Eosinophilic oesophagitis: relationship of quality of life with clinical, endoscopic and histological activity.

BACKGROUND Knowledge about determinants of quality of life (QoL) in eosinophilic oesophagitis (EoO) patients helps to identify patients at risk of experiencing poor QoL and to tailor therapeutic interventions accordingly. AIM To evaluate the impact of symptom severity, endoscopic and histological activity on EoE-specific QoL in adult EoE patients. METHODS Ninety-eight adult EoE patients were prospectively included (64% male, median age 39 years). Patients completed two validated instruments to assess EoE-specific QoL (EoO-QoL-A) and symptom severity (adult EoE activity index patient-reported outcome) and then underwent esophagogastroduodenoscopy with biopsy sampling. Physicians reported standardised information on EoE-associated endoscopic and histological alterations. The Spearman's rank correlation coefficient was calculated to determine the relationship between QoL and symptom severity. Linear regression and analysis of variance was used to quantify the extent to which variations in severity of EoE symptoms, endoscopic and histological findings explain variations in QoL. RESULTS Quality of life strongly correlated with symptom severity (r = 0.610, P < 0.001). While the variation in severity of symptoms, endoscopic and histological findings alone explained 38%, 35% and 22% of the variability in EoE-related QoL, respectively, these together explained 60% of variation. Symptom severity explained 18-35% of the variation in each of the five QoL subscale scores. CONCLUSIONS Eosinophilic oesophagitis symptom severity and biological disease activity determine QoL in adult patients with eosinophilic oesophagitis. Therefore, reduction in both eosinophilic oesophagitis symptoms as well as biological disease activity is essential for improvement of QoL in adult patients. Clinicaltrials.gov number, NCT00939263.

Perception of a hectic hospital environment at admission relates to acute stress disorder symptoms in myocardial infarction patients.

OBJECTIVE Hospital crowding is a public health problem that may impact on the quality of medical treatment and increase the risk of developing traumatic stress, e.g., after myocardial infarction (MI). This study examines whether subjective appraisal of crowding at hospital admission due to MI is associated with acute stress disorder (ASD) symptoms. METHOD We investigated 102 consecutive patients with acute MI within 48h after having reached stable circulatory conditions. The appraisal of crowding was measured by the retrospective assessment of the perception of a hectic hospital environment at admission. Furthermore, patients completed the Acute Stress Disorder Scale to rate the psychological stress reaction. RESULTS The perception of a hectic hospital environment was associated with the development of ASD symptoms (r=0.254, P=.013) independently of demographic, peritraumatic and medical factors. Post hoc analysis revealed associations with dissociative (r=0.211, P=.041), reexperiencing (r=0.184, P=.074) and arousal (r=0.179, P=.083) symptoms. CONCLUSION The findings suggest that, besides objective circumstances, the way hospital admission due to MI is perceived by the patient may influence the development of MI-triggered ASD symptoms. The psychological and physiological long-term outcomes of the perception of a hectic hospital environment and the role of preventive interventions need further examination.

Automatic quality control in clinical (1) H MRSI of brain cancer.

MRSI grids frequently show spectra with poor quality, mainly because of the high sensitivity of MRS to field inhomogeneities. These poor quality spectra are prone to quantification and/or interpretation errors that can have a significant impact on the clinical use of spectroscopic data. Therefore, quality control of the spectra should always precede their clinical use. When performed manually, quality assessment of MRSI spectra is not only a tedious and time-consuming task, but is also affected by human subjectivity. Consequently, automatic, fast and reliable methods for spectral quality assessment are of utmost interest. In this article, we present a new random forest-based method for automatic quality assessment of (1) H MRSI brain spectra, which uses a new set of MRS signal features. The random forest classifier was trained on spectra from 40 MRSI grids that were classified as acceptable or non-acceptable by two expert spectroscopists. To account for the effects of intra-rater reliability, each spectrum was rated for quality three times by each rater. The automatic method classified these spectra with an area under the curve (AUC) of 0.976. Furthermore, in the subset of spectra containing only the cases that were classified every time in the same way by the spectroscopists, an AUC of 0.998 was obtained. Feature importance for the classification was also evaluated. Frequency domain skewness and kurtosis, as well as time domain signal-to-noise ratios (SNRs) in the ranges 50-75 ms and 75-100 ms, were the most important features. Given that the method is able to assess a whole MRSI grid faster than a spectroscopist (approximately 3 s versus approximately 3 min), and without loss of accuracy (agreement between classifier trained with just one session and any of the other labelling sessions, 89.88%; agreement between any two labelling sessions, 89.03%), the authors suggest its implementation in the clinical routine. The method presented in this article was implemented in jMRUI's SpectrIm plugin. Copyright © 2016 John Wiley & Sons, Ltd.

Age Related Differences in Individual Quality of Life Domains in Youth with Type 1 Diabetes.

BACKGROUND: Investigating individual, as opposed to predetermined, quality of life domains may yield important information about quality of life. This study investigated the individual quality of life domains nominated by youth with type 1 diabetes. METHODS: Eighty young people attending a diabetes summer camp completed the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting interview, which allows respondents to nominate and evaluate their own quality of life domains. RESULTS: The most frequently nominated life domains were 'family', 'friends', 'diabetes', 'school', and 'health' respectively; ranked in terms of importance, domains were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'; ranked in order of satisfaction, domains were 'camp', 'religion', 'pets', and 'family' and 'a special person' were tied for fifth. Respondent age was significantly positively associated with the importance of 'friends', and a significantly negatively associated with the importance of 'family'. Nearly all respondents nominated a quality of life domain relating to physical status, however, the specific physical status domain and the rationale for its nomination varied. Some respondents nominated 'diabetes' as a domain and emphasized diabetes 'self-care behaviors' in order to avoid negative health consequences such as hospitalization. Other respondents nominated 'health' and focused more generally on 'living well with diabetes'. In an ANOVA with physical status domain as the independent variable and age as the dependent variable, participants who nominated 'diabetes' were younger (M = 12.9 years) than those who nominated 'health' (M = 15.9 years). In a second ANOVA, with rationale for nomination the physical status domain as the independent variable, and age as the dependent variable, those who emphasized 'self care behaviors' were younger (M = 11.8 years) than those who emphasized 'living well with diabetes' (M = 14.6 years). These differences are discussed in terms of cognitive development and in relation to the decline in self-care and glycemic control often observed during adolescence. CONCLUSIONS: Respondents nominated many non-diabetes life domains, underscoring that QOL is multidimensional. Subtle changes in conceptualization of diabetes and health with increasing age may reflect cognitive development or disease adjustment, and speak to the need for special attention to adolescents. Understanding individual quality of life domains can help clinicians motivate their young patients with diabetes for self-care. Future research should employ a larger, more diverse sample, and use longitudinal designs.

Development and preliminary validation of the cancer family impact scale for colorectal cancer

This study aimed to develop and validate The Cancer Family Impact Scale (CFIS), an instrument for use in studies investigating relationships among family factors and colorectal cancer (CRC) screening when family history is a risk factor. We used existing data to develop the measure from 1,285 participants (637 families) across the United States who were in the Johns Hopkins Colon Cancer Genetic Testing study. Participants were 94% white with an average age of 50.1 years, and 60% were women. None had a personal CRC history, and eighty percent had 1 FDR with CRC and 20% had more than one FDR with CRC. The study had three aims: (1) to identify the latent factors underlying the CFIS via exploratory factor analysis (EFA); (2) to confirm the findings of the EFA via confirmatory factor analysis (CFA); and (3) to assess the reliability of the scale via Cronbach's alpha. Exploratory analyses were performed on a split half of the sample, and the final model was confirmed on the other half. The EFA suggested the CFIS was an 18-item measure with 5 latent constructs: (1) NEGATIVE: negative effects of cancer on the family; (2) POSITIVE: positive effects of cancer on the family; (3) COMMUNICATE: how families communicate about cancer; (4) FLOW: how information about cancer is conveyed in families; and (5) NORM: how individuals react to family norms about cancer. CFA on the holdout sample showed the CFIS to have a reasonably good fit (Chi-square = 389.977, df = 122, RMSEA= 0.058 (.052-.065), CFI=.902, TLI=.877, GF1=.939). The overall reliability of the scale was α=0.65. The reliability of the subscales was: (1) NEGATIVE α = 0.682; (2) POSITIVE α = 0.686; (3) COMMUNICATE α = 0.723; (4) FLOW α = 0.467; and (5) NORM α = 0.732. ^ We concluded the CFIS to be a good measure with most fit levels over 0.90. The CFIS could be used to compare theoretically driven hypotheses about the pathways through which family factors could influence health behavior among unaffected individuals at risk due to family history, and also aid in the development and evaluation of cancer prevention interventions including a family component. ^

Distribution of quality adjusted life expectancy: A systems approach

Statistical methods are developed which assess survival data for two attributes; (1) prolongation of life, (2) quality of life. Health state transition probabilities correspond to prolongation of life and are modeled as a discrete-time semi-Markov process. Imbedded within the sojourn time of a particular health state are the quality of life transitions. They reflect events which differentiate perceptions of pain and suffering over a fixed time period. Quality of life transition probabilities are derived from the assumptions of a simple Markov process. These probabilities depend on the health state currently occupied and the next health state to which a transition is made. Utilizing the two forms of attributes the model has the capability to estimate the distribution of expected quality adjusted life years (in addition to the distribution of expected survival times). The expected quality of life can also be estimated within the health state sojourn time making more flexible the assessment of utility preferences. The methods are demonstrated on a subset of follow-up data from the Beta Blocker Heart Attack Trial (BHAT). This model contains the structure necessary to make inferences when assessing a general survival problem with a two dimensional outcome. ^

Intensive care unit utilization among patients with cancer at the end of life

Over the last 2 decades, survival rates in critically ill cancer patients have improved. Despite the increase in survival, the intensive care unit (ICU) continues to be a location where end-of-life care takes place. More than 20% of deaths in the United States occur after admission to an ICU, and as baby boomers reach the seventh and eighth decades of their lives, the volume of patients in the ICU is predicted to rise. The aim of this study was to evaluate intensive care unit utilization among patients with cancer who were at the end of life. End of life was defined using decedent and high-risk cohort study designs. The decedent study evaluated characteristics and ICU utilization during the terminal hospital stay among patients who died at The University of Texas MD Anderson Cancer Center during 2003-2007. The high-risk cohort study evaluated characteristics and ICU utilization during the index hospital stay among patients admitted to MD Anderson during 2003-2007 with a high risk of in-hospital mortality. Factors associated with higher ICU utilization in the decedent study included non-local residence, hematologic and non-metastatic solid tumor malignancies, malignancy diagnosed within 2 months, and elective admission to surgical or pediatric services. Having a palliative care consultation on admission was associated with dying in the hospital without ICU services. In the cohort of patients with high risk of in-hospital mortality, patients who went to the ICU were more likely to be younger, male, with newly diagnosed non-metastatic solid tumor or hematologic malignancy, and admitted from the emergency center to one of the surgical services. A palliative care consultation on admission was associated with a decreased likelihood of having an ICU stay. There were no differences in ethnicity, marital status, comorbidities, or insurance status between patients who did and did not utilize ICU services. Inpatient mortality probability models developed for the general population are inadequate in predicting in-hospital mortality for patients with cancer. The following characteristics that differed between the decedent study and high-risk cohort study can be considered in future research to predict risk of in-hospital mortality for patients with cancer: ethnicity, type and stage of malignancy, time since diagnosis, and having advance directives. Identifying those at risk can precipitate discussions in advance to ensure care remains appropriate and in accordance with the wishes of the patient and family.^

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

Social Indicators in the Sustainable Refurbishment: Calculating Quality of Life Indicator in a Residential Building in Málaga

How can we measure ‘quality of life���? The sustainable refurbishment goes beyond strictly energy aspects. Sustainability indicators are needed to facilitate data collection and to provide information which does not require too time-consuming calculations. Thus, you can offer an idea of the extent and quality of the rehabilitation before starting the project and, also, the obtained results can be evaluated in an agile way after the refurbishment. From a list of social indicators gathered from different methods, sustainability assessment tools and International and European standards, three social indicators are proposed: Users Satisfaction, Participation Agreement and Quality of Life. This paper shows the development of Quality of Life social indicator, the more closely related to the main objectives of Researchand Development Project “Sustainable Refurbishment”: improving energy efficiency and wellbeing of users in existing residential buildings. Finally, this social indicator is applied to a real case study in Málaga (Spain).

New QR Survey Methodologies to Analyze User Perception of Service Quality in Public Transport: The Experience of Madrid

Customer Satisfaction Surveys (CSS) have become an important tool for public transport planners, as improvements in the perceived quality of service lead to greater use of public transport and lower traffic pollution. Until now, Intelligent Transportation System (ITS) enhancements in public transport have traditionally included fleet management systems based on Automatic Vehicle Location (AVL) technologies, which can be used to optimize routing and scheduling, and to feed real-time information into passenger information channels. However, surveys of public transport users could also benefit from the new information technologies. As most customers carry their smartphones when traveling, Quick Response (QR) codes open up the possibility of conducting these surveys at a lower cost.This paper contributes to the limited existing literature by developing the analysis of QR codes applied to CSS in public transport and highlighting their importance in reducing the cost of data collection and processing. The added value of this research is that it provides the first assessment of a real case study in Madrid (Spain) using QR codes for this purpose. This pilot experience was part of a research project analyzing bus service quality in the same case study, so the QR code survey (155 valid questionnaires) was validated using a conventional face-to-face survey (520 valid questionnaires). The results show clearly that, after overcoming a few teething troubles, this QR code application will ultimately provide transport management with a useful tool to reduce survey costs

Evaluation of quality of life related to nutritional status

The way in which the quality of life related to health (HRQoL) is affected by the nutritional status of the patient is a subject of constant interest and permanent debate. The purpose of the present paper is to review those studies that relate HRQoL to nutritional status and examine the tools (questionnaires) that they use to investigate this relationship. A critical review of published studies was carried out via an investigation of the following databases: MEDLINE (via PubMed); EMBASE; The Cochrane Library; Cumulative Index to Nursing and Allied Health Literature (CINAHL); Institute for Scientific Information (ISI) Web of Science; Latin American and Caribbean Health Sciences Literature (LILACS); Spanish Health Sciences Bibliographic Index (IBECS). The search was carried out from the earliest date possible until July 2007.The medical subject heading terms used were ‘quality of life���, ‘nutritional status’ and ‘questionnaires’. The articles had to contain at least one questionnaire that evaluated quality of life. Twenty-eight documents fulfilling the inclusion criteria were accepted, although none of them used a specific questionnaire to evaluate HRQoL related to nutritional status. However, some of them used a combination of generic questionnaires with the intention of evaluating the same. Only three studies selectively addressed the relationship between nutritional status and quality of life, this evaluation being performed not by means of specific questionnaires but by statistical analysis of data obtained via validated questionnaires.