Yoxas/statistical_literacy huggingface dataset:
Osteoarthritis (OA) is one of the most common disabilities in the elderly. When conservative management fails, total joint arthroplasty (TJA) is the treatment of choice for end-stage OA. Since quality and durability of implants has steadily improved, pre -and postsurgical processes moved into the focus of research. Hence, eHealth approaches offer an opportunity to provide a more available continuity of care. Regarding individualized pre-, peri-, and postsurgical stages, eHealth is expected to improve patient engagement, self-care, and outcomes across the surgical pathway. Aim of this study is to evaluate the effectiveness of the eHealth application "alley" as an adjuvant intervention to TJA. The app provides comprehensive information to empower patient with hip or knee OA to prepare and accompany them for their TJA surgery. Our primary hypothesis is that the pre- and postoperative adjuvant use of the eHealth application "alley" (intervention group, IG) leads to improved functional outcome. Prospective, randomized, controlled, multi-center trial including n = 200 patients diagnosed with hip and n = 200 patients with knee OA (n = 200) scheduled for TJA. Patients of both groups will be randomly assigned to one of two study arms. Patients in the intervention group will receive access to the functions of the "alley" app. The app presents informative (e.g., information about osteoarthritis), organizational (e.g., information about medical rehabilitation), and emotional/empowerment (e.g., information about the relationship between mood and pain) content. Patients evaluate their condition and functional level by means of standardized digitally questionnaires. Patients in the control group will not receive any functions of the app. Assessments will be performed at baseline before, 10 days after, 1 months after, 3 months after, 6 months after, and 12 months after TJA. Primary outcome is change from baseline measured by the Hip Osteoarthritis Outcome Score or Knee injury and Osteoarthritis Outcome Score 3 months after TJA. The statistical analysis (t-test for independent variables with effect size Cohen's d) is performed separately for patients with TKA and THA. Overall, the study aims to improve the understanding of the benefits of eHealth applications in the treatment of elderly patients with knee or hip arthroplasty. The approach is novel since a health care companion is combined with a digital information platform enabling direct and continuous feedback from the patients to the therapeutic treatment team. As the study investigate the effectiveness under everyday conditions, it is not feasible to control whether the patients in the IG read the educational information of the app respectively the control group consume additional information from other sources. However, this increases the external validity of the study if significant effects for the app can be demonstrated. German Clinical Trials Register: DRKS00025608. Registered on 21 June 2021.
Osteoporosis (OP) is closely associated with gut microbiota (GM), yet the nature of their causal relationship remains elusive. Therefore, this study aims to reverse causality between GM and OP by using population cohorts and two-sample MR (TSMR) analysis. In this study, we conducted an extensive genome-wide association study (GWAS) using publicly accessible summary statistics data for GM and OP. Employing rigorous criteria (p < 1*e-5), we identified independent genetic loci that exhibited significant associations with GM relative abundances as instrumental variables (IVs). A causal evaluation was primarily carried out using the inverse variance-weighted (IVW) method, supplemented by additional analyses such as MR-Egger, weighted median, simple mode, and weighted mode. We unveiled that increased abundances of the family Pasteurellaceae, order Pasteurellales, and genus Ruminococcaceae UCG004 were linked to an increased risk of OP. Conversely, the family Oxalobacteraceae, unknown family id.1000006161, genus Lachnospiraceae NK4A136 group, unknown genus id.1000006162, and order NB1n were associated with a reduced risk of OP. To ensure the reliability of our findings, we conducted quality assessments through Cochrane's Q test and a leave-one-out analysis. Furthermore, the stability and consistency of the results were confirmed by the MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) global test, and sensitivity analysis (p > 0.05). Our study reveals the causal relationships between 211 GM taxa and OP, pinpointing specific GM taxa associated with the risk of OP. This research sheds light on the genetic mechanisms that underlie GM-mediated OP and opens up promising avenues for identifying valuable biomarkers and potential therapeutic targets in future OP research. This study establishes a substantial GM-OP link with specific taxa being identified, offering biomarkers for early detection, tailored interventions, and improved patient education. These findings enhance OP diagnosis, prevention, and treatment, promising more effective, individualized care and inspiring future research.
Osteoporosis is characterized by decreased bone mass and decreased bone quality, leading to increased bone fragility and risk of fractures. The number of fractures due to osteoporosis is projected to increase to over three million by the year 2025 and cost $25.3 billion annually. It ranks highly among diseases that cause patients to become bedridden with serious complications and reduced quality of life. Additionally, osteoporosis disproportionately affects Hispanics, which comprise most of the Rio Grande Valley (RGV) population. Therefore, our primary objective was to determine the prevalence of osteoporosis within the RGV. Additionally, we had secondary objectives to determine the screening rates of osteoporosis in the RGV and identify other potential risk factors associated with osteoporosis. We hypothesize that individuals residing in the RGV have higher rates of osteoporosis and lower rates of osteoporosis screening than the national average. This retrospective observational cross-sectional study utilized Medicare beneficiary data via the "Mapping Medicare Disparities by Population" interactive tool. Osteoporosis data were compared within the RGV (comprising Starr, Hidalgo, Cameron, and Willacy counties) and compared with national averages between the years 2016 and 2021. Statistical analysis included prevalence ratios with 95% confidence intervals and chi-square values when applicable. Among Medicare beneficiaries residing in the RGV, there are higher rates of osteoporosis compared to the national average (11.5% vs. 7.20%; p < .00001). Screening for osteoporosis within the RGV is above the national average (9.29% vs. 6.67%, p < .00001). Hispanics residing in the RGV have higher overall rates of osteoporosis than Caucasians residing in the RGV (12.3% vs. 8.60%, p < .00001). Females residing in the RGV have nearly twice the rate of osteoporosis compared to the national average (19.1% vs. 11.8%, p < .00001) and 6.58 times the rate of males residing in the RGV (19.1% vs. 2.9%, p < .00001). Individuals residing in the RGV are disproportionately affected by osteoporosis. Despite increased screening rates seen among Medicare beneficiaries, we also suspect many individuals, uninsured or undocumented, have not received any appropriate osteoporosis screening. Risk factors in the RGV associated with higher rates of osteoporosis could include low education levels, socioeconomic status, physical activity, and mineral intake. These results demonstrate a need to address osteoporosis health literacy, promote earlier interventions to treat osteoporosis and increase healthcare accessibility in the RGV.
Osteoporosis poses a significant health burden, particularly among postmenopausal women. While obesity in the form of BMI has been implicated in various health conditions, the relationship between waist-hip ratio (WHR) and osteoporosis remains debated. This study aims to estimate the prevalence of osteoporosis risk and explore the association between WHR and osteoporosis risk among postmenopausal women in rural South India. A community-based cross-sectional study was conducted in the Chengalpattu district of Tamil Nadu. The study enrolled 435 postmenopausal women aged 45 years and above and the data were collected on socio-demographic characteristics, anthropometric measurements, and osteoporosis risk assessment using the Osteoporosis Self-assessment Tool for Asian Women (OSTA) scale. Logistic regression analysis was performed to identify factors associated with osteoporosis risk with 95%CI. The mean (SD) age of participants was 54.5 (8.6) years, 87% were married, 33% were illiterate with mean (SD) WHR of 0.88 (0.1). Around 80.5% of the participants were categorized as low risk, 16.1% as intermediate risk, and 3.5% as high risk based on OSTA scores. Older age, lower educational attainment, and higher waist-hip ratio were significantly associated with increased osteoporosis risk. This community-based study found a 20% osteoporosis risk among postmenopausal women using the OSTA scale, with age, lower education, and waist-hip ratio as key determinants. Early identification and interventions, particularly targeting older and obese individuals, are crucial to alleviate the burden and complications of osteoporosis.
Osteoporosis, the silent epidemic, is defined as a systemic skeletal disease characterized by low mineral bone mass and micro-architectural deterioration of bone tissue. Osteoporosis is considered a burden to global economic, social, and health development. Osteoporosis exerts a substantial global influence, markedly influencing rates of illness and death on a broad scale. Clinical features of osteoporosis can include chronic back pain, loss of height, and a stooped posture, as well as an increased risk of fractures in the spine, hip, and wrist. Accurate identification and monitoring of these clinical features are essential for effective management and treatment of osteoporosis. This study aims to identify the knowledge, attitudes, and practices (KAP) of adults (over 18 years) about osteoporosis and identify relations between knowledge, attitudes, and practices with demographic data. Furthermore, to assess the risk factors and preventive measures for osteoporosis. Data from 446 responders were collected using a Google Forms questionnaire, including questions to assess knowledge, attitudes, and practice levels among adults 18 years and above in the United Arab Emirates (UAE). The collected data and statistical analysis were done through the IBM® SPSS® Statistics. Chi-Square was used in SPSS Statistics; the chi-square test was used for the relation between categorical variables, and P less than 0.05 was the cut-off level of significance. The research revealed that 41.9% of the participants had good knowledge, 38.8% had a positive attitude, and 45.3% had poor practices. The results also showed that there is a statistically significant correlation between gender and knowledge, attitudes, and practices. Our research demonstrates that there's a statistically significant correlation between gender variables with knowledge, attitudes, and practices. These findings have important implications in assessing the correlation between variables in our research that could be used to prevent osteoporosis further, target the specific demographic group, and provide the required education. Overall, our research contributes to a better understanding of the knowledge, attitude, and practices towards Osteoporosis among adults in the UAE and underscores the importance of further awareness in this area.
Osteoporotic fractures significantly impact individuals's quality of life and exert substantial pressure on the social pension system. This study aims to develop prediction models for osteoporotic fracture and uncover potential risk factors based on Electronic Health Records (EHR). Data of patients with osteoporosis were extracted from the EHR of Xinhua Hospital (July 2012-October 2017). Demographic and clinical features were used to develop prediction models based on 12 independent machine learning (ML) algorithms and 3 hybrid ML models. To facilitate a nuanced interpretation of the results, a comprehensive importance score was conceived, incorporating various perspectives to effectively discern and mine critical features from the data. A total of 8530 patients with osteoporosis were included for analysis, of which 1090 cases (12.8%) were fracture patients. The hybrid model that synergistically combines the Support Vector Machine (SVM) and XGBoost algorithms demonstrated the best predictive performance in terms of accuracy and precision (above 90%) among all benchmark models. Blood Calcium, Alkaline phosphatase (ALP), C-reactive Protein (CRP), Apolipoprotein A/B ratio and High-density lipoprotein cholesterol (HDL-C) were statistically found to be associated with osteoporotic fracture. The hybrid machine learning model can be a reliable tool for predicting the risk of fracture in patients with osteoporosis. It is expected to assist clinicians in identifying high-risk fracture patients and implementing early interventions.
Our aim is to reveal the interaction of cultural and religious influences with professional equipment by determining the level of knowledge, sexual attitudes, and homophobia of medical students about LGBTI+ individuals. The study included 324 students from our faculty of medicine. The Hudson and Ricketts Homophobia scale, the Attitudes Towards Lesbians and Gay Men scale, and the Hendrick Sexual Attitudes scale were used with the sociodemograpic data form. Data were collected and analyzed using descriptive and inferential statistical tests. The mean score of the students from the Hudson and Ricketts Homophobia scale was 58.50. The findings of our study support that medical students consider that the education they receive in this regard is inadequate. One of the goals of undergraduate medical education is the provision of health services to all segments of society; therefore, it is recommended to make improvements in the curriculum in this regard.
Our aim was to assess the use of dual/poly tobacco in a sample of pregnant women. cross-sectional survey. Twenty prenatal care units in Botucatu, Sao Paulo, Brazil. We evaluated 127 high-risk pregnant smokers during prenatal care. Those who were 12-38 weeks pregnant and were currently smoking conventional cigarettes. The study enrollment took place between January 2015 and December 2015. The dual/poly prevalence of tobacco products during pregnancy and the characteristics related to smoking in pregnant smokers through a specific questionnaire containing questions related to sociodemographic characteristics, comorbidities, gestational history, smoking history, secondhand smoke exposure, nicotine dependence, motivation stage and use of alternative forms of tobacco. Mean age was 26.9 ± 6.6 years, most had only elementary education and belonged to lower income economic groups. Twenty-five (19.7%) smoked conventional cigarettes only while 102 used conventional and alternative forms of tobacco products. Smoking pack-years was significantly lower in those only smoking conventional cigarettes than in dual/poly users. Proportion of patients with elevated degree of nicotine dependence was higher in conventional cigarettes users. On the other side, alcohol intake was higher in dual/poly smokers when compared to conventional cigarettes group. The alternative forms of smoking were associated with significantly higher occurrences of comorbidities as pulmonary, cardiovascular and cancer. The prevalence of alternative forms users of smoking products is high during pregnancy. These data reinforce the importance of a family approach towards smoking in pregnant women and education about the risks of alternative forms of tobacco.
Our aim was to characterise the in-depth metabolic response to aerobic exercise and the impact of residual pancreatic beta cell function in type 1 diabetes. We also aimed to use the metabolome to distinguish individuals with type 1 diabetes with reduced maximal aerobic capacity in exercise defined by V˙O2peak . Thirty participants with type 1 diabetes (≥3 years duration) and 30 control participants were recruited. Groups did not differ in age or sex. After quantification of peak stimulated C-peptide, participants were categorised into those with undetectable (<3 pmol/l), low (3-200 pmol/l) or high (>200 pmol/l) residual beta cell function. Maximal aerobic capacity was assessed by V˙O2peak test and did not differ between control and type 1 diabetes groups. All participants completed 45 min of incline treadmill walking (60% V˙O2peak ) with venous blood taken prior to exercise, immediately post exercise and after 60 min recovery. Serum was analysed using targeted metabolomics. Metabolomic data were analysed by multivariate statistics to define the metabolic phenotype of exercise in type 1 diabetes. Receiver operating characteristic (ROC) curves were used to identify circulating metabolomic markers of maximal aerobic capacity ( V˙O2peak ) during exercise in health and type 1 diabetes. Maximal aerobic capacity ( V˙O2peak ) inversely correlated with HbA1c in the type 1 diabetes group (r2=0.17, p=0.024). Higher resting serum tricarboxylic acid cycle metabolites malic acid (fold change 1.4, p=0.001) and lactate (fold change 1.22, p=1.23×10-5) differentiated people with type 1 diabetes. Higher serum acylcarnitines (AC) (AC C14:1, F value=12.25, p=0.001345; AC C12, F value=11.055, p=0.0018) were unique to the metabolic response to exercise in people with type 1 diabetes. C-peptide status differentially affected metabolic responses in serum ACs during exercise (AC C18:1, leverage 0.066; squared prediction error 3.07). The malic acid/pyruvate ratio in rested serum was diagnostic for maximal aerobic capacity ( V˙O2peak ) in people with type 1 diabetes (ROC curve AUC 0.867 [95% CI 0.716, 0.956]). The serum metabolome distinguishes high and low maximal aerobic capacity and has diagnostic potential for facilitating personalised medicine approaches to manage aerobic exercise and fitness in type 1 diabetes.
Our aim was to evaluate the association between eHealth literacy and lifestyle behaviors to intervene among Chinese university students. The Chinese eHealth Literacy Scale (C-eHEALS) questionnaire was used to investigate the eHealth literacy level and association with lifestyle behaviors among Chinese university students. Independent sample t-test and Pearson's correlation coefficient were used by statistical software SPSS v20. In the first round, 5,151 university students participated in the study, including 71.46% female and 28.54% male, aged 18-22 (93.13%).The average eHealth literacy score was 26.81 ± 5.83. Four lifestyle behaviors (e.g., exercise, smoking, drinking and sleeping) were all significantly correlated with eHealth literacy scores and demonstrated significant differences. In the second investigation (N = 2,939), the average eHealth literacy score was 31.64 ± 6.44, a notable improvement compared with the first investigation. Those in the group with high eHealth literacy scores have a healthier lifestyle than those in the low-score group. Training in eHealth-related resources is a positive measure to improve university students' eHealth literacy.
Our goal was to improve placement success rates for peripheral arterial line (PAL) placements by introducing an ultrasound-guided (USg) approach. Our aim was to maintain success rates over 70% within 18 months. Interventions included development of a training curriculum, and procedure standardization. Among 302 patients, 115 underwent USg catheter placement; the traditional method was used in 187 patients. Outcome measures were first-attempt and overall success rates. Process measures were proportion of PALs placed under US guidance, trainer availability, and trainee sign-off. Line complications were balancing measures. Statistical process control charts were used to monitor metrics. Sustained improvement was seen with the USg approach. The USg approach had first and overall attempt success by the trainers (i.e., independent users) of 83.7% (77/92) and 96.5% (111/115), compared to 50.3% (82/163) and 73.8% (138/187) with the traditional approach. Introducing the USg approach had a significant impact on PAL placement success in neonatal patients.
Our hospice caters to referrals from the wide areas in the northern Indian territory. A descriptive analysis of hospice admissions can bring to light, the status of palliative care in the region overall. The aim was to assess the clinical and demographic profile of hospice admissions in New Delhi during the time period 2016-2017. Hospice admission records from the calendar year 2016 were digitized from paper charts, and statistical analysis was carried out using SPSS v21. Patient and caregiver demographic profile and dominant referral and utilization patterns were retrospectively assessed. One hundred and fifty-four admissions (mean age 51.8 ± 15 years; 60% females) were recorded. Up to one-third of the patients (48, 31%) were single at the time of admission. Majority of the patients had below 10th grade literacy level (116, 75.3%) and belonged to low socioeconomic status. Two large tertiary care centers were the most common referrers (54.6%). The top three diagnoses were head-and-neck cancers (56, 36.4%), gastrointestinal cancers (27, 17.5%), and metastatic breast cancer (23, 14.9%). Major patient-reported debilities were pain (73%), dysphagia (51%), and incontinence (45%). The mean duration from diagnosis to hospice referral was 2.7 ± 0.7 years. Majority of the patients (76%) reported to have undergone some form of oncologic treatment. Up to two-thirds of the patients received opioids with or without additional supportive care. Pain, dysphagia, and incontinence were the most common reasons for hospice referral, with incontinence being significantly correlated with the divorced status. There were no differences in the prevalence of other symptoms with relation to the marital status. Data on hospice utilization patterns in India are limited to pilot experiences. More data are needed to drive national-level policies.
Our institution recently implemented a virtual reality (VR) skills curriculum for general surgery residents using the SimNow simulator. Based on a content alignment study, we revised the curriculum to include only 20 of 33 VR tasks and we added 3 previously validated inanimate tasks. The purpose of this study was to establish expert-derived proficiency levels for all tasks and to evaluate the validity of the scoring for the VR tasks. Two expert robotic surgeons performed 5 repetitions of each VR and inanimate task. The trimmed mean (lowest scoring attempt and outliers [>2 standard deviations] were eliminated) was defined as the expert level for each task. For the VR tasks, expert levels were compared to resident performance to evaluate validity. This study was conducted at the University of Texas Southwestern Medical Center (Dallas, TX), a tertiary care academic teaching hospital. Two expert robotic surgeons participated in this study. The data from 42 residents (PGY2-4) who completed the original curriculum was used to represent novice performance. Comparison of expert levels and resident performance was statistically significant for 15 VR tasks (supporting validity) and approached significance (p = 0.06, 0.09) for 2 VR tasks; expert levels were designated as proficiency levels for these 17 tasks. Group comparisons were clearly not significant (p = 0.2-0.8) for 3 VR tasks; 2 of these 3 tasks were retained as introductory exercises (with 3 repetitions required) and 1 was excluded. For the 3 inanimate tasks, expert levels minus 2 standard deviations were designated as proficiency levels. This analysis generated validity evidence for 15 VR tasks and established expert-derived proficiency levels for 17 VR tasks and 3 inanimate tasks. Our proposed curriculum now consists of 19 VR and 3 inanimate tasks using the selected proficiency levels. We anticipate that this design will maximize curriculum efficiency and effectiveness.