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Osteoarthritis (OA) prevalence increases as the population ages. Diagnosing osteoarthritis often occurs in the late stages when cartilage degradation is severe, making it difficult to distinguish from other types of arthritis. Accurate differentiation of primary osteoarthritis from other arthritic conditions is crucial for effective treatment planning. A new diagnostic test has been developed that uses a dual‐biomarker algorithm to inform osteoarthritis diagnosis. Synovial fluid from patients with confirmed primary osteoarthritis showed elevated levels of cartilage oligomeric matrix protein. However, this biomarker alone could not distinguish primary osteoarthritis from other inflammatory conditions that also cause cartilage deterioration. Therefore, a combinatorial algorithm using cartilage oligomeric matrix protein and Interleukin‐8 concentrations was developed to differentiate primary osteoarthritis from inflammatory arthritis. Clinical decision limits for cartilage oligomeric matrix protein concentration and the cartilage oligomeric matrix protein to Interleukin‐8 ratio were established and validated using 171 human knee synovial fluid specimens. The osteoarthritis algorithm demonstrated clinical sensitivity and specificity of 87.0% and 88.9%, respectively. This is the first report of a biomarker test that can differentiate primary osteoarthritis from inflammatory arthritis with a high degree of accuracy. Clinical Significance: This study introduces a novel dual‐biomarker algorithm utilizing synovial fluid analysis, offering a significant advancement in accurately diagnosing osteoarthritis, particularly in distinguishing it from inflammatory arthritis. This approach holds promise for improving clinical decision‐making and patient outcomes, addressing a critical unmet need in arthritis diagnosis. [ABSTRACT FROM AUTHOR]

Selecting an in vitro culture model of the human placenta is challenging due to representation of different trophoblast cell types with distinct biological roles and limited comparative studies that define key characteristics of these models. The aim of this research was to compare the transcriptomes of common in vitro models of the human placenta compared to bulk human placental tissue. We performed differential gene expression analysis on publicly available transcriptomic data from 7 in vitro models of the human placenta (HTR-8/SVneo, BeWo, JEG-3, JAR, Primary Trophoblasts, Villous Explants, and Trophoblast Stem Cells) and compared to bulk placental tissue from 2 cohort studies (CANDLE and GAPPS) or individual trophoblast cell types derived from bulk placental tissue. All in vitro placental models had a substantial number of differentially expressed genes (DEGs, FDR<0.01) compared to the CANDLE and GAPPS placentas (Average DEGs = 10,624), and the individual trophoblast cell types (Average DEGs = 5413), indicating that there are vast differences in gene expression. Hierarchical clustering identified 54 gene clusters with distinct expression profiles across placental models, with 23 clusters enriched for specific KEGG pathways. Placental cell lines were classified by fetal sex based on expression of Y-chromosome genes that identified HTR-8/SVneo cells as female origin, while JEG-3, JAR, and BeWo cells are of male origin. None of the models were a close approximation of the human bulk placental transcriptome, highlighting the challenges with model selection. To enable appropriate model selection, we adapted our data into a web application: "Comparative Transcriptomic Placental Model Atlas (CTPMA)". [Display omitted] • We characterized global transcriptomic differences across in-vitro models and placental tissue. • Trophoblast cell types were transcriptionally dissimilar compared to commercial cell lines. • Y-chromosome gene expression was profiled to determine the fetal sex of commercial cell lines. • We identified 54 gene clusters within all placental models using hierarchical clustering. • The CTPMA web application can be used to investigate expression profiles of placental cell models. [ABSTRACT FROM AUTHOR]

This study examines New Jersey voter identification numbers for hidden algorithmic attributes, following similar findings in New York, where algorithms could track certain illegal records. Analysis reveals complex obfuscation patterns in New Jersey, including shift ciphers, in these public-facing numbers. The purpose of such obfuscation in accessible data is unclear, raising transparency concerns. Approximately 102,854 potentially erroneous or falsified records were discovered, indicating serious integrity issues. While no direct link was found between these problematic records and the algorithmic modifications, their coexistence is concerning. The ability to algorithmically track illegal records, as seen in New York, suggests a potential for misuse. These findings have significant implications for election integrity and data management practices. [ABSTRACT FROM AUTHOR]

Aim: Having a child with congenital heart disease (CHD) is stressful for parents, but research on the impact this stress can have on child development has been lacking. We investigated the associations between parenting stress when children were infants and neurodevelopmental outcomes in toddlers with CHD. Methods: This study was carried out at the Neurocardiac Clinic at the Sainte‐Justine University Hospital in Montréal, Canada. Patients born from 2012 to 2019 and followed up to 24 months of age were recruited. Parenting stress levels were measured when the child was 4–6 months and 24 months and the child's neurodevelopment was assessed at 24 months. Multiple linear regressions analyses were carried out. Results: We studied 100 children (56% boys) with CHD. Most of the parenting stress scores were below the clinical threshold. However, they accounted for a significant part of the variance in the children's cognitive (15%–16%), receptive language (14%–15%) and gross motor outcomes (15%–18%). They had no impact on the children's expressive language or fine motor outcomes. Conclusion: Higher parenting stress was associated with poorer neurodevelopmental outcomes in toddlers with CHD. Early screening of parenting stress in CHD clinics is necessary to provide individualised intervention for parents and optimise neurodevelopmental outcomes in children. [ABSTRACT FROM AUTHOR]

Background: Many clinicians feel uncomfortable with de-labelling penicillin allergies despite ample safety data. Point of care tools effectively support providers with de-labelling. This study's objective was to increase the number of providers intending to pursue a penicillin oral challenge by 15% by February 2023. Methods: A validated de-labelling algorithm was translated into an electronic point of care tool and disseminated to eight healthcare institutions. Applying the Model for Improvement Framework, three PDSA cycles were conducted, where collected data and completed surveys were analysed to implement changes. Number of providers intending to pursue an oral challenge, tool usage as well as number of clinicians who felt satisfied with the tool and felt confident in its ability to risk-stratify patients was collected. Results: 50.4% of providers intended to give an oral challenge of penicillin with version 1, which improved to 65.5% with version 2, representing a 15.1% increase. With version 1 of the tool, there was an average of 61.3 counts of tool usage per month. 73.1% of providers felt satisfied with the tool and 76.9% felt confident in its ability to risk-stratify patients. With version 2 of the tool, after implementing changes through three PDSA cycles, monthly usage counts increased to an average of 98.6. Furthermore, 100.0% of providers felt satisfied with the tool and 98.1% felt confident with the tool's ability to risk-stratify patients. Conclusion: Our quality improvement approach demonstrated improvement in the percentage of providers that intended to pursue an oral challenge and felt satisfied and confident in the risk-stratification capabilities of penicillin allergy de-labelling tool. Electronic tools should be further incorporated into institutional penicillin de-labelling protocols. [ABSTRACT FROM AUTHOR]

Glioblastoma multiforme (GBM) is the most prevalent malignant brain tumor, with an average survival time of 14 to 20 months. Its capacity to invade brain parenchyma leads to the failure of conventional treatments and subsequent tumor recurrence. Recent studies have explored new therapeutic strategies using a chemoattracting gradient to attract GBM cells into a soft hydrogel trap where they can be exposed to higher doses of radiation or chemotherapy. It has been demonstrated in vitro under static conditions, that nanoparticles (NPs) encapsulating the chemoattractant CXCL12 can create a gradient to attract GBM cell. However, GBM cell invasion is also largely dependent on interstitial fluid flow (IFF). In the present study, a custom-made in vitro 3D model with indirect perfusion to mimic IFF at flow rates of 0.5 μL/min and 3 μL/min was used to examine the invasive behavior of F98-rodent-derived and U87-human-derived GBM cells. This model simulated IFF and CXCL12 gradient within an alginate:matrigel-based hydrogel mimicking brain parenchyma. Findings revealed that CXCL12 (1600 ng/mL) released from NPs significantly increased the migration of F98 GBM cells after 72 hours under IFF conditions at both 0.5 and 3 μL/min. In contrast, U87 GBM cells required a higher CXCL12 concentration (2400 ng/mL) and longer incubation time for migration (120 hours). Unlike the F98 cells, U87 GBM cells showed a CXCL12 dose-dependent proliferation. Semi-quantitative qPCR showed higher CXCR4 mRNA levels in F98 cells than in U87 cells. CXCL12 significantly increased intracellular calcium levels via CXCR4 activation, with a 2.3-fold rise in F98 cells compared to U87, consistent with observed cell behavior during perfusion. This highlights the combined influence of IFF and CXCL12 on cell migration, dependent on cell line. This 3D dynamic model is a valuable tool to analyze parameters like interstitial fluid flow (IFF) and chemokine gradients, influenced by GBM tumor diversity. [ABSTRACT FROM AUTHOR]

Background: After release from incarceration, individuals are rarely connected to primary care or to social services despite bearing a disproportionate burden of poor health (e.g., chronic illness) and structural determinants of health (e.g., housing instability). The Rhode Island Transitions Clinic (RITC) works to fill this gap, particularly for patients with complex needs, by linking individuals to primary care and social services. However, prior work has not formally assessed how successful the TCN is at connecting patients to social services. Our objective was to assess the relationship between RITC and connections to healthcare use and services addressing structural determinants of health. Methods: This retrospective cohort study utilizes data among those released from the Rhode Island Department of Corrections (RIDOC) from 2018–2020. These data were linked with state agency data (e.g., unemployment, Medicaid medical claims, housing and homelessness services). We estimated 6-month risk differences (RDs) of each outcome, using stabilized inverse probability weights to account for censoring and confounding. Results: Of 8,694 individuals, the 68 enrolled in RITC are, on average, older, more likely to be Black, and have had more incarcerations. The RITC was associated with higher likelihood of connection to housing and homelessness services (RD: 0.29; 95% CI: 0.17, 0.41), (re)instatement of Supplemental Security Income (RD: 0.17, 95% CI: 0.06, 0.28), Emergency Department (RD: 0.29; 95% CI: 0.17, 0.41), and primary care visits (RD: 0.32; 95% CI: 0.21, 0.43), and lower likelihood of receiving taxable wages (RD: -0.05; 95% CI: -0.14, 0.05) compared to not being in RITC within six-months of release. Conclusions: RITC patients have complex healthcare and social service needs. The RITC is an innovative approach that is successful at connecting its patients to primary care and social services. [ABSTRACT FROM AUTHOR]

Background: Shared decision-making is an imperative in chronic pain care. However, we know little about the decision-making process, especially in primary care where most chronic pain care is provided. We sought to understand decisional needs of people living with chronic pain in Canada. Methods: We conducted a population-based cross-sectional online survey of random samples of adults living in Canada with chronic noncancer pain and registered with the Leger Marketing panel. We followed the International Association for Study of Pain definition of chronic pain (i.e., persistent or recurrent pain lasting longer than three months). We used a stratified proportional random sampling based on the population and chronic pain prevalence of each province to achieve representativeness. Based on the Ottawa Decision Support Framework, we collected data on difficult decisions (i.e., decision with more than one option and no clear best option) related to their chronic pain condition, the level of decisional conflict associated with the most difficult decisions (i.e., Decisional Conflict Scale), the assumed and preferred role during the decision-making process (i.e., Control Preferences Scale), and respondents' characteristics. We used descriptive quantitative analyses of survey responses. Results: Of the 31,545 invited panellists, 2,666 met the eligibility criteria, and 1,649 respondents from the 10 Canadian provinces completed the survey. Respondents had diverse socio-demographic profiles. Mean age was 51.8 years (SD = 16.3). Half were men (51.4%), most lived in urban areas (87.8%), mean pain duration was 8.5 years (SD = 9.6), and respondents reported an average number of painful body regions of 2.3 (SD = 1.5). We observed that 96.7% of respondents faced at least one difficult decision across their care pathways. These difficult decisions were related to numerous issues from the medical consultation, diagnosis, treatment, and daily life. Almost half of respondents made their most difficult decision with a primary care physician. One third of respondents experienced a high level of clinically significant decisional conflict (Decisional Conflict Scale score ≥ 37.5). Two-thirds of respondents self-reported having a collaborative role during their decision while three-quarters wanted this role. Conclusions: People living with chronic pain in Canada have unmet decisional needs and need support to make optimal decisions to manage their chronic pain. Our findings will guide future development of interventions to implement shared decision-making, especially to support primary care where discussions about difficult decisions often occur. Key points: 1. We conducted an online survey across 10 Canadian provinces and collected responses from a wide diversity of people living with chronic pain. 2. Over 96% of respondents faced at least one difficult decision concerning pain care across their care pathways, from diagnosis to daily living modifications. 3. A third of respondents experienced a high level of clinically significant decisional conflict. 4. People living with chronic pain in Canada have unmet needs and desire to be involved in the decisions about their pain care. 5. Our national survey justifies the development of shared decision-making interventions, especially to support primary care, to address difficult decisions, reduce decisional conflict and increase involvement in chronic pain care. [ABSTRACT FROM AUTHOR]