An Abscopal Effect on Lung Metastases in Canine Mammary Cancer Patients Induced by Neoadjuvant Intratumoral Immunotherapy with Cowpea Mosaic Virus Nanoparticles and Anti-Canine PD-1.

Neoadjuvant intratumoral (IT) therapy could amplify the weak responses to checkpoint blockade therapy observed in breast cancer (BC). In this study, we administered neoadjuvant IT anti-canine PD-1 therapy (IT acPD-1) alone or combined with IT cowpea mosaic virus therapy (IT CPMV/acPD-1) to companion dogs diagnosed with canine mammary cancer (CMC), a spontaneous tumor resembling human BC. CMC patients treated weekly with acPD-1 (n = 3) or CPMV/acPD-1 (n = 3) for four weeks or with CPMV/acPD-1 (n = 3 patients not candidates for surgery) for up to 11 weeks did not experience immune-related adverse events. We found that acPD-1 and CPMV/acPD-1 injections resulted in tumor control and a reduction in injected tumors in all patients and in noninjected tumors located in the ipsilateral and contralateral mammary chains of treated dogs. In two metastatic CMC patients, CPMV/acPD-1 treatments resulted in the control and reduction of established lung metastases. CPMV/acPD-1 treatments were associated with altered gene expression related to TLR1-4 signaling and complement pathways. These novel therapies could be effective for CMC patients. Owing to the extensive similarities between CMC and human BC, IT CPMV combined with approved anti-PD-1 therapies could be a novel and effective immunotherapy to treat local BC and suppress metastatic BC.

Utilizing Augmented Reality to Evaluate Service Member Team Performance.

INTRODUCTION: Decision-making is a complex process that relies on situational awareness and experience to create a potential list of actions while weighing the risks and benefits of each action. There is a paucity of data evaluating decision-making for individual service members (SM) during the performance of team-based military-relevant activities. Understanding individual performance and decision-making within the context of a team-based activity has potential to aid in the detection and management of mild traumatic brain injuries and assist with safe and timely return-to-duty decision making. The aim of this project was to evaluate cognitive and motor performance in healthy SM during an augmented reality military specific, team-based activity. MATERIALS AND METHODS: Data from 110 SMs from Fort Moore Georgia were analyzed for this project. Service members completed 3 augmented reality room breaching and clearing scenarios (Empty Room, Civilian/Combatant, and Incorrect Position of a unit member) with 3 avatar team members. Participants wore a Microsoft HoloLens 2 (HL2) device and used a replica M4 weapon (Haptech Defense Systems) during scenarios. Three-dimensional position data from the HL2 headset was used to compute temporal measures of room breaching and clearing events while the number and timing of weapon discharge was monitored by the M4. Temporal outcomes included time to enter room, time to fire first shot, time in fatal funnel, and total trial time while motor outcomes were distance traveled and average movement velocity. RESULTS: Pairwise comparisons between the Incorrect Position scenario and the Civilian/Combatant scenario demonstrated no difference in time to enter the room (2.36 seconds in both scenarios). Time to fire the first shot in the Civilian/Combatant scenario was longer (0.97 seconds to 0.58 seconds) while time in fatal funnel (2.58 seconds to 3.31 seconds) and time to trial completion (7.46 seconds to 8.41 seconds) were significantly longer in the Incorrect Position scenario. CONCLUSIONS: Reaction time to fire the first shot, time in the fatal funnel, and total trial time reflect a change in information-processing and decision-making capabilities during military specific, ecological, team-based scenarios when altering the environment inside of the room and modifying avatar movements. Future studies are planned to evaluate the effects of mild traumatic brain injury on specific aspects of military team performance.

Nicotine inhalation and metabolism triggers AOX-mediated superoxide generation with oxidative lung injury.

With the increasing use of vaping devices that deliver high levels of nicotine (NIC) to the lungs, sporadic lung injury has been observed. Commercial vaping solutions can contain high NIC concentrations of 150 mM or more. With high NIC levels, its metabolic products may induce toxicity. NIC is primarily metabolized to form NIC iminium (NICI) which is further metabolized by aldehyde oxidase (AOX) to cotinine. We determine that NICI in the presence of AOX is a potent trigger of superoxide generation. NICI stimulated superoxide generation from AOX with Km = 2.7 µM and Vmax = 794 nmol/min/mg measured by cytochrome-c reduction. EPR spin-trapping confirmed that NICI in the presence of AOX is a potent source of superoxide. AOX is expressed in the lungs and chronic e-cigarette exposure in mice greatly increased AOX expression. NICI or NIC stimulated superoxide production in the lungs of control mice with an even greater increase after chronic e-cigarette exposure. This superoxide production was quenched by AOX inhibition. Furthermore, e-cigarette-mediated NIC delivery triggered oxidative lung damage that was blocked by AOX inhibition. Thus, NIC metabolism triggers AOX-mediated superoxide generation that can cause lung injury. Therefore, high uncontrolled levels of NIC inhalation, as occur with e-cigarette use, can induce oxidative lung damage.

Recommendations for clinical trial design in acute kidney injury from the 31st acute disease quality initiative consensus conference. A consensus statement.

PURPOSE: Novel interventions for the prevention or treatment of acute kidney injury (AKI) are currently lacking. To facilitate the evaluation and adoption of new treatments, the use of the most appropriate design and endpoints for clinical trials in AKI is critical and yet there is little consensus regarding these issues. We aimed to develop recommendations on endpoints and trial design for studies of AKI prevention and treatment interventions based on existing data and expert consensus. METHODS: At the 31st Acute Disease Quality Initiative (ADQI) meeting, international experts in critical care, nephrology, involving adults and pediatrics, biostatistics and people with lived experience (PWLE) were assembled. We focused on four main areas: (1) patient enrichment strategies, (2) prevention and attenuation studies, (3) treatment studies, and (4) innovative trial designs of studies other than traditional (parallel arm or cluster) randomized controlled trials. Using a modified Delphi process, recommendations and consensus statements were developed based on existing data, with > 90% agreement among panel members required for final adoption. RESULTS: The panel developed 12 consensus statements for clinical trial endpoints, application of enrichment strategies where appropriate, and inclusion of PWLE to inform trial designs. Innovative trial designs were also considered. CONCLUSION: The current lack of specific therapy for prevention or treatment of AKI demands refinement of future clinical trial design. Here we report the consensus findings of the 31st ADQI group meeting which has attempted to address these issues including the use of predictive and prognostic enrichment strategies to enable appropriate patient selection.

Tobacco cigarette smoking induces cerebrovascular dysfunction followed by oxidative neuronal injury with the onset of cognitive impairment.

While chronic smoking triggers cardiovascular disease, controversy remains regarding its effects on the brain and cognition. We investigated the effects of long-term cigarette smoke (CS) exposure (CSE) on cerebrovascular function, neuronal injury, and cognition in a novel mouse exposure model. Longitudinal studies were performed in CS or air-exposed mice, 2 hours/day, for up to 60 weeks. Hypertension and carotid vascular endothelial dysfunction (VED) occurred by 16 weeks of CSE, followed by reduced carotid artery blood flow, with oxidative stress detected in the carotid artery, and subsequently in the brain of CS-exposed mice with generation of reactive oxygen species (ROS) and secondary protein and DNA oxidation, microglial activation and astrocytosis. Brain small vessels exhibited decreased levels of endothelial NO synthase (eNOS), enlarged perivascular spaces with blood brain barrier (BBB) leak and decreased levels of tight-junction proteins. In the brain, amyloid-ß deposition and phosphorylated-tau were detected with increases out to 60 weeks, at which time mice exhibited impaired spatial learning and memory. Thus, long-term CSE initiates a cascade of ROS generation and oxidative damage, eNOS dysfunction with cerebral hypoperfusion, as well as cerebrovascular and BBB damage with intracerebral inflammation, and neuronal degeneration, followed by the onset of impaired cognition and memory.

Trajectories of behavior and social cognition in behavioral variant frontotemporal dementia and primary psychiatric disorders: A call for better operationalization of socioemotional changes.

BACKGROUND AND PURPOSE: Behavioral variant frontotemporal dementia (bvFTD) and primary psychiatric disorders (PPD), such as mood, psychotic, and autism spectrum disorders, share similar clinical characteristics of behavior and social cognition. Better understanding of clinical progression in bvFTD and PPD is essential for adequate disease monitoring and trial design. METHODS: In this longitudinal study (N = 89), patients with bvFTD and PPD with at least one follow-up assessment were included from the Social Brain Project of the Alzheimer Center Amsterdam. Behavioral change and social cognitive decline were assessed via informant-rated questionnaires (Cambridge Behavioral Inventory-Revised, Frontal Behavioral Inventory [FBI], Stereotypy Rating Inventory, Frontotemporal Dementia Rating Scale, Revised Self-Monitoring Scale [RSMS]-caregiver) and patient assessment (Ekman 60-Faces Test, RSMS-patient, Emotional Contagion Scale). Clinical trajectories (median = 1.4 years, interquartile range = 1.0-2.2) were examined using linear mixed models. In a subsample, associations with baseline serum neurofilament light (sNfL) were examined. RESULTS: At baseline, behavioral and social cognitive symptoms were similar between diagnosis groups, except for poorer emotion recognition in bvFTD. Over time, behavioral symptoms worsened in bvFTD, whereas most measures remained stable and the FBI improved in PPD. Regarding social cognition, emotion recognition and caregiver-reported socioemotional sensitivity worsened in bvFTD and remained stable in PPD. Patient-reported social cognitive measures did not change over time. Higher sNfL was associated with faster behavioral change. CONCLUSIONS: Trajectories of behavior and social cognition differentiate bvFTD from PPD, provided that social cognition is not patient-reported. Therefore, we stress the need to optimize longitudinal social cognitive assessment in bvFTD. sNfL may be a useful prognostic marker of behavioral progression in neuropsychiatric populations.

The Road to Precision Medicine for Acute Kidney Injury.

OBJECTIVES: Acute kidney injury (AKI) is a common form of organ dysfunction in the ICU. AKI is associated with adverse short- and long-term outcomes, including high mortality rates, which have not measurably improved over the past decade. This review summarizes the available literature examining the evidence of the need for precision medicine in AKI in critical illness, highlights the current evidence for heterogeneity in the field of AKI, discusses the progress made in advancing precision in AKI, and provides a roadmap for studying precision-guided care in AKI. DATA SOURCES: Medical literature regarding topics relevant to precision medicine in AKI, including AKI definitions, epidemiology, and outcomes, novel AKI biomarkers, studies of electronic health records (EHRs), clinical trial design, and observational studies of kidney biopsies in patients with AKI. STUDY SELECTION: English language observational studies, randomized clinical trials, reviews, professional society recommendations, and guidelines on areas related to precision medicine in AKI. DATA EXTRACTION: Relevant study results, statements, and guidelines were qualitatively assessed and narratively synthesized. DATA SYNTHESIS: We synthesized relevant study results, professional society recommendations, and guidelines in this discussion. CONCLUSIONS: AKI is a syndrome that encompasses a wide range of underlying pathologies, and this heterogeneity has hindered the development of novel therapeutics for AKI. Wide-ranging efforts to improve precision in AKI have included the validation of novel biomarkers of AKI, leveraging EHRs for disease classification, and phenotyping of tubular secretory clearance. Ongoing efforts such as the Kidney Precision Medicine Project, identifying subphenotypes in AKI, and optimizing clinical trials and endpoints all have great promise in advancing precision medicine in AKI.

An immersive virtual reality shopping task detects declines in instrumental activities of daily living in individuals with Parkinson's disease.

INTRODUCTION: Declines in instrumental activities of daily living (IADLs) have been proposed as a prodromal marker of Parkinson's disease (PD). The Cleveland Clinic Virtual Reality Shopping (CC-VRS) platform combines an omnidirectional treadmill with a virtual reality headset to create a virtual grocery store that a user physically walks through and completes a shopping task. The primary aim of this project was to determine the known-group validity of the CC-VRS platform in discriminating IADL performance and to characterize specific motor and cognitive declines responsible for PD-related IADL impairments. METHODS: Sixteen individuals with PD and 15 healthy adults completed traditional motor, cognitive, and IADL assessments and the CC-VRS task. Group differences were evaluated using Welch's t-test. RESULTS: There were no between-group differences in traditional performance measures of motor, cognitive, or IADL function. Regarding CC-VRS performance, participants in the PD group completed the task significantly slower than controls (690 vs. 523 sec, respectively). Participants with PD spent 25 % more time walking and turning and were stopped 46 % longer than controls. Average gait speed when viewing the shopping list, a measure of dual-task performance, was significantly slower in the PD group compared to controls (0.26 vs. 0.17 m/s, respectively). CONCLUSION: Unlike traditional performance measures of motor, cognitive, and IADL function, the CC-VRS discriminated participants with PD from healthy older adults. For the PD group, motor and dual-task declines contributed to diminished CC-VRS performance. Identifying underlying contributors to IADL declines supports using ecological assessments, such as the CC-VRS, for the routine clinical evaluation of IADLs.

Real world predictors of response and 24-month survival in high-grade TP53-mutated myeloid neoplasms.

Current therapies for high-grade TP53-mutated myeloid neoplasms (≥10% blasts) do not offer a meaningful survival benefit except allogeneic stem cell transplantation in the minority who achieve a complete response to first line therapy (CR1). To identify reliable pre-therapy predictors of complete response to first-line therapy (CR1) and outcomes, we assembled a cohort of 242 individuals with TP53-mutated myeloid neoplasms and ≥10% blasts with well-annotated clinical, molecular and pathology data. Key outcomes examined were CR1 & 24-month survival (OS24). In this elderly cohort (median age 68.2 years) with 74.0% receiving frontline non-intensive regimens (hypomethylating agents +/- venetoclax), the overall cohort CR1 rate was 25.6% (50/195). We additionally identified several pre-therapy factors predictive of inferior CR1 including male gender (P = 0.026), ≥2 autosomal monosomies (P < 0.001), -17/17p (P = 0.011), multi-hit TP53 allelic state (P < 0.001) and CUX1 co-alterations (P = 0.010). In univariable analysis of the entire cohort, inferior OS24 was predicated by ≥2 monosomies (P = 0.004), TP53 VAF > 25% (P = 0.002), TP53 splice junction mutations (P = 0.007) and antecedent treated myeloid neoplasm (P = 0.001). In addition, mutations/deletions in CUX1, U2AF1, EZH2, TET2, CBL, or KRAS ('EPI6' signature) predicted inferior OS24 (HR = 2.0 [1.5-2.8]; P < 0.0001). In a subgroup analysis of HMA +/-Ven treated individuals (N = 144), TP53 VAF and monosomies did not impact OS24. A risk score for HMA +/-Ven treated individuals incorporating three pre-therapy predictors including TP53 splice junction mutations, EPI6 and antecedent treated myeloid neoplasm stratified 3 prognostic distinct groups: intermediate, intermediate-poor, and poor with significantly different median (12.8, 6.0, 4.3 months) and 24-month (20.9%, 5.7%, 0.5%) survival (P < 0.0001). For the first time, in a seemingly monolithic high-risk cohort, our data identifies several baseline factors that predict response and 24-month survival.

A one health approach for monitoring antimicrobial resistance: developing a national freshwater pilot effort.

Antimicrobial resistance (AMR) is a world-wide public health threat that is projected to lead to 10 million annual deaths globally by 2050. The AMR public health issue has led to the development of action plans to combat AMR, including improved antimicrobial stewardship, development of new antimicrobials, and advanced monitoring. The National Antimicrobial Resistance Monitoring System (NARMS) led by the United States (U.S) Food and Drug Administration along with the U.S. Centers for Disease Control and U.S. Department of Agriculture has monitored antimicrobial resistant bacteria in retail meats, humans, and food animals since the mid 1990's. NARMS is currently exploring an integrated One Health monitoring model recognizing that human, animal, plant, and environmental systems are linked to public health. Since 2020, the U.S. Environmental Protection Agency has led an interagency NARMS environmental working group (EWG) to implement a surface water AMR monitoring program (SWAM) at watershed and national scales. The NARMS EWG divided the development of the environmental monitoring effort into five areas: (i) defining objectives and questions, (ii) designing study/sampling design, (iii) selecting AMR indicators, (iv) establishing analytical methods, and (v) developing data management/analytics/metadata plans. For each of these areas, the consensus among the scientific community and literature was reviewed and carefully considered prior to the development of this environmental monitoring program. The data produced from the SWAM effort will help develop robust surface water monitoring programs with the goal of assessing public health risks associated with AMR pathogens in surface water (e.g., recreational water exposures), provide a comprehensive picture of how resistant strains are related spatially and temporally within a watershed, and help assess how anthropogenic drivers and intervention strategies impact the transmission of AMR within human, animal, and environmental systems.

Multidecadal mangrove forest change in Macajalar Bay, Northern Mindanao, Philippines (1950-2020) using remote sensing and geographic information systems.

The mangrove forest in Macajalar Bay is regarded as an important coastal ecosystem since it provides numerous ecosystem services. Despite their importance, the clearing of mangroves has been rampant and has reached critical rates. Addressing this problem and further advancing its conservation require accurate mangrove mapping. However, current spatial information related to mangroves is sparse and insufficient to understand the historical change dynamics. In this study, the synergy of 1950 vegetation maps and Landsat images was explored to provide multidecadal monitoring of mangrove forest change dynamics in Macajalar Bay, Philippines. Vegetation maps containing the 1950 mangrove extent and Landsat images were used as input data to monitor the rates of loss over 70 years. In 2020, the mangrove forest cover was estimated to be 201.73 ha, equivalent to only 61.99% of the 325.43 ha that was estimated in 1950. Between 1950 and 2020, net mangrove loss in Macajalar Bay totaled 324.29 ha. The highest clearing rates occurred between 1950 and 1990 when it recorded a total of 258.51 ha, averaging 6.46 ha/year. The original mangrove forest that existed in 1950 only represents 8.56% of the 2020 extent, suggesting that much of the old-growth mangrove had been cleared before 2000 and the existing mangrove forest is mainly composed of secondary mangrove forest stands. Across Macajalar Bay, intensified clearing that happened between 1950 and 1990 has been driven by large-scale aquaculture developments. Mangrove gains on the other hand were evident and have increased the total extent by 79.84 ha since 2000 as a result of several afforestation programs. However, approximately half of these gains that were observed since 2010 exhibited low canopy cover. As of writing, approximately 85% of the 2020 mangrove forest stands fall outside the 1950 original mangrove extent. Examining the viability of the original mangrove forest for mangrove reforestation together with promoting site-species matching, and biophysical assessment are necessary undertakings to advance current mangrove conservation initiatives in Macajalar Bay.

Forward genetics combined with unsupervised classifications identified zebrafish mutants affecting biliary system formation.

Impaired formation of the biliary network can lead to congenital cholestatic liver diseases; however, the genes responsible for proper biliary system formation and maintenance have not been fully identified. Combining computational network structure analysis algorithms with a zebrafish forward genetic screen, we identified 24 new zebrafish mutants that display impaired intrahepatic biliary network formation. Complementation tests suggested these 24 mutations affect 24 different genes. We applied unsupervised clustering algorithms to unbiasedly classify the recovered mutants into three classes. Further computational analysis revealed that each of the recovered mutations in these three classes has a unique phenotype on node-subtype composition and distribution within the intrahepatic biliary network. In addition, we found most of the recovered mutations are viable. In those mutant fish, which are already good animal models to study chronic cholestatic liver diseases, the biliary network phenotypes persist into adulthood. Altogether, this study provides unique genetic and computational toolsets that advance our understanding of the molecular pathways leading to biliary system malformation and cholestatic liver diseases.

The pursuit for markers of disease progression in behavioral variant frontotemporal dementia: a scoping review to optimize outcome measures for clinical trials.

Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by diverse and prominent changes in behavior and personality. One of the greatest challenges in bvFTD is to capture, measure and predict its disease progression, due to clinical, pathological and genetic heterogeneity. Availability of reliable outcome measures is pivotal for future clinical trials and disease monitoring. Detection of change should be objective, clinically meaningful and easily assessed, preferably associated with a biological process. The purpose of this scoping review is to examine the status of longitudinal studies in bvFTD, evaluate current assessment tools and propose potential progression markers. A systematic literature search (in PubMed and Embase.com) was performed. Literature on disease trajectories and longitudinal validity of frequently-used measures was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. Evaluating current longitudinal data, we propose an adaptive battery, combining a set of sensitive clinical, neuroimaging and fluid markers, adjusted for genetic and sporadic variants, for adequate detection of disease progression in bvFTD.

The i-gel® supraglottic airway device compared to endotracheal intubation as the initial prehospital advanced airway device: A natural experiment during the COVID-19 pandemic.

Objective: Unlike randomized controlled trials, practical real-world studies can offer important information about implementation of prehospital interventions, particularly in community settings where there may be reluctance to adopt new practices. We present the results of a natural experiment that was driven by mandated COVID-19 pandemic-driven shift from endotracheal intubation (ETI) to the i-gel® supraglottic airway (SGA) as a primary advanced airway management device in the prehospital setting to reduce emergency medical services (EMS) personnel exposure to potentially infectious secretions. The objective was to compare first-pass success and timing to successful airway placement between ETI and the i-gel® SGA under extenuating circumstances. Methods: This pre/post study compared airway placement metrics in prehospital patients requiring advance airway management for non-trauma-related conditions. Data from EMS records were extracted over 2 years, 12 months pre-pandemic, and 12 months post-pandemic. During the pre-COVID-19 year, the EMS protocols utilized ETI as the primary advanced airway device (ETI group). Post-pandemic paramedics were mandated to utilize i-gel® SGA as the primary advanced airway device to reduce exposure to secretions (SGA group). Results: There were 199 adult patients, 83 (42%) in the ETI group and 116 (58%) in the SGA group. First-pass success was significantly higher with SGA 96% (92%-99%) than ETI 68% (57%-78%) with paramedics citing the inability to visualize the airway in 52% of ETI cases. Time to first-pass success was significantly shorter in the SGA group (5.9 min [5.1-6.7 min]) than in the ETI group (8.3 min [6.9-9.6 min]), as was time to overall successful placement at 6.0 min (5.1-6.8 min) versus 9.6 min (8.2-11.1 min), respectively. Multiple placement attempts were required in 26% of ETI cases and 1% of the SGA cases. There were no statistically significant differences in the number and types of complications between the cohorts. Return of spontaneous circulation (on/before emergency department [ED] arrival), mortality at 28 days, intensive care unit length of stay, or ventilator-free days between the groups were not statistically different between the groups. Conclusion: In this natural experiment, the SGA performed significantly better than ETI in first-pass airway device placement success and was significantly faster in achieving first-pass success, and overall airway placement, thus potentially reducing exposure to respiratory pathogens. Practical real-world studies can offer important information about implementation of prehospital interventions, particularly in community settings and in systems with a low frequency of tracheal intubations.

Head Impact Exposure in Hawaiian High School Football: Influence of Adherence Rates on a Helmetless Tackling and Blocking Training Intervention.

CONTEXT: High school football remains a popular, physically demanding sport despite the known risks for acute brain and neck injury. Impacts to the head also raise concerns about their cumulative effects and long-term health consequences. OBJECTIVE: To examine the effectiveness of a helmetless tackling training program to reduce head impact exposure in football participants. DESIGN: A three-year, quasi-experimental, prospective cohort (clinicaltrials.gov #NCTXXX) study. SETTING: Honolulu (XXX, XXX) area public and private secondary schools with varsity and junior varsity football. PATIENTS OR OTHER PARTICIPANTS: Football participants (n=496) ages 14 to 18 years old. Intervention(s) Participants wore new football helmets furnished with head impact sensor technology. Teams employed a season-long helmetless tackling and blocking intervention in Years 2 and 3 consisting of a 3-phase, systematic progression of 10 instructional drills. MAIN OUTCOME MEASURE(S): Head impact frequency per athlete exposure (ImpAE), location, and impact magnitude per participant intervention adherence levels (60% and 80%). RESULTS: An overall regression analysis revealed a significant negative association between ImpAE and adherence (p=0.003, beta=-1.21, SE=0.41). In year 3, a longitudinal data analysis of weekly ImpAE data resulted in an overall difference between the adherent and non-adherent groups (p=0.040 at 80%; p=0.004 at 60%), mainly due to decreases in top and side impacts. Mean cumulative impact burden for the adherent group (n=131: 2,105.84g ± 219.76,) was significantly (p=0.020) less than the non-adherent group (n=90: 3,158.25g ± 434.80) at the 60% adherence level. CONCLUSIONS: Participants adhering to the intervention on at least a 60% level experienced a 34% to 37% significant reduction in the number of head impacts (per exposure) through the season. These results provide additional evidence that a helmetless tackling and blocking training intervention (utilizing the HuTT® program) reduces head impact exposure in high school football players. Adherence to an intervention is crucial for achieving intended outcomes.

Development and external validation of deep learning clinical prediction models using variable-length time series data.

OBJECTIVES: To compare and externally validate popular deep learning model architectures and data transformation methods for variable-length time series data in 3 clinical tasks (clinical deterioration, severe acute kidney injury [AKI], and suspected infection). MATERIALS AND METHODS: This multicenter retrospective study included admissions at 2 medical centers that spanned 2007-2022. Distinct datasets were created for each clinical task, with 1 site used for training and the other for testing. Three feature engineering methods (normalization, standardization, and piece-wise linear encoding with decision trees [PLE-DTs]) and 3 architectures (long short-term memory/gated recurrent unit [LSTM/GRU], temporal convolutional network, and time-distributed wrapper with convolutional neural network [TDW-CNN]) were compared in each clinical task. Model discrimination was evaluated using the area under the precision-recall curve (AUPRC) and the area under the receiver operating characteristic curve (AUROC). RESULTS: The study comprised 373 825 admissions for training and 256 128 admissions for testing. LSTM/GRU models tied with TDW-CNN models with both obtaining the highest mean AUPRC in 2 tasks, and LSTM/GRU had the highest mean AUROC across all tasks (deterioration: 0.81, AKI: 0.92, infection: 0.87). PLE-DT with LSTM/GRU achieved the highest AUPRC in all tasks. DISCUSSION: When externally validated in 3 clinical tasks, the LSTM/GRU model architecture with PLE-DT transformed data demonstrated the highest AUPRC in all tasks. Multiple models achieved similar performance when evaluated using AUROC. CONCLUSION: The LSTM architecture performs as well or better than some newer architectures, and PLE-DT may enhance the AUPRC in variable-length time series data for predicting clinical outcomes during external validation.

Social cognition differentiates phenocopy syndrome of behavioural variant frontotemporal dementia from behavioural variant frontotemporal dementia.

BACKGROUND: Patients displaying clinical features of behavioural variant of frontotemporal dementia (bvFTD) but lacking both neuroimaging abnormalities and clinical progression are considered to represent the phenocopy syndrome of bvFTD (phFTD). Extensive clinical overlap between early phase bvFTD and phFTD hampers diagnostic distinction. We aimed to assess the diagnostic value of clinician-rated, self-reported and caregiver-reported symptoms for clinical distinction between phFTD and bvFTD. METHODS: There were 33 phFTD and 95 probable bvFTD patients included in the study (total N = 128). Clinician-rated, self-reported tests and caregiver-reported symptoms were compared between phFTD and bvFTD on social cognition, behaviour, mood and activities of daily living (ADL). Scores were compared between groups, followed by multiple logistic regression analysis, adjusted for age and sex. Receiver operating characteristic curves were plotted to assess diagnostic value. RESULTS: Using clinician-rated and self-reported tests, phFTD patients performed better on facial emotion recognition and reported more depressive symptoms. Caregiver-reported behavioural symptoms indicated higher behavioural and ADL impairment in phFTD compared to bvFTD. Facial emotion recognition provided highest diagnostic accuracy for distinction of phFTD from bvFTD (area under the curve (AUC) 0.813 95% CI 0.735-0.892, P < 0.001, sensitivity 81%, specificity 74%) followed by depressive symptoms (AUC 0.769 95% 0.674-0.864, P < 0.001 sensitivity 81%, specificity of 63%). CONCLUSION: Social cognition tests are most suitable for distinction of phFTD from bvFTD. Caregiver-reported questionnaires and phFTD diagnosis seemed inversely correlated, showing more symptoms in phFTD. Further research is needed on phFTD aetiology and in caregivers taking into account disease burden to assess what explains this discrepancy between clinician-rated and caregiver-based tools.

Assessing the role of Chemokine (C-C motif) ligand 14 in AKI: a European consensus meeting.

BACKGROUND: Urinary Chemokine (C-C motif) ligand 14 (CCL14) is a biomarker associated with persistent severe acute kidney injury (AKI). There is limited data to support the implementation of this AKI biomarker to guide therapeutic actions. METHODS: Sixteen AKI experts with clinical CCL14 experience participated in a Delphi-based method to reach consensus on when and how to potentially use CCL14. Consensus was defined as ≥ 80% agreement (participants answered with 'Yes', or three to four points on a five-point Likert Scale). RESULTS: Key consensus areas for CCL14 test implementation were: identifying challenges and mitigations, developing a comprehensive protocol and pairing it with a treatment plan, and defining the target population. The majority agreed that CCL14 results can help to prioritize AKI management decisions. CCL14 levels above the high cutoff (> 13 ng/mL) significantly changed the level of concern for modifying the AKI treatment plan (p < 0.001). The highest level of concern to modify the treatment plan was for discussions on renal replacement therapy (RRT) initiation for CCL14 levels > 13 ng/mL. The level of concern for discussion on RRT initiation between High and Low, and between Medium and Low CCL14 levels, showed significant differences. CONCLUSION: Real world urinary CCL14 use appears to provide improved care options to patients at risk for persistent severe AKI. Experts believe there is a role for CCL14 in AKI management and it may potentially reduce AKI-disease burden. There is, however, an urgent need for evidence on treatment decisions and adjustments based on CCL14 results.

CCL14 testing to guide clinical practice in patients with AKI: Results from an international expert panel.

PURPOSE: Urinary C-C motif chemokine ligand 14 (CCL14) is a strong predictor of persistent stage 3 acute kidney injury (AKI). Multiple clinical actions are recommended for AKI but how these are applied in individual patients and how the CCL14 test results may impact their application is unknown. METHODS: We assembled an international panel of 12 experts and conducted a modified Delphi process to evaluate patients at risk for persistent stage 3 AKI (lasting 72 hours or longer). Using a Likert scale, we rated 11 clinical actions based on international guidelines applied to each case before and after CCL14 testing and analyzed the association between the strength and direction of recommendations and CCL14 results. RESULTS: The strength and direction of clinical recommendations were strongly influenced by CCL14 results (P < 0.001 for the interaction). Nine (82%) recommendations for clinical actions were significantly impacted by CCL14 results (P < 0.001 comparing low to highest CCL14 risk category). CONCLUSIONS: Most recommendations for care of patients with stage 2-3 by an international panel of experts were strongly modified by CCL14 test results. This work should set the stage for clinical practice protocols and studies to determine the effects of recommended actions informed by CCL14.

Explainable machine learning for predicting conversion to neurological disease: Results from 52,939 medical records.

Objective: This study assesses the application of interpretable machine learning modeling using electronic medical record data for the prediction of conversion to neurological disease. Methods: A retrospective dataset of Cleveland Clinic patients diagnosed with Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, or Parkinson's disease, and matched controls based on age, sex, race, and ethnicity was compiled. Individualized risk prediction models were created using eXtreme Gradient Boosting for each neurological disease at four timepoints in patient history. The prediction models were assessed for transparency and fairness. Results: At timepoints 0-months, 12-months, 24-months, and 60-months prior to diagnosis, Alzheimer's disease models achieved the area under the receiver operating characteristic curve on a holdout test dataset of 0.794, 0.742, 0.709, and 0.645; amyotrophic lateral sclerosis of 0.883, 0.710, 0.658, and 0.620; multiple sclerosis of 0.922, 0.877, 0.849, and 0.781; and Parkinson's disease of 0.809, 0.738, 0.700, and 0.651, respectively. Conclusions: The results demonstrate that electronic medical records contain latent information that can be used for risk stratification for neurological disorders. In particular, patient-reported outcomes, sleep assessments, falls data, additional disease diagnoses, and longitudinal changes in patient health, such as weight change, are important predictors.