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Flow cytometry of the cerebrospinal fluid (CSF) is used in isolation or as an adjunct to cytology to increase the sensitivity of detecting primary central nervous system (CNS) lymphoma. We aim to evaluate the sensitivity of CSF flow cytometry as a diagnostic tool for primary CNS lymphoma in patients presenting with undifferentiated neurologic symptoms. We retrospectively reviewed all CSF samples received by the Calgary Laboratory Services Flow Cytometry Laboratory from 2012- 2015. Clinical data, laboratory investigations, radiologic imaging studies, and pathological data were analyzed. Clinical review extended to 2 years post CSF flow cytometric testing. The number of samples of CSF flow cytometry that were positive for a hematological malignancy was 43/763 (5.6%). The overall sensitivity of the test was 69.4%. A positive result was more likely to occur in patients with a prior history of a hematological malignancy or abnormal enhancement on MRI (p<0.0001). CSF flow cytometry was negative in all patients who did not have a previous hematological malignancy or abnormal enhancement on MRI (n = 247). CSF flow cytometry has a limited role in screening for primary CNS lymphoma, unless a strictly endorsed testing algorithm is applied. It is, however, an invaluable tool in evaluating CNS involvement in patients with a previous diagnosis of hematolymphoid malignancy or abnormal enhancement on MRI.
This presentation will enable the learner to:
Discuss the costs and benefits of using CSF flow cytometry to diagnose CNS lymphoma
1. Identify appropriate clinical indications for using CSF flow cytometry as a first-line test
2. Apply a testing algorithm to increase the diagnostic yield of CSF flow cytometry
Digital platform business models are disrupting traditional business processes and reveal a new way of creating value. Current validation processes for business models are designed to assess pipeline business models. They cannot grasp the logic of digital platforms, which increasingly integrate Artificial Intelligence (AI) to ensure success. This study developed a new validation process for early market validation of digital platform business models by following the Design Science Research methodology. The designed process, the Smart Platform Experiment Cycle (SPEC), is created by combining the Four-Step Iterative Cycle of business experiments, the Customer Development Process, and the Build-Measure-Learn feedback loop of the Lean Startup approach and enriching it with the knowledge of digital platforms. It consists of five iterative steps showing the startup how to design their platform business model and corresponding experiments and how to run, measure, analyze, and learn from the outcomes and results. To assess its efficacy, applicability, and validity, SPEC was applied in the German startup GassiAlarm, a service marketplace business model. The application of SPEC revealed shortcomings in the pricing strategy and highlighted to what extent their current business model would be successful. SPEC reduces the risk of building a product or service the market deems redundant and gives insights into its success rate. More applications of the SPEC are needed to validate its robustness further and to extend it to other types of digital platform business models for improved generalization.
We hypothesized healthcare workers (HCW) with high-risk exposures outside the healthcare system would have less asymptomatic coronavirus 2019 (COVID-19) disease and more symptoms than those without such exposures.
A longitudinal point prevalence study during August 17- September 4 2020 and December 2nd - 23rd.
Community based teaching health system
All HCS were invited to participate. Among HCW who acquired COVID-19, logistic regression models were used to evaluate the adjusted odds of asymptomatic disease using high-risk exposure outside the healthcare system as the explanatory variable. The number of symptoms between exposure groups was evaluated with the Wilcoxon rank-sum test. The risk of seropositivity among all HCS by work exposure was evaluated during both periods.
Survey and serological testing
Seroprevalence increased from 1.9% (95% CI 1.2% - 2.6%) to 13.7% (95% CI 11.9% - 15.5%) during the study. Only during Period 2 did HCW with the highest work exposure (versus low exposure) have an increased risk of seropositivity (RD 7% [95% CI 1% -13%]). Participants who had a high-risk exposure outside of work (compared to those without) had a decreased probability of asymptomatic disease (OR 0.38 [95% CI 0.16 – 0.86]) and demonstrated more symptoms (median of 3 [IQR 5] vs 1 [IQR 2]; P = 0.001).
Health care acquired COVID-19 increases the probability of asymptomatic or mild COVID-19 disease compared to community acquired disease. This suggests infection prevention strategies (including masks and eye protection) may be mitigating inoculum and supports the variolation theory in COVID-19.
MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.
We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.
The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.
Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.
This study evaluated the relationships between the occurrence of recent and recurring natural disasters on the incidence of acute and chronic health outcomes at the census tract level in 500 cities across the United States between 2001 and 2015.
Using the Centers for Disease Control and Prevention (CDC) 500 cities data set, the CDC Social Vulnerability Index, and the US Small Business Administration (SBA) Disaster Loan Database, we modeled the incidence of self-reported, poor mental and physical health, or a clinical diagnosis of high blood pressure or asthma in census tracts (N = 27 204 tracts in 500 cities) that had experienced recent or recurring natural disasters while controlling for social and environmental risk factors.
Communities that experienced a natural disaster in the previous 5 years compared to those that had not had a higher incidence of poor mental health (RR: 1.02, 95% CI: 1.01-1.02), poor physical health (RR: 1.03, 95% CI: 1.02-1.04), high blood pressure (RR: 1.04, 95% CI: 1.02-1.05), and asthma (RR: 1.01, 95% CI: 1.01-1.02). The incidence of these poor health outcomes increased 1-2% with each additional year that a community experienced a disaster.
Prevention and preparedness plans that work to build resilience in communities before disasters should focus on closing the gap in environmental and social determinants that have been linked with disproportionate health burdens and slow recovery post-disaster.
ABSTRACT IMPACT: This work will develop a novel drug delivery system that has improved biocompatibility and controlled release than current systems and allow for customizable loading and drug delivery to unique patient and treatment requirements. OBJECTIVES/GOALS: The goal of my project is a novel hybrid core/shell nanoparticle system for controlling in vivo chemotherapeutic concentration. The current goal is to confirm core and shell polymeric nanoparticle formation via emulsion technique and validate predictive model developed to optimize shell formation efficiency and control shell thickness. METHODS/STUDY POPULATION: Though early results are promising, they are not proof that the desired core/shell structure is being formed via my novel process. I constructed a theoretical model to use to optimize and control the process for precise shell thicknesses. Therefore, the current experimental plan focus is to not only visually confirm the predicted formation of my core/shell design but use these experiments to validate the model.
1. Gel-Suspended SEM: nanoparticles suspended in gel matrix, bisected to reveal inner structure
2. Fluorescent Conjugation Microscopy: visually-distinct dyes used to show polymer distribution and validated against the theoretical model predictions.
3. Modified Hydrophobic Dye Release: different mixtures of polymers with release showing if previous promising results due to core/shell structure RESULTS/ANTICIPATED RESULTS: As stated, the experiments will confirm the core/shell nanoparticle structure, validate the developed theoretical model, or provide direct evidence against any formation. This core/shell structure is key to the current design for controlling payload release rate and thus in vivo drug concentration. For the gel-suspension experiment, the interior core will be labeled with ultrasmall SPIONs and thus any layers within the particles will be distinct. While this result is qualitative, high magnification fluorescent microscope images will be analyzed using image processing software to determine core/shell formation efficiency and compared to estimated efficiencies from the model. Finally, the mixed release will clarify previous experiments’ release mechanism and either support or disprove shell influence. DISCUSSION/SIGNIFICANCE OF FINDINGS: The significance of this work is twofold: core/shell particles have been proven to provide variable control of release on the micron scale but not yet at the nanoscale, allowing for a circulating, targeted system that can finely control release. The process is also novel for producing this type of structure, at highly consistent quality and size.
ABSTRACT IMPACT: E-values can help quantify the amount of unmeasured confounded necessary to fully explain away a relationship between treatment and outcomes in observational data. OBJECTIVES/GOALS: Older patients with HL have worse outcomes than younger patients, which may reflect treatment choice (e.g., fewer chemotherapy cycles). We studied the relationship between treatment intensity and 3-year overall survival (OS) in SEER-Medicare. We calculated an E-value to quantify the unmeasured confounding needed to explain away any relationship. METHODS/STUDY POPULATION: This retrospective cohort study of SEER-Medicare data from 1999-2016 included 1131 patients diagnosed with advanced stage HL at age ≥65 years. Treatment was categorized as: (1) full chemotherapy regimens (‘full regimen’, n=689); (2) partial chemotherapy regimen (‘partial regimen’, n=175); (3) single chemotherapy agent or radiotherapy (‘single agent/RT’, n=102), or (4) no treatment (n=165). A multivariable Cox regression model estimated the relationship between treatment and 3-year OS, adjusting for disease and patient factors. An E-value was computed to quantify the minimum strength of association that an unmeasured confounder would need to have with both the treatment and OS to completely explain away a significant association between treatment and OS based on the multivariable model. RESULTS/ANTICIPATED RESULTS: Results from the multivariable model found higher hazards of death for partial regimens (HR=1.81, 95% CI=1.43, 2.29), single agent/RT (HR=1.74, 95% CI=1.30, 2.34), or no treatment (HR=1.98, 95% CI=1.56, 2.552) compared to full regimens. We calculated an E-value for single agent/RT because it has the smallest HR of the treatment levels. The observed HR of 1.74 could be explained away by an unmeasured confounder that was associated with both treatment and OS with a HR of 2.29, above and beyond the measured confounders; the 95% CI could be moved to include the null by an unmeasured confounder that was associated with both the treatment and OS with a HR of 1.69. Of the measured confounders, B symptoms had the strongest relationship with treatment (HR=2.08) and OS (HR=1.38), which was below the E-value. DISCUSSION/SIGNIFICANCE OF FINDINGS: Patients with advanced stage HL who did not receive full chemotherapy regimens had worse 3-year OS, even after adjusting for potential confounders related to the patient and disease. The E-value analysis made explicit the amount of unmeasured confounding necessary to fully explain away the relationship between treatment and OS.
Hereditary transthyretin-mediated (hATTR) amyloidosis is a progressive disease caused by mutations in the TTR gene leading to multisystem organ dysfunction. Pathogenic TTR aggregation, misfolding, and fibrillization lead to deposition of amyloid in multiple body organs and frequently involve the peripheral nerve system and the heart. Common neurologic manifestations include: sensorimotor polyneuropathy (PN), autonomic neuropathy, small-fiber PN, and carpal tunnel syndrome. Many patients have significant progression due to diagnostic delays as hATTR PN is not considered within the differential diagnosis. Recently, two effective novel disease-modifying therapies, inotersen and patisiran, were approved by Health Canada for the treatment of hATTR PN. Early diagnosis is crucial for the timely introduction of these disease-modifying treatments that reduce impairments, improve quality of life, and extend survival. In this guideline, we aim to improve awareness and outcomes of hATTR PN by making recommendations directed to the diagnosis, monitoring, and treatment in Canada.
In the group testing problem the aim is to identify a small set of k ⁓ nθ infected individuals out of a population size n, 0 < θ < 1. We avail ourselves of a test procedure capable of testing groups of individuals, with the test returning a positive result if and only if at least one individual in the group is infected. The aim is to devise a test design with as few tests as possible so that the set of infected individuals can be identified correctly with high probability. We establish an explicit sharp information-theoretic/algorithmic phase transition minf for non-adaptive group testing, where all tests are conducted in parallel. Thus with more than minf tests the infected individuals can be identified in polynomial time with high probability, while learning the set of infected individuals is information-theoretically impossible with fewer tests. In addition, we develop an optimal adaptive scheme where the tests are conducted in two stages.
In 2008 and 2020, the Congregation for the Doctrine of the Faith published two responses to questions posed regarding the validity of modified baptismal formulas. When administering baptism, some Catholic ministers had altered the prescribed formula with regard to the naming of the Trinity and with regard to the declarative introduction of the formula (ie ‘We baptise you …’ instead of ‘I baptise you …’). The Congregation dismissed all of these formulas as invalidating baptism and demanded that individuals baptised with these formulas be baptised again. In explaining its 2020 response the Congregation referred to Thomas Aquinas, who addressed these and similar issues in his sacramental theology. This reference is evidently due to Aquinas’ pioneering thoughts on the issue. However, in studying Aquinas’ work on the subject it is surprising to find that they reveal a far less literalist approach than the Congregation suggests. In fact, his considerations point at an alternative reading, namely that sacramental formulas should be understood as acts of communication which, based on the ministers’ intention of doing what the Church does, aim at communicating God's grace to the receivers in an understandable way.
Wild-type transthyretin amyloidosis (wtATTR) is an important cause of heart failure (HF); however, the prevalence and clinical significance of neurologic complications remains uncertain.
This analysis reports findings from a single-centre experience of routine neuropathy screening at the time of wtATTR diagnosis by nerve conduction studies and neurologist assessment, compared with age-matched controls.
Forty-one wtATTR patients were included, 39 (95%) males, mean age 78.4 ± 7.7 years, 22 (54%) New York Heart Association (NYHA) class III–IV HF, along with 15 age-matched controls (mean age 77.1 ± 4.2 years, 80% male). Twenty-one (51%) wtATTR patients were diagnosed with polyneuropathy, 15 (37%) with spinal stenosis, 36 (88%) with carpal tunnel syndrome (CTS) and 14 (34%) with ulnar neuropathy. Comparison diagnoses among controls were 1 (7%), 0, 1 (7%) and 3 (20%), respectively. Among patients with NYHA class III–IV HF, 16 (73%) had polyneuropathy compared with 5 (26%) with class I–II (p < 0.01), odds ratio of 7.5 (95% confidence interval 1.9–29.9). After neuropathy screening, 19 (46%) patients were offered neurologic therapy and/or additional diagnostic evaluation. This included CTS release surgery (16, 39%), neuropathic pain medication (3, 7%), nerve block (1, 2%), wrist splinting (2, 5%) and foot care (1, 2%). Spine imaging was performed for 3 (7%) patients, and deltoid muscle and sural nerve biopsy for 1 (2%) patient.
Screening of wtATTR patients for neurologic complications resulted in a management change for nearly half. CTS, polyneuropathy and ulnar neuropathy were common. This approach warrants consideration as part of routine assessment for newly diagnosed wtATTR patients.
Our qualitative descriptive study compared how older patients and their informal caregivers experienced the care transition from acute care or rehabilitation to home. We recruited patients 65 years of age or older, or their informal caregivers, from in-patient units within acute care hospitals and rehabilitation facilities to participate in semi-structured interviews. We identified emergent themes via thematic analysis. In all, 16 patients and four patient caregivers participated. Across all care settings, caregivers were integral in facilitating the transition as well as experiencing variable discharge preparation, health care providers’ optimizing transitions, and missed care and medication discrepancies at transition points. Orthopedic and rehabilitation patients more commonly voiced prior transition experiences in discharge preparation, including having to unexpectedly coordinate and wait for outpatient services. Differing responses between acute care and orthopedic settings suggest that transitional care practices and policies favor an individualized approach that considers patients’ previous experiences, needs, and care expectations.
In the field of public health, network models are useful for understanding the spread of both information and infectious diseases. Collecting network data requires determining network boundaries (ie, the entities selected for data collection). These decisions, if not made carefully, have potential outsized downstream effects on study findings. In practice, collaboration and coordination between healthcare organizations are often dictated by historical or geopolitical boundaries (eg, state or county boundaries), which may distort the underlying network under study, and thereby affect the reliability and/or accuracy of the network model. Objective: We compared natural communities in a patient-sharing network with those induced by geopolitical boundaries. Methods: Using data from the Healthcare Cost and Utilization Project (HCUP), we constructed a patient-sharing network among hospitals in California, splitting the data into a training set and a holdout set. We performed edge-betweenness clustering on the training set, and with the holdout set, we compared the resulting partition with the partition by counties using modularity. We also clustered contiguous counties that might function more cohesively together than individually. We performed spatially constrained hierarchical clustering on the network constructed from total patient flow between pairs of counties. The results were again compared via modularity on the holdout set to the county partition. Lastly, we built an individual-based model (IBM) using HCUP and American Hospital Association data to perform epidemic simulations. For each of several counties, we implemented this model to estimate the proportion of patients infected over time. We then reran the individual-based model using the entire state while dividing the results into corresponding counties. Results: In total, 680,485 patients transferred between 374 hospitals in 55 counties from 2003 to 2011. The out-of-sample modularity for the edge-betweenness clustering partition was 464% higher than that of the county partition. Aggregating the counties into half as many contiguous clusters was 319% higher, and aggregating them into 6 clusters was 489% higher (Fig. 1). The epicurves from the individual-based model ranged from small to significant deviations between state versus county boundaries (Fig. 2) . Conclusions: Collecting network data using externally imposed boundaries may lead to inaccurate network models. For example, counties serve as a poor proxy for their underlying communities, resulting in poor overall disease spread simulation results when county boundaries are allowed to drive network construction. These issues should be considered when building coordination partnerships such as the Accountable Communities for Health.
Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness.
A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects.
Disease state (pFWE < 0.042) and number of hospitalizations (pFWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (pFWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (pFWE < 0.040) mapping to the right SLF.
Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.