Real-world Results Research Articles

Use of AI methods as a complement or alternative to biomechanical testing of lower limb peak torque in football

Purpose Monitoring and assessing the level of lower limb motor skills using the Biodex System plays an important role in the training of football players and in post-traumatic rehabilitation. The aim of this study is to build and test an artificial intelligence-based model to assess the peak torque of the lower limb extensors and flexors. The model was based on real-world results in three groups: hearing (n = 19) and deaf football players (n = 28) and non-training deaf pupils (n=46). Methods The research used a 4-layer forward CNN neural network with two hidden layers with typical normalization for small data sets and Multilayer Perceptron (MLP) based on MatlabR2023a software with Neural Networks and Deep Learning toolkits and semiautomated learning algorithm selection using ML.NET Results The 70-90% accuracy shown in the article is sufficient here. AI provides a highly accurate, objective and efficient means of assessing neuromuscular performance, which can improve injury prevention and rehabilitation strategies. Conclusions The high accuracy shows that AI-based models can help with this, but their wider practical implementation requires further cross-disciplinary research. AI, and in particular MLP and CNN can support both training methods and various gaming aspects. The contribution of the research is to use an innovative approach to derive computational rules/guidelines from an explicitly given dataset and then identify the relevant physiological torque of the lower limb extensors and flexors in the knee joint. The model complements existing methodologies for describing physiology of peak torque of lower limbs with using fuzzy logic, with a so-called dynamic norm built into the model.

CARE: Cloudified Android With Optimized Rendering Platform

Due to the excellent rendering capabilities, GPUs are mainstream accelerators in the Cloud-rendering industry. However, current Cloud-rendering systems suffer from a CPU-GPU workload imbalance that not only degrades application performance but also causes a significant waste of GPU resources. Recent proposals (such as API-forwarding and c-GPU) for improving CPU-GPU balance are promising but fail to solve system-resource redundancy issues (i.e., each instance tends to occupy all resources, exceeding its requirements). Such behavior will increase CPU load and lower effective GPU utilization. To demonstrate the severity of the issue, we evaluated real-world applications and results show that in most cases, nearly 50% of resources are useless. To solve this problem, we present CARE, the first framework intended to reduce the system-level redundancy by cloudifying the system from monolithic to Cloud-native. To allow users to configure required services, CARE puts forward a functional unit called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Configurable Android (CA)</i> . To allow multiple instances to share certain types of resources, CARE innovates <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Sharing Resource (SR)</i> . To reduce the unused services, CARE introduces <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Pruning Resources (PR)</i> . To further alleviate the CPU pressure and achieve CPU-GPU balance, we propose rShare, a system aiming at enhancing CPU effective utilization and increasing Android instance density of the Cloud-rendering platform. Based on Kubernetes, rShare divides all the CPUs into non-overlapping shared CPU pools, allocates instances to pools within milliseconds, and dynamically migrates them by tracking their QoS status. So far, CARE primarily focuses on Android systems and can handle 60 heavyweight instances (e.g., KOG (King of Glory)) on Intel®SG1. rShare can apply instance allocation within milliseconds and increase the platform density by 39.4%.

A New Modified Liu Ridge-Type Estimator for the Gamma Regression Model

The Gamma Regression Model (GRM) is a special form of the generalized linear model (GLM), where the response variable is positively skewed and well fitted to the gamma distribution. The most popular technique for estimating GRM coefficients is maximum likelihood (ML) estimation. The ML estimation method performs better if there is no correlation between the explanatory variables. It is known that the variance of the maximum likelihood estimator of the gamma regression coefficients is impacted in situations when the explanatory variables are correlated. Based on Aslam and Ahmad’s Modified Liu-Ridge-Type (MLRT) estimator, which has been demonstrated to lessen the effects of multicollinearity in the linear regression model, the paper presented a New Modified Liu Ridge-Type Estimator for the Gamma Regression Model (GMLRT) to address the problem of multicollinearity. Simulation and real-world application results show the superiority of the GMLRT estimator using the mean square error criterion.

Characterization of Psychiatric Inpatients: The Role of Gender Differences in Clinical and Pharmacological Patterns.

Severe mental disorders that require hospitalization are disabling conditions that contribute to the burden of mental diseases. They pose increased clinical challenges and highlight the need to thoroughly explore variables emerging from daily clinical practice. In this study, we assessed to what extent gender differences may characterize a large population of psychiatric inpatients. We conducted a cross-sectional study in 2 Italian teaching medical centers, which included 2358 patients who were consecutively admitted to the psychiatric emergency units. We explored and characterized gender differences for variables such as prevalence of psychiatric diagnosis, presence of suicidal ideation, suicide attempts, age at onset of psychiatric illness, presence of substance or alcohol abuse, length of stay, number of hospitalizations, presence of involuntary admission, type of discharge from the hospital, and pharmacological treatment at discharge. Female patients were primarily diagnosed with bipolar disorder or personality disorders. Female patients had a significantly higher prevalence of lifetime suicide attempts (23.1% vs. 16.5%, P<0.001) and a longer length of hospitalization (11.43±10.73d vs. 10.52±10.37d, t=-2.099, gl=2356, P=0.036) compared with male patients. Male patients had more involuntary admissions (25.1% vs. 19.7%, χ2=9.616, gl=1, P=0.002), more use of illicit substances (34.1% vs. 20.9%, χ2=51.084, gl=1, P<0.001), and higher rates of alcohol abuse (21.3% vs. 14.7%, χ2=17.182, gl=1, P<0.001) compared with female patients. Finally, antidepressants and lithium were prescribed more frequently to the female patients, whereas other mood stabilizers were more often prescribed to the male patients. Our real-world results highlighted gender differences among patients with severe mental disorders admitted to psychiatric units, and suggest further investigations that may help in understanding trajectories accompanying disabling clinical conditions.

Comparison And Analysis of Treatment Strategies for Radius Fractures: Internal Fixation Surgery Versus External Plaster Fixation Treatment

One of the most frequent forms of fractures is the radius fracture. This kind of fracture would have a significant negative impact on people's lives. There has been ongoing debate regarding the treatment options for radius fractures. This article conducts a comparative analysis of two treatment approaches for radius fractures: internal fixation surgery and non-surgical external plaster fixation treatment. This article provides a comprehensive elucidation and analysis of the principles, actual treatment outcomes, and various factors associated with these two treatment approaches. It separately outlines the treatment principles and real-world results for each of the two treatment methods, concluding with a summary and comparison. When viewed from a singular perspective, both treatment approaches demonstrate reasonable and excellent treatment outcomes. However, when these two approaches are compared, this article finds that surgical internal fixation typically outperforms non-surgical cast external fixation in a broader range of evaluations.

BDS-3 RTK/UWB semi-tightly coupled integrated positioning system in harsh environments

Real-time kinematic (RTK) positioning is a commonly used technique in modern industry, which is limited by problems such as signal occlusion, attenuation, and multipath, especially in complex urban canyons. To maintain the consistency of centimeter-level accuracy, we adopt the ultra-wideband (UWB) enhanced BDS-3 RTK positioning algorithm. This paper proposed a semi-tightly coupled (STC) BDS-3 RTK/UWB integration positioning model. This model realizes the UWB and BDS-3 complement each other and integrate information in the position domain. Besides, height constraint is imposed on UWB positioning to mitigate the effect of poor positioning of UWB in height components. To verify the effectiveness of the above algorithm, we have compared and analyzed the positioning performance of the STC BDS-3 RTK/UWB integration model and single BDS-3 RTK model in different occlusion environments. The positioning performance of static and kinematic of BDS-3 RTK/UWB STC based on different number of UWB anchors is further analyzed. The real-world experiment results show that the positioning accuracy of the proposed method can reach centimeter-level. Moreover, the proposed model can obtain more accurate positioning results than those of using single system, and it shows more obvious advantages, especially in the occlusion environment. In the occlusion environment, the root means square error in the east, north, and up directions is improved from (0.629 m, 0.325 m, 1.160 m) of the BDS-3-only to (0.075 m, 0.074 m, 0.029 m). This study can provide a reference for the future development of high-precision, real-time, continuous positioning, navigation, and timing in complex urban environments.

Optimizing Robotic Task Sequencing and Trajectory Planning on the Basis of Deep Reinforcement Learning.

The robot task sequencing problem and trajectory planning problem are two important issues in the robotic optimization domain and are solved sequentially in two separate levels in traditional studies. This paradigm disregards the potential synergistic impact between the two problems, resulting in a local optimum solution. To address this problem, this paper formulates a co-optimization model that integrates the task sequencing problem and trajectory planning problem into a holistic problem, abbreviated as the robot TSTP problem. To solve the TSTP problem, we model the optimization process as a Markov decision process and propose a deep reinforcement learning (DRL)-based method to facilitate problem solving. To validate the proposed approach, multiple test cases are used to verify the feasibility of the TSTP model and the solving capability of the DRL method. The real-world experimental results demonstrate that the DRL method can achieve a 30.54% energy savings compared to the traditional evolution algorithm, and the computational time required by the proposed DRL method is much shorter than those of the evolutionary algorithms. In addition, when adopting the TSTP model, a 18.22% energy reduction can be achieved compared to using the sequential optimization model.

Long-term secondary prevention and outcome following acute coronary syndrome: real-world results from the Swedish Primary Care Cardiovascular Database.

Most studies of treatment adherence after acute coronary syndrome (ACS) are based on prescribed drugs and lack long-term follow-up or consecutive data on risk factor control. We studied the long-term treatment adherence, risk factor control, and its association to recurrent ACS and death. We retrospectively included 3765 patients (mean age 75 years, 40% women) with incident ACS from 1 January 2006 until 31 December 2010 from the Swedish Primary Care Cardiovascular Database of Skaraborg. All patients were followed until 31 December 2014 or death. We recorded blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), recurrent ACS, and death. We used data on dispensed drugs to calculate the proportion of days covered for secondary prevention medications. Cox regressions were used to analyse the association of achieved BP and LDL-C to recurrent ACS and death. The median follow-up time was 4.8 years. The proportion of patients that reached BP of <140/90 mm Hg was 58% at Year 1 and 66% at Year 8. 65% of the patients reached LDL-C of <2.5 mmol/L at Year 1 and 56% at Year 8; however, adherence to statins varied from 43% to 60%. Only 62% of the patients had yearly measured BP, and only 28% yearly measured LDL-C. Systolic BP was not associated with a higher risk of recurrent ACS or death. Low-density lipoprotein cholesterol of 3.0 mmol/L was associated with a higher risk of recurrent ACS {hazard ratio [HR] 1.19 [95% confidence interval (CI) 1.00-1.40]} and death HR [1.26 (95% CI 1.08-1.47)] compared with an LDL-C of 1.8 mmol/L. This observational long-term real-world study demonstrates low drug adherence and potential for improvement of risk factors after ACS. Furthermore, the study confirms that uncontrolled LDL-C is associated with adverse outcome even in this older population.

NAFLD and NASH are obesity-independent risk factors in COVID-19: Matched real-world results from the large PINC AI™ Healthcare Database.

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are potential risk factors for severe pneumonia and other infections. Available data on the role of NAFLD/NASH in worsening outcomes for COVID-19 are controversial and might be confounded by comorbidities. We used the PINC AI™ Healthcare Data Special Release (PHD-SR) to identify patients with COVID-19 (ICD-10) at approximately 900 hospitals in the United States. We performed exact matching (age, gender, and ethnicity) for patients with or without NAFLD/NASH, adjusting for demographics (admission type, region) and comorbidities (e.g., obesity, diabetes) through inverse probability of treatment weighting and then analysed hospitalisation-related outcomes. Among 513 623 patients with SARS-CoV-2 (COVID-19), we identified 14 667 with NAFLD/NASH who could be matched to 14 667 controls. Mean age was 57.6 (±14.9) years, 50.8% were females and 43.7% were non-Hispanic whites. After matching, baseline characteristics (e.g., age, ethnicity, and gender) and comorbidities (e.g., hypertension, obesity, diabetes, and cardiovascular disease) were well balanced (standard difference (SD) <.10), except for cirrhosis and malignancies. Patients with COVID-19 and NAFLD/NASH had higher FIB-4 scores, a significantly longer hospital length of stay (LOS) and intensive care LOS than controls (9.4 vs. 8.3 days, and 10.4 vs. 9.3, respectively), even after adjusting for cirrhosis and malignancies. Patients with COVID-19 and NAFLD/NASH also had significantly higher risk of needing invasive mandatory ventilation (IMV) (odds ratio 1.0727; 95% CI 1.0095-1.1400). Other outcomes were similar in both groups. In this large real-world cohort of patients hospitalised for COVID-19 in the United States, NAFLD/NASH were obesity-independent risk factors for complicated disease courses.

Targeted Display Advertising using Machine Learning

This paper delves into the intricate challenges of problem formulation and data representation in the context of a large-scale machine learning system for targeted display advertising. Unlike traditional models, this system is not just conceptual but has been operational for years across thousands of advertising campaigns. Since obtaining ideal training data is cost-prohibitive, data is sourced from related domains and tasks and then adapted for the target task. The paper outlines the architecture of this multi-stage transfer learning system, emphasizing the problem formulation aspects. Extensive experiments demonstrate the value of each transfer stage. Real-world results with diverse advertising clients from various industries showcase the system's performance. The paper concludes with valuable insights gained from over half a decade of work on this complex, widely deployed machine learning system.

Bio-inspired affordance learning for 6-DoF robotic grasping: A transformer-based global feature encoding approach

The 6-Degree-of-Freedom (6-DoF) robotic grasping is a fundamental task in robot manipulation, aimed at detecting graspable points and corresponding parameters in a 3D space, i.e affordance learning, and then a robot executes grasp actions with the detected affordances. Existing research works on affordance learning predominantly focus on learning local features directly for each grid in a voxel scene or each point in a point cloud scene, subsequently filtering the most promising candidate for execution. Contrarily, cognitive models of grasping highlight the significance of global descriptors, such as size, shape, and orientation, in grasping. These global descriptors indicate a grasp path closely tied to actions. Inspired by this, we propose a novel bio-inspired neural network that explicitly incorporates global feature encoding. In particular, our method utilizes a Truncated Signed Distance Function (TSDF) as input, and employs the recently proposed Transformer model to encode the global features of a scene directly. With the effective global representation, we then use deconvolution modules to decode multiple local features to generate graspable candidates. In addition, to integrate global and local features, we propose using a skip-connection module to merge lower-layer global features with higher-layer local features. Our approach, when tested on a recently proposed pile and packed grasping dataset for a decluttering task, surpassed state-of-the-art local feature learning methods by approximately 5% in terms of success and declutter rates. We also evaluated its running time and generalization ability, further demonstrating its superiority. We deployed our model on a Franka Panda robot arm, with real-world results aligning well with simulation data. This underscores our approach’s effectiveness for generalization and real-world applications.

Estimating Changes in Weight and Metabolic Parameters Before and After Treatment With Cariprazine: A Retrospective Study of Electronic Health Records

Weight gain and associated negative cardiometabolic effects can occur as a result of mental illness or treatment with second-generation antipsychotics (SGAs), leading to increased rates of morbidity and mortality. In this analysis, we evaluated the effect of the SGA cariprazine on weight and metabolic parameters in a real-world, retrospective, observational dataset. Electronic health records from the Optum Humedica database (October 1, 2014-December 31, 2020) were analyzed during the 12-month period before starting cariprazine (baseline) and for up to 12 months following cariprazine initiation; approved and off-label indications were included. Body weight trajectories were estimated in the overall patient cohort and at 3-, 6-, and 12-month timepoints (primary objective). Changes in hemoglobin A1c (HbA1c), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides were also evaluated (secondary objectives). Percentages of patients with clinically relevant shifts in body weight, total cholesterol, and fasting triglycerides were also determined. Discontinuation rates for metabolic regulating medications were calculated. Average predicted values were estimated by linear mixed-effects regression models. A total of 2,301 patients were included; average duration of follow-up was 133.7 days. Average predicted weight change for patients during the cariprazine overall follow-up period was +2.4 kg, with predicted weight changes of +0.8 kg (n=811), +1.1 kg (n=350), and +1.4 kg (n=107) at months 3, 6, and 12, respectively. Overall, the majority of patients did not experience clinically significant (≥7%) weight gain (82.8%) or loss (90.5%) after starting cariprazine. Average predicted HbA1c levels (n=189) increased during baseline (0.15%/year) and decreased during cariprazine treatment (-0.2%/year). Average predicted triglyceride levels (n=257) increased during baseline (15.0 mg/dL/year) and decreased during cariprazine treatment (-0.7 mg/dL/year). Predicted LDL (n=247) and HDL (n=255) values decreased during baseline (-7.3 and -1.1 mg/dL/year, respectively); during cariprazine treatment, LDL increased by 5.6 mg/dL/year and HDL decreased by -0.6 mg/dL/year. During follow-up, most patients did not shift from normal/borderline to high total cholesterol (<240 to ≥240 mg/dL; 522 [90.2%]) or fasting triglyceride (<200 to ≥200 mg/dL; 143 [88.8%] patients) levels; shifts from high to normal/borderline levels occurred in 44 (61.1%) patients for total cholesterol and 38 (57.6%) patients for fasting triglycerides. After starting cariprazine, the discontinuation rate per 100 patient-years was 60.4 for antihyperglycemic medication and 87.4 for hyperlipidemia medication. These real-world results support short-term clinical trial findings describing a neutral weight and metabolic profile associated with cariprazine treatment and they expand the dataset to include long-term follow-up.

Validating Flip Chip Package Models Through Experimental Deflection Measurements

Tektronix Component Solutions is advancing its simulation capabilities to improve product reliability, reduce development costs, and speed up time-to-market. Developing a model that accurately predicts performance requires that it be validated through correlation to real-world results. In this work, a high-fidelity, multi-step, nonlinear finite element model was built including processing steps and thermal cycling to mirror the real environment of a flip chip package. Extensive materials characterization was performed to capture accurate time-and-temperature dependent (viscoelastic) properties of the underfill adhesive, stiffener ring adhesive, and substrate components. Model accuracy was established through three measurement techniques to characterize package deflections. The Thermo-Moiré technique was used to measure package warpages as a function of processing step and thermal loading. Optical Interferometry was used as a secondary approach to measure package warpage as a function of processing step. Lastly, Digital Image Correlation was performed on a cross-section of the package to characterize shear and through-thickness strains of critical solder bumps. The simulation produced excellent correlation with the various measurement techniques, and it was found that component pre-warpage (inherent to the substrate and stiffener ring) was a necessary variable to account for during simulation and measurement. With the excellent correlation provided by the models, Tektronix Component Solutions is now using these methods in combination with material strength testing to advance critical stress and survivability predictions in advanced packages.

Do the Control Cohorts of Phase III Randomized Trials Reflect the Real-World Results of DLBCL Patients?

Do the Control Cohorts of Phase III Randomized Trials Reflect the Real-World Results of DLBCL Patients?

Two-Year Real-World Results for Aflibercept Using the Treat-and-Extend Regimen in Neovascular Age-Related Macular Degeneration and Polypoidal Choroidal Vasculopathy.

To evaluate the real-world efficacy of aflibercept using the treat-and-extend (TnE) regimen in treating neovascular age-related macular degeneration (nAMD) and polypoidal choroidal vasculopathy (PCV), and to analyze biomarkers using optical coherence tomography (OCT) to predict treatment outcomes. Patients diagnosed with nAMD or PCV who received an intravitreal injection of aflibercept following the TnE regimen for ≥ 2years were retrospectively reviewed. Data on best-corrected visual acuity (BCVA), number of injections, treatment interval, and OCT biomarkers, including central macular thickness, presence of subretinal fluid (SRF), and serous pigmented epithelial detachment, were collected at baseline and at 3, 6, 12, 18, and 24months after the first injection. A total of 43 patients were enrolled in this study, 24 of whom were diagnosed with nAMD and 19 with PCV. The BCVA in logMAR(mean± standard deviation) improved from 0.75 ± 0.41 (baseline) to 0.60 ± 0.41 (P = 0.002) at 3 months after treatment initiation, and further improved to 0.66 ± 0.46 at 24 months (P = 0.137). The number of injections (mean± standard deviation)within the 2-year treatment course was 10.95 ± 3.65. At month 24 of the TnE regimen, the treatment interval was extended to ≥ 16weeks in 60.5% of all cases and to 78.9% of the PCV cases. After three loading injections, persistent subretinal fluid and intraretinal fluid were predictive of more frequent injections (P = 0.026) and poorer visual outcomes (P = 0.050), respectively. Aflibercept combined with a TnE regimen was effective in treating nAMD and PCV in a real-world setting. The treatment interval could be extended to ≥ 16weeks in 60.5% of the cases after a 2-year treatment regimen. OCT can be used to predict the treatment course and visual outcomes.

Real-World Utilization of Radiation Therapy in Multiple Myeloma: An Analysis of the Connect MM Registry

Radiation therapy (RT) is an important treatment modality for patients with multiple myeloma (MM). Although patients are living longer with MM, they are more likely to have comorbidities related to treatment, such as bone pain; however, RT can provide symptom relief. To date, the characterization of patients who have received RT in the real-world setting has been limited. The Connect® MM Registry is a large, US multicenter, prospective observational cohort study of adult patients with newly diagnosed MM from mostly community sites. RT utilization and outcomes were analyzed quarterly throughout treatment. Factors associated with RT use were identified via multivariable analysis. A total of 3011 patients were enrolled in the Connect MM Registry with 903 patients (30%) having received RT at any time. There was a significant difference (P < .05) in overall RT use among patients with an Eastern Cooperative Oncology Group performance status of 0 to 1 versus ≥2, International Staging System disease stage I/II versus III, a history of plasmacytoma or a novel agent in their first regimen, and any number of bone lesions or severe osteoporosis/fracture. RT use was associated with having bone lesions or severe osteoporosis (vs not having bone lesions). Additionally, RT use was associated with ethnicity (Hispanic vs not) and Connect MM Registry cohort (cohort 1 [enrolled 2009-2011] vs 2 [enrolled 2012-2016]). In the 6 months before death, increased RT use was associated with increasing number of treatment lines (P < .0001) and high- versus standard-risk disease (per International Myeloma Working Group criteria; P = .0028). Real-world results from the Connect MM Registry show RT is frequently used and is associated with clinical factors, including performance status and disease stage. Earlier in MM diagnosis, RT may be used as an adjunct to palliate symptoms or delay systemic therapy. Toward the end of life, RT is more frequently used for palliation when treatment options are often limited.

Tribocorrosion in biomaterials and control techniques: a review

Abstract Tribocorrosion is getting more and more popular in biomaterials research. The synergism between wear and corrosion is creating deviations from the expected real-world results from individual corrosion or wear studies. The host body consisting of immune system and dissolved proteins makes them highly corrosive which makes the material selection a unique and challenging process for implant materials. The synergism between corrosion and wear leads to shorter implant life. The research on tribocorrosion has bought an insight into this phenomenon and presented ideas to arrest the premature failure of implants. This review focuses on the recent developments in tribocorrosion research and the effectiveness of remedial actions suggested by them. The influence of materials, processing methods and post-processing treatments are also reviewed in detail.

Direct oral anticoagulants versus vitamin k antagonists in patients with atrial fibrillation and bioprosthesis: a systematic review and meta-analysis

Abstract Background/Introduction The large randomized clinical trials published to date have shown that direct oral anticoagulants (DOACs) are as or more effective than vitamin K antagonists (VKAs) in the prevention of thromboembolic events in atrial fibrillation (AF) and generally show a better bleeding risk profile. However, patients with bioprosthetic valves have been underrepresented in RCTs. The aim of this study was to assess the safety and efficacy of DOAC in patients with AF and bioprosthetic valves through a systematic review and meta-analysis including recent evidence from comparative cohort studies and real-world results. Methods A systematic review of the scientific literature and a subsequent meta-analysis were carried out. We included RCTs or comparative observational studies, published from January 2017 to January 2022 comparing DOACs versus vitamin K antagonists in patients with AF or atrial flutter and bioprostheses. We collected data of all-cause mortality, major bleeding, and systemic embolism. The primary outcome of interest was all-cause mortality. Secondary outcomes were systemic embolism or stroke. The primary safety outcome was major bleeding. Results Our analysis included 12 studies, 4 RCTs and 8 observational studies that enrolled a total of 30.283 patients. All-cause mortality 6 observational and 3 RCT were combined. A 9% reduction was found for all-cause mortality in patients treated with DOACs (HR,0.91; P=.0068;95%CI,0.85–0.97;I2=8%). Stroke and systemic embolism 4 RCT and 8 observational studies were combined. No evidence showing a significant effect of DOAC therapy on risk reduction for stroke and embolism was obtained (HR, 0.87; P =.29; 95%CI, 0.67–1.14; I2=45%). Major bleeding The results of the 12 studies were combined. A robustness analysis was performed, and the ENVISAGE RCT was identified as atypical. We therefore proceeded to re-run the meta-analysis without this study’s results. The overall effect size was HR, 0.79 (P = .0001; 95%CI, 0.73-0.85; I2 = 0%), with a 21.1% reduction of major bleeding with DOAC therapy compared with VKA. The present study has several limitations. It has the inherent limitations of the studies included and the combination of findings from comparative observational cohort studies and ad hoc studies from RCTs, which entails a potential source of bias. Second, individual risks for each type of bioprosthesis were not studied. Finally, the four currently marketed DOACs were included in our meta-analysis, but their efficacy and safety were not evaluated separately. Conclusions Our study found that DOAC therapy is associated with a significant reduction of all-cause mortality with no significant increase in the risk of systemic embolism or stroke. This reduction could be attributed to a decrease in major bleeding. Our results therefore suggest that DOACs could be a safer alternative than VKAs in this group of patients.

Abstract 16693: Trends in the Use of Oral Anticoagulation for Nonvalvular Atrial Fibrillation Vary by Specialty: Real World Results From a Large Integrated Health Care System 2011-2022

Introduction: Direct Oral anticoagulants (DOACs) have demonstrated superiority or non inferiority to vitamin K antagonists (VKAs) for stroke/embolic prevention in patients with nonvalvular atrial fibrillation (NVAF). However, clinical inertia may delay widespread adoption of newer therapies in medicine. Hypothesis: We evaluated whether uptake of DOACs into clinical medicine varied by physician specialty. Methods: We performed a retrospective review of patients with NVAF within the Geisinger Health System from 2011-2022. Longitudinal yearly trends for new/initial prescriptions (Rx) of DOAC vs VKA by cardiology or primary care (PCP) specialties Results: We identified patients with NVAF initiated on an oral anticoagulant from the years 2011 through 2023. Figures 1 and 2 demonstrate a statistically significant linear yearly increase in new Rx for DOACs for both cardiology and PCP specialties.By 2022, DOACs currently account for 96% of all new oral anticoagulant Rx by cardiologists and 90% of Rx by PCP. New Rx for DOAC by PCP lagged cardiology at all time points. Cardiology initial Rx &gt;50% DOAC by 2015 while PCP did not achieve this mark until 2018. Conclusions: In this real-world setting, we observed a significant increase in DOAC use as the initial prescription for patients with NVAF by both cardiology and primary care specialties.Significant difference in the adoption of DOAC was noted between cardiology and primary care specialties.Primary care use of DOAC as first Rx for NVAF increased over time but lagged cardiology by 2-3 years.

EVALUATION OF THE POTENTIAL ASSOCIATED FACTORS CONTRIBUTING TO VARIOUS SIDE EFFECTS OF COVID-19 VACCINES IN BANGLADESH

Objective: Due to questions about the safety and possible side effects of COVID-19 vaccines, initially, most individuals with chronic comorbid conditions showed unwillingness to vaccination. Though COVID-19 vaccines were found safe in clinical trials, real-world results still need to be explored to generate and further analyze the safety and efficacy profile of these vaccines. Our study aimed to evaluate and associate the various side effects of COVID-19 vaccines at different covariate levels along with comorbid conditions. Methods: This cross-sectional study aimed to evaluate the side effects of COVID-19 vaccines in Bangladesh using data collected from a sample of vaccinated individuals through a structured questionnaire. The data were analyzed using descriptive statistics, bivariate analysis with a chi-square test, and multiple logistic regression model to identify the frequency, severity, and duration of side effects, as well as the associations between side effects and potential predictors. Our study investigated the side effects of four prominent approved COVID-19 vaccines in Bangladesh. Results: The findings revealed that Sinopharm was the most administered vaccine, accounting for 55% of the respondents. The majority of participants (38%) reported experiencing mild side effects, such as pain at the injection site, fatigue, and headache, while only 13% required hospitalization due to severe side effects. Significant associations were observed between vaccine type and variables such as gender, age group, concomitant health complications, prior COVID-19 history, physician's recommendation, and adverse consequences. Logistic regression analysis identified significant associations between the presence of side effects and variables such as concomitant health complications (OR=3.2 p-value: 0.011) and concomitant medications (OR=0.38, p-value: 0.039). Conclusion: These results provide valuable insights to help guide vaccination strategies and ensure vaccine safety in Bangladesh. Further investigation into these aspects in larger and more diverse groups is necessary, taking longitudinal follow-up and the objective evaluation of side effects into consideration.