Digitising diabetes education for a safer Ramadan: Design, delivery, and evaluation of massive open online courses in Ramadan-focused diabetes education.

AIMS: Ramadan-focused diabetes education is critical to facilitate safer Ramadan fasting amongst Muslim people living with diabetes. We present the design, delivery, and evaluation of two parallel massive open online courses (MOOCs) in Ramadan-focused diabetes education for people with diabetes and HCPs. METHODS: Two Ramadan-focused diabetes education MOOCs were developed and delivered for Ramadan 2023: one for HCPs in English, and another for people with diabetes in English, Arabic and Malay. A user-centred iterative design process was adopted, informed by user feedback from a 2022 pilot MOOC. Evaluation comprised a mixed-methods evaluation of pre- and post-course user surveys. RESULTS: The platform was utilised by people with diabetes and their family, friends and healthcare professionals. Overall, a total of 1531 users registered for the platform from 50 countries, 809 started a course with a 48% subsequent completion rate among course starters. Qualitative analysis showed users found the course a user-friendly and authoritative information source. In the HCP MOOC, users reported improved post-MOOC Ramadan awareness, associated diabetes knowledge and ability to assess and advise patients in relation to their diabetes during Ramadan (p<0.01). CONCLUSIONS: We demonstrate the potential of MOOCs to deliver culturally tailored, high-quality, scalable, multilingual Ramadan-focused diabetes education to HCPs and people with diabetes.

Continuing the quality improvement of an electronic personal health record and interactive website for people with diabetes in Scotland (My Diabetes My Way).

AIMS: eHealth applications have the potential to enable patients to take more control over managing their own health, helping to delay and prevent complications. My Diabetes My Way (MDMW) is an electronic personal health record/educational platform available to people with diabetes in Scotland. This study aims to assess user experience with respect to demographic subgroups, examine effectiveness of previous improvements made to the platform and inform its ongoing development. METHODS: All active MDMW users (22,665) were invited to take part in a questionnaire combining Likert scale and free-response items relating to system utility. Likert responses were used to generate a 'utility score'. This was used in regression analyses to determine predictors of system utility scoring. Free-response answers were analysed thematically and themes were generated. RESULTS: A total of 4713 (21%) MDMW users responded to the questionnaire. Most agreed that MDMW helps them to track changes over time, prepare for face-to-face consultations, remember information discussed in consultations and reduced the need to contact their general practitioner. Free-response answers showed that users valued earlier enhancements made to the site (e.g. linking Fitbit data), and highlighted areas needing further improvement. Evidence of the 'digital divide' was seen in respondent demographics, and some users mentioned 'lack of digital skills' as a barrier to engaging with the platform. CONCLUSIONS: User experience of MDMW was positive. Users agreed with statements that MDMW facilitates diabetes self management. Several areas of potential improvement were identified, including linking more wearable device data, and assisting/directing users to gain the digital skills required to engage fully with MDMW.

Cost-Utility of an Online Education Platform and Diabetes Personal Health Record: Analysis Over Ten Years.

BACKGROUND AND AIMS: My Diabetes My Way (MDMW) is Scotland's interactive website and mobile app for people with diabetes and their caregivers. It contains multimedia resources for diabetes education and offers access to electronic personal health records. This study aims to assess the cost-utility of MDMW compared with routine diabetes care in people with type 2 diabetes who do not use insulin. MATERIALS AND METHODS: Analysis used the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model 2. Clinical parameters of MDMW users (n = 2576) were compared with a matched cohort of individuals receiving routine care alone (n = 11 628). Matching criteria: age, diabetes duration, sex, and socioeconomic status. Impact on life expectancy, quality-adjusted life years (QALYs), and costs of treatment and complications were simulated over ten years, including a 10% sensitivity analysis. RESULTS: MDMW cohort: 1670 (64.8%) men; average age 64.3 years; duration of diabetes 5.5 years. 906 (35.2%) women: average age 61.6 years; duration 4.7 years. The cumulative mean QALY (95% CI) gain: 0.054 (0.044-0.062) years. Mean difference in cost: -£118.72 (-£150.16 to -£54.16) over ten years. Increasing MDMW costs (10%): -£50.49 (-£82.24-£14.14). Decreasing MDMW costs (10%): -£186.95 (-£218.53 to -£122.51). CONCLUSIONS: MDMW is "dominant" over usual care (cost-saving and life improving) in supporting self-management in people with type 2 diabetes not treated with insulin. Wider use may result in significant cost savings through delay or reduction of long-term complications and improved QALYs in Scotland and other countries. MDMW may be among the most cost-effective interventions currently available to support diabetes.

Providing Care with Cultural, Racial, and Ethnic Humility: the Framework for an Additional Entrustable Professional Activity.

Healthcare inequities are rampant in the USA. There is a lack of standardization for training medical students in providing care with cultural, racial, and ethnic humility. This innovation is the framework of an entrustable professional activity that can be utilized to address this vital issue.

User-Centered Design of A Novel Risk Prediction Behavior Change Tool Augmented With an Artificial Intelligence Engine (MyDiabetesIQ): A Sociotechnical Systems Approach.

BACKGROUND: Diabetes and its complications account for 10% of annual health care spending in the United Kingdom. Digital health care interventions (DHIs) can provide scalable care, fostering diabetes self-management and reducing the risk of complications. Tailorability (providing personalized interventions) and usability are key to DHI engagement/effectiveness. User-centered design of DHIs (aligning features to end users' needs) can generate more usable interventions, avoiding unintended consequences and improving user engagement. OBJECTIVE: MyDiabetesIQ (MDIQ) is an artificial intelligence engine intended to predict users' diabetes complications risk. It will underpin a user interface in which users will alter lifestyle parameters to see the impact on their future risks. MDIQ will link to an existing DHI, My Diabetes My Way (MDMW). We describe the user-centered design of the user interface of MDIQ as informed by human factors engineering. METHODS: Current users of MDMW were invited to take part in focus groups to gather their insights about users being shown their likelihood of developing diabetes-related complications and any risks they perceived from using MDIQ. Findings from focus groups informed the development of a prototype MDIQ interface, which was then user-tested through the "think aloud" method, in which users speak aloud about their thoughts/impressions while performing prescribed tasks. Focus group and think aloud transcripts were analyzed thematically, using a combination of inductive and deductive analysis. For think aloud data, a sociotechnical model was used as a framework for thematic analysis. RESULTS: Focus group participants (n=8) felt that some users could become anxious when shown their future complications risks. They highlighted the importance of easy navigation, jargon avoidance, and the use of positive/encouraging language. User testing of the prototype site through think aloud sessions (n=7) highlighted several usability issues. Issues included confusing visual cues and confusion over whether user-updated information fed back to health care teams. Some issues could be compounded for users with limited digital skills. Results from the focus groups and think aloud workshops were used in the development of a live MDIQ platform. CONCLUSIONS: Acting on the input of end users at each iterative stage of a digital tool's development can help to prioritize users throughout the design process, ensuring the alignment of DHI features with user needs. The use of the sociotechnical framework encouraged the consideration of interactions between different sociotechnical dimensions in finding solutions to issues, for example, avoiding the exclusion of users with limited digital skills. Based on user feedback, the tool could scaffold good goal setting, allowing users to balance their palatable future complications risk against acceptable lifestyle changes. Optimal control of diabetes relies heavily on self-management. Tools such as MDMW/ MDIQ can offer personalized support for self-management alongside access to users' electronic health records, potentially helping to delay or reduce long-term complications, thereby providing significant reductions in health care costs.

Multicentre service evaluation of presentation of newly diagnosed cancers and type 1 diabetes in children in the UK during the COVID-19 pandemic.

Background: The COVID-19 pandemic led to changes in patterns of presentation to emergency departments. Child health professionals were concerned that this could contribute to the delayed diagnosis of life-threatening conditions, including childhood cancer (CC) and type 1 diabetes (T1DM). Our multicentre, UK-based service evaluation assessed diagnostic intervals and disease severity for these conditions. Methods: We collected presentation route, timing and disease severity for children with newly diagnosed CC in three principal treatment centres and T1DM in four centres between 1 January and 31 July 2020 and the corresponding period in 2019. Total diagnostic interval (TDI), patient interval (PI), system interval (SI) and disease severity across different time periods were compared. Results: For CCs and T1DM, the route to diagnosis and severity of illness at presentation were unchanged across all time periods. Diagnostic intervals for CCs during lockdown were comparable to that in 2019 (TDI 4.6, PI 1.1 and SI 2.1 weeks), except for an increased PI in January-March 2020 (median 2.7 weeks). Diagnostic intervals for T1DM during lockdown were similar to that in 2019 (TDI 16 vs 15 and PI 14 vs 14 days), except for an increased PI in January-March 2020 (median 21 days). Conclusions: There is no evidence of diagnostic delay or increased illness severity for CC or T1DM, during the first phase of the pandemic across the participating centres. This provides reassuring data for children and families with these life-changing conditions.

A novel binary pipette splitting sediment subsampling method for improving reproducibility in laser-diffraction particle-size analysis.

Laser-diffraction analysis has been established as one of the standard methods for particle-size distribution (PSD) measurement. However, the uncertainty when analyzing naturally heterogeneous sediment is poorly constrained for the lack of control on one of its largest error sources simply originating from subsampling. Here, we introduce a novel subsampling method, binary pipette splitting (BPS), and verify its precision by using sediment samples from ten flood-layer deposits that have formed in the wake of Hurricane Florence (2018). The BPS approach avoids extracting from only a fixed part of the suspended fluid but considers all the suspended sediment, resulting in the generation of twin subsamples. The median coefficient of variation (COV) for D10, D50, and D90 of subsamples obtained using BPS is 4%, 3%, and 2%, respectively. These values are significantly smaller than the corresponding values of 18%, 15%, and 13% obtained using the conventional pipette subsampling method. Therefore, the new BPS method represents a significant improvement in producing statistically identical subsamples for laser-diffraction particle-size analysis. •The binary pipette splitting (BPS) subsampling method dramatically improves the reproducibility of subsampling wet sediment.

Remote Learning and Its Impact on Newly Matriculated Medical Students.

Objective The coronavirus disease 2019 (COVID-19) pandemic has led to massive disruptions in medical education. In the fall of 2020, newly matriculated medical students around the country started medical school in a remote learning setting. The purpose of this study is to assess the impact of remote learning during the COVID-19 pandemic on academic performance and student satisfaction among first-year medical students. Methods The newest cohort of first-year medical students (class of 2024; n = 128) who completed their first basic science course, "Genes, Molecules & Cells (GMC)," using an adapted remote format was compared to the prior year's cohort (class of 2023; n = 122) of first-year medical students who were taught using traditional approaches. The items that were compared were numerical performance on exams and quizzes, study strategies, and course evaluation in GMC. Data were analyzed with a two-sided t-test and Pearson correlation coefficient. Students' perception of remote learning was also reported and results were obtained using a five-point Likert scale through anonymous surveys via E-value. Results No statistical difference was observed in students' performance on the midterm and final examinations between the two cohorts in both multiple-choice and written examinations. Mean multiple-choice question (MCQ) midterm students' performance in remote learning compared to traditional learning cohort was 75.9%, standard deviation (SD) 6.1 to 75.89%, SD 6.49, respectively. Mean MCQ final students' performance was 84%, SD 6.37 (class of 2024) to 85%, SD 8.78 (class of 2023). Students' satisfaction with their learning experience was similar among the two groups (class of 2024: mean = 4.61, SD 0.66; class of 2023: mean = 4.57, SD 0.68). Most students (70%) in the remote learning cohort had a positive opinion of remote learning. Of the students, 17% reported feeling disconnected, isolated, or not actively involved. Conclusions The results of this study demonstrate that not only is remote learning effective but that the students were also resilient in their adaptation to a new learning format. Our experience highlights the importance of including wellness solutions to mitigate the feeling of isolation and disconnection during remote learning.

A Longitudinal Perspective on User Uptake of an Electronic Personal Health Record for Diabetes, With Respect To Patient Demographics.

INTRODUCTION: The growing prevalence of diabetes has increased the need for scalable technologies to improve outcomes. My Diabetes My Way (MDMW) is an electronic personal health record (ePHR) available to all people with diabetes in Scotland since 2010, associated with improved clinical outcomes among users. MDMW pulls data from a national clinician-facing informatics platform and provides self-management and educational information. This study aims to describe MDMW user demographics through time with respect to the national diabetes population, with a view to addressing potential health inequalities. METHODS: Aggregate data were obtained retrospectively from the MDMW database and annual Scottish Diabetes Survey (SDS) from 2010 to 2020. Variables included diabetes type, sex, age, socioeconomic status, ethnicity, and glycemic control. Prevalence of MDMW uptake was calculated using corresponding SDS data as denominators. Comparisons between years and demographic sub-groups were made using Chi- Squared tests. RESULTS: Overall uptake of MDMW has steadily increased since implementation. By 2020, of all people with T1D or T2D in Scotland, 13% were fully enrolled to MDMW (39,881/312,326). There was proportionately greater numbers of users in younger, more affluent demographic groups (with a clear social gradient) with better glycemic control. As uptake has increased through time, so too has the observed gaps between different demographic sub-groups. CONCLUSIONS: The large number of MDMW users is encouraging, but remains a minority of people with diabetes in Scotland. There is a risk that innovations like MDMW can widen health inequalities and it is incumbent upon healthcare providers to identify strategies to prevent this.

Unique presentation and management of Gowers intrasyringal hemorrhage.

Context: Intrasyringal hemorrhage was first described in literature in the renowned Lectures on Diseases of the Nervous System by Sir William Richard Gowers [Gowers W. A lecture on syringal haemorrhage into the spinal cord. Lancet [Internet]; 162(4180):993-997. [cited 2019 August 19]. Available from https://www.sciencedirect.com/science/article/pii/S0140673601362785]. The pathophysiology of this disease is a hemorrhage within a preexisting intramedullary fluid-filled cavity or hydrosyringomyelia in the spinal cord. Most common symptoms of this disease are numbness, weakness, paresthesia in the extremities and gait disturbances. Since first noted in 1903, there have been just fourteen confirmed cases of this disease reported in literature, making it extremely rare and difficult to study.Findings: Here we discuss a unique presentation of Gowers intrasyringal hemorrhage. The patient is a male in his late teens with no prior established neurological history. He presented at our institution four days post suspected injury with persistent mild left upper extremity numbness and weakness. The patient was admitted and underwent an MRI of the cervical spine without intravenous contrast. The imaging findings confirm subacute on chronic Gowers intrasyringal hemorrhage in the setting of a Chiari 1 malformation. This patient underwent neurosurgical intervention four months post initial presentation and had complete postoperative resolution of his interval non-progressive but persistent symptoms.Clinical relevance: This unique case suggests immediate surgical intervention may not always be necessary for treating Gowers intrasyringal hemorrhage.

Glycaemic control trends in people with type 1 diabetes in Scotland 2004-2016.

AIMS/HYPOTHESIS: The aim of this work was to examine whether glycaemic control has improved in those with type 1 diabetes in Scotland between 2004 and 2016, and whether any trends differed by sociodemographic factors. METHODS: We analysed records from 30,717 people with type 1 diabetes, registered anytime between 2004 and 2016 in the national diabetes database, which contained repeated measures of HbA1c. An additive mixed regression model was used to estimate calendar time and other effects on HbA1c. RESULTS: Overall, median (IQR) HbA1c decreased from 72 (21) mmol/mol [8.7 (4.1)%] in 2004 to 68 (21) mmol/mol (8.4 [4.1]%) in 2016. However, all of the improvement across the period occurred in the latter 4 years: the regression model showed that the only period of significant change in HbA1c was 2012-2016 where there was a fall of 3 (95% CI 1.82, 3.43) mmol/mol. The largest reductions in HbA1c in this period were seen in children, from 69 (16) mmol/mol (8.5 [3.6]%) to 63 (14) mmol/mol (7.9 [3.4]%), and adolescents, from 75 (25) mmol/mol (9.0 [4.4]%) to 70 (23) mmol/mol (8.6 [4.3]%). Socioeconomic status (according to Scottish Index of Multiple Deprivation) affected the HbA1c values: from the regression model, the 20% of people living in the most-deprived areas had HbA1c levels on average 8.0 (95% CI 7.4, 8.9) mmol/mol higher than those of the 20% of people living in the least-deprived areas. However this difference did not change significantly over time. From the regression model HbA1c was on average 1.7 (95% CI 1.6, 1.8) mmol/mol higher in women than in men. This sex difference did not narrow over time. CONCLUSIONS/INTERPRETATION: In this high-income country, we identified a modest but important improvement in HbA1c since 2012 that was most marked in children and adolescents. These changes coincided with national initiatives to reduce HbA1c including an expansion of pump therapy. However, in most people, overall glycaemic control remains far from target levels and further improvement is badly needed, particularly in those from more-deprived areas.

My Diabetes My Way: supporting online diabetes self-management: progress and analysis from 2016.

BACKGROUND: My Diabetes My Way (MDMW) is the National Health Service (NHS) Scotland website for people with diabetes and their carers. It consists of an interactive information website and an electronic personal health record (ePHR) available to the 291,981 people with diabetes in Scotland. We aimed to analyse the demographic characteristics of current registrants and system usage and activity during 2016. METHODS: We analysed system audit trails to monitor user activity and page accesses on the information website, and logins and activity within the ePHR. The ePHR contains data from SCI-Diabetes, NHS Scotland's flagship diabetes record, sourcing data from primary and secondary care, specialist screening services and laboratory systems. We reviewed patient registration characteristics to collate demographic data for the MWDH cohort, then compared this to aggregate data published in the 2016 Scottish Diabetes Survey. The Scottish Diabetes Survey is an annual population-based report detailing diabetes statistics for the whole diabetes population in NHS Scotland. RESULTS: The MDMW information website received an average of 101,382 page accesses per month during 2016 (56.9% increase from 2015; n = 64,607). ePHR registrants were more likely to be younger (p < 0.001) and have an ethnicity of "white" (p < 0.001) than the background diabetes population. At the end of 2016, 11,840 people with diabetes had accessed their personal clinical information (58.6% increase since end 2015; n = 7464). During 2016, an average of 1907 people accessed their records each month (48.3% increase from 2015; n = 1286). CONCLUSION: My Diabetes My Way is a useful tool aid to diabetes self-management. The service is unique in offering records access to a national population, providing information from all relevant diabetes-related sources, rather than a single silo. MDMW supports the diabetes improvement, self-management, healthcare quality and eHealth strategies of the Scottish Government. The service also has potential to be adapted to work with other clinical systems and conditions.

User Experiences of an Electronic Personal Health Record for Diabetes.

BACKGROUND: My Diabetes My Way (MDMW) is an electronic personal health record (ePHR) that provides access to educational resources and clinical data to people with diabetes in Scotland. This questionnaire study aims to assess user experience, barriers to access, and inform future development. METHODS: All active MDMW users (n = 3797) were invited to complete an online questionnaire in May 2015, surveying usage patterns and system utility. A "utility score" was calculated, based on responses to Likert-scale questions and used as the dependent variable within regression analysis, with demographic features as independent predictors. Free-text responses were analyzed thematically and presented using descriptive statistics. RESULTS: A total of 1095/3797 (27.5%) active users completed the survey. Of them, 690/1095 (63%) were male. There was representation of all age and socioeconomic groups. Respondents were positive regarding the system utility, which met expectations. The majority of respondents believed that online access to diabetes information has the potential to improve diabetes self-care within the population. The most valued features were personal clinical data associated visualizations. Th main problems cited were data accuracy and system access (ie, log-in procedure). Perceived usefulness of the system was inversely associated with duration of diabetes, which was the only significant predictor of utility score. CONCLUSIONS: This study has demonstrated that MDMW users find the system useful in supporting diabetes self-management. The system was found to have greatest utility among those most recently diagnosed with diabetes. This study has informed further development of the service, including enhancing data visualization and the need to improve access to the system.

Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

BACKGROUND: Automated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014. METHODS: Feedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year. RESULTS: The CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). DISCUSSION AND CONCLUSIONS: The CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

Incidence of type 1 diabetes has doubled in Kuwaiti children 0-14 years over the last 20 years.

AIMS: This study had 2 aims: to report data on the incidence of childhood-onset type 1 diabetes in Kuwaiti children aged 0-14 years during 2011 to 2013 and to compare the recent data with those collected during 1992 to 1997. METHODS: All newly diagnosed patients were registered through the Childhood-Onset Diabetes eRegistry (CODeR) in 2011-2013, based on the DiaMond protocol used in 1992-1997. RESULTS: A total of 515 Kuwaiti children (247 boys and 268 girls) aged 0-14 years newly diagnosed with type 1 diabetes were registered from 1 January 2011 to 31 December 2013. Data ascertainment were 96.7%. The mean age ± SD at diagnosis was 8.7 ± 3.4 years in boys and 7.9 ± 3.1 years in girls. The crude incidence rate (95% CI) was 40.9 (37.4-44.6) and the age standardized rate 41.7 (95% 38.1-45.4) per 100,000 per year, 39.3 (34.6-44.4) among boys and 44.1 (39.0-49.7) among girls. A statistically significant increasing trend in incidence was observed as the overall crude incidence rose from 17.7 in 1992-1994 to 40.9 per 100,000 per year in 2011-2013. The Poisson regression model depicting the trend in incidence revealed that, the incidence rates adjusted for age and sex in 2011 to 2013 was 2.3 (95% CI 1.9-2.7) times higher than 1992-1997. CONCLUSIONS: The incidence of type 1 diabetes in Kuwaiti children 0-14 years has doubled in the last 2 decades. The reasons for this increase requires further investigation.

eHealth and the use of individually tailored information: A systematic review.

Tailored messages are those that specifically target individuals following an assessment of their unique characteristics. This systematic review assesses the evidence regarding the effectiveness of tailoring within eHealth interventions aimed at chronic disease management. OVID Medline/Embase databases were searched for randomised control trials, controlled clinical, trials, before -after studies, and time series analyses from inception - May 2014. Objectively measured clinical processes/outcomes were considered. Twenty-two papers were eligible for inclusion: 6/22 used fully tailored messaging and 16/22 used partially tailored messages. Two studies isolated tailoring as the active component. The remainder compared intervention with standard care. In all, 12/16 studies measuring clinical processes and 2/6 studies reporting clinical outcomes showed improvements, regardless of target group. Study quality was low and design did not allow for identification of interventions' active component. Heterogeneity precluded meta-analysis. This review has demonstrated that there is a lack of evidence to suggest that tailoring within an eHealth context confers benefit over non-tailored eHealth interventions.

Viral Etiology and the Impact of Codetection in Young Children Presenting With Influenza-Like Illness.

BACKGROUND: Children with acute respiratory tract infection (ARTI) frequently exhibit virus-virus codetection, yet the clinical significance of ARTI remains contentious. Using data from a prospective cohort of children with influenza-like illness, we examined the virology of ARTI and determined the clinical impact of virus-virus codetection. METHODS: Children aged 6 to 59 months who presented to a tertiary pediatric hospital between influenza seasons 2008 and 2012 with fever and acute respiratory symptoms were enrolled, and nasal samples were collected. Respiratory viruses were identified by culture and polymerase chain reaction. We compared demographics, presenting symptoms, and clinical outcomes of children with a single-virus infection and those in whom 2 or more viruses were detected (virus-virus codetection). We used logistic regression models and estimated marginal means to calculate the adjusted odds ratios and probabilities of symptom presentation, prescription of antibiotics, and hospitalization. RESULTS: Of 2356 children, a virus was detected in 1630 (69.2%) of them; rhinovirus (40.8%), influenza (29.5%), and respiratory syncytial virus (26.4%) were detected most commonly. Two or more viruses were detected in 25% of these children. After we adjusted for demographic factors, children with virus-virus codetection had greater odds of presenting with cough (adjusted odds ratio [aOR], 1.9; 95% confidence interval [CI], 1.2-3.1) and rhinorrhea (aOR, 1.8; 95% CI, 1.1-2.9) than those with a single-virus infection, although both symptoms were common. Children with influenza and respiratory syncytial virus combined had the highest probability of hospitalization (55%; 95% CI, 35%-73%), which was significantly greater than for those with influenza infection alone (22%; 95% CI, 16%-29%). CONCLUSIONS: Overall, virus-virus codetection has limited impact on clinical severity among children with influenza-like illness. However, infection with specific pathogen pairs might be associated with more severe outcomes. Routine diagnostics to identify specific viruses should be restricted to common pathogens.

Design, synthesis, and testing toward a 57-codon genome.

Recoding--the repurposing of genetic codons--is a powerful strategy for enhancing genomes with functions not commonly found in nature. Here, we report computational design, synthesis, and progress toward assembly of a 3.97-megabase, 57-codon Escherichia coli genome in which all 62,214 instances of seven codons were replaced with synonymous alternatives across all protein-coding genes. We have validated 63% of recoded genes by individually testing 55 segments of 50 kilobases each. We observed that 91% of tested essential genes retained functionality with limited fitness effect. We demonstrate identification and correction of lethal design exceptions, only 13 of which were found in 2229 genes. This work underscores the feasibility of rewriting genomes and establishes a framework for large-scale design, assembly, troubleshooting, and phenotypic analysis of synthetic organisms.

mHealth applications for diabetes: User preference and implications for app development.

Increasing diabetes prevalence has led to the need for more sustainable and person-centred services. The diabetes self-care mHealth marketplace is growing, but most effective/valued features are unknown. This study gauges diabetes app user opinion to inform development work. An analysis of diabetes mHealth apps informed design of a questionnaire sent to a random sample of 400 patients stratified by diabetes type and age. Responses were analysed by sub-group, and preferences were compared with current diabetes apps. App features included data storage/graphics, exercise tracking, health/diet, reminders/alarms, education. Questionnaire response rate was 59 per cent (234/400); 144/233 (62%) owned smartphones. Smartphone users expressed preference towards mHealth (101/142 (71%)), although diabetes use was low (12/163 (7%)). Respondents favoured many potential features, with similar preferences between diabetes types. This study demonstrates that while mHealth acceptance is high, current engagement is low. Engagement and functionality could be improved by including stakeholders in future development, driven by clinical/user need.