Digital health interventions to promote healthy lifestyle in hemodialysis patients: an interventional pilot study.

Low physical activity has been associated with poor prognosis in hemodialysis (HD) patients. Interventions to maintain healthy lifestyle in this population are important to reduce mortality. This study aimed to evaluate the effectiveness of digital health interventions (DHIs) for improving the physical activity and health-related quality of life (HRQoL) in HD patients. The 24-week prospective study enrolled 31 clinically stable HD patients. All participants were assigned home exercises and provided with wearable devices. Dietary and exercise information was uploaded to a health management platform. Suggestions about diet and exercise were provided, and a social media group was created. Physical performance testing was performed at baseline and during weeks 4, 8, 12, 16 and 24. HRQoL and nutritional status were evaluated. A total of 25 participants completed the study. After the interventions, the daily step count increased 1658 steps. The 10-time-repeated sit-to-stand test reduced by 4.4 s, the sit-to-stand transfers in 60 s increased 12 repetitions, the distance of six-minute walk test (6MWT) increased by 55.4 m. The mental health components and burden of kidney disease of the Kidney Disease Quality of Life survey, and subjective global assessment (SGA) scores improved. By Spearman correlation, the monthly step count correlated positively with 6MWT and SGA. DHIs that combined wearable devices, a health management platform, and social media could strengthen physical activity and improve the HRQoL and nutrition of maintenance HD patients. The results outline a new model to promote healthy lifestyle behaviors in HD patients.

Environmental pollutants increase the risks of acute exacerbation in patients with chronic airway disease.

Objective: Respiratory infections are a common cause of acute exacerbations in patients with chronic airway disease, however, environmental factors such as air pollution can also contribute to these exacerbations. The study aimed to determine the correlation between pollutant levels and exacerbation risks in areas exposed to environmental pollution sources. Methods: From 2015 to 2016, a total of 788 patients with chronic airway diseases were enrolled in a study. Their medical records, including hospital visits due to acute exacerbations of varying severity were analyzed. Additionally, data on daily pollutant levels from the Air Quality Monitoring Network from 2014 to 2016 was also collected and analyzed. Results: Patients with chronic airway disease and poor lung function (FEV1 < 50% or obstructive ventilatory defect) have a higher risk of severe acute exacerbations and are more likely to experience more than two severe acute exacerbations within a year. The study found that in areas exposed to environmental pollution sources, there is a significant correlation between NO2, O3, and humidity with the main causes of severe acute exacerbation. When the levels of NO2 were higher than 16.65 ppb, O3 higher than 35.65 ppb, or humidity higher than 76.95%, the risk of severe acute exacerbation in patients with chronic airway disease increased. Conclusion: Acute exacerbations of chronic airway disease can be triggered by both the underlying disease state and the presence of air pollution. Computer simulations and early warning systems should be developed to predict acute exacerbations of chronic airway disease based on dynamic changes in air pollution.

The 10 top-cited authors who published papers in journal medicine since 2000 using the betweenness centrality to identify unique names: Bibliometric analysis.

BACKGROUND: Numerous studies have explored the most productive and influential authors in a specific field. However, 2 challenges arise when conducting such research. First, some authors may have identical names in the study data, and second, the contributions of coauthors may vary in the article by line, requiring consideration. Failure to address these issues may result in biased research findings. Our objective was to illustrate how the author-weighted scheme (AWS) and betweenness centrality (BC) can be employed to identify the 10 most frequently cited authors in a particular journal and analyze their research themes. METHODS: We collected 24,058 abstracts from the PubMed library between 2000 and 2020 using the keyword "Medicine [Journal]." Author names, countries/regions, and medical subject headings (MeSH terms) were collected. The AWS to identify the top 10 authors with a higher x-index was applied. To address the issue of authors with identical names affiliated with different research institutes, we utilized the BC method. Social network analysis (SNA) was conducted, and 10 major clusters were identified to highlight authors with a higher x-index within the corresponding clusters. We utilized SNA to analyze the MeSH terms from articles of the 10 top-cited authors to identify their research themes. RESULTS: Our findings revealed the following: within the top 10 cited authors, 2 authors from China shared identical names with Jing Li and Tao-Wang; JA Winkelstein from Maryland (US) had the highest x-index (15.58); Chia-Hung Kao from Taiwan was the most prolific author, having published 115 articles in Medicine since 2003; and the 3 primary research themes, namely, complications, etiology, and epidemiology, were identified using MeSH terms from the 10 most frequently cited authors. CONCLUSIONS: Using AWS and BC, we identified the top 10 most cited authors. The research methods we utilized in this study (BC and AWS) have the potential to be applied to other bibliometric analyses in the future.

Can peripheral biomarkers reflect the psychological condition in geriatric populations? The influence of cardiovascular comorbidities.

BACKGROUND: Although previous studies indicated the association between peripheral biomarkers and psychological conditions, a higher prevalence of cardiovascular diseases (CVD) among geriatric populations may hinder the applicability of the biomarkers. The objective of this study was to assess the adequacy of the application of biomarkers to evaluate psychological conditions among geriatric populations. METHOD: We collected information on the demographics and history of CVD in all participants. All participants completed the Brief Symptom Rating Scale (BSRS-5) and the Chinese Happiness Inventory (CHI), which are the measurement of negative and positive psychological conditions, respectively. Four indicators of the peripheral biomarkers, including the standard deviation of normal to normal RR intervals (SDNN), finger temperature, skin conductance, and electromyogram were collected for each participant during a 5-min resting state. Multiple linear regression models were conducted to evaluate the association between the biomarkers and the psychological measurements (BSRS-5, CHI) with and without the inclusion of the participants with CVD. RESULTS: A total of 233 participants without CVD (non-CVD group) and 283 participants with CVD (CVD group) were included. The CVD group was older and with higher body mass index compared to the non-CVD group. In the multiple linear regression model with all participants, only BSRS-5 scores had a positive association with electromyogram. After the exclusion of the CVD group, the association between the BSRS-5 scores and electromyogram was more relevant, while CHI scores became positively associated with SDNN. CONCLUSIONS: A single measurement of the peripheral biomarker may be insufficient to depict psychological conditions among geriatric populations.

Evaluation of the optimal cutoff number of types of social participation activities in older people.

INTRODUCTION: Social participation activities have a close association with health aging. However, the clinical significance of numbers of social participation activities and its cutoff value has not been defined. METHODS: We recruited 516 people aged ≥55 years. Twelve social participation behaviors modified according to Taiwanese culture were investigated, and the adequacy of cutoff number was determined by the area under the receiver operating characteristic curve (AUC) according to the results of cluster analysis of individual activities and scores of the Brief Symptom Rating Scale-5 (BSRS-5) and the Chinese Happiness Inventory (CHI). Demographic, BSRS-5 and CHI data were then compared according to the candidate cutoff numbers. RESULTS: The distribution of the numbers of social activities suggested that the highest partition of numbers of social activities was 3 in women and 4 in men. The AUC regarding the cluster of activity types was 0.917, with the highest Youden's J value located between 3 and 4. The AUC regarding the cluster of activity types and scores of the BSRS-5 and the CHI was 0.929, with similar cutoffs. If 3 and 4 were used as cutoffs, the between-group differences of both the CHI and the BSRS-5 were significant. More types of social activities had a different engaging frequency with the 3 and 4 cutoffs. CONCLUSION: Our findings found an adequate cutoff with better differential power in the psychopathology and happiness of older people that provided a basis for application in intervention and policy formation.

Enhancing patient self-management after a first stroke: An application of the wearable devices and the health management platform.

BACKGROUND: Post-stroke disability restricts a patient's physical activity, affects the patient's quality of life, and leads to higher medical costs. Therefore, it is essential to promote patients' continuous exercise during this period of recovery. OBJECTIVE: This study aimed to verify the effectiveness of applying a health management platform combined with wearable devices to enhance stroke patients' self-management of recovery and to allow comparisons with active care intervention management. METHOD: This quasi-experimental study aimed at examining those participants who had sustained a stroke for the first time. A 90-day experiment was implemented with the intervention of monitoring and active care from the researchers who also interviewed the selected participants at the end of the study. A total of 26 participants were examined (14 in the experimental group and 12 in the control group). RESULT: The participants in the experimental group made significant progress between the pre- and post-tests. Firstly, their six-minute walking distance improved by 89.5 m (p < 0.001). Secondly, their sit-to-stand transfers in 60 s improved 2.85 times (p = 0.017), and their Berg balance test improved by 6.36 points (p = 0.003). Finally, the Partners in Health scale (PIH) scores also improved. According to the data collected in the interviews, the researchers' intervention improved the patients' self-management ability. CONCLUSION: The short-term physical performance in the experimental group after the intervention was better than that in the control group. In clinical practice, it is suggested that continuous interaction between medical staff and patients be sustained while applying wearable devices to promote the patient's self-management ability.

Nurse anesthetist training Center on IFNA standards in Mainland China.

AIM: The first training center for nurse anesthetists in Jiangsu Province, China was established. The aim of this study is to understand the status of and effectiveness of a training program based on International Federation of Nurse Anesthetists (IFNA) standards for nurse anesthetists in China. BACKGROUND: China recently issued a clear policy to improve the quality of anesthesia care and to ensure the safety and comfort of patients. As a result, the roles of nurse anesthetists have received more attention, highlighting the importance of the development and implementation of relevant training. INTRODUCTION: IFNA standards were applied to the development of a specialized training program for nurse anesthetists, which is expected to serve as a reference for various medical institutions and to lead to increased uniformity and improvement in the quality and efficiency of care. METHODS: These standards are divided into two indicators: curriculum and core competencies. Through questionnaires, course evaluations, and satisfaction surveys before and after the implementation of the training program, the effectiveness of the training program was analyzed. RESULTS: Theoretical assessment of the program was higher after its completion than before and the core competencies of nurse anesthetists significantly improved. Overall, the curriculum was highly satisfactory and important. DISCUSSION: Curriculum design was based on IFNA standards. Nurse anesthetists who are trained in a systematic way can work better with other professionals in providing anesthesia care. The objectives are to improve anesthesia care, reduce errors, improve physician satisfaction, and allow nurse anesthetists to realize their value. Overall, quality of anesthesia care improved after implementation of IFNA-standard training.

Mobile Health App With Social Media to Support Self-Management for Patients With Chronic Kidney Disease: Prospective Randomized Controlled Study.

BACKGROUND: Chronic kidney disease (CKD) is a global health burden. Self-management plays a key role in improving modifiable risk factors. OBJECTIVE: The aim of this study was to evaluate the effectiveness of wearable devices, a health management platform, and social media at improving the self-management of CKD, with the goal of establishing a new self-management intervention model. METHODS: In a 90-day prospective experimental study, a total of 60 people with CKD at stages 1-4 were enrolled in the intervention group (n=30) and control group (n=30). All participants were provided with wearable devices that collected exercise-related data. All participants maintained dietary diaries using a smartphone app. All dietary and exercise information was then uploaded to a health management platform. Suggestions about diet and exercise were provided to the intervention group only, and a social media group was created to inspire the participants in the intervention group. Participants' self-efficacy and self-management questionnaire scores, Kidney Disease Quality of Life scores, body composition, and laboratory examinations before and after the intervention were compared between the intervention and control groups. RESULTS: A total of 49 participants completed the study (25 in the intervention group and 24 in the control group); 74% of the participants were men and the mean age was 51.22 years. There were no differences in measured baseline characteristics between the groups except for educational background. After the intervention, the intervention group showed significantly higher scores for self-efficacy (mean 171.28, SD 22.92 vs mean 142.21, SD 26.36; P<.001) and self-management (mean 54.16, SD 6.71 vs mean 47.58, SD 6.42; P=.001). Kidney Disease Quality of Life scores were also higher in the intervention group (mean 293.16, SD 34.21 vs mean 276.37, SD 32.21; P=.02). The number of steps per day increased in the intervention group (9768.56 in week 1 and 11,389.12 in week 12). The estimated glomerular filtration rate (eGFR) of the intervention group was higher than that of the control group (mean 72.47, SD 24.28 vs mean 59.69, SD 22.25 mL/min/1.73m2; P=.03) and the decline in eGFR was significantly slower in the intervention group (-0.56 vs -4.58 mL/min/1.73m2). There were no differences in body composition between groups postintervention. CONCLUSIONS: The use of wearable devices, a health management platform, and social media support not only strengthened self-efficacy and self-management but also improved quality of life and a slower eGFR decline in people with CKD at stages 1-4. These results outline a new self-management model to promote healthy lifestyle behaviors for patients with CKD. TRIAL REGISTRATION: ClinicalTrials.gov NCT04617431; https://www.clinicaltrials.gov/ct2/show/NCT04617431.

The computation of case fatality rate for novel coronavirus (COVID-19) based on Bayes theorem: An observational study.

BACKGROUND: When a new disease such starts to spread, the commonly asked questions are how deadly is it? and how many people are likely to die of this outbreak? The World Health Organization (WHO) announced in a press conference on January 29, 2020 that the death rate of COVID-19 was 2% on the case fatality rate (CFR). It was underestimated assuming no lag days from symptom onset to deaths while many CFR formulas have been proposed, the estimation on Bays theorem is worthy of interpretation. Hence, it is hypothesized that the over-loaded burdens of treating patients and capacities to contain the outbreak (LSBHRS) may increase the CFR. METHODS: We downloaded COVID-19 outbreak numbers from January 21 to February 14, 2020, in countries/regions on a daily basis from Github that contains information on confirmed cases in >30 Chinese locations and other countries/regions. The pros and cons were compared among the 5 formula of CFR, including [A] deaths/confirmed; [B] deaths/(deaths + recovered); [C] deaths/(cases x days ago); [D] Bayes estimation based on [A] and the outbreak (LSBHRS) in each country/region; and [E] Bayes estimation based on [C] deaths/(cases x days ago). The coefficients of variance (CV = the ratio of the standard deviation to the mean) were applied to measure the relative variability for each CFR. A dashboard was developed for daily display of the CFR across each region. RESULTS: The Bayes based on (A)[D] has the lowest CV (=0.10) followed by the deaths/confirmed (=0.11) [A], deaths/(deaths + recoveries) (=0.42) [B], Bayes based on (C) (=0.49) [E], and deaths/(cases x days ago) (=0.59) [C]. All final CFRs will be equal using the formula (from, A to E). A dashboard was developed for the daily reporting of the CFR. The CFR (3.7%) greater than the prior CFR of 2.2% was evident in LSBHRS, increasing the CFR. A dashboard was created to present the CFRs on COVID-19. CONCLUSION: We suggest examining both trends of the Bayes based on both deaths/(cases 7 days ago) and deaths/confirmed cases as a reference to the final CFR. An app developed for displaying the provisional CFR with the 2 CFR trends can improve the underestimated CFR reported by WHO and media.

Constructing a prediction model for physiological parameters for malnutrition in hemodialysis patients.

A retrospective analysis of the improvement in the health condition of patients undergoing hemodialysis was done to understand the important factors that can affect malnutrition in these patients. In this study, data from patients who underwent hemodialysis between 2010 and 2015 in a regional hospital in Yunlin County were collected from the Taiwan Society of Nephrology-Kidney Transplantation database. A total of 1049 medical records from 300 patients with age over 20 and underwent hemodialysis were collected for this study. A decision tree C5.0 and logistic regression were used to identify 40 independent variables, as well as the association of the dependent variable albumin. Then, the C5.0 decision tree, logistic regression, and support vector machine (SVM) methods were applied to find a combination of factors that contributed to malnutrition in patients undergoing hemodialysis. Predictive models were established. Finally, a receiver operating characteristic curve and confusion matrix was used to evaluate the standard of performance of these models. All analytical methods indicated that "age" was an important factor. In particular, the best predictive model was the SVM-model 4, with a training accuracy rate of 98.95% and test accuracy rate of 66.89%, identified that "age" and 15 other important factors were the most related to hemodialysis. The findings of this study can be used as a reference for clinical applications.

Construction the model on the breast cancer survival analysis use support vector machine, logistic regression and decision tree.

The aim of the paper is to use data mining technology to establish a classification of breast cancer survival patterns, and offers a treatment decision-making reference for the survival ability of women diagnosed with breast cancer in Taiwan. We studied patients with breast cancer in a specific hospital in Central Taiwan to obtain 1,340 data sets. We employed a support vector machine, logistic regression, and a C5.0 decision tree to construct a classification model of breast cancer patients' survival rates, and used a 10-fold cross-validation approach to identify the model. The results show that the establishment of classification tools for the classification of the models yielded an average accuracy rate of more than 90% for both; the SVM provided the best method for constructing the three categories of the classification system for the survival mode. The results of the experiment show that the three methods used to create the classification system, established a high accuracy rate, predicted a more accurate survival ability of women diagnosed with breast cancer, and could be used as a reference when creating a medical decision-making frame.

Diagnosing breast masses in digital mammography using feature selection and ensemble methods.

Methods that can accurately predict breast cancer are greatly needed and good prediction techniques can help to predict breast cancer more accurately. In this study, we used two feature selection methods, forward selection (FS) and backward selection (BS), to remove irrelevant features for improving the results of breast cancer prediction. The results show that feature reduction is useful for improving the predictive accuracy and density is irrelevant feature in the dataset where the data had been identified on full field digital mammograms collected at the Institute of Radiology of the University of Erlangen-Nuremberg between 2003 and 2006. In addition, decision tree (DT), support vector machine-sequential minimal optimization (SVM-SMO) and their ensembles were applied to solve the breast cancer diagnostic problem in an attempt to predict results with better performance. The results demonstrate that ensemble classifiers are more accurate than a single classifier.

Brugada-type electrocardiogram in the Taiwanese population--is it a risk factor for sudden death?

BACKGROUND/PURPOSE: People receive electrocardiogram (ECG) examination for various reasons in a hospital setting. An important clinical practice issue may be that cardiologists need to be consulted for Brugada-type ECGs identified through routine screening. We investigated the prevalence and prognosis of patients with Brugada-type ECG in a hospital-based population in an attempt to improve the management of these patients. METHODS: In 20,562 patients seeking medical care for non-cardiovascular reasons, 74,955 ECGs were performed from December 1999 to February 2001. The diagnostic criteria for Brugada-like ECG from the European Society of Cardiology were used. International Statistical Classification of Diseases codes and city residents' records were documented to indicate the reasons for visiting clinics or hospitalization and mortality outcome. Medical records were reviewed and telephone interviews were conducted. RESULTS: Twenty-six (0.13%) of the 20,562 patients were confirmed to have Brugada-type ECGs. None of these patients had ever experienced syncope, near syncope or sudden cardiac death. After 57.1 ± 15.8 months of follow-up, there were four deaths out of the 26 patients with Brugada-type ECG (15.4%, 95% CI: 1.53-2.9%) compared with 2899 of those without (14.1%, 95% CI: 13.6-14.5%; p=0.89, log-rank test). Neither sudden cardiac death (p=0.61) nor hospitalized death (p=0.55) was different between patients with and without Brugada-type ECG. CONCLUSION: Patients with Brugada-type ECGs are not rare in a hospital-based population. The presence of Brugada-type ECGs in patients without syncope or sudden cardiac death was not associated with hospitalized mortality.

Kidney impairment in primary aldosteronism.

BACKGROUND: Kidney impairment is noted in primary aldosteronism (PA), and probably initiated by glomerular hyperfiltration. METHODS: A prospectively defined survey was conducted on 602 patients who were suspected of PA in the multiple-center Taiwan Primary Aldosteronism Investigation (TAIPAI) database. Estimated glomerular filtration rate (eGFR) was calculated and followed up at 1 yr after treatment. RESULTS: The diagnosis of PA was confirmed in 330 patients. Among them 17% of these patients had kidney impairment (eGFR<60 ml/min/1.73 m²). Patients with PA had a higher prevalence of estimated hyperfiltration than those with essential hypertension (EH) (14.5% vs. 7.0%, p=0.005). The eGFR independently predicted PA (OR, 1.017) in the propensity-adjusted multivariate logistic model. In PA, plasma renin activity and lower serum potassium (p=0.018) was correlated with kidney impairment (p=0.001), while this relationship was not significant in patients with EH. Either unilateral adrenalectomy or treatment of spironolactone for PA patients caused a decrease of eGFR (p<0.001). Pre-operative hypokalemia (p=0.013) and the long latency of hypertension (p=0.016) could enhance the significant decrease of eGFR after adrenalectomy. CONCLUSIONS: Patients with aldosteronism had relative estimated hyperfiltration than patients with EH. Calculation of eGFR may increase the specificity in identifying patients with PA. Our findings demonstrate the correlation of serum potassium and renin with estimated hyperfiltration in PA and their relationship to kidney damage. These results provide a high priority for future renal protective strategies and methods for the early diagnosis and prompt treatment of PA.

Effects of using a portable navigation system and paper map in real driving.

Navigation systems are very useful tools because they display a user's location and guide them to a destination using graphics, text and voice information. Recent work has revealed that millions of consumers received driving directions using their cell phone or PDA. This present work aimed to explore whether the efficiency to destination and driver behavior were distinguishable when using a portable navigation system compared to a paper map. Thirty-two subjects were paid to participate in this research, with field experiments being carried out in both urban and rural environments. A smart phone was adopted as the portable navigation system in the study. The results revealed that the drivers performed better when using a portable navigation system compared to those using a paper map, in terms of efficiency to destination and driving performance. In addition, drivers could save time and gasoline using a portable navigation system when in an unfamiliar region, and driving performance may be safer, despite the fact that the display screen of the phone is small.

Knowledge-based quality management and clinical pathways.

OBJECTIVES: Although 65% of the hospitals in Taiwan claim to be applying the clinical pathway concept, most hospitals do not implement this concept effectively. The purpose of this study was to determine the reasons for the improper or inappropriate application of the clinical pathway design in hospitals. METHODS: This study differs from other studies in clinical pathway design and application in that it seeks to resolve misunderstandings of the clinical pathway analysis that may have been generated by the responses to survey questionnaires. Therefore, in-depth interviews and Senge's system archetype have been used to ascertain the reasons why the use of a clinical pathway design has been ineffective. We also used the 4 dimensions of knowledge-based management proposed by Drucker to set up the knowledge-based clinical pathway. Thirteen experts used the Delphi method to construct 20 knowledge-based clinical pathway guidelines. CONCLUSIONS: The application of knowledge- and management-based clinical pathway designs is recommended.