Eosinophil recovery in hospitalized COVID-19 patients is associated with lower rates of ICU admission and in-hospital mortality: An observational cohort analysis.

BACKGROUND: Admission eosinopenia (<100 cells/µL) is associated with poor clinical outcomes in hospitalized COVID-19 patients. However, the effects of eosinophil recovery (defined as reaching ≥50 eosinophils/µL) during hospitalization on COVID-19 outcomes have been inconsistent. METHODS: The study included 1,831 patients admitted to UCLA hospitals between February 2020 and February 2021 with PCR-confirmed COVID-19. Using competing risk regression and modeling eosinophil recovery as a time-dependent covariate, we evaluated the longitudinal relationship between eosinophil recovery and in-hospital outcomes including ICU admission, need for mechanical ventilation, and in-hospital mortality. All analyses were adjusted for covariates including age, BMI, tobacco smoke exposure, comorbidities known to be risk factors for COVID-19 mortality, and treatments including dexamethasone and remdesivir. RESULTS: Eosinophil recovery was evaluated in patients with <50 eosinophils/µL on admission (n = 1282). These patients cumulatively amassed 11,633 hospital patient-days; 3,985 of those days qualified as eosinophil recovery events, which were represented by 781 patients achieving at least one instance of eosinophil recovery during hospitalization. Despite no significant difference in the rate of mechanical ventilation, eosinophil recoverers had significantly lower rates of in-hospital mortality (aHR: 0.44 [0.29, 0.65], P = 0.001) and ICU admission (aHR: 0.25 [0.11, 0.61], P = 0.002). CONCLUSION: Trending eosinophil counts during hospitalization is simple and can be performed in resource-limited healthcare settings to track the inflammatory status of a patient. Lack of eosinophil recovery events can identify those at risk for future progression to severe COVID.

Measuring the accuracy of cardiac output using POCUS: the introduction of artificial intelligence into routine care.

BACKGROUND: Shock management requires quick and reliable means to monitor the hemodynamic effects of fluid resuscitation. Point-of-care ultrasound (POCUS) is a relatively quick and non-invasive imaging technique capable of capturing cardiac output (CO) variations in acute settings. However, POCUS is plagued by variable operator skill and interpretation. Artificial intelligence may assist healthcare professionals obtain more objective and precise measurements during ultrasound imaging, thus increasing usability among users with varying experience. In this feasibility study, we compared the performance of novice POCUS users in measuring CO with manual techniques to a novel automation-assisted technique that provides real-time feedback to correct image acquisition for optimal aortic outflow velocity measurement. METHODS: 28 junior critical care trainees with limited experience in POCUS performed manual and automation-assisted CO measurements on a single healthy volunteer. CO measurements were obtained using left ventricular outflow tract (LVOT) velocity time integral (VTI) and LVOT diameter. Measurements obtained by study subjects were compared to those taken by board-certified echocardiographers. Comparative analyses were performed using Spearman's rank correlation and Bland-Altman matched-pairs analysis. RESULTS: Adequate image acquisition was 100% feasible. The correlation between manual and automated VTI values was not significant (p = 0.11) and means from both groups underestimated the mean values obtained by board-certified echocardiographers. Automated measurements of VTI in the trainee cohort were found to have more reproducibility, narrower measurement range (6.2 vs. 10.3 cm), and reduced standard deviation (1.98 vs. 2.33 cm) compared to manual measurements. The coefficient of variation across raters was 11.5%, 13.6% and 15.4% for board-certified echocardiographers, automated, and manual VTI tracing, respectively. CONCLUSIONS: Our study demonstrates that novel automation-assisted VTI is feasible and can decrease variability while increasing precision in CO measurement. These results support the use of artificial intelligence-augmented image acquisition in routine critical care ultrasound and may have a role for evaluating the response of CO to hemodynamic interventions. Further investigations into artificial intelligence-assisted ultrasound systems in clinical settings are warranted.

Chronic Obstructive Pulmonary Disease is Not Associated with In-Hospital Mortality in COVID-19: An Observational Cohort Analysis.

Background: Chronic obstructive pulmonary disease (COPD) is associated with worsened outcomes in COVID-19 (coronavirus disease 2019). However, data remain fraught with heterogeneity and bias from comorbid conditions. Additionally, data on the impact of COPD-specific factors, such as pre-hospital medications and pulmonologist involvement, remain sparse. Objective: We report a single-center analysis of COPD patients hospitalized with COVID-19 compared to those without COPD. Primary outcomes include ICU admission, mechanical ventilation, and in-hospital mortality. Methods: We evaluated all patients ≥40 years admitted with PCR-confirmed COVID-19 between February 2020 and February 2021. COPD was defined by documented ICD-10 diagnosis of COPD, confirmed smoking history, and active bronchodilator use. We compared outcomes between COPD patients and the remainder of the COVID-19 cohort. Multivariable analyses were adjusted for age, sex, smoking status, and comorbid conditions. Results: Of 1537 hospitalized COVID-19 patients, 122 (7.9%) carried a diagnosis of COPD. The COPD cohort was older (74 ± 13 vs 66 ± 15 years, P < 0.001) and more often former smokers (P < 0.001). Comorbid conditions including diabetes, cardiovascular disease, and kidney disease were more prevalent in the COPD group (P < 0.001). After adjusting for comorbid conditions, the COPD cohort had higher severity scores and trended towards fewer hospital-free days. Among patients with COPD, pre-hospital use of aspirin was associated with decreased ICU admissions (aHR 0.56, P = 0.049) and mechanical ventilation (aHR 0.25, P = 0.008), while LAMAs (long-acting muscarinic antagonists) were associated with decreased in-hospital mortality (aHR 0.34, P = 0.047). Involvement of pulmonology in pre-hospital management of COPD was not found to significantly affect outcomes. Conclusion: When corrected for comorbid illnesses, COPD was associated with more severe disease but not with increased ICU admission, mechanical ventilation, or in-hospital mortality rates. Among COPD patients, prehospital treatment with aspirin and COPD-directed therapies were associated with improved outcomes.

Clinical and neurocognitive outcomes after transcatheter aortic valve implantation (TAVI) with cerebral protection: initial experience with a novel dual-filter device in Southeast Asia.

INTRODUCTION: Transcatheter aortic valve implantation (TAVI) is increasingly performed in patients with severe aortic stenosis. A novel dual-filter system to reduce cerebral embolism during TAVI recently became available. We aimed to assess the feasibility, safety, and clinical and neurocognitive outcomes of TAVI with cerebral protection in Asian patients. METHODS: 40 consecutive patients undergoing TAVI with cerebral protection were enrolled. All procedures were performed via femoral access using the self-expanding Evolut R/PRO or Portico, or the balloon-expandable SAPIEN 3 bioprostheses. Baseline characteristics, procedural and clinical outcomes were recorded. Cognition was assessed at baseline and 30 days using the abbreviated mental test (AMT). RESULTS: The mean age of the patients (75% male) was 76.4 ± 8.4 years. TAVI was uncomplicated in all patients. The filter device was successfully deployed in 38 (95.0%) patients without safety issues. There was no stroke or death at 30 days, and the survival rate at nine months was 95.0%. There was no overall cognitive change (baseline vs. 30-day AMT: 9.2 ± 1.1 vs. 9.0 ± 1.5, p = 0.12), and only 1 (2.5%) patient developed impaired cognition at 30 days. Patients with a decreased AMT score at 30 days were significantly older than those without (82.1 ± 4.5 vs. 74.4 ± 7.7 years, p = 0.019). All patients with decreased AMT scores were aged ≥ 76 years. CONCLUSION: In this early Asian experience of TAVI under cerebral protection, the filter device was successfully deployed in 95% of patients, with 100% procedural success. There were no filter-related complications and no stroke or mortality at 30 days. Overall cognition was preserved, although increased age was associated with a decline in AMT score.

Cannabis consumption is associated with lower COVID-19 severity among hospitalized patients: a retrospective cohort analysis.

BACKGROUND: While cannabis is known to have immunomodulatory properties, the clinical consequences of its use on outcomes in COVID-19 have not been extensively evaluated. We aimed to assess whether cannabis users hospitalized for COVID-19 had improved outcomes compared to non-users. METHODS: We conducted a retrospective analysis of 1831 patients admitted to two medical centers in Southern California with a diagnosis of COVID-19. We evaluated outcomes including NIH COVID-19 Severity Score, need for supplemental oxygen, ICU (intensive care unit) admission, mechanical ventilation, length of hospitalization, and in-hospital death for cannabis users and non-users. Cannabis use was reported in the patient's social history. Propensity matching was used to account for differences in age, body-mass index, sex, race, tobacco smoking history, and comorbidities known to be risk factors for COVID-19 mortality between cannabis users and non-users. RESULTS: Of 1831 patients admitted with COVID-19, 69 patients reported active cannabis use (4% of the cohort). Active users were younger (44 years vs. 62 years, p < 0.001), less often diabetic (23.2% vs 37.2%, p < 0.021), and more frequently active tobacco smokers (20.3% vs. 4.1%, p < 0.001) compared to non-users. Notably, active users had lower levels of inflammatory markers upon admission than non-users-CRP (C-reactive protein) (3.7 mg/L vs 7.6 mg/L, p < 0.001), ferritin (282 µg/L vs 622 µg/L, p < 0.001), D-dimer (468 ng/mL vs 1140 ng/mL, p = 0.017), and procalcitonin (0.10 ng/mL vs 0.15 ng/mL, p = 0.001). Based on univariate analysis, cannabis users had significantly better outcomes compared to non-users as reflected in lower NIH scores (5.1 vs 6.0, p < 0.001), shorter hospitalization (4 days vs 6 days, p < 0.001), lower ICU admission rates (12% vs 31%, p < 0.001), and less need for mechanical ventilation (6% vs 17%, p = 0.027). Using propensity matching, differences in overall survival were not statistically significant between cannabis users and non-users, nevertheless ICU admission was 12 percentage points lower (p = 0.018) and intubation rates were 6 percentage points lower (p = 0.017) in cannabis users. CONCLUSIONS: This retrospective cohort study suggests that active cannabis users hospitalized with COVID-19 had better clinical outcomes compared with non-users, including decreased need for ICU admission or mechanical ventilation. However, our results need to be interpreted with caution given the limitations of a retrospective analysis. Prospective and observational studies will better elucidate the effects cannabis use in COVID-19 patients.

Discovering dominant tumor immune archetypes in a pan-cancer census.

Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.

Feasibility of a wearable biosensor device to characterize exercise and sleep in neurology residents.

BACKGROUND: Research suggests optimizing sleep, exercise and work-life balance may improve resident physician burnout. Wearable biosensors may allow residents to detect and correct poor sleep and exercise habits before burnout develops. Our objectives were to evaluate the feasibility of a wearable biosensor to characterize exercise/sleep in neurology residents and examine its relationship to self-reported, validated survey measures. We also assessed the device's impact on well-being and barriers to use. METHODS: This prospective cohort study evaluated the WHOOP Strap 2.0 in neurology residents. Participants completed regular online surveys, including self-reported hours of sleep/exercise, and validated sleep/exercise scales at 3-month intervals. Autonomic, exercise, and sleep measures were obtained from WHOOP. Changes were evaluated over time via linear regression. Survey and WHOOP metrics were compared using Pearson correlations. RESULTS: Sixteen (72.7%) of 22 eligible participants enrolled. Eleven (68.8%) met the minimum usage requirement (6+ months) and were classified as 'consecutive wearers.' Significant increases were found in sleep duration and exercise intensity. Moderate-to-low correlations were found between survey responses and WHOOP measures. Most (73%) participants reported a positive impact on well-being. Barriers to use included 'Forgetting to wear' (20%) and 'not motivational' (23.3%). CONCLUSION: Wearable biosensors may be a feasible tool to evaluate sleep/exercise in residents.

A journey into the unknown: An ethnographic examination of drug-resistant epilepsy treatment and management in the United States.

Patients often recognize unmet needs that can improve patient-provider experiences in disease treatment management. These needs are rarely captured and may be hard to quantify in difficult-to-treat disease states such as drug-resistant epilepsy (DRE). To further understand challenges living with and managing DRE, a team of medical anthropologists conducted ethnographic field assessments with patients to qualitatively understand their experience with DRE across the United States. In addition, healthcare provider assessments were conducted in community clinics and Comprehensive Epilepsy Centers to further uncover patient-provider treatment gaps. We identified four distinct stages of the treatment and management journey defined by patients' perceived control over their epilepsy: Gripped in the Panic Zone, Diligently Tracking to Plan, Riding a Rollercoaster in the Dark, and Reframing Priorities to Redefine Treatment Success. We found that patients sought resources to streamline communication with their care team, enhanced education on treatment options beyond medications, and long-term resources to protect against a decline in control over managing their epilepsy once drug-resistant. Likewise, treatment management optimization strategies are provided to improve current DRE standard of care with respect to identified patient-provider gaps. These include the use of digital disease management tools, standardizing neuropsychiatrists into patients' initial care team, and introducing surgical and non-pharmacological treatment options upon epilepsy and DRE diagnoses, respectively. This ethnographic study uncovers numerous patient-provider gaps, thereby presenting a conceptual framework to advance DRE treatment. Further Incentivization from professional societies and healthcare systems to support standardization of the treatment optimization strategies provided herein into clinical practice is needed.

The effects of white noise on sleep and duration in individuals living in a high noise environment in New York City.

INTRODUCTION: Undisturbed sleep has been shown to be important for both health and quality of life (Medic et al. [7]). The World Health Organization estimates that nearly 25% of the population suffers from disturbed sleep due to environmental noise (Health TWECfEa, [2]). Sleep disturbance associated with elevated noise levels is particularly prevalent in metropolitan areas. Our study tested the hypothesis that white noise would improve sleep in New Yorkers complaining of sleep difficulty due to elevated sound levels. METHODS: Ten adult participants were included in this study. All participants were recruited from a New York City based sleep clinic. Inclusion criteria was based on the presence of sleep disturbance and the reporting of high levels of environmental noise in participants' sleep location. The study was conducted using a within-subject, ABA design, with baseline, treatment phase, followed by another baseline (washout) period. Each phase lasted one-week, during which noise level and sleep were assessed. The treatment consisted of the application of a white noise device (Dohm Classic by Marpac, LLC) in the participants' bedroom. Sleep parameters were measured subjectively using the Consensus Sleep Diary (Carney et al. [15]), and objectively using a Motionlogger Actigraph. RESULTS: Paired sample t-tests were conducted to evaluate the hypothesis that white noise improves sleep in a high noise environment. Significance was found on the variables WASO, as measured by actigraphy, t(9) = 3.438, p = 0.007 and sleep latency as measured by sleep diary, t(9) = 2.947, p = 0.016. There was a trend toward significance on the number of awakenings during the night, as measured by sleep diary, t(9) = 2.622, p = 0.028 (Holm's sequential correction of p-value required a value of <0.01 to find significance on this comparison) and sleep efficiency (actigraph), t(9) = -2.121, p = 0.063. CONCLUSION: Our data show that white noise significantly improved sleep based on subjective and objective measurements in subjects complaining of difficulty sleeping due to high levels of environmental noise. This suggests that the application of white noise may be an effective tool in helping to improve sleep in those settings.

Education Research: NeuroBytes: A New Rapid, High-Yield e-Learning Platform for Continuing Professional Development in Neurology.

OBJECTIVE: To determine whether NeuroBytes is a helpful e-Learning tool in neurology through usage, viewer type, estimated time and cost of development, and postcourse survey responses. BACKGROUND: A sustainable Continuing Professional Development (CPD) system is vital in neurology due to the field's expanding therapeutic options and vulnerable patient populations. In an effort to offer concise, evidence-based updates to a wide range of neurology professionals, the American Academy of Neurology (AAN) launched NeuroBytes in 2018. NeuroBytes are brief (<5 minutes) videos that provide high-yield updates to AAN members. METHODS: NeuroBytes was beta tested from August 2018 to December 2018 and launched for pilot circulation from January 2019 to April 2019. Usage was assessed by quantifying course enrollment and completion rates; feasibility by cost and time required to design and release a module; appeal by user satisfaction; and effect by self-reported change in practice. RESULTS: A total of 5,130 NeuroBytes enrollments (1,026 ± 551/mo) occurred from January 11, 2019, to May 28, 2019, with a median of 588 enrollments per module (interquartile range, 194-922) and 37% course completion. The majority of viewers were neurologists (54%), neurologists in training (26%), and students (8%). NeuroBytes took 59 hours to develop at an estimated $77.94/h. Of the 1,895 users who completed the survey, 82% were "extremely" or "very likely" to recommend NeuroBytes to a colleague and 60% agreed that the depth of educational content was "just right." CONCLUSIONS: NeuroBytes is a user-friendly, easily accessible CPD product that delivers concise updates to a broad range of neurology practitioners and trainees. Future efforts will explore models where NeuroBytes combines with other CPD programs to affect quality of training and clinical practice.

An Anti-CD22-seco-CBI-Dimer Antibody-Drug Conjugate (ADC) for the Treatment of Non-Hodgkin Lymphoma That Provides a Longer Duration of Response than Auristatin-Based ADCs in Preclinical Models.

We are interested in developing a second generation of antibody-drug conjugates (ADCs) for the treatment of non-Hodgkin lymphoma (NHL) that could provide a longer duration of response and be more effective in indolent NHL than the microtubule-inhibiting ADCs pinatuzumab vedotin [anti-CD22-vc-monomethyl auristatin E (MMAE)] and polatuzumab vedotin (anti-CD79b-vc-MMAE). Pinatuzumab vedotin (anti-CD22-vc-MMAE) and polatuzumab vedotin (anti-CD79b-vc-MMAE) are ADCs that contain the microtubule inhibitor MMAE. Clinical trial data suggest that these ADCs have promising efficacy for the treatment of NHL; however, some patients do not respond or become resistant to the ADCs. We tested an anti-CD22 ADC with a seco-CBI-dimer payload, thio-Hu anti-CD22-(LC:K149C)-SN36248, and compared it with pinatuzumab vedotin for its efficacy and duration of response in xenograft models and its ability to deplete normal B cells in cynomolgus monkeys. We found that anti-CD22-(LC:K149C)-SN36248 was effective in xenograft models resistant to pinatuzumab vedotin, gave a longer duration of response, had a different mechanism of resistance, and was able to deplete normal B cells better than pinatuzumab vedotin. These studies provide evidence that anti-CD22-(LC:K149C)-SN36248 has the potential for longer duration of response and more efficacy in indolent NHL than MMAE ADCs and may provide the opportunity to improve outcomes for patients with NHL.

SCENITH: A Flow Cytometry-Based Method to Functionally Profile Energy Metabolism with Single-Cell Resolution.

Energetic metabolism reprogramming is critical for cancer and immune responses. Current methods to functionally profile the global metabolic capacities and dependencies of cells are performed in bulk. We designed a simple method for complex metabolic profiling called SCENITH, for single-cell energetic metabolism by profiling translation inhibition. SCENITH allows for the study of metabolic responses in multiple cell types in parallel by flow cytometry. SCENITH is designed to perform metabolic studies ex vivo, particularly for rare cells in whole blood samples, avoiding metabolic biases introduced by culture media. We analyzed myeloid cells in solid tumors from patients and identified variable metabolic profiles, in ways that are not linked to their lineage or their activation phenotype. SCENITH's ability to reveal global metabolic functions and determine complex and linked immune-phenotypes in rare cell subpopulations will contribute to the information needed for evaluating therapeutic responses or patient stratification.

Automated spectrographic seizure detection using convolutional neural networks.

PURPOSE: Non-convulsive seizures are common in critically ill patients, and delays in diagnosis contribute to increased morbidity and mortality. Many intensive care units employ continuous EEG (cEEG) for seizure monitoring. Although cEEG is continuously recorded, it is often reviewed intermittently, which may delay seizure diagnosis and treatment. This may be mitigated with automated seizure detection. In this study, we develop and evaluate convolutional neural networks (CNN) to automate seizure detection on EEG spectrograms. METHODS: Adult EEGs (12 patients, 12 EEGs, 33 seizures) from New-York Presbyterian Hospital (NYP) and pediatric EEGs (22 patients, 130 EEGs, 177 seizures) from Children's Hospital Boston (CHB) were converted into spectrograms. To simulate a telemetry display, seizure and non-seizure events on spectrograms were sequentially sampled as images across a detection window (26,380 total images). Four CNN models of increasing complexity (number of layers) were trained, cross-validated, and tested on CHB and NYP spectrographic images. All CNNs were based on the VGG-net architecture, with adjustments to alleviate overfitting. RESULTS: For spectrographically visible seizures, two CNN models (containing 4 and 7 convolution layers) achieved >90% seizure detection sensitivity and specificity on the CHB test set and >90% sensitivity and 75-80% specificity on the NYP test set. The one CNN model (10 convolution layers) did not converge during training; while another CNN (2 convolution layers) performed poorly (60% sensitivity and 32% specificity) on the NYP test set. CONCLUSIONS: Seizure detection on EEG spectrograms with CNN models is feasible with sensitivity and specificity potentially suitable for clinical use.

Evaluation of a novel median power spectrogram for seizure detection by non-neurophysiologists.

PURPOSE: (1) To evaluate how well resident physicians use a novel EEG spectral analysis tool (the median power spectrogram; MPS) to detect seizures. (2) To assess the capability of the MPS to identify different seizure types. METHODS: 120 EEG records from children with intractable seizures were converted to MPS by taking the median power across leads and using multi-taper spectral estimation. Twelve blinded neurology residents were trained to interpret the spectrogram with a five-minute video tutorial and post-test. Two residents independently assessed each set for presence of seizures. Their performance was compared to seizures identified using conventional EEG. Two blinded neurologists separately reviewed the EEGs and spectrograms to independently categorize the seizures. Their results were used to determine the spectrogram's capability to reveal seizures and visualize different seizure types for the user. RESULTS: Three key MPS features distinguished seizures from inter-ictal background: power difference relative to background, down-sloping resonance bands, and power in high frequencies. Using these features, residents identified seizures with 77% sensitivity and 72% specificity. 86% (51/59) of focal seizures and 81% (22/27) of generalized seizures were detected by at least one resident. Missed seizures included brief (<60s) seizures, tonic seizures, seizures with predominant delta (0-4Hz) activity, and seizures evident primarily in supplementary low temporal leads. CONCLUSIONS: The MPS is a novel qEEG modality that requires minimal training to interpret. It enables physicians without extensive neurophysiology training to identify seizures with sensitivity and specificity comparable to more complex multi-modal qEEG displays.

Mapping Novel Metabolic Nodes Targeted by Anti-Cancer Drugs that Impair Triple-Negative Breast Cancer Pathogenicity.

Triple-negative breast cancers (TNBCs) are estrogen receptor, progesterone receptor, and HER2 receptor-negative subtypes of breast cancers that show the worst prognoses and lack targeted therapies. Here, we have coupled the screening of ∼400 anticancer agents that are under development or in the clinic with chemoproteomic and metabolomic profiling to identify novel metabolic mechanisms for agents that impair TNBC pathogenicity. We identify 20 anticancer compounds that significantly impaired cell survival across multiple types of TNBC cells. Among these 20 leads, the phytoestrogenic natural product licochalcone A was of interest, since TNBCs are unresponsive to estrogenic therapies, indicating that licochalcone A was likely acting through another target. Using chemoproteomic profiling approaches, we reveal that licochalcone A impairs TNBC pathogenicity, not through modulating estrogen receptor activity but rather through inhibiting prostaglandin reductase 1, a metabolic enzyme involved in leukotriene B4 inactivation. We also more broadly performed metabolomic profiling to map additional metabolic mechanisms of compounds that impair TNBC pathogenicity. Overlaying lipidomic profiling with drug responses, we find that deubiquitinase inhibitors cause dramatic elevations in acyl carnitine levels, which impair mitochondrial respiration and contribute to TNBC pathogenic impairments. We thus put forth two unique metabolic nodes that are targeted by drugs or drug candidates that impair TNBC pathogenicity. Our results also showcase the utility of coupling drug screens with chemoproteomic and metabolomic profiling to uncover unique metabolic drivers of TNBC pathogenicity.

Guiding Principles for a Pediatric Neurology ICU (neuroPICU) Bedside Multimodal Monitor: Findings from an International Working Group.

BACKGROUND: Physicians caring for children with serious acute neurologic disease must process overwhelming amounts of physiological and medical information. Strategies to optimize real time display of this information are understudied. OBJECTIVES: Our goal was to engage clinical and engineering experts to develop guiding principles for creating a pediatric neurology intensive care unit (neuroPICU) monitor that integrates and displays data from multiple sources in an intuitive and informative manner. METHODS: To accomplish this goal, an international group of physicians and engineers communicated regularly for one year. We integrated findings from clinical observations, interviews, a survey, signal processing, and visualization exercises to develop a concept for a neuroPICU display. RESULTS: Key conclusions from our efforts include: (1) A neuroPICU display should support (a) rapid review of retrospective time series (i.e. cardiac, pulmonary, and neurologic physiology data), (b) rapidly modifiable formats for viewing that data according to the specialty of the reviewer, and (c) communication of the degree of risk of clinical decline. (2) Specialized visualizations of physiologic parameters can highlight abnormalities in multivariable temporal data. Examples include 3-D stacked spider plots and color coded time series plots. (3) Visual summaries of EEG with spectral tools (i.e. hemispheric asymmetry and median power) can highlight seizures via patient-specific "fingerprints." (4) Intuitive displays should emphasize subsets of physiology and processed EEG data to provide a rapid gestalt of the current status and medical stability of a patient. CONCLUSIONS: A well-designed neuroPICU display must present multiple datasets in dynamic, flexible, and informative views to accommodate clinicians from multiple disciplines in a variety of clinical scenarios.

Statin-centric versus low-density lipoprotein-centric approach for atherosclerotic cardiovascular disease prevention: a Singapore perspective.

The link between cholesterol levels and atherosclerotic cardiovascular disease (ASCVD) is well-established. In Singapore, there is an increasing prevalence of risk factors for ASCVD. Like many Asian countries, Singapore's population is rapidly ageing and increasingly sedentary, which predisposes individuals to chronic health problems. Current international and local guidelines recommend statin therapy for the primary and secondary prevention of ASCVD. However, despite the effectiveness of statin therapy, some studies have highlighted that Asian patients with cardiovascular disease are not achieving target lipid goals. Furthermore, it is widely believed that the responses of Asians (both patients and physicians) to statin therapy are different from those of their Western counterparts. Experts convened in 2014 to determine the impact of current guidelines on clinical practice in Singapore. This review summarises the key findings and recommendations of these guidelines, and presents key principles to aid clinicians to manage the cardiovascular risk of their patients more effectively.

Protein Sialylation Regulates a Gene Expression Signature that Promotes Breast Cancer Cell Pathogenicity.

Many mechanisms have been proposed for how heightened aerobic glycolytic metabolism fuels cancer pathogenicity, but there are still many unexplored pathways. Here, we have performed metabolomic profiling to map glucose incorporation into metabolic pathways upon transformation of mammary epithelial cells by 11 commonly mutated human oncogenes. We show that transformation of mammary epithelial cells by oncogenic stimuli commonly shunts glucose-derived carbons into synthesis of sialic acid, a hexosamine pathway metabolite that is converted to CMP-sialic acid by cytidine monophosphate N-acetylneuraminic acid synthase (CMAS) as a precursor to glycoprotein and glycolipid sialylation. We show that CMAS knockdown leads to elevations in intracellular sialic acid levels, a depletion of cellular sialylation, and alterations in the expression of many cancer-relevant genes to impair breast cancer pathogenicity. Our study reveals the heretofore unrecognized role of sialic acid metabolism and protein sialylation in regulating the expression of genes that maintain breast cancer pathogenicity.

Beyond neuropathic pain: gabapentin use in cancer pain and perioperative pain.

BACKGROUND: Gabapentin (GBP), originally an antiepileptic drug, is more commonly used in the treatment of neuropathic pain. In recent years, GBP has been used as an adjunct or primary therapy in non-neuropathic pain, most commonly for the treatment of perioperative and cancer pain. OBJECTIVES: The aim of this study was to conduct a clinical evidence literature review of GBP's use in perioperative pain and cancer pain. METHODS: Using PUBMED and OVID Medline databases, keyword searches for surgery and cancer in reference to GBP and pain were carried out. Nonblinded studies and case reports that did not present a unique finding were excluded. Studies that focused only on neuropathic pain were also excluded. RESULTS: An initial 142 references focusing on GBP's use in surgical pain and cancer pain were identified. Of these, 48 studies were quality of evidence at a level of II-2 or higher. DISCUSSION: Although efficacy varies, multiple well-designed clinical trials have demonstrated reduced pain and analgesic use with otolaryngology, orthopedic, mastectomy, and abdominal/pelvic surgical perioperative use of GBP, whereas there is limited or no efficacy for cardiothoracic surgery. Cancer pain studies have had greater design variability, often nonblinded, with pain benefit being mild to moderate, and more efficacious with partial neuropathic pain quality. Overall, GBP seems to have significant benefit in neuropathic and non-neuropathic pain associated with the perioperative period and cancer. Considering its favorable side effect profile, GBP represents a beneficial pain adjunctive therapy, beyond neuropathic symptoms.

Development and validation of a novel method to derive central aortic systolic pressure from the radial pressure waveform using an n-point moving average method.

OBJECTIVES: The purpose of this study was to develop and validate the novel application of a simple n-point moving average (NPMA)--a mathematical low pass filter--to noninvasively derive central aortic systolic pressure (CASP) from the radial artery pressure waveform (RAPWF) in humans. BACKGROUND: CASP may be an important independent determinant of clinical outcomes. Development of simple, well-validated methods to noninvasively derive CASP is necessary to facilitate the routine clinical measurement of CASP. METHODS: Three studies in different population cohorts were used to develop and validate the NPMA method to derive CASP in humans: 1) a development study (n = 217), describing the optimal application of the NPMA to derive CASP; 2) a validation study comparing NPMA-CASP with CASP derived using a generalized transfer function (GTF-CASP [SphygmoCor system, AtCor, Sydney, Australia]) using 5,349 RAPWFs from the CAFE (Conduit Artery Function Evaluation) study; and 3) an invasive validation study (n = 20) comparing NPMA-CASP with direct aortic root pressure measurements during cardiac catheterization. RESULTS: In the development study, when using the NPMA, a denominator of n/4 (where n = tonometer sampling frequency) most accurately defined CASP relative to GTF-CASP. Validation of NPMA-CASP using RAPWFs from the CAFE study revealed excellent correlation and agreement (r(2) = 0.993, mean difference 0.3 ± 1.0 mm Hg). The agreement remained robust after stratification by sex, age, treatment, and diabetes status. There was also excellent correlation and agreement (r(2) = 0.98, p < 0.001) between directly measured aortic root systolic pressures (Millar's catheter) at cardiac catheterization versus NPMA-CASP, derived simultaneously from noninvasive RAPWFs. CONCLUSIONS: We show that an NPMA with a denominator of one-quarter of the tonometer sampling frequency accurately defines CASP when applied to noninvasively acquired RAPWFs in man. These novel findings have important implications for the simplification of noninvasive CASP measurement and its wider application in clinical trials and clinical practice.