The impact of rotavirus gastroenteritis on the family

BACKGROUND: Rotavirus is the leading cause of severe diarrhea in young children and causes substantial morbidity and mortality. Although the clinical aspects have been well described, little information is available regarding the emotional, social, and economic impact of rotavirus gastroenteritis on the family of a sick child. The objectives of this study were to: 1) assess the family impact of rotavirus gastroenteritis through qualitative interviews with parents; 2) compare the clinical severity of rotavirus-positive and negative gastroenteritis; 3) test a questionnaire asking parents to rank the importance of various factors associated with a case of rotavirus gastroenteritis. METHODS: The study enrolled parents and children (2–36 months of age) brought to one of the study sites (outpatient clinic or ER) if the child experienced ≥ 3 watery or looser-than normal stools and/or forceful vomiting within any 24-hour period within the prior 3 days. The clinical severity of each child's illness was rated using a clinical scoring system and stool samples were tested for rotavirus antigen. Parents of rotavirus-positive children were invited to participate in focus group or individual interviews and subsequently completed a questionnaire regarding the impact of their child's illness. RESULTS: Of 62 enrolled children, 43 stool samples were collected and 63% tested positive for rotavirus. Illness was more severe in children with rotavirus-positive compared to rotavirus-negative gastroenteritis (92% vs. 37.5% rated as moderate/severe). Seventeen parents of rotavirus-positive children participated in the interviews and completed the written questionnaire. Parents were frightened by the severity of vomiting and diarrhea associated with rotavirus gastroenteritis, and noted that family life was impacted in several ways including loss of sleep, missed work, and an inability to complete normal household tasks. They expressed frustration at the lack of a specific medication and the difficulty of treating the illness with oral rehydration solutions, but had a largely positive outlook concerning the prospect of a rotavirus vaccine. CONCLUSION: A better understanding of how rotavirus gastroenteritis impacts the family can help healthcare providers ease parental fears and advise them on the characteristics of this illness, practices to prevent infection, and the optimal care of an affected child

Prediction of recurrent Clostridium difficile infection using comprehensive electronic medical records in an integrated healthcare delivery system

BACKGROUNDPredicting recurrentClostridium difficileinfection (rCDI) remains difficult. METHODS. We employed a retrospective cohort design. Granular electronic medical record (EMR) data had been collected from patients hospitalized at 21 Kaiser Permanente Northern California hospitals. The derivation dataset (2007–2013) included data from 9,386 patients who experienced incident CDI (iCDI) and 1,311 who experienced their first CDI recurrences (rCDI). The validation dataset (2014) included data from 1,865 patients who experienced incident CDI and 144 who experienced rCDI. Using multiple techniques, including machine learning, we evaluated more than 150 potential predictors. Our final analyses evaluated 3 models with varying degrees of complexity and 1 previously published model.RESULTSDespite having a large multicenter cohort and access to granular EMR data (eg, vital signs, and laboratory test results), none of the models discriminated well (c statistics, 0.591–0.605), had good calibration, or had good explanatory power.CONCLUSIONSOur ability to predict rCDI remains limited. Given currently available EMR technology, improvements in prediction will require incorporating new variables because currently available data elements lack adequate explanatory power.Infect Control Hosp Epidemiol2017;38:1196–1203</jats:sec

Epidemiological and economic burden of Clostridium difficile in the United States: Estimates from a modeling approach

Appendix A: Population and Setting. Appendix B: Demographic, epidemiologic and economic model parameters. Appendix C: Supplementary Methods and Results. (DOCX 132 kb

Medical Records-Based Postmarketing Safety Evaluation of Rare Events with Uncertain Status

We develop a simple statistic for comparing rates of rare adverse events between treatment groups in post-marketing safety studies where the events have uncertain status. In this setting, the statistic is asymptotically equivalent to the logrank statistic, but the limiting distribution has Poisson and binomial components instead of being Guassian. We develop two new procedures for computing critical values, a Gaussian approximation and a parametric bootstrap. Both numerical and asymptotic properties of the procedures are studied. The test procedures are demonstrated on a post-marketing safety study of the RotaTeq vaccine. This vaccine was developed to reduce the incidence of severe diarrhea in infants

Talking Less during Social Interactions Predicts Enjoyment: A Mobile Sensing Pilot Study

Can we predict which conversations are enjoyable without hearing the words that are spoken? A total of 36 participants used a mobile app, My Social Ties, which collected data about 473 conversations that the participants engaged in as they went about their daily lives. We tested whether conversational properties (conversation length, rate of turn taking, proportion of speaking time) and acoustical properties (volume, pitch) could predict enjoyment of a conversation. Surprisingly, people enjoyed their conversations more when they spoke a smaller proportion of the time. This pilot study demonstrates how conversational properties of social interactions can predict psychologically meaningful outcomes, such as how much a person enjoys the conversation. It also illustrates how mobile phones can provide a window into everyday social experiences and well-being

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Commentaries on viewpoint : physiology and fast marathons

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Minimum Information about a Biosynthetic Gene cluster

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.Chemistry and Chemical Biolog