the positive predictive value was 28.0% (95% CI: 26.0-30.1%), and the negative predictive value was 92.2% (95% CI: 91.8-92.7%). Conclusions: These findings demonstrate that a simple machine-learning model can be used to stratify the risk for PPD before delivery hospitalization discharge. This tool could help identify patients within a practice at the highest risk and facilitate individualized postpartum care planning regarding the prevention of, screening for, and management of PPD at the start of the postpartum period and potentially the onset of symptoms.

Genome-Wide Association Study of Treatment-Resistant Depression: Shared Biology With Metabolic Traits.

OBJECTIVE: Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD. METHODS: Using receipt of electroconvulsive therapy (ECT) as a surrogate for TRD, the authors applied standard machine learning methods to electronic health record data to derive predicted probabilities of receiving ECT. These probabilities were then applied as a quantitative trait in a genome-wide association study of 154,433 genotyped patients across four large biobanks. RESULTS: Heritability estimates ranged from 2% to 4.2%, and significant genetic overlap was observed with cognition, attention deficit hyperactivity disorder, schizophrenia, alcohol and smoking traits, and body mass index. Two genome-wide significant loci were identified, both previously implicated in metabolic traits, suggesting shared biology and potential pharmacological implications. CONCLUSIONS: This work provides support for the utility of estimation of disease probability for genomic investigation and provides insights into the genetic architecture and biology of TRD.

Outcomes and care quality metrics for people living with rheumatic heart disease and atrial fibrillation in Uganda.

Background: Atrial fibrillation (AF) is a common complication of rheumatic heart disease (RHD) and is challenging to treat in lower-resourced settings in which RHD remains endemic. Objective: We characterized demographics, treatment outcomes, and factors leading to care retention for participants with RHD and AF in Uganda. Methods: We conducted a retrospective analysis of the Uganda national RHD registry between June 2009 and May 2018. Participants with AF or atrial flutter were included. Demographics, survival, and care metrics were compared with participants without AF. Multivariable logistic regression was used to identify factors associated with retention in care among participants with AF. Results: A total of 1530 participants with RHD were analyzed and 293 (19%) had AF. The median age was 24 (interquartile range 14-38) years. Mortality was similar in both groups (adjusted hazard ratio 1.183, P = .77) over a median follow-up of 203 (interquartile range 98-275) days. A total of 79% of AF participants were prescribed anticoagulation, and 43% were aware of their target international normalized ratio. Retention in care was higher in participants with AF (18% vs 12%, P < .01). Factors associated with decreased retention in care include New York Heart Association functional class III/IV (adjusted odds ratio [OR] 0.48, 95% confidence interval [CI] 0.30-0.76) and distance to nearest health center (adjusted OR 0.94, 95% CI 0.90-0.99). Anticoagulation prescription was associated with enhanced care retention (adjusted OR 1.86, 95% CI 1.24-2.79). Conclusion: Participants with RHD and AF in Uganda do not experience higher mortality than those without AF. Anticoagulation prescription rates are high. Although retention in care is poor among RHD participants, those with concurrent AF are more likely to be retained.

Promoting Growth in Behavioral Neurology: A Path Forward.

Behavioral neurology & neuropsychiatry (BNNP) is a field that seeks to understand brain-behavior relationships, including fundamental brain organization principles and the many ways that brain structures and connectivity can be disrupted, leading to abnormalities of behavior, cognition, emotion, perception, and social cognition. In North America, BNNP has existed as an integrated subspecialty through the United Council for Neurologic Subspecialties since 2006. Nonetheless, the number of behavioral neurologists across academic medical centers and community settings is not keeping pace with increasing clinical and research demand. In this commentary, we provide a brief history of BNNP followed by an outline of the current challenges and opportunities for BNNP from the behavioral neurologist's perspective across clinical, research, and educational spheres. We provide a practical guide for promoting BNNP and addressing the shortage of behavioral neurologists to facilitate the continued growth and development of the subspecialty. We also urge a greater commitment to recruit trainees from diverse backgrounds so as to dismantle persistent obstacles that hinder inclusivity in BNNP-efforts that will further enhance the growth and impact of the subspecialty. With rapidly expanding diagnostic and therapeutic approaches across a range of conditions at the intersection of neurology and psychiatry, BNNP is well positioned to attract new trainees and expand its reach across clinical, research, and educational activities.

Optimal timing of hip and knee arthroplasty after bariatric surgery: A systematic review.

Background: Obesity is a risk factor for the development of osteoarthritis and contributes to the increasing demand for total joint arthroplasty (TJA). Because a lower preoperative weight decreases the risk of complications after TJA, and because bariatric surgery (BS) can reduce weight and comorbidity burden, orthopedic surgeons often recommend BS prior to TJA in patients with obesity. However, the optimal timing of TJA after BS in terms of complications, revisions and dislocations is unknown. Methods: PubMed, Embase and Cochrane CENTRAL databases were systematically searched for any type of study reporting rates of complications, revisions and dislocations in patients who had TJA after BS. The included studies' quality was assessed using the Newcastle-Ottawa Scale. Results: Out of the 16 studies eligible for review, eight registry-based retrospective studies of high to moderate quality compared different time periods between BS and TJA and overall their results suggest little differences in complication rates. The remaining eight retrospective studies evaluated only one time period and had moderate to poor quality. Overall, there were no clear differences in outcomes after TJA for the different time frames between BS and TJA. Conclusion: The results of this systematic review suggest that there is limited and insufficient high-quality evidence to determine the optimal timing of TJA after BS in terms of the rates of complications, revisions and dislocations. Given this lack of evidence, timing of TJA after BS will have to be decided by weighing the individual patients' risk factors against the expected benefits of TJA.

Frequency tunable magnetostatic wave filters with zero static power magnetic biasing circuitry.

A single tunable filter simplifies complexity, reduces insertion loss, and minimizes size compared to frequency switchable filter banks commonly used for radio frequency (RF) band selection. Magnetostatic wave (MSW) filters stand out for their wide, continuous frequency tuning and high-quality factor. However, MSW filters employing electromagnets for tuning consume excessive power and space, unsuitable for consumer wireless applications. Here, we demonstrate miniature and high selectivity MSW tunable filters with zero static power consumption, occupying less than 2 cc. The center frequency is continuously tunable from 3.4 GHz to 11.1 GHz via current pulses of sub-millisecond duration applied to a small and nonvolatile magnetic bias assembly. This assembly is limited in the area over which it can achieve a large and uniform magnetic field, necessitating filters realized from small resonant cavities micromachined in thin films of Yttrium Iron Garnet. Filter insertion loss of 3.2 dB to 5.1 dB and out-of-band third order input intercept point greater than 41 dBm are achieved. The filter's broad frequency range, compact size, low insertion loss, high out-of-band linearity, and zero static power consumption are essential for protecting RF transceivers from interference, thus facilitating their use in mobile applications like IoT and 6 G networks.

Identifying data-driven subtypes of major depressive disorder with electronic health records.

BACKGROUND: Efforts to reduce the heterogeneity of major depressive disorder (MDD) by identifying subtypes have not yet facilitated treatment personalization or investigation of biology, so novel approaches merit consideration. METHODS: We utilized electronic health records drawn from 2 academic medical centers and affiliated health systems in Massachusetts to identify data-driven subtypes of MDD, characterizing sociodemographic features, comorbid diagnoses, and treatment patterns. We applied Latent Dirichlet Allocation (LDA) to summarize diagnostic codes followed by agglomerative clustering to define patient subgroups. RESULTS: Among 136,371 patients (95,034 women [70 %]; 41,337 men [30 %]; mean [SD] age, 47.0 [14.0] years), the 15 putative MDD subtypes were characterized by comorbidities and distinct patterns in medication use. There was substantial variation in rates of selective serotonin reuptake inhibitor (SSRI) use (from a low of 62 % to a high of 78 %) and selective norepinephrine reuptake inhibitor (SNRI) use (from 4 % to 21 %). LIMITATIONS: Electronic health records lack reliable symptom-level data, so we cannot examine the extent to which subtypes might differ in clinical presentation or symptom dimensions. CONCLUSION: These data-driven subtypes, drawing on representative clinical cohorts, merit further investigation for their utility in identifying more homogeneous patient populations for basic as well as clinical investigation.

Psychiatric Symptoms, Treatment Uptake, and Barriers to Mental Health Care Among US Adults With Post-COVID-19 Condition.

Importance: Psychiatric symptoms are reportedly common among adults with post-COVID-19 condition (PCC). However, nationally representative data regarding symptom prevalence, treatment uptake, and barriers to care are needed to inform the development of care models. Objectives: To evaluate the prevalence of psychiatric symptoms in US adults with PCC compared with those without PCC and assess treatment uptake and cost-related barriers to treatment. Design, Setting, and Participants: Data from the 2022 National Health Interview Survey (NHIS), a nationally representative US cross-sectional survey, were analyzed between October 2023 and February 2024. Exposure: Current PCC, defined as new symptoms following SARS-CoV-2 infection lasting more than 3 months and ongoing at the time of interview. Main Outcomes and Measures: Depression symptoms were evaluated by the Patient Health Questionnaire-8 and anxiety symptoms were assessed using the General Anxiety Disorder-7 instrument. Participants were classified as having received treatment if they received mental health counseling or therapy or medications for mental health. Sleep difficulties, cognitive difficulties, disabling fatigue, and cost-related barriers were assessed from additional NHIS questions. Results: Of the 25 122 participants representing approximately 231 million US adults (median [IQR] age, 46 [32-61] years; 49.8% male and 50.2% female participants), a weighted prevalence (wPr) of 3.4% (95% CI, 3.1%-3.6%) had current PCC. Compared with other US adults, participants with current PCC were more likely to have depression symptoms (wPr, 16.8% vs 7.1%; adjusted odds ratio [AOR], 1.96; 95% CI, 1.51-2.55), anxiety symptoms (wPr, 16.7% vs 6.3%; AOR, 2.21; 95% CI, 1.53-3.19), sleep difficulties (wPr, 41.5% vs 22.7%; AOR 1.95; 95% CI, 1.65-2.29), cognitive difficulties (wPr, 35.0% vs 19.5%; AOR, 2.04; 95% CI, 1.66-2.50), and disabling fatigue (wPr, 4.0% vs 1.6%; AOR, 1.85; 95% CI, 1.20-2.86). Among participants who had depression or anxiety symptoms, those with PCC had a similar likelihood of not having received treatment (wPr, 28.2% vs 34.9%; AOR, 1.02; 95% CI, 0.66-1.57). However, participants with current PCC were more likely to report a cost-related barrier to accessing mental health counseling or therapy (wPr, 37.2% vs 23.3%; AOR, 2.05; 95% CI, 1.40-2.98). Conclusions and Relevance: The findings of this study suggest that people with PCC have a higher prevalence of psychiatric symptoms than other adults but are more likely to experience cost-related barriers to accessing therapy. Care pathways for PCC should consider prioritizing mental health screening and affordable treatment.