Diagnostic Identification of Acute Brain Dysfunction in Pediatric Sepsis and Septic Shock in the Electronic Health Record: A Comparison of Four Definitions in a Reference Dataset.

OBJECTIVES: Acute brain dysfunction (ABD) in pediatric sepsis has a prevalence of 20%, but can be difficult to identify. Our previously validated ABD computational phenotype (CP ABD ) used variables obtained from the electronic health record indicative of clinician concern for acute neurologic or behavioral change. We tested whether the CP ABD has better diagnostic performance to identify confirmed ABD than other definitions using the Glasgow Coma Scale or delirium scores. DESIGN: Diagnostic testing in a curated cohort of pediatric sepsis/septic shock patients. SETTING: Quaternary freestanding children's hospital. SUBJECTS: The test dataset comprised 527 children with sepsis/septic shock managed between 2011 and 2021 with a prevalence (pretest probability) of confirmed ABD of 30% (159/527). MEASUREMENTS AND MAIN RESULTS: CP ABD was based on use of neuroimaging, electroencephalogram, and/or administration of new antipsychotic medication. We compared the performance of the CP ABD with three GCS/delirium-based definitions of ABD-Proulx et al, International Pediatric Sepsis Consensus Conference, and Pediatric Organ Dysfunction Information Update Mandate. The posttest probability of identifying ABD was highest in CP ABD (0.84) compared with other definitions. CP ABD also had the highest sensitivity (83%; 95% CI, 76-89%) and specificity (93%; 95% CI, 90-96%). The false discovery rate was lowest in CP ABD (1-in-6) as was the false omission rate (1-in-14). Finally, the prevalence threshold for the definitions varied, with the CP ABD being the definition closest to 20%. CONCLUSIONS: In our curated dataset of pediatric sepsis/septic shock, CP ABD had favorable characteristics to identify confirmed ABD compared with GCS/delirium-based definitions. The CP ABD can be used to further study the impact of ABD in studies using large electronic health datasets.

Participant Recruitment From Low- and Middle-Income Countries for Pivotal Trials of Drugs Approved by the U.S. Food and Drug Administration : A Cross-Sectional Analysis.

BACKGROUND: Many participants in clinical trials supporting U.S. Food and Drug Administration (FDA) drug approvals are recruited from outside the United States, including from low- and middle-income countries (LMICs). Where participants are recruited for pivotal trials has implications for ethical research conduct and generalizability. OBJECTIVE: To describe LMIC recruitment for pivotal trials of newly approved drugs for cancer, neurologic disease, and cardiovascular disease. DESIGN: Cross-sectional analysis. SETTING: Pivotal trials of new cancer, cardiovascular, and neurologic drugs approved from 2012 to 2019 matched to ClinicalTrials.gov, FDA records, and publications. MEASUREMENTS: Host countries and available per country enrollments were extracted. The primary end point was the proportion of pivotal trials enrolling participants in LMICs. The secondary end point was the proportion of pivotal trial participants contributed by LMICs for each indication area. RESULTS: Data were obtained from 66 new drugs and 144 pivotal clinical trials. All cardiovascular approvals (12 drugs, 29 trials) and neurologic approvals (26 drugs, 54 trials) were analyzed, as well as a random sample of cancer approvals (28 of 85 drugs [33%]) matched to their pivotal trials (61 of 210 trials [29%]). Among the trials, 56% in cancer, 79% in cardiovascular disease, and 56% in neurology recruited from an LMIC. For multicountry trials, country-level enrollment figures were not available for 71 trials (55%). For those reporting per country enrollment, the percentage of participants recruited from LMICs was 8% for cancer trials, 36% for cardiovascular trials, and 17% for neurology trials. LIMITATIONS: The study was limited to FDA-approved drugs in 3 areas, including a sample of cancer drugs. Pivotal trials of nonapproved drugs or drugs for other indications were not captured. CONCLUSION: Most pivotal trials for FDA-approved drugs recruit from LMICs. Publications and FDA documents generally do not provide country-level data on recruitment. PRIMARY FUNDING SOURCE: None.

Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.

BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualitatively. Advances in machine learning (ML) image processing provide a means of identifying "hidden" features in pictures. This pilot study trains a convolutional neural network (CNN) to predict gene expression based on digital photographs of wounds in a canine model of volumetric muscle loss (VML). MATERIALS AND METHODS: Images of volumetric muscle loss injuries and tissue biopsies were obtained in a canine model of VML. A CNN was trained to regress gene expression values as a function of the extracted image segment (color and spatial distribution). Performance of the CNN was assessed in a held-back test set of images using Mean Absolute Percentage Error (MAPE). RESULTS: The CNN was able to predict the gene expression of certain genes based on digital images, with a MAPE ranging from ∼10% to ∼30%, indicating the presence and identification of distinct, and identifiable patterns in gene expression throughout the wound. CONCLUSIONS: These initial results suggest promise for further research regarding this novel use of ML regression on medical images. Specifically, the use of CNNs to determine the mechanistic biological state of a VML wound could aid both the design of future mechanistic interventions and the design of trials to test those therapies. Future work will expand the CNN training and/or test set, with potential expansion to predicting functional gene modules.

Low-frequency stimulation of a fiber tract in bilateral temporal lobe epilepsy.

OBJECTIVE: Pharmacoresistant bilateral mesial temporal lobe epilepsy often implies poor resective surgical candidacy. Low-frequency stimulation of a fiber tract connected to bilateral hippocampi, the fornicodorsocommissural tract, has been shown to be safe and efficacious in reducing seizures in a previous short-term study. Here, we report a single-blinded, within-subject control, long-term deep-brain stimulation trial of low-frequency stimulation of the fornicodorsocommissural tract in bilateral mesial temporal lobe epilepsy. Outcomes of interest included safety with respect to verbal memory scores and reduction of seizure frequency. METHODS: Our enrollment goal was 16 adult subjects to be randomized to 2-Hz or 5-Hz low-frequency stimulation of the fornicodorsocommissural tract starting at 2 mA. The study design consisted of four two-month blocks of stimulation with a 50%-duty cycle, alternating with two-month blocks of no stimulation. RESULTS: We terminated the study after enrollment of five subjects due to slow accrual. Fornicodorsocommissural tract stimulation elicited bilateral hippocampal evoked responses in all subjects. Three subjects underwent implantation of pulse generators and long-term low-frequency stimulation with mean monthly seizures of 3.14 ±â€¯2.67 (median 3.0 [IQR 1-4.0]) during stimulation-off blocks, compared with 0.96 ±â€¯1.23 (median 1.0 [IQR 0-1.0]) during stimulation-on blocks (p = 0.0005) during the blinded phase. Generalized Estimating Equations showed that low-frequency stimulation reduced monthly seizure-frequency by 0.71 per mA (p < 0.001). Verbal memory scores were stable with no psychiatric complications or other adverse events. SIGNIFICANCE: The results demonstrate feasibility of stimulating both hippocampi using a single deep-brain stimulation electrode in the fornicodorsocommissural tract, efficacy of low-frequency stimulation in reducing seizures, and safety as regards verbal memory.

Validation of a Computational Phenotype to Identify Acute Brain Dysfunction in Pediatric Sepsis.

OBJECTIVES: To validate a computational phenotype that identifies acute brain dysfunction (ABD) based on clinician concern for neurologic or behavioral changes in pediatric sepsis. DESIGN: Retrospective observational study. SETTING: Single academic children's hospital. PATIENTS: Four thousand two hundred eighty-nine index sepsis episodes. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: An existing computational phenotype of ABD was optimized to include routinely collected variables indicative of clinician concern for acute neurologic or behavioral change (completion of CT or MRI, electroencephalogram, or new antipsychotic administration). First, the computational phenotype was compared with an ABD reference standard established from chart review of 527 random sepsis episodes to determine criterion validity. Next, the computational phenotype was compared with a separate validation cohort of 3,762 index sepsis episodes to determine content and construct validity. Criterion validity for the final phenotype had sensitivity 83% (95% CI, 76-89%), specificity 93% (90-95%), positive predictive value 84% (77-89%), and negative predictive value 93% (90-96%). In the validation cohort, the computational phenotype identified ABD in 35% (95% CI 33-36%). Content validity was demonstrated as those with the ABD computational phenotype were more likely to have characteristics of neurologic dysfunction and severe illness than those without the ABD phenotype, including nonreactive pupils (15% vs 1%; p < 0.001), Glasgow Coma Scale less than 5 (44% vs 12%; p < 0.001), greater than or equal to two nonneurologic organ dysfunctions (50% vs 25%; p < 0.001), and need for intensive care (81% vs 65%; p < 0.001). Construct validity was demonstrated by higher odds for mortality (odds ratio [OR], 6.9; 95% CI, 5.3-9.1) and discharge to rehabilitation (OR, 11.4; 95% CI 7.4-17.5) in patients with, versus without, the ABD computational phenotype. CONCLUSIONS: A computational phenotype of ABD indicative of clinician concern for new neurologic or behavioral change offers a valid retrospective measure to identify episodes of sepsis that involved ABD. This computational phenotype provides a feasible and efficient way to study risk factors for and outcomes from ABD using routinely collected clinical data.

Continuous Electroencephalogram Evaluation of Paroxysmal Events in Critically Ill Patients: Diagnostic Yield and Impact on Clinical Decision Making.

BACKGROUND: Continuous electroencephalogram (cEEG) monitoring has been widely used in the intensive care unit (ICU) for the evaluation of patients in the ICU with altered consciousness to detect nonconvulsive seizures. We investigated the yield of cEEG when used to evaluate paroxysmal events in patients in the ICU and assessed the predictors of a diagnostic findings. The clinical impact of cEEG was also evaluated in this study. METHODS: We identified patients in the ICU who underwent cEEG monitoring (> 6 h) to evaluate paroxysmal events between January 1, 2018, and December 31, 2019. We extracted patient demographics, medical history, neurological examination, brain imaging results, and the description of the paroxysmal events that necessitated the monitoring. We dichotomized the cEEG studies into those that captured habitual nonepileptic events or revealed epileptiform discharges (ictal or interictal), i.e., those considered to be of positive diagnostic yield (Y +), and those studies that did not show those findings (negative diagnostic yield, Y -). We also assessed the clinical impact of cEEG by documenting changes in administered antiseizure medication (ASM) before and after the cEEG. RESULTS: We identified 159 recordings that were obtained for the indication of paroxysmal events, of which abnormal movements constituted the majority (n = 123). For the remaining events (n = 36), descriptions included gaze deviations, speech changes, and sensory changes. Twenty-nine percent (46 of 159) of the recordings were Y + , including the presence of ictal or interictal epileptiform discharges (n = 33), and captured habitual nonepileptic events (n = 13). A history of epilepsy was the only predictor of the study outcome. Detection of abnormal findings occurred within 6 h of the recording in most patients (30 of 46, 65%). Overall, cEEG studies led to 49 (31%) changes in ASM administration. The changes included dosage increases or initiation of ASM in patients with epileptiform discharges (n = 28) and reduction or elimination of ASM in patients with either habitual nonepileptic events (n = 5) or Y - cEEG studies (n = 16). CONCLUSIONS: Continuous electroencephalogram monitoring is valuable in evaluating paroxysmal events, with a diagnostic yield of 29% in critically ill patients. A history of epilepsy predicts diagnostic studies. Both Y + and Y - cEEG studies may directly impact clinical decisions by leading to ASMs changes.

Intracranial Hypertension in Multisystem Inflammatory Syndrome in Children.

Multisystem inflammatory syndrome in children (MIS-C) is characterized by fever and multiorgan system dysfunction. Neurologic complications of MIS-C are not well described. We present 4 patients with MIS-C who had intracranial hypertension and discuss the unique management considerations when this occurs concurrently with significant myocardial dysfunction.

eIF5A-Independent Role of DHPS in p21CIP1 and Cell Fate Regulation.

Deoxyhypusine synthase (DHPS) catalyzes the first step of hypusination of the elongation translation factor 5A (eIF5A), and these two proteins have an exclusive enzyme-substrate relationship. Here we demonstrate that DHPS has a role independent of eIF5A hypusination in A375 and SK-MEL-28 human melanoma cells, in which the extracellular signal regulated kinase 1/2 (ERK1/2) pathway is deregulated. We found that RNA interference of DHPS induces G0/G1 cell cycle arrest in association with increased p21CIP1 expression in these cells whereas eIF5A knockdown induces cell death without increasing p21CIP1 expression. Interestingly, p21CIP1 knockdown switched DHPS knockdown-induced growth arrest to cell death in these cells, suggesting a specific relation between DHPS and p21CIP1 in determining cell fate. Surprisingly, ectopic expression of DHPS-K329R mutant that cannot hypusinate eIF5A abrogated DHPS knockdown-induced p21CIP1 expression in these cells, suggesting a non-canonical role of DHPS underlying the contrasting effects of DHPS and eIF5A knockdowns. We also show that DHPS knockdown induces p21CIP1 expression in these cells by increasing CDKN1A transcription through TP53 and SP1 in an ERK1/2-dependent manner. These data suggest that DHPS has a role independent of its ability to hypusinate eIF5A in cells, which appears to be important for regulating p21CIP1 expression and cell fate.

Growth Inhibitory Signaling of the Raf/MEK/ERK Pathway.

In response to extracellular stimuli, the Raf/MEK/extracellular signal-regulated kinase (ERK) pathway regulates diverse cellular processes. While mainly known as a mitogenic signaling pathway, the Raf/MEK/ERK pathway can mediate not only cell proliferation and survival but also cell cycle arrest and death in different cell types. Growing evidence suggests that the cell fate toward these paradoxical physiological outputs may be determined not only at downstream effector levels but also at the pathway level, which involves the magnitude of pathway activity, spatial-temporal regulation, and non-canonical functions of the molecular switches in this pathway. This review discusses recent updates on the molecular mechanisms underlying the pathway-mediated growth inhibitory signaling, with a major focus on the regulation mediated at the pathway level.

The Ponseti Method for Clubfoot Treatment in Low and Middle-Income Countries: A Systematic Review of Barriers and Solutions to Service Delivery.

BACKGROUND: Use of the minimally invasive Ponseti method has been increasing in low and middle-income countries, where most of the world's children with clubfoot are born. This method requires a system of service delivery involving screening, serial casting with or without a tenotomy to achieve correction, and long-term use of an orthosis to maintain correction. The goal of this systematic review is to evaluate the barriers to service delivery and the solutions that have been proposed or implemented to address these barriers. METHODS: A literature search of Medline, Embase, and SCOPUS produced 3251 results. Twenty-four papers were selected for final review. Barriers and their attempted solutions were organized into a previously described health barrier model. We reported on high-impact, sustainable solutions that are feasible for organizations to implement, as opposed to solutions that require major policy or country-wide infrastructure changes. RESULTS: Common barriers found to have the most impact on patient care included financial constraints, transportation, difficulties with brace and cast care, self-perceived health status, lack of physical resources, and provider's lack of knowledge and skill. The most common solutions detailed were education of the provider or patient and financial assistance for patients. CONCLUSIONS: Recognizing that contextually relevant solutions to the challenges of setting up a system for clubfoot service delivery are required, several common barriers have emerged within this systematic review of papers from multiple countries, including spatial accessibility, affordability, and availability. Programs can best prepare for challenges by placing clinics close to population centers and/or allocating funds to subsidize transportation, ensuring that an adequate supply of materials are available for the casting and tenotomy, and enhancing the education of families and health providers. Strengthening communication and establishing partnerships between individuals and organizations promoting the Ponseti method will improve systems for service delivery. LEVEL OF EVIDENCE: Level IV-prognostic study.

State Department of Motor Vehicles Reporting Mandates of Dementia Diagnoses and Dementia Underdiagnosis.

Importance: With older drivers representing the fastest growing segment of the driver population and dementia prevalence increasing with age, policymakers face the challenge of balancing road safety and mobility of older adults. In states that require reporting a dementia diagnosis to the Department of Motor Vehicles (DMV), individuals with dementia may be reluctant to disclose symptoms of cognitive decline, and clinicians may be reluctant to probe for those symptoms, which may be associated with missed or delayed diagnoses. Objective: To assess whether DMV reporting policies for drivers with dementia are associated with primary care clinicians' underdiagnosing dementia. Design, Setting, and Participants: This cross-sectional study used data from the 100% Medicare fee-for-service program and the Medicare Advantage plans from 2017 to 2019 on 223 036 primary care clinicians with at least 25 Medicare patients. Statistical analysis was performed from July to October 2023. Exposures: State DMV reporting policies for drivers with dementia. Main Outcomes and Measures: The main outcome was a binary variable indicating whether the clinician underdiagnosed dementia or not. Each clinician's expected number of dementia cases was estimated using a predictive model based on patient characteristics. Comparing the estimation with observed dementia diagnoses identified clinicians who underdiagnosed dementia vs those who did not, after accounting for sampling errors. Results: Four states have clinician reporting mandates, 14 have mandates requiring drivers to self-report dementia diagnoses, and 32 states and the District of Columbia do not have explicit requirements. Among primary care clinicians in states with clinician reporting mandates (n = 35 620), 51.4% were female, 91.9% worked in a metropolitan area, and 19.9% of the patient panel were beneficiaries dually eligible for Medicare and Medicaid. Among primary care clinicians in states with patient self-reporting mandates (n = 57 548), 55.7% were female, 83.1% worked in a metropolitan area, and 15.4% of the patient panel were dually eligible for Medicare and Medicaid. Among clinicians in states without mandates, 55.7% were female, 83.0% worked in a metropolitan area, and 14.6% of the patient panel were dually eligible for Medicare and Medicaid. Clinicians in states with clinician reporting mandates had an adjusted 12.4% (95% CI, 10.5%-14.2%) probability of underdiagnosing dementia compared with 7.8% (95% CI, 6.9%-8.7%) in states with self-reporting and 7.7% (95% CI, 6.9%-8.4%) in states with no mandates, an approximately 4-percentage point difference (P < .001). Conclusions and Relevance: Results of this cross-sectional study of primary care clinicians suggest that mandatory DMV policies for clinicians to report patients with dementia may be associated with a higher risk of missed or delayed dementia diagnoses. Future research is needed to better understand the unintended consequences and the risk-benefit tradeoffs of these policies.

Evaluation of Paroxysmal Events in Critically Ill Patients: Relationship of Primary Diagnosis to Long-Term Electroencephalogram Yield.

Continuous EEG (cEEG) is indicated for the workup of paroxysmal events. We aimed to assess whether primary admission diagnoses predict the yield of cEEG when ordered for evaluating paroxysmal events. We identified patients in the ICU who underwent at least 6 hours of cEEG monitoring to evaluate paroxysmal events. Primary admission diagnoses were categorized into neurological or non-neurological conditions. cEEG results were dichotomized into presence or absence of epileptiform discharges. We identified 159 recordings that were obtained for the evaluation of paroxysmal events. Most patients (n = 100, 63%) were admitted with primary admission diagnoses of neurological disorders, such as ischemic stroke, or intracranial hemorrhage. We found that patients with primary neurological conditions were more likely to have brain surgeries, abnormal brain imaging, and focal neurological deficits on examination compared to those with primary non-neurological conditions. However, there was no significant difference in the prevalence of epileptiform discharges in cEEG among patients with primary diagnoses of neurological or non-neurological disorders. These results suggest that cEEG is often necessary to evaluate paroxysmal events, even among patients without primary neurological disorders.

Advances in Point-of-Care Ultrasound in Pediatric Acute Care Medicine.

Pediatric point-of-care ultrasonography (POCUS) has grown in utilization and is now an integral part of pediatric acute care. Applications within the pediatric critical care, neonatology and pediatric emergency were once limited to evaluation of undifferentiated shock states, abdominal free fluid assessments in trauma resuscitation and procedural guidance. The body of pediatric POCUS literature is ever expanding and recently published international consensus guidelines are available to guide implementation into clinical practice. The authors present a review of emerging applications and controversies within thoracic, hemodynamic, neurologic, and ocular POCUS in pediatric acute care medicine.

Lipid- and protein-directed photosensitizer proximity labeling captures the cholesterol interactome.

The physical properties of cellular membranes, including fluidity and function, are influenced by protein and lipid interactions. In situ labeling chemistries, most notably proximity-labeling interactomics are well suited to characterize these dynamic and often fleeting interactions. Established methods require distinct chemistries for proteins and lipids, which limits the scope of such studies. Here we establish a singlet-oxygen-based photocatalytic proximity labeling platform (POCA) that reports intracellular interactomes for both proteins and lipids with tight spatiotemporal resolution using cell-penetrant photosensitizer reagents. Using both physiologically relevant lipoprotein-complexed probe delivery and genetic manipulation of cellular cholesterol handling machinery, cholesterol-directed POCA captured established and unprecedented cholesterol binding proteins, including protein complexes sensitive to intracellular cholesterol levels and proteins uniquely captured by lipoprotein uptake. Protein-directed POCA accurately mapped known intracellular membrane complexes, defined sterol-dependent changes to the non-vesicular cholesterol transport protein interactome, and captured state-dependent changes in the interactome of the cholesterol transport protein Aster-B. More broadly, we find that POCA is a versatile interactomics platform that is straightforward to implement, using the readily available HaloTag system, and fulfills unmet needs in intracellular singlet oxygen-based proximity labeling proteomics. Thus, we expect widespread utility for POCA across a range of interactome applications, spanning imaging to proteomics.

Artificial Intelligence Assistive Software Tool for Automated Detection and Quantification of Amyloid-Related Imaging Abnormalities.

Importance: Amyloid-related imaging abnormalities (ARIA) are brain magnetic resonance imaging (MRI) findings associated with the use of amyloid-ß-directed monoclonal antibody therapies in Alzheimer disease (AD). ARIA monitoring is important to inform treatment dosing decisions and might be improved through assistive software. Objective: To assess the clinical performance of an artificial intelligence (AI)-based software tool for assisting radiological interpretation of brain MRI scans in patients monitored for ARIA. Design, Setting, and Participants: This diagnostic study used a multiple-reader multiple-case design to evaluate the diagnostic performance of radiologists assisted by the software vs unassisted. The study enrolled 16 US Board of Radiology-certified radiologists to perform radiological reading with (assisted) and without the software (unassisted). The study encompassed 199 retrospective cases, where each case consisted of a predosing baseline and a postdosing follow-up MRI of patients from aducanumab clinical trials PRIME, EMERGE, and ENGAGE. Statistical analysis was performed from April to July 2023. Exposures: Use of icobrain aria, an AI-based assistive software for ARIA detection and quantification. Main Outcomes and Measures: Coprimary end points were the difference in diagnostic accuracy between assisted and unassisted detection of ARIA-E (edema and/or sulcal effusion) and ARIA-H (microhemorrhage and/or superficial siderosis) independently, assessed with the area under the receiver operating characteristic curve (AUC). Results: Among the 199 participants included in this study of radiological reading performance, mean (SD) age was 70.4 (7.2) years; 105 (52.8%) were female; 23 (11.6%) were Asian, 1 (0.5%) was Black, 157 (78.9%) were White, and 18 (9.0%) were other or unreported race and ethnicity. Among the 16 radiological readers included, 2 were specialized neuroradiologists (12.5%), 11 were male individuals (68.8%), 7 were individuals working in academic hospitals (43.8%), and they had a mean (SD) of 9.5 (5.1) years of experience. Radiologists assisted by the software were significantly superior in detecting ARIA than unassisted radiologists, with a mean assisted AUC of 0.87 (95% CI, 0.84-0.91) for ARIA-E detection (AUC improvement of 0.05 [95% CI, 0.02-0.08]; P = .001]) and 0.83 (95% CI, 0.78-0.87) for ARIA-H detection (AUC improvement of 0.04 [95% CI, 0.02-0.07]; P = .001). Sensitivity was significantly higher in assisted reading compared with unassisted reading (87% vs 71% for ARIA-E detection; 79% vs 69% for ARIA-H detection), while specificity remained above 80% for the detection of both ARIA types. Conclusions and Relevance: This diagnostic study found that radiological reading performance for ARIA detection and diagnosis was significantly better when using the AI-based assistive software. Hence, the software has the potential to be a clinically important tool to improve safety monitoring and management of patients with AD treated with amyloid-ß-directed monoclonal antibody therapies.

Expected and diagnosed rates of mild cognitive impairment and dementia in the U.S. Medicare population: observational analysis.

BACKGROUND: With the emergence of disease-modifying Alzheimer's treatments, timely detection of early-stage disease is more important than ever, as the treatment will not be indicated for later stages. Contemporary population-level data for detection rates of mild cognitive impairment (MCI), the stage at which treatment would ideally start, are lacking, and detection rates for dementia are only available for subsets of the Medicare population. We sought to compare documented diagnosis rates of MCI and dementia in the full Medicare population with expected rates based on a predictive model. METHODS: We performed an observational analysis of Medicare beneficiaries aged 65 and older with a near-continuous enrollment over a 3-year observation window or until death using 100% of the Medicare fee-for-service or Medicare Advantage Plans beneficiaries from 2015 to 2019. Actual diagnoses for MCI and dementia were derived from ICD-10 codes documented in those data. We used the 2000-2016 data of the Health and Retirement Study to develop a prediction model for expected diagnoses for the included population. The ratios between actually diagnosed cases of MCI and dementia over number of cases expected, the observed over expected ratio, reflects the detection rate. RESULTS: Although detection rates for MCI cases increased from 2015 to 2019 (0.062 to 0.079), the results mean that 7.4 of 8 million (92%) expected MCI cases remained undiagnosed. The detection rate for MCI was 0.039 and 0.048 in Black and Hispanic beneficiaries, respectively, compared with 0.098 in non-Hispanic White beneficiaries. Individuals dually eligible for Medicare and Medicaid had lower estimated detection rates than their Medicare-only counterparts for MCI (0.056 vs 0.085). Dementia was diagnosed more frequently than expected (1.086 to 1.104) from 2015 to 2019, mostly in non-Hispanic White beneficiaries (1.367) compared with 0.696 in Black beneficiaries and 0.758 in Hispanic beneficiaries. CONCLUSIONS: These results highlight the need to increase the overall detection rates of MCI and of dementia particularly in socioeconomically disadvantaged groups.

Association of Adverse Events in Opioid Addiction Treatment With Quality Measure for Continuity of Pharmacotherapy.

ABSTRACT: Several quality measures for continuity of substance use care are being used in accountability programs, but it is not known whether they are predictive of better patient outcomes. We analyzed whether opioid use disorder (OUD) patients in the care of clinicians and practices with higher rates on one of these measures-continuity of pharmacotherapy for OUD-have a lower risk of overdose and detox events using Medicare data. For a 10-percentage point increase in an individual clinician's measure rate, the estimated odds ratios of a patient experiencing each of these two events were 0.92 (95% confidence interval [CI] 0.85 to 0.99) for overdose and 0.83 (95% CI 0.75 to 0.92) for detox. The corresponding estimates at the practice level were 0.90 (95% CI 0.85 to 0.95) for overdose and 0.83 (95% CI 0.77 to 0.89) for detox. These results suggest that a clinician's or practice's higher measure rate for continuity of pharmacotherapy for OUD is predictive of their patients' lower likelihood of having an adverse event. The findings contribute to a growing body of evidence on the importance of treatment continuity for OUD and support the validity of measuring continuity in provider-level accountability programs.

Sepsis-Related Brain MRI Abnormalities Are Associated With Mortality and Poor Neurological Outcome in Pediatric Sepsis.

BACKGROUND: It is not known whether brain magnetic resonance imaging (MRI) abnormalities in pediatric sepsis are associated with clinical outcomes. Study objectives were to (1) determine the prevalence and type of sepsis-related neuroimaging abnormalities evident on clinically indicated brain MRI in children with sepsis and (2) test the association of these abnormalities with mortality, new disability, length of stay (LOS), and MRI indication. METHODS: Retrospective cohort study of 140 pediatric patients with sepsis and a clinically indicated brain MRI obtained within 60 days of sepsis onset at a single, large academic pediatric intensive care unit (PICU). Two radiologists systematically reviewed the first post-sepsis brain MRI and determined which abnormalities were sepsis-related. Outcomes compared in patients with versus without sepsis-related MRI abnormalities. RESULTS: PICU mortality was 7%. Thirty patients had one or more sepsis-related MRI abnormality, yielding a prevalence of 21% (95% confidence interval 15%, 28%). Among those, 53% (16 of 30) had sepsis-related white matter signal abnormalities; 53% (16 of 30) sepsis-related ischemia, infarction, or thrombosis; and 27% (eight of 30) sepsis-related posterior reversible encephalopathy. Patients with one or more sepsis-related MRI abnormality had increased mortality (17% vs 5%; P = 0.04), new neurological disability at PICU discharge (32% vs 11%; P = 0.03), and longer PICU LOS (median 18 vs 11 days; P = 0.04) compared with patients without. CONCLUSIONS: In children with sepsis and a clinically indicated brain MRI, 21% had a sepsis-related MRI abnormality. Sepsis-related MRI abnormalities were associated with increased mortality, new neurological disability, and longer PICU LOS.

Light echoes from ancient supernovae in the Large Magellanic Cloud.

The light from historical supernovae could in principle still be visible as scattered-light echoes centuries after the explosion. The detection of light echoes could allow us to pinpoint the supernova event both in position and age and, most importantly, permit the acquisition of spectra to determine the 'type' of the supernova centuries after the direct light from the explosion first reached Earth. Although echoes have been discovered around some nearby extragalactic supernovae, targeted searches have not found any echoes in the regions of historical Galactic supernovae. Here we report three faint variable-surface-brightness complexes with high apparent proper motions pointing back to three of the six smallest (and probably youngest) previously catalogued supernova remnants in the Large Magellanic Cloud, which are believed to have been thermonuclear (type Ia) supernovae. Using the distance and apparent proper motions of these echo arcs, we estimate ages of 610 and 410 years for two of them.