Preventive effect of Lactobacillus johnsonii YH1136 against uric acid accumulation and renal damages.

Background: Hyperuricemia (HUA) is a prevalent metabolic disorder whose development is associated with intestinal microbiota. Therefore, probiotics have emerged as a potential and safe approach for lowering uric acid (UA) levels. However, the underlying mechanisms of many effective probiotic strains remain unknown. Methods and results: C57BL/6 mice were randomly divided into two groups: control and model groups. The model group received 12 weeks of potassium oxonate. Through 16s sequencing we found that HUA resulted in a significant decrease in the total diversity of all intestinal segments. When each intestinal segment was analyzed individually, the reduction in diversity was only significant in the cecum and colon sections. RDA analysis showed that lactobacilli in the rat colon exhibited a strong correlation with model group, suggesting that Lactobacillus may play an important role in HUA. Consequently, the preventive effects of Lactobacillus johnsonii YH1136 against HUA were investigated. C57BL/6 mice were randomly divided into three groups: control, model and YH1136 groups. The results showed that administering Lactobacillus johnsonii YH1136 effectively reduced serum UA levels in vivo by inhibiting hepatic xanthine oxidase (XOD) activity and promoting renal ABCG2 transporter expression. Moreover, supplementation with Lactobacillus johnsonii YH1136 significantly ameliorated pathological damage in the kidney and liver, thereby reducing UA accumulation. Conclusion: Hyperuricemia is accompanied by an altered composition of multiple gut bacteria, of which Lactobacillus is a key genus. Lactobacillus johnsonii YH1136 may ameliorate renal involvement in HUA via the gut-kidney axis.

Disrupted gut microbiota aggravates spatial memory dysfunction induced by high altitude exposure: A link between plateau environment and microbiome-gut-brain axis.

Approximately 400 million people work and live in high-altitude areas and suffer from memory dysfunction worldwide. Until now, the role of the intestinal flora in plateau-induced brain damage has rarely been reported. To address this, we investigated the effect of intestinal flora on spatial memory impairment induced by high altitudes based on the microbiome-gut-brain axis theory. C57BL/6 mice were divided into three groups: control, high-altitude (HA), and high-altitude antibiotic treatment (HAA) group. The HA and HAA groups were exposed to a low-pressure oxygen chamber that simulated an altitude of 4000 m above sea level (m. a. s.l.) for 14 days, with the air pressure in the chamber set at 60-65 kPa. The results showed that spatial memory dysfunction induced by the high-altitude environment was aggravated by antibiotic treatment, manifesting as lowered escape latency and hippocampal memory-related proteins (BDNF and PSD-95). 16 S rRNA sequencing showed a remarkable separation of the ileal microbiota among the three groups. Antibiotic treatment exacerbated the reduced richness and diversity of the ileal microbiota in mice in the HA group. Lactobacillaceae were the main target bacteria and were significantly reduced in the HA group, which was exacerbated by antibiotic treatment. Meanwhile, reduced intestinal permeability and ileal immune function in mice exposed high-altitude environment was also aggravated by antibiotic treatment, as indicated by the lowered tight junction proteins and IL-1ß and IFN-γ levels. Furthermore, indicator species analysis and Netshift co-analysis revealed that Lactobacillaceae (ASV11) and Corynebacteriaceae (ASV78, ASV25, and ASV47) play important roles in high-altitude exposure-induced memory dysfunction. Interestingly, ASV78 was negatively correlated with IL-1ß and IFN-γ levels, indicating that ASV78 may be induced by reduced ileal immune function, which mediates high-altitude environment exposure-induced memory dysfunction. This study provides evidence that the intestinal flora is effective in preventing brain dysfunction caused by exposure to high-altitude environments, suggesting a relationship between the microbiome-gut-brain axis and altitude exposure.

Developing and Validating an Emergency Triage Model Using Machine Learning Algorithms with Medical Big Data.

Objective: To establish an emergency triage model through the statistical analysis of big data during a particular time period from a hospital information system to improve the accuracy of triage in emergency department (ED). Methods: A total of 276,164 patients who visited the Emergency Medicine Department of Beijing Chao-Yang Hospital from 2017 to 2020 were included in this study, including 123,392 men and 152,772 women aged from 14 to 112 years. The baseline characteristics (age and gender) and medical records (patient's condition, body temperature, heart rate, breathing, blood pressure, consciousness, and oxygen saturation) of the patients was collected. The data samples were randomly allocated, with 80% as the training set and 20% as the testing set. The patients were divided into levels I, II, III, and IV in accordance with a four-level triage standard. We selected the effective Extreme Gradient Boosting (XGBoost) algorithm as our emergency classification prediction model. The XGBoost model was applied to simulate the thinking process of triage nurses, and the De Long's test was used to compare the receiver operating characteristic (ROC) curve of different models. The P value was obtained by calculating the variance and covariance of area under the curve (AUC) values of different ROC curves. Results: Level I had 4960 (1.8%) patients, level II had 25,646 (9.29%), level III had 130,664 (47.31%), and level IV had 114,894 (41.6%). The XGBoost model was built following a logic exercise based on the traditional manual pre-inspection and triage results. After verification, the prediction accuracy was 82.57%. The AUC of each disease severity level (levels I, II, III, and IV) was 0.9629, 0.9554, 0.9120, and 0.9296, respectively. Conclusion: The emergency triage prediction model, which achieved a relatively strong accuracy rate, can reduce the work intensity of medical workers and improve their working efficiency.

Emerging roles of growth differentiation factor-15 in brain disorders (Review).

Brain disorders, such as Alzheimer's and Parkinson's disease and cerebral stroke, are an important contributor to mortality and disability worldwide, where their pathogenesis is currently a topic of intense research. The mechanisms underlying the development of brain disorders are complex and vary widely, including aberrant protein aggregation, ischemic cell necrosis and neuronal dysfunction. Previous studies have found that the expression and function of growth differentiation factor-15 (GDF15) is closely associated with the incidence of brain disorders. GDF15 is a member of the TGFß superfamily, which is a dimer-structured stress-response protein. The expression of GDF15 is regulated by a number of proteins upstream, including p53, early growth response-1, non-coding RNAs and hormones. In particular, GDF15 has been reported to serve an important role in regulating angiogenesis, apoptosis, lipid metabolism and inflammation. For example, GDF15 can promote angiogenesis by promoting the proliferation of human umbilical vein endothelial cells, apoptosis of prostate cancer cells and fat metabolism in fasted mice, and GDF15 can decrease the inflammatory response of lipopolysaccharide-treated mice. The present article reviews the structure and biosynthesis of GDF15, in addition to the possible roles of GDF15 in Alzheimer's disease, cerebral stroke and Parkinson's disease. The purpose of the present review is to summarize the mechanism underlying the role of GDF15 in various brain disorders, which hopes to provide evidence and guide the prevention and treatment of these debilitating conditions.

[The predictive value of medical big data for the prognosis of elderly patients with pneumonia: based on the result of clinical database of a Beijing Chaoyang Hospital Consortium Chaoyang Emergency Ward].

OBJECTIVE: To explore a medical big data algorithm to screen the core indicators in clinical database that can be used to evaluate the prognosis of elderly patients with pneumonia. METHODS: Based on the clinical database of a Beijing Chaoyang Hospital Consortium Chaoyang Emergency Ward in Beijing Chaoyang Hospital, Capital Medical University, patients with pulmonary infection were selected through the big data retrieval technology. According to the prognosis at the time of discharge, they were divided into death group and survival group. The general data of patients were collected, including gender, age, blood gas and laboratory indices. A computer language called Python was used to make batch calculations of key indicators that affect mortality in elderly patients with pneumonia. Logistic regression analysis was used to analyze the relationship between laboratory indicators and patients' prognosis. Receiver operating characteristic curve (ROC curve) was drawn to analyze the predictive value of screening method for patients' prognosis. RESULTS: A total of 265 patients were included in the study, 64 died and 201 survived. The data of the first detection indexes of each patient after admission were collected, and 23 key indicators with significant differences were selected from 472 indicators: blood routine indicators (n = 7), blood gas indicators (n = 3), tumor markers indicators (n = 3), coagulation related indicators (n = 4), and nutrition and organ function indicators (n = 6). (1) The key indicators of blood gas in patients died of pneumonia: Cl- was 97-111 mmol/L in 51.6% (33 cases) of patients, lactic acid (Lac) was 0.5-2.5 mmol/L in 81.2% (52 cases) of patients, and H+ was 0-46 mmol/L in 87.5% (56 cases) of patients. (2) The key indicators of blood routine of patients died of pneumonia: hemoglobin count (Hb) of 46.9% (30 cases) patients was 80-109 g/L, the eosinophils proportions (EOS%) in 67.2% (43 cases) patients was 0.000-0.009, the lymphocytes proportions (LYM%) in 51.6% (33 cases) patients was 0.00-0.09, the red blood cell count (RBC) in 50.0% (32 cases) patients was (3.0-3.9)×1012/L, the white blood cell count (WBC) in 54.7% (35 cases) patients was (0.0-9.9)×109/L, and the red blood cell volume distribution width coefficientof variability (RDW-CV) in 48.4% (31 cases) patients was 10.0%-14.9%, serum C-reactive protein (CRP) was 0.0-49.9 mg/L in 48.4% (31 cases) patients. (3) The key indicators of tumor markers in patients died of pneumonia: 76.6% (49 cases) of patients had negative free prostate specific antigen/total prostate specific antigen (FPSA/TPSA, the ratio was 0), 92.2% (59 cases) had cytokeratin 19 fragment (CYFRA21-1) between 0.0-11.0 µg/L, and 75.0% (48 cases) had carbohydrate antigen 125 (CA125) between 0-104 kU/L. (4) The key coagulation indexes of patients died of pneumonia: 68.8% (44 cases) of patients had activated partial thromboplastin time (APTT) of 57-96 s, 73.4% (47 cases) of patients had D-dimer of 0-6 mg/L, 93.8% (60 cases) of patients had thrombin time (TT) of 14-22 s, and 89.1% (57 cases) of patients had adenosine diphosphate (ADP) inhibition rate of 0%-53%. (5) Nutrition and organ function key indicatorsin patients died of pneumonia: 92.2% (59 cases) of brain natriuretic peptide (BNP) in patients with 0, 46.9% (30 cases) of patients had prealbumin (PA) of 71-140 mg/L, 90.6% (58 cases) of the patients with uric acid (UA) for 21-41 µmol/L, 75.0% (48 cases) of the patients with albumin (Alb) to 10-20 g/L, 93.5% (60 cases) of patients had albumin/globulin ratio (A/G ratio) of 0-0.9, 84.4% (54 cases) of the patients with lactate dehydrogenase (LDH) from 0-6.68 µmol/L×s-1×L-1. (6) Logistic regression analysis and ROC curve analysis: Logistic regression analysis showed that PA and Lac were the prognostic factors. PA could reduce the risk of death by 0.9%, Lac could increase the risk of death by 69.4%; the area under ROC curve (AUC) between laboratory indicators and the prediction effect of death prediction model for patients' prognosis was 0.80, which showed that the classification effect was better, and this study model could better predict the prognosis of elderly patients with pneumonia. CONCLUSIONS: By using big data technology, 23 core indicators for evaluating the prognosis of elderly patients with pneumonia can be screened from the clinical database of emergency ward, which provides a new perspective and method for clinical evaluation of the prognosis of elderly patients with pneumonia.

Development of a Consumer Health Vocabulary by Mining Health Forum Texts Based on Word Embedding: Semiautomatic Approach.

BACKGROUND: The vocabulary gap between consumers and professionals in the medical domain hinders information seeking and communication. Consumer health vocabularies have been developed to aid such informatics applications. This purpose is best served if the vocabulary evolves with consumers' language. OBJECTIVE: Our objective is to develop a method for identifying and adding new terms to consumer health vocabularies, so that it can keep up with the constantly evolving medical knowledge and language use. METHODS: In this paper, we propose a consumer health term-finding framework based on a distributed word vector space model. We first learned word vectors from a large-scale text corpus and then adopted a supervised method with existing consumer health vocabularies for learning vector representation of words, which can provide additional supervised fine tuning after unsupervised word embedding learning. With a fine-tuned word vector space, we identified pairs of professional terms and their consumer variants by their semantic distance in the vector space. A subsequent manual review of the extracted and labeled pairs of entities was conducted to validate the results generated by the proposed approach. The results were evaluated using mean reciprocal rank (MRR). RESULTS: Manual evaluation showed that it is feasible to identify alternative medical concepts by using professional or consumer concepts as queries in the word vector space without fine tuning, but the results are more promising in the final fine-tuned word vector space. The MRR values indicated that on an average, a professional or consumer concept is about 14th closest to its counterpart in the word vector space without fine tuning, and the MRR in the final fine-tuned word vector space is 8. Furthermore, the results demonstrate that our method can collect abbreviations and common typos frequently used by consumers. CONCLUSIONS: By integrating a large amount of text information and existing consumer health vocabularies, our method outperformed several baseline ranking methods and is effective for generating a list of candidate terms for human review during consumer health vocabulary development.

Usability Study of Mainstream Wearable Fitness Devices: Feature Analysis and System Usability Scale Evaluation.

BACKGROUND: Wearable devices have the potential to promote a healthy lifestyle because of their real-time data monitoring capabilities. However, device usability is a critical factor that determines whether they will be adopted on a large scale. Usability studies on wearable devices are still scarce. OBJECTIVE: This study aims to compare the functions and attributes of seven mainstream wearable devices and to evaluate their usability. METHODS: The wearable devices selected were the Apple Watch, Samsung Gear S, Fitbit Surge, Jawbone Up3, Mi Band, Huawei Honor B2, and Misfit Shine. A mixed method of feature comparison and a System Usability Scale (SUS) evaluation based on 388 participants was applied; the higher the SUS score, the better the usability of the product. RESULTS: For features, all devices had step counting, an activity timer, and distance recording functions. The Samsung Gear S had a unique sports track recording feature and the Huawei Honor B2 had a unique wireless earphone. The Apple Watch, Samsung Gear S, Jawbone Up3, and Fitbit Surge could measure heart rate. All the devices were able to monitor sleep, except the Apple Watch. For product characteristics, including attributes such as weight, battery life, price, and 22 functions such as step counting, activity time, activity type identification, sleep monitoring, and expandable new features, we found a very weak negative correlation between the SUS scores and price (r=-.10, P=.03) and devices that support expandable new features (r=-.11, P=.02), and a very weak positive correlation between the SUS scores and devices that support the activity type identification function (r=.11, P=.02). The Huawei Honor B2 received the highest score of mean 67.6 (SD 16.1); the lowest Apple Watch score was only 61.4 (SD 14.7). No significant difference was observed among brands. The SUS score had a moderate positive correlation with the user's experience (length of time the device was used) (r=.32, P<.001); participants in the medical and health care industries gave a significantly higher score (mean 61.1, SD 17.9 vs mean 68.7, SD 14.5, P=.03). CONCLUSIONS: The functions of wearable devices tend to be homogeneous and usability is similar across various brands. Overall, Mi Band had the lowest price and the lightest weight. Misfit Shine had the longest battery life and most functions, and participants in the medical and health care industries had the best evaluation of wearable devices. The perceived usability of mainstream wearable devices is unsatisfactory and customer loyalty is not high. A consumer's SUS rating for a wearable device is related to their personal situation instead of the device brand. Device manufacturers should put more effort into developing innovative functions and improving the usability of their products by integrating more cognitive behavior change techniques.

Physicians' perceptions of physician-nurse interactions and information needs in China.

BACKGROUND: Good communication between physicians and nurses is important for the understanding of disease status and treatment feedback; however, certain issues in Chinese hospitals could lead to suboptimal physician-nurse communication in clinical work. METHODS: Convenience sampling was used to recruit participants. Questionnaires were sent to clinical physicians in three top tertiary Grade-A teaching hospitals in China and six hundred and seventeen physicians participated in the survey. RESULTS: (1) Common physician-nurse interactions were shift-change reports and provisional reports when needed, and interactions expected by physicians included face-to-face reports and communication via a phone or mobile device. (2) Most respondents believed that the need for information in physician-nurse interactions was high, information was moderately accurate and timely, and feedback regarding interaction time and satisfaction indicated that they were only average and required improvement. (3) Information needs in physician-nurse interactions differed significantly according to hospital category, role, workplace, and educational background (p < .05). CONCLUSIONS: There was a considerable need for information within physician-nurse interactions, and the level of satisfaction with the information obtained was average; requirements for the improvement of communication differed between physicians and nurses because of differences in their characteristics. Currently, the use of information technology in physician-nurse communication was less common but was highly expected by physicians.

Enabling Health Reform through Regional Health Information Exchange: A Model Study from China

Objective: To investigate and share the major challenges and experiences of building a regional health information exchange system in China in the context of health reform. Methods: This study used interviews, focus groups, a field study, and a literature review to collect insights and analyze data. The study examined Xinjin's approach to developing and implementing a health information exchange project, using exchange usage data for analysis. Results: Within three years and after spending approximately $2.4 million (15 million RMB), Xinjin County was able to build a complete, unified, and shared information system and many electronic health record components to integrate and manage health resources for 198 health institutions in its jurisdiction, thus becoming a model of regional health information exchange for facilitating health reform. Discussion: Costs, benefits, experiences, and lessons were discussed, and the unique characteristics of the Xinjin case and a comparison with US cases were analyzed. Conclusion: The Xinjin regional health information exchange system is different from most of the others due to its government-led, government-financed approach. Centralized and coordinated efforts played an important role in its operation. Regional health information exchange systems have been proven critical for meeting the global challenges of health reform.

Enabling Health Reform through Regional Health Information Exchange: A Model Study from China.

Objective. To investigate and share the major challenges and experiences of building a regional health information exchange system in China in the context of health reform. Methods. This study used interviews, focus groups, a field study, and a literature review to collect insights and analyze data. The study examined Xinjin's approach to developing and implementing a health information exchange project, using exchange usage data for analysis. Results. Within three years and after spending approximately $2.4 million (15 million RMB), Xinjin County was able to build a complete, unified, and shared information system and many electronic health record components to integrate and manage health resources for 198 health institutions in its jurisdiction, thus becoming a model of regional health information exchange for facilitating health reform. Discussion. Costs, benefits, experiences, and lessons were discussed, and the unique characteristics of the Xinjin case and a comparison with US cases were analyzed. Conclusion. The Xinjin regional health information exchange system is different from most of the others due to its government-led, government-financed approach. Centralized and coordinated efforts played an important role in its operation. Regional health information exchange systems have been proven critical for meeting the global challenges of health reform.

How the public uses social media wechat to obtain health information in china: a survey study.

BACKGROUND: On average, 570 million users, 93% in China's first-tier cities, log on to WeChat every day. WeChat has become the most widely and frequently used social media in China, and has been profoundly integrated into the daily life of many Chinese people. A variety of health-related information may be found on WeChat. The objective of this study is to understand how the general public views the impact of the rapidly emerging social media on health information acquisition. METHODS: A self-administered questionnaire was designed, distributed, collected, and analyzed utilizing the online survey tool Sojump. WeChat was adopted to randomly release the questionnaires using convenience sampling and collect the results after a certain amount of time. RESULTS: (1) A total of 1636 questionnaires (WeChat customers) were collected from 32 provinces. (2) The primary means by which respondents received health education was via the Internet (71.79%). Baidu and WeChat were the top 2 search tools utilized (90.71% and 28.30%, respectively). Only 12.41% of respondents were satisfied with their online health information search. (3) Almost all had seen (98.35%) or read (97.68%) health information; however, only 14.43% believed that WeChat health information could improve health. Nearly one-third frequently received and read health information through WeChat. WeChat was selected (63.26%) as the most expected means for obtaining health information. (4) The major concerns regarding health information through WeChat included the following: excessively homogeneous information, the lack of a guarantee of professionalism, and the presence of advertisements. (5) Finally, the general public was most interested in individualized and interactive health information by managing clinicians, they will highly benefit from using social media rather than Internet search tools. CONCLUSIONS: The current state of health acquisition proves worrisome. The public has a high chance to access health information via WeChat. The growing popularity of interactive social platforms (e.g. WeChat) presents a variety of challenges and opportunities with respect to public health acquisition.

The challenges of emerging HISs in bridging the communication gaps among physicians and nurses in China: an interview study.

BACKGROUND: To explore the current situation, existing problems and possible causes of said problems with regards to physician-nurse communication under an environment of increasingly widespread usage of Hospital Information Systems and to seek out new potential strategies in information technology to improve physician-nurse communication. METHODS: Semi-structured interviews were conducted with 20 physicians and nurses in five leading tertiary grade A hospitals in Beijing, China (two physicians and two nurses in each hospital). The interviews primarily included three aspects comprising the current situation and problems of clinical physician-nurse communication, the application and problems of Hospital Information Systems, and assessments on the improvement of physician-nurse communication through the usage of information technology. The inductive conventional content analysis approach was employed. RESULTS: (1) Physicians and nurses are generally quite satisfied with the current situation of communication. However, the information needs of nurses are prone to being overlooked, and the communication methods are primarily synchronous communication such as face-to-face and phone communication. (2) Hospital Information Systems are gradually being used for physician-nurse communication; in the meantime, physicians and nurses face challenges with regards to the improvement of physician-nurse communication through the usage of information technology. Challenges differ based on the different stages of using the system and the different levels of understanding of physicians and nurses towards information technology. Their dissatisfaction mainly deals with system errors and the level of convenience in using the system. (3) In-depth interviews found that in general, physicians and nurses have a strong interest and trust in improving physician-nurse communication through appropriate information technology, e.g., communication methods such as information reminders for physicians and nurses through mobile devices and instant voice-to-text conversion methods. CONCLUSIONS: There are objective risks in physician-nurse communication in Chinese hospitals, and clinical information systems lack solutions to the relevant problems. Developing a dedicated, mobile, quick and convenient module for physician-nurse communication within existing hospital information system with automatic reminders for important information that segregates between synchronous and asynchronous communication according to the different types of information could help improve physician-nurse communication.

Evaluating the Consistency of Current Mainstream Wearable Devices in Health Monitoring: A Comparison Under Free-Living Conditions.

BACKGROUND: Wearable devices are gaining increasing market attention; however, the monitoring accuracy and consistency of the devices remains unknown. OBJECTIVE: The purpose of this study was to assess the consistency of the monitoring measurements of the latest wearable devices in the state of normal activities to provide advice to the industry and support to consumers in making purchasing choices. METHODS: Ten pieces of representative wearable devices (2 smart watches, 4 smart bracelets of Chinese brands or foreign brands, and 4 mobile phone apps) were selected, and 5 subjects were employed to simultaneously use all the devices and the apps. From these devices, intact health monitoring data were acquired for 5 consecutive days and analyzed on the degree of differences and the relationships of the monitoring measurements ​​by the different devices. RESULTS: The daily measurements by the different devices fluctuated greatly, and the coefficient of variation (CV) fluctuated in the range of 2-38% for the number of steps, 5-30% for distance, 19-112% for activity duration, .1-17% for total energy expenditure (EE), 22-100% for activity EE, 2-44% for sleep duration, and 35-117% for deep sleep duration. After integrating the measurement data of 25 days among the devices, the measurements of the number of steps (intraclass correlation coefficient, ICC=.89) and distance (ICC=.84) displayed excellent consistencies, followed by those of activity duration (ICC=.59) and the total EE (ICC=.59) and activity EE (ICC=.57). However, the measurements for sleep duration (ICC=.30) and deep sleep duration (ICC=.27) were poor. For most devices, there was a strong correlation between the number of steps and distance measurements (R2>.95), and for some devices, there was a strong correlation between activity duration measurements and EE measurements (R2>.7). A strong correlation was observed in the measurements of steps, distance and EE from smart watches and mobile phones of the same brand, Apple or Samsung (r>.88). CONCLUSIONS: Although wearable devices are developing rapidly, the current mainstream devices are only reliable in measuring the number of steps and distance, which can be used as health assessment indicators. However, the measurement consistencies of activity duration, EE, sleep quality, and so on, are still inadequate, which require further investigation and improved algorithms.

Consumers' perceived attitudes to wearable devices in health monitoring in China: A survey study.

BACKGROUND AND OBJECTIVE: Capital market and consumer market interest in wearable devices has surged in recent years, however, their actual acceptance in the field of health monitoring is somewhat not as expected. This study aims to understand the perceptions of wearable devices of general consumers, analyze the review of the devices by users, and find existing problems associated with current wearable devices. METHODS: Sojump.com, an on-line questionnaire tool, was used to generate the questionnaire, which focused on four aspects. The snowball sampling method was employed to collect questionnaires by making use of the author's social network. RESULTS: (1) A total of 2058 valid questionnaires were received from the respondents from every province in China; of the respondents, 52.4% have used a wearable device. (2) The respondents had a low level of knowledge about wearable devices (2.79/5) but were optimistic with regard to the devices' future (3.86/5), and 84% recognized an acceptable price of less than 2000 RMB. Nearly half of the respondents were unwilling to continuously wear the device (47.1%) and share their health data (44.7%). (3) The functions of wearable devices that the respondents expected were mainly health management (63.5%), mobile phone accessories (61.9%), and location tracking (61.2%), and the promising hot future functions were mainly data analysis (74.2%), exercise coaching (60.5%), and child tracking (58.8%). Regarding the health monitoring functions, the respondents were most interested in heart health monitoring. (4) The respondents had different levels of emphasis regarding the existing problems of wearable devices at different use stages. Being easily damaged or lost (49.7%), being incapable of providing health recommendations based on data analysis (46.7%), and being uncomfortable to wear (45.8%) likely lead consumers to abandon the use of wearable devices. CONCLUSIONS: Consumers are optimistic about the prospects of wearable devices; however, there is a large gap between the reliability of the measurement data, the ease of use, and the interpretation of measurement data of current wearable products and consumer expectations. Consumer demand for health management functions is higher than that for daily auxiliary-type functions, which is an issue that should be properly addressed and resolved by manufacturers.

Detecting negation and scope in Chinese clinical notes using character and word embedding.

BACKGROUND AND OBJECTIVES: Researchers have developed effective methods to index free-text clinical notes into structured database, in which negation detection is a critical but challenging step. In Chinese clinical records, negation detection is particularly challenging because it may depend on upstream Chinese information processing components such as word segmentation [1]. Traditionally, negation detection was carried out mostly using rule-based methods, whose comprehensiveness and portability were usually limited. Our objectives in this paper are to: 1) Construct a large Chinese clinical notes corpus with negation annotated; 2) develop a negation detection tool for Chinese clinical notes; 3) evaluate the performance of character and word embedding features in Chinese clinical natural language processing. METHODS: In this paper, we construct a Chinese clinical corpus consisting of admission and discharge summaries, and propose sequence labeling based systems for negation and scope detection. Our systems rely on features from bag of characters, bag of words, character embedding and word embedding. For scopes, we introduce an additional feature to handle nested scopes with multiple negations. RESULTS: The two annotators reached an agreement of 0.79 measured by Kappa in manual annotation. In cue detection, our systems are able to achieve a performance as high as 99.0% measured by F score, which significantly outperform its rule-based counterpart (79% F). The best system uses word embedding as features, which yields precision of 99.0% and recall of 99.1%. In scope detection, our system is able to achieve a performance of 94.6% measured by F score. CONCLUSIONS: Our study provides a state-of-the-art negation-detecting tool for Chinese clinical free-text notes; Experimental results demonstrate that word embedding is effective in identifying negations, and that nested scopes can be identified effectively by our method.

Assessing and comparing the usability of Chinese EHRs used in two Peking University hospitals to EHRs used in the US: A method of RUA.

OBJECTIVES: The objective of this study was to investigate the usability level of Chinese hospital Electronic Health Records (EHRs) by assessing the completion times of EHRs for seven "meaningful use (MU)" relevant tasks conducted at two Chinese tertiary hospitals and comparing the results to those of relevant research conducted in US EHRs. METHODS: Using Rapid Usability Assessment (RUA) developed by the National Center for Cognitive Informatics and Decision Making (NCCD), the usability of EHRs from two Peking University hospitals was assessed using a three-step Keystroke Level Model (KLM) in a laboratory environment. RESULTS: (1) The total EHR task completion time for 7 MU relevant test tasks showed no significant differences between the two Chinese EHRs and their US counterparts, in which the time for thinking was relatively large and comprised 35.6% of the total time. The time for the electronic physician order was the largest. (2) For specific tasks, the mean completion times of the 2 hospital EHR systems spent on recording, modifying and searching (RMS) the medication orders were similar to those for the RMS radioactive tests; the mean time spent on the RMS laboratory test orders were much less. (3) There were 85 usability problems identified in the 2 hospital EHR systems. DISCUSSION: In Chinese EHRs, a substantial amount of time is required to complete tasks relevant to MU targets and many preventable usability problems can be discovered. The task completion time of the 2 Chinese EHR systems was a little shorter than in the 5 reported US EHR systems, while the differences in smoking status and CPOE tasks were obvious; one main reason for these differences was the use of structured data entry. CONCLUSIONS: The efficiency of Chinese and US EHRs was not significantly different. The key to improving the efficiency of both systems lies in expediting the Computerized physician order entry (CPOE) task. Many usability problems can be identified using heuristic assessments and improved by corresponding actions.

Speculation detection for Chinese clinical notes: Impacts of word segmentation and embedding models.

Speculations represent uncertainty toward certain facts. In clinical texts, identifying speculations is a critical step of natural language processing (NLP). While it is a nontrivial task in many languages, detecting speculations in Chinese clinical notes can be particularly challenging because word segmentation may be necessary as an upstream operation. The objective of this paper is to construct a state-of-the-art speculation detection system for Chinese clinical notes and to investigate whether embedding features and word segmentations are worth exploiting toward this overall task. We propose a sequence labeling based system for speculation detection, which relies on features from bag of characters, bag of words, character embedding, and word embedding. We experiment on a novel dataset of 36,828 clinical notes with 5103 gold-standard speculation annotations on 2000 notes, and compare the systems in which word embeddings are calculated based on word segmentations given by general and by domain specific segmenters respectively. Our systems are able to reach performance as high as 92.2% measured by F score. We demonstrate that word segmentation is critical to produce high quality word embedding to facilitate downstream information extraction applications, and suggest that a domain dependent word segmenter can be vital to such a clinical NLP task in Chinese language.