3,064 research outputs found
Quantitative Risk-Benefit Analysis of Probiotic Use for Irritable Bowel Syndrome and Inflammatory Bowel Disease
Probiotics have seen widespread use for a variety of gastrointestinal problems, especially in two common disorders: irritable bowel syndrome and inflammatory bowel disease. Since a wide variety of probiotic preparations has been used, and despite a large number of studies performed, a great deal of heterogeneity exists among them. Straightforward evidence-based recommendations for the use of probiotics in irritable bowel syndrome and inflammatory bowel disease have thus been difficult to formulate. In an effort to improve understanding of the risk–benefit balance of probiotics in these conditions, this study (1) queried the US FDA Adverse Event Reporting System (FAERS) database for all reported adverse drug events related to probiotics in 2013, and (2) constructed risk–benefit planes for both irritable bowel syndrome and inflammatory bowel disease using a geometric approximation of the confidence region between risk and benefit. The results show that adverse events from probiotics vary widely by disease, and when they occur, they are mild and may be difficult to distinguish from the natural history of the underlying disorders they are used to treat. The risk–benefit plane for irritable bowel syndrome straddles the risk–benefit threshold, so patients can expect a balance between a low chance of risk and also a low chance of benefit. The risk–benefit plane for inflammatory bowel disease largely lies above the risk–benefit threshold, so patients may expect more benefit than risk in most cases. More standardized and high-quality research is needed to improve our understanding of risk and benefit for these complex biopharmaceuticals
Bayesian Networks to Assess the Newborn Stool Microbiome
In human stool, a large population of bacterial genes and transcripts from hundreds of genera coexist with host genes and transcripts. Assessments of the metagenome and transcriptome are particularly challenging, since there is a great deal of sequence overlap among related species and related genes. We sequenced the total RNA content from stool samples in a neonate using previously-described methods. We then performed stepwise alignment of different populations of RNA sequence reads to different indices, including ribosomal databases, the human genome, and all sequenced bacterial genomes. Each pool of RNA at each alignment step was subjected to compression to assess sequence complexity in bits per symbol. In order to account for the high degree of overlap among species, a Bayesian network tool (RNABayes) was constructed using a node based on 16S sequencing, and a large number of nodes based on alignment scores to bacterial genes. The following algorithm was then employed: (1) fit 16S census from a sample onto a Dirichlet distribution using maximum likelihood estimation to get the conjugate prior, (2) estimate probabilities of each bacterial genus for each bacterial mRNA alignment using BLAST alignment scores, (3) fit each of these probabilities to a Dirichlet distribution using maximum likelihood estimation, (4) perform inference iteratively to update the conjugate prior, with the result being the posterior probability distribution of metabolically active stool bacteria. This algorithm was then applied to three datasets: (1) a simulated data set with normally distributed mRNAs, (2) a simulated data set with skewed mRNAs for a single bacterial population, and (3) the RNASeq dataset from our newborn stool sample. Results indicate that a Bayesian network built in this fashion reliably adjusts the prior bacterial population distribution to more accurately reflect the transcriptionally active bacterial population. Application of this method to real world samples appears to show even more marked skew, indicating transcripts are not uniformly distributed by population
A cross-sectional study of predatory publishing emails received by career development grant awardees
OBJECTIVE:
To investigate the scope of academic spam emails (ASEs) among career development grant awardees and the factors associated with the amount of time spent addressing them.
DESIGN:
A cross-sectional survey of career development grant investigators via an anonymous online survey was conducted. In addition to demographic and professional information, we asked investigators to report the number of ASEs received each day, how they determined whether these emails were spam and time they spent per day addressing them. We used bivariate analysis to assess factors associated with the amount of time spent on ASEs.
SETTING:
An online survey sent via email on three separate occasions between November and December 2016.
PARTICIPANTS:
All National Institutes of Health career development awardees funded in the 2015 fiscal year.
MAIN OUTCOME MEASURES:
Factors associated with the amount of time spent addressing ASEs.
RESULTS:
A total of 3492 surveys were emailed, of which 206 (5.9%) were returned as undeliverable and 96 (2.7%) reported an out-of-office message; our overall response rate was 22.3% (n=733). All respondents reported receiving ASEs, with the majority (54.4%) receiving between 1 and 10 per day and spending between 1 and 10 min each day evaluating them. The amount of time respondents reported spending on ASEs was associated with the number of peer-reviewed journal articles authored (p<0.001), a history of publishing in open access format (p<0.01), the total number of ASEs received (p<0.001) and a feeling of having missed opportunities due to ignoring these emails (p=0.04).
CONCLUSIONS:
ASEs are a common distraction for career development grantees that may impact faculty productivity. There is an urgent need to mitigate this growing problem
Hypothyroidism is a rare cause of isolated constipation
The prevalence of constipation in children is high and accounts for a large percentage of pediatric and pediatric gastroenterology visits. Thyroid testing is frequently ordered to evaluate constipation and other gastrointestinal complaints in children. We reviewed all patients with thyroid testing ordered by our pediatric gastroenterology division over a five-year period. We found 873 patients on whom thyroid testing was performed, and 56 had evidence of hypothyroidism. Nine patients had constipation and clinically significant hypothyroidism in this group. However, only one child had constipation as their sole presenting symptom. The contribution of occult hypothyroidism to isolated constipation in children may have been previously overestimated
Cross-sectional comparison of critically ill pediatric patients across hospitals with various levels of pediatric care
BACKGROUND: Inpatient administrative data sources describe the care provided to hospitalized children. The Kids' Inpatient Database (KID) provides nationally representative estimates, while the Pediatric Health Information System (PHIS, a consortium of pediatric facilities) derives more detailed information from revenue codes. The objective was to contextualize a diagnosis and procedure-based definition of critical illness to a revenue-based definition; then compare it across hospitals with different levels of pediatric care.
METHODS: This retrospective, cross-sectional study utilized the 2009 KID, and 2009 inpatient discharges from the PHIS database. Patients <21 years of age (excluding neonates) were included to focus on pediatric critical illness. Critical illness was defined as: (1) critical care services (CC services) using diagnosis and procedures codes and (2) intensive care unit (ICU) care using revenue codes. Demographics, invasive procedures, and categories of critical illness were compared using Chi square and survey-weighted methods. The definitions of critical illness were compared in PHIS hospitals. CC services populations identified in General Hospitals, Pediatric Facilities, and Freestanding Children's hospitals (from KID) were compared to those in PHIS hospitals.
RESULTS: Among PHIS hospitals, critically ill discharges identified by CC services accounted for 37.7% of ICU care. CC services discharges were younger and had greater proportion of respiratory illness and invasive procedure use. Critically ill patients identified by CC services in PHIS hospitals were statistically similar to those in Freestanding Children's hospitals. Pediatric Facilities and General Hospitals had more adolescents with more traumas. CC services patients in general hospitals had lower use of invasive procedures and predominance of trauma, respiratory illness, mental health issues, and general infections. Freestanding children's hospitals discharged 22% of the estimated 96,700 CC services cases. Similar proportions of critically ill patients were seen in Pediatric Facilities (31%) and General Hospitals (33%).
CONCLUSION: The CC services definition captured a more severely ill fraction of critically ill children. Critically ill discharges from PHIS hospitals can likely be extrapolated to Freestanding Children's hospitals and Pediatric Facilities. General Hospitals, which provide a significant amount of pediatric critical care, are different. Studies utilizing administrative data can benefit from multiple data sources, which balance the individual strengths and weaknesses
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