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Objective This qualitative study aimed to understand patient and researcher perspectives regarding consent and data-sharing preferences for research and a patient-centered system to manage consent and data-sharing preferences. Materials and Methods We conducted focus groups with patient and researcher participants recruited from three academic health centers via snowball sampling. Discussions focused on perspectives on the use of electronic health record (EHR) data for research. Themes were identified through consensus coding, starting from an exploratory framework. Results We held two focus groups with patients (n = 12 patients) and two with researchers (n = 8 researchers). We identified two patient themes (1–2), one theme common to patients and researchers (3), and two researcher themes (4–5). Themes included (1) motivations for sharing EHR data, (2) perspectives on the importance of data-sharing transparency, (3) individual control of personal EHR data sharing, (4) how EHR data benefits research, and (5) challenges researchers face using EHR data. Discussion Patients expressed a tension between the benefits of their data being used in studies to benefit themselves/others and avoiding risk by limiting data access. Patients resolved this tension by acknowledging they would often share their data but wanted greater transparency on its use. Researchers expressed concern about incorporating bias into datasets if patients opted out. Conclusions A research consent and data-sharing platform must consider two competing goals: empowering patients to have more control over their data and maintaining the integrity of secondary data sources. Health systems and researchers should increase trust-building efforts with patients to engender trust in data access and use.

Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe involvement during seizures. Bilateral TLE (BiTLE) remains understudied, likely due to its complex underlying pathophysiology and heterogeneous clinical presentation.In this study, using a multicenter resting state functional MRI (rs-fMRI) dataset, we constructed whole brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting-state, whole-brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities ranging from 0.10-0.50. Curves of network density versus each network metric were compared between groups. Finally, we derived a combined metric, which we term the “integration-segregation axis”, by combining whole brain average clustering coefficient and global efficiency curves and applying principal component analysis (PCA)-based dimensionality reduction.Compared to UTLE, BiTLE had decreased global efficiency (p=0.026), increased whole brain average clustering coefficient (p=0.035), and decreased whole brain average participation coefficient across a range of network densities (p=0.001). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p=0.016). Differences in network properties separate BiTLE and UTLE along the integration-segregation axis: 68% of patients with BiTLE were identified within the high segregation region, while only 41% of the UTLE patients were identified in the same region (p=0.042). Along the integration-segregation axis, UTLE patients with poor surgical outcomes were more similar to BiTLE than those with good surgical outcomes (p=0.72).Increased interictal whole brain network segregation, as measured by rs-fMRI, is specific to BiTLE, and may assist in non-invasively identifying this patient population prior to intracranial EEG or device implantation.

BACKGROUND: Benzodiazepines are commonly used among older adults, despite well-known risks. Clinical pharmacists can lead tapering efforts, leveraging their clinical expertise and relieving time-pressured primary care providers. OBJECTIVES: The objective is to describe the design, implementation, and evaluation of an outpatient pharmacist-led benzodiazepine tapering clinic. PRACTICE DESCRIPTION: The clinic is based within a community medical group associated with a large academic health system in Los Angeles, California. PRACTICE INNOVATION: The clinic is staffed by clinical pharmacists and supervised by a psychiatrist. The initial visit consists of patient education, design of patient-driven tapering schedule, and medical history review. Follow-up phone/video visits are used to monitor withdrawal symptoms and provide support. EVALUATION METHODS: We used chart review to assess tapering status among those enrolled in the tapering clinic versus those who did not enroll. We compared outcomes across the two groups using bivariate statistics. RESULTS: From March 2017- May 2019, 176 patients were referred to the clinic; 17 were deemed ineligible. Of the 159 patients contacted, 62 patients enrolled in the clinic; 97 patients did not enroll. Among patients in the clinic, 13 (27%) of patients were tapered down, 29 (60%) completely tapered off, 6 (13%) were unable to taper, and 14 (23%) were in the process of tapering. In contrast, among patients who did not enroll, 3 (4%) of patients were tapered down, 15 (20%) completely tapered off, 57 (76%) were unable to taper, and 22 (22%) were in the process of tapering. 90% of patients had at least some benzodiazepine tapering when enrolled in the clinic compared to 41% among not enrolled in the clinic (p

Background and ObjectivesChronic poststroke language impairment is typically worse in older individuals or those with large stroke lesions. However, there is unexplained variance that likely depends on intact tissue beyond the lesion. Brain age is an emerging concept, which is partially independent from chronologic age. Advanced brain age is associated with cognitive decline in healthy older adults; therefore, we aimed to investigate the relationship with stroke aphasia. We hypothesized that advanced brain age is a significant factor associated with chronic poststroke language impairments, above and beyond chronologic age, and lesion characteristics.MethodsThis cohort study retrospectively evaluated participants from the Predicting Outcomes of Language Rehabilitation in Aphasia clinical trial (NCT03416738), recruited through local advertisement in South Carolina (US). Primary inclusion criteria were left hemisphere stroke and chronic aphasia (≥12 months after stroke). Participants completed baseline behavioral testing including the Western Aphasia Battery–Revised (WAB-R), Philadelphia Naming Test (PNT), Pyramids and Palm Trees Test (PPTT), and Wechsler Adult Intelligence Scale Matrices subtest, before completing 6 weeks of language therapy. The PNT was repeated 1 month after therapy. We leveraged modern neuroimaging techniques to estimate brain age and computed a proportional difference between chronologic age and estimated brain age. Multiple linear regression models were used to evaluate the relationship between proportional brain age difference (PBAD) and behavior.ResultsParticipants (N = 93, 58 males and 35 females, average age = 61 years) had estimated brain ages ranging from 14 years younger to 23 years older than chronologic age. Advanced brain age predicted performance on semantic tasks (PPTT) and language tasks (WAB-R). For participants with advanced brain aging (n = 47), treatment gains (improvement on the PNT) were independently predicted by PBAD (T = −2.0474,p= 0.0468, 9% of variance explained).DiscussionThrough the application of modern neuroimaging techniques, advanced brain aging was associated with aphasia severity and performance on semantic tasks. Notably, therapy outcome scores were also associated with PBAD, albeit only among participants with advanced brain aging. These findings corroborate the importance of brain age as a determinant of poststroke recovery and underscore the importance of personalized health factors in determining recovery trajectories, which should be considered during the planning or implementation of therapeutic interventions.

In the pelvis, anatomic complexity and difficulty in visualization and access make surgery a formidable task. Surgeons are prone to work-related musculoskeletal injuries from the frequently poor design and flow of their work environment. This is exacerbated by the strain of surgery in the pelvis. These injuries can result in alterations to a surgeons practice, inadvertent patient injury, and even early retirement. Human factors examines the relationships between the surgeon, their instruments and their environment. By bridging physiology, psychology, and ergonomics, human factors allows a better understanding of some of the challenges posed by pelvic surgery. The operative approach involved (open, laparoscopic, robotic, or perineal) plays an important role in the relevant human factors. Improved understanding of ergonomics can mitigate these risks to surgeons. Other human factors approaches such as standardization, use of checklists, and employing resiliency efforts can all improve patient safety in the operating theatre.

Deep-plane rhytidectomy, first described by Skoog, has had a resurgence in popularity and is in high demand today. We describe anatomical findings that establish the presence of a true deep fascia in the midface, we named as Chiara's fascia, like the first author's first name, which helps to form the facial ligaments and is contiguous with the superficial layer of the deep temporal fascia. This fascia inserts on the periosteum of the inferior orbital rim at the arcus marginalis and separates the suborbicularis oculi fat (SOOF) from the preperiosteal fat. This distinct fascial layer lies under the superficial fascia or superficial musculoaponeurotic system (SMAS) and represents the floor of what is commonly termed the “deep plane.” When this fascial highway is identified intraoperatively, blunt dissection immediately superficial to this layer will protect facial nerve branches overlying the muscles lifting the upper lip such as the zygomaticus. Subsequent dissection over the middle and lower face can usually be performed bluntly. Over a 10-year period, a total of 100 hemifaces were dissected with a 100% success rate of identifying this fascia in all specimens. This work was further validated by examining histologic specimens that clearly demonstrate this unique fibrofatty fascial layer. These dissections and new anatomical findings were then correlated to over 300 intraoperative deep-plane facelift cases by the primary and senior authors. We term this operative technique as the suprafibromuscular facelift. Dissection in this plane allows for safe release of facial retaining ligaments with protection of facial nerve branches.

Guidelines recommend adjuvant chemotherapy for stage II colon cancer with high-risk features, but there has been little study on compliance with guidelines. This work sought to evaluate compliance with adjuvant chemotherapy and factors associated with compliance in high-risk stage II colon cancer. This work's hypothesis was that compliance with adjuvant chemotherapy recommendations is low, but improves overall survival when used.The National Cancer Database was reviewed for stage II high-risk colon cancers that underwent curative resection from 2010 to 2017. The cases were stratified into adjuvant chemotherapy and no adjuvant chemotherapy cohorts. A multivariate logistic regression identified factors associated with adjuvant chemotherapy compliance. Propensity-score matching was performed to balance the cohorts and Kaplan-Meier analysis assessed overall survival. The main outcome measures were adjuvant chemotherapy compliance, factors associated with compliance, and overall survival in high-risk stage II colon cancer.A total of 52,609 patients were evaluated, and 23.2% received adjuvant chemotherapy. The factors associated with noncompliance included older age (odds ratio 0.919; 95% confidence interval 0.915-0.922; P.001), Medicaid (odds ratio 0.720; 95% confidence interval 0.623-0.832; P.001) payor, greater comorbidities (odds ratio 0.423; 95% confidence interval 0.334-0.530; P.001), and residing in the Midwest (odds ratio 0.898; 95% confidence interval 0.812-0.994; P = .037). All of the known high-risk features were significantly independently associated with compliance. In a matched cohort, adjuvant chemotherapy significantly improved the 5-year overall survival (78.1% vs 66.6%; P.001).Nationally, there is low compliance with adjuvant chemotherapy in high-risk stage II colon cancer. Despite the low compliance, adjuvant chemotherapy was associated with improved overall survival. Demographic variables were associated with poor compliance, whereas tumor factors were associated with increased compliance. These results highlighted the disparities in care and opportunities to improve outcomes in high-risk stage II colon cancer.

The aim of this study was to determine the role of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in the prognostication of patients ≥80 years of age undergoing percutaneous coronary intervention (PCI).Elderly patients with coronary artery disease in need of PCI represent a growing patient population. Advanced risk prediction in this frail and comorbid patient population is important.A total of 460 consecutive patients ≥80 years of age undergoing PCI for acute (ACS) or chronic coronary syndromes (CCS) at the University Hospital Zurich, Switzerland, between January 2016 and December 2018 and with available baseline NT-proBNP levels were included in the analysis. Patients were stratified according to baseline NT-proBNP levels. The primary endpoint was all-cause mortality at a median follow-up of 33 (interquartile range: 3-392) days.Median baseline NT-proBNP levels were 1411 (457-3984) ng/L. All-cause mortality was 7.8% in the lowest and 27.8% in the highest NT-proBNP quartile group (p 0.001). In patients with ACS, all-cause mortality was 4.8% and 30.4% in the lowest and the highest NT-proBNP quartile (p 0.001), and corresponding rates in patients with CCS were 11.1% and 22.2% (p = 0.38). In multivariable Cox regression analysis, baseline NT-proBNP levels were independently associated with an increased risk of all-cause mortality (adjusted hazard ratio: 1.00, 95% confidence interval: 1.00-1.00, p = 0.04).Baseline NT-proBNP levels were identified as independent predictor of mortality in elderly (≥80 years) patients undergoing PCI. Hence, baseline NT-proBNP allows for the identification of a high-risk elderly patient subset.

Background: Idiopathic generalized epilepsy (IGE) is a collection of generalized nonlesional epileptic network disorders. Around 20-40% of patients with IGE are refractory to antiseizure medication, and mechanisms underlying refractoriness are poorly understood. Here, we characterize structural brain network alterations and determine whether network alterations differ between patients with refractory and nonrefractory IGE. Methods: Thirty-three patients with IGE (10 nonrefractory and 23 refractory) and 39 age- and sex-matched healthy controls were studied. Network nodes were segmented from T1-weighted images, while connections between these nodes (edges) were reconstructed from diffusion magnetic resonance imaging (MRI). Diffusion networks of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and streamline count (Count) were studied. Differences between all patients, refractory, nonrefractory, and control groups were computed using network-based statistics. Nodal volume differences between groups were computed using Cohen's d effect size calculation. Results: Patients had significantly decreased bihemispheric FA and Count networks and increased MD and RD networks compared with controls. Alterations in network architecture, with respect to controls, differed depending on treatment outcome, including predominant FA network alterations in refractory IGE and increased nodal volume in nonrefractory IGE. Diffusion MRI networks were not influenced by nodal volume. Discussion: Although a nonlesional disorder, patients with IGE have bihemispheric structural network alterations that may differ between patients with refractory and nonrefractory IGE. Given that distinct nodal volume and FA network alterations were observed between treatment outcome groups, a multifaceted network analysis may be useful for identifying imaging biomarkers of refractory IGE.

Firearm sales in the United States (U.S.) markedly increased during the COVID-19 pandemic. Our objective was to determine if firearm injuries in children were associated with stay-at-home orders (SHO) during the COVID-19 pandemic. We hypothesized there would be an increase in pediatric firearm injuries during SHO.This was a multi institutional, retrospective study of institutional trauma registries. Patients18 years with traumatic injuries meeting National Trauma Data Bank (NTDB) criteria were included. A "COVID" cohort, defined as time from initiation of state SHO through September 30, 2020 was compared to "Historical" controls from an averaged period of corresponding dates in 2016-2019. An interrupted time series analysis (ITSA) was utilized to evaluate the association of the U.S. declaration of a national state of emergency with pediatric firearm injuries.Nine Level I pediatric trauma centers were included, contributing 48,111 pediatric trauma patients, of which 1,090 patients (2.3%) suffered firearm injuries. There was a significant increase in the proportion of firearm injuries in the COVID cohort (COVID 3.04% vs. Historical 1.83%; p 0.001). There was an increased cumulative burden of firearm injuries in 2020 compared to a historical average. ITSA showed an 87% increase in the observed rate of firearm injuries above expected after the declaration of a nationwide emergency (p 0.001).The proportion of firearm injuries affecting children increased during the COVID-19 pandemic. The pandemic was associated with an increase in pediatric firearm injuries above expected rates based on historical patterns.

Objective: Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross‐sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE‐HS) correlate with clinical features. Methods: We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1‐weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA‐Epilepsy consortium, comprising 804 people with MTLE‐HS and 1625 healthy controls from 25 centers. Features with a moderate case–control effect size (Cohen d ≥ .5) were used to train an event‐based model (EBM), which estimates a sequence of disease‐specific biomarker changes from cross‐sectional data and assigns a biomarker‐based fine‐grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. Results: In MTLE‐HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10−16), age at onset (ρ = −.18, p = 9.82 × 10−7), and ASM resistance (area under the curve = .59, p = .043, Mann–Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE‐HS with mild or nondetectable abnormality on T1W MRI. Significance: From cross‐sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE‐HS subjects in other cohorts and help establish connections between imaging‐based progression staging and clinical features.

Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive for clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson’s disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between January 01, 2000, and April 01, 2022, and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson’s disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson’s disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions were also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimising individualised therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.

Cold spraying (CS) of high strength materials, e.g., Inconel 625 is still challenging due to the limited material deformability and thus high critical velocities. Further fine tuning and optimization of cold spray process parameters is required, to reach higher particle impact velocities as well as temperatures, while avoiding nozzle clogging. Only then, sufficiently high amounts of well-bonded particle-substrate and particle-particle interfaces can be achieved, assuring high cohesive strength and minimum amounts of porosities. In this study, Inconel 625 powder was cold sprayed on carbon steel substrates using N2 as propellant gas under different refined spray parameter sets and powder sizes for a systematic evaluation. Coating microstructure, porosity, electrical conductivity, hardness, cohesive strength and residual stress were characterized in as-sprayed condition. Increasing the process gas temperature or pressure leads to low coating porosity of less than 1 % and higher electrical conductivity. The as-sprayed coatings show microstructures with highly deformed particles and well bonded internal boundaries. X-ray diffraction reveals that powder and deposits are present as γ- solid-solution phase without any precipitations. By work hardening and peening effects, the deposits show high microhardness and compressive residual stresses. With close to bulk material properties, the optimized deposits should fulfill criteria for industrial applications.

Background and Objectives:A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. Here we explore the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input.Methods:Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared to a randomized model (comparison to chance) and a hippocampal volume logistic regression (comparison to current clinically-available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients.Results:Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD= 5.1%) of runs with the best performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification.Discussion:These extra-temporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extra-hippocampal regions that may require additional radiological attention.Classification of Evidence:This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MR images can correctly classify seizure laterality.