Characterizing the Discussion of Antibiotics in the Twittersphere: What is the Bigger Picture?

Background

User content posted through Twitter has been used for biosurveillance, to characterize public perception of health-related topics, and as a means of distributing information to the general public. Most of the existing work surrounding Twitter and health care has shown Twitter to be an effective medium for these problems but more could be done to provide finer and more efficient access to all pertinent data. Given the diversity of user-generated content, small samples or summary presentations of the data arguably omit a large part of the virtual discussion taking place in the Twittersphere. Still, managing, processing, and querying large amounts of Twitter data is not a trivial task. This work describes tools and techniques capable of handling larger sets of Twitter data and demonstrates their use with the issue of antibiotics.

Objective

This work has two principle objectives: (1) to provide an open-source means to efficiently explore all collected tweets and query health-related topics on Twitter, specifically, questions such as what users are saying and how messages are spread, and (2) to characterize the larger discourse taking place on Twitter with respect to antibiotics.

Methods

Open-source software suites Hadoop, Flume, and Hive were used to collect and query a large number of Twitter posts. To classify tweets by topic, a deep network classifier was trained using a limited number of manually classified tweets. The particular machine learning approach used also allowed the use of a large number of unclassified tweets to increase performance.

Results

Query-based analysis of the collected tweets revealed that a large number of users contributed to the online discussion and that a frequent topic mentioned was resistance. A number of prominent events related to antibiotics led to a number of spikes in activity but these were short in duration. The category-based classifier developed was able to correctly classify 70% of manually labeled tweets (using a 10-fold cross validation procedure and 9 classes). The classifier also performed well when evaluated on a per category basis.

Conclusions

Using existing tools such as Hive, Flume, Hadoop, and machine learning techniques, it is possible to construct tools and workflows to collect and query large amounts of Twitter data to characterize the larger discussion taking place on Twitter with respect to a particular health-related topic. Furthermore, using newer machine learning techniques and a limited number of manually labeled tweets, an entire body of collected tweets can be classified to indicate what topics are driving the virtual, online discussion. The resulting classifier can also be used to efficiently explore collected tweets by category and search for messages of interest or exemplary content.     

Research progress in rehabilitation treatment of stroke patients A bibliometric analysis

BACKGROUND: Stroke presents as a transient or chronic brain dysfunction and is associated with high morbidity and high mortality. The doctors and scientists would like to argue how to enhance the validity of the rehabilitation treatment and how to further improve the level of treatment on stroke. OBJECTIVE: The aim of this study was to quantitatively analyze the current worldwide progress in research on stroke rehabilitation treatment based on Web of Science database and ClinicalTrial.gov in the past 10 years. METHODS: We conducted a quantitative analysis of clinical trial articles regarding stroke rehabilitation published in English from 2003 to 2013 and indexed in the National Institutes of Health Clinical Trials registry and Web of Science databases. Data were downloaded on March 15, 2013. RESULTS: (1) From 2003 to 2013, 2 654 clinical trials investigating stroke were indexed in ClinicalTrials.gov. There were only 58 clinical trials registered in 2003, and there was a marked increase from 2005. A total of 605 clinical trials on the rehabilitation of stroke were conducted in the past 10 years. (2) The analysis showed that most of the trials in the field were registered by North American institutions. With respect to the Asian countries, China and Taiwan area of China also published a reasonable proportion of the trials, but comparatively speaking, the number of trials is really rare. Most of the interventions were drugs, followed by the devices, and behavioral interventions were ranked third. (3) In the past 10 years, there were 4 052 studies on stroke indexed by Web of Science database. CONCLUSION: From perspective of research progress, we found that the number of clinical trials and papers on stroke rehabilitation has increased significantly in the past 10 years, between them a remarkable positive correlation exists.     

The top cited articles on glioma stem cells in Web of Science

BACKGROUND: Glioma is the most common intracranial tumor and has a poor patient prognosis. The presence of brain tumor stem cells was gradually being understood and recognized, which might be beneficial for the treatment of glioma. OBJECTIVE: To use bibliometric indexes to track study focuses on glioma stem cell, and to investigate the relationships among geographic origin, impact factors, and highly cited articles indexed in Web of Science. METHODS: A list of citation classics for glioma stem cells was generated by searching the database of Web of Science-Expanded using the terms "glioma stem cell" or "glioma, stem cell’" or "brain tumor stem cell". The top 63 cited research articles which were cited more than 100 times were retrieved by reading the abstract or full text if needed. Each eligible article was reviewed for basic information on subject categories, country of origin, journals, authors, and source of journals. Inclusive criteria: (1) articles in the field of glioma stem cells which was cited more than 100 times; (2) fundamental research on humans or animals, clinical trials and case reports; (3) research article; (4) year of publication: 1899-2012; and (5) citation database: Science Citation Index-Expanded. Exclusive criteria: (1) articles needing to be manually searched or accessed only by telephone; (2) unpublished articles; and (3) reviews, conference proceedings, as well as corrected papers. RESULTS: Of 2 040 articles published, the 63 top-cited articles were published between 1992 and 2010. The number of citations ranged from 100 to 1 754, with a mean of 280 citations per article. These citation classics came from nineteen countries, of which 46 articles came from the United States. Duke University and University of California, San Francisco led the list of classics with seven papers each. The 63 top-cited articles were published in 28 journals, predominantly Cancer Research and Cancer Cell, followed by Cell Stem Cell and Nature. CONCLUSION: Our bibliometric analysis provides a historical perspective on the progress of glioma stem cell research. Articles originating from outstanding institutions of the United States and published in high-impact journals are most likely to be cited.     

OPEN TREATMENT OF SYNDACTYLY OF THE FOOT

The aim of reconstruction of the webs for syndactyly of the foot is cosmetic improvement, so skin grafting should be avoided. We present our long-term results of 19 feet with simple cutaneous syndactyly in 15 patients who were treated by an open technique. The bottom of the web was covered with a dorsal rectangular flap and the remaining skin defect was left open to epithelialise spontaneously. This took about 4 weeks. After a mean follow-up of 5.7 years (range 3-9), no hypertrophic scar or pigmentation of the skin had developed. Creeping of the web was seen only during the first postoperative year. The final depth of the web satisfied the families of all patients. As the aim of web reconstruction for syndactyly of the foot is purely cosmetic, we conclude that this simple method is reasonable treatment.     

血吸虫病网络地理信息系统软件开发及应用

目的利用网络地理信息系统（WebGIS） 技术开发江苏省血吸虫病网络地理信息系统.方法在江苏省血吸虫病地理信息系统（GIS）数据库的基础上,利用ESRI公司的ArcIMS软件开发主动式江苏省血吸虫病WebGIS.结果江苏省血吸虫病WebGIS已初步开发完成,并在江苏省血吸虫病防治研究所内部局域网试运行,实现了江苏省血吸虫病管理控制中相关的各类地理数据、属性数据、专业库、资料库数据的统一管理,提供各种查询、显示、分析、统计以及图形输出等功能.结论利用WebGIS技术开发血吸虫病GIS是可行的,为建立江苏省血吸虫病管理决策系统提供了基础.     

Predicting severity of pathological scarring due to burn injuries: a clinical decision making tool using Bayesian networks

It is important for clinicians to understand which are the clinical signs, the patient characteristics and the procedures that are related with the occurrence of hypertrophic burn scars in order to carry out a possible prognostic assessment. Providing clinicians with an easy‐to‐ use tool for predicting the risk of pathological scars. A total of 703 patients with 2440 anatomical burn sites who were admitted to the Department of Plastic and Reconstructive Surgery, Burn Center of the Traumatological Hospital in Torino between January 1994 and May 2006 were included in the analysis. A Bayesian network (BN) model was implemented. The probability of developing a hypertrophic scar was evaluated on a number of scenarios. The error rate of the BN model was assessed internally and it was equal to 24·83%. While classical statistical method as logistic models can infer only which variables are related to the final outcome, the BN approach displays a set of relationships between the final outcome (scar type) and the explanatory covariates (patient's age and gender, burn surface area, full‐thickness burn surface area, burn anatomical area and wound‐healing time; burn treatment options such as advanced dressings, type of surgical approach, number of surgical procedures, type of skin graft, excision and coverage timing). A web‐based interface to handle the BN model was developed on the website www.pubchild.org (burns header). Clinicians who registered at the website could submit their data in order to get from the BN model the predicted probability of observing a pathological scar type.     

Provision of medical abortion using telemedicine in Brazil

Objective

To evaluate the need for and outcome of self-administered medical abortion with mifepristone and misoprostol in Brazil, provided through Women on Web, a global telemedicine abortion service.

Study Design

A retrospective case review of women from Brazil who contacted Women on Web in 2011. Information from the online consultation, follow-up questionnaire and emails were used to analyze data including demographics, gestational age, outcome of the medical abortion and symptoms that lead to surgical interventions.

Results

The Women on Web website had 109779 unique visitors from Brazil, 2104 women contacted the helpdesk by email. Of the 1401 women who completed the online consultation, 602 women continued their request for a medical abortion. Of the 370 women who used the medicines, 307 women gave follow-up information about the outcome of the medical abortion. Of these, 207 (67.4%) women were 9 weeks or less pregnant, 71 (23.1%) were 10, 11 or 12 weeks pregnant, and 29 (9.5%) women were 13 weeks or more pregnant. There was a significant difference in surgical intervention rates after the medical abortion (19.3% at < 9 weeks, 15.5% at 11–12 weeks and 44.8% at > 13 weeks, p=.06). However, 42.2% of the women who had a surgical intervention had no symptoms of a complication.

Conclusion

There is large need for medical abortion in Brazil. Home use of mifepristone and misoprostol provided through telemedicine is safe and effective. However, after 13 weeks gestation, there is an increased risk of surgical intervention that may be due to the regimen used and local clinical practices in Brazil.

Implications

The current study shows that there is an unmet need for medical abortion in Brazil, a country with legal restrictions on access to safe abortion services. Telemedicine can help fulfill the need and self administration of medical abortion is safe and effective even at late first trimester abortion. Prospective trials are needed to establish safety, effectiveness and acceptability of home use of medical abortion beyond 12 weeks of pregnancy.     

Strategies to address participant misrepresentation for eligibility in Web‐based research

Emerging methodological research suggests that the World Wide Web (“Web”) is an appropriate venue for survey data collection, and a promising area for delivering behavioral intervention. However, the use of the Web for research raises concerns regarding sample validity, particularly when the Web is used for recruitment and enrollment. The purpose of this paper is to describe the challenges experienced in two different Web‐based studies in which participant misrepresentation threatened sample validity: a survey study and an online intervention study. The lessons learned from these experiences generated three types of strategies researchers can use to reduce the likelihood of participant misrepresentation for eligibility in Web‐based research. Examples of procedural/design strategies, technical/software strategies and data analytic strategies are provided along with the methodological strengths and limitations of specific strategies. The discussion includes a series of considerations to guide researchers in the selection of strategies that may be most appropriate given the aims, resources and target population of their studies. Copyright © 2014 John Wiley & Sons, Ltd.     

2009~2018年癌症康复研究的CiteSpace科学知识图谱可视化分析

目的 了解2009~2018年癌症康复相关研究的研究现状、研究热点及研究前沿。方法 检索2009~2018年Web of Science核心数据库中癌症康复相关文献,利用CiteSpace软件生成可视化科学知识图谱并进行分析。结果 2009~2018年,Web of Science核心数据库中共检索到癌症康复相关论文13956篇,年度发表论文数量总体呈增长趋势;《SUPPORTIVE CARE IN CANCER》是发表论文最多的期刊,美国是发表文章数量最多、最具权威性的国家,UNIVERSITY OF ALBERTA（阿尔伯塔大学）是最活跃的机构,Courneya KS是发表文献数量最多的作者;癌症研究领域热点词包括生活质量、体育活动、康复、运动、随机对照试验、前列腺癌、乳腺癌、淋巴水肿和肺癌。癌症、绝经后妇女、心血管疾病、主要结局指标、规律运动、氧化应激、社会支持、住院时间等可能是癌症康复未来潜在的研究方向。结论 癌症康复研究正在经历快速发展的阶段。近10年来,癌症康复研究形成了以国家和研究机构为单位的研究群体,其中欧美国家对癌症康复的研究处于世界领先水平,美国在癌症康复领域的研究具有相当重要的地位。癌症康复领域研究热点和学术前沿包括研究疾病、研究对象和研究方法3个方面,研究疾病主要集中于前列腺癌、乳腺及肺癌及并发症,研究群体以女性居多,研究方法多采用随机对照试验。     

Do Cancer Patients Tweet? Examining the Twitter Use of Cancer Patients in Japan

Background

Twitter is an interactive, real-time media that could prove useful in health care. Tweets from cancer patients could offer insight into the needs of cancer patients.

Objective

The objective of this study was to understand cancer patients’ social media usage and gain insight into patient needs.

Methods

A search was conducted of every publicly available user profile on Twitter in Japan for references to the following: breast cancer, leukemia, colon cancer, rectal cancer, colorectal cancer, uterine cancer, cervical cancer, stomach cancer, lung cancer, and ovarian cancer. We then used an application programming interface and a data mining method to conduct a detailed analysis of the tweets from cancer patients.

Results

Twitter user profiles included references to breast cancer (n=313), leukemia (n=158), uterine or cervical cancer (n=134), lung cancer (n=87), colon cancer (n=64), and stomach cancer (n=44). A co-occurrence network is seen for all of these cancers, and each cancer has a unique network conformation. Keywords included words about diagnosis, symptoms, and treatments for almost all cancers. Words related to social activities were extracted for breast cancer. Words related to vaccination and support from public insurance were extracted for uterine or cervical cancer.

Conclusions

This study demonstrates that cancer patients share information about their underlying disease, including diagnosis, symptoms, and treatments, via Twitter. This information could prove useful to health care providers.