Impact of Intra-Articular Injection Use on Patient-Reported Outcomes Among Patients with Knee Osteoarthritis

Background: Knee osteoarthritis (OA) is the most common type of OA and is a major cause of pain and thus results in disability for daily activities among persons living in the community. OA currently has no cure. In addition to the conflicting recommendations from clinical guidelines, evidence about the extent to which long-term use of intra-articular injections improves patient outcomes is also lacking. Methods: Using data from the Osteoarthritis Initiative (OAI), marginal structural models (MSMs) applying inverse probability treatment weights (IPTW) were used to examine the effectiveness of intra-articular injections and changes in symptoms over time. The specific aims of this dissertation were to: 1) evaluate longitudinal use of intra-articular injections after treatment initiation among persons with radiographic knee OA; 2) quantify the extent to which intra-articular injection relieves symptoms among persons with radiographic knee OA; and 3) evaluate the performance of missing data techniques under the setting of MSMs. Results: Of those initiating injections, ~19% switched, ~21% continued injection type, and ~60% did not report any additional injections. For participants initiating corticosteroid (CO) injections, greater symptoms post-initial injection rather than changes in symptoms over time were associated with continued use compared to one-time use. Among participants with radiographic evidence of knee OA, initiating treatments with either CO or hyaluronic acid (HA) injections was not associated with reduced symptoms compared to non-users over two years. Compared to inverse probability weighting (IPW), missing data techniques such as multiple imputation (MI) produced less biased marginal causal effects (IPW: -2.33% to 15.74%; -1.88% to 4.24%). For most scenarios, estimates using MI had smaller mean square error (range: 0.013 to 0.024) than IPW (range: 0.027 to 0.22). Conclusions: Among participants with radiographic evidence of knee OA living in the community, the proportion of those switching injection use and one-time users was substantial after treatment initiation. In addition, initiating injection use was not associated with reduced symptoms over time. With respect to issues of missing data, using MI may confer an advantage over IPW in MSMs applications. The results of this work highlight the importance of using comparative effectiveness research with non-experimental data to study these commonly used injections and may help to understand the usefulness of these treatments for patients with knee OA

Study on Application of Grey Prediction Model in Superalloy MAR-247 Machining

Superalloy MAR-247 is mainly applied in the space industry and die industry. With its characteristics of mechanical property, fatigue resistance, and high temperature corrosion resistance, therefore, it is mainly applied in machine parts of high temperature and corrosion resistance, such as turbine blades and rotor of the aeroengine and turbine assembly in the nuclear power plant. However, considering that its properties of high strength, low thermal conductivity, being difficult to soften, and work hardening may reduce the life of cutting-tool and weaken the surface accuracy, the study provided minimizing experiment occurring during milling process for superalloy material. As a statistical approach used to analyse experiment data, this study used GM(1,1) in the grey prediction model to conduct simulation and then predict and analyze its characteristics based on the experimental data, focusing on the tool life and surface accuracy. Moreover, with the superalloy machining parameters of the current effective application improved grey prediction model, it can decrease the errors, extend the tool life, and improve the prediction precision of surface accuracy

The Use of Response Surface Methodology to Optimize Parameter Adjustments in CNC Machine Tools

This paper mainly covers a research intended to improve the circular accuracy of CNC machine tools and the adjustment and analysis of the main controller parameters applied to improve accuracy. In this study, controller analysis software was used to detect the adjustment status of the servo parameters of the feed axis. According to the FANUC parameter manual, the parameter address, frequency, response measurements, and the one-fourth corner acceleration and deceleration measurements of the machine tools were adjusted. The experimental design (DOE) was adopted in this study for taking circular measurements and engaging in the planning and selection of important parameter data. The Minitab R15 software was adopted to predict the experimental data analysis, while the seminormal probability map, Plato, and analysis of variance (ANOVA) were adopted to determine the impacts of the significant parameter factors and the interactions among them. Additionally, based on the response surface map and contour plot, the optimal values were obtained. In addition, comparison and verification were conducted through the Taguchi method, regression analysis to improved machining accuracy and efficiency. The unadjusted error was 7.8 μm; through the regression analysis method, the error was 5.8 μm and through the Taguchi analysis method, the error was 6.4 μm

Implementation and reporting of causal mediation analysis in 2015: a systematic review in epidemiological studies

BACKGROUND: Causal mediation analysis is often used to understand the impact of variables along the causal pathway of an occurrence relation. How well studies apply and report the elements of causal mediation analysis remains unknown. METHODS: We systematically reviewed epidemiological studies published in 2015 that employed causal mediation analysis to estimate direct and indirect effects of observed associations between an exposure on an outcome. We identified potential epidemiological studies through conducting a citation search within Web of Science and a keyword search within PubMed. Two reviewers independently screened studies for eligibility. For eligible studies, one reviewer performed data extraction, and a senior epidemiologist confirmed the extracted information. Empirical application and methodological details of the technique were extracted and summarized. RESULTS: Thirteen studies were eligible for data extraction. While the majority of studies reported and identified the effects of measures, most studies lacked sufficient details on the extent to which identifiability assumptions were satisfied. Although most studies addressed issues of unmeasured confounders either from empirical approaches or sensitivity analyses, the majority did not examine the potential bias arising from the measurement error of the mediator. Some studies allowed for exposure-mediator interaction and only a few presented results from models both with and without interactions. Power calculations were scarce. CONCLUSIONS: Reporting of causal mediation analysis is varied and suboptimal. Given that the application of causal mediation analysis will likely continue to increase, developing standards of reporting of causal mediation analysis in epidemiological research would be prudent

Unbiased Pain Assessment through Wearables and EHR Data: Multi-attribute Fairness Loss-based CNN Approach

The combination of diverse health data (IoT, EHR, and clinical surveys) and scalable-adaptable Artificial Intelligence (AI), has enabled the discovery of physical, behavioral, and psycho-social indicators of pain status. Despite the hype and promise to fundamentally alter the healthcare system with technological advancements, much AI adoption in clinical pain evaluation has been hampered by the heterogeneity of the problem itself and other challenges, such as personalization and fairness. Studies have revealed that many AI (i.e., machine learning or deep learning) models display biases and discriminate against specific population segments (such as those based on gender or ethnicity), which breeds skepticism among medical professionals about AI adaptability. In this paper, we propose a Multi-attribute Fairness Loss (MAFL) based CNN model that aims to account for any sensitive attributes included in the data and fairly predict patients' pain status while attempting to minimize the discrepancies between privileged and unprivileged groups. In order to determine whether the trade-off between accuracy and fairness can be satisfied, we compare the proposed model with well-known existing mitigation procedures, and studies reveal that the implemented model performs favorably in contrast to state-of-the-art methods. Utilizing NIH All-Of-US data, where a cohort of 868 distinct individuals with wearables and EHR data gathered over 1500 days has been taken into consideration to analyze our suggested fair pain assessment system.Comment: Under Review IEEE-EMBS International Conference on Body Sensor Networks: Sensor and Systems for Digital Healt

Physical activity and attitudes towards exercise in people with axial and peripheral spondyloarthritis

OBJECTIVE: To evaluate physical activity and attitudes towards exercise among people with axial and peripheral spondyloarthritis (SpA). METHODS: Using baseline information from an on-going, longitudinal, prospective SpA cohort study (n=264), self-reported attitudes and beliefs towards exercise were assessed using questionnaires. Total metabolic equivalent (MET) hours of self-reported physical activity per week, time spent in activities, and activity levels were calculated from the Nurses\u27 Health Study Physical Activity Questionnaire II (NHSPAQ II). Adjusted multivariable linear models estimated the relationship between physical activity and disease status (axial versus peripheral). RESULTS: Regardless of predominant anatomic distribution of disease, most participants were well-educated, non-Hispanic white men. Approximately 40% met the United States Department of Health and Human Services physical activity recommendations. Positive attitudes, beliefs, and perceived benefits towards exercise were similar by anatomic distribution of disease. Despite similar MET-hours per week, participants with axial disease had greater concerns regarding discomfort and joint injuries than those with peripheral disease. Compared to those with peripheral SpA (n=201), participants with axial SpA (n=63) spent less time engaging in light and moderate activities (adjusted beta in light activity: -1.94 minutes/week, 95% Confidence Interval (CI): -2.96 to -0.93; adjusted beta in moderate activity: -1.05 minutes/week, 95% CI: -2.12 to 0.02). CONCLUSION: Participants with axial SpA had greater concerns regarding discomfort and injuries from exercise than those with peripheral SpA. Although no differences in time spent in vigorous activities were observed, participants with axial SpA spent less time than those with peripheral SpA in light to moderate activities

Correlates of hyaluronic acid and corticosteroid injections among patients with radiographically confirmed osteoarthritis

Objective: Despite the rapid proliferation of hyaluronate (HA) and corticosteroid (CO) injections and clinical guidelines regarding their use in osteoarthritis (OA), information on the characteristics of people receiving them is scarce. We described use of injections among adults with radiographically confirmed knee OA and identified correlates of injection use. Methods: We used publicly available data from Osteoarthritis Initiative and included participants with ≥ one radiographically confirmed knee OA (Kellgren-Lawrence grade (K-L) \u3e 2) at baseline. We matched 415 participants reporting HA and/or CO during the 6 month before one of the first 7 annual follow-up assessments to 1,841 non-injection users by randomly selecting a study visit to match the distribution observed in the injection users. Multinomial logistic regression models identified correlates of injection use including sociodemographics and clinical/functional factors. Results: Injections were common (16.9% -year 1, 13.7% -year 2, 16.6 % -year 3, 13.5% - year 4, 15.9% -year 5, 13.5 % -year 6 and 9.9% -year 7) with corticosteroid injections most common (68.4%). HA and CO were more commonly reported by those with higher income (e.g. adjusted Odds Ratio (aOR) HA \u3e $50k versus \u3c$25k: 3.63; (95% CI: 1.20-10.99)) and less common among blacks (aOR HA: 0.19; 95% CI: 0.06-0.55). Greater K-L grade (grade 4 versus 2) was associated with increased odds of HA (aOR: 4.79; 95% CI: 2.47-9.30), CO (aOR: 1.56; 95% CI: 1.04-2.34), or both (aOR: 4.94; 95% CI: 1.99-12.27). Conclusion: Hyaluronic acid or corticosteroid injections are associated with higher socioeconomic positioning and indicators of greater disease severity

A Decline in Walking Speed is Associated with Incident Knee Replacement in Adults with and at Risk for Knee Osteoarthritis

OBJECTIVE: To determine if a one-year change in walking speed is associated with receiving an incident knee replacement during the following year in adults with and at risk for knee osteoarthritis (OA). METHODS: Using data from the Osteoarthritis Initiative, we determined a one-year change in 20- meter walk speed from three observation periods (i.e., 0-12, 12-24, and 24-36 month). We operationally defined one-year change in walking speed as either: 1) decline: \u3c -0.1 m/s change, 2) no change: between -0.1 and 0.1 m/s change, 3) increase: \u3e 0.1 m/s change. Incident knee replacement was defined using each subsequent one-year period (i.e., 12-24, 24- 36, and 36-48 month). Combining data from the three observation periods, we performed a Poisson regression with robust error variance to determine the relative risk between a change in walking speed (exposure) and incident knee replacement over the following year (outcome). RESULTS: Of the 4,264 participants included within this analysis (11,311 total person visits), 115 (3%) adults received a knee replacement. Decline in walking speed was associated with a 104% increase in risk [adjusted relative risk (RR)=2.04; 95% confidence interval (CI)= 1.40-2.98], while an increase in walking speed associated with a 55% decrease in risk (RR=0.45; 95% CI=0.22-0.93) of incident knee replacement in the following year compared to a person with no change in walking speed. CONCLUSION: A one-year decline in walking speed is associated with an increased risk, while one-year increase in walking speed is associated with a decreased risk of future incident knee replacement

Primary care physician perspectives on barriers to diagnosing axial Spondyloarthritis: a qualitative study

BACKGROUND: The average delay in diagnosis for patients with axial spondyloarthritis (axSpA) is 7 to 10 years. Factors that contribute to this delay are multifactorial and include the lack of diagnostic criteria (although classification criteria exist) for axSpA and the difficulty in distinguishing inflammatory back pain, a key symptom of axSpA, from other highly prevalent forms of low back pain. We sought to describe reasons for diagnostic delay for axSpA provided by primary care physicians. METHODS: We conducted a qualitative research study which included 18 US primary care physicians, balanced by gender. Physicians provided informed consent to participate in an in-depth interview ( \u3c 60 min), conducted in person (n = 3) or over the phone (n = 15), in 2019. The analysis focuses on thoughts about factors contributing to diagnostic delay in axSpA. RESULTS: Physicians noted that the disease characteristics contributing to diagnostic delay include: back pain is common and axSpA is less prevalent, slow progression of axSpA, intermittent nature of axSpA pain, and in the absence of abnormal radiographs of the spine or sacroiliac joints, there is no definitive test for axSpA. Patient characteristics believed to contribute to diagnostic delay included having multiple conditions in need of attention, infrequent interactions with the health care system, and doctor shopping. Doctors noted that patients wait until the last moments of the clinical encounter to discuss back pain. Problematic physician characteristics included lack of rapport with patients, lack of setting appropriate expectations, and attribution of back pain to other factors. Structural/system issues included short appointments, lack of continuity of care, insufficient insurance coverage for tests, lack of back pain clinics, and a shortage of rheumatologists. CONCLUSION: Primary care physicians agreed that lengthy axSpA diagnosis delays are challenging to address owing to the multifactorial causes (e.g., disease characteristics, patient characteristics, lack of definitive tests, system factors)