Effectiveness of a programme of exercise on physical function in survivors of critical illness following discharge from the ICU: study protocol for a randomised controlled trial (REVIVE)

Background: Following discharge home from the ICU, patients often suffer from reduced physical function, exercise capacity, health-related quality of life and social functioning. There is usually no support to address these longer term problems, and there has been limited research carried out into interventions which could improve patient outcomes. The aim of this study is to investigate the effectiveness and cost-effectiveness of a 6-week programme of exercise on physical function in patients discharged from hospital following critical illness compared to standard care.

Methods/Design: The study design is a multicentre prospective phase II, allocation-concealed, assessor-blinded, randomised controlled clinical trial. Participants randomised to the intervention group will complete three exercise sessions per week (two sessions of supervised exercise and one unsupervised session) for 6 weeks. Supervised sessions will take place in a hospital gymnasium or, if this is not possible, in the participants home and the unsupervised session will take place at home. Blinded outcome assessment will be conducted at baseline after hospital discharge, following the exercise intervention, and at 6 months following baseline assessment (or equivalent time points for the standard care group). The primary outcome measure is physical function as measured by the physical functioning subscale of the Short-Form-36 health survey following the exercise programme. Secondary outcomes are health-related quality of life, exercise capacity, anxiety and depression, self efficacy to exercise and healthcare resource use. In addition, semi-structured interviews will be conducted to explore participants’ perceptions of the exercise programme, and the feasibility (safety, practicality and acceptability) of providing the exercise programme will be assessed. A within-trial cost-utility analysis to assess the cost-effectiveness of the intervention compared to standard care will also be conducted.

Discussion: If the exercise programme is found to be effective, this study will improve outcomes that are meaningful to patients and their families. It will inform the design of a future multicentre phase III clinical trial of exercise following recovery from critical illness. It will provide useful information which will help the development of services for patients after critical illness.

Day case stapled haemorrhoidopexy for prolapsing haemorrhoids

Objective Conventional surgical management of prolapsing haemorrhoids is by excisional haemorrhoidectomy. Postoperative pain has restricted the application of such procedures in the day case setting. These operations remain associated with a period of restricted activity. The use of circular stapling devices as an alternative to the excisional approach in the management of haemorrhoids has been described. This study reports our experience of stapled haemorrhoidopexy as a day case procedure.

Methods Patients with third or fourth degree haemorrhoids were eligible for the procedure. Patients were considered suitable candidates for day case surgery based on conventional parameters. Symptoms were assessed using a previously validated symptom severity rating score. Stapled haemorrhoiclopexy was carried out using a circular stapling device. Pain scores were obtained prior to discharge. Patients were admitted if pain was uncontrolled despite oral analgesia. Symptoms were re-scored at six-week follow-up.

Results Over a 70-month period 168 consecutive stapled haemorrhoidopexies were performed or directly supervised by one consultant colorectal surgeon. One hundred and ten (65%) patients were considered appropriate candidates for day case surgery by conventional criteria. Ninety-six (87.3%) patients successfully underwent stapled haemorrhoidopexyon a day case basis. Fourteen (12.7%) patients required admission on the day of surgery (5 for early Postoperative bleeding, 4 for pain necessitating continuing opiate analgesia, two for urinary retention and three for surgery performed late in the day). Six (5%) patients were re-admitted postoperatively; four for pain relief and two because of urinary retention. Of the day case patients, 91 (82.7%) and 56 (50.9%) had been seen for 6 week and 6 month review, respectively, at the time of analysis. Symptom scores were 6 (pre-operatively) vs 0 (postoperatively) (P <0.01). 76/91 (83.5%) patients reviewed at 6/52 were asymptomatic.

Conclusion Stapled haemorrhoidopexy is a safe and effective procedure that can be carried out on selected patients on a day case basis. Complications are of a similar nature to excisional haemorrhoidectomy.

Étude des impacts écologiques du dynamisme spatio-temporel des habitats naturels sur la faune menacée du Complexe Zones Humides Mahavavy-Kinkony, Madagascar.

This study of the Mahavavy-Kinkony Wetland Complex (MKWC) assesses the impacts of habitat change on the resident globally threatened fauna. Located in Boeny Region, northwest Madagascar, the Complex encompasses a range of habitats including freshwater lakes, rivers, marshes, mangrove forests, and deciduous forest. Spatial modelling and analysis tools were used to (i) identify the important habitats for selected, threatened fauna, (ii) assess their change from 1950 to 2005, (iii) detect the causes of change, (iv) simulate changes to 2050 and (v) evaluate the impacts of change. The approach for prioritising potential habitats for threatened species used ecological science techniques assisted by the decision support software Marxan. Nineteen species were analysed: nine birds, three primates, three fish, three bats and one reptile. Based on knowledge of local land use, supervised classification of Landsat images from 2005 was used to classify the land use of the Complex. Simulations of land use change to 2050 were carried out based on the Land Change Modeler module in Idrisi Andes with the neural network algorithm. Changes in land use at site level have occurred over time but they are not significant. However, reductions in the extent of reed marshes at Lake Kinkony and forests at Tsiombikibo and Marofandroboka directly threaten the species that depend on these habitats. Long term change monitoring is recommended for the Mahavavy Delta, in order to evaluate the predictions through time. The future change of Andohaomby forest is of great concern and conservation actions are recommended as a high priority. Abnormal physicochemical properties were detected in lake Kinkony due to erosion of the four watersheds to the south, therefore an anti-erosion management plan is required for these watersheds. Among the species of global conservation concern, Sakalava rail (Amaurornis olivieri), Crowned sifaka (Propithecus coronatus) and dambabe (Paretroplus dambabe) are estimated the most affected, but at the site level Decken’s sifaka (Propithecus deckeni), kotsovato (Paretroplus kieneri) and Madagascan big-headed turtle (Erymnochelys madagascariensis) are also threatened. Local enforcement of national legislation on hunting means that MKWC is among the sites where the flying fox (Pteropus rufus) and Madagascan rousette (Rousettus madagascariensis) are well protected. Ecological restoration, ecological research and actions to reduce anthropogenic pressures are recommended.

Root Cause Analysis by a Combined Sparse Classification and Monte Carlo Approach

Classification methods with embedded feature selection capability are very appealing for the analysis of complex processes since they allow the analysis of root causes even when the number of input variables is high. In this work, we investigate the performance of three techniques for classification within a Monte Carlo strategy with the aim of root cause analysis. We consider the naive bayes classifier and the logistic regression model with two different implementations for controlling model complexity, namely, a LASSO-like implementation with a L1 norm regularization and a fully Bayesian implementation of the logistic model, the so called relevance vector machine. Several challenges can arise when estimating such models mainly linked to the characteristics of the data: a large number of input variables, high correlation among subsets of variables, the situation where the number of variables is higher than the number of available data points and the case of unbalanced datasets. Using an ecological and a semiconductor manufacturing dataset, we show advantages and drawbacks of each method, highlighting the superior performance in term of classification accuracy for the relevance vector machine with respect to the other classifiers. Moreover, we show how the combination of the proposed techniques and the Monte Carlo approach can be used to get more robust insights into the problem under analysis when faced with challenging modelling conditions.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.

Career choices on graduation--a study of recent graduates from University College Cork

INTRODUCTION: Irish dental graduates are eligible to enter general dental practice immediately after qualification. Unlike their United Kingdom counterparts, there is no requirement to undertake vocational training (VT) or any pre-registration training. VT is a mandatory 12-month period for all UK dental graduates who wish to work within the National Health Service. It provides structured, supervised experience in training practices and through organised study days.

AIMS: This study aimed to profile the career choices made by recent dental graduates from UCC. It aimed to record the uptake of VT and associate posts, and where the graduates gained employment.

METHODOLOGY: A self-completion questionnaire was developed and circulated electronically to recent graduates from UCC. An existing database of email addresses was used and responses were returned by post or by email. A copy of the questionnaire used is included as Appendix 1.

RESULTS: Questionnaires were distributed over an eight-week period and 142 were returned, giving a response rate of 68.90%. Responses were gathered from those who graduated between 2001 and 2007; however, the majority came from more recent classes. Overall, the majority of graduates took up associate positions after qualification (71.8%) with smaller numbers undertaking VT (28.2%). Increasing numbers have entered VT in recent years, including 54.3% from the class of 2007. Overall, the majority of graduates initially took up positions in England (43%); however, in recent times more have been employed in Scotland. Subsequent work profiles of the graduates illustrate that the majority are now working as associates in general practice (51.4%) and in Ireland (54.2%).

CONCLUSIONS: There has been an increase in the proportion of UCC graduates undertaking VT. Graduates tended to move away from Ireland initially to gain employment. There has been a shift away from employment in England towards Scotland where the majority of new UCC graduates are now initially employed. The majority of graduates returned to Ireland for employment after the initial move away.

Decision Making by Credal Nets

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. This feature makes the model particularly suited for the implementation of classifiers and knowledge-based systems. When working with sets of (instead of single) probability distributions, the identification of the optimal option can be based on different criteria, some of them eventually leading to multiple choices. Yet, most of the inference algorithms for credal nets are designed to compute only the bounds of the posterior probabilities. This prevents some of the existing criteria from being used. To overcome this limitation, we present two simple transformations for credal nets which make it possible to compute decisions based on the maximality and E-admissibility criteria without any modification in the inference algorithms. We also prove that these decision problems have the same complexity of standard inference, being NP^PP-hard for general credal nets and NP-hard for polytrees.

Sarcasm Detection on Czech and English Twitter

This paper presents a machine learning approach to sarcasm detection on Twitter in two languages – English and Czech. Although there has been some research in sarcasm detection in languages other than English (e.g., Dutch, Italian, and Brazilian Portuguese), our work is the first attempt at sarcasm detection in the Czech language. We created a large Czech Twitter corpus consisting of 7,000 manually-labeled tweets and provide it to the community. We evaluate two classifiers with various combinations of features on both the Czech and English datasets. Furthermore, we tackle the issues of rich Czech morphology by examining different preprocessing techniques. Experiments show that our language-independent approach significantly outperforms adapted state-of-the-art methods in English (F-measure 0.947) and also represents a strong baseline for further research in Czech (F-measure 0.582).

Retinopathy in type 1 diabetes mellitus: Major differences between rural and urban dwellers in northwest Ethiopia

Aim: To audit levels of diabetes-related eye disease in Type 1 diabetes mellitus (T1DM) patients in northwest Ethiopia. In particular to establish whether, despite identical clinical goals, major differences between the physically demanding life-style of rural subsistence farmers and the sedentary life-style of urban dwellers would influence the prevalence of diabetes-related eye complications. 

Methods: A robust infrastructure for chronic disease management that comprehensively includes all rural dwellers was a pre-requisite for the investigation. A total of 544 T1DM were examined, representing 80% of all T1DM patients under regular review at both the urban and rural clinics and representative of patient age and gender (62.1% male, 37.9% female) of T1DM patients from this region; all were supervised by the same clinical team. Eye examinations were performed for visual acuity, cataract and retinal changes (retinal photography). HbA1c levels and the presence or absence of hypertension were recorded. 

Results/conclusions: Urban and rural groups had similar prevalences of severe visual impairment/blindness (7.0% urban, 5.2% rural) and cataract (7.3% urban, 7.1% rural). By contrast, urban dwellers had a significantly higher prevalence of retinopathy compared to rural patients, 16.1% and 5.0%, respectively (OR 2.9, p <. 0.02, after adjustment for duration, age, gender and hypertension). There was a 3-fold greater prevalence of hypertension in urban patients, whereas HbA1c levels were similar in the two groups. Since diabetic retinopathy is closely associated with microvascular disease and endothelial dysfunction, the possible influences of hypertension to increase and of sustained physical activity to reduce endothelial dysfunction are discussed.

Graduate Attitudes towards Vocational Training

Introduction: Vocational training (VT) is a mandatory requirement for all UK dental graduates prior to entering NHS practice. The VT period provides structured, supervised experience supported by study days and interaction with peers. It is not compulsory for Irish dental graduates working in either Ireland or the UK to undertake VT but yet a proportion voluntarily do so each year.

Objectives: This study was designed to explore the choices made by Irish dental graduates. It aimed to record any benefits of VT and its impact upon future career choices.

Method: A self-completion questionnaire was developed and piloted before being circulated electronically to recent dental graduates from University College Cork. After collecting demographic information respondents were asked to indicate if they pursued vocational training on graduation, give their perception of their post-graduation experience, describe their current work profile and detail any formal postgraduate studies.

Results: 35% of respondents opted to undertake VT and 79% did so in the UK. Those who completed VT regarded it as a very positive experience with benefits including: working in a positive learning environment, help on demand and interaction with peers. Of those who chose VT, 49% have pursued some form of further formal postgraduate study as compared to 40% of those who did not. All of the respondents who completed VT indicated they would recommend it to current Irish graduates. The majority of those who took up an associate position immediately after graduation reported that this was beneficial but up to three quarters would recommend current graduates undertake VT and 45% would now chose to do so themselves.

Conclusions: Increasing numbers of Irish graduates are moving to the UK to undertake VT and they find it a beneficial experience. In addition, those who undertook VT were more likely to undertake formal postgraduate study.

Combining vitamin C and carotenoid biomarkers better predicts fruit and vegetable intake than individual biomarkers in dietary intervention studies

PURPOSE: The aim of this study was to determine whether combining potential biomarkers of fruit and vegetables is better at predicting FV intake within FV intervention studies than single biomarkers.

DESIGN: Data from a tightly controlled randomised FV intervention study (BIOFAV; all food provided and two meals/day on weekdays consumed under supervision) were used. A total of 30 participants were randomised to either 2, 5 or 8 portions FV/day for 4 weeks, and blood samples were collected at baseline and 4 weeks for plasma vitamin C and serum carotenoid analysis. The combined biomarker approach was also tested in three further FV intervention studies conducted by the same research team, with less strict dietary control (FV provided and no supervised meals).

RESULTS: The combined model containing all carotenoids and vitamin C was a better fit than either the vitamin C only (P < 0.001) model or the lutein only (P = 0.006) model in the BIOFAV study. The C-statistic was slightly lower in the lutein only model (0.85) and in the model based upon factor analysis (0.88), and much lower in the vitamin C model (0.68) compared with the full model (0.95). Results for the other studies were similar, although the differences between the models were less marked.

CONCLUSIONS: Although there was some variation between studies, which may relate to the level of dietary control or participant characteristics, a combined biomarker approach to assess overall FV consumption may more accurately predict FV intake within intervention studies than the use of a single biomarker. The generalisability of these findings to other populations and study designs remains to be tested. 

A survey of perceived training differences between ophthalmology residents in Hong Kong and China.

Background: To study the differences in ophthalmology resident training between China and the Hong Kong Special Administrative Region (HKSAR).Methods: Training programs were selected from among the largest and best-known teaching hospitals. Ophthalmology residents were sent an anonymous 48-item questionnaire by mail. Work satisfaction, time allocation between training activities and volume of surgery performed were determined.Results: 50/75 residents (66.7 %) from China and 20/26 (76.9 %) from HKSAR completed the survey. Age (28.9 ± 2.5 vs. 30.2 ± 2.9 years, p = 0.15) and number of years in training (3.4 ± 1.6 vs. 2.8 ± 1.5, p = 0.19) were comparable between groups. The number of cataract procedures performed by HKSAR trainees (extra-capsular, median 80.0, quartile range: 30.0, 100.0; phacoemulsification, median: 20.0, quartile range: 0.0, 100.0) exceeded that for Chinese residents (extra-capsular: median = 0, p < 0.0001; phacoemulsification: median = 0, p < 0.0001). Chinese trainees spent more time completing medical charts (>50 % of time on charts: 62.5 % versus 5.3 %, p < 0.0001) and received less supervision (≥90 % of training supervised: 4.4 % versus 65 %, p < 0.0001). Chinese residents were more likely to feel underpaid (96.0 % vs. 31.6 %, p < 0.0001) and hoped their children would not practice medicine (69.4 % vs. 5.0 %, p = 0.0001) compared HKSAR residents.Conclusions: In this study, ophthalmology residents in China report strikingly less surgical experience and supervision, and lower satisfaction than HKSAR residents. The HKSAR model of hands-on resident training might be useful in improving the low cataract surgical rate in China.

Supervisor Continuity or Co-Location: Which Matters in Residency Education? Findings From a Qualitative Study of Remote Supervisor Family Physicians in Australia and Canada

Purpose: Changes to health care systems andworking hours have fragmentedresidents’ clinical experiences withpotentially negative effects ontheir development as professionals.Investigation of off-site supervision,which has been implemented in isolatedrural practice, could reveal importantbut less overt components of residencyeducation. 

Method: Insights from sociocultural learningtheory and work-based learning provideda theoretical framework. In 2011–2012,16 family physicians in Australia andCanada were asked in-depth how theyremotely supervised residents’ workand learning, and for their reflectionson this experience. The verbatiminterview transcripts and researchers’memos formed the data set. Templateanalysis produced a description andinterpretation of remote supervision. 

Results: Thirteen Australian family physiciansfrom five states and one territory, andthree Canadians from one province,participated. The main themes werehow remoteness changed the dynamicsof care and supervision; the importanceof ongoing, holistic, nonhierarchical,supportive supervisory relationships; andthat residents learned “clinical courage”through responsibility for patients’ careover time. Distance required supervisorsto articulate and pass on their expertiseto residents but made monitoringdifficult. Supervisory continuityencouraged residents to build on pastexperiences and confront deficiencies. 

Conclusions: Remote supervision enabled residents todevelop as clinicians and professionals.This questions the supremacy of co-locationas an organizing principle forresidency education. Future specialists maybenefit from programs that give themongoing and increasing responsibilityfor a group of patients and supportive.

Cascaded multimodal biometric recognition framework

A practically viable multi-biometric recognition system should not only be stable, robust and accurate but should also adhere to real-time processing speed and memory constraints. This study proposes a cascaded classifier-based framework for use in biometric recognition systems. The proposed framework utilises a set of weak classifiers to reduce the enrolled users' dataset to a small list of candidate users. This list is then used by a strong classifier set as the final stage of the cascade to formulate the decision. At each stage, the candidate list is generated by a Mahalanobis distance-based match score quality measure. One of the key features of the authors framework is that each classifier in the ensemble can be designed to use a different modality thus providing the advantages of a truly multimodal biometric recognition system. In addition, it is one of the first truly multimodal cascaded classifier-based approaches for biometric recognition. The performance of the proposed system is evaluated both for single and multimodalities to demonstrate the effectiveness of the approach.

Compositional data-driven alternatives to single geochemical component maps

Conventional practice in Regional Geochemistry includes as a final step of any geochemical campaign the generation of a series of maps, to show the spatial distribution of each of the components considered. Such maps, though necessary, do not comply with the compositional, relative nature of the data, which unfortunately make any conclusion based on them sensitive
to spurious correlation problems. This is one of the reasons why these maps are never interpreted isolated. This contribution aims at gathering a series of statistical methods to produce individual maps of multiplicative combinations of components (logcontrasts), much in the flavor of equilibrium constants, which are designed on purpose to capture certain aspects of the data.
We distinguish between supervised and unsupervised methods, where the first require an external, non-compositional variable (besides the compositional geochemical information) available in an analogous training set. This external variable can be a quantity (soil density, collocated magnetics, collocated ratio of Th/U spectral gamma counts, proportion of clay particle fraction, etc) or a category (rock type, land use type, etc). In the supervised methods, a regression-like model between the external variable and the geochemical composition is derived in the training set, and then this model is mapped on the whole region. This case is illustrated with the Tellus dataset, covering Northern Ireland at a density of 1 soil sample per 2 square km, where we map the presence of blanket peat and the underlying geology. The unsupervised methods considered include principal components and principal balances
(Pawlowsky-Glahn et al., CoDaWork2013), i.e. logcontrasts of the data that are devised to capture very large variability or else be quasi-constant. Using the Tellus dataset again, it is found that geological features are highlighted by the quasi-constant ratios Hf/Nb and their ratio against SiO2; Rb/K2O and Zr/Na2O and the balance between these two groups of two variables; the balance of Al2O3 and TiO2 vs. MgO; or the balance of Cr, Ni and Co vs. V and Fe2O3. The largest variability appears to be related to the presence/absence of peat.