bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Approach for Detecting Sleep Apnea Using a Contactless Bed Sensor: Comparison Study
Authors: Sadek Ibrahim , Heng Terry Tan Soon , Seet Edwin , Abdulrazak Bessam 
Published: July 2020

Background
At present, there is an increased demand for accurate and personalized patient monitoring because of the various challenges facing health care systems. For instance, rising costs and lack of physicians are two serious problems affecting the patient’s care. Nonintrusive monitoring of vital signs is a potential solution to close current gaps in patient monitoring. As an example, bed-embedded ballistocardiogram (BCG) sensors can help physicians identify cardiac arrhythmia and obstructive sleep apnea (OSA) nonintrusively without interfering with the patient’s everyday activities. Detecting OSA using BCG sensors is gaining popularity among researchers because of its simple installation and accessibility, that is, their nonwearable nature. In the field of nonintrusive vital sign monitoring, a microbend fiber optic sensor (MFOS), among other sensors, has proven to be suitable. Nevertheless, few studies have examined apnea detection.

Objective
This study aims to assess the capabilities of an MFOS for nonintrusive vital signs and sleep apnea detection during an in-lab sleep study. Data were collected from patients with sleep apnea in the sleep laboratory at Khoo Teck Puat Hospital.

Methods
In total, 10 participants underwent full polysomnography (PSG), and the MFOS was placed under the patient’s mattress for BCG data collection. The apneic event detection algorithm was evaluated against the manually scored events obtained from the PSG study on a minute-by-minute basis. Furthermore, normalized mean absolute error (NMAE), normalized root mean square error (NRMSE), and mean absolute percentage error (MAPE) were employed to evaluate the sensor capabilities for vital sign detection, comprising heart rate (HR) and respiratory rate (RR). Vital signs were evaluated based on a 30-second time window, with an overlap of 15 seconds. In this study, electrocardiogram and thoracic effort signals were used as references to estimate the performance of the proposed vital sign detection algorithms.

Results
For the 10 patients recruited for the study, the proposed system achieved reasonable results compared with PSG for sleep apnea detection, such as an accuracy of 49.96% (SD 6.39), a sensitivity of 57.07% (SD 12.63), and a specificity of 45.26% (SD 9.51). In addition, the system achieved close results for HR and RR estimation, such as an NMAE of 5.42% (SD 0.57), an NRMSE of 6.54% (SD 0.56), and an MAPE of 5.41% (SD 0.58) for HR, whereas an NMAE of 11.42% (SD 2.62), an NRMSE of 13.85% (SD 2.78), and an MAPE of 11.60% (SD 2.84) for RR.

Conclusions
Overall, the recommended system produced reasonably good results for apneic event detection, considering the fact that we are using a single-channel BCG sensor. Conversely, satisfactory results were obtained for vital sign detection when compared with the PSG outcomes. These results provide preliminary support for the potential use of the MFOS for sleep apnea detection.
Investigation of a Mobile Health Texting Tool for Embedding Patient-Reported Data Into Diabetes Management (i-Matter): Development and Usability Study
Authors: Schoenthaler Antoinette , Cruz Jocelyn , Payano Leydi , Rosado Marina , Labbe Kristen , Johnson Chrystal , Gonzalez Javier , Patxot Melissa , Patel Smit , Leven Eric , Mann Devin 
Published: July 2020

Background
Patient-reported outcomes (PROs) are increasingly being used in the management of type 2 diabetes (T2D) to integrate data from patients’ perspective into clinical care. To date, the majority of PRO tools have lacked patient and provider involvement in their development, thus failing to meet the unique needs of end users, and lack the technical infrastructure to be integrated into the clinic workflow.

Objective
This study aims to apply a systematic, user-centered design approach to develop i-Matter (investigating a mobile health [mHealth] texting tool for embedding patient-reported data into diabetes management), a theory-driven, mobile PRO system for patients with T2D and their primary care providers.

Methods
i-Matter combines text messaging with dynamic data visualizations that can be integrated into electronic health records (EHRs) and personalized patient reports. To build i-Matter, we conducted semistructured group and individual interviews with patients with T2D and providers, a design thinking workshop to refine initial ideas and design the prototype, and user testing sessions of prototypes using a rapid-cycle design (ie, design-test-modify-retest).

Results
Using an iterative user-centered process resulted in the identification of 6 PRO messages that were relevant to patients and providers: medication adherence, dietary behaviors, physical activity, sleep quality, quality of life, and healthy living goals. In user testing, patients recommended improvements to the wording and timing of the PRO text messages to increase clarity and response rates. Patients also recommended including motivational text messages to help sustain engagement with the program. The personalized report was regarded as a key tool for diabetes self-management by patients and providers because it aided in the identification of longitudinal patterns in the PRO data, which increased patient awareness of their need to adopt healthier behaviors. Patients recommended adding individualized tips to the journal on how they can improve their behaviors. Providers preferred having a separate tab built into the EHR that included the personalized report and highlighted key trends in patients’ PRO data over the past 3 months.

Conclusions
PRO tools that capture patients’ well-being and the behavioral aspects of T2D management are important to patients and providers. A clinical trial will test the efficacy of i-Matter in 282 patients with uncontrolled T2D.

Trial Registration
ClinicalTrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389
Expert Opinions on Web-Based Peer Education Interventions for Youth Sexual Health Promotion: Qualitative Study
Authors: Martin Philippe , Alberti Corinne , Gottot Serge , Bourmaud Aurelie , de La Rochebrochard Elise 
Published: July 2020

Background
Participatory education, in the form of peer education, may be an effective way to promote youth sexual health. With the advent of the internet, web-based interventions have potential as an attractive new tool for sexual health promotion by peers.

Objective
The aim of this study was to evaluate professional experts’ opinions on the perspectives for web-based participatory interventions to promote sexual health by peers and among young people.

Methods
Semistructured interviews were carried out with 20 experts (stakeholders in direct contact with young people, researchers, and institutional actors) specializing in sexual health, health promotion, peer education, youth, internet, and social media. After coding with N’Vivo, data were subjected to qualitative thematic analysis.

Results
The majority of experts (18/20, 90%) found this kind of intervention to be attractive, but highlighted the necessary conditions, risks, and limitations attached to developing an acceptable peer intervention on the internet for sexual health promotion among young people. Five main themes were identified: (1) an internet intervention; (2) sexual health; (3) internet skills, and uses and the need for moderation; (4) multifaceted peers; and (5) minority peers. In the absence of youth interest for institutional messages, the experts highlighted the attractive participatory features of web-based interventions and the need for geolocalized resources. However, they also warned of the limitations associated with the possibility of integrating peers into education: peers should not be mere messengers, and should remain peers so as not to be outsiders to the target group. Experts highlighted concrete proposals to design an online participatory peer intervention, including the process of peer implication, online features in the intervention, and key points for conception and evaluation.

Conclusions
The experts agreed that web-based participatory interventions for youth sexual health promotion must be tailored to needs, uses, and preferences. This type of action requires youth involvement framed in an inclusive and holistic sexual health approach. Peer education can be implemented via the internet, but the design of the intervention also requires not being overly institutional in nature. Involving young people in their own education in an interactive, safe online space has the potential to develop their empowerment and to foster long-term positive behaviors, especially in the area of sexual health.
Patients’ Experiences of Telephone-Based and Web-Based Cognitive Behavioral Therapy for Irritable Bowel Syndrome: Longitudinal Qualitative Study
Authors: Hughes Stephanie , Sibelli Alice , Everitt Hazel A , Moss-Morris Rona , Chalder Trudie , Harvey J Matthew , Vas Falcao Andrea , Landau Sabine , O'Reilly Gilly , Windgassen Sula , Holland Rachel , Little Paul , McCrone Paul , Goldsmith Kimberley , Coleman Nicholas , Logan Robert , Bishop Felicity L 
Published: July 2020

Background
Cognitive behavioral therapy (CBT) is recommended in guidelines for people with refractory irritable bowel syndrome (IBS). However, the availability of CBT is limited, and poor adherence has been reported in face-to-face CBT.

Objective
Nested within a randomized controlled trial of telephone- and web-delivered CBT for refractory IBS, this qualitative study aims to identify barriers to and facilitators of engagement over time with the interventions, identify social and psychological processes of change, and provide insight into trial results.

Methods
A longitudinal qualitative study was nested in a randomized controlled trial. Repeated semistructured interviews were conducted at 3 (n=34) and 12 months (n=25) post baseline. Participants received telephone-based CBT (TCBT; n=17 at 3 months and n=13 at 12 months) or web-based CBT (WCBT; n=17 at 3 months and n=12 at 12 months). Inductive thematic analysis was used to analyze the data.

Results
Participants viewed CBT as credible for IBS, perceived their therapists as knowledgeable and supportive, and liked the flexibility of web-based and telephone-based delivery; these factors facilitated engagement. Potential barriers to engagement in both groups (mostly overcome by our participants) included initial skepticism and concerns about the biopsychosocial nature of CBT, initial concerns about telephone-delivered talking therapy, challenges of maintaining motivation and self-discipline given already busy lives, and finding nothing new in the WCBT (WCBT group only). Participants described helpful changes in their understanding of IBS, attitudes toward IBS, ability to recognize IBS patterns, and IBS-related behaviors. Consistent with the trial results, participants described lasting positive effects on their symptoms, work, and social lives. Reasons and remedies for some attenuation of effects were identified.

Conclusions
Both TCBT and WCBT for IBS were positively received and had lasting positive impacts on participants’ understanding of IBS, IBS-related behaviors, symptoms, and quality of life. These forms of CBT may broaden access to CBT for IBS.
An Artificial Intelligence Fusion Model for Cardiac Emergency Decision Making: Application and Robustness Analysis
Authors: Gong Liheng , Zhang Xiao , Li Ling 
Published: July 2020

Background
During cardiac emergency medical treatment, reducing the incidence of avoidable adverse events, ensuring the safety of patients, and generally improving the quality and efficiency of medical treatment have been important research topics in theoretical and practical circles.

Objective
This paper examines the robustness of the decision-making reasoning process from the overall perspective of the cardiac emergency medical system.

Methods
The principle of robustness was introduced into our study on the quality and efficiency of cardiac emergency decision making. We propose the concept of robustness for complex medical decision making by targeting the problem of low reasoning efficiency and accuracy in cardiac emergency decision making. The key bottlenecks such as anti-interference capability, fault tolerance, and redundancy were studied. The rules of knowledge acquisition and transfer in the decision-making process were systematically analyzed to reveal the core role of knowledge reasoning.

Results
The robustness threshold method was adopted to construct the robustness criteria group of the system, and the fusion and coordination mechanism was realized through information entropy, information gain, and mutual information methods.

Conclusions
A set of fusion models and robust threshold methods such as the R2CMIFS (treatment mode of fibroblastic sarcoma) model and the RTCRF (clinical trial observation mode) model were proposed. Our study enriches the theoretical research on robustness in this field.
Developing a Mobile App (iGAM) to Promote Gingival Health by Professional Monitoring of Dental Selfies: User-Centered Design Approach
Authors: Tobias Guy , Spanier Assaf B 
Published: July 2020

Background
Dental visits are unpleasant; sometimes, patients only seek treatment when they are in intolerable pain. Recently, the novel coronavirus (COVID-19) pandemic has highlighted the need for remote communication when patients and dentists cannot meet in person.
Gingivitis is very common and characterized by red, swollen, bleeding gums. Gingivitis heals within 10 days of professional care and with daily, thorough oral hygiene practices. If left untreated, however, its progress may lead to teeth becoming mobile or lost. Of the many medical apps currently available, none monitor gingivitis.

Objective
This study aimed to present a characterization and development model of a mobile health (mHealth) app called iGAM, which focuses on periodontal health and improves the information flow between dentists and patients.

Methods
A focus group discussed the potential of an app to monitor gingivitis, and 3 semistructured in-depth interviews were conducted on the use of apps for monitoring gum infections. We used a qualitative design process based on the Agile approach, which incorporated the following 5 steps: (1) user story, (2) use cases, (3) functional requirements, (4) nonfunctional requirements, and (5) Agile software development cycles. In a pilot study with 18 participants aged 18-45 years and with different levels of health literacy, participants were given a toothbrush, toothpaste, mouthwash, toothpicks, and dental floss. After installing iGAM, they were asked to photograph their gums weekly for 4 weeks.

Results
All participants in the focus group believed in the potential of a mobile app to monitor gingivitis and reduce its severity. Concerns about security and privacy issues were discussed. From the interviews, 2 themes were derived: (1) “what's in it for me?” and (2) the need for a take-home message. The 5 cycles of development highlighted the importance of communication between dentists, app developers, and the pilot group. Qualitative analysis of the data from the pilot study showed difficulty with: (1) the camera, which was alleviated with the provision of mouth openers, and (2) the operation of the phone, which was alleviated by changing the app to be fully automated, with a weekly reminder and an instructions document. Final interviews showed satisfaction.

Conclusions
iGAM is the first mHealth app for monitoring gingivitis using self-photography. iGAM facilitates the information flow between dentists and patients between checkups and may be useful when face-to-face consultations are not possible (such as during the COVID-19 pandemic).
Clinical Characteristics and Outcomes of Childbearing-Age Women With COVID-19 in Wuhan: Retrospective, Single-Center Study
Authors: Wei Lijie , Gao Xuan , Chen Suhua , Zeng Wanjiang , Wu Jianli , Lin Xingguang , Zhang Huiting , Mwamaka Sharifu Lali , Chen Ling , Feng Ling , Wang Shaoshuai 
Published: July 2020

Background
Since December 2019, an outbreak of the coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly in Wuhan and worldwide. However, previous studies on pregnant patients were limited.

Objective
The aim of this study is to evaluate the clinical characteristics and outcomes of pregnant and nonpregnant women with COVID-19.

Methods
This study retrospectively collected epidemiological, clinical, laboratory, imaging, management, and outcome data of 43 childbearing-age women patients (including 17 pregnant and 26 nonpregnant patients) who presented with laboratory-confirmed COVID-19 in Tongji Hospital, Wuhan, China from January 19 to March 2, 2020. Clinical outcomes were followed up to March 28, 2020.

Results
Of the 43 childbearing-age women in this study, none developed a severe adverse illness or died. The median ages of pregnant and nonpregnant women were 33.0 and 33.5 years, respectively. Pregnant women had a markedly higher proportion of history exposure to hospitals within 2 weeks before onset compared to nonpregnant women (9/17, 53% vs 5/26, 19%, P=.02) and a lower proportion of other family members affected (4/17, 24% vs 19/26, 73%, P=.004). Fever (8/17, 47% vs 18/26, 69%) and cough (9/17, 53% vs 12/26, 46%) were common onsets of symptoms for the two groups. Abdominal pain (n=4, 24%), vaginal bleeding (n=1, 6%), reduced fetal movement (n=1, 6%), and increased fetal movement (n=2, 13%) were observed at onset in the 17 pregnant patients. Higher neutrophil and lower lymphocyte percent were observed in the pregnant group compared to the nonpregnant group (79% vs 56%, P<.001; 15% vs 33%, P<.001, respectively). In both groups, we observed an elevated concentration of high-sensitivity C-reactive protein, erythrocyte sedimentation rate, aminotransferase, and lactate dehydrogenase. Concentrations of alkaline phosphatase and D-dimer in the pregnant group were significantly higher than those of the nonpregnant group (119.0 vs 48.0 U/L, P<.001; 2.1 vs 0.3μg/mL, P<.001, respectively). Both pregnant (4/10, 40%) and nonpregnant (8/15, 53%) women tested positive for influenza A virus. A majority of pregnant and nonpregnant groups received antiviral (13/17, 76% vs 25/26, 96%) and antibiotic (13/17, 76% vs 23/26, 88%) therapy. Additionally, both pregnant (2/11, 18%) and nonpregnant (2/19, 11%) recovered women redetected positive for SARS-CoV-2 after discharge.

Conclusions
The epidemiology and clinical and laboratory features of pregnant women with COVID-19 were diverse and atypical, which increased the difficulty of diagnosis. Most pregnant women with COVID-19 were mild and moderate, and rarely developed severe pneumonia or severe adverse outcomes.
Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries
Authors: Lim Cherry , Miliya Thyl , Chansamouth Vilada , Aung Myint Thazin , Karkey Abhilasha , Teparrukkul Prapit , Rahul Batra , Lan Nguyen Phu Huong , Stelling John , Turner Paul , Ashley Elizabeth , van Doorn H Rogier , Lin Htet Naing , Ling Clare , Hinjoy Soawapak , Iamsirithaworn Sopon , Dunachie Susanna , Wangrangsimakul Tri , Hantrakun Viriya , Schilling William , Yen Lam Minh , Tan Le Van , Hlaing Htay Htay , Mayxay Mayfong , Vongsouvath Manivanh , Basnyat Buddha , Edgeworth Jonathan , Peacock Sharon J , Thwaites Guy , Day Nicholas PJ , Cooper Ben S , Limmathurotsakul Direk 
Published: July 2020

Background
Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel.

Objective
This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly.

Methods
An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People’s Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam.

Results
We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.website/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository.

Conclusions
The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports.