Bayesian predictors of very poor health related quality of life and mortality in patients with COPD

Background: Chronic obstructive pulmonary disease (COPD) is associated with increased mortality and poor health-related quality of life (HRQoL) compared with the general population. The objective of this study was to identify clinical characteristics which predict mortality and very poor HRQoL among the COPD population and to develop a Bayesian prediction model. Methods: The data consisted of 738 patients with COPD who had visited the Pulmonary Clinic of the Helsinki and Turku University Hospitals during 1995-2006. The data set contained 49 potential predictor variables and two outcome variables: survival (dead/alive) and HRQoL measured with a 15D instrument (very poor HRQoL = 0.70). In the first phase of model validation we randomly divided the material into a training set (n = 538), and a test set (n = 200). This procedure was repeated ten times in random fashion to obtain independently created training sets and corresponding test sets. Modeling was performed by using the training set, and each model was tested by using the corresponding test set, repeated in each training set. In the second phase the final model was created by using the total material and eighteen most predictive variables. The performance of six logistic regressions approaches were shown for comparison purposes. Results: In the final model, the following variables were associated with mortality or very poor HRQoL: age at onset, cerebrovascular disease, diabetes, alcohol abuse, cancer, psychiatric disease, body mass index, Forced Expiratory Volume (FEV1) % of predicted, atrial fibrillation, and prolonged QT time in ECG. The prediction accuracy of the model was 77%, sensitivity 0.30, specificity 0.95, positive predictive value 0.68, negative predictive value 0.78, and area under the ROC curve 0.69. While the sensitivity of the model reminded limited, good specificity, moderate accuracy, comparable or better performance in classification and better performance in variable selection and data usage in comparison to the logistic regression approaches, and positive and negative predictive values indicate that the model has potential in predicting mortality and very poor HRQoL in COPD patients. Conclusion: We developed a Bayesian prediction model which is potentially useful in predicting mortality and very poor HRQoL in patients with COPD.Peer reviewe

Plate versus bulk trolley food service in a hospital: comparison of patients’ satisfaction

Objective The aim of this research was to compare plate with bulk trolley food service in hospitals in terms of patient satisfaction. Key factors distinguishing satisfaction with each system would also be identified. Methods A consumer opinion card (n = 180), concentrating on the quality indicators of core foods, was used to measure patient satisfaction and compare two systems of delivery, plate and trolley. Binary logistic regression analysis was used to build a model that would predict food service style on the basis of the food attributes measured. Further investigation used multinomial logistic regression to predict opinion for the assessment of each food attribute within food service style. Results Results showed that the bulk trolley method of food distribution enables all foods to have a more acceptable texture, and for some foods (potato, P = 0.007; poached fish, P = 0.001; and minced beef, P ≤ 0.0005) temperature, and for other foods (broccoli, P ≤ 0.0005; carrots, P ≤ 0.0005; and poached fish, P = 0.001) flavor, than the plate system of delivery, where flavor is associated with bad opinion or dissatisfaction. A model was built indicating patient satisfaction with the two service systems. Conclusion This research confirms that patient satisfaction is enhanced by choice at the point of consumption (trolley system); however, portion size was not the controlling dimension. Temperature and texture were the most important attributes that measure patient satisfaction with food, thus defining the focus for hospital food service managers. To date, a model predicting patient satisfaction with the quality of food as served has not been proposed, and as such this work adds to the body of knowledge in this field. This report brings new information about the service style of dishes for improving the quality of food and thus enhancing patient satisfaction

Coincidental detection of the first outbreak of carbapenemase-producing Klebsiella pneumoniae colonisation in a primary care hospital, Finland, 2013

In Finland, occurrence of Klebsiella pneumoniae carbapenemase-producing K. pneumoniae (KPC-KP) has previously been sporadic and related to travel. We describe the first outbreak of colonisation with KPC-KP strain ST512; it affected nine patients in a 137-bed primary care hospital. The index case was detected by chance when a non-prescribed urine culture was taken from an asymptomatic patient with suprapubic urinary catheter in June 2013. Thereafter, all patients on the 38-bed ward were screened until two screening rounds were negative and extensive control measures were performed. Eight additional KPC-KP-carriers were found, and the highest prevalence of carriers on the ward was nine of 38. All other patients hospitalised on the outbreak ward between 1 May and 10 June and 101 former roommates of KPC-KP carriers since January had negative screening results. Two screening rounds on the hospital's other wards were negative. No link to travel abroad was detected. Compared with non-carriers, but without statistical significance, KPC-KP carriers were older (83 vs 76 years) and had more often received antimicrobial treatment within the three months before screening (9/9 vs 90/133). No clinical infections occurred during the six-month follow-up. Early detection, prompt control measures and repetitive screening were crucial in controlling the outbreak.Peer reviewe

Identifying factors likely to influence compliance with diagnostic imaging guideline recommendations for spine disorders among chiropractors in North America: a focus group study using the Theoretical Domains Framework

Background: The Theoretical Domains Framework (TDF) was developed to investigate determinants of specific clinical behaviors and inform the design of interventions to change professional behavior. This framework was used to explore the beliefs of chiropractors in an American Provider Network and two Canadian provinces about their adherence to evidence-based recommendations for spine radiography for uncomplicated back pain. The primary objective of the study was to identify chiropractors’ beliefs about managing uncomplicated back pain without xrays and to explore barriers and facilitators to implementing evidence-based recommendations on lumbar spine xrays. A secondary objective was to compare chiropractors in the United States and Canada on their beliefs regarding the use of spine x-rays. Methods: Six focus groups exploring beliefs about managing back pain without x-rays were conducted with a purposive sample. The interview guide was based upon the TDF. Focus groups were digitally recorded, transcribed verbatim, and analyzed by two independent assessors using thematic content analysis based on the TDF. Results: Five domains were identified as likely relevant. Key beliefs within these domains included the following: conflicting comments about the potential consequences of not ordering x-rays (risk of missing a pathology, avoiding adverse treatment effects, risks of litigation, determining the treatment plan, and using x-ray-driven techniques contrasted with perceived benefits of minimizing patient radiation exposure and reducing costs; beliefs about consequences); beliefs regarding professional autonomy, professional credibility, lack of standardization, and agreement with guidelines widely varied (social/professional role & identity); the influence of formal training, colleagues, and patients also appeared to be important factors (social influences); conflicting comments regarding levels of confidence and comfort in managing patients without x-rays (belief about capabilities); and guideline awareness and agreements (knowledge). Conclusions: Chiropractors’ use of diagnostic imaging appears to be influenced by a number of factors. Five key domains may be important considering the presence of conflicting beliefs, evidence of strong beliefs likely to impact the behavior of interest, and high frequency of beliefs. The results will inform the development of a theorybased survey to help identify potential targets for behavioral-change strategies

Fall Classification by Machine Learning Using Mobile Phones

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls–left and right lateral, forward trips, and backward slips–while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls

Multifactorial day hospital intervention to reduce falls in high risk older people in primary care: a multi-centre randomised controlled trial [ISRCTN46584556]

Falls in older people are a major public health concern in terms of morbidity, mortality and cost. Previous studies suggest that multifactorial interventions can reduce falls, and many geriatric day hospitals are now offering falls intervention programmes. However, no studies have investigated whether these programmes, based in the day hospital are effective, nor whether they can be successfully applied to high-risk older people screened in primary care. The hypothesis is that a multidisciplinary falls assessment and intervention at Day hospitals can reduce the incidence of falls in older people identified within primary care as being at high risk of falling. This will be tested by a pragmatic parallel-group randomised controlled trial in which the participants, identified as at high risk of falling, will be randomised into either the intervention Day hospital arm or to a control (current practice) arm. Those participants preferring not to enter the full randomised study will be offered the opportunity to complete brief diaries only at monthly intervals. This data will be used to validate the screening questionnaire. Three day hospitals (2 Nottingham, 1 Derby) will provide the interventions, and the University of Nottingham's Departments of Primary Care, the Division of Rehabilitation and Ageing Unit, and the Trent Institute for Health Service Research will provide the methodological and statistical expertise. Four hundred subjects will be randomised into the two arms. The primary outcome measure will be the rate of falls over one year. Secondary outcome measures will include the proportion of people experiencing at least one fall, the proportion of people experiencing recurrent falls (>1), injuries, fear of falling, quality of life, institutionalisation rates, and use of health services. Cost-effectiveness analyses will be performed to inform health commissioners about resource allocation issues. The importance of this trial is that the results may be applicable to any UK day hospital setting. SITES: General practices across Nottinghamshire and Derbyshire. Day hospitals: Derbyshire Royal Infirmary (Southern Derbyshire Acute Hospitals NHS Trust) Sherwood Day Service (Nottingham City Hospital Trust) Leengate Day Hospital (Queen's Medical Centre Nottingham University Hospital NHS Trust

Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library

<p>Abstract</p> <p>Background</p> <p>To enhance capabilities for genomic analyses in rainbow trout, such as genomic selection, a large suite of polymorphic markers that are amenable to high-throughput genotyping protocols must be identified. Expressed Sequence Tags (ESTs) have been used for single nucleotide polymorphism (SNP) discovery in salmonids. In those strategies, the salmonid semi-tetraploid genomes often led to assemblies of paralogous sequences and therefore resulted in a high rate of false positive SNP identification. Sequencing genomic DNA using primers identified from ESTs proved to be an effective but time consuming methodology of SNP identification in rainbow trout, therefore not suitable for high throughput SNP discovery. In this study, we employed a high-throughput strategy that used pyrosequencing technology to generate data from a reduced representation library constructed with genomic DNA pooled from 96 unrelated rainbow trout that represent the National Center for Cool and Cold Water Aquaculture (NCCCWA) broodstock population.</p> <p>Results</p> <p>The reduced representation library consisted of 440 bp fragments resulting from complete digestion with the restriction enzyme <it>Hae</it>III; sequencing produced 2,000,000 reads providing an average 6 fold coverage of the estimated 150,000 unique genomic restriction fragments (300,000 fragment ends). Three independent data analyses identified 22,022 to 47,128 putative SNPs on 13,140 to 24,627 independent contigs. A set of 384 putative SNPs, randomly selected from the sets produced by the three analyses were genotyped on individual fish to determine the validation rate of putative SNPs among analyses, distinguish apparent SNPs that actually represent paralogous loci in the tetraploid genome, examine Mendelian segregation, and place the validated SNPs on the rainbow trout linkage map. Approximately 48% (183) of the putative SNPs were validated; 167 markers were successfully incorporated into the rainbow trout linkage map. In addition, 2% of the sequences from the validated markers were associated with rainbow trout transcripts.</p> <p>Conclusion</p> <p>The use of reduced representation libraries and pyrosequencing technology proved to be an effective strategy for the discovery of a high number of putative SNPs in rainbow trout; however, modifications to the technique to decrease the false discovery rate resulting from the evolutionary recent genome duplication would be desirable.</p

RNA-Seq Identifies SNP Markers for Growth Traits in Rainbow Trout

Fast growth is an important and highly desired trait, which affects the profitability of food animal production, with feed costs accounting for the largest proportion of production costs. Traditional phenotype-based selection is typically used to select for growth traits; however, genetic improvement is slow over generations. Single nucleotide polymorphisms (SNPs) explain 90% of the genetic differences between individuals; therefore, they are most suitable for genetic evaluation and strategies that employ molecular genetics for selective breeding. SNPs found within or near a coding sequence are of particular interest because they are more likely to alter the biological function of a protein. We aimed to use SNPs to identify markers and genes associated with genetic variation in growth. RNA-Seq whole-transcriptome analysis of pooled cDNA samples from a population of rainbow trout selected for improved growth versus unselected genetic cohorts (10 fish from 1 full-sib family each) identified SNP markers associated with growth-rate. The allelic imbalances (the ratio between the allele frequencies of the fast growing sample and that of the slow growing sample) were considered at scores >5.0 as an amplification and <0.2 as loss of heterozygosity. A subset of SNPs (n = 54) were validated and evaluated for association with growth traits in 778 individuals of a three-generation parent/offspring panel representing 40 families. Twenty-two SNP markers and one mitochondrial haplotype were significantly associated with growth traits. Polymorphism of 48 of the markers was confirmed in other commercially important aquaculture stocks. Many markers were clustered into genes of metabolic energy production pathways and are suitable candidates for genetic selection. The study demonstrates that RNA-Seq at low sequence coverage of divergent populations is a fast and effective means of identifying SNPs, with allelic imbalances between phenotypes. This technique is suitable for marker development in non-model species lacking complete and well-annotated genome reference sequences