Yoxas/statistical_literacy huggingface dataset:
Mucopolysaccharidosis type II (MPS II), or Hunter syndrome, is a rare X-linked metabolic disorder predominantly affecting males. Pabinafusp alfa, an iduronate-2-sulfatase enzyme designed to cross the blood-brain barrier, was approved in Japan in 2021 as the first enzyme replacement therapy targeting both the neuropathic and somatic signs and symptoms of MPS II. This study reports caregivers' experiences of MPS II patients receiving pabinafusp alfa through qualitative interviews. Semi-structured, qualitative interviews were conducted with caregivers at seven clinical sites in Japan using a semi-structured moderation guide (Voice of the Caregiver guide). Thematic analysis was applied to the interview transcripts to identify symptoms and health-related quality of life impacts at baseline, changes during treatment, and overall treatment experience. Seven caregivers from 16 trial sites participated, representing seven children aged 8-18 years who had received pabinafusp alfa for 3.3-3.5 years at the time of the interviews. Data suggest a general trend toward improvement in multiple aspects, although not all caregivers observed discernible changes. Reported cognitive improvements included language skills, concentration, self-control, eye contact, mental clarity, concept understanding, following instructions, and expressing personal needs. Further changes were reported that included musculoskeletal improvements and such somatic changes as motor function, mobility, organ involvement, joint mobility, sleep patterns, and fatigue. Four caregivers reported improvements in family quality of life, five expressed treatment satisfaction, and all seven indicated a strong willingness to continue treatment of their children with pabinafusp alfa. Caregivers' perspectives in this study demonstrate treatment satisfaction and improvement in various aspects of quality of life following therapy with pabinafusp alfa. These findings enhance understanding of pabinafusp alfa's potential benefits in treating MPS II and contribute to defining MPS II-specific outcome measures for future clinical trials.
Multi-parametric magnetic resonance imaging (mpMRI) is a diagnostic tool used for screening, localizing, and staging prostate cancer. Patients with Prostate Imaging Reporting and Data System (PI-RADS) score of 1 and 2 are considered negative mpMRI, with a lower likelihood of detecting clinically significant prostate cancer (csPCa). However, relying solely on mpMRI is insufficient to completely exclude csPCa, necessitating further stratification of csPCa patients using biomarkers. A retrospective study was conducted on mpMRI-negative patients who underwent prostate biopsy at the First Affiliated Hospital of Zhejiang University from January 2022 to June 2023. A total of 607 patients were included based on inclusion and exclusion criteria. Univariate and multivariate logistic regression analysis were performed to identify risk factors for diagnosing csPCa in patients with negative mpMRI. Receiver Operating Characteristic (ROC) curves were plotted to compare the discriminatory ability of different Prostate-Specific Antigen Density (PSAD) cutoff values for csPCa. Among the 607 patients with negative mpMRI, 73 patients were diagnosed with csPCa. In univariate logistic regression analysis, age, PSA, f/tPSA, prostate volume, and PSAD were all associated with diagnosing csPCa in patients with negative mpMRI (P < 0.05), with PSAD being the most accurate predictor. In multivariate logistic regression analysis, f/tPSA, age, and PSAD were independent predictors of csPCa (P < 0.05). PSAD cutoff value of 0.20 ng/ml/ml has better discriminatory ability for predicting csPCa and is a significant risk factor for csPCa in multivariate analysis. Age, f/tPSA, and PSAD are independent predictors of diagnosing csPCa in patients with negative mpMRI. It is suggested that patients with negative mpMRI and PSAD less than 0.20 ng/ml/ml could avoid prostate biopsy, as a PSAD cutoff value of 0.20 ng/ml/ml has better diagnostic performance than the traditional cutoff value of 0.15 ng/ml/ml.
Multi-tiered systems of support (MTSS) are effective in addressing challenges in schools through a tiered system of support and diagnostics. A broad field of research has developed over the past 50 years. This systematic literature review aims to provide an overview of MTSS quality, outcomes, and characteristics in elementary education research. The review includes international studies and focuses on MTSS approaches that integrate behavior modification. After searching several databases, 40 studies published between 2004 and 2020 met the criteria for closer examination. The review presents study characteristics and theoretical references of different MTSS, including location, time, sample, study design, outcome measures, groups involved, interventions, and effects. In summary, MTSS have been found to be effective in elementary schools internationally, particularly for behavior change. Future studies should investigate the interactions between interventions within the school setting and involve teachers, school staff, and stakeholders in MTSS development to improve the system's coherence and effectiveness. It's important to note that MTSS have a political dimension that affects implementation and sustainability and can impact society by improving school experiences and reducing negative behaviors.
Multidisciplinary care with free, rapid, and on-site bictegravir/emtricitabine/tenofovir alafenamide (B/F/TAF) dispensation may improve health outcomes among migrants living with HIV. However, models for rapid B/F/TAF initiation are not well studied among migrants living with HIV, and an understanding of how social determinants of health (SDH) may affect HIV-related health outcomes for migrants enrolled in such care models is limited. Within a 96-week pilot feasibility prospective cohort study at a multidisciplinary HIV clinic, participants received free B/F/TAF rapidly after care linkage. The effects of SDH (i.e., birth region, sexual orientation, living status, education, employment, French proficiency, health coverage, use of a public health facility outside our clinic for free blood tests, and time in Canada) and other covariates (i.e., age, sex) on median time to antiretroviral therapy (ART) initiation and HIV viral undetectability from care linkage were calculated via survival analyses. Thirty-five migrants were enrolled in this study. Median time to ART initiation and HIV undetectability was 5 days (range 0-50) and 57 days (range 5-365), respectively. Those who took significantly longer to initiate ART were aged <35 years, identified as heterosexual, had less than university-level education, or were unemployed. No factor was found to significantly affect time to undetectability. Despite the provision of free B/F/TAF, several SDH were linked to delays in ART initiation. However, once initiated and engaged, migrants living with HIV reached HIV undetectability efficiently. Findings provide preliminary support for adopting this care model with migrants living with HIV and suggest that SDH should be considered when designing clinical interventions for more equitable outcomes.
Multidisciplinary tumor conference (MTC) is a key instrument in multidisciplinary cancer care. In recent years, if and how patient participation in MTC can contribute to a more patient-centered care have been scientifically discussed. This study aimed to identify determinants of treatment confidence in the context of patient participation in MTC. Therefore, the association among health literacy-sensitive communication, trust in health-care providers (HCP), and treatment confidence is examined. This study used data from the multicenter, observational study "PINTU" on patient participation in MTC. Data were collected from November 2018 to February 2020. Validated scales for treatment confidence, health literacy-sensitive communication, and trust in providers were included in the structural equation modeling (SEM) analysis. A total of 95 patients participated in MTC. The sample compromised n = 80 completed datasets. The SEM fit measures indicated good fit of the proposed model. The analysis showed a positive association between health literacy-sensitive communication and treatment confidence when adding the mediating effect of trust in providers. Patient-centered communication during MTC in combination with a trustful relationship between participating patients and health-care providers is positively associated with treatment confidence. The results indicated the relevance of a trustful doctor-patient communication and relationship. Trainings for physicians targeting patient-centered communication could be a promising approach to strengthen patient participation.
Multilayer neural networks set the current state of the art for many technical classification problems. But, these networks are still, essentially, black boxes in terms of analyzing them and predicting their performance. Here, we develop a statistical theory for the one-layer perceptron and show that it can predict performances of a surprisingly large variety of neural networks with different architectures. A general theory of classification with perceptrons is developed by generalizing an existing theory for analyzing reservoir computing models and connectionist models for symbolic reasoning known as vector symbolic architectures. Our statistical theory offers three formulas leveraging the signal statistics with increasing detail. The formulas are analytically intractable, but can be evaluated numerically. The description level that captures maximum details requires stochastic sampling methods. Depending on the network model, the simpler formulas already yield high prediction accuracy. The quality of the theory predictions is assessed in three experimental settings, a memorization task for echo state networks (ESNs) from reservoir computing literature, a collection of classification datasets for shallow randomly connected networks, and the ImageNet dataset for deep convolutional neural networks. We find that the second description level of the perceptron theory can predict the performance of types of ESNs, which could not be described previously. Furthermore, the theory can predict deep multilayer neural networks by being applied to their output layer. While other methods for prediction of neural networks performance commonly require to train an estimator model, the proposed theory requires only the first two moments of the distribution of the postsynaptic sums in the output neurons. Moreover, the perceptron theory compares favorably to other methods that do not rely on training an estimator model.
Multilevel models have gained immense popularity across almost every discipline due to the presence of hierarchy in most data and phenomena. In this paper, we present a systematic review on the adoption and application of multilevel models and the important information reported on the results generated from the use of these models. The review was performed by searching Google Scholar for original research articles on the application of multilevel models published between 2010 and 2020. The search strategy involved topics such as "multilevel models," "hierarchical linear models," and "mixed models with hierarchy." The search placed more emphasis on the application of hierarchical models in any discipline but excluded software methodological development and related articles. A total of 121 articles were initially obtained from the search results. However, 65 articles met the inclusion criteria for the review. Out of the 65 articles reviewed, 46.2% were related to health/epidemiology, 15.4% to education and psychology, and 16.9% to social life. The majority of the articles (78.5%) were two-level models, and most of these studies modelled univariate responses. However, the few that modelled more than one response modelled them separately. Moreover, 83.1% were cross-sectional design, and 9.2% and 6.2% were longitudinal and repeated measures, respectively. Moreover, a little over half (55.4%) of articles reported on the intraclass correlation measure, and all articles indicated the response variable distribution where most (47.7%) were normally distributed. Only 58.5% of articles reported on the estimation methods used as Bayesian (20%) and MLE (18.5%). Again, model validation measures and statistical software were reported in 70.8% and 90.8% articles, respectively. There is an increase in the utilization of multilevel modelling in the last decade, which could be attributed to the presence of clustered and hierarchically correlated data structures. There is a need for improvement in the area of measurement and reporting on the intraclass correlation, parameter estimation, and variable selection measures to further improve the quality of the application of multilevel models. The integration of spatial effects into multilevel models is very limited and needs to be explored in the future.
Multimedia technology holds paramount importance in driving innovation within vocational education, significantly influencing learning satisfaction. Its integration facilitates dynamic and interactive learning environments, catering to diverse learning styles and preferences. Moreover, multimedia technology enables educators to simulate real-world scenarios, providing practical and hands-on training opportunities. This aspect is particularly valuable in vocational education, where practical skills and application are required. The paper investigates the impact of multimedia technology in enhancing learning satisfaction within innovative vocational education. It delves into the utilization of multimedia tools and their correlation with learner satisfaction, exploring how these technologies augment engagement and comprehension in vocational training. The primary data from 515 students of vocational colleges of China has been collected and regression analysis is applied for empirical analysis. The findings of the study highlight that multimedia technology has positive relationship with innovative vocational education and learning outcome. The findings contribute valuable insights for policymakers regarding significant role multimedia plays in fostering enhanced learning experiences and overall satisfaction among vocational learners.
Multimodal integration combines information from different sources or modalities to gain a more comprehensive understanding of a phenomenon. The challenges in multi-omics data analysis lie in the complexity, high dimensionality, and heterogeneity of the data, which demands sophisticated computational tools and visualization methods for proper interpretation and visualization of multi-omics data. In this paper, we propose a novel method, termed Orthogonal Multimodality Integration and Clustering (OMIC), for analyzing CITE-seq. Our approach enables researchers to integrate multiple sources of information while accounting for the dependence among them. We demonstrate the effectiveness of our approach using CITE-seq data sets for cell clustering. Our results show that our approach outperforms existing methods in terms of accuracy, computational efficiency, and interpretability. We conclude that our proposed OMIC method provides a powerful tool for multimodal data analysis that greatly improves the feasibility and reliability of integrated data.
Multimorbid and frail elderly patients often carry a high burden of treatment. Hospitalization due to the onset of an acute illness can disrupt the fragile balance, resulting in further readmissions after hospital discharge. Current models of care in Germany do not meet the needs of this patient group. Rather lack of coordination and integration of care combined with a lack of interdisciplinary approaches result in fragmented and inadequate care and increase the burden of treatment even more. eliPfad is a randomized controlled trial conducted in 6 hospitals in Germany. Multimorbid elderly patients aged 55 or older are randomly assigned to the intervention or control group. Patients in the intervention group receive the eliPfad intervention additional to standard care. The core components of eliPfad are: Early assessment of patients' individual treatment burden and support through a specially trained case manager Involvement of the patient's general practitioner (GP) right from the beginning of the hospital stay Preparation of an individual, cross-sectoral treatment plan through the interdisciplinary hospital team with the involvement of the patient's GP Establishment of a cross-sectoral electronic patient record (e-ePA) for documentation and cross-sectoral exchange Support/Promote patient adherence Tailored early rehabilitation during the hospital stay, which is continued at home Close-tele-monitoring of medically meaningful vital parameters through the use of tablets, digital devices, and personal contacts in the home environment The intervention period begins in the hospital and continues 6 weeks after discharge. Patients in the control group will be treated according to standard clinical care and discharged according to current discharge management. The primary aim is the prevention/reduction of readmissions in the first 6 months after discharge. In addition, the impact on health-related quality of life, the burden of treatment, survival, self-management, medication prescription, health literacy, patient-centered care, cost-effectiveness, and process evaluation will be examined. Nine hundred forty-eight patients will be randomized 1:1 to intervention and control group. If eliPfad leads to fewer readmissions, proves (cost-)effective, and lowers the treatment burden, it should be introduced as a new standard of care in the German healthcare system. The trial was registered in the German Clinical Trials Registry (Deutsches Register Klinischer Studien (DRKS)) on 08/14/2023 under the ID DRKS00031500 .
Multiple COVID-19 vaccines were proven to be safe and effective in curbing severe illness, but despite vaccine availability, vaccination rates were relatively low in the United States (U.S.). To better understand factors associated with low COVID-19 vaccine uptake in the U.S., our study provides a comprehensive, data-driven population-level statistical analysis at the county level. We find that political affiliation, as determined by the proportion of votes received by the Republican candidate in the 2020 presidential election, has the strongest association with our response variable, the percent of the population that received no COVID-19 vaccine. The next strongest association was median household income, which has a negative association. The percentage of Black people and the average number of vehicles per household are positively associated with the percent unvaccinated. In contrast, COVID-19 infection rate, percentage of Latinx people, postsecondary education percentage, median age, and prior non-COVID-19 childhood vaccination coverage are negatively associated with percent unvaccinated. Unlike previous studies, we do not find significant relationships between cable TV news viewership or Twitter misinformation variables with COVID-19 vaccine uptake. These results shed light on some factors that may impact vaccination choice in the U.S. and can be used to target specific populations for educational outreach and vaccine campaign strategies in efforts to increase vaccination uptake.
Multiple factors influence the fall risk in end-stage kidney disease. This study aims to investigate how medication factors influence the interpretation of fall risk due to age, gender, and years of dialysis treatment among patients undergoing hemodialysis (HD). A cross-sectional study was carried out in 2023 using the Johns Hopkins Fall Risk Assessment tool. Participants were recruited from the HD unit at a tertiary care academic medical center in Ajman, UAE. Data were analyzed between different ages, genders, and years on HD categories with or without medication factors. Data were collected and analyzed for 44 patients. The fall risk of the study population assessed with the Kruskal-Wallis test showed no difference between different age groups (P = 0.43) but did show a significant difference when the score of medication factor was removed from the fall risk estimation (P = 0.002). A pairwise analysis showed fall risk score of the age group 46-60 years was differing from the age cohort >60 (P < 0.001). A positive moderate correlation (Spearman's correlation coefficient 0.514 was found, with a P < 0.001) was seen with an increase in age and fall risk only when the medication factor was removed from the fall risk estimation. Results on gender or duration of dialysis were insignificant. Medication factors being a significant contributor to fall risk among the study population was found to mask the fall risk difference between age groups 46-60 years and >60 years. Such influence was not found for gender or duration of dialysis.
Multiple myeloma (MM) in rural western Kenya is characterized by under and late diagnosis with poor long-term outcomes. Inadequate skilled rural health care teams are partly to blame. The Extension for Community Healthcare Outcomes (ECHO) model attempts to bridge this skills gap by linking rural primary/secondary health care teams (spokes) to myeloma experts in a tertiary care center (hub) in a longitudinal training program. A hub team comprising myeloma experts and administrators from Moi Teaching and Referral Hospital/Academic Model Providing Access to Healthcare was assembled and spoke sites were recruited from rural health care facilities across western Kenya. A curriculum was developed by incorporating input from spokes on their perceived skills gaps in myeloma. Participants joined sessions remotely through virtual meeting technology. ECHO sessions consisted of a spoke-led case presentation with guided discussion followed by an expert-led lecture. An end-of-program survey was used to evaluate participant satisfaction, knowledge, and practice patterns. A total of eight sessions were conducted between April and November 2021 with a median of 40 attendees per session drawn from diverse health care disciplines. Twenty-four spoke sites were identified from 15 counties across western Kenya. The majority of attendees reported satisfaction with the ECHO program (25 of 29) and improvement in their myeloma knowledge (24 of 29). There were 74 new myeloma diagnoses made at the hub site in 2021, representing a 35% increase from the previous 3-year average despite the COVID-19 pandemic that suppressed health care access globally. The pilot ECHO model was successfully implemented in myeloma training for rural-based health care teams. Key attributes included collaborative curriculum development, interactive case-based bidirectional learning, and multidisciplinary engagement.