Defining constipation to estimate its prevalence in the community: Results from a national survey

© 2019 The Author(s). Background: Different definitions of constipation have been used to estimate its prevalence in the community but this creates difficulties when comparing results from various studies. This study explores the impact of different definitions on prevalence estimates in the same population and compares the performance of simple definitions with the Rome III criteria. Methods: The prevalence of constipation in a large nationally representative sample of community-dwelling adults was estimated using five simple definitions of constipation and compared with definitions based on the Rome III criteria. The sensitivity, specificity, and positive and negative predictive values, were calculated for each definition using the Rome III criteria as the gold standards for chronic and sub-chronic constipation. Results: Prevalence estimates for the five simple definitions ranged from 9.4 to 58.9%, while the prevalence estimates using the Rome III criteria were 24.0% (95%CI: 22.1, 25.9) for chronic constipation and 39.6% (95%CI: 37.5, 41.7) for sub-chronic constipation. None of the simple definitions were adequate compared to the Rome III criteria. Self-reported constipation over the past 12 months had the highest sensitivity (91.1%, 95%CI: 88.8, 93.4) and negative predictive value (94.5%, 95%CI: 93.1, 96.1) compared to the Rome III criteria for chronic constipation but an unacceptably low specificity (51.3%, 95%CI: 48.8, 53.8) and positive predictive value (37.1%, 95%CI: 34.4, 39.9). Conclusions: The definition used to identify constipation within a population has a considerable impact on the prevalence estimate obtained. Simple definitions, commonly used in research, performed poorly compared with the Rome III criteria. Studies estimating population prevalence of constipation should use definitions based on the Rome criteria where possible

Evaluation of clinical sites used for training undergraduate physiotherapy students: Factors that may impact on learning

Background. Clinical education forms an integral part of the training of undergraduate healthcare students. Clinical learning and education can be influenced by a number of factors.Objectives. To evaluate clinical service sites used to train undergraduate physiotherapy students at Stellenbosch University, in terms of: (i) the suitability of the site as a training facility; and (ii) the range of clinical problems students encounter at these clinical service sites.Methods. A descriptive study was conducted. Data were gathered through structured clinical site visits, staff interviews and student record sheets documenting the number and type of patients students encountered at the clinical service sites.Results. Seven of the nine clinical sites used for training were evaluated. Close proximity to the Faculty was an identified strength of three of the sites. There were opportunities for the expansion of multidisciplinary services and group treatment classes. There were safety concerns at most of the sites visited. The number of qualified physiotherapists was low and there was also a lack of basic equipment needed for patient management at more than half of the clinical sites. Students’ exposure to the various fields of physiotherapy varied greatly at the tertiary service settings versus primary healthcare settings. On average students saw only two patients per day during a 5-hour clinical day.Conclusion. The suitability of healthcare service sites for training undergraduate students should be carefully evaluated prior to commencing training at these sites. The development of good clinical training sites for undergraduate healthcare students requires the availability of adequate resources such as equipment, an adequate complement of clinical staff and effective measures to ensure student and patient safety

Potential for Detection of Safety Signals for Over-the-Counter Medicines Using National ADR Spontaneous Reporting Data: The Example of OTC NSAID-Associated Gastrointestinal Bleeding.

One post-marketing surveillance challenge for many regulatory authorities is access to information regarding the safety of over-the-counter (OTC) medicines. National spontaneous adverse drug reaction (ADR) report data represent a rich potential data source for the detection of safety signals associated with OTC medicines, yet little is known regarding the possibility of detecting safety signals for OTC medicines within these datasets. The aim of this study was to evaluate the potential for detecting safety signals for OTC medicines in National ADR spontaneous reporting data, using OTC non-steroidal anti-inflammatory drugs (NSAIDs) and gastrointestinal bleeding as an example. Data from the Australian Adverse Drug Reactions System (ADRS) dataset (1971-2008) and the Canadian Vigilance Adverse Reaction Online Database (VAROD) (1965-2013) were used to explore the feasibility of using spontaneous reporting data, exploring the association between gastrointestinal bleeding and the use of OTC NSAIDs. Safety signals were examined using disproportionality analyses and reporting odds ratios calculated. After adjusting for age, gender, medications known to increase the risk of bleeding, and medications used for the management of conditions associated with an increased risk of bleeding, a two-fold increase in the risk of gastrointestinal (GI) bleeding with OTC NSAID was observed within each dataset. This study demonstrates that spontaneous ADR reporting data can be used in pharmacovigilance to monitor the safety of OTC medicines

On the Computational Complexity of MapReduce

In this paper we study MapReduce computations from a complexity-theoretic perspective. First, we formulate a uniform version of the MRC model of Karloff et al. (2010). We then show that the class of regular languages, and moreover all of sublogarithmic space, lies in constant round MRC. This result also applies to the MPC model of Andoni et al. (2014). In addition, we prove that, conditioned on a variant of the Exponential Time Hypothesis, there are strict hierarchies within MRC so that increasing the number of rounds or the amount of time per processor increases the power of MRC. To the best of our knowledge we are the first to approach the MapReduce model with complexity-theoretic techniques, and our work lays the foundation for further analysis relating MapReduce to established complexity classes

Innovative development of the inspired sinewave device to measure lung functions and inhomogeneity for diagnosis and evaluations of early lung diseases

Surprisingly, lung disease is still one of the leading causes of deaths in the developed countries, including UK. According to the UK National Health Service (NHS), Chronic Obstructive Pulmonary Disease (COPD) is the fifth biggest killer disease in the UK, killing approximately 25,000 people a year. This prob-lem is even worse in developing countries such as Vietnam, India and China, where air pollution is a big problem and the disease awareness is under-recognised. The NHS has set out one of its challenges is to identify people with lung disease earlier in the disease’s development pathway, in order to pro-vide more effective and timely intervention and treatment. This paper presents a novel Inspired Sinewave Device (ISD) to measure lung function and inhomogeneity. Both set of infor-mation are important for diagnosis and detection of early lung diseases. ISD has the potential to replace or supplement the traditional spirometry in the routine lung function testing. The paper describes both the principle of ISD and a set of experi-mental results demonstrating the capability of ISD to asymp-totically detect asthmatic symptoms. Finally the paper discuss-es the future plan, including the testing of 300+ COPD patients at the Oxford Respiratory Trials Unit in UK, and the potential collaborations among research institutions in Vietnam and UK about cost-effective and innovative developments of smart devices, biosensors, lab-on-chips and telehealth solutions for the routine lung function testing, diagnosis and evaluations of early lung diseases

How weeds emerge: a taxonomic and trait‐based examination using United States data

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106812/1/nph12698.pd

Using the Traditional Ex Vivo Whole Blood Model to Discriminate Bacteria by Their Inducible Host Responses

\ua9 2024 by the authors.Whole blood models are rapid and versatile for determining immune responses to inflammatory and infectious stimuli, but they have not been used for bacterial discrimination. Staphylococcus aureus, S. epidermidis and Escherichia coli are the most common causes of invasive disease, and rapid testing strategies utilising host responses remain elusive. Currently, immune responses can only discriminate between bacterial ‘domains’ (fungi, bacteria and viruses), and very few studies can use immune responses to discriminate bacteria at the species and strain level. Here, whole blood was used to investigate the relationship between host responses and bacterial strains. Results confirmed unique temporal profiles for the 10 parameters studied: IL-6, MIP-1α, MIP-3α, IL-10, resistin, phagocytosis, S100A8, S100A8/A9, C5a and TF3. Pairwise analysis confirmed that IL-6, resistin, phagocytosis, C5a and S100A8/A9 could be used in a discrimination scheme to identify to the strain level. Linear discriminant analysis (LDA) confirmed that (i) IL-6, MIP-3α and TF3 could predict genera with 95% accuracy; (ii) IL-6, phagocytosis, resistin and TF3 could predict species at 90% accuracy and (iii) phagocytosis, S100A8 and IL-10 predicted strain at 40% accuracy. These data are important because they confirm the proof of concept that host biomarker panels could be used to identify bacterial pathogens

African penguins as predators and prey — coping (or not) with change

African penguins Spheniscus demersus live in the Benguela and western Agulhas ecosystems off southern Africa. Their numbers decreased throughout the 20th century from at least 1.5 million to about 0.18 million adults, although different regional trends were apparent. They feed to a large extent on shoaling epipelagic fish, notably anchovy Engraulis capensis and sardine Sardinops sagax, and regional trends in the abundance of penguins are associated with trends in the abundance and distribution of these prey fish. Many first-time breeders emigrate from colonies where feeding or other conditions at the time are unfavourable to more favourable breeding localities. This has led to both the extinction and formation of colonies. Food now may limit colonies at relatively small sizes, a fact attributable to industrial fisheries reducing the densities of forage fish. African penguins share their habitat with several other predators, with which they compete for food and breeding space. One of these, the Cape fur seal Arctocephalus p. pusillus, increased through the 20th century to 1.5–2 million animals at its close. Reported observations of predation by fur seals on seabirds have increased in recent decades and threaten the continued existence of small colonies of penguins. Stochastic modelling suggests that colonies of 10 000 pairs have a 9% probability of extinction in 100 years, so smaller populations should be regarded as “Vulnerable”. However, in a period of prolonged food scarcity off southern Namibia, the regional population decreased from more than 40 000 pairs in 1956 to about 1 000 pairs in 2000, and many colonies numbering less than 1 000 pairs became extinct. The minimum viable population for African penguins is currently considered to be >40 000 pairs, likely of the order of 50 000 pairs, a figure equivalent to its level in 2000. The chance of survival of the species through the 21st century is tenuous.African Journal of Marine Science 2001, 23: 435–44

Testing for hybridisation of the Critically Endangered Iguana delicatissima on Anguilla to inform conservation efforts

The Caribbean Island of Anguilla in the north-eastern Lesser Antilles is home to one of the last populations of the Critically Endangered Lesser Antillean iguana Iguana delicatissima. This population is highly threatened primarily because of hybridisation with non-native Iguana iguana. This study assesses the degree of hybridisation between Anguilla’s Iguana species firstly using morphological characteristics and then genetic analysis to validate the genetic integrity of morphologically identified I. delicatissima. We also examined the genetic diversity of Anguilla’s I. delicatissima population, and that of a population on the nearby island of Îlet Fourchue, St Barthélemy. Forty-five iguanas were captured in Anguilla and 10 in St Barthélemy, and sequences from 3 nuclear and 1 mtDNA genes were obtained for each. Of the 45 iguanas captured in Anguilla, 22 were morphologically identified as I. delicatissima, 12 as I. iguana and the remainder were identified as hybrids. Morphological assignments were all confirmed by genetic analyses except for one I. iguana and one hybrid individual. These two individuals appeared likely to have originated following ancestral hybridisation events several generations ago. A significant paucity of genetic diversity was found within Anguillan and St Barthélemy I. delicatissima populations, with a single haplotype being identified for each of the three nuclear genes and the mtDNA sequence. This study highlights the urgency for immediate action to conserve Anguilla’s remnant I. delicatissima population. Protection from hybridisation will require translocation to I. iguana-free offshore cays, with supplementary individuals being sourced from neighbouring islands to enhance the genetic diversity of the population

Comparison of hospital charge prediction models for gastric cancer patients: neural network vs. decision tree models

<p>Abstract</p> <p>Background</p> <p>In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients.</p> <p>Methods</p> <p>Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes.</p> <p>Results</p> <p>After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model.</p> <p>Conclusion</p> <p>ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.</p