Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of exercise post vertebral augmentation in osteoporotic patients: A systematic review and meta‐analysis

This meta‐analysis investigated the effects of exercise on Visual Analog Scale (VAS) and Oswestry Disability Index (ODI) scores following vertebroplasty or kyphoplasty in osteoporotic fractures. A literature search of PubMed, EMBASE (Elsevier), CiNAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, Scopus, and Web of Science was conducted from database inception to October 6, 2022. Eligible studies reported osteoporosis patients over 18 years of age with a diagnosis of at least one vertebral fracture via radiography or clinical assessment. This review was registered in PROSPERO (ID: CRD42022340791). Ten studies met the eligibility criteria (n = 889). VAS scores at baseline were 7.75 (95% CI: 7.54, 7.97, I2 = 76.11%). Following initiation of exercise, VAS scores at the endpoint of 12 months were 1.91 (95% CI: 1.53, 2.29, I2 = 92.69%). ODI scores at baseline were 68.66 (95% CI: 56.19, 81.13, I2 = 85%). Following initiation of exercise, ODI scores at the endpoint of 12 months were 21.20 (95% CI: 14.52, 27.87, I2 = 99.30). A two‐arm analysis demonstrated improved VAS and ODI for the exercise group compared to non‐exercise control at 6 months (MD = −0.70, 95% CI: −1.08, −0.32, I2 = 87% and MD = −6.48, 95% CI: −7.52, −5.44, I2 = 46%, respectively) and 12 months (MD = −0.88, 95% CI: −1.27, −0.49, I2 = 85% and MD = −9.62, 95% CI: −13.24, −5.99, I2 = 93%). Refracture was the only adverse event reported and occurred almost twice as frequently in the non‐exercise group than in the exercise group. Exercise rehabilitation post vertebral augmentation is associated with improved pain and functionality, particularly after 6 months of exposure, and may reduce refracture rate.
Efficacy of innovative therapies in myasthenia gravis: A systematic review, meta‐analysis and network meta‐analysis

Therapy for myasthenia gravis (MG) is undergoing a profound change, with new treatments being tested. These include complement inhibitors and neonatal Fc receptor (FcRn) blockers. The aim of this study was to perform a meta‐analysis and network meta‐analysis of randomized and placebo‐controlled trials of innovative therapies in MG with available efficacy data.
Redefining caregiver strain for family caregivers in end-of-life care in Hong Kong.

OBJECTIVES Caregiving for family members at their end of life is stressful. Caregivers' strain, burden, or stress has been measured in various geographical and sociodemographic contexts. The concept of stress, burden, and strain are sometimes used interchangeably. By analysing the factor structure of the Chinese version of the Modified Caregiver Strain Index (C-M-CSI), this study aimed to examine the caregiving strain concept and its demographic correlates. METHODS A sample of 453 family caregivers of patients with a terminal illness in Hong Kong was employed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed. In addition, generalized linear models (GLM) were used to examine the demographic correlates. RESULTS The EFA yielded a 3-factor model termed "Perception of Caregiving," "Empathetic Strain," and "Adjustment Demand. " This 3-factor model explained 50% of the variance and showed good internal consistency. The CFA confirmed the 3-factor construct with satisfactory internal reliability (χ2 [61, N = 226] = 108.86, p < 0.001, CFI = 0.96, TLI = 0.95, SRMR = 0.04, and RMSEA = 0.06). Inspired by this factor structure and concepts of stress and strain from engineering discipline, a new model of caregiver strain is proposed. Additionally, family caregivers of non-cancer patients, who were not living with the patient, or younger were associated negatively with different dimensions of caregiver strain. SIGNIFICANCE OF RESULTS The results gave insights into the advancement of the conceptualization of caregiver strain, its multidimensional nature, and process of change, which inform directions for future research and practices.
Data-Driven Identification of Clinical Real-World Expressions Linked to ICD

A semi-structured clinical problem list containing ∼1.9 million de-identified entries linked to ICD-10 codes was used to identify closely related real-world expressions. A log-likelihood based co-occurrence analysis generated seed-terms, which were integrated as part of a k-NN search, by leveraging SapBERT for the generation of an embedding representation.
Automated kidney morphology measurements from ultrasound images using texture and edge analysis

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.
The effect of electron inertia in Hall-driven magnetic field penetration in electron-magnetohydrodynamics

Magnetic field penetration in electron-magnetohydrodynamics (EMHD) can be driven by density gradients through the Hall term [Kingsep et al., Sov. J. Plasma Phys. 10, 495 (1984)]. Particle-in-cell simulations have shown that a magnetic front can go unstable and break into vortices in the Hall-driven EMHD regime. In order to understand these results, a new fluid model had been derived from the Ly/Ln≪1 limit of EMHD, where Ly is the length scale along the front and Ln is the density gradient length scale. This model is periodic in the direction along the magnetic front, which allows the dynamics of the front to be studied independently of electrode boundary effects that could otherwise dominate the dynamics. Numerical solutions of this fluid model are presented that show for the first time the relation between Hall-driven EMHD, electron inertia, the Kelvin-Helmholtz (KH) instability, and the formation of magnetic vortices. These solutions show that a propagating magnetic front is unstable to the same KH mode.
Evolution of the technique of renoportal anastomosis for patients with complete portal venous occlusion in living donor liver transplantation: a retrospective cohort study

Background: This study aimed to present our surgical technique and the long-term outcomes of living donor liver transplantations with renoportal anastomosis for patients with complete portal venous occlusion. Renoportal anastomosis (RPA) is a promising technique for portal flow reconstruction during liver transplantation in patients with complete occlusion of the portal vein and extensive splanchnic vein thrombosis. However, reports demonstrating living donor liver transplantations (LDLT) with renoportal anastomosis are rarer than those demonstrating deceased donor liver transplantation. Materials and methods: In this single-centre retrospective cohort study, the authors analyzed the medical records of patients who underwent portal flow reconstruction via RPA with end-to-end anastomosis between the interposition graft and LRV-connected inferior vena cava (VC) cuff. The outcomes included postoperative RPA-related morbidity and patient and allograft survival for patients who underwent LDLT with RPA. Results: Fifteen patients underwent LDLT with portal flow reconstruction via RPA from January 2005 to December 2019. The median follow-up period was 80.7 months (range: 27 days–195.2 months). RPA evolved from end-to-end anastomosis in 1 (6.7%) patient to end-to-side anastomoses in the next 6 (40%) patients and finally, to end-to-end anastomoses between the inferior VC cuff connected to the left renal vein and interposing vascular grafts in 8 (53.3%) patients. After standardization of the RPA technique from the eighth case in 2011, the incidence rate of RPA-related complications significantly decreased from 42.9% (3/7) to 12.5% (1/8). At the last follow-up, all 11 surviving patients had normal liver function, and 10 patients had patent anastomoses on imaging examination. Conclusions: This standardized RPA technique using an inferior VC cuff connected to the left renal vein creates a safe end-to-end RPA.
Effect of radial shock wave and ultrasound therapy combined with traditional physical therapy exercises on foot function and dorsiflexion range in plantar fasciitis: a prospective randomized clinical trial.

OBJECTIVE This study aimed to assess the effect of radial shock wave and ultrasound therapy combined with traditional physical therapy on foot function and range of motion in chronic plantar fasciitis. PATIENTS AND METHODS Sixty-nine participants with chronic plantar fasciitis (25-56 years) were allocated randomly into three groups. Group (A) received ultrasound (US) therapy plus conventional physical therapy exercises (in the form of stretching, strengthening exercise, and deep friction massage), Group (B) received a radial shock wave (RSW) therapy plus conventional physical therapy exercises, and Group (C) received a combination of both RSW and US therapy in addition to conventional physical therapy exercises, with 3 sessions per week for US therapy and one session for RSW therapy, in addition to 45 minutes of exercises for all groups for 4 consecutive weeks. Foot function was assessed using the foot function index (FFI), and ankle dorsiflexion range of motion was measured using the Baseline® bubble inclinometer at baseline and 4 weeks following treatment. RESULTS ANOVA revealed significant differences (p<0.05) in the measured outcomes among the groups after treatment. Tukey's honest significant difference post-hoc test demonstrated a highly statistically significant (p<0.001) improvement in the assessed outcomes of group C in the post-intervention settings when compared to the other groups. After 4 weeks of intervention, the mean (SD) of FFI in groups A, B, and C were (64.54±4.91, 61.93±4.17, and 45.16±4.57) respectively, and the active range of motion (ROM) of the ankle dorsiflexion were (35.27±3.22, 36.59±2.91, and 41.85±3.04) respectively. CONCLUSIONS The addition of RSW to US with the conventional physical therapy program improved foot function and ankle dorsiflexion range of motion significantly for patients with chronic plantar fasciitis.
Automatic Outlier Detection in Laboratory Result Distributions Within a Real World Data Network

Laboratory data must be interoperable to be able to accurately compare the results of a lab test between healthcare organizations. To achieve this, terminologies like LOINC (Logical Observation Identifiers, Names and Codes) provide unique identification codes for laboratory tests. Once standardized, the numeric results of laboratory tests can be aggregated and represented in histograms. Due to the characteristics of Real World Data (RWD), outliers and abnormal values are common, but these cases should be treated as exceptions, excluding them from possible analysis. The proposed work analyses two methods capable of automating the selection of histogram limits to sanitize the generated lab test result distributions, Tukey's box-plot method and a "Distance to Density" approach, within the TriNetX Real World Data Network. The generated limits using clinical RWD are generally wider for Tukey's method and narrower for the second method, both greatly dependent on the values used for the algorithm's parameters.
Breaking Barriers for Interoperability: A Reference Implementation of CSV-FHIR Transformation Using Open-Source Tools

FHIR is a widely accepted interoperability standard for exchanging medical data, but data transformation from the primary health information systems into FHIR is usually challenging and requires advanced technical skills and infrastructure. There is a critical need for low-cost solutions, and using Mirth Connect as an open-source tool provides this opportunity. We developed a reference implementation to transform data from CSV (the most common data format) into FHIR resources using Mirth Connect without any advanced technical resources or programming skills. This reference implementation is tested successfully for both quality and performance, and it enables reproducing and improving the implemented approach by healthcare providers to transform raw data into FHIR resources. For ensuring replicability, the used channel, mapping, and templates are available publicly on GitHub (https://github.com/alkarkoukly/CSV-FHIR-Transformer).
Predicting Depression Risk in Patients with Cancer Using Multimodal Data

When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.
Genome analysis Letter to the editor: Testing on external independent datasets is necessary to corroborate machine learning model improvement

Letter to the editor: Testing on external independent datasets is necessary to corroborate machine learning model improvement Giulia Ilaria Corsi , Christian Anthon , Jan Gorodkin * Department of Veterinary and Animal Sciences, Center for non-coding RNA in Technology and Health, University of Copenhagen, 1870 Frederiksberg, Denmark *Corresponding author. Department of Veterinary and Animal Sciences, Center for non-coding RNA in Technology and Health, University of Copenhagen, 1870 Frederiksberg, Denmark. E-mail: gorodkin@rth.dk (J.G.) Associate Editor: Alfonso Valencia
Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System

Electroencephalography (EEG) has recently gained popularity in user authentication systems since it is unique and less impacted by fraudulent interceptions. Although EEG is known to be sensitive to emotions, understanding the stability of brain responses to EEG-based authentication systems is challenging. In this study, we compared the effect of different emotion stimuli for the application in the EEG-based biometrics system (EBS). Initially, we pre-processed audio-visual evoked EEG potentials from the 'A Database for Emotion Analysis using Physiological Signals' (DEAP) dataset. A total of 21 time-domain and 33 frequency-domain features were extracted from the considered EEG signals in response to Low valence Low arousal (LVLA) and High valence low arousal (HVLA) stimuli. These features were fed as input to an XGBoost classifier to evaluate the performance and identify the significant features. The model performance was validated using leave-one-out cross-validation. The pipeline achieved high performance with multiclass accuracy of 80.97% and a binary-class accuracy of 99.41% with LVLA stimuli. In addition, it also achieved recall, precision and F-measure scores of 80.97%, 81.58% and 80.95%, respectively. For both the cases of LVLA and LVHA, skewness was the stand-out feature. We conclude that boring stimuli (negative experience) that fall under the LVLA category can elicit a more unique neuronal response than its counterpart the LVHA (positive experience). Thus, the proposed pipeline involving LVLA stimuli could be a potential authentication technique in security applications.
A subregion-based survival prediction framework for GBM via multi-sequence MRI space optimization and clustering-based feature bundling and construction

Aiming at accurate survival prediction of Glioblastoma (GBM) patients following radiation therapy, we developed a subregion-based survival prediction framework via a novel feature construction method on multi-sequence MRIs. The proposed method consists of two main steps: (1) a feature space optimization algorithm to determine the most appropriate matching relation derived between multi-sequence MRIs and tumor subregions, for using multimodal image data more reasonable; (2) a clustering-based feature bundling and construction algorithm to compress the high-dimensional extracted radiomic features and construct a smaller but effective set of features, for accurate prediction model construction. For each tumor subregion, a total of 680 radiomic features were extracted from one MRI sequence using Pyradiomics. Additional 71 geometric features and clinical information were collected resulting in an extreme high-dimensional feature space of 8231 to train and evaluate the survival prediction at 1 year, and the more challenging overall survival prediction. The framework was developed based on 98 GBM patients from the BraTS 2020 dataset under five-fold cross-validation, and tested on an external cohort of 19 GBM patients randomly selected from the same dataset. Finally, we identified the best matching relationship between each subregion and its corresponding MRI sequence, a subset of 235 features (out of 8231 features) were generated by the proposed feature bundling and construction framework. The subregion-based survival prediction framework achieved AUCs of 0.998 and 0.983 on the training and independent test cohort respectively for 1 year survival prediction, compared to AUCs of 0.940 and 0.923 for survival prediction using the 8231 initial extracted features for training and validation cohorts respectively. Finally, we further constructed an effective stacking structure ensemble regressor to predict the overall survival with the C-index of 0.872. The proposed subregion-based survival prediction framework allow us to better stratified patients towards personalized treatment of GBM.
The CDC Domestic Mpox Response — United States, 2022–2023

Monkeypox (mpox) is a serious viral zoonosis endemic in west and central Africa. An unprecedented global outbreak was first detected in May 2022. CDC activated its emergency outbreak response on May 23, 2022, and the outbreak was declared a Public Health Emergency of International Concern on July 23, 2022, by the World Health Organization (WHO),* and a U.S. Public Health Emergency on August 4, 2022, by the U.S. Department of Health and Human Services. † A U.S. government response was initiated, and CDC coordinated activities with the White House, the U.S. Department of Health and Human Services, and many other federal, state, and local partners. CDC quickly adapted surveillance systems, diagnostic tests, vaccines, therapeutics, grants, and communication systems originally developed for U.S. smallpox preparedness and other infectious diseases to fit the unique needs of the outbreak. In 1 year, more than 30,000 U.S. mpox cases were reported, more than 140,000 specimens were tested, >1.2 million doses of vaccine were administered, and more than 6,900 patients were treated with tecovirimat, an antiviral medication with activity against orthopoxviruses such as Variola virus and Monkeypox virus. Non-Hispanic Black (Black) and Hispanic or Latino (Hispanic) persons represented 33% and 31% of mpox cases, respectively; 87% of 42 fatal cases occurred in Black persons. Sexual contact among gay, bisexual, and other men who have sex with men (MSM) was rapidly identified as the primary risk for infection, resulting in profound changes in our scientific understanding of mpox clinical presentation, pathogenesis, and transmission dynamics. This report provides an overview of the first year of the response to the U.S. mpox outbreak by CDC, reviews lessons learned to improve response and future readiness, and previews continued mpox response and prevention activities as local viral transmission continues in multiple U.S. jurisdictions (Figure).
Optimal cut‐off value of the modified Toronto Clinical Neuropathy Score in the diagnosis of polyneuropathy

The modified Toronto Clinical Neuropathy Score (mTCNS) is a valid and reliable scale for the diagnosis and staging of diabetic sensorimotor polyneuropathy (DSP). The aim of this study was to determine the optimal diagnostic cut‐off value of the mTCNS in diverse polyneuropathies (PNPs).
Combination therapy with BMSCs‑exosomes and porous tantalum for the repair of femur supracondylar defects

In the field of orthopedics, defects in large bones have proven challenging to resolve. The aim of the present study was to address this problem through the combination of tantalum metal (pTa) with exosomes derived from bone marrow mesenchymal stem cells (BMSCs), which have the potential to enhance regeneration of full thickness femoral bone defects in rats. Cell culture results demonstrated that exosomes improved the proliferation and differentiation of BMSCs. Following establishment of a supracondylar femoral bone defect, exosomes and pTa were implanted into the defect area. Results demonstrated that pTa acts as a core scaffold for cell adhesion and exhibits good biocompatibility. Moreover, micro-CT scan results as well as histological examination demonstrated that pTa had a significant effect on osteogenesis, with the addition of exosomes further promoting bone tissue regeneration and repair. In conclusion, this novel composite scaffold can effectively promote bone regeneration in large bone defect areas, providing a new approach for the treatment of large bone defects.
Estimated US Pediatric Hospitalizations and School Absenteeism Associated With Accelerated COVID-19 Bivalent Booster Vaccination

Key Points Question Would accelerated COVID-19 bivalent booster vaccination uptake in the US be associated with decreased outcomes of pediatric hospitalizations and student absenteeism? Findings In this decision analytical model using US population estimates, a simulation model revealed that booster campaigns achieving an uptake similar to seasonal influenza vaccination could have prevented an estimated 10 019 pediatric hospitalizations and 5 448 694 days of school absenteeism from October 1, 2022, to March 31, 2023. Meaning These findings suggest that although COVID-19 prevention strategies often focus on older populations, the benefits of booster campaigns for children may be substantial.